diff --git a/.quarto/xref/14aca4aa b/.quarto/xref/14aca4aa
index 953f991..6d79b57 100644
--- a/.quarto/xref/14aca4aa
+++ b/.quarto/xref/14aca4aa
@@ -1 +1 @@
-{"entries":[],"options":{"chapters":true},"headings":["our-objective","user-resources","background-of-the-gap_products-repo","major-advantages"]}
\ No newline at end of file
+{"headings":["our-objective","user-resources","background-of-the-gap_products-repo","major-advantages"],"entries":[],"options":{"chapters":true}}
\ No newline at end of file
diff --git a/GAP-Production-Data-Documentation.tex b/GAP-Production-Data-Documentation.tex
index 84314a2..e910175 100644
--- a/GAP-Production-Data-Documentation.tex
+++ b/GAP-Production-Data-Documentation.tex
@@ -519,7 +519,7 @@
\setcounter{page}{1}
\end{frontmatter}
-%%%%% end titlepage extension code\ifdefined\Shaded\renewenvironment{Shaded}{\begin{tcolorbox}[boxrule=0pt, frame hidden, sharp corners, interior hidden, borderline west={3pt}{0pt}{shadecolor}, breakable, enhanced]}{\end{tcolorbox}}\fi
+%%%%% end titlepage extension code\ifdefined\Shaded\renewenvironment{Shaded}{\begin{tcolorbox}[boxrule=0pt, interior hidden, frame hidden, sharp corners, borderline west={3pt}{0pt}{shadecolor}, enhanced, breakable]}{\end{tcolorbox}}\fi
\renewcommand*\contentsname{Table of contents}
{
@@ -1114,96 +1114,38 @@ \section{Data levels}\label{data-levels}}
\hypertarget{news}{%
\chapter{News}\label{news}}
-\hypertarget{future-plans}{%
-\section{Future plans}\label{future-plans}}
-
-\hypertarget{goa-2025-restratification-mock-data-for-testing}{%
-\subsection{GOA 2025 Restratification -- Mock Data for
-Testing}\label{goa-2025-restratification-mock-data-for-testing}}
-
-The plan will be, once all are satisfied with the new GAP\_PRODUCTS
-schema and tables, to sunset the historic product tables in 2024 and
-proceed with only GAP\_PRODUCTS for the 2024 post-survey stock
-assessment season.
-
-\begin{itemize}
-\item
- December 2023 - March 2024: Meeting between GAP and stock assessment
- groups in early December 2023 to update progress on the GAP\_PRODUCTS
- testing phase. \textbf{Deadline for Comments and Feedback on
- GAP\_PRODUCTS data structures is March 8, 2024.}
-\item
- September 2024: GAP will only release data products according to the
- new standard. Current, historical data product tables will be archived
- in a new schema called "\textbf{GAP\_ARCHIVE}".
-\end{itemize}
-
-\hypertarget{previous-updates}{%
-\section{Previous updates}\label{previous-updates}}
-
-\begin{itemize}
-\item
- September 2023: Provisional data product tables -- CPUE, BIOMASS,
- SIZECOMP, and AGECOMP -- as well as provisional support tables --
- AREA, STRATUM\_GROUPS, METADATA\_COLUMN, SPECIES\_YEAR, SURVEY\_DESIGN
- -- are available in the GAP\_PRODUCTS Oracle schema with updated 2023
- GOA and EBS survey data.
-
- \begin{itemize}
- \item
- Additionally, the inclusion of mock data for the under the new 2025
- GOA stratified random survey (labeled in the GAP\_PRODUCTS tables as
- YEAR 2025) will provide stock authors with the opportunity to
- interact with data from the new survey design to be implemented in
- 2025.
- \item
- Provisional AKFIN and FOSS tables are also available in the
- GAP\_PRODUCTS Oracle schema. These include: AKFIN\_AGECOMP,
- AKFIN\_AREA, AKFIN\_BIOMASS, AKFIN\_CATCH, AKFIN\_CPUE,
- AKFIN\_CRUISE, AKFIN\_HAUL, AKFIN\_LENGTH, AKFIN\_METADATA\_COLUMN,
- AKFIN\_SIZECOMP, AKFIN\_SPECIMEN, AKFIN\_SURVEY\_DESIGN,
- AKFIN\_STRATUM\_GROUPS, FOSS\_CATCH, FOSS\_CPUE\_PRESONLY,
- FOSS\_HAUL, and FOSS\_TAXON\_GROUP.
- \end{itemize}
-\item
- May 2023: Release of new, draft, standard data product tables,
- including restratified GOA data. Stock assessment authors will have
- the opportunity to explore differences between datasets, test
- workflows, and provide comments and issues during summer 2023.
-\item
- February 2023: Decision was made to include the mock restratified GOA
- data with the development of the new consolidated standard data
- products.
-\item
- December 2022:
- \href{https://docs.google.com/document/d/1AURrvC1na6TL1Um3p7018svBLDOnih_7nxxyRU34M0k/edit}{GAP
- and SSMA discuss} integration of the restratification of the GOA
- survey design into standard data products.
-
- \begin{itemize}
- \item
- Stock assessors requested a "dry run" test to work with new mock
- restratified GOA survey data before implementation of the new survey
- design.
- \item
- This prompted the postponement of the restratified GOA design to
- 2025.
- \end{itemize}
-\item
- October 2022: The data processes and index computation working group
- convened to address the development of standard survey data products
- (e.g., biomass/abundance, size composition, age composition, CPUE).
-
- \begin{itemize}
- \item
- Index Computation Working Group: consolidation of index computation
- methods between the Bering Sea and AI-GOA regions.
- \item
- Data Processes Working Group: consolidation, clean up, and
- reorganization of survey oracle schemata, tables, and other data for
- all surveys.
- \end{itemize}
-\end{itemize}
+\hypertarget{newschange-logs}{%
+\section{News/change logs}\label{newschange-logs}}
+
+--
+\href{C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-06-01_v2-1-0.txt}{Run
+2023-06-01 gapindex v2.1.0}: Initial compiling and planning notes
+
+--
+\href{C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-11-14_v2-1-1.txt}{GAP\_PRODUCTS
+ChangeLog (last produced on 2023-11-14) using gapindex v2.1.1}: A new
+version of gapindex (v2.1.1) was used to produced these data. There was
+a slight change to how subarea biomass totals are calculated. The
+modified biomass records reflect this change. New 2022 otolith data were
+available since the last iteration of the GAP\_PRODUCTS for Aleutian
+Island Pacific ocean perch and northern rockifsh and Eastern Bering Sea
+northern rock sole. Zero-filled CPUE records for four GOA species codes
+(SPECIES\_CODE: 21210, 30010, 30360, 77102, 98101) were added due to how
+the 1990 data were integrated in the last production run of
+GAP\_PRODUCTS. Two Arctic cod (SPECIES\_CODE: 21725) and one plain
+sculpin (SPECIES\_CODE: 21371) count records were modified in the NBS
+data, which changes the numerical CPUE estimates for those hauls which
+changes the estimated population abundance and size composition for
+those species.
+
+--
+\href{C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-11-17.txt}{GAP\_PRODUCTS
+ChangeLog (last produced on 2023-11-17) using gapindex v2.1.2}: A new
+version of gapindex
+(\href{https://github.com/afsc-gap-products/gapindex/releases/tag/v2.1.2}{v2.1.2})
+was used to produced these data. There was a slight change to how
+subarea biomass totals are calculated that was not fully addressed in
+v2.1.1. The modified biomass records reflect this change.
\hypertarget{code-of-conduct}{%
\chapter{Code of Conduct}\label{code-of-conduct}}
@@ -4265,9 +4207,9 @@ \section*{Data SQL Query Examples:}\label{data-sql-query-examples}}
\end{Highlighting}
\end{Shaded}
-\hypertarget{ex.-select-all-data-from-a-table}{%
-\subsection{Ex. Select all data from a
-table}\label{ex.-select-all-data-from-a-table}}
+\hypertarget{ex.-select-all-data-from-tables}{%
+\subsection{Ex. Select all data from
+tables}\label{ex.-select-all-data-from-tables}}
You can download all of the tables locally using a variation of the code
below. Once connected, pull and save the tables of interest into the
@@ -4300,6 +4242,130 @@ \subsection{Ex. Select all data from a
\end{Highlighting}
\end{Shaded}
+\hypertarget{ex.-cpue-for-all-ebs-and-nbs-stations-with-associated-haul-cruise-and-species-information.}{%
+\subsection{Ex. CPUE for all EBS and NBS stations with associated haul,
+cruise, and species
+information.}\label{ex.-cpue-for-all-ebs-and-nbs-stations-with-associated-haul-cruise-and-species-information.}}
+
+\begin{Shaded}
+\begin{Highlighting}[]
+\NormalTok{a }\OtherTok{\textless{}{-}}\NormalTok{ RODBC}\SpecialCharTok{::}\FunctionTok{sqlQuery}\NormalTok{(}\AttributeTok{channel =}\NormalTok{ channel, }\CommentTok{\# NOT RACEBASE.HAUL}
+ \AttributeTok{query =} \FunctionTok{paste0}\NormalTok{(}
+\StringTok{"}
+\StringTok{{-}{-} Select columns for output data}
+\StringTok{SELECT}
+\StringTok{cr.CRUISEJOIN,}
+\StringTok{cr.CRUISE,}
+\StringTok{cr.YEAR,}
+\StringTok{cr.SURVEY\_DEFINITION\_ID,}
+\StringTok{cr.SURVEY\_NAME,}
+\StringTok{cr.VESSEL\_ID,}
+\StringTok{cr.VESSEL\_NAME,}
+\StringTok{cp.HAULJOIN,}
+\StringTok{cp.SPECIES\_CODE,}
+\StringTok{tt.SPECIES\_NAME,}
+\StringTok{tt.COMMON\_NAME,}
+\StringTok{cp.WEIGHT\_KG,}
+\StringTok{cp.COUNT,}
+\StringTok{cp.AREA\_SWEPT\_KM2,}
+\StringTok{cp.CPUE\_KGKM2,}
+\StringTok{cp.CPUE\_NOKM2,}
+\StringTok{hh.HAUL,}
+\StringTok{hh.STATION}
+
+\StringTok{{-}{-} Identify what tables to pull data from}
+\StringTok{FROM GAP\_PRODUCTS.AKFIN\_HAUL hh}
+\StringTok{LEFT JOIN GAP\_PRODUCTS.AKFIN\_CRUISE cr}
+\StringTok{ON hh.CRUISEJOIN = cr.CRUISEJOIN}
+\StringTok{LEFT JOIN GAP\_PRODUCTS.AKFIN\_CPUE cp}
+\StringTok{ON hh.HAULJOIN = cp.HAULJOIN}
+\StringTok{LEFT JOIN GAP\_PRODUCTS.TAXONOMIC\_CLASSIFICATION tt}
+\StringTok{ON cp.SPECIES\_CODE = tt.SPECIES\_CODE}
+
+\StringTok{{-}{-} Filter for EBS and NBS observations}
+\StringTok{WHERE SURVEY\_DEFINITION\_ID IN (143, 98) {-}{-} 143 NBS, 98 EBS}
+\StringTok{AND tt.SURVEY\_SPECIES = 1}
+
+\StringTok{{-}{-} Only return the first 3 rows because otherwise this would be a huge table!}
+\StringTok{FETCH FIRST 3 ROWS ONLY;"}\NormalTok{)) }
+
+\NormalTok{flextable}\SpecialCharTok{::}\FunctionTok{flextable}\NormalTok{(}\FunctionTok{head}\NormalTok{(a)) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{theme\_zebra}\NormalTok{()}
+\end{Highlighting}
+\end{Shaded}
+
+\global\setlength{\Oldarrayrulewidth}{\arrayrulewidth}
+
+\global\setlength{\Oldtabcolsep}{\tabcolsep}
+
+\setlength{\tabcolsep}{0pt}
+
+\renewcommand*{\arraystretch}{1.5}
+
+
+
+\providecommand{\ascline}[3]{\noalign{\global\arrayrulewidth #1}\arrayrulecolor[HTML]{#2}\cline{#3}}
+
+\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}
+\caption{Ex.: CPUE for all EBS and NBS stations with associated haul, cruise, and
+species information.}\tabularnewline
+
+
+
+
+\hhline{>{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}-}
+
+\multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{CRUISEJOIN}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{CRUISE}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{YEAR}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{SURVEY\_DEFINITION\_ID}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{SURVEY\_NAME}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{VESSEL\_ID}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{VESSEL\_NAME}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{HAULJOIN}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{SPECIES\_CODE}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{SPECIES\_NAME}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{COMMON\_NAME}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{WEIGHT\_KG}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{COUNT}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{AREA\_SWEPT\_KM2}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{CPUE\_KGKM2}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{CPUE\_NOKM2}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{HAUL}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{STATION}}}} \\
+
+\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
+
+\endfirsthead
+
+\hhline{>{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}-}
+
+\multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{CRUISEJOIN}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{CRUISE}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{YEAR}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{SURVEY\_DEFINITION\_ID}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{SURVEY\_NAME}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{VESSEL\_ID}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{VESSEL\_NAME}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{HAULJOIN}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{SPECIES\_CODE}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{SPECIES\_NAME}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{COMMON\_NAME}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{WEIGHT\_KG}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{COUNT}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{AREA\_SWEPT\_KM2}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{CPUE\_KGKM2}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{CPUE\_NOKM2}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{HAUL}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{STATION}}}} \\
+
+\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
+
+\endhead
+
+
+
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{80}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{198,203}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,982}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{98}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Eastern\ Bering\ Sea\ Crab/Groundfish\ Bottom\ Trawl\ Survey}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{CHAPMAN}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{877}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{fish\ egg\ unid.}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.042021}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{G-10}}} \\
+
+\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
+
+
+
+
+
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{80}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{198,203}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,982}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{98}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Eastern\ Bering\ Sea\ Crab/Groundfish\ Bottom\ Trawl\ Survey}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{CHAPMAN}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{877}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{fish\ larvae\ unid.}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.042021}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{G-10}}} \\
+
+\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
+
+
+
+
+
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{80}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{198,203}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,982}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{98}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Eastern\ Bering\ Sea\ Crab/Groundfish\ Bottom\ Trawl\ Survey}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{CHAPMAN}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{877}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{3}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{fish\ unid.}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.042021}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{G-10}}} \\
+
+\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
+
+
+
+
+
+\end{longtable}
+
+
+
+\arrayrulecolor[HTML]{000000}
+
+\global\setlength{\arrayrulewidth}{\Oldarrayrulewidth}
+
+\global\setlength{\tabcolsep}{\Oldtabcolsep}
+
+\renewcommand*{\arraystretch}{1}
+
\hypertarget{ex.-cpue-for-all-stations-contained-in-the-inpfc-shumagin-region-area_id-919-for-pacific-cod.}{%
\subsection{Ex. CPUE for all stations contained in the INPFC Shumagin
region (AREA\_ID = 919) for Pacific
@@ -4388,7 +4454,7 @@ \subsection{Ex. CPUE for all stations contained in the INPFC Shumagin
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,239}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{12}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{55.43748}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-160.1269}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{717.63085}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4.5}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,270}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{13}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{55.11515}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-159.3512}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{209.28994}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4.3}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4396,7 +4462,7 @@ \subsection{Ex. CPUE for all stations contained in the INPFC Shumagin
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,215}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{13}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{54.58732}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-161.1945}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{76.90763}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4.3}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,250}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{13}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{55.05143}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-159.9679}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{8,700.92017}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{5.1}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4404,7 +4470,7 @@ \subsection{Ex. CPUE for all stations contained in the INPFC Shumagin
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,168}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{11}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{54.45823}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-163.0872}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2,004.49628}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4.9}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,238}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{13}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{55.11365}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-159.4264}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{363.17325}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4.4}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4412,7 +4478,7 @@ \subsection{Ex. CPUE for all stations contained in the INPFC Shumagin
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,204}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{110}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{54.51804}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-160.7493}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.00000}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4.7}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,214}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{13}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{54.78608}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-160.0008}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{63.71506}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4.6}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4420,7 +4486,7 @@ \subsection{Ex. CPUE for all stations contained in the INPFC Shumagin
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,188}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{210}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{54.38733}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-159.6986}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.00000}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{5.5}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,202}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{111}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{54.48341}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-159.7261}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{618.72120}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4.7}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4428,7 +4494,7 @@ \subsection{Ex. CPUE for all stations contained in the INPFC Shumagin
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,183}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{210}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{54.09314}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-161.6996}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.00000}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{5.3}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-22,247}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{112}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21720}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{55.59093}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-160.0740}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{114.73042}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4.0}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4531,7 +4597,7 @@ \subsection{\texorpdfstring{Ex. EBS Pacific Ocean perch CPUE and
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.0000000}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{58.75863}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-174.9285}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.00000000}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{60.67043}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-178.0946}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4539,7 +4605,7 @@ \subsection{\texorpdfstring{Ex. EBS Pacific Ocean perch CPUE and
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.2813533}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{57.32545}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-173.3217}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.00000000}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{60.31361}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-176.0138}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4547,7 +4613,7 @@ \subsection{\texorpdfstring{Ex. EBS Pacific Ocean perch CPUE and
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.0000000}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{57.64161}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-172.7963}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.00000000}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{60.35098}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-175.3850}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4555,7 +4621,7 @@ \subsection{\texorpdfstring{Ex. EBS Pacific Ocean perch CPUE and
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.0000000}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{59.67831}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-172.5754}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.00000000}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{60.99712}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-177.6638}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4563,7 +4629,7 @@ \subsection{\texorpdfstring{Ex. EBS Pacific Ocean perch CPUE and
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.0000000}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{60.96936}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-174.8760}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.00000000}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{60.96495}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-176.2634}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4571,7 +4637,7 @@ \subsection{\texorpdfstring{Ex. EBS Pacific Ocean perch CPUE and
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.0000000}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{58.64012}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-173.5922}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{0.02416379}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{58.97844}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-175.7204}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4648,7 +4714,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and
\StringTok{{-}{-} Manipulate data to join to}
\StringTok{WITH FILTERED\_STRATA AS (}
\StringTok{SELECT AREA\_ID, DESCRIPTION FROM GAP\_PRODUCTS.AKFIN\_AREA}
-\StringTok{WHERE TYPE in (\textquotesingle{}REGULATORY\_AREA\textquotesingle{}, \textquotesingle{}REGION\textquotesingle{}) }
+\StringTok{WHERE AREA\_TYPE in (\textquotesingle{}REGULATORY\_AREA\textquotesingle{}, \textquotesingle{}REGION\textquotesingle{}) }
\StringTok{AND SURVEY\_DEFINITION\_ID = 47)}
\StringTok{{-}{-} Select columns for output data}
@@ -4728,7 +4794,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{483,622.6}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{833,902,161}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1993}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{157,295.1}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{317,129,408}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1990}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4736,7 +4802,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{483,622.6}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{833,902,161}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1993}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{157,295.1}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{317,129,408}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1990}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4744,7 +4810,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{771,412.8}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,252,616,603}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1996}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{483,622.6}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{833,902,161}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1993}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4752,7 +4818,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{771,412.8}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,252,616,603}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1996}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{483,622.6}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{833,902,161}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1993}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4760,7 +4826,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{727,063.5}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,212,034,913}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1999}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{771,412.8}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,252,616,603}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1996}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4768,7 +4834,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{727,063.5}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,212,034,913}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1999}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{771,412.8}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,252,616,603}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1996}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{GOA\ Region:\ All\ Strata}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4837,11 +4903,11 @@ \subsection{Ex. AI rock sole size compositions and ridge
\StringTok{WITH FILTERED\_STRATA AS (}
\StringTok{SELECT }
\StringTok{AREA\_ID, }
-\StringTok{DESCRIPTION }
+\StringTok{DESCRIPTION}
\StringTok{{-}{-} Identify what tables to pull data from}
\StringTok{FROM GAP\_PRODUCTS.AKFIN\_AREA}
-\StringTok{WHERE TYPE = \textquotesingle{}REGION\textquotesingle{} }
+\StringTok{WHERE AREA\_TYPE = \textquotesingle{}REGION\textquotesingle{} }
\StringTok{AND SURVEY\_DEFINITION\_ID = 52)}
\StringTok{{-}{-} Select columns for output data}
@@ -4862,10 +4928,12 @@ \subsection{Ex. AI rock sole size compositions and ridge
\begin{Highlighting}[]
\NormalTok{dat0 }\OtherTok{\textless{}{-}}\NormalTok{ dat }\SpecialCharTok{\%\textgreater{}\%}
\NormalTok{ janitor}\SpecialCharTok{::}\FunctionTok{clean\_names}\NormalTok{() }\SpecialCharTok{\%\textgreater{}\%}
-\NormalTok{ dplyr}\SpecialCharTok{::}\FunctionTok{mutate}\NormalTok{(}\AttributeTok{length\_cm =}\NormalTok{ length\_mm}\SpecialCharTok{/}\DecValTok{10}\NormalTok{)}
-\NormalTok{flextable}\SpecialCharTok{::}\FunctionTok{flextable}\NormalTok{(}\FunctionTok{head}\NormalTok{(dat)) }\SpecialCharTok{\%\textgreater{}\%}
- \FunctionTok{theme\_zebra}\NormalTok{() }\SpecialCharTok{\%\textgreater{}\%}
-\NormalTok{ flextable}\SpecialCharTok{::}\FunctionTok{colformat\_num}\NormalTok{(}\AttributeTok{x =}\NormalTok{ ., }\AttributeTok{j =} \StringTok{"YEAR"}\NormalTok{, }\AttributeTok{big.mark =} \StringTok{""}\NormalTok{)}
+\NormalTok{ dplyr}\SpecialCharTok{::}\FunctionTok{mutate}\NormalTok{(}\AttributeTok{length\_cm =}\NormalTok{ length\_mm}\SpecialCharTok{/}\DecValTok{10}\NormalTok{) }\SpecialCharTok{\%\textgreater{}\%}
+ \FunctionTok{head}\NormalTok{() }\SpecialCharTok{\%\textgreater{}\%}
+\NormalTok{ flextable}\SpecialCharTok{::}\FunctionTok{flextable}\NormalTok{() }\SpecialCharTok{\%\textgreater{}\%}
+\NormalTok{ flextable}\SpecialCharTok{::}\FunctionTok{theme\_zebra}\NormalTok{() }\SpecialCharTok{\%\textgreater{}\%}
+\NormalTok{ flextable}\SpecialCharTok{::}\FunctionTok{colformat\_num}\NormalTok{(}\AttributeTok{x =}\NormalTok{ ., }\AttributeTok{j =} \StringTok{"year"}\NormalTok{, }\AttributeTok{big.mark =} \StringTok{""}\NormalTok{)}
+\NormalTok{dat0}
\end{Highlighting}
\end{Shaded}
@@ -4881,23 +4949,23 @@ \subsection{Ex. AI rock sole size compositions and ridge
\providecommand{\ascline}[3]{\noalign{\global\arrayrulewidth #1}\arrayrulecolor[HTML]{#2}\cline{#3}}
-\begin{longtable}[c]{|p{0.75in}|p{0.75in}}
+\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}}
\caption{Ex. 2: AI Rock sole size compositions and ridge plot.}\tabularnewline
-\hhline{>{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}-}
+\hhline{>{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}-}
-\multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{LENGTH\_MM}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{YEAR}}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{length\_mm}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{year}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{length\_cm}}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
\endfirsthead
-\hhline{>{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}-}
+\hhline{>{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}->{\arrayrulecolor[HTML]{000000}\global\arrayrulewidth=0pt}-}
-\multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{LENGTH\_MM}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{YEAR}}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{length\_mm}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{year}}}} & \multicolumn{1}{>{\cellcolor[HTML]{CFCFCF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{\textbf{length\_cm}}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4905,7 +4973,7 @@ \subsection{Ex. AI rock sole size compositions and ridge
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{180}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2014}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{110}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1997}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{11}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4913,7 +4981,7 @@ \subsection{Ex. AI rock sole size compositions and ridge
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{190}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2014}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{130}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1997}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{13}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4921,7 +4989,7 @@ \subsection{Ex. AI rock sole size compositions and ridge
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{200}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2014}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{140}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1997}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{14}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4929,7 +4997,7 @@ \subsection{Ex. AI rock sole size compositions and ridge
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{210}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2014}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{150}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1997}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{15}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4937,7 +5005,7 @@ \subsection{Ex. AI rock sole size compositions and ridge
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{220}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2014}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{160}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1997}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{16}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4945,7 +5013,7 @@ \subsection{Ex. AI rock sole size compositions and ridge
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{230}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2014}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{170}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1997}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{17}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -4971,8 +5039,8 @@ \subsection{Ex. AI rock sole size compositions and ridge
\FunctionTok{library}\NormalTok{(ggridges)}
\NormalTok{figure }\OtherTok{\textless{}{-}}
\NormalTok{ ggplot2}\SpecialCharTok{::}\FunctionTok{ggplot}\NormalTok{(}
- \AttributeTok{data =}\NormalTok{ dat0, }
- \AttributeTok{mapping =} \FunctionTok{aes}\NormalTok{(}\AttributeTok{x =}\NormalTok{ length\_cm, }\AttributeTok{y =} \FunctionTok{as.factor}\NormalTok{(year), }\AttributeTok{fill =} \FunctionTok{stat}\NormalTok{(x))) }\SpecialCharTok{+}
+ \AttributeTok{data =}\NormalTok{ dat, }
+ \AttributeTok{mapping =} \FunctionTok{aes}\NormalTok{(}\AttributeTok{x =}\NormalTok{ LENGTH\_MM, }\AttributeTok{y =} \FunctionTok{as.factor}\NormalTok{(YEAR), }\AttributeTok{fill =} \FunctionTok{stat}\NormalTok{(x))) }\SpecialCharTok{+}
\NormalTok{ ggridges}\SpecialCharTok{::}\FunctionTok{theme\_ridges}\NormalTok{(}\AttributeTok{center\_axis\_labels =} \ConstantTok{TRUE}\NormalTok{) }\SpecialCharTok{+}
\NormalTok{ ggridges}\SpecialCharTok{::}\FunctionTok{geom\_density\_ridges\_gradient}\NormalTok{(}\AttributeTok{scale =} \DecValTok{4}\NormalTok{, }\AttributeTok{show.legend =} \ConstantTok{FALSE}\NormalTok{) }\SpecialCharTok{+}
\NormalTok{ ggplot2}\SpecialCharTok{::}\FunctionTok{scale\_y\_discrete}\NormalTok{(}\AttributeTok{name =} \StringTok{"Year"}\NormalTok{, }\AttributeTok{expand =} \FunctionTok{c}\NormalTok{(}\FloatTok{0.01}\NormalTok{, }\DecValTok{0}\NormalTok{)) }\SpecialCharTok{+}
@@ -5012,7 +5080,7 @@ \subsection{Ex. EBS Walleye Pollock Age Compositions and Age
\StringTok{AREA\_ID, }
\StringTok{DESCRIPTION }
\StringTok{FROM GAP\_PRODUCTS.AKFIN\_AREA}
-\StringTok{WHERE TYPE = \textquotesingle{}REGION\textquotesingle{} AND }
+\StringTok{WHERE AREA\_TYPE = \textquotesingle{}REGION\textquotesingle{} AND }
\StringTok{SURVEY\_DEFINITION\_ID = 98)}
\StringTok{{-}{-} Select columns for output data}
@@ -5082,7 +5150,7 @@ \subsection{Ex. EBS Walleye Pollock Age Compositions and Age
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{9}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{39,371}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{3}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{11}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{48,791,451}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5090,7 +5158,7 @@ \subsection{Ex. EBS Walleye Pollock Age Compositions and Age
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{10}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{32,156}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{3}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{12}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{120,673,580}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5098,7 +5166,7 @@ \subsection{Ex. EBS Walleye Pollock Age Compositions and Age
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{11}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{15,200}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{3}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{13}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{42,580,054}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5106,7 +5174,7 @@ \subsection{Ex. EBS Walleye Pollock Age Compositions and Age
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{12}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{9,976}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{3}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{14}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47,229,378}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5114,7 +5182,7 @@ \subsection{Ex. EBS Walleye Pollock Age Compositions and Age
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{13}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,957}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{3}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{15}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{25,140,523}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5122,7 +5190,7 @@ \subsection{Ex. EBS Walleye Pollock Age Compositions and Age
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{131,950,343}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{16}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{19,473,255}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5191,7 +5259,7 @@ \subsection{Ex. NBS Pacific cod biomass and
\StringTok{AREA\_NAME, }
\StringTok{DESCRIPTION }
\StringTok{FROM GAP\_PRODUCTS.AKFIN\_AREA}
-\StringTok{WHERE TYPE in (\textquotesingle{}STRATUM\textquotesingle{}) AND }
+\StringTok{WHERE AREA\_TYPE in (\textquotesingle{}STRATUM\textquotesingle{}) AND }
\StringTok{SURVEY\_DEFINITION\_ID = 143) }
\StringTok{{-}{-} Select columns for output data}
@@ -5266,7 +5334,7 @@ \subsection{Ex. NBS Pacific cod biomass and
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{95,849.983}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{68,767,498}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2021}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{7,462.559}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4,724,153}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2010}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5274,7 +5342,7 @@ \subsection{Ex. NBS Pacific cod biomass and
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{107,096.730}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{102,734,142}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2019}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{7,462.559}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4,724,153}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2010}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5282,7 +5350,7 @@ \subsection{Ex. NBS Pacific cod biomass and
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{76,708.433}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{39,605,860}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2023}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{7,462.559}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4,724,153}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2010}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5290,7 +5358,7 @@ \subsection{Ex. NBS Pacific cod biomass and
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{132,490.152}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{66,187,245}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2017}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{7,462.559}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4,724,153}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2010}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5298,7 +5366,7 @@ \subsection{Ex. NBS Pacific cod biomass and
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{96,500.697}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{60,433,135}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2022}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{7,462.559}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4,724,153}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2010}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5306,7 +5374,7 @@ \subsection{Ex. NBS Pacific cod biomass and
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{7,462.559}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{4,724,153}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2010}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{95,849.983}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{68,767,498}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2021}}} & \multicolumn{1}{>{\raggedright}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{Inner\ Domain}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5435,7 +5503,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and line
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{483,622.6}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{11,803,384,787}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1993}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{483.6226}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{700.9093}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{266.33581}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{157,295.1}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2,221,176,968}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1990}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{157.2951}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{251.5538}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{63.03638}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5443,7 +5511,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and line
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{771,412.8}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{41,434,152,202}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1996}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{771.4128}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,178.5204}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{364.30515}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{483,622.6}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{11,803,384,787}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1993}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{483.6226}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{700.9093}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{266.33581}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5451,7 +5519,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and line
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{727,063.5}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{150,983,542,178}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1999}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{727.0635}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,504.1955}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-50.06854}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{771,412.8}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{41,434,152,202}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1996}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{771.4128}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,178.5204}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{364.30515}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5459,7 +5527,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and line
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{673,155.1}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{49,285,342,922}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2001}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{673.1551}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,117.1611}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{229.14901}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{727,063.5}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{150,983,542,178}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1999}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{727.0635}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,504.1955}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{-50.06854}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5467,7 +5535,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and line
-\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{457,421.6}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{5,186,126,529}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2003}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{457.4216}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{601.4511}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{313.39204}}} \\
+\multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{673,155.1}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{49,285,342,922}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2001}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{673.1551}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,117.1611}}} & \multicolumn{1}{>{\cellcolor[HTML]{EFEFEF}\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{229.14901}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -5475,7 +5543,7 @@ \subsection{Ex. GOA Pacific Ocean perch biomass and line
-\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{764,901.4}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{21,499,807,010}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2005}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{764.9014}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{1,058.1577}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{471.64517}}} \\
+\multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{47}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{457,421.6}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{5,186,126,529}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{2003}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{457.4216}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{601.4511}}} & \multicolumn{1}{>{\raggedleft}m{\dimexpr 0.75in+0\tabcolsep}}{\textcolor[HTML]{000000}{\fontsize{11}{11}\selectfont{313.39204}}} \\
\noalign{\global\arrayrulewidth 0pt}\arrayrulecolor[HTML]{000000}
@@ -7740,8 +7808,8 @@ \section{Ex. 7: Visualize CPUE data in distribution
\AttributeTok{set.breaks =} \StringTok{"jenks"}\NormalTok{, }\CommentTok{\# Gets Jenks breaks from classint::classIntervals()}
\AttributeTok{in.crs =} \StringTok{"+proj=longlat"}\NormalTok{, }\CommentTok{\# Set input coordinate reference system}
\AttributeTok{out.crs =} \StringTok{"EPSG:3338"}\NormalTok{, }\CommentTok{\# Set output coordinate reference system}
- \AttributeTok{grid.cell =} \FunctionTok{c}\NormalTok{(}\DecValTok{20000}\NormalTok{, }\DecValTok{20000}\NormalTok{), }\CommentTok{\# 20x20km grid}
- \AttributeTok{key.title =} \StringTok{"Pacific Ocean perch"}\NormalTok{) }\CommentTok{\# Include in the legend title}
+ \AttributeTok{grid.cell =} \FunctionTok{c}\NormalTok{(}\DecValTok{20000}\NormalTok{, }\DecValTok{20000}\NormalTok{))}\SpecialCharTok{$}\NormalTok{plot }\SpecialCharTok{+} \CommentTok{\# 20x20km grid}
+\NormalTok{ ggplot2}\SpecialCharTok{::}\FunctionTok{guides}\NormalTok{(}\AttributeTok{fill=}\FunctionTok{guide\_legend}\NormalTok{(}\AttributeTok{title =} \StringTok{"Pacific cod}\SpecialCharTok{\textbackslash{}n}\StringTok{CPUE (kg/km2)"}\NormalTok{))}
\end{Highlighting}
\end{Shaded}
@@ -7750,23 +7818,6 @@ \section{Ex. 7: Visualize CPUE data in distribution
[inverse distance weighted interpolation]
\end{verbatim}
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{figure}\SpecialCharTok{$}\NormalTok{plot }\SpecialCharTok{+}
-\NormalTok{ ggplot2}\SpecialCharTok{::}\FunctionTok{guides}\NormalTok{(}\AttributeTok{fill=}\FunctionTok{guide\_legend}\NormalTok{(}\AttributeTok{title =} \StringTok{"Pacific cod}\SpecialCharTok{\textbackslash{}n}\StringTok{CPUE (kg/km2)"}\NormalTok{))}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{figure}[H]
-
-{\centering \includegraphics{content/foss-api-r_files/figure-pdf/test-7-fig-1.pdf}
-
-}
-
-\caption{Ex. 7: Visualize CPUE data in distribution map.}
-
-\end{figure}
-
\hypertarget{access-via-api-and-python}{%
\chapter{Access via API and Python}\label{access-via-api-and-python}}
diff --git a/_freeze/content/akfin-oracle-sql-r/execute-results/docx.json b/_freeze/content/akfin-oracle-sql-r/execute-results/docx.json
index 9c8efbb..6d87513 100644
--- a/_freeze/content/akfin-oracle-sql-r/execute-results/docx.json
+++ b/_freeze/content/akfin-oracle-sql-r/execute-results/docx.json
@@ -1,7 +1,7 @@
{
- "hash": "6ca4dec388d9bb5ed42dd65c29ee5da6",
+ "hash": "e95dda4032f9d6c0c84201c12b9852cc",
"result": {
- "markdown": "---\ntitle: Access data\nnumber-sections: true\nnumber-depth: 3\n---\n\n\n\n\n\n\n## Access data via Oracle (AFSC only) {.unnumbered}\n\nAFSC `Oracle` users can access the database via `SQL developer` to view and pull the production data directly from the `GAP_PRODUCTS` `Oracle` schema. The user can also use `SQL developer` to view and pull the GAP Products data directly from the `GAP_PRODUCTS` `Oracle` schema. \n\n### Connect to Oracle from R\n\nMany users will want to access the data from `Oracle` using `R`. The user will need to install the `RODBC` `R` package and ask OFIS (IT) connect `R` to `Oracle`. Then, use the following code in `R` to establish a connection from `R` to `Oracle`: \n\nHere, the user can establish the oracle connection by entering their username and password in the `channel <- gapindex::oracle_connect()` function. Never save usernames or passwords in scripts that may be intentionally or unintentionally shared with others. If no username and password is entered in the function, pop-ups will appear on the screen asking for the username and password. \n\nAfter you connect to VPN, you'll be able to log into Oracle. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(RODBC)\nchannel <- gapindex::get_connected()\n```\n:::\n\n\n\n\n## Data SQL Query Examples: {.unnumbered}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(gapindex)\nlibrary(RODBC)\nlibrary(flextable)\nlibrary(ggplot2)\nlibrary(magrittr)\nlibrary(dplyr)\n```\n:::\n\n\n\n\n### Ex. Select all data from a table\n\nYou can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the `R` environment. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlocations <- c(\n \"GAP_PRODUCTS.AKFIN_AGECOMP\", \n \"GAP_PRODUCTS.AKFIN_AREA\", \n \"GAP_PRODUCTS.AKFIN_BIOMASS\", \n \"GAP_PRODUCTS.AKFIN_CATCH\", \n \"GAP_PRODUCTS.AKFIN_CPUE\", \n \"GAP_PRODUCTS.AKFIN_CRUISE\", \n \"GAP_PRODUCTS.AKFIN_HAUL\", \n \"GAP_PRODUCTS.AKFIN_LENGTH\", \n \"GAP_PRODUCTS.AKFIN_METADATA_COLUMN\", \n \"GAP_PRODUCTS.AKFIN_SIZECOMP\", \n \"GAP_PRODUCTS.AKFIN_SPECIMEN\", \n \"GAP_PRODUCTS.AKFIN_STRATUM_GROUPS\", \n \"GAP_PRODUCTS.AKFIN_SURVEY_DESIGN\", \n \"GAP_PRODUCTS.AKFIN_TAXONOMIC_CLASSIFICATION\"\n)\n\nfor (i in 1:length(locations)) {\n print(locations[i])\n a <- RODBC::sqlQuery(channel, paste0(\"SELECT * FROM \", locations[i]))\n write.csv(x = a, file = here::here(\"data\", paste0(locations[i], \".csv\")))\n}\n```\n:::\n\n::: {.cell}\n\n:::\n\n::: {.cell}\n\n:::\n\n::: {.cell tbl-cap='Ex. 7: Summary table of Number hauls where species were observed (N_HAULS) and number of length measurements that were colelcted for this species (N_LENGTHS) for EBS and NBS, for arrowtooth flounder (10110), Bering flounder (10140), and Alaska skate (435). '}\n\n:::\n\n\n\n\n### Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel,\n query =\n\"\n-- Select columns for output data\nSELECT \nHAULJOIN, \nSPECIES_CODE, \nSTRATUM, \nLATITUDE_DD_START, \nLONGITUDE_DD_START,\nCPUE_KGKM2, \nGEAR_TEMPERATURE_C\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_CPUE cpue\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL haul\nUSING (HAULJOIN) \n\n-- Filter for P. Cod observations\nWHERE SPECIES_CODE IN (21720)\n\n-- Select all stratum within the area_id 919 (INPFC Shumagin region)\nAND haul.STRATUM IN\n(\nSELECT \nSTRATUM\nFROM GAP_PRODUCTS.AKFIN_STRATUM_GROUPS \nWHERE AREA_ID = 919\n);\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 8: CPUE for all stations contained in the Shumagin region (AREA_ID = 919). '}\n\n```{.r .cell-code}\ndat <- dat %>% \n dplyr::select(HAULJOIN, STRATUM, SPECIES_CODE, LATITUDE_DD_START, LONGITUDE_DD_START, CPUE_KGKM2, GEAR_TEMPERATURE_C) %>% \n dplyr::mutate(SPECIES_CODE = as.character(SPECIES_CODE), \n STRATUM = as.character(STRATUM)) %>% \n dplyr::arrange(SPECIES_CODE)\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1HAULJOINSTRATUMSPECIES_CODELATITUDE_DD_STARTLONGITUDE_DD_STARTCPUE_KGKM2GEAR_TEMPERATURE_Cbody1-22,239122172055.43748-160.1269717.630854.5body2-22,215132172054.58732-161.194576.907634.3body3-22,168112172054.45823-163.08722,004.496284.9body4-22,2041102172054.51804-160.74930.000004.7body5-22,1882102172054.38733-159.69860.000005.5body6-22,1832102172054.09314-161.69960.000005.3\n``````\n:::\n:::\n\n\n\n\n### Ex. EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map \n\nPacific Ocean perch catch-per-unit-effort estimates for EBS in 2021 from `GAP_PRODUCTS.AKFIN_CPUE` and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). Here, we'll use AKFIN HAUL and CRUISES data also included in this repo, for convenience, though they are very similar to their `RACEBASE` analogs. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \n(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares\nhh.LATITUDE_DD_START LATITUDE,\nhh.LONGITUDE_DD_START LONGITUDE\n\n-- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin\nFROM GAP_PRODUCTS.AKFIN_CPUE cp\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh\nON cp.HAULJOIN = hh.HAULJOIN\n\n-- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc\nON hh.CRUISEJOIN = cc.CRUISEJOIN\n\n-- Filter data\nWHERE cp.SPECIES_CODE = 30060 \nAND cc.SURVEY_DEFINITION_ID = 98 \nAND cc.YEAR = 2021;\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1CPUE_KGHALATITUDELONGITUDEbody10.000000058.75863-174.9285body20.281353357.32545-173.3217body30.000000057.64161-172.7963body40.000000059.67831-172.5754body50.000000060.96936-174.8760body60.000000058.64012-173.5922\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n x = dat, # Pass data as a data frame\n region = \"bs.south\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n\n```{.r .cell-code}\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific Ocean perch\\nCPUE (kg/km2)\")) |> \n change_fill_color(new.scheme = \"grey\", show.plot = FALSE)\n```\n\n::: {.cell-output-display}\n![Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. ](akfin-oracle-sql-r_files/figure-docx/test-6-fig-1.png)\n:::\n:::\n\n\n\n\n### Ex. GOA Pacific Ocean perch biomass and abundance\n\nBiomass and abundance for Pacific Ocean perch from 1990 – 2023 for the western/central/eastern GOA management areas as well as for the entire region. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE in ('REGULATORY_AREA', 'REGION') \nAND SURVEY_DEFINITION_ID = 47)\n\n-- Select columns for output data\nSELECT \nBIOMASS_MT,\nPOPULATION_COUNT, \nYEAR, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SPECIES_CODE = 30060\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 1: GOA Pacific Ocean perch biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = description) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = gsub(x = area, pattern = \" - \", replacement = \"\\n\"), \n area = gsub(x = area, pattern = \": \", replacement = \"\\n\"), \n type = sapply(X = strsplit(x = area, split = \"\\n\", fixed = TRUE), `[[`, 2)) %>% \n dplyr::arrange(type) %>% \n dplyr::mutate(\n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\n\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1BIOMASS_MTPOPULATION_COUNTYEARDESCRIPTIONbody1483,622.6833,902,1611993GOA Region: All Stratabody2483,622.6833,902,1611993GOA Region: All Stratabody3771,412.81,252,616,6031996GOA Region: All Stratabody4771,412.81,252,616,6031996GOA Region: All Stratabody5727,063.51,212,034,9131999GOA Region: All Stratabody6727,063.51,212,034,9131999GOA Region: All Strata\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"scales\")\nlibrary(scales)\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(x = year, y = val, color = type)) +\n ggplot2::geom_point(size = 3) + \n ggplot2::facet_grid(cols = vars(area), rows = vars(var), scales = \"free_y\") + \n ggplot2::scale_x_continuous(name = \"Year\", n.breaks = 3) +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::labs(title = 'GOA Pacific Ocean perch biomass and abundance 1990 – 2023') + \n ggplot2::guides(color=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_color_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 1: GOA Pacific Ocean perch biomass and abundance. ](akfin-oracle-sql-r_files/figure-docx/test-1-plot-1.png)\n:::\n:::\n\n\n\n\n### Ex. AI rock sole size compositions and ridge plot\n\nNorthern and Southern rock sole size composition data from 1991 – 2022 for the Aleutian Islands, with Ridge plot from [`ggridges`](https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html).\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE = 'REGION' \nAND SURVEY_DEFINITION_ID = 52)\n\n-- Select columns for output data\nSELECT \nLENGTH_MM, \nYEAR\nFROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = SIZECOMP.AREA_ID\n\n-- Filter data results\nWHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52 \nAND SIZECOMP.SPECIES_CODE IN (10261, 10262)\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 2: AI Rock sole size compositions and ridge plot. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::mutate(length_cm = length_mm/10)\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1LENGTH_MMYEARbody11802014body21902014body32002014body42102014body52202014body62302014\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"ggridges\")\nlibrary(ggridges)\nfigure <- \n ggplot2::ggplot(\n data = dat0, \n mapping = aes(x = length_cm, y = as.factor(year), fill = stat(x))) +\n ggridges::theme_ridges(center_axis_labels = TRUE) + \n ggridges::geom_density_ridges_gradient(scale = 4, show.legend = FALSE) + \n ggplot2::scale_y_discrete(name = \"Year\", expand = c(0.01, 0)) +\n ggplot2::scale_x_continuous(name = \"Length (cm)\", expand = c(0.01, 0)) +\n # ggplot2::scale_fill_grey() +\n ggplot2::labs(title = 'AI Rock sole Size Compositions 1991 – 2022') \n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 2: AI Rock sole size compositions and ridge plot. ](akfin-oracle-sql-r_files/figure-docx/test-2-plot-1.png)\n:::\n:::\n\n\n\n\n### Ex. EBS Walleye Pollock Age Compositions and Age Pyramid\n\nWalleye pollock age composition for the EBS Standard Area from 1982 – 2022 and the EBS + NW Area from 1987 – 2022, with age pyramid plot. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE = 'REGION' AND \nSURVEY_DEFINITION_ID = 98)\n\n-- Select columns for output data\nSELECT \nAGECOMP.AGE, \nAGECOMP.POPULATION_COUNT, \nAGECOMP.SEX\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = AGECOMP.AREA_ID\n\n-- Filter data results\nWHERE SPECIES_CODE = 21740\nAND AGE >= 0\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::filter(sex %in% c(1,2)) %>%\n dplyr::mutate(\n sex = ifelse(sex == 1, \"M\", \"F\"),\n population_count = # change male population to negative\n ifelse(sex==\"M\", population_count*(-1), population_count*1)/1e9) \n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1AGEPOPULATION_COUNTSEXbody1939,3713body21032,1563body31115,2003body4129,9763body5131,9573body61131,950,3431\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n data = dat0, \n mapping = \n aes(x = age,\n y = population_count, \n fill = sex)) +\n ggplot2::scale_fill_grey() +\n ggplot2::geom_bar(stat = \"identity\") +\n ggplot2::coord_flip() +\n ggplot2::scale_x_continuous(name = \"Age\") +\n ggplot2::scale_y_continuous(name = \"Population (billions)\", labels = abs) +\n ggplot2::ggtitle(label = \"EBS Walleye Pollock Age Compositions 1982 – 2022\") + \n ggplot2::guides(fill = guide_legend(title = \"Sex\"))+\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. ](akfin-oracle-sql-r_files/figure-docx/test-3-plot-1.png)\n:::\n:::\n\n\n\n\n### Ex. NBS Pacific cod biomass and abundance\n\nPacific cod biomass and abundance data for the NBS by stratum. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nAREA_NAME, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE in ('STRATUM') AND \nSURVEY_DEFINITION_ID = 143) \n\n-- Select columns for output data\nSELECT \nBIOMASS.BIOMASS_MT, \nBIOMASS.POPULATION_COUNT, \nBIOMASS.YEAR, \nSTRATA.AREA_NAME\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS \nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SURVEY_DEFINITION_ID IN 143 \nAND BIOMASS.SPECIES_CODE = 21720\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 4: NBS Pacific cod biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = area_name) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1BIOMASS_MTPOPULATION_COUNTYEARAREA_NAMEbody195,849.98368,767,4982021Inner Domainbody2107,096.730102,734,1422019Inner Domainbody376,708.43339,605,8602023Inner Domainbody4132,490.15266,187,2452017Inner Domainbody596,500.69760,433,1352022Inner Domainbody67,462.5594,724,1532010Inner Domain\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(y = val, x = year, fill = area)) + \n ggplot2::geom_bar(position=\"stack\", stat=\"identity\") + \n ggplot2::facet_grid(rows = vars(var), scales = \"free_y\") +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::scale_x_continuous(name = \"Year\", breaks = unique(dat0$year)) +\n ggplot2::labs(title = 'NBS Pacific cod biomass and abundance by stratum') + \n ggplot2::guides(fill=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_fill_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 4: NBS Pacific cod biomass and abundance. ](akfin-oracle-sql-r_files/figure-docx/test-4-fig-1.png)\n:::\n:::\n\n\n\n\n### Ex. GOA Pacific Ocean perch biomass and line plot\n\nPacific Ocean perch biomass totals for GOA between 1984-2021 from `GAP_PRODUCTS.AKFIN_BIOMASS`\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \nSURVEY_DEFINITION_ID, \nBIOMASS_MT, \nBIOMASS_VAR, \nYEAR\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS\n\n-- Filter data results\nWHERE SPECIES_CODE = 30060 \nAND SURVEY_DEFINITION_ID = 47 \nAND AREA_ID = 99903 \nAND YEAR BETWEEN 1984 AND 2023;\") %>% \n janitor::clean_names() %>% \n dplyr::mutate(biomass_kmt = biomass_mt/1000, \n # **approximate** 95% confidence interval\n biomass_kci_up = (biomass_mt + (2*sqrt(biomass_var)))/1000, \n biomass_kci_dw = (biomass_mt - (2*sqrt(biomass_var)))/1000) \n```\n:::\n\n::: {.cell tbl-cap='Ex. 5: GOA Pacific Ocean perch biomass and line plot. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>%\n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1survey_definition_idbiomass_mtbiomass_varyearbiomass_kmtbiomass_kci_upbiomass_kci_dwbody147483,622.611,803,384,7871993483.6226700.9093266.33581body247771,412.841,434,152,2021996771.41281,178.5204364.30515body347727,063.5150,983,542,1781999727.06351,504.1955-50.06854body447673,155.149,285,342,9222001673.15511,117.1611229.14901body547457,421.65,186,126,5292003457.4216601.4511313.39204body647764,901.421,499,807,0102005764.90141,058.1577471.64517\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\na_mean <- dat %>% \n dplyr::group_by(survey_definition_id) %>% \n dplyr::summarise(biomass_kmt = mean(biomass_kmt, na.rm = TRUE), \n minyr = min(year, na.rm = TRUE), \n maxyr = max(year, na.rm = TRUE)) \n\nfigure <-\n ggplot(data = dat, \n mapping = aes(x = year, \n y = biomass_kmt)) +\n ggplot2::geom_point(size = 2.5, color = \"grey40\") + \n ggplot2::scale_x_continuous(\n name = \"Year\", \n labels = scales::label_number(\n accuracy = 1, \n big.mark = \"\")) +\n ggplot2::scale_y_continuous(\n name = \"Biomass (Kmt)\", \n labels = comma) +\n ggplot2::geom_segment(\n data = a_mean,\n mapping = aes(x = minyr, \n xend = maxyr, \n y = biomass_kmt, \n yend = biomass_kmt),\n linetype = \"dashed\", \n linewidth = 2) +\n ggplot2::geom_errorbar(\n mapping = aes(ymin = biomass_kci_dw, ymax = biomass_kci_up),\n position = position_dodge(.9),\n alpha = 0.5, width=.2) +\n ggplot2::ggtitle(\n label = \"GOA Pacific Ocean Perch Biomass 1984-2021\", \n subtitle = paste0(\"Mean = \", \n formatC(x = a_mean$biomass_kmt, \n digits = 2, \n big.mark = \",\", \n format = \"f\"), \n \" Kmt\")) +\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 5: GOA Pacific Ocean perch biomass and line plot. ](akfin-oracle-sql-r_files/figure-docx/test-5-fig-1.png)\n:::\n:::\n\n::: {.cell}\n\n:::\n",
+ "markdown": "---\ntitle: Access data\nnumber-sections: true\nnumber-depth: 3\n---\n\n\n\n\n\n\n## Access data via Oracle (AFSC only) {.unnumbered}\n\nAFSC `Oracle` users can access the database via `SQL developer` to view and pull the production data directly from the `GAP_PRODUCTS` `Oracle` schema. The user can also use `SQL developer` to view and pull the GAP Products data directly from the `GAP_PRODUCTS` `Oracle` schema. \n\n### Connect to Oracle from R\n\nMany users will want to access the data from `Oracle` using `R`. The user will need to install the `RODBC` `R` package and ask OFIS (IT) connect `R` to `Oracle`. Then, use the following code in `R` to establish a connection from `R` to `Oracle`: \n\nHere, the user can establish the oracle connection by entering their username and password in the `channel <- gapindex::oracle_connect()` function. Never save usernames or passwords in scripts that may be intentionally or unintentionally shared with others. If no username and password is entered in the function, pop-ups will appear on the screen asking for the username and password. \n\nAfter you connect to VPN, you'll be able to log into Oracle. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(RODBC)\nchannel <- gapindex::get_connected()\n```\n:::\n\n\n\n\n## Data SQL Query Examples: {.unnumbered}\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(gapindex)\nlibrary(RODBC)\nlibrary(flextable)\nlibrary(ggplot2)\nlibrary(magrittr)\nlibrary(dplyr)\n```\n:::\n\n\n\n\n### Ex. Select all data from tables\n\nYou can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the `R` environment. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlocations <- c(\n \"GAP_PRODUCTS.AKFIN_AGECOMP\", \n \"GAP_PRODUCTS.AKFIN_AREA\", \n \"GAP_PRODUCTS.AKFIN_BIOMASS\", \n \"GAP_PRODUCTS.AKFIN_CATCH\", \n \"GAP_PRODUCTS.AKFIN_CPUE\", \n \"GAP_PRODUCTS.AKFIN_CRUISE\", \n \"GAP_PRODUCTS.AKFIN_HAUL\", \n \"GAP_PRODUCTS.AKFIN_LENGTH\", \n \"GAP_PRODUCTS.AKFIN_METADATA_COLUMN\", \n \"GAP_PRODUCTS.AKFIN_SIZECOMP\", \n \"GAP_PRODUCTS.AKFIN_SPECIMEN\", \n \"GAP_PRODUCTS.AKFIN_STRATUM_GROUPS\", \n \"GAP_PRODUCTS.AKFIN_SURVEY_DESIGN\", \n \"GAP_PRODUCTS.AKFIN_TAXONOMIC_CLASSIFICATION\"\n)\n\nfor (i in 1:length(locations)) {\n print(locations[i])\n a <- RODBC::sqlQuery(channel, paste0(\"SELECT * FROM \", locations[i]))\n write.csv(x = a, file = here::here(\"data\", paste0(locations[i], \".csv\")))\n}\n```\n:::\n\n\n\n\n### Ex. CPUE for all EBS and NBS stations with associated haul, cruise, and species information.\n\n\n\n\n::: {.cell tbl-cap='Ex.: CPUE for all EBS and NBS stations with associated haul, cruise, and species information. '}\n\n```{.r .cell-code}\na <- RODBC::sqlQuery(channel = channel, # NOT RACEBASE.HAUL\n query = paste0(\n\"\n-- Select columns for output data\nSELECT\ncr.CRUISEJOIN,\ncr.CRUISE,\ncr.YEAR,\ncr.SURVEY_DEFINITION_ID,\ncr.SURVEY_NAME,\ncr.VESSEL_ID,\ncr.VESSEL_NAME,\ncp.HAULJOIN,\ncp.SPECIES_CODE,\ntt.SPECIES_NAME,\ntt.COMMON_NAME,\ncp.WEIGHT_KG,\ncp.COUNT,\ncp.AREA_SWEPT_KM2,\ncp.CPUE_KGKM2,\ncp.CPUE_NOKM2,\nhh.HAUL,\nhh.STATION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_HAUL hh\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cr\nON hh.CRUISEJOIN = cr.CRUISEJOIN\nLEFT JOIN GAP_PRODUCTS.AKFIN_CPUE cp\nON hh.HAULJOIN = cp.HAULJOIN\nLEFT JOIN GAP_PRODUCTS.TAXONOMIC_CLASSIFICATION tt\nON cp.SPECIES_CODE = tt.SPECIES_CODE\n\n-- Filter for EBS and NBS observations\nWHERE SURVEY_DEFINITION_ID IN (143, 98) -- 143 NBS, 98 EBS\nAND tt.SURVEY_SPECIES = 1\n\n-- Only return the first 3 rows because otherwise this would be a huge table!\nFETCH FIRST 3 ROWS ONLY;\")) \n\nflextable::flextable(head(a)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1CRUISEJOINCRUISEYEARSURVEY_DEFINITION_IDSURVEY_NAMEVESSEL_IDVESSEL_NAMEHAULJOINSPECIES_CODESPECIES_NAMECOMMON_NAMEWEIGHT_KGCOUNTAREA_SWEPT_KM2CPUE_KGKM2CPUE_NOKM2HAULSTATIONbody180198,2031,98298Eastern Bering Sea Crab/Groundfish Bottom Trawl Survey1CHAPMAN8771fish egg unid.000.0420210021G-10body280198,2031,98298Eastern Bering Sea Crab/Groundfish Bottom Trawl Survey1CHAPMAN8772fish larvae unid.000.0420210021G-10body380198,2031,98298Eastern Bering Sea Crab/Groundfish Bottom Trawl Survey1CHAPMAN8773fish unid.000.0420210021G-10\n``````\n:::\n:::\n\n\n\n\n### Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel,\n query =\n\"\n-- Select columns for output data\nSELECT \nHAULJOIN, \nSPECIES_CODE, \nSTRATUM, \nLATITUDE_DD_START, \nLONGITUDE_DD_START,\nCPUE_KGKM2, \nGEAR_TEMPERATURE_C\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_CPUE cpue\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL haul\nUSING (HAULJOIN) \n\n-- Filter for P. Cod observations\nWHERE SPECIES_CODE IN (21720)\n\n-- Select all stratum within the area_id 919 (INPFC Shumagin region)\nAND haul.STRATUM IN\n(\nSELECT \nSTRATUM\nFROM GAP_PRODUCTS.AKFIN_STRATUM_GROUPS \nWHERE AREA_ID = 919\n);\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 8: CPUE for all stations contained in the Shumagin region (AREA_ID = 919). '}\n\n```{.r .cell-code}\ndat <- dat %>% \n dplyr::select(HAULJOIN, STRATUM, SPECIES_CODE, LATITUDE_DD_START, LONGITUDE_DD_START, CPUE_KGKM2, GEAR_TEMPERATURE_C) %>% \n dplyr::mutate(SPECIES_CODE = as.character(SPECIES_CODE), \n STRATUM = as.character(STRATUM)) %>% \n dplyr::arrange(SPECIES_CODE)\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1HAULJOINSTRATUMSPECIES_CODELATITUDE_DD_STARTLONGITUDE_DD_STARTCPUE_KGKM2GEAR_TEMPERATURE_Cbody1-22,270132172055.11515-159.3512209.289944.3body2-22,250132172055.05143-159.96798,700.920175.1body3-22,238132172055.11365-159.4264363.173254.4body4-22,214132172054.78608-160.000863.715064.6body5-22,2021112172054.48341-159.7261618.721204.7body6-22,2471122172055.59093-160.0740114.730424.0\n``````\n:::\n:::\n\n\n\n\n### Ex. EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map \n\nPacific Ocean perch catch-per-unit-effort estimates for EBS in 2021 from `GAP_PRODUCTS.AKFIN_CPUE` and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). Here, we'll use AKFIN HAUL and CRUISES data also included in this repo, for convenience, though they are very similar to their `RACEBASE` analogs. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \n(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares\nhh.LATITUDE_DD_START LATITUDE,\nhh.LONGITUDE_DD_START LONGITUDE\n\n-- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin\nFROM GAP_PRODUCTS.AKFIN_CPUE cp\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh\nON cp.HAULJOIN = hh.HAULJOIN\n\n-- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc\nON hh.CRUISEJOIN = cc.CRUISEJOIN\n\n-- Filter data\nWHERE cp.SPECIES_CODE = 30060 \nAND cc.SURVEY_DEFINITION_ID = 98 \nAND cc.YEAR = 2021;\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1CPUE_KGHALATITUDELONGITUDEbody10.0000000060.67043-178.0946body20.0000000060.31361-176.0138body30.0000000060.35098-175.3850body40.0000000060.99712-177.6638body50.0000000060.96495-176.2634body60.0241637958.97844-175.7204\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n x = dat, # Pass data as a data frame\n region = \"bs.south\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n\n```{.r .cell-code}\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific Ocean perch\\nCPUE (kg/km2)\")) |> \n change_fill_color(new.scheme = \"grey\", show.plot = FALSE)\n```\n\n::: {.cell-output-display}\n![Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. ](akfin-oracle-sql-r_files/figure-docx/test-6-fig-1.png)\n:::\n:::\n\n\n\n\n### Ex. GOA Pacific Ocean perch biomass and abundance\n\nBiomass and abundance for Pacific Ocean perch from 1990 – 2023 for the western/central/eastern GOA management areas as well as for the entire region. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE in ('REGULATORY_AREA', 'REGION') \nAND SURVEY_DEFINITION_ID = 47)\n\n-- Select columns for output data\nSELECT \nBIOMASS_MT,\nPOPULATION_COUNT, \nYEAR, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SPECIES_CODE = 30060\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 1: GOA Pacific Ocean perch biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = description) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = gsub(x = area, pattern = \" - \", replacement = \"\\n\"), \n area = gsub(x = area, pattern = \": \", replacement = \"\\n\"), \n type = sapply(X = strsplit(x = area, split = \"\\n\", fixed = TRUE), `[[`, 2)) %>% \n dplyr::arrange(type) %>% \n dplyr::mutate(\n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\n\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1BIOMASS_MTPOPULATION_COUNTYEARDESCRIPTIONbody1157,295.1317,129,4081990GOA Region: All Stratabody2157,295.1317,129,4081990GOA Region: All Stratabody3483,622.6833,902,1611993GOA Region: All Stratabody4483,622.6833,902,1611993GOA Region: All Stratabody5771,412.81,252,616,6031996GOA Region: All Stratabody6771,412.81,252,616,6031996GOA Region: All Strata\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"scales\")\nlibrary(scales)\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(x = year, y = val, color = type)) +\n ggplot2::geom_point(size = 3) + \n ggplot2::facet_grid(cols = vars(area), rows = vars(var), scales = \"free_y\") + \n ggplot2::scale_x_continuous(name = \"Year\", n.breaks = 3) +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::labs(title = 'GOA Pacific Ocean perch biomass and abundance 1990 – 2023') + \n ggplot2::guides(color=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_color_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 1: GOA Pacific Ocean perch biomass and abundance. ](akfin-oracle-sql-r_files/figure-docx/test-1-plot-1.png)\n:::\n:::\n\n\n\n\n### Ex. AI rock sole size compositions and ridge plot\n\nNorthern and Southern rock sole size composition data from 1991 – 2022 for the Aleutian Islands, with Ridge plot from [`ggridges`](https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html).\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE = 'REGION' \nAND SURVEY_DEFINITION_ID = 52)\n\n-- Select columns for output data\nSELECT \nLENGTH_MM, \nYEAR\nFROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = SIZECOMP.AREA_ID\n\n-- Filter data results\nWHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52 \nAND SIZECOMP.SPECIES_CODE IN (10261, 10262)\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 2: AI Rock sole size compositions and ridge plot. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::mutate(length_cm = length_mm/10) %>% \n head() %>% \n flextable::flextable() %>% \n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\ndat0\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1length_mmyearlength_cmbody1110199711body2130199713body3140199714body4150199715body5160199716body6170199717\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"ggridges\")\nlibrary(ggridges)\nfigure <- \n ggplot2::ggplot(\n data = dat, \n mapping = aes(x = LENGTH_MM, y = as.factor(YEAR), fill = stat(x))) +\n ggridges::theme_ridges(center_axis_labels = TRUE) + \n ggridges::geom_density_ridges_gradient(scale = 4, show.legend = FALSE) + \n ggplot2::scale_y_discrete(name = \"Year\", expand = c(0.01, 0)) +\n ggplot2::scale_x_continuous(name = \"Length (cm)\", expand = c(0.01, 0)) +\n # ggplot2::scale_fill_grey() +\n ggplot2::labs(title = 'AI Rock sole Size Compositions 1991 – 2022') \n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 2: AI Rock sole size compositions and ridge plot. ](akfin-oracle-sql-r_files/figure-docx/test-2-plot-1.png)\n:::\n:::\n\n\n\n\n### Ex. EBS Walleye Pollock Age Compositions and Age Pyramid\n\nWalleye pollock age composition for the EBS Standard Area from 1982 – 2022 and the EBS + NW Area from 1987 – 2022, with age pyramid plot. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE = 'REGION' AND \nSURVEY_DEFINITION_ID = 98)\n\n-- Select columns for output data\nSELECT \nAGECOMP.AGE, \nAGECOMP.POPULATION_COUNT, \nAGECOMP.SEX\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = AGECOMP.AREA_ID\n\n-- Filter data results\nWHERE SPECIES_CODE = 21740\nAND AGE >= 0\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::filter(sex %in% c(1,2)) %>%\n dplyr::mutate(\n sex = ifelse(sex == 1, \"M\", \"F\"),\n population_count = # change male population to negative\n ifelse(sex==\"M\", population_count*(-1), population_count*1)/1e9) \n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1AGEPOPULATION_COUNTSEXbody11148,791,4512body212120,673,5802body31342,580,0542body41447,229,3782body51525,140,5232body61619,473,2552\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n data = dat0, \n mapping = \n aes(x = age,\n y = population_count, \n fill = sex)) +\n ggplot2::scale_fill_grey() +\n ggplot2::geom_bar(stat = \"identity\") +\n ggplot2::coord_flip() +\n ggplot2::scale_x_continuous(name = \"Age\") +\n ggplot2::scale_y_continuous(name = \"Population (billions)\", labels = abs) +\n ggplot2::ggtitle(label = \"EBS Walleye Pollock Age Compositions 1982 – 2022\") + \n ggplot2::guides(fill = guide_legend(title = \"Sex\"))+\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. ](akfin-oracle-sql-r_files/figure-docx/test-3-plot-1.png)\n:::\n:::\n\n\n\n\n### Ex. NBS Pacific cod biomass and abundance\n\nPacific cod biomass and abundance data for the NBS by stratum. \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nAREA_NAME, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE in ('STRATUM') AND \nSURVEY_DEFINITION_ID = 143) \n\n-- Select columns for output data\nSELECT \nBIOMASS.BIOMASS_MT, \nBIOMASS.POPULATION_COUNT, \nBIOMASS.YEAR, \nSTRATA.AREA_NAME\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS \nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SURVEY_DEFINITION_ID IN 143 \nAND BIOMASS.SPECIES_CODE = 21720\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 4: NBS Pacific cod biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = area_name) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1BIOMASS_MTPOPULATION_COUNTYEARAREA_NAMEbody17,462.5594,724,1532010Inner Domainbody295,849.98368,767,4982021Inner Domainbody3107,096.730102,734,1422019Inner Domainbody476,708.43339,605,8602023Inner Domainbody5132,490.15266,187,2452017Inner Domainbody696,500.69760,433,1352022Inner Domain\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(y = val, x = year, fill = area)) + \n ggplot2::geom_bar(position=\"stack\", stat=\"identity\") + \n ggplot2::facet_grid(rows = vars(var), scales = \"free_y\") +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::scale_x_continuous(name = \"Year\", breaks = unique(dat0$year)) +\n ggplot2::labs(title = 'NBS Pacific cod biomass and abundance by stratum') + \n ggplot2::guides(fill=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_fill_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 4: NBS Pacific cod biomass and abundance. ](akfin-oracle-sql-r_files/figure-docx/test-4-fig-1.png)\n:::\n:::\n\n\n\n\n### Ex. GOA Pacific Ocean perch biomass and line plot\n\nPacific Ocean perch biomass totals for GOA between 1984-2021 from `GAP_PRODUCTS.AKFIN_BIOMASS`\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \nSURVEY_DEFINITION_ID, \nBIOMASS_MT, \nBIOMASS_VAR, \nYEAR\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS\n\n-- Filter data results\nWHERE SPECIES_CODE = 30060 \nAND SURVEY_DEFINITION_ID = 47 \nAND AREA_ID = 99903 \nAND YEAR BETWEEN 1984 AND 2023;\") %>% \n janitor::clean_names() %>% \n dplyr::mutate(biomass_kmt = biomass_mt/1000, \n # **approximate** 95% confidence interval\n biomass_kci_up = (biomass_mt + (2*sqrt(biomass_var)))/1000, \n biomass_kci_dw = (biomass_mt - (2*sqrt(biomass_var)))/1000) \n```\n:::\n\n::: {.cell tbl-cap='Ex. 5: GOA Pacific Ocean perch biomass and line plot. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>%\n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1survey_definition_idbiomass_mtbiomass_varyearbiomass_kmtbiomass_kci_upbiomass_kci_dwbody147157,295.12,221,176,9681990157.2951251.553863.03638body247483,622.611,803,384,7871993483.6226700.9093266.33581body347771,412.841,434,152,2021996771.41281,178.5204364.30515body447727,063.5150,983,542,1781999727.06351,504.1955-50.06854body547673,155.149,285,342,9222001673.15511,117.1611229.14901body647457,421.65,186,126,5292003457.4216601.4511313.39204\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\na_mean <- dat %>% \n dplyr::group_by(survey_definition_id) %>% \n dplyr::summarise(biomass_kmt = mean(biomass_kmt, na.rm = TRUE), \n minyr = min(year, na.rm = TRUE), \n maxyr = max(year, na.rm = TRUE)) \n\nfigure <-\n ggplot(data = dat, \n mapping = aes(x = year, \n y = biomass_kmt)) +\n ggplot2::geom_point(size = 2.5, color = \"grey40\") + \n ggplot2::scale_x_continuous(\n name = \"Year\", \n labels = scales::label_number(\n accuracy = 1, \n big.mark = \"\")) +\n ggplot2::scale_y_continuous(\n name = \"Biomass (Kmt)\", \n labels = comma) +\n ggplot2::geom_segment(\n data = a_mean,\n mapping = aes(x = minyr, \n xend = maxyr, \n y = biomass_kmt, \n yend = biomass_kmt),\n linetype = \"dashed\", \n linewidth = 2) +\n ggplot2::geom_errorbar(\n mapping = aes(ymin = biomass_kci_dw, ymax = biomass_kci_up),\n position = position_dodge(.9),\n alpha = 0.5, width=.2) +\n ggplot2::ggtitle(\n label = \"GOA Pacific Ocean Perch Biomass 1984-2021\", \n subtitle = paste0(\"Mean = \", \n formatC(x = a_mean$biomass_kmt, \n digits = 2, \n big.mark = \",\", \n format = \"f\"), \n \" Kmt\")) +\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 5: GOA Pacific Ocean perch biomass and line plot. ](akfin-oracle-sql-r_files/figure-docx/test-5-fig-1.png)\n:::\n:::\n\n::: {.cell}\n\n:::\n",
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"akfin-oracle-sql-r_files\\figure-docx"
],
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- "hash": "6ca4dec388d9bb5ed42dd65c29ee5da6",
+ "hash": "e95dda4032f9d6c0c84201c12b9852cc",
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- "markdown": "---\ntitle: Access data\nnumber-sections: true\nnumber-depth: 3\n---\n\n\n\n\n## Access data via Oracle (AFSC only) {.unnumbered}\n\nAFSC `Oracle` users can access the database via `SQL developer` to view and pull the production data directly from the `GAP_PRODUCTS` `Oracle` schema. The user can also use `SQL developer` to view and pull the GAP Products data directly from the `GAP_PRODUCTS` `Oracle` schema. \n\n### Connect to Oracle from R\n\nMany users will want to access the data from `Oracle` using `R`. The user will need to install the `RODBC` `R` package and ask OFIS (IT) connect `R` to `Oracle`. Then, use the following code in `R` to establish a connection from `R` to `Oracle`: \n\nHere, the user can establish the oracle connection by entering their username and password in the `channel <- gapindex::oracle_connect()` function. Never save usernames or passwords in scripts that may be intentionally or unintentionally shared with others. If no username and password is entered in the function, pop-ups will appear on the screen asking for the username and password. \n\nAfter you connect to VPN, you'll be able to log into Oracle. \n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(RODBC)\nchannel <- gapindex::get_connected()\n```\n:::\n\n\n## Data SQL Query Examples: {.unnumbered}\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(gapindex)\nlibrary(RODBC)\nlibrary(flextable)\nlibrary(ggplot2)\nlibrary(magrittr)\nlibrary(dplyr)\n```\n:::\n\n\n### Ex. Select all data from a table\n\nYou can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the `R` environment. \n\n\n::: {.cell}\n\n```{.r .cell-code}\nlocations <- c(\n \"GAP_PRODUCTS.AKFIN_AGECOMP\", \n \"GAP_PRODUCTS.AKFIN_AREA\", \n \"GAP_PRODUCTS.AKFIN_BIOMASS\", \n \"GAP_PRODUCTS.AKFIN_CATCH\", \n \"GAP_PRODUCTS.AKFIN_CPUE\", \n \"GAP_PRODUCTS.AKFIN_CRUISE\", \n \"GAP_PRODUCTS.AKFIN_HAUL\", \n \"GAP_PRODUCTS.AKFIN_LENGTH\", \n \"GAP_PRODUCTS.AKFIN_METADATA_COLUMN\", \n \"GAP_PRODUCTS.AKFIN_SIZECOMP\", \n \"GAP_PRODUCTS.AKFIN_SPECIMEN\", \n \"GAP_PRODUCTS.AKFIN_STRATUM_GROUPS\", \n \"GAP_PRODUCTS.AKFIN_SURVEY_DESIGN\", \n \"GAP_PRODUCTS.AKFIN_TAXONOMIC_CLASSIFICATION\"\n)\n\nfor (i in 1:length(locations)) {\n print(locations[i])\n a <- RODBC::sqlQuery(channel, paste0(\"SELECT * FROM \", locations[i]))\n write.csv(x = a, file = here::here(\"data\", paste0(locations[i], \".csv\")))\n}\n```\n:::\n\n::: {.cell}\n\n:::\n\n::: {.cell}\n\n:::\n\n::: {.cell tbl-cap='Ex. 7: Summary table of Number hauls where species were observed (N_HAULS) and number of length measurements that were colelcted for this species (N_LENGTHS) for EBS and NBS, for arrowtooth flounder (10110), Bering flounder (10140), and Alaska skate (435). '}\n\n:::\n\n\n### Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel,\n query =\n\"\n-- Select columns for output data\nSELECT \nHAULJOIN, \nSPECIES_CODE, \nSTRATUM, \nLATITUDE_DD_START, \nLONGITUDE_DD_START,\nCPUE_KGKM2, \nGEAR_TEMPERATURE_C\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_CPUE cpue\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL haul\nUSING (HAULJOIN) \n\n-- Filter for P. Cod observations\nWHERE SPECIES_CODE IN (21720)\n\n-- Select all stratum within the area_id 919 (INPFC Shumagin region)\nAND haul.STRATUM IN\n(\nSELECT \nSTRATUM\nFROM GAP_PRODUCTS.AKFIN_STRATUM_GROUPS \nWHERE AREA_ID = 919\n);\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 8: CPUE for all stations contained in the Shumagin region (AREA_ID = 919). '}\n\n```{.r .cell-code}\ndat <- dat %>% \n dplyr::select(HAULJOIN, STRATUM, SPECIES_CODE, LATITUDE_DD_START, LONGITUDE_DD_START, CPUE_KGKM2, GEAR_TEMPERATURE_C) %>% \n dplyr::mutate(SPECIES_CODE = as.character(SPECIES_CODE), \n STRATUM = as.character(STRATUM)) %>% \n dplyr::arrange(SPECIES_CODE)\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=html}\n
HAULJOIN
STRATUM
SPECIES_CODE
LATITUDE_DD_START
LONGITUDE_DD_START
CPUE_KGKM2
GEAR_TEMPERATURE_C
-22,239
12
21720
55.43748
-160.1269
717.63085
4.5
-22,215
13
21720
54.58732
-161.1945
76.90763
4.3
-22,168
11
21720
54.45823
-163.0872
2,004.49628
4.9
-22,204
110
21720
54.51804
-160.7493
0.00000
4.7
-22,188
210
21720
54.38733
-159.6986
0.00000
5.5
-22,183
210
21720
54.09314
-161.6996
0.00000
5.3
\n```\n:::\n:::\n\n\n### Ex. EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map \n\nPacific Ocean perch catch-per-unit-effort estimates for EBS in 2021 from `GAP_PRODUCTS.AKFIN_CPUE` and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). Here, we'll use AKFIN HAUL and CRUISES data also included in this repo, for convenience, though they are very similar to their `RACEBASE` analogs. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \n(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares\nhh.LATITUDE_DD_START LATITUDE,\nhh.LONGITUDE_DD_START LONGITUDE\n\n-- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin\nFROM GAP_PRODUCTS.AKFIN_CPUE cp\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh\nON cp.HAULJOIN = hh.HAULJOIN\n\n-- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc\nON hh.CRUISEJOIN = cc.CRUISEJOIN\n\n-- Filter data\nWHERE cp.SPECIES_CODE = 30060 \nAND cc.SURVEY_DEFINITION_ID = 98 \nAND cc.YEAR = 2021;\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=html}\n
CPUE_KGHA
LATITUDE
LONGITUDE
0.0000000
58.75863
-174.9285
0.2813533
57.32545
-173.3217
0.0000000
57.64161
-172.7963
0.0000000
59.67831
-172.5754
0.0000000
60.96936
-174.8760
0.0000000
58.64012
-173.5922
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n x = dat, # Pass data as a data frame\n region = \"bs.south\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n\n```{.r .cell-code}\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific Ocean perch\\nCPUE (kg/km2)\")) |> \n change_fill_color(new.scheme = \"grey\", show.plot = FALSE)\n```\n\n::: {.cell-output-display}\n![Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. ](akfin-oracle-sql-r_files/figure-html/test-6-fig-1.png){width=672}\n:::\n:::\n\n\n### Ex. GOA Pacific Ocean perch biomass and abundance\n\nBiomass and abundance for Pacific Ocean perch from 1990 – 2023 for the western/central/eastern GOA management areas as well as for the entire region. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE in ('REGULATORY_AREA', 'REGION') \nAND SURVEY_DEFINITION_ID = 47)\n\n-- Select columns for output data\nSELECT \nBIOMASS_MT,\nPOPULATION_COUNT, \nYEAR, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SPECIES_CODE = 30060\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 1: GOA Pacific Ocean perch biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = description) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = gsub(x = area, pattern = \" - \", replacement = \"\\n\"), \n area = gsub(x = area, pattern = \": \", replacement = \"\\n\"), \n type = sapply(X = strsplit(x = area, split = \"\\n\", fixed = TRUE), `[[`, 2)) %>% \n dplyr::arrange(type) %>% \n dplyr::mutate(\n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\n\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=html}\n
BIOMASS_MT
POPULATION_COUNT
YEAR
DESCRIPTION
483,622.6
833,902,161
1993
GOA Region: All Strata
483,622.6
833,902,161
1993
GOA Region: All Strata
771,412.8
1,252,616,603
1996
GOA Region: All Strata
771,412.8
1,252,616,603
1996
GOA Region: All Strata
727,063.5
1,212,034,913
1999
GOA Region: All Strata
727,063.5
1,212,034,913
1999
GOA Region: All Strata
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"scales\")\nlibrary(scales)\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(x = year, y = val, color = type)) +\n ggplot2::geom_point(size = 3) + \n ggplot2::facet_grid(cols = vars(area), rows = vars(var), scales = \"free_y\") + \n ggplot2::scale_x_continuous(name = \"Year\", n.breaks = 3) +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::labs(title = 'GOA Pacific Ocean perch biomass and abundance 1990 – 2023') + \n ggplot2::guides(color=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_color_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 1: GOA Pacific Ocean perch biomass and abundance. ](akfin-oracle-sql-r_files/figure-html/test-1-plot-1.png){width=672}\n:::\n:::\n\n\n### Ex. AI rock sole size compositions and ridge plot\n\nNorthern and Southern rock sole size composition data from 1991 – 2022 for the Aleutian Islands, with Ridge plot from [`ggridges`](https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html).\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE = 'REGION' \nAND SURVEY_DEFINITION_ID = 52)\n\n-- Select columns for output data\nSELECT \nLENGTH_MM, \nYEAR\nFROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = SIZECOMP.AREA_ID\n\n-- Filter data results\nWHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52 \nAND SIZECOMP.SPECIES_CODE IN (10261, 10262)\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 2: AI Rock sole size compositions and ridge plot. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::mutate(length_cm = length_mm/10)\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=html}\n
LENGTH_MM
YEAR
180
2014
190
2014
200
2014
210
2014
220
2014
230
2014
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"ggridges\")\nlibrary(ggridges)\nfigure <- \n ggplot2::ggplot(\n data = dat0, \n mapping = aes(x = length_cm, y = as.factor(year), fill = stat(x))) +\n ggridges::theme_ridges(center_axis_labels = TRUE) + \n ggridges::geom_density_ridges_gradient(scale = 4, show.legend = FALSE) + \n ggplot2::scale_y_discrete(name = \"Year\", expand = c(0.01, 0)) +\n ggplot2::scale_x_continuous(name = \"Length (cm)\", expand = c(0.01, 0)) +\n # ggplot2::scale_fill_grey() +\n ggplot2::labs(title = 'AI Rock sole Size Compositions 1991 – 2022') \n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 2: AI Rock sole size compositions and ridge plot. ](akfin-oracle-sql-r_files/figure-html/test-2-plot-1.png){width=672}\n:::\n:::\n\n\n### Ex. EBS Walleye Pollock Age Compositions and Age Pyramid\n\nWalleye pollock age composition for the EBS Standard Area from 1982 – 2022 and the EBS + NW Area from 1987 – 2022, with age pyramid plot. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE = 'REGION' AND \nSURVEY_DEFINITION_ID = 98)\n\n-- Select columns for output data\nSELECT \nAGECOMP.AGE, \nAGECOMP.POPULATION_COUNT, \nAGECOMP.SEX\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = AGECOMP.AREA_ID\n\n-- Filter data results\nWHERE SPECIES_CODE = 21740\nAND AGE >= 0\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::filter(sex %in% c(1,2)) %>%\n dplyr::mutate(\n sex = ifelse(sex == 1, \"M\", \"F\"),\n population_count = # change male population to negative\n ifelse(sex==\"M\", population_count*(-1), population_count*1)/1e9) \n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=html}\n
AGE
POPULATION_COUNT
SEX
9
39,371
3
10
32,156
3
11
15,200
3
12
9,976
3
13
1,957
3
1
131,950,343
1
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n data = dat0, \n mapping = \n aes(x = age,\n y = population_count, \n fill = sex)) +\n ggplot2::scale_fill_grey() +\n ggplot2::geom_bar(stat = \"identity\") +\n ggplot2::coord_flip() +\n ggplot2::scale_x_continuous(name = \"Age\") +\n ggplot2::scale_y_continuous(name = \"Population (billions)\", labels = abs) +\n ggplot2::ggtitle(label = \"EBS Walleye Pollock Age Compositions 1982 – 2022\") + \n ggplot2::guides(fill = guide_legend(title = \"Sex\"))+\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. ](akfin-oracle-sql-r_files/figure-html/test-3-plot-1.png){width=672}\n:::\n:::\n\n\n### Ex. NBS Pacific cod biomass and abundance\n\nPacific cod biomass and abundance data for the NBS by stratum. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nAREA_NAME, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE in ('STRATUM') AND \nSURVEY_DEFINITION_ID = 143) \n\n-- Select columns for output data\nSELECT \nBIOMASS.BIOMASS_MT, \nBIOMASS.POPULATION_COUNT, \nBIOMASS.YEAR, \nSTRATA.AREA_NAME\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS \nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SURVEY_DEFINITION_ID IN 143 \nAND BIOMASS.SPECIES_CODE = 21720\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 4: NBS Pacific cod biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = area_name) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=html}\n
BIOMASS_MT
POPULATION_COUNT
YEAR
AREA_NAME
95,849.983
68,767,498
2021
Inner Domain
107,096.730
102,734,142
2019
Inner Domain
76,708.433
39,605,860
2023
Inner Domain
132,490.152
66,187,245
2017
Inner Domain
96,500.697
60,433,135
2022
Inner Domain
7,462.559
4,724,153
2010
Inner Domain
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(y = val, x = year, fill = area)) + \n ggplot2::geom_bar(position=\"stack\", stat=\"identity\") + \n ggplot2::facet_grid(rows = vars(var), scales = \"free_y\") +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::scale_x_continuous(name = \"Year\", breaks = unique(dat0$year)) +\n ggplot2::labs(title = 'NBS Pacific cod biomass and abundance by stratum') + \n ggplot2::guides(fill=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_fill_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 4: NBS Pacific cod biomass and abundance. ](akfin-oracle-sql-r_files/figure-html/test-4-fig-1.png){width=672}\n:::\n:::\n\n\n### Ex. GOA Pacific Ocean perch biomass and line plot\n\nPacific Ocean perch biomass totals for GOA between 1984-2021 from `GAP_PRODUCTS.AKFIN_BIOMASS`\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \nSURVEY_DEFINITION_ID, \nBIOMASS_MT, \nBIOMASS_VAR, \nYEAR\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS\n\n-- Filter data results\nWHERE SPECIES_CODE = 30060 \nAND SURVEY_DEFINITION_ID = 47 \nAND AREA_ID = 99903 \nAND YEAR BETWEEN 1984 AND 2023;\") %>% \n janitor::clean_names() %>% \n dplyr::mutate(biomass_kmt = biomass_mt/1000, \n # **approximate** 95% confidence interval\n biomass_kci_up = (biomass_mt + (2*sqrt(biomass_var)))/1000, \n biomass_kci_dw = (biomass_mt - (2*sqrt(biomass_var)))/1000) \n```\n:::\n\n::: {.cell tbl-cap='Ex. 5: GOA Pacific Ocean perch biomass and line plot. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>%\n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=html}\n
survey_definition_id
biomass_mt
biomass_var
year
biomass_kmt
biomass_kci_up
biomass_kci_dw
47
483,622.6
11,803,384,787
1993
483.6226
700.9093
266.33581
47
771,412.8
41,434,152,202
1996
771.4128
1,178.5204
364.30515
47
727,063.5
150,983,542,178
1999
727.0635
1,504.1955
-50.06854
47
673,155.1
49,285,342,922
2001
673.1551
1,117.1611
229.14901
47
457,421.6
5,186,126,529
2003
457.4216
601.4511
313.39204
47
764,901.4
21,499,807,010
2005
764.9014
1,058.1577
471.64517
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\na_mean <- dat %>% \n dplyr::group_by(survey_definition_id) %>% \n dplyr::summarise(biomass_kmt = mean(biomass_kmt, na.rm = TRUE), \n minyr = min(year, na.rm = TRUE), \n maxyr = max(year, na.rm = TRUE)) \n\nfigure <-\n ggplot(data = dat, \n mapping = aes(x = year, \n y = biomass_kmt)) +\n ggplot2::geom_point(size = 2.5, color = \"grey40\") + \n ggplot2::scale_x_continuous(\n name = \"Year\", \n labels = scales::label_number(\n accuracy = 1, \n big.mark = \"\")) +\n ggplot2::scale_y_continuous(\n name = \"Biomass (Kmt)\", \n labels = comma) +\n ggplot2::geom_segment(\n data = a_mean,\n mapping = aes(x = minyr, \n xend = maxyr, \n y = biomass_kmt, \n yend = biomass_kmt),\n linetype = \"dashed\", \n linewidth = 2) +\n ggplot2::geom_errorbar(\n mapping = aes(ymin = biomass_kci_dw, ymax = biomass_kci_up),\n position = position_dodge(.9),\n alpha = 0.5, width=.2) +\n ggplot2::ggtitle(\n label = \"GOA Pacific Ocean Perch Biomass 1984-2021\", \n subtitle = paste0(\"Mean = \", \n formatC(x = a_mean$biomass_kmt, \n digits = 2, \n big.mark = \",\", \n format = \"f\"), \n \" Kmt\")) +\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 5: GOA Pacific Ocean perch biomass and line plot. ](akfin-oracle-sql-r_files/figure-html/test-5-fig-1.png){width=672}\n:::\n:::\n\n::: {.cell}\n\n:::\n",
+ "markdown": "---\ntitle: Access data\nnumber-sections: true\nnumber-depth: 3\n---\n\n\n\n\n## Access data via Oracle (AFSC only) {.unnumbered}\n\nAFSC `Oracle` users can access the database via `SQL developer` to view and pull the production data directly from the `GAP_PRODUCTS` `Oracle` schema. The user can also use `SQL developer` to view and pull the GAP Products data directly from the `GAP_PRODUCTS` `Oracle` schema. \n\n### Connect to Oracle from R\n\nMany users will want to access the data from `Oracle` using `R`. The user will need to install the `RODBC` `R` package and ask OFIS (IT) connect `R` to `Oracle`. Then, use the following code in `R` to establish a connection from `R` to `Oracle`: \n\nHere, the user can establish the oracle connection by entering their username and password in the `channel <- gapindex::oracle_connect()` function. Never save usernames or passwords in scripts that may be intentionally or unintentionally shared with others. If no username and password is entered in the function, pop-ups will appear on the screen asking for the username and password. \n\nAfter you connect to VPN, you'll be able to log into Oracle. \n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(RODBC)\nchannel <- gapindex::get_connected()\n```\n:::\n\n\n## Data SQL Query Examples: {.unnumbered}\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(gapindex)\nlibrary(RODBC)\nlibrary(flextable)\nlibrary(ggplot2)\nlibrary(magrittr)\nlibrary(dplyr)\n```\n:::\n\n\n### Ex. Select all data from tables\n\nYou can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the `R` environment. \n\n\n::: {.cell}\n\n```{.r .cell-code}\nlocations <- c(\n \"GAP_PRODUCTS.AKFIN_AGECOMP\", \n \"GAP_PRODUCTS.AKFIN_AREA\", \n \"GAP_PRODUCTS.AKFIN_BIOMASS\", \n \"GAP_PRODUCTS.AKFIN_CATCH\", \n \"GAP_PRODUCTS.AKFIN_CPUE\", \n \"GAP_PRODUCTS.AKFIN_CRUISE\", \n \"GAP_PRODUCTS.AKFIN_HAUL\", \n \"GAP_PRODUCTS.AKFIN_LENGTH\", \n \"GAP_PRODUCTS.AKFIN_METADATA_COLUMN\", \n \"GAP_PRODUCTS.AKFIN_SIZECOMP\", \n \"GAP_PRODUCTS.AKFIN_SPECIMEN\", \n \"GAP_PRODUCTS.AKFIN_STRATUM_GROUPS\", \n \"GAP_PRODUCTS.AKFIN_SURVEY_DESIGN\", \n \"GAP_PRODUCTS.AKFIN_TAXONOMIC_CLASSIFICATION\"\n)\n\nfor (i in 1:length(locations)) {\n print(locations[i])\n a <- RODBC::sqlQuery(channel, paste0(\"SELECT * FROM \", locations[i]))\n write.csv(x = a, file = here::here(\"data\", paste0(locations[i], \".csv\")))\n}\n```\n:::\n\n\n### Ex. CPUE for all EBS and NBS stations with associated haul, cruise, and species information.\n\n\n::: {.cell tbl-cap='Ex.: CPUE for all EBS and NBS stations with associated haul, cruise, and species information. '}\n\n```{.r .cell-code}\na <- RODBC::sqlQuery(channel = channel, # NOT RACEBASE.HAUL\n query = paste0(\n\"\n-- Select columns for output data\nSELECT\ncr.CRUISEJOIN,\ncr.CRUISE,\ncr.YEAR,\ncr.SURVEY_DEFINITION_ID,\ncr.SURVEY_NAME,\ncr.VESSEL_ID,\ncr.VESSEL_NAME,\ncp.HAULJOIN,\ncp.SPECIES_CODE,\ntt.SPECIES_NAME,\ntt.COMMON_NAME,\ncp.WEIGHT_KG,\ncp.COUNT,\ncp.AREA_SWEPT_KM2,\ncp.CPUE_KGKM2,\ncp.CPUE_NOKM2,\nhh.HAUL,\nhh.STATION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_HAUL hh\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cr\nON hh.CRUISEJOIN = cr.CRUISEJOIN\nLEFT JOIN GAP_PRODUCTS.AKFIN_CPUE cp\nON hh.HAULJOIN = cp.HAULJOIN\nLEFT JOIN GAP_PRODUCTS.TAXONOMIC_CLASSIFICATION tt\nON cp.SPECIES_CODE = tt.SPECIES_CODE\n\n-- Filter for EBS and NBS observations\nWHERE SURVEY_DEFINITION_ID IN (143, 98) -- 143 NBS, 98 EBS\nAND tt.SURVEY_SPECIES = 1\n\n-- Only return the first 3 rows because otherwise this would be a huge table!\nFETCH FIRST 3 ROWS ONLY;\")) \n\nflextable::flextable(head(a)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=html}\n
\n```\n:::\n:::\n\n\n### Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel,\n query =\n\"\n-- Select columns for output data\nSELECT \nHAULJOIN, \nSPECIES_CODE, \nSTRATUM, \nLATITUDE_DD_START, \nLONGITUDE_DD_START,\nCPUE_KGKM2, \nGEAR_TEMPERATURE_C\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_CPUE cpue\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL haul\nUSING (HAULJOIN) \n\n-- Filter for P. Cod observations\nWHERE SPECIES_CODE IN (21720)\n\n-- Select all stratum within the area_id 919 (INPFC Shumagin region)\nAND haul.STRATUM IN\n(\nSELECT \nSTRATUM\nFROM GAP_PRODUCTS.AKFIN_STRATUM_GROUPS \nWHERE AREA_ID = 919\n);\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 8: CPUE for all stations contained in the Shumagin region (AREA_ID = 919). '}\n\n```{.r .cell-code}\ndat <- dat %>% \n dplyr::select(HAULJOIN, STRATUM, SPECIES_CODE, LATITUDE_DD_START, LONGITUDE_DD_START, CPUE_KGKM2, GEAR_TEMPERATURE_C) %>% \n dplyr::mutate(SPECIES_CODE = as.character(SPECIES_CODE), \n STRATUM = as.character(STRATUM)) %>% \n dplyr::arrange(SPECIES_CODE)\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=html}\n
HAULJOIN
STRATUM
SPECIES_CODE
LATITUDE_DD_START
LONGITUDE_DD_START
CPUE_KGKM2
GEAR_TEMPERATURE_C
-22,270
13
21720
55.11515
-159.3512
209.28994
4.3
-22,250
13
21720
55.05143
-159.9679
8,700.92017
5.1
-22,238
13
21720
55.11365
-159.4264
363.17325
4.4
-22,214
13
21720
54.78608
-160.0008
63.71506
4.6
-22,202
111
21720
54.48341
-159.7261
618.72120
4.7
-22,247
112
21720
55.59093
-160.0740
114.73042
4.0
\n```\n:::\n:::\n\n\n### Ex. EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map \n\nPacific Ocean perch catch-per-unit-effort estimates for EBS in 2021 from `GAP_PRODUCTS.AKFIN_CPUE` and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). Here, we'll use AKFIN HAUL and CRUISES data also included in this repo, for convenience, though they are very similar to their `RACEBASE` analogs. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \n(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares\nhh.LATITUDE_DD_START LATITUDE,\nhh.LONGITUDE_DD_START LONGITUDE\n\n-- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin\nFROM GAP_PRODUCTS.AKFIN_CPUE cp\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh\nON cp.HAULJOIN = hh.HAULJOIN\n\n-- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc\nON hh.CRUISEJOIN = cc.CRUISEJOIN\n\n-- Filter data\nWHERE cp.SPECIES_CODE = 30060 \nAND cc.SURVEY_DEFINITION_ID = 98 \nAND cc.YEAR = 2021;\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=html}\n
CPUE_KGHA
LATITUDE
LONGITUDE
0.00000000
60.67043
-178.0946
0.00000000
60.31361
-176.0138
0.00000000
60.35098
-175.3850
0.00000000
60.99712
-177.6638
0.00000000
60.96495
-176.2634
0.02416379
58.97844
-175.7204
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n x = dat, # Pass data as a data frame\n region = \"bs.south\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n\n```{.r .cell-code}\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific Ocean perch\\nCPUE (kg/km2)\")) |> \n change_fill_color(new.scheme = \"grey\", show.plot = FALSE)\n```\n\n::: {.cell-output-display}\n![Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. ](akfin-oracle-sql-r_files/figure-html/test-6-fig-1.png){width=672}\n:::\n:::\n\n\n### Ex. GOA Pacific Ocean perch biomass and abundance\n\nBiomass and abundance for Pacific Ocean perch from 1990 – 2023 for the western/central/eastern GOA management areas as well as for the entire region. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE in ('REGULATORY_AREA', 'REGION') \nAND SURVEY_DEFINITION_ID = 47)\n\n-- Select columns for output data\nSELECT \nBIOMASS_MT,\nPOPULATION_COUNT, \nYEAR, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SPECIES_CODE = 30060\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 1: GOA Pacific Ocean perch biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = description) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = gsub(x = area, pattern = \" - \", replacement = \"\\n\"), \n area = gsub(x = area, pattern = \": \", replacement = \"\\n\"), \n type = sapply(X = strsplit(x = area, split = \"\\n\", fixed = TRUE), `[[`, 2)) %>% \n dplyr::arrange(type) %>% \n dplyr::mutate(\n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\n\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=html}\n
BIOMASS_MT
POPULATION_COUNT
YEAR
DESCRIPTION
157,295.1
317,129,408
1990
GOA Region: All Strata
157,295.1
317,129,408
1990
GOA Region: All Strata
483,622.6
833,902,161
1993
GOA Region: All Strata
483,622.6
833,902,161
1993
GOA Region: All Strata
771,412.8
1,252,616,603
1996
GOA Region: All Strata
771,412.8
1,252,616,603
1996
GOA Region: All Strata
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"scales\")\nlibrary(scales)\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(x = year, y = val, color = type)) +\n ggplot2::geom_point(size = 3) + \n ggplot2::facet_grid(cols = vars(area), rows = vars(var), scales = \"free_y\") + \n ggplot2::scale_x_continuous(name = \"Year\", n.breaks = 3) +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::labs(title = 'GOA Pacific Ocean perch biomass and abundance 1990 – 2023') + \n ggplot2::guides(color=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_color_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 1: GOA Pacific Ocean perch biomass and abundance. ](akfin-oracle-sql-r_files/figure-html/test-1-plot-1.png){width=672}\n:::\n:::\n\n\n### Ex. AI rock sole size compositions and ridge plot\n\nNorthern and Southern rock sole size composition data from 1991 – 2022 for the Aleutian Islands, with Ridge plot from [`ggridges`](https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html).\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE = 'REGION' \nAND SURVEY_DEFINITION_ID = 52)\n\n-- Select columns for output data\nSELECT \nLENGTH_MM, \nYEAR\nFROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = SIZECOMP.AREA_ID\n\n-- Filter data results\nWHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52 \nAND SIZECOMP.SPECIES_CODE IN (10261, 10262)\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 2: AI Rock sole size compositions and ridge plot. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::mutate(length_cm = length_mm/10) %>% \n head() %>% \n flextable::flextable() %>% \n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\ndat0\n```\n\n::: {.cell-output-display}\n```{=html}\n
length_mm
year
length_cm
110
1997
11
130
1997
13
140
1997
14
150
1997
15
160
1997
16
170
1997
17
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"ggridges\")\nlibrary(ggridges)\nfigure <- \n ggplot2::ggplot(\n data = dat, \n mapping = aes(x = LENGTH_MM, y = as.factor(YEAR), fill = stat(x))) +\n ggridges::theme_ridges(center_axis_labels = TRUE) + \n ggridges::geom_density_ridges_gradient(scale = 4, show.legend = FALSE) + \n ggplot2::scale_y_discrete(name = \"Year\", expand = c(0.01, 0)) +\n ggplot2::scale_x_continuous(name = \"Length (cm)\", expand = c(0.01, 0)) +\n # ggplot2::scale_fill_grey() +\n ggplot2::labs(title = 'AI Rock sole Size Compositions 1991 – 2022') \n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 2: AI Rock sole size compositions and ridge plot. ](akfin-oracle-sql-r_files/figure-html/test-2-plot-1.png){width=672}\n:::\n:::\n\n\n### Ex. EBS Walleye Pollock Age Compositions and Age Pyramid\n\nWalleye pollock age composition for the EBS Standard Area from 1982 – 2022 and the EBS + NW Area from 1987 – 2022, with age pyramid plot. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE = 'REGION' AND \nSURVEY_DEFINITION_ID = 98)\n\n-- Select columns for output data\nSELECT \nAGECOMP.AGE, \nAGECOMP.POPULATION_COUNT, \nAGECOMP.SEX\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = AGECOMP.AREA_ID\n\n-- Filter data results\nWHERE SPECIES_CODE = 21740\nAND AGE >= 0\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::filter(sex %in% c(1,2)) %>%\n dplyr::mutate(\n sex = ifelse(sex == 1, \"M\", \"F\"),\n population_count = # change male population to negative\n ifelse(sex==\"M\", population_count*(-1), population_count*1)/1e9) \n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=html}\n
AGE
POPULATION_COUNT
SEX
11
48,791,451
2
12
120,673,580
2
13
42,580,054
2
14
47,229,378
2
15
25,140,523
2
16
19,473,255
2
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n data = dat0, \n mapping = \n aes(x = age,\n y = population_count, \n fill = sex)) +\n ggplot2::scale_fill_grey() +\n ggplot2::geom_bar(stat = \"identity\") +\n ggplot2::coord_flip() +\n ggplot2::scale_x_continuous(name = \"Age\") +\n ggplot2::scale_y_continuous(name = \"Population (billions)\", labels = abs) +\n ggplot2::ggtitle(label = \"EBS Walleye Pollock Age Compositions 1982 – 2022\") + \n ggplot2::guides(fill = guide_legend(title = \"Sex\"))+\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. ](akfin-oracle-sql-r_files/figure-html/test-3-plot-1.png){width=672}\n:::\n:::\n\n\n### Ex. NBS Pacific cod biomass and abundance\n\nPacific cod biomass and abundance data for the NBS by stratum. \n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nAREA_NAME, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE in ('STRATUM') AND \nSURVEY_DEFINITION_ID = 143) \n\n-- Select columns for output data\nSELECT \nBIOMASS.BIOMASS_MT, \nBIOMASS.POPULATION_COUNT, \nBIOMASS.YEAR, \nSTRATA.AREA_NAME\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS \nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SURVEY_DEFINITION_ID IN 143 \nAND BIOMASS.SPECIES_CODE = 21720\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 4: NBS Pacific cod biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = area_name) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=html}\n
BIOMASS_MT
POPULATION_COUNT
YEAR
AREA_NAME
7,462.559
4,724,153
2010
Inner Domain
95,849.983
68,767,498
2021
Inner Domain
107,096.730
102,734,142
2019
Inner Domain
76,708.433
39,605,860
2023
Inner Domain
132,490.152
66,187,245
2017
Inner Domain
96,500.697
60,433,135
2022
Inner Domain
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(y = val, x = year, fill = area)) + \n ggplot2::geom_bar(position=\"stack\", stat=\"identity\") + \n ggplot2::facet_grid(rows = vars(var), scales = \"free_y\") +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::scale_x_continuous(name = \"Year\", breaks = unique(dat0$year)) +\n ggplot2::labs(title = 'NBS Pacific cod biomass and abundance by stratum') + \n ggplot2::guides(fill=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_fill_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 4: NBS Pacific cod biomass and abundance. ](akfin-oracle-sql-r_files/figure-html/test-4-fig-1.png){width=672}\n:::\n:::\n\n\n### Ex. GOA Pacific Ocean perch biomass and line plot\n\nPacific Ocean perch biomass totals for GOA between 1984-2021 from `GAP_PRODUCTS.AKFIN_BIOMASS`\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \nSURVEY_DEFINITION_ID, \nBIOMASS_MT, \nBIOMASS_VAR, \nYEAR\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS\n\n-- Filter data results\nWHERE SPECIES_CODE = 30060 \nAND SURVEY_DEFINITION_ID = 47 \nAND AREA_ID = 99903 \nAND YEAR BETWEEN 1984 AND 2023;\") %>% \n janitor::clean_names() %>% \n dplyr::mutate(biomass_kmt = biomass_mt/1000, \n # **approximate** 95% confidence interval\n biomass_kci_up = (biomass_mt + (2*sqrt(biomass_var)))/1000, \n biomass_kci_dw = (biomass_mt - (2*sqrt(biomass_var)))/1000) \n```\n:::\n\n::: {.cell tbl-cap='Ex. 5: GOA Pacific Ocean perch biomass and line plot. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>%\n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=html}\n
survey_definition_id
biomass_mt
biomass_var
year
biomass_kmt
biomass_kci_up
biomass_kci_dw
47
157,295.1
2,221,176,968
1990
157.2951
251.5538
63.03638
47
483,622.6
11,803,384,787
1993
483.6226
700.9093
266.33581
47
771,412.8
41,434,152,202
1996
771.4128
1,178.5204
364.30515
47
727,063.5
150,983,542,178
1999
727.0635
1,504.1955
-50.06854
47
673,155.1
49,285,342,922
2001
673.1551
1,117.1611
229.14901
47
457,421.6
5,186,126,529
2003
457.4216
601.4511
313.39204
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\na_mean <- dat %>% \n dplyr::group_by(survey_definition_id) %>% \n dplyr::summarise(biomass_kmt = mean(biomass_kmt, na.rm = TRUE), \n minyr = min(year, na.rm = TRUE), \n maxyr = max(year, na.rm = TRUE)) \n\nfigure <-\n ggplot(data = dat, \n mapping = aes(x = year, \n y = biomass_kmt)) +\n ggplot2::geom_point(size = 2.5, color = \"grey40\") + \n ggplot2::scale_x_continuous(\n name = \"Year\", \n labels = scales::label_number(\n accuracy = 1, \n big.mark = \"\")) +\n ggplot2::scale_y_continuous(\n name = \"Biomass (Kmt)\", \n labels = comma) +\n ggplot2::geom_segment(\n data = a_mean,\n mapping = aes(x = minyr, \n xend = maxyr, \n y = biomass_kmt, \n yend = biomass_kmt),\n linetype = \"dashed\", \n linewidth = 2) +\n ggplot2::geom_errorbar(\n mapping = aes(ymin = biomass_kci_dw, ymax = biomass_kci_up),\n position = position_dodge(.9),\n alpha = 0.5, width=.2) +\n ggplot2::ggtitle(\n label = \"GOA Pacific Ocean Perch Biomass 1984-2021\", \n subtitle = paste0(\"Mean = \", \n formatC(x = a_mean$biomass_kmt, \n digits = 2, \n big.mark = \",\", \n format = \"f\"), \n \" Kmt\")) +\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 5: GOA Pacific Ocean perch biomass and line plot. ](akfin-oracle-sql-r_files/figure-html/test-5-fig-1.png){width=672}\n:::\n:::\n\n::: {.cell}\n\n:::\n",
"supporting": [
"akfin-oracle-sql-r_files\\figure-html"
],
diff --git a/_freeze/content/akfin-oracle-sql-r/execute-results/tex.json b/_freeze/content/akfin-oracle-sql-r/execute-results/tex.json
index 97ee5c6..b29e5b5 100644
--- a/_freeze/content/akfin-oracle-sql-r/execute-results/tex.json
+++ b/_freeze/content/akfin-oracle-sql-r/execute-results/tex.json
@@ -1,7 +1,7 @@
{
- "hash": "6ca4dec388d9bb5ed42dd65c29ee5da6",
+ "hash": "e95dda4032f9d6c0c84201c12b9852cc",
"result": {
- "markdown": "---\ntitle: Access data\nnumber-sections: true\nnumber-depth: 3\n---\n\n\n\n\n\n## Access data via Oracle (AFSC only) {.unnumbered}\n\nAFSC `Oracle` users can access the database via `SQL developer` to view and pull the production data directly from the `GAP_PRODUCTS` `Oracle` schema. The user can also use `SQL developer` to view and pull the GAP Products data directly from the `GAP_PRODUCTS` `Oracle` schema. \n\n### Connect to Oracle from R\n\nMany users will want to access the data from `Oracle` using `R`. The user will need to install the `RODBC` `R` package and ask OFIS (IT) connect `R` to `Oracle`. Then, use the following code in `R` to establish a connection from `R` to `Oracle`: \n\nHere, the user can establish the oracle connection by entering their username and password in the `channel <- gapindex::oracle_connect()` function. Never save usernames or passwords in scripts that may be intentionally or unintentionally shared with others. If no username and password is entered in the function, pop-ups will appear on the screen asking for the username and password. \n\nAfter you connect to VPN, you'll be able to log into Oracle. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(RODBC)\nchannel <- gapindex::get_connected()\n```\n:::\n\n\n\n## Data SQL Query Examples: {.unnumbered}\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(gapindex)\nlibrary(RODBC)\nlibrary(flextable)\nlibrary(ggplot2)\nlibrary(magrittr)\nlibrary(dplyr)\n```\n:::\n\n\n\n### Ex. Select all data from a table\n\nYou can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the `R` environment. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlocations <- c(\n \"GAP_PRODUCTS.AKFIN_AGECOMP\", \n \"GAP_PRODUCTS.AKFIN_AREA\", \n \"GAP_PRODUCTS.AKFIN_BIOMASS\", \n \"GAP_PRODUCTS.AKFIN_CATCH\", \n \"GAP_PRODUCTS.AKFIN_CPUE\", \n \"GAP_PRODUCTS.AKFIN_CRUISE\", \n \"GAP_PRODUCTS.AKFIN_HAUL\", \n \"GAP_PRODUCTS.AKFIN_LENGTH\", \n \"GAP_PRODUCTS.AKFIN_METADATA_COLUMN\", \n \"GAP_PRODUCTS.AKFIN_SIZECOMP\", \n \"GAP_PRODUCTS.AKFIN_SPECIMEN\", \n \"GAP_PRODUCTS.AKFIN_STRATUM_GROUPS\", \n \"GAP_PRODUCTS.AKFIN_SURVEY_DESIGN\", \n \"GAP_PRODUCTS.AKFIN_TAXONOMIC_CLASSIFICATION\"\n)\n\nfor (i in 1:length(locations)) {\n print(locations[i])\n a <- RODBC::sqlQuery(channel, paste0(\"SELECT * FROM \", locations[i]))\n write.csv(x = a, file = here::here(\"data\", paste0(locations[i], \".csv\")))\n}\n```\n:::\n\n::: {.cell}\n\n:::\n\n::: {.cell}\n\n:::\n\n::: {.cell tbl-cap='Ex. 7: Summary table of Number hauls where species were observed (N_HAULS) and number of length measurements that were colelcted for this species (N_LENGTHS) for EBS and NBS, for arrowtooth flounder (10110), Bering flounder (10140), and Alaska skate (435). '}\n\n:::\n\n\n\n### Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel,\n query =\n\"\n-- Select columns for output data\nSELECT \nHAULJOIN, \nSPECIES_CODE, \nSTRATUM, \nLATITUDE_DD_START, \nLONGITUDE_DD_START,\nCPUE_KGKM2, \nGEAR_TEMPERATURE_C\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_CPUE cpue\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL haul\nUSING (HAULJOIN) \n\n-- Filter for P. Cod observations\nWHERE SPECIES_CODE IN (21720)\n\n-- Select all stratum within the area_id 919 (INPFC Shumagin region)\nAND haul.STRATUM IN\n(\nSELECT \nSTRATUM\nFROM GAP_PRODUCTS.AKFIN_STRATUM_GROUPS \nWHERE AREA_ID = 919\n);\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 8: CPUE for all stations contained in the Shumagin region (AREA_ID = 919). '}\n\n```{.r .cell-code}\ndat <- dat %>% \n dplyr::select(HAULJOIN, STRATUM, SPECIES_CODE, LATITUDE_DD_START, LONGITUDE_DD_START, CPUE_KGKM2, GEAR_TEMPERATURE_C) %>% \n dplyr::mutate(SPECIES_CODE = as.character(SPECIES_CODE), \n STRATUM = as.character(STRATUM)) %>% \n dplyr::arrange(SPECIES_CODE)\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{HAULJOIN}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{STRATUM}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SPECIES\\_CODE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LATITUDE\\_DD\\_START}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LONGITUDE\\_DD\\_START}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_KGKM2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{GEAR\\_TEMPERATURE\\_C}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 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0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{717.63085}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.5}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,215}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{13}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{54.58732}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-161.1945}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{76.90763}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,168}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{11}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{54.45823}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-163.0872}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2,004.49628}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.9}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,204}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{110}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{54.51804}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-160.7493}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.00000}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.7}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,188}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{210}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{54.38733}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-159.6986}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.00000}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{5.5}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,183}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{210}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{54.09314}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-161.6996}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.00000}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{5.3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n### Ex. EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map \n\nPacific Ocean perch catch-per-unit-effort estimates for EBS in 2021 from `GAP_PRODUCTS.AKFIN_CPUE` and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). Here, we'll use AKFIN HAUL and CRUISES data also included in this repo, for convenience, though they are very similar to their `RACEBASE` analogs. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \n(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares\nhh.LATITUDE_DD_START LATITUDE,\nhh.LONGITUDE_DD_START LONGITUDE\n\n-- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin\nFROM GAP_PRODUCTS.AKFIN_CPUE cp\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh\nON cp.HAULJOIN = hh.HAULJOIN\n\n-- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc\nON hh.CRUISEJOIN = cc.CRUISEJOIN\n\n-- Filter data\nWHERE cp.SPECIES_CODE = 30060 \nAND cc.SURVEY_DEFINITION_ID = 98 \nAND cc.YEAR = 2021;\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_KGHA}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LATITUDE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LONGITUDE}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_KGHA}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LATITUDE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LONGITUDE}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.0000000}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{58.75863}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-174.9285}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.2813533}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{57.32545}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-173.3217}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.0000000}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{57.64161}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-172.7963}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.0000000}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{59.67831}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-172.5754}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.0000000}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{60.96936}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-174.8760}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.0000000}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{58.64012}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-173.5922}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n x = dat, # Pass data as a data frame\n region = \"bs.south\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n\n```{.r .cell-code}\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific Ocean perch\\nCPUE (kg/km2)\")) |> \n change_fill_color(new.scheme = \"grey\", show.plot = FALSE)\n```\n\n::: {.cell-output-display}\n![Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. ](akfin-oracle-sql-r_files/figure-pdf/test-6-fig-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. GOA Pacific Ocean perch biomass and abundance\n\nBiomass and abundance for Pacific Ocean perch from 1990 – 2023 for the western/central/eastern GOA management areas as well as for the entire region. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE in ('REGULATORY_AREA', 'REGION') \nAND SURVEY_DEFINITION_ID = 47)\n\n-- Select columns for output data\nSELECT \nBIOMASS_MT,\nPOPULATION_COUNT, \nYEAR, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SPECIES_CODE = 30060\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 1: GOA Pacific Ocean perch biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = description) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = gsub(x = area, pattern = \" - \", replacement = \"\\n\"), \n area = gsub(x = area, pattern = \": \", replacement = \"\\n\"), \n type = sapply(X = strsplit(x = area, split = \"\\n\", fixed = TRUE), `[[`, 2)) %>% \n dplyr::arrange(type) %>% \n dplyr::mutate(\n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\n\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{BIOMASS\\_MT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{DESCRIPTION}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{BIOMASS\\_MT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{DESCRIPTION}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{483,622.6}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{833,902,161}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1993}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{483,622.6}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{833,902,161}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1993}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{771,412.8}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,252,616,603}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1996}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{771,412.8}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,252,616,603}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1996}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{727,063.5}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,212,034,913}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1999}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{727,063.5}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,212,034,913}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1999}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"scales\")\nlibrary(scales)\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(x = year, y = val, color = type)) +\n ggplot2::geom_point(size = 3) + \n ggplot2::facet_grid(cols = vars(area), rows = vars(var), scales = \"free_y\") + \n ggplot2::scale_x_continuous(name = \"Year\", n.breaks = 3) +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::labs(title = 'GOA Pacific Ocean perch biomass and abundance 1990 – 2023') + \n ggplot2::guides(color=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_color_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 1: GOA Pacific Ocean perch biomass and abundance. ](akfin-oracle-sql-r_files/figure-pdf/test-1-plot-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. AI rock sole size compositions and ridge plot\n\nNorthern and Southern rock sole size composition data from 1991 – 2022 for the Aleutian Islands, with Ridge plot from [`ggridges`](https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html).\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE = 'REGION' \nAND SURVEY_DEFINITION_ID = 52)\n\n-- Select columns for output data\nSELECT \nLENGTH_MM, \nYEAR\nFROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = SIZECOMP.AREA_ID\n\n-- Filter data results\nWHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52 \nAND SIZECOMP.SPECIES_CODE IN (10261, 10262)\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 2: AI Rock sole size compositions and ridge plot. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::mutate(length_cm = length_mm/10)\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LENGTH\\_MM}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LENGTH\\_MM}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{180}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2014}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{190}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2014}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{200}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2014}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{210}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2014}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{220}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2014}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{230}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2014}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"ggridges\")\nlibrary(ggridges)\nfigure <- \n ggplot2::ggplot(\n data = dat0, \n mapping = aes(x = length_cm, y = as.factor(year), fill = stat(x))) +\n ggridges::theme_ridges(center_axis_labels = TRUE) + \n ggridges::geom_density_ridges_gradient(scale = 4, show.legend = FALSE) + \n ggplot2::scale_y_discrete(name = \"Year\", expand = c(0.01, 0)) +\n ggplot2::scale_x_continuous(name = \"Length (cm)\", expand = c(0.01, 0)) +\n # ggplot2::scale_fill_grey() +\n ggplot2::labs(title = 'AI Rock sole Size Compositions 1991 – 2022') \n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 2: AI Rock sole size compositions and ridge plot. ](akfin-oracle-sql-r_files/figure-pdf/test-2-plot-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. EBS Walleye Pollock Age Compositions and Age Pyramid\n\nWalleye pollock age composition for the EBS Standard Area from 1982 – 2022 and the EBS + NW Area from 1987 – 2022, with age pyramid plot. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE = 'REGION' AND \nSURVEY_DEFINITION_ID = 98)\n\n-- Select columns for output data\nSELECT \nAGECOMP.AGE, \nAGECOMP.POPULATION_COUNT, \nAGECOMP.SEX\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = AGECOMP.AREA_ID\n\n-- Filter data results\nWHERE SPECIES_CODE = 21740\nAND AGE >= 0\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::filter(sex %in% c(1,2)) %>%\n dplyr::mutate(\n sex = ifelse(sex == 1, \"M\", \"F\"),\n population_count = # change male population to negative\n ifelse(sex==\"M\", population_count*(-1), population_count*1)/1e9) \n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AGE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SEX}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AGE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SEX}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{9}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{39,371}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{10}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{32,156}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{11}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{15,200}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{12}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{9,976}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{13}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,957}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{131,950,343}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n data = dat0, \n mapping = \n aes(x = age,\n y = population_count, \n fill = sex)) +\n ggplot2::scale_fill_grey() +\n ggplot2::geom_bar(stat = \"identity\") +\n ggplot2::coord_flip() +\n ggplot2::scale_x_continuous(name = \"Age\") +\n ggplot2::scale_y_continuous(name = \"Population (billions)\", labels = abs) +\n ggplot2::ggtitle(label = \"EBS Walleye Pollock Age Compositions 1982 – 2022\") + \n ggplot2::guides(fill = guide_legend(title = \"Sex\"))+\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. ](akfin-oracle-sql-r_files/figure-pdf/test-3-plot-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. NBS Pacific cod biomass and abundance\n\nPacific cod biomass and abundance data for the NBS by stratum. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nAREA_NAME, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE in ('STRATUM') AND \nSURVEY_DEFINITION_ID = 143) \n\n-- Select columns for output data\nSELECT \nBIOMASS.BIOMASS_MT, \nBIOMASS.POPULATION_COUNT, \nBIOMASS.YEAR, \nSTRATA.AREA_NAME\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS \nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SURVEY_DEFINITION_ID IN 143 \nAND BIOMASS.SPECIES_CODE = 21720\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 4: NBS Pacific cod biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = area_name) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{BIOMASS\\_MT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AREA\\_NAME}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{BIOMASS\\_MT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AREA\\_NAME}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{95,849.983}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{68,767,498}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2021}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{107,096.730}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{102,734,142}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2019}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{76,708.433}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{39,605,860}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2023}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{132,490.152}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{66,187,245}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2017}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{96,500.697}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{60,433,135}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,462.559}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4,724,153}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2010}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(y = val, x = year, fill = area)) + \n ggplot2::geom_bar(position=\"stack\", stat=\"identity\") + \n ggplot2::facet_grid(rows = vars(var), scales = \"free_y\") +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::scale_x_continuous(name = \"Year\", breaks = unique(dat0$year)) +\n ggplot2::labs(title = 'NBS Pacific cod biomass and abundance by stratum') + \n ggplot2::guides(fill=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_fill_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 4: NBS Pacific cod biomass and abundance. ](akfin-oracle-sql-r_files/figure-pdf/test-4-fig-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. GOA Pacific Ocean perch biomass and line plot\n\nPacific Ocean perch biomass totals for GOA between 1984-2021 from `GAP_PRODUCTS.AKFIN_BIOMASS`\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \nSURVEY_DEFINITION_ID, \nBIOMASS_MT, \nBIOMASS_VAR, \nYEAR\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS\n\n-- Filter data results\nWHERE SPECIES_CODE = 30060 \nAND SURVEY_DEFINITION_ID = 47 \nAND AREA_ID = 99903 \nAND YEAR BETWEEN 1984 AND 2023;\") %>% \n janitor::clean_names() %>% \n dplyr::mutate(biomass_kmt = biomass_mt/1000, \n # **approximate** 95% confidence interval\n biomass_kci_up = (biomass_mt + (2*sqrt(biomass_var)))/1000, \n biomass_kci_dw = (biomass_mt - (2*sqrt(biomass_var)))/1000) \n```\n:::\n\n::: {.cell tbl-cap='Ex. 5: GOA Pacific Ocean perch biomass and line plot. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>%\n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{survey\\_definition\\_id}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_mt}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_var}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kmt}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kci\\_up}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kci\\_dw}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{survey\\_definition\\_id}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_mt}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_var}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kmt}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kci\\_up}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kci\\_dw}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{483,622.6}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{11,803,384,787}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1993}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{483.6226}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{700.9093}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{266.33581}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{771,412.8}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{41,434,152,202}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1996}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{771.4128}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,178.5204}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{364.30515}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{727,063.5}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{150,983,542,178}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1999}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{727.0635}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,504.1955}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-50.06854}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{673,155.1}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{49,285,342,922}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2001}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{673.1551}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,117.1611}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{229.14901}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{457,421.6}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{5,186,126,529}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2003}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{457.4216}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{601.4511}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{313.39204}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{764,901.4}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21,499,807,010}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2005}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{764.9014}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,058.1577}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{471.64517}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\na_mean <- dat %>% \n dplyr::group_by(survey_definition_id) %>% \n dplyr::summarise(biomass_kmt = mean(biomass_kmt, na.rm = TRUE), \n minyr = min(year, na.rm = TRUE), \n maxyr = max(year, na.rm = TRUE)) \n\nfigure <-\n ggplot(data = dat, \n mapping = aes(x = year, \n y = biomass_kmt)) +\n ggplot2::geom_point(size = 2.5, color = \"grey40\") + \n ggplot2::scale_x_continuous(\n name = \"Year\", \n labels = scales::label_number(\n accuracy = 1, \n big.mark = \"\")) +\n ggplot2::scale_y_continuous(\n name = \"Biomass (Kmt)\", \n labels = comma) +\n ggplot2::geom_segment(\n data = a_mean,\n mapping = aes(x = minyr, \n xend = maxyr, \n y = biomass_kmt, \n yend = biomass_kmt),\n linetype = \"dashed\", \n linewidth = 2) +\n ggplot2::geom_errorbar(\n mapping = aes(ymin = biomass_kci_dw, ymax = biomass_kci_up),\n position = position_dodge(.9),\n alpha = 0.5, width=.2) +\n ggplot2::ggtitle(\n label = \"GOA Pacific Ocean Perch Biomass 1984-2021\", \n subtitle = paste0(\"Mean = \", \n formatC(x = a_mean$biomass_kmt, \n digits = 2, \n big.mark = \",\", \n format = \"f\"), \n \" Kmt\")) +\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 5: GOA Pacific Ocean perch biomass and line plot. ](akfin-oracle-sql-r_files/figure-pdf/test-5-fig-1.pdf){fig-pos='H'}\n:::\n:::\n\n::: {.cell}\n\n:::\n",
+ "markdown": "---\ntitle: Access data\nnumber-sections: true\nnumber-depth: 3\n---\n\n\n\n\n\n## Access data via Oracle (AFSC only) {.unnumbered}\n\nAFSC `Oracle` users can access the database via `SQL developer` to view and pull the production data directly from the `GAP_PRODUCTS` `Oracle` schema. The user can also use `SQL developer` to view and pull the GAP Products data directly from the `GAP_PRODUCTS` `Oracle` schema. \n\n### Connect to Oracle from R\n\nMany users will want to access the data from `Oracle` using `R`. The user will need to install the `RODBC` `R` package and ask OFIS (IT) connect `R` to `Oracle`. Then, use the following code in `R` to establish a connection from `R` to `Oracle`: \n\nHere, the user can establish the oracle connection by entering their username and password in the `channel <- gapindex::oracle_connect()` function. Never save usernames or passwords in scripts that may be intentionally or unintentionally shared with others. If no username and password is entered in the function, pop-ups will appear on the screen asking for the username and password. \n\nAfter you connect to VPN, you'll be able to log into Oracle. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(RODBC)\nchannel <- gapindex::get_connected()\n```\n:::\n\n\n\n## Data SQL Query Examples: {.unnumbered}\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(gapindex)\nlibrary(RODBC)\nlibrary(flextable)\nlibrary(ggplot2)\nlibrary(magrittr)\nlibrary(dplyr)\n```\n:::\n\n\n\n### Ex. Select all data from tables\n\nYou can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the `R` environment. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlocations <- c(\n \"GAP_PRODUCTS.AKFIN_AGECOMP\", \n \"GAP_PRODUCTS.AKFIN_AREA\", \n \"GAP_PRODUCTS.AKFIN_BIOMASS\", \n \"GAP_PRODUCTS.AKFIN_CATCH\", \n \"GAP_PRODUCTS.AKFIN_CPUE\", \n \"GAP_PRODUCTS.AKFIN_CRUISE\", \n \"GAP_PRODUCTS.AKFIN_HAUL\", \n \"GAP_PRODUCTS.AKFIN_LENGTH\", \n \"GAP_PRODUCTS.AKFIN_METADATA_COLUMN\", \n \"GAP_PRODUCTS.AKFIN_SIZECOMP\", \n \"GAP_PRODUCTS.AKFIN_SPECIMEN\", \n \"GAP_PRODUCTS.AKFIN_STRATUM_GROUPS\", \n \"GAP_PRODUCTS.AKFIN_SURVEY_DESIGN\", \n \"GAP_PRODUCTS.AKFIN_TAXONOMIC_CLASSIFICATION\"\n)\n\nfor (i in 1:length(locations)) {\n print(locations[i])\n a <- RODBC::sqlQuery(channel, paste0(\"SELECT * FROM \", locations[i]))\n write.csv(x = a, file = here::here(\"data\", paste0(locations[i], \".csv\")))\n}\n```\n:::\n\n\n\n### Ex. CPUE for all EBS and NBS stations with associated haul, cruise, and species information.\n\n\n\n::: {.cell tbl-cap='Ex.: CPUE for all EBS and NBS stations with associated haul, cruise, and species information. '}\n\n```{.r .cell-code}\na <- RODBC::sqlQuery(channel = channel, # NOT RACEBASE.HAUL\n query = paste0(\n\"\n-- Select columns for output data\nSELECT\ncr.CRUISEJOIN,\ncr.CRUISE,\ncr.YEAR,\ncr.SURVEY_DEFINITION_ID,\ncr.SURVEY_NAME,\ncr.VESSEL_ID,\ncr.VESSEL_NAME,\ncp.HAULJOIN,\ncp.SPECIES_CODE,\ntt.SPECIES_NAME,\ntt.COMMON_NAME,\ncp.WEIGHT_KG,\ncp.COUNT,\ncp.AREA_SWEPT_KM2,\ncp.CPUE_KGKM2,\ncp.CPUE_NOKM2,\nhh.HAUL,\nhh.STATION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_HAUL hh\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cr\nON hh.CRUISEJOIN = cr.CRUISEJOIN\nLEFT JOIN GAP_PRODUCTS.AKFIN_CPUE cp\nON hh.HAULJOIN = cp.HAULJOIN\nLEFT JOIN GAP_PRODUCTS.TAXONOMIC_CLASSIFICATION tt\nON cp.SPECIES_CODE = tt.SPECIES_CODE\n\n-- Filter for EBS and NBS observations\nWHERE SURVEY_DEFINITION_ID IN (143, 98) -- 143 NBS, 98 EBS\nAND tt.SURVEY_SPECIES = 1\n\n-- Only return the first 3 rows because otherwise this would be a huge table!\nFETCH FIRST 3 ROWS ONLY;\")) \n\nflextable::flextable(head(a)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CRUISEJOIN}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CRUISE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SURVEY\\_DEFINITION\\_ID}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SURVEY\\_NAME}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{VESSEL\\_ID}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{VESSEL\\_NAME}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{HAULJOIN}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SPECIES\\_CODE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SPECIES\\_NAME}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{COMMON\\_NAME}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{WEIGHT\\_KG}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AREA\\_SWEPT\\_KM2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_KGKM2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_NOKM2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{HAUL}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{STATION}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CRUISEJOIN}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CRUISE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SURVEY\\_DEFINITION\\_ID}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SURVEY\\_NAME}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{VESSEL\\_ID}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{VESSEL\\_NAME}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{HAULJOIN}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SPECIES\\_CODE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SPECIES\\_NAME}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{COMMON\\_NAME}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{WEIGHT\\_KG}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AREA\\_SWEPT\\_KM2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_KGKM2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_NOKM2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{HAUL}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{STATION}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{80}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{198,203}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,982}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{98}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Eastern\\ Bering\\ Sea\\ Crab/Groundfish\\ Bottom\\ Trawl\\ Survey}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{CHAPMAN}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{877}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{fish\\ egg\\ unid.}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.042021}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{G-10}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{80}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{198,203}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,982}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{98}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Eastern\\ Bering\\ Sea\\ Crab/Groundfish\\ Bottom\\ Trawl\\ Survey}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{CHAPMAN}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{877}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{fish\\ larvae\\ unid.}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.042021}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{G-10}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{80}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{198,203}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,982}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{98}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Eastern\\ Bering\\ Sea\\ Crab/Groundfish\\ Bottom\\ Trawl\\ Survey}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{CHAPMAN}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{877}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{fish\\ unid.}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.042021}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{G-10}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n### Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel,\n query =\n\"\n-- Select columns for output data\nSELECT \nHAULJOIN, \nSPECIES_CODE, \nSTRATUM, \nLATITUDE_DD_START, \nLONGITUDE_DD_START,\nCPUE_KGKM2, \nGEAR_TEMPERATURE_C\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_CPUE cpue\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL haul\nUSING (HAULJOIN) \n\n-- Filter for P. Cod observations\nWHERE SPECIES_CODE IN (21720)\n\n-- Select all stratum within the area_id 919 (INPFC Shumagin region)\nAND haul.STRATUM IN\n(\nSELECT \nSTRATUM\nFROM GAP_PRODUCTS.AKFIN_STRATUM_GROUPS \nWHERE AREA_ID = 919\n);\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 8: CPUE for all stations contained in the Shumagin region (AREA_ID = 919). '}\n\n```{.r .cell-code}\ndat <- dat %>% \n dplyr::select(HAULJOIN, STRATUM, SPECIES_CODE, LATITUDE_DD_START, LONGITUDE_DD_START, CPUE_KGKM2, GEAR_TEMPERATURE_C) %>% \n dplyr::mutate(SPECIES_CODE = as.character(SPECIES_CODE), \n STRATUM = as.character(STRATUM)) %>% \n dplyr::arrange(SPECIES_CODE)\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{HAULJOIN}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{STRATUM}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SPECIES\\_CODE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LATITUDE\\_DD\\_START}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LONGITUDE\\_DD\\_START}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_KGKM2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{GEAR\\_TEMPERATURE\\_C}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{HAULJOIN}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{STRATUM}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SPECIES\\_CODE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LATITUDE\\_DD\\_START}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LONGITUDE\\_DD\\_START}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_KGKM2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{GEAR\\_TEMPERATURE\\_C}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,270}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{13}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{55.11515}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-159.3512}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{209.28994}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,250}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{13}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{55.05143}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-159.9679}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{8,700.92017}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{5.1}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,238}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{13}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{55.11365}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-159.4264}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{363.17325}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.4}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,214}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{13}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{54.78608}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-160.0008}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{63.71506}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.6}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,202}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{111}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{54.48341}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-159.7261}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{618.72120}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.7}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-22,247}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{112}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21720}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{55.59093}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-160.0740}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{114.73042}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.0}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n### Ex. EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map \n\nPacific Ocean perch catch-per-unit-effort estimates for EBS in 2021 from `GAP_PRODUCTS.AKFIN_CPUE` and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). Here, we'll use AKFIN HAUL and CRUISES data also included in this repo, for convenience, though they are very similar to their `RACEBASE` analogs. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \n(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares\nhh.LATITUDE_DD_START LATITUDE,\nhh.LONGITUDE_DD_START LONGITUDE\n\n-- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin\nFROM GAP_PRODUCTS.AKFIN_CPUE cp\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh\nON cp.HAULJOIN = hh.HAULJOIN\n\n-- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc\nON hh.CRUISEJOIN = cc.CRUISEJOIN\n\n-- Filter data\nWHERE cp.SPECIES_CODE = 30060 \nAND cc.SURVEY_DEFINITION_ID = 98 \nAND cc.YEAR = 2021;\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_KGHA}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LATITUDE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LONGITUDE}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{CPUE\\_KGHA}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LATITUDE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{LONGITUDE}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.00000000}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{60.67043}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-178.0946}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.00000000}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{60.31361}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-176.0138}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.00000000}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{60.35098}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-175.3850}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.00000000}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{60.99712}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-177.6638}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.00000000}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{60.96495}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-176.2634}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.02416379}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{58.97844}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-175.7204}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n x = dat, # Pass data as a data frame\n region = \"bs.south\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n\n```{.r .cell-code}\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific Ocean perch\\nCPUE (kg/km2)\")) |> \n change_fill_color(new.scheme = \"grey\", show.plot = FALSE)\n```\n\n::: {.cell-output-display}\n![Ex. 6: EBS Pacific Ocean perch CPUE and [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps) map. ](akfin-oracle-sql-r_files/figure-pdf/test-6-fig-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. GOA Pacific Ocean perch biomass and abundance\n\nBiomass and abundance for Pacific Ocean perch from 1990 – 2023 for the western/central/eastern GOA management areas as well as for the entire region. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE in ('REGULATORY_AREA', 'REGION') \nAND SURVEY_DEFINITION_ID = 47)\n\n-- Select columns for output data\nSELECT \nBIOMASS_MT,\nPOPULATION_COUNT, \nYEAR, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SPECIES_CODE = 30060\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 1: GOA Pacific Ocean perch biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = description) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = gsub(x = area, pattern = \" - \", replacement = \"\\n\"), \n area = gsub(x = area, pattern = \": \", replacement = \"\\n\"), \n type = sapply(X = strsplit(x = area, split = \"\\n\", fixed = TRUE), `[[`, 2)) %>% \n dplyr::arrange(type) %>% \n dplyr::mutate(\n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\n\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{BIOMASS\\_MT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{DESCRIPTION}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{BIOMASS\\_MT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{DESCRIPTION}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{157,295.1}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{317,129,408}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1990}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{157,295.1}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{317,129,408}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1990}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{483,622.6}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{833,902,161}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1993}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{483,622.6}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{833,902,161}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1993}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{771,412.8}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,252,616,603}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1996}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{771,412.8}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,252,616,603}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1996}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{GOA\\ Region:\\ All\\ Strata}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"scales\")\nlibrary(scales)\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(x = year, y = val, color = type)) +\n ggplot2::geom_point(size = 3) + \n ggplot2::facet_grid(cols = vars(area), rows = vars(var), scales = \"free_y\") + \n ggplot2::scale_x_continuous(name = \"Year\", n.breaks = 3) +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::labs(title = 'GOA Pacific Ocean perch biomass and abundance 1990 – 2023') + \n ggplot2::guides(color=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_color_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 1: GOA Pacific Ocean perch biomass and abundance. ](akfin-oracle-sql-r_files/figure-pdf/test-1-plot-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. AI rock sole size compositions and ridge plot\n\nNorthern and Southern rock sole size composition data from 1991 – 2022 for the Aleutian Islands, with Ridge plot from [`ggridges`](https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html).\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE = 'REGION' \nAND SURVEY_DEFINITION_ID = 52)\n\n-- Select columns for output data\nSELECT \nLENGTH_MM, \nYEAR\nFROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = SIZECOMP.AREA_ID\n\n-- Filter data results\nWHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52 \nAND SIZECOMP.SPECIES_CODE IN (10261, 10262)\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 2: AI Rock sole size compositions and ridge plot. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::mutate(length_cm = length_mm/10) %>% \n head() %>% \n flextable::flextable() %>% \n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\ndat0\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{length\\_mm}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{length\\_cm}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{length\\_mm}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{length\\_cm}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{110}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1997}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{11}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{130}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1997}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{13}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{140}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1997}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{14}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{150}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1997}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{15}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{160}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1997}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{16}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{170}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1997}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{17}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# install.packages(\"ggridges\")\nlibrary(ggridges)\nfigure <- \n ggplot2::ggplot(\n data = dat, \n mapping = aes(x = LENGTH_MM, y = as.factor(YEAR), fill = stat(x))) +\n ggridges::theme_ridges(center_axis_labels = TRUE) + \n ggridges::geom_density_ridges_gradient(scale = 4, show.legend = FALSE) + \n ggplot2::scale_y_discrete(name = \"Year\", expand = c(0.01, 0)) +\n ggplot2::scale_x_continuous(name = \"Length (cm)\", expand = c(0.01, 0)) +\n # ggplot2::scale_fill_grey() +\n ggplot2::labs(title = 'AI Rock sole Size Compositions 1991 – 2022') \n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 2: AI Rock sole size compositions and ridge plot. ](akfin-oracle-sql-r_files/figure-pdf/test-2-plot-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. EBS Walleye Pollock Age Compositions and Age Pyramid\n\nWalleye pollock age composition for the EBS Standard Area from 1982 – 2022 and the EBS + NW Area from 1987 – 2022, with age pyramid plot. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE = 'REGION' AND \nSURVEY_DEFINITION_ID = 98)\n\n-- Select columns for output data\nSELECT \nAGECOMP.AGE, \nAGECOMP.POPULATION_COUNT, \nAGECOMP.SEX\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = AGECOMP.AREA_ID\n\n-- Filter data results\nWHERE SPECIES_CODE = 21740\nAND AGE >= 0\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::filter(sex %in% c(1,2)) %>%\n dplyr::mutate(\n sex = ifelse(sex == 1, \"M\", \"F\"),\n population_count = # change male population to negative\n ifelse(sex==\"M\", population_count*(-1), population_count*1)/1e9) \n\nflextable::flextable(head(dat)) %>% theme_zebra()\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AGE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SEX}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AGE}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{SEX}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{11}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{48,791,451}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{12}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{120,673,580}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{13}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{42,580,054}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{14}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47,229,378}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{15}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{25,140,523}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{16}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{19,473,255}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n data = dat0, \n mapping = \n aes(x = age,\n y = population_count, \n fill = sex)) +\n ggplot2::scale_fill_grey() +\n ggplot2::geom_bar(stat = \"identity\") +\n ggplot2::coord_flip() +\n ggplot2::scale_x_continuous(name = \"Age\") +\n ggplot2::scale_y_continuous(name = \"Population (billions)\", labels = abs) +\n ggplot2::ggtitle(label = \"EBS Walleye Pollock Age Compositions 1982 – 2022\") + \n ggplot2::guides(fill = guide_legend(title = \"Sex\"))+\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid. ](akfin-oracle-sql-r_files/figure-pdf/test-3-plot-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. NBS Pacific cod biomass and abundance\n\nPacific cod biomass and abundance data for the NBS by stratum. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nAREA_NAME, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE in ('STRATUM') AND \nSURVEY_DEFINITION_ID = 143) \n\n-- Select columns for output data\nSELECT \nBIOMASS.BIOMASS_MT, \nBIOMASS.POPULATION_COUNT, \nBIOMASS.YEAR, \nSTRATA.AREA_NAME\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS \nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SURVEY_DEFINITION_ID IN 143 \nAND BIOMASS.SPECIES_CODE = 21720\")\n```\n:::\n\n::: {.cell tbl-cap='Ex. 4: NBS Pacific cod biomass and abundance. '}\n\n```{.r .cell-code}\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = area_name) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{BIOMASS\\_MT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AREA\\_NAME}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{BIOMASS\\_MT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{POPULATION\\_COUNT}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{YEAR}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{AREA\\_NAME}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,462.559}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4,724,153}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2010}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,462.559}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4,724,153}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2010}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,462.559}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4,724,153}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2010}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,462.559}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4,724,153}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2010}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,462.559}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4,724,153}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2010}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{95,849.983}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{68,767,498}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2021}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Inner\\ Domain}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(y = val, x = year, fill = area)) + \n ggplot2::geom_bar(position=\"stack\", stat=\"identity\") + \n ggplot2::facet_grid(rows = vars(var), scales = \"free_y\") +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::scale_x_continuous(name = \"Year\", breaks = unique(dat0$year)) +\n ggplot2::labs(title = 'NBS Pacific cod biomass and abundance by stratum') + \n ggplot2::guides(fill=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_fill_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 4: NBS Pacific cod biomass and abundance. ](akfin-oracle-sql-r_files/figure-pdf/test-4-fig-1.pdf){fig-pos='H'}\n:::\n:::\n\n\n\n### Ex. GOA Pacific Ocean perch biomass and line plot\n\nPacific Ocean perch biomass totals for GOA between 1984-2021 from `GAP_PRODUCTS.AKFIN_BIOMASS`\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \nSURVEY_DEFINITION_ID, \nBIOMASS_MT, \nBIOMASS_VAR, \nYEAR\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS\n\n-- Filter data results\nWHERE SPECIES_CODE = 30060 \nAND SURVEY_DEFINITION_ID = 47 \nAND AREA_ID = 99903 \nAND YEAR BETWEEN 1984 AND 2023;\") %>% \n janitor::clean_names() %>% \n dplyr::mutate(biomass_kmt = biomass_mt/1000, \n # **approximate** 95% confidence interval\n biomass_kci_up = (biomass_mt + (2*sqrt(biomass_var)))/1000, \n biomass_kci_dw = (biomass_mt - (2*sqrt(biomass_var)))/1000) \n```\n:::\n\n::: {.cell tbl-cap='Ex. 5: GOA Pacific Ocean perch biomass and line plot. '}\n\n```{.r .cell-code}\nflextable::flextable(head(dat)) %>%\n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{survey\\_definition\\_id}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_mt}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_var}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kmt}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kci\\_up}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kci\\_dw}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{survey\\_definition\\_id}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_mt}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_var}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kmt}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kci\\_up}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{biomass\\_kci\\_dw}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{157,295.1}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2,221,176,968}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1990}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{157.2951}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{251.5538}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{63.03638}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{483,622.6}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{11,803,384,787}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1993}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{483.6226}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{700.9093}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{266.33581}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{771,412.8}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{41,434,152,202}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1996}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{771.4128}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,178.5204}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{364.30515}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{727,063.5}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{150,983,542,178}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1999}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{727.0635}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,504.1955}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-50.06854}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{673,155.1}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{49,285,342,922}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2001}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{673.1551}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,117.1611}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{229.14901}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{47}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{457,421.6}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{5,186,126,529}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2003}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{457.4216}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{601.4511}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{313.39204}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\na_mean <- dat %>% \n dplyr::group_by(survey_definition_id) %>% \n dplyr::summarise(biomass_kmt = mean(biomass_kmt, na.rm = TRUE), \n minyr = min(year, na.rm = TRUE), \n maxyr = max(year, na.rm = TRUE)) \n\nfigure <-\n ggplot(data = dat, \n mapping = aes(x = year, \n y = biomass_kmt)) +\n ggplot2::geom_point(size = 2.5, color = \"grey40\") + \n ggplot2::scale_x_continuous(\n name = \"Year\", \n labels = scales::label_number(\n accuracy = 1, \n big.mark = \"\")) +\n ggplot2::scale_y_continuous(\n name = \"Biomass (Kmt)\", \n labels = comma) +\n ggplot2::geom_segment(\n data = a_mean,\n mapping = aes(x = minyr, \n xend = maxyr, \n y = biomass_kmt, \n yend = biomass_kmt),\n linetype = \"dashed\", \n linewidth = 2) +\n ggplot2::geom_errorbar(\n mapping = aes(ymin = biomass_kci_dw, ymax = biomass_kci_up),\n position = position_dodge(.9),\n alpha = 0.5, width=.2) +\n ggplot2::ggtitle(\n label = \"GOA Pacific Ocean Perch Biomass 1984-2021\", \n subtitle = paste0(\"Mean = \", \n formatC(x = a_mean$biomass_kmt, \n digits = 2, \n big.mark = \",\", \n format = \"f\"), \n \" Kmt\")) +\n ggplot2::theme_bw()\n\nfigure\n```\n\n::: {.cell-output-display}\n![Ex. 5: GOA Pacific Ocean perch biomass and line plot. ](akfin-oracle-sql-r_files/figure-pdf/test-5-fig-1.pdf){fig-pos='H'}\n:::\n:::\n\n::: {.cell}\n\n:::\n",
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"akfin-oracle-sql-r_files\\figure-pdf"
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@@ -11,7 +11,7 @@
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{
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"result": {
- "markdown": "---\ntitle: Access via API and R\n---\n\n\n\n\n\n\nAn application programming interface (API) is a way for two or more computer programs to communicate with each other.\n\nMore information about how to amend API links can be found [here](https://docs.oracle.com/en/database/oracle/oracle-rest-data-services/22.3/books.html#AELIG90103/). Useful introductions to using APIs in `R` can be found [here](https://www.dataquest.io/blog/r-api-tutorial/). \n\n## Ex. 1: Load the first 25 rows (default) of data\n\n\n\n\n::: {.cell tbl-cap='Ex. 1: Load the first 25 rows (default) of data. '}\n\n```{.r .cell-code}\n # install.packages(c(\"httr\", \"jsonlite\"))\nlibrary(httr)\nlibrary(jsonlite)\nlibrary(dplyr)\n\n # link to the API\napi_link <- \"https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/\"\n\nres <- httr::GET(url = api_link)\n # res # Test connection\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n # names(data)\ntibble::as_tibble(data$items) %>% \n dplyr::mutate_if(is.character, type.convert, as.is = TRUE) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n head(3) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"cruise\", \"species_code\", \"tsn\", \"ak_survey_id\"), big.mark = \"\")\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvysurveysurvey_idcruisehaulstratumstationvessel_namevessel_iddate_timelatitude_ddlongitude_ddspecies_codecommon_namescientific_nametaxon_confidencecpue_kghacpue_kgkm2cpue_kg1000km2cpue_nohacpue_nokm2cpue_no1000km2weight_kgcountbottom_temperature_csurface_temperature_cdepth_mdistance_fished_kmnet_width_mnet_height_marea_swept_haduration_hrtsnak_survey_idlinksbody12002AIAleutian Islands Bottom Trawl Survey522002016722307-63Vesteraalen9405/17/2002 18:56:5853.737-167.01695020feathery bryozoanEucratea loricataLow0.0171.7491,749.4450.04404.15.31871.56116.1127.252.5150.281558091917453[[data.frame]]body22002AIAleutian Islands Bottom Trawl Survey522002016722307-63Vesteraalen9405/17/2002 18:56:5853.737-167.01679000squid unid.DecapodiformesHigh0.0222.2272,226.5673.181318.081318,080.930.05684.15.31871.56116.1127.252.5150.281917454[[data.frame]]body32002AIAleutian Islands Bottom Trawl Survey522002016722307-63Vesteraalen9405/17/2002 18:56:5853.737-167.01624191shortfin eelpoutLycodes brevipesHigh0.0363.5783,578.4100.79579.52079,520.230.09024.15.31871.56116.1127.252.5150.281652581917455[[data.frame]]\n``````\n:::\n:::\n\n\n\n\n## Ex. 2: Load the first 10000 rows of data\n\n\n\n\n::: {.cell tbl-cap='Ex. 2: Load the first 10000 rows of data. '}\n\n```{.r .cell-code}\n# Not run because too big:\nres <- httr::GET(url = paste0(api_link, \"?offset=0&limit=10000\"))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\nprint(paste0(\"rows: \", dim(data$items)[1], \"; cols: \", dim(data$items)[2]))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"rows: 10000; cols: 36\"\n```\n:::\n:::\n\n\n\n\n## Ex. 3: Filter by Year\n\nShow all the data greater than the year 2020. \n\n\n\n\n::: {.cell tbl-cap='Ex. 3: Filter by Year. '}\n\n```{.r .cell-code}\nres <- httr::GET(url = paste0(api_link, '?q={\"year\":{\"$gt\":2020}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvystratumspecies_codecpue_kgkm2body12022AI793805400.361body22022AI7934010.903body32022AI793200061.661\n``````\n:::\n:::\n\n\n\n\n## Ex. 4: Filter by species name\n\nShow all the data where the product name contains pollock Please note that here the word pollock is case sensitive.\n\nThe notation for finding a string is to use % around it. Since % is a reserved character in a URL, you have to replace `%` with `%25`. \n\n\n\n\n::: {.cell tbl-cap='Ex. 4: Filter by species name. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvystratumspecies_codecpue_kgkm2body12002AI72221740775.322body22002AI7222174010,685.806body32002AI721217400.640\n``````\n:::\n:::\n\n\n\n\n## Ex. 5: Combination of year and name filters\n\nShow all the data where years > 2020 and the product name contains pollock\n\n\n\n\n::: {.cell tbl-cap='Ex. 5: Combination of year and name filters. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, \n '?q={\"year\":{\"$gt\":2020},\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvystratumspecies_codecpue_kgkm2body12022AI793217407,853.632body22022AI721217407,235.010body32022AI7222174022,754.334\n``````\n:::\n:::\n\n\n\n\n## Ex. 6: Combination of year, srvy, stratum\n\nShow all the data where year = 1989, srvy = \"EBS\", and stratum is not equal to 81\n\n\n\n\n::: {.cell tbl-cap='Ex. 6: Combination of year, srvy, stratum. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":1989,\"srvy\":\"EBS\",\"stratum\":{\"$ne\":\"81\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvystratumspecies_codecpue_kgkm2body11989EBS10665481.164body21989EBS10693221.164body31989EBS10430002.353\n``````\n:::\n:::\n\n\n\n\n## Ex. 7: Visualize CPUE data in distribution map\n\nPacific cod catch-per-unit-effort estimates for NBS in 2021 and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). \n\n\n\n\n::: {.cell tbl-cap='Ex. 7: Visualize CPUE data in distribution map. '}\n\n```{.r .cell-code}\n# res <- httr::GET(\n# url = paste0(api_link, \"?offset=0&limit=10000\"), \n# query = list(year = 2021, srvy = \"EBS\", species_code = 30060))\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\",\"species_code\":21720}'))\ndata_catch <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, cpue_kgkm2) \n\n# zero-fill data (imperfectly, but effective for this example)\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\"}offset=0&limit=10000'))\ndata_haul <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, latitude_dd, longitude_dd) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>% \n dplyr::distinct()\n\ndata <- dplyr::left_join(data_haul, data_catch) %>% \n dplyr::mutate(cpue_kgkm2 = ifelse(is.na(cpue_kgkm2), 0, cpue_kgkm2), \n dplyr::across(dplyr::everything(), as.numeric)) \n\nflextable::flextable(data[1:3,]) %>% \n flextable::theme_zebra() \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1stratumstationlatitude_ddlongitude_ddcpue_kgkm2body18161.66434-172.26552,895.258body28162.33740-173.17021,235.545body37062.03713-171.65280.000\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n CPUE_KGHA = data$cpue_kgkm2, # calculates the same, regardless of units. \n LATITUDE = data$latitude_dd, \n LONGITUDE = data$longitude_dd, \n region = \"bs.north\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n\n```{.r .cell-code}\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific cod\\nCPUE (kg/km2)\"))\n```\n\n::: {.cell-output-display}\n![Ex. 7: Visualize CPUE data in distribution map. ](foss-api-r_files/figure-docx/test-7-fig-1.png)\n:::\n:::\n",
+ "markdown": "---\ntitle: Access via API and R\n---\n\n\n\n\n\n\nAn application programming interface (API) is a way for two or more computer programs to communicate with each other.\n\nMore information about how to amend API links can be found [here](https://docs.oracle.com/en/database/oracle/oracle-rest-data-services/22.3/books.html#AELIG90103/). Useful introductions to using APIs in `R` can be found [here](https://www.dataquest.io/blog/r-api-tutorial/). \n\n## Ex. 1: Load the first 25 rows (default) of data\n\n\n\n\n::: {.cell tbl-cap='Ex. 1: Load the first 25 rows (default) of data. '}\n\n```{.r .cell-code}\n # install.packages(c(\"httr\", \"jsonlite\"))\nlibrary(httr)\nlibrary(jsonlite)\nlibrary(dplyr)\n\n # link to the API\napi_link <- \"https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/\"\n\nres <- httr::GET(url = api_link)\n # res # Test connection\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n # names(data)\ntibble::as_tibble(data$items) %>% \n dplyr::mutate_if(is.character, type.convert, as.is = TRUE) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n head(3) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"cruise\", \"species_code\", \"tsn\", \"ak_survey_id\"), big.mark = \"\")\n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvysurveysurvey_idcruisehaulstratumstationvessel_namevessel_iddate_timelatitude_ddlongitude_ddspecies_codecommon_namescientific_nametaxon_confidencecpue_kghacpue_kgkm2cpue_kg1000km2cpue_nohacpue_nokm2cpue_no1000km2weight_kgcountbottom_temperature_csurface_temperature_cdepth_mdistance_fished_kmnet_width_mnet_height_marea_swept_haduration_hrtsnak_survey_idlinksbody12002AIAleutian Islands Bottom Trawl Survey522002016722307-63Vesteraalen9405/17/2002 18:56:5853.737-167.01695020feathery bryozoanEucratea loricataLow0.0171.7491,749.4450.04404.15.31871.56116.1127.252.5150.281558091917453[[data.frame]]body22002AIAleutian Islands Bottom Trawl Survey522002016722307-63Vesteraalen9405/17/2002 18:56:5853.737-167.01679000squid unid.DecapodiformesHigh0.0222.2272,226.5673.181318.081318,080.930.05684.15.31871.56116.1127.252.5150.281917454[[data.frame]]body32002AIAleutian Islands Bottom Trawl Survey522002016722307-63Vesteraalen9405/17/2002 18:56:5853.737-167.01624191shortfin eelpoutLycodes brevipesHigh0.0363.5783,578.4100.79579.52079,520.230.09024.15.31871.56116.1127.252.5150.281652581917455[[data.frame]]\n``````\n:::\n:::\n\n\n\n\n## Ex. 2: Load the first 10000 rows of data\n\n\n\n\n::: {.cell tbl-cap='Ex. 2: Load the first 10000 rows of data. '}\n\n```{.r .cell-code}\n# Not run because too big:\nres <- httr::GET(url = paste0(api_link, \"?offset=0&limit=10000\"))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\nprint(paste0(\"rows: \", dim(data$items)[1], \"; cols: \", dim(data$items)[2]))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"rows: 10000; cols: 36\"\n```\n:::\n:::\n\n\n\n\n## Ex. 3: Filter by Year\n\nShow all the data greater than the year 2020. \n\n\n\n\n::: {.cell tbl-cap='Ex. 3: Filter by Year. '}\n\n```{.r .cell-code}\nres <- httr::GET(url = paste0(api_link, '?q={\"year\":{\"$gt\":2020}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvystratumspecies_codecpue_kgkm2body12022AI793805400.361body22022AI7934010.903body32022AI793200061.661\n``````\n:::\n:::\n\n\n\n\n## Ex. 4: Filter by species name\n\nShow all the data where the product name contains pollock Please note that here the word pollock is case sensitive.\n\nThe notation for finding a string is to use % around it. Since % is a reserved character in a URL, you have to replace `%` with `%25`. \n\n\n\n\n::: {.cell tbl-cap='Ex. 4: Filter by species name. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvystratumspecies_codecpue_kgkm2body12002AI72221740775.322body22002AI7222174010,685.806body32002AI721217400.640\n``````\n:::\n:::\n\n\n\n\n## Ex. 5: Combination of year and name filters\n\nShow all the data where years > 2020 and the product name contains pollock\n\n\n\n\n::: {.cell tbl-cap='Ex. 5: Combination of year and name filters. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, \n '?q={\"year\":{\"$gt\":2020},\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvystratumspecies_codecpue_kgkm2body12022AI793217407,853.632body22022AI721217407,235.010body32022AI7222174022,754.334\n``````\n:::\n:::\n\n\n\n\n## Ex. 6: Combination of year, srvy, stratum\n\nShow all the data where year = 1989, srvy = \"EBS\", and stratum is not equal to 81\n\n\n\n\n::: {.cell tbl-cap='Ex. 6: Combination of year, srvy, stratum. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":1989,\"srvy\":\"EBS\",\"stratum\":{\"$ne\":\"81\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1yearsrvystratumspecies_codecpue_kgkm2body11989EBS10665481.164body21989EBS10693221.164body31989EBS10430002.353\n``````\n:::\n:::\n\n\n\n\n## Ex. 7: Visualize CPUE data in distribution map\n\nPacific cod catch-per-unit-effort estimates for NBS in 2021 and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). \n\n\n\n\n::: {.cell tbl-cap='Ex. 7: Visualize CPUE data in distribution map. '}\n\n```{.r .cell-code}\n# res <- httr::GET(\n# url = paste0(api_link, \"?offset=0&limit=10000\"), \n# query = list(year = 2021, srvy = \"EBS\", species_code = 30060))\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\",\"species_code\":21720}'))\ndata_catch <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, cpue_kgkm2) \n\n# zero-fill data (imperfectly, but effective for this example)\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\"}offset=0&limit=10000'))\ndata_haul <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, latitude_dd, longitude_dd) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>% \n dplyr::distinct()\n\ndata <- dplyr::left_join(data_haul, data_catch) %>% \n dplyr::mutate(cpue_kgkm2 = ifelse(is.na(cpue_kgkm2), 0, cpue_kgkm2), \n dplyr::across(dplyr::everything(), as.numeric)) \n\nflextable::flextable(data[1:3,]) %>% \n flextable::theme_zebra() \n```\n\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1stratumstationlatitude_ddlongitude_ddcpue_kgkm2body18161.66434-172.26552,895.258body28162.33740-173.17021,235.545body37062.03713-171.65280.000\n``````\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n CPUE_KGHA = data$cpue_kgkm2, # calculates the same, regardless of units. \n LATITUDE = data$latitude_dd, \n LONGITUDE = data$longitude_dd, \n region = \"bs.north\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000))$plot + # 20x20km grid\n ggplot2::guides(fill=guide_legend(title = \"Pacific cod\\nCPUE (kg/km2)\"))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n:::\n",
"supporting": [
"foss-api-r_files\\figure-docx"
],
diff --git a/_freeze/content/foss-api-r/execute-results/html.json b/_freeze/content/foss-api-r/execute-results/html.json
index 2e11071..947838a 100644
--- a/_freeze/content/foss-api-r/execute-results/html.json
+++ b/_freeze/content/foss-api-r/execute-results/html.json
@@ -1,9 +1,9 @@
{
- "hash": "2eb6f941b64730743e5c01ae71e268dd",
+ "hash": "9b419c3eb2cb72acb9b71d1fec7c1dac",
"result": {
- "markdown": "---\ntitle: Access via API and R\n---\n\n\n\n\nAn application programming interface (API) is a way for two or more computer programs to communicate with each other.\n\nMore information about how to amend API links can be found [here](https://docs.oracle.com/en/database/oracle/oracle-rest-data-services/22.3/books.html#AELIG90103/). Useful introductions to using APIs in `R` can be found [here](https://www.dataquest.io/blog/r-api-tutorial/). \n\n## Ex. 1: Load the first 25 rows (default) of data\n\n\n::: {.cell tbl-cap='Ex. 1: Load the first 25 rows (default) of data. '}\n\n```{.r .cell-code}\n # install.packages(c(\"httr\", \"jsonlite\"))\nlibrary(httr)\nlibrary(jsonlite)\nlibrary(dplyr)\n\n # link to the API\napi_link <- \"https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/\"\n\nres <- httr::GET(url = api_link)\n # res # Test connection\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n # names(data)\ntibble::as_tibble(data$items) %>% \n dplyr::mutate_if(is.character, type.convert, as.is = TRUE) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n head(3) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"cruise\", \"species_code\", \"tsn\", \"ak_survey_id\"), big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
survey
survey_id
cruise
haul
stratum
station
vessel_name
vessel_id
date_time
latitude_dd
longitude_dd
species_code
common_name
scientific_name
taxon_confidence
cpue_kgha
cpue_kgkm2
cpue_kg1000km2
cpue_noha
cpue_nokm2
cpue_no1000km2
weight_kg
count
bottom_temperature_c
surface_temperature_c
depth_m
distance_fished_km
net_width_m
net_height_m
area_swept_ha
duration_hr
tsn
ak_survey_id
links
2002
AI
Aleutian Islands Bottom Trawl Survey
52
200201
6
722
307-63
Vesteraalen
94
05/17/2002 18:56:58
53.737
-167.016
95020
feathery bryozoan
Eucratea loricata
Low
0.017
1.749
1,749.445
0.044
0
4.1
5.3
187
1.561
16.112
7.25
2.515
0.28
155809
1917453
[[data.frame]]
2002
AI
Aleutian Islands Bottom Trawl Survey
52
200201
6
722
307-63
Vesteraalen
94
05/17/2002 18:56:58
53.737
-167.016
79000
squid unid.
Decapodiformes
High
0.022
2.227
2,226.567
3.181
318.081
318,080.93
0.056
8
4.1
5.3
187
1.561
16.112
7.25
2.515
0.28
1917454
[[data.frame]]
2002
AI
Aleutian Islands Bottom Trawl Survey
52
200201
6
722
307-63
Vesteraalen
94
05/17/2002 18:56:58
53.737
-167.016
24191
shortfin eelpout
Lycodes brevipes
High
0.036
3.578
3,578.410
0.795
79.520
79,520.23
0.090
2
4.1
5.3
187
1.561
16.112
7.25
2.515
0.28
165258
1917455
[[data.frame]]
\n```\n:::\n:::\n\n\n## Ex. 2: Load the first 10000 rows of data\n\n\n::: {.cell tbl-cap='Ex. 2: Load the first 10000 rows of data. '}\n\n```{.r .cell-code}\n# Not run because too big:\nres <- httr::GET(url = paste0(api_link, \"?offset=0&limit=10000\"))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\nprint(paste0(\"rows: \", dim(data$items)[1], \"; cols: \", dim(data$items)[2]))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"rows: 10000; cols: 36\"\n```\n:::\n:::\n\n\n## Ex. 3: Filter by Year\n\nShow all the data greater than the year 2020. \n\n\n::: {.cell tbl-cap='Ex. 3: Filter by Year. '}\n\n```{.r .cell-code}\nres <- httr::GET(url = paste0(api_link, '?q={\"year\":{\"$gt\":2020}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
stratum
species_code
cpue_kgkm2
2022
AI
793
80540
0.361
2022
AI
793
401
0.903
2022
AI
793
20006
1.661
\n```\n:::\n:::\n\n\n## Ex. 4: Filter by species name\n\nShow all the data where the product name contains pollock Please note that here the word pollock is case sensitive.\n\nThe notation for finding a string is to use % around it. Since % is a reserved character in a URL, you have to replace `%` with `%25`. \n\n\n::: {.cell tbl-cap='Ex. 4: Filter by species name. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
stratum
species_code
cpue_kgkm2
2002
AI
722
21740
775.322
2002
AI
722
21740
10,685.806
2002
AI
721
21740
0.640
\n```\n:::\n:::\n\n\n## Ex. 5: Combination of year and name filters\n\nShow all the data where years > 2020 and the product name contains pollock\n\n\n::: {.cell tbl-cap='Ex. 5: Combination of year and name filters. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, \n '?q={\"year\":{\"$gt\":2020},\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
stratum
species_code
cpue_kgkm2
2022
AI
793
21740
7,853.632
2022
AI
721
21740
7,235.010
2022
AI
722
21740
22,754.334
\n```\n:::\n:::\n\n\n## Ex. 6: Combination of year, srvy, stratum\n\nShow all the data where year = 1989, srvy = \"EBS\", and stratum is not equal to 81\n\n\n::: {.cell tbl-cap='Ex. 6: Combination of year, srvy, stratum. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":1989,\"srvy\":\"EBS\",\"stratum\":{\"$ne\":\"81\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
stratum
species_code
cpue_kgkm2
1989
EBS
10
66548
1.164
1989
EBS
10
69322
1.164
1989
EBS
10
43000
2.353
\n```\n:::\n:::\n\n\n## Ex. 7: Visualize CPUE data in distribution map\n\nPacific cod catch-per-unit-effort estimates for NBS in 2021 and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). \n\n\n::: {.cell tbl-cap='Ex. 7: Visualize CPUE data in distribution map. '}\n\n```{.r .cell-code}\n# res <- httr::GET(\n# url = paste0(api_link, \"?offset=0&limit=10000\"), \n# query = list(year = 2021, srvy = \"EBS\", species_code = 30060))\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\",\"species_code\":21720}'))\ndata_catch <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, cpue_kgkm2) \n\n# zero-fill data (imperfectly, but effective for this example)\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\"}offset=0&limit=10000'))\ndata_haul <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, latitude_dd, longitude_dd) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>% \n dplyr::distinct()\n\ndata <- dplyr::left_join(data_haul, data_catch) %>% \n dplyr::mutate(cpue_kgkm2 = ifelse(is.na(cpue_kgkm2), 0, cpue_kgkm2), \n dplyr::across(dplyr::everything(), as.numeric)) \n\nflextable::flextable(data[1:3,]) %>% \n flextable::theme_zebra() \n```\n\n::: {.cell-output-display}\n```{=html}\n
stratum
station
latitude_dd
longitude_dd
cpue_kgkm2
81
61.66434
-172.2655
2,895.258
81
62.33740
-173.1702
1,235.545
70
62.03713
-171.6528
0.000
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n CPUE_KGHA = data$cpue_kgkm2, # calculates the same, regardless of units. \n LATITUDE = data$latitude_dd, \n LONGITUDE = data$longitude_dd, \n region = \"bs.north\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n\n```{.r .cell-code}\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific cod\\nCPUE (kg/km2)\"))\n```\n\n::: {.cell-output-display}\n![Ex. 7: Visualize CPUE data in distribution map. ](foss-api-r_files/figure-html/test-7-fig-1.png){width=672}\n:::\n:::\n",
+ "markdown": "---\ntitle: Access via API and R\n---\n\n\n\n\nAn application programming interface (API) is a way for two or more computer programs to communicate with each other.\n\nMore information about how to amend API links can be found [here](https://docs.oracle.com/en/database/oracle/oracle-rest-data-services/22.3/books.html#AELIG90103/). Useful introductions to using APIs in `R` can be found [here](https://www.dataquest.io/blog/r-api-tutorial/). \n\n## Ex. 1: Load the first 25 rows (default) of data\n\n\n::: {.cell tbl-cap='Ex. 1: Load the first 25 rows (default) of data. '}\n\n```{.r .cell-code}\n # install.packages(c(\"httr\", \"jsonlite\"))\nlibrary(httr)\nlibrary(jsonlite)\nlibrary(dplyr)\n\n # link to the API\napi_link <- \"https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/\"\n\nres <- httr::GET(url = api_link)\n # res # Test connection\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n # names(data)\ntibble::as_tibble(data$items) %>% \n dplyr::mutate_if(is.character, type.convert, as.is = TRUE) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n head(3) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"cruise\", \"species_code\", \"tsn\", \"ak_survey_id\"), big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
survey
survey_id
cruise
haul
stratum
station
vessel_name
vessel_id
date_time
latitude_dd
longitude_dd
species_code
common_name
scientific_name
taxon_confidence
cpue_kgha
cpue_kgkm2
cpue_kg1000km2
cpue_noha
cpue_nokm2
cpue_no1000km2
weight_kg
count
bottom_temperature_c
surface_temperature_c
depth_m
distance_fished_km
net_width_m
net_height_m
area_swept_ha
duration_hr
tsn
ak_survey_id
links
2002
AI
Aleutian Islands Bottom Trawl Survey
52
200201
6
722
307-63
Vesteraalen
94
05/17/2002 18:56:58
53.737
-167.016
95020
feathery bryozoan
Eucratea loricata
Low
0.017
1.749
1,749.445
0.044
0
4.1
5.3
187
1.561
16.112
7.25
2.515
0.28
155809
1917453
[[data.frame]]
2002
AI
Aleutian Islands Bottom Trawl Survey
52
200201
6
722
307-63
Vesteraalen
94
05/17/2002 18:56:58
53.737
-167.016
79000
squid unid.
Decapodiformes
High
0.022
2.227
2,226.567
3.181
318.081
318,080.93
0.056
8
4.1
5.3
187
1.561
16.112
7.25
2.515
0.28
1917454
[[data.frame]]
2002
AI
Aleutian Islands Bottom Trawl Survey
52
200201
6
722
307-63
Vesteraalen
94
05/17/2002 18:56:58
53.737
-167.016
24191
shortfin eelpout
Lycodes brevipes
High
0.036
3.578
3,578.410
0.795
79.520
79,520.23
0.090
2
4.1
5.3
187
1.561
16.112
7.25
2.515
0.28
165258
1917455
[[data.frame]]
\n```\n:::\n:::\n\n\n## Ex. 2: Load the first 10000 rows of data\n\n\n::: {.cell tbl-cap='Ex. 2: Load the first 10000 rows of data. '}\n\n```{.r .cell-code}\n# Not run because too big:\nres <- httr::GET(url = paste0(api_link, \"?offset=0&limit=10000\"))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\nprint(paste0(\"rows: \", dim(data$items)[1], \"; cols: \", dim(data$items)[2]))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"rows: 10000; cols: 36\"\n```\n:::\n:::\n\n\n## Ex. 3: Filter by Year\n\nShow all the data greater than the year 2020. \n\n\n::: {.cell tbl-cap='Ex. 3: Filter by Year. '}\n\n```{.r .cell-code}\nres <- httr::GET(url = paste0(api_link, '?q={\"year\":{\"$gt\":2020}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
stratum
species_code
cpue_kgkm2
2022
AI
793
80540
0.361
2022
AI
793
401
0.903
2022
AI
793
20006
1.661
\n```\n:::\n:::\n\n\n## Ex. 4: Filter by species name\n\nShow all the data where the product name contains pollock Please note that here the word pollock is case sensitive.\n\nThe notation for finding a string is to use % around it. Since % is a reserved character in a URL, you have to replace `%` with `%25`. \n\n\n::: {.cell tbl-cap='Ex. 4: Filter by species name. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
stratum
species_code
cpue_kgkm2
2002
AI
722
21740
775.322
2002
AI
722
21740
10,685.806
2002
AI
721
21740
0.640
\n```\n:::\n:::\n\n\n## Ex. 5: Combination of year and name filters\n\nShow all the data where years > 2020 and the product name contains pollock\n\n\n::: {.cell tbl-cap='Ex. 5: Combination of year and name filters. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, \n '?q={\"year\":{\"$gt\":2020},\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
stratum
species_code
cpue_kgkm2
2022
AI
793
21740
7,853.632
2022
AI
721
21740
7,235.010
2022
AI
722
21740
22,754.334
\n```\n:::\n:::\n\n\n## Ex. 6: Combination of year, srvy, stratum\n\nShow all the data where year = 1989, srvy = \"EBS\", and stratum is not equal to 81\n\n\n::: {.cell tbl-cap='Ex. 6: Combination of year, srvy, stratum. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":1989,\"srvy\":\"EBS\",\"stratum\":{\"$ne\":\"81\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=html}\n
year
srvy
stratum
species_code
cpue_kgkm2
1989
EBS
10
66548
1.164
1989
EBS
10
69322
1.164
1989
EBS
10
43000
2.353
\n```\n:::\n:::\n\n\n## Ex. 7: Visualize CPUE data in distribution map\n\nPacific cod catch-per-unit-effort estimates for NBS in 2021 and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). \n\n\n::: {.cell tbl-cap='Ex. 7: Visualize CPUE data in distribution map. '}\n\n```{.r .cell-code}\n# res <- httr::GET(\n# url = paste0(api_link, \"?offset=0&limit=10000\"), \n# query = list(year = 2021, srvy = \"EBS\", species_code = 30060))\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\",\"species_code\":21720}'))\ndata_catch <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, cpue_kgkm2) \n\n# zero-fill data (imperfectly, but effective for this example)\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\"}offset=0&limit=10000'))\ndata_haul <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, latitude_dd, longitude_dd) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>% \n dplyr::distinct()\n\ndata <- dplyr::left_join(data_haul, data_catch) %>% \n dplyr::mutate(cpue_kgkm2 = ifelse(is.na(cpue_kgkm2), 0, cpue_kgkm2), \n dplyr::across(dplyr::everything(), as.numeric)) \n\nflextable::flextable(data[1:3,]) %>% \n flextable::theme_zebra() \n```\n\n::: {.cell-output-display}\n```{=html}\n
stratum
station
latitude_dd
longitude_dd
cpue_kgkm2
81
61.66434
-172.2655
2,895.258
81
62.33740
-173.1702
1,235.545
70
62.03713
-171.6528
0.000
\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n CPUE_KGHA = data$cpue_kgkm2, # calculates the same, regardless of units. \n LATITUDE = data$latitude_dd, \n LONGITUDE = data$longitude_dd, \n region = \"bs.north\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000))$plot + # 20x20km grid\n ggplot2::guides(fill=guide_legend(title = \"Pacific cod\\nCPUE (kg/km2)\"))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n:::\n",
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- "foss-api-r_files"
+ "foss-api-r_files\\figure-html"
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diff --git a/_freeze/content/foss-api-r/execute-results/tex.json b/_freeze/content/foss-api-r/execute-results/tex.json
index b55b560..7218577 100644
--- a/_freeze/content/foss-api-r/execute-results/tex.json
+++ b/_freeze/content/foss-api-r/execute-results/tex.json
@@ -1,7 +1,7 @@
{
- "hash": "2eb6f941b64730743e5c01ae71e268dd",
+ "hash": "9b419c3eb2cb72acb9b71d1fec7c1dac",
"result": {
- "markdown": "---\ntitle: Access via API and R\n---\n\n\n\n\n\nAn application programming interface (API) is a way for two or more computer programs to communicate with each other.\n\nMore information about how to amend API links can be found [here](https://docs.oracle.com/en/database/oracle/oracle-rest-data-services/22.3/books.html#AELIG90103/). Useful introductions to using APIs in `R` can be found [here](https://www.dataquest.io/blog/r-api-tutorial/). \n\n## Ex. 1: Load the first 25 rows (default) of data\n\n\n\n::: {.cell tbl-cap='Ex. 1: Load the first 25 rows (default) of data. '}\n\n```{.r .cell-code}\n # install.packages(c(\"httr\", \"jsonlite\"))\nlibrary(httr)\nlibrary(jsonlite)\nlibrary(dplyr)\n\n # link to the API\napi_link <- \"https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/\"\n\nres <- httr::GET(url = api_link)\n # res # Test connection\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n # names(data)\ntibble::as_tibble(data$items) %>% \n dplyr::mutate_if(is.character, type.convert, as.is = TRUE) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n head(3) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"cruise\", \"species_code\", \"tsn\", \"ak_survey_id\"), big.mark = \"\")\n```\n\n::: 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0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{318,080.93}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.056}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{8}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.1}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{5.3}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{187}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.561}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{16.112}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7.25}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2.515}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.28}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1917454}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{[[data.frame]]}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2002}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Aleutian\\ Islands\\ Bottom\\ Trawl\\ Survey}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{52}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{200201}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{6}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{722}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{307-63}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Vesteraalen}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{94}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{05/17/2002\\ 18:56:58}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{53.737}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-167.016}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{24191}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{shortfin\\ eelpout}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Lycodes\\ brevipes}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{High}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.036}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3.578}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3,578.410}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.795}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{79.520}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{79,520.23}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.090}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.1}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{5.3}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{187}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.561}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{16.112}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7.25}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2.515}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.28}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{165258}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1917455}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{[[data.frame]]}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 2: Load the first 10000 rows of data\n\n\n\n::: {.cell tbl-cap='Ex. 2: Load the first 10000 rows of data. '}\n\n```{.r .cell-code}\n# Not run because too big:\nres <- httr::GET(url = paste0(api_link, \"?offset=0&limit=10000\"))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\nprint(paste0(\"rows: \", dim(data$items)[1], \"; cols: \", dim(data$items)[2]))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"rows: 10000; cols: 36\"\n```\n:::\n:::\n\n\n\n## Ex. 3: Filter by Year\n\nShow all the data greater than the year 2020. \n\n\n\n::: {.cell tbl-cap='Ex. 3: Filter by Year. '}\n\n```{.r .cell-code}\nres <- httr::GET(url = paste0(api_link, '?q={\"year\":{\"$gt\":2020}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{793}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{80540}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.361}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{793}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{401}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.903}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{793}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{20006}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.661}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 4: Filter by species name\n\nShow all the data where the product name contains pollock Please note that here the word pollock is case sensitive.\n\nThe notation for finding a string is to use % around it. Since % is a reserved character in a URL, you have to replace `%` with `%25`. \n\n\n\n::: {.cell tbl-cap='Ex. 4: Filter by species name. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2002}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{722}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{775.322}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2002}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{722}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{10,685.806}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2002}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{721}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.640}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 5: Combination of year and name filters\n\nShow all the data where years > 2020 and the product name contains pollock\n\n\n\n::: {.cell tbl-cap='Ex. 5: Combination of year and name filters. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, \n '?q={\"year\":{\"$gt\":2020},\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{793}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,853.632}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{721}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,235.010}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{722}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{22,754.334}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 6: Combination of year, srvy, stratum\n\nShow all the data where year = 1989, srvy = \"EBS\", and stratum is not equal to 81\n\n\n\n::: {.cell tbl-cap='Ex. 6: Combination of year, srvy, stratum. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":1989,\"srvy\":\"EBS\",\"stratum\":{\"$ne\":\"81\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1989}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{EBS}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{10}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{66548}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.164}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1989}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{EBS}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{10}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{69322}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.164}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1989}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{EBS}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{10}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{43000}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2.353}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 7: Visualize CPUE data in distribution map\n\nPacific cod catch-per-unit-effort estimates for NBS in 2021 and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). \n\n\n\n::: {.cell tbl-cap='Ex. 7: Visualize CPUE data in distribution map. '}\n\n```{.r .cell-code}\n# res <- httr::GET(\n# url = paste0(api_link, \"?offset=0&limit=10000\"), \n# query = list(year = 2021, srvy = \"EBS\", species_code = 30060))\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\",\"species_code\":21720}'))\ndata_catch <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, cpue_kgkm2) \n\n# zero-fill data (imperfectly, but effective for this example)\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\"}offset=0&limit=10000'))\ndata_haul <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, latitude_dd, longitude_dd) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>% \n dplyr::distinct()\n\ndata <- dplyr::left_join(data_haul, data_catch) %>% \n dplyr::mutate(cpue_kgkm2 = ifelse(is.na(cpue_kgkm2), 0, cpue_kgkm2), \n dplyr::across(dplyr::everything(), as.numeric)) \n\nflextable::flextable(data[1:3,]) %>% \n flextable::theme_zebra() \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{station}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{latitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{longitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{station}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{latitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{longitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{81}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{61.66434}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-172.2655}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2,895.258}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{81}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{62.33740}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-173.1702}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,235.545}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{70}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{62.03713}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-171.6528}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.000}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n CPUE_KGHA = data$cpue_kgkm2, # calculates the same, regardless of units. \n LATITUDE = data$latitude_dd, \n LONGITUDE = data$longitude_dd, \n region = \"bs.north\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n\n```{.r .cell-code}\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific cod\\nCPUE (kg/km2)\"))\n```\n\n::: {.cell-output-display}\n![Ex. 7: Visualize CPUE data in distribution map. ](foss-api-r_files/figure-pdf/test-7-fig-1.pdf){fig-pos='H'}\n:::\n:::\n",
+ "markdown": "---\ntitle: Access via API and R\n---\n\n\n\n\n\nAn application programming interface (API) is a way for two or more computer programs to communicate with each other.\n\nMore information about how to amend API links can be found [here](https://docs.oracle.com/en/database/oracle/oracle-rest-data-services/22.3/books.html#AELIG90103/). Useful introductions to using APIs in `R` can be found [here](https://www.dataquest.io/blog/r-api-tutorial/). \n\n## Ex. 1: Load the first 25 rows (default) of data\n\n\n\n::: {.cell tbl-cap='Ex. 1: Load the first 25 rows (default) of data. '}\n\n```{.r .cell-code}\n # install.packages(c(\"httr\", \"jsonlite\"))\nlibrary(httr)\nlibrary(jsonlite)\nlibrary(dplyr)\n\n # link to the API\napi_link <- \"https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/\"\n\nres <- httr::GET(url = api_link)\n # res # Test connection\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n # names(data)\ntibble::as_tibble(data$items) %>% \n dplyr::mutate_if(is.character, type.convert, as.is = TRUE) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n head(3) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"cruise\", \"species_code\", \"tsn\", \"ak_survey_id\"), big.mark = \"\")\n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{survey}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{survey\\_id}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cruise}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{haul}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{station}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{vessel\\_name}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{vessel\\_id}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{date\\_time}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{latitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{longitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{common\\_name}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{scientific\\_name}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{taxon\\_confidence}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgha}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kg1000km2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_noha}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_nokm2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_no1000km2}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{weight\\_kg}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{count}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{bottom\\_temperature\\_c}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{surface\\_temperature\\_c}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{depth\\_m}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{distance\\_fished\\_km}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{net\\_width\\_m}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{net\\_height\\_m}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{area\\_swept\\_ha}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{duration\\_hr}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{tsn}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{ak\\_survey\\_id}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{links}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 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0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{318,080.93}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.056}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{8}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.1}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{5.3}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{187}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.561}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{16.112}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7.25}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2.515}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.28}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1917454}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{[[data.frame]]}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2002}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Aleutian\\ Islands\\ Bottom\\ Trawl\\ Survey}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{52}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{200201}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{6}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{722}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{307-63}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Vesteraalen}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{94}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{05/17/2002\\ 18:56:58}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{53.737}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-167.016}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{24191}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{shortfin\\ eelpout}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{Lycodes\\ brevipes}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{High}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.036}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3.578}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{3,578.410}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.795}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{79.520}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{79,520.23}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.090}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{4.1}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{5.3}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{187}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.561}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{16.112}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7.25}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2.515}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.28}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{165258}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1917455}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{[[data.frame]]}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 2: Load the first 10000 rows of data\n\n\n\n::: {.cell tbl-cap='Ex. 2: Load the first 10000 rows of data. '}\n\n```{.r .cell-code}\n# Not run because too big:\nres <- httr::GET(url = paste0(api_link, \"?offset=0&limit=10000\"))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\nprint(paste0(\"rows: \", dim(data$items)[1], \"; cols: \", dim(data$items)[2]))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"rows: 10000; cols: 36\"\n```\n:::\n:::\n\n\n\n## Ex. 3: Filter by Year\n\nShow all the data greater than the year 2020. \n\n\n\n::: {.cell tbl-cap='Ex. 3: Filter by Year. '}\n\n```{.r .cell-code}\nres <- httr::GET(url = paste0(api_link, '?q={\"year\":{\"$gt\":2020}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{793}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{80540}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.361}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{793}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{401}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.903}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{793}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{20006}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.661}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 4: Filter by species name\n\nShow all the data where the product name contains pollock Please note that here the word pollock is case sensitive.\n\nThe notation for finding a string is to use % around it. Since % is a reserved character in a URL, you have to replace `%` with `%25`. \n\n\n\n::: {.cell tbl-cap='Ex. 4: Filter by species name. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2002}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{722}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{775.322}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2002}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{722}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{10,685.806}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2002}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{721}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.640}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 5: Combination of year and name filters\n\nShow all the data where years > 2020 and the product name contains pollock\n\n\n\n::: {.cell tbl-cap='Ex. 5: Combination of year and name filters. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, \n '?q={\"year\":{\"$gt\":2020},\"common_name\":{\"$like\":\"%25pollock%25\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{793}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,853.632}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{721}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{7,235.010}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2022}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{AI}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{722}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{21740}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{22,754.334}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 6: Combination of year, srvy, stratum\n\nShow all the data where year = 1989, srvy = \"EBS\", and stratum is not equal to 81\n\n\n\n::: {.cell tbl-cap='Ex. 6: Combination of year, srvy, stratum. '}\n\n```{.r .cell-code}\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":1989,\"srvy\":\"EBS\",\"stratum\":{\"$ne\":\"81\"}}'))\ndata <- jsonlite::fromJSON(base::rawToChar(res$content))\n\nas_tibble(data$items) %>% \n mutate_if(is.character, type.convert, as.is = TRUE) %>%\n head(3) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>%\n dplyr::select(year, srvy, stratum, species_code, cpue_kgkm2) %>%\nflextable::flextable() %>%\n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = c(\"year\", \"species_code\"), big.mark = \"\") \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{year}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{srvy}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species\\_code}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1989}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{EBS}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{10}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{66548}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.164}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1989}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{EBS}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{10}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{69322}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1.164}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1989}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{EBS}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{10}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{43000}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2.353}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n## Ex. 7: Visualize CPUE data in distribution map\n\nPacific cod catch-per-unit-effort estimates for NBS in 2021 and map constructed using [`akgfmaps`](https://github.com/afsc-gap-products/akgfmaps). \n\n\n\n::: {.cell tbl-cap='Ex. 7: Visualize CPUE data in distribution map. '}\n\n```{.r .cell-code}\n# res <- httr::GET(\n# url = paste0(api_link, \"?offset=0&limit=10000\"), \n# query = list(year = 2021, srvy = \"EBS\", species_code = 30060))\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\",\"species_code\":21720}'))\ndata_catch <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, cpue_kgkm2) \n\n# zero-fill data (imperfectly, but effective for this example)\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\"}offset=0&limit=10000'))\ndata_haul <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, latitude_dd, longitude_dd) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>% \n dplyr::distinct()\n\ndata <- dplyr::left_join(data_haul, data_catch) %>% \n dplyr::mutate(cpue_kgkm2 = ifelse(is.na(cpue_kgkm2), 0, cpue_kgkm2), \n dplyr::across(dplyr::everything(), as.numeric)) \n\nflextable::flextable(data[1:3,]) %>% \n flextable::theme_zebra() \n```\n\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}|p{0.75in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{station}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{latitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{longitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{stratum}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{station}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{latitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{longitude\\_dd}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{cpue\\_kgkm2}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{81}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{61.66434}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-172.2655}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{2,895.258}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{81}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{62.33740}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-173.1702}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{1,235.545}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{70}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{62.03713}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{-171.6528}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.75in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{0.000}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n CPUE_KGHA = data$cpue_kgkm2, # calculates the same, regardless of units. \n LATITUDE = data$latitude_dd, \n LONGITUDE = data$longitude_dd, \n region = \"bs.north\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000))$plot + # 20x20km grid\n ggplot2::guides(fill=guide_legend(title = \"Pacific cod\\nCPUE (kg/km2)\"))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n```\n:::\n:::\n",
"supporting": [
"foss-api-r_files\\figure-pdf"
],
diff --git a/_freeze/content/intro-news/execute-results/docx.json b/_freeze/content/intro-news/execute-results/docx.json
new file mode 100644
index 0000000..424c9a3
--- /dev/null
+++ b/_freeze/content/intro-news/execute-results/docx.json
@@ -0,0 +1,20 @@
+{
+ "hash": "0aca6a944b7528c3b0940be2bddef95f",
+ "result": {
+ "markdown": "---\ntitle: News\n---\n\n\n\n\n## News/change logs\n\n\n\n\n::: {.cell}\n\n:::\n\n\n\n\n -- [Run 2023-06-01 gapindex v2.1.0](C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-06-01_v2-1-0.txt): Initial compiling and planning notes\n\n -- [GAP_PRODUCTS ChangeLog (last produced on 2023-11-14) using gapindex v2.1.1](C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-11-14_v2-1-1.txt): A new version of gapindex (v2.1.1) was used to produced these data. There was a slight change to how subarea biomass totals are calculated. The modified biomass records reflect this change. New 2022 otolith data were available since the last iteration of the GAP_PRODUCTS for Aleutian Island Pacific ocean perch and northern rockifsh and Eastern Bering Sea northern rock sole. Zero-filled CPUE records for four GOA species codes (SPECIES_CODE: 21210, 30010, 30360, 77102, 98101) were added due to how the 1990 data were integrated in the last production run of GAP_PRODUCTS. Two Arctic cod (SPECIES_CODE: 21725) and one plain sculpin (SPECIES_CODE: 21371) count records were modified in the NBS data, which changes the numerical CPUE estimates for those hauls which changes the estimated population abundance and size composition for those species.\n\n -- [GAP_PRODUCTS ChangeLog (last produced on 2023-11-17) using gapindex v2.1.2](C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-11-17.txt): A new version of gapindex ([v2.1.2](https://github.com/afsc-gap-products/gapindex/releases/tag/v2.1.2)) was used to produced these data. There was a slight change to how subarea biomass totals are calculated that was not fully addressed in v2.1.1. The modified biomass records reflect this change.\n\n",
+ "supporting": [
+ "intro-news_files"
+ ],
+ "filters": [
+ "rmarkdown/pagebreak.lua"
+ ],
+ "includes": {},
+ "engineDependencies": {
+ "knitr": [
+ "{\"type\":\"list\",\"attributes\":{},\"value\":[]}"
+ ]
+ },
+ "preserve": null,
+ "postProcess": false
+ }
+}
\ No newline at end of file
diff --git a/_freeze/content/intro-news/execute-results/html.json b/_freeze/content/intro-news/execute-results/html.json
new file mode 100644
index 0000000..55ce5af
--- /dev/null
+++ b/_freeze/content/intro-news/execute-results/html.json
@@ -0,0 +1,16 @@
+{
+ "hash": "0aca6a944b7528c3b0940be2bddef95f",
+ "result": {
+ "markdown": "---\ntitle: News\n---\n\n\n## News/change logs\n\n\n::: {.cell}\n\n:::\n\n\n -- [Run 2023-06-01 gapindex v2.1.0](C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-06-01_v2-1-0.txt): Initial compiling and planning notes\n\n -- [GAP_PRODUCTS ChangeLog (last produced on 2023-11-14) using gapindex v2.1.1](C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-11-14_v2-1-1.txt): A new version of gapindex (v2.1.1) was used to produced these data. There was a slight change to how subarea biomass totals are calculated. The modified biomass records reflect this change. New 2022 otolith data were available since the last iteration of the GAP_PRODUCTS for Aleutian Island Pacific ocean perch and northern rockifsh and Eastern Bering Sea northern rock sole. Zero-filled CPUE records for four GOA species codes (SPECIES_CODE: 21210, 30010, 30360, 77102, 98101) were added due to how the 1990 data were integrated in the last production run of GAP_PRODUCTS. Two Arctic cod (SPECIES_CODE: 21725) and one plain sculpin (SPECIES_CODE: 21371) count records were modified in the NBS data, which changes the numerical CPUE estimates for those hauls which changes the estimated population abundance and size composition for those species.\n\n -- [GAP_PRODUCTS ChangeLog (last produced on 2023-11-17) using gapindex v2.1.2](C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-11-17.txt): A new version of gapindex ([v2.1.2](https://github.com/afsc-gap-products/gapindex/releases/tag/v2.1.2)) was used to produced these data. There was a slight change to how subarea biomass totals are calculated that was not fully addressed in v2.1.1. The modified biomass records reflect this change.\n\n",
+ "supporting": [
+ "intro-news_files"
+ ],
+ "filters": [
+ "rmarkdown/pagebreak.lua"
+ ],
+ "includes": {},
+ "engineDependencies": {},
+ "preserve": {},
+ "postProcess": true
+ }
+}
\ No newline at end of file
diff --git a/_freeze/content/intro-news/execute-results/tex.json b/_freeze/content/intro-news/execute-results/tex.json
new file mode 100644
index 0000000..a5443d3
--- /dev/null
+++ b/_freeze/content/intro-news/execute-results/tex.json
@@ -0,0 +1,20 @@
+{
+ "hash": "0aca6a944b7528c3b0940be2bddef95f",
+ "result": {
+ "markdown": "---\ntitle: News\n---\n\n\n\n## News/change logs\n\n\n\n::: {.cell}\n\n:::\n\n\n\n -- [Run 2023-06-01 gapindex v2.1.0](C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-06-01_v2-1-0.txt): Initial compiling and planning notes\n\n -- [GAP_PRODUCTS ChangeLog (last produced on 2023-11-14) using gapindex v2.1.1](C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-11-14_v2-1-1.txt): A new version of gapindex (v2.1.1) was used to produced these data. There was a slight change to how subarea biomass totals are calculated. The modified biomass records reflect this change. New 2022 otolith data were available since the last iteration of the GAP_PRODUCTS for Aleutian Island Pacific ocean perch and northern rockifsh and Eastern Bering Sea northern rock sole. Zero-filled CPUE records for four GOA species codes (SPECIES_CODE: 21210, 30010, 30360, 77102, 98101) were added due to how the 1990 data were integrated in the last production run of GAP_PRODUCTS. Two Arctic cod (SPECIES_CODE: 21725) and one plain sculpin (SPECIES_CODE: 21371) count records were modified in the NBS data, which changes the numerical CPUE estimates for those hauls which changes the estimated population abundance and size composition for those species.\n\n -- [GAP_PRODUCTS ChangeLog (last produced on 2023-11-17) using gapindex v2.1.2](C:/Users/emily.markowitz/Work/projects/gap_products/content/intro-news/2023-11-17.txt): A new version of gapindex ([v2.1.2](https://github.com/afsc-gap-products/gapindex/releases/tag/v2.1.2)) was used to produced these data. There was a slight change to how subarea biomass totals are calculated that was not fully addressed in v2.1.1. The modified biomass records reflect this change.\n\n",
+ "supporting": [
+ "intro-news_files"
+ ],
+ "filters": [
+ "rmarkdown/pagebreak.lua"
+ ],
+ "includes": {},
+ "engineDependencies": {
+ "knitr": [
+ "{\"type\":\"list\",\"attributes\":{},\"value\":[]}"
+ ]
+ },
+ "preserve": null,
+ "postProcess": false
+ }
+}
\ No newline at end of file
diff --git a/content/akfin-oracle-sql-r.qmd b/content/akfin-oracle-sql-r.qmd
index f08d8da..e2a856f 100644
--- a/content/akfin-oracle-sql-r.qmd
+++ b/content/akfin-oracle-sql-r.qmd
@@ -37,7 +37,7 @@ library(magrittr)
library(dplyr)
```
-### Ex. Select all data from a table
+### Ex. Select all data from tables
You can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the `R` environment.
@@ -72,101 +72,57 @@ for (i in 1:length(locations)) {
}
```
+### Ex. CPUE for all EBS and NBS stations with associated haul, cruise, and species information.
+
```{r}
#| label: test-7
#| message: false
#| warning: false
-#| echo: false
-#| eval: false
-
-# ### Ex. Summary table for EBS and NBS arrowtooth flounder (10110), Bering flounder (10140), and Bering skate (435)
-#
-# - Number hauls where species were observed (N_HAULS)
-# - Number of length measurements that were colelcted for this species (N_LENGTHS)
-#
-#
+#| echo: true
+#| tbl-cap: "Ex.: CPUE for all EBS and NBS stations with associated haul, cruise, and species information. "
-dat <- RODBC::sqlQuery(channel = channel,
- query =
+a <- RODBC::sqlQuery(channel = channel, # NOT RACEBASE.HAUL
+ query = paste0(
"
-- Select columns for output data
SELECT
-bb.SPECIES_CODE,
-bb.YEAR,
-bb.SURVEY_DEFINITION_ID,
-bb.AREA_ID,
-SUM(bb.N_HAUL) AS N_HAULS, -- Number hauls where species were observed
-SUM(bb.N_LENGTH) AS N_LENGTHS -- Number of length measurements that were colelcted for this species
+cr.CRUISEJOIN,
+cr.CRUISE,
+cr.YEAR,
+cr.SURVEY_DEFINITION_ID,
+cr.SURVEY_NAME,
+cr.VESSEL_ID,
+cr.VESSEL_NAME,
+cp.HAULJOIN,
+cp.SPECIES_CODE,
+tt.SPECIES_NAME,
+tt.COMMON_NAME,
+cp.WEIGHT_KG,
+cp.COUNT,
+cp.AREA_SWEPT_KM2,
+cp.CPUE_KGKM2,
+cp.CPUE_NOKM2,
+hh.HAUL,
+hh.STATION
-- Identify what tables to pull data from
-FROM GAP_PRODUCTS.AKFIN_BIOMASS bb
-
--- Filter data results
-WHERE bb.SPECIES_CODE IN (10110, 435, 10140)
-AND bb.YEAR IN (2022, 2023)
-AND bb.AREA_ID IN (99900, 99902)
-GROUP BY bb.SPECIES_CODE, bb.YEAR, bb.SURVEY_DEFINITION_ID, bb.AREA_ID
-ORDER BY bb.SURVEY_DEFINITION_ID, bb.YEAR, bb.SPECIES_CODE;")
-```
-
-```{r}
-#| label: test-7-workspace
-#| message: false
-#| warning: false
-#| echo: false
-#| eval: false
+FROM GAP_PRODUCTS.AKFIN_HAUL hh
+LEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cr
+ON hh.CRUISEJOIN = cr.CRUISEJOIN
+LEFT JOIN GAP_PRODUCTS.AKFIN_CPUE cp
+ON hh.HAULJOIN = cp.HAULJOIN
+LEFT JOIN GAP_PRODUCTS.TAXONOMIC_CLASSIFICATION tt
+ON cp.SPECIES_CODE = tt.SPECIES_CODE
-# Workspace
-
-# --COUNT(N_LENGTH) AS N_HAULS_W_LENGTH, -- Number of hauls where lengths for this species were collected
-# --HAULS_W_OTOLITHS, -- Number of hauls where otoliths were collected for this species were collected
-# --HAULS_W_AGES, -- Number of hauls where otoliths were collected for this species were collected
-# --NUM_OTOLITHS,
-# -- NUM_AGES
-
-# dat_specimen <- RODBC::sqlQuery(channel = channel,
-# query =
-# "SELECT
-# ss.SPECIES_CODE,
-# cc.YEAR,
-# cc.SURVEY_DEFINITION_ID,
-# aa.AREA_ID,
-# COUNT(ss.AGE_YEARS) AS N_AGES -- The number of age specimens collected
-# FROM GAP_PRODUCTS.AKFIN_SPECIMEN ss
-# LEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh
-# ON ss.HAULJOIN = hh.HAULJOIN
-# LEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc
-# ON hh.CRUISEJOIN = cc.CRUISEJOIN
-# LEFT JOIN GAP_PRODUCTS.AKFIN_STRATUM_GROUPS aa
-# ON hh.STRATUM = aa.STRATUM
-# AND cc.SURVEY_DEFINITION_ID = aa.SURVEY_DEFINITION_ID
-# WHERE ss.specimen_sample_type = 1
-# AND ss.SPECIES_CODE IN (10110, 435, 10140)
-# AND cc.YEAR IN (2022, 2023)
-# AND bb.AREA_ID IN (99900, 99902)
-# GROUP BY ss.SPECIES_CODE, cc.YEAR, cc.SURVEY_DEFINITION_ID, aa.AREA_ID
-# ORDER BY cc.SURVEY_DEFINITION_ID, cc.YEAR, ss.SPECIES_CODE;")
-#
-# dat <- dplyr::full_join(dat_specimen, dat_haul)
+-- Filter for EBS and NBS observations
+WHERE SURVEY_DEFINITION_ID IN (143, 98) -- 143 NBS, 98 EBS
+AND tt.SURVEY_SPECIES = 1
-```
+-- Only return the first 3 rows because otherwise this would be a huge table!
+FETCH FIRST 3 ROWS ONLY;"))
-```{r}
-#| label: test-7-tbl
-#| tbl-cap: "Ex. 7: Summary table of Number hauls where species were observed (N_HAULS) and number of length measurements that were colelcted for this species (N_LENGTHS) for EBS and NBS, for arrowtooth flounder (10110), Bering flounder (10140), and Alaska skate (435). "
-#| message: false
-#| warning: false
-#| echo: false
-#| eval: false
-
-dat <- dat %>%
- dplyr::mutate(SPECIES_CODE = as.character(SPECIES_CODE),
- YEAR = as.character(YEAR),
- AREA_ID = as.character(AREA_ID)) %>%
- dplyr::relocate(SURVEY_DEFINITION_ID, YEAR, SPECIES_CODE) %>%
- dplyr::arrange(SPECIES_CODE)
+flextable::flextable(head(a)) %>% theme_zebra()
-flextable::flextable(dat) %>% theme_zebra()
```
### Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod.
@@ -309,7 +265,7 @@ dat <- RODBC::sqlQuery(channel = channel,
-- Manipulate data to join to
WITH FILTERED_STRATA AS (
SELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA
-WHERE TYPE in ('REGULATORY_AREA', 'REGION')
+WHERE AREA_TYPE in ('REGULATORY_AREA', 'REGION')
AND SURVEY_DEFINITION_ID = 47)
-- Select columns for output data
@@ -399,11 +355,11 @@ dat <- RODBC::sqlQuery(channel = channel,
WITH FILTERED_STRATA AS (
SELECT
AREA_ID,
-DESCRIPTION
+DESCRIPTION
-- Identify what tables to pull data from
FROM GAP_PRODUCTS.AKFIN_AREA
-WHERE TYPE = 'REGION'
+WHERE AREA_TYPE = 'REGION'
AND SURVEY_DEFINITION_ID = 52)
-- Select columns for output data
@@ -428,11 +384,12 @@ AND SIZECOMP.SPECIES_CODE IN (10261, 10262)")
dat0 <- dat %>%
janitor::clean_names() %>%
- dplyr::mutate(length_cm = length_mm/10)
-flextable::flextable(head(dat)) %>%
- theme_zebra() %>%
- flextable::colformat_num(x = ., j = "YEAR", big.mark = "")
-
+ dplyr::mutate(length_cm = length_mm/10) %>%
+ head() %>%
+ flextable::flextable() %>%
+ flextable::theme_zebra() %>%
+ flextable::colformat_num(x = ., j = "year", big.mark = "")
+dat0
```
@@ -447,8 +404,8 @@ flextable::flextable(head(dat)) %>%
library(ggridges)
figure <-
ggplot2::ggplot(
- data = dat0,
- mapping = aes(x = length_cm, y = as.factor(year), fill = stat(x))) +
+ data = dat,
+ mapping = aes(x = LENGTH_MM, y = as.factor(YEAR), fill = stat(x))) +
ggridges::theme_ridges(center_axis_labels = TRUE) +
ggridges::geom_density_ridges_gradient(scale = 4, show.legend = FALSE) +
ggplot2::scale_y_discrete(name = "Year", expand = c(0.01, 0)) +
@@ -478,7 +435,7 @@ SELECT
AREA_ID,
DESCRIPTION
FROM GAP_PRODUCTS.AKFIN_AREA
-WHERE TYPE = 'REGION' AND
+WHERE AREA_TYPE = 'REGION' AND
SURVEY_DEFINITION_ID = 98)
-- Select columns for output data
@@ -561,7 +518,7 @@ AREA_ID,
AREA_NAME,
DESCRIPTION
FROM GAP_PRODUCTS.AKFIN_AREA
-WHERE TYPE in ('STRATUM') AND
+WHERE AREA_TYPE in ('STRATUM') AND
SURVEY_DEFINITION_ID = 143)
-- Select columns for output data
diff --git a/content/functions.R b/content/functions.R
index 7fa7f68..5992bca 100644
--- a/content/functions.R
+++ b/content/functions.R
@@ -51,14 +51,14 @@ fix_metadata_table <- function(metadata_table0, name0, dir_out) {
metadata_table0 <- gsub(pattern = "\n", replacement = " ", x = metadata_table0)
metadata_table0 <- gsub(pattern = " ", replacement = " ", x = metadata_table0)
metadata_table0 <- gsub(pattern = " ", replacement = " ", x = metadata_table0)
-
+
readr::write_lines(
x = metadata_table0,
file = paste0(dir_out, name0, "_comment.txt")
)
# readr::write_lines(x = metadata_table,
# file = paste0(dir_out, a_name, "_metadata_table.txt", collapse="\n"))
-
+
return(metadata_table0)
}
@@ -73,7 +73,7 @@ update_metadata <- function(
update_metadata = TRUE,
share_with_all_users = TRUE) {
cat("Updating Metadata ...\n")
-
+
## Add column metadata
if (nrow(x = metadata_column) > 0) {
for (i in 1:nrow(x = metadata_column)) {
@@ -89,7 +89,7 @@ update_metadata <- function(
x = metadata_column$colname[i],
fixed = TRUE
)
-
+
RODBC::sqlQuery(
channel = channel,
query = paste0(
@@ -114,8 +114,8 @@ update_metadata <- function(
table_metadata, "';"
)
)
-
-
+
+
## ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Grant select access to all users
## ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -125,7 +125,7 @@ update_metadata <- function(
channel = channel,
query = paste0("SELECT * FROM all_users;")
)
-
+
for (iname in sort(all_schemas$USERNAME)) {
RODBC::sqlQuery(
channel = channel,
@@ -144,20 +144,20 @@ print_table_metadata <- function(channel, locations) {
b <- dplyr::bind_rows(
# tables
RODBC::sqlQuery(
- channel = channel,
- query = "SELECT table_name, comments
+ channel = channel,
+ query = "SELECT table_name, comments
FROM all_tab_comments
WHERE owner = 'GAP_PRODUCTS'
ORDER BY table_name") %>%
- data.frame(),
+ data.frame(),
# materialized view
- RODBC::sqlQuery(
- channel = channel,
- query = "SELECT *FROM user_mview_comments") %>%
- data.frame() %>%
- dplyr::rename(TABLE_NAME = MVIEW_NAME)
+ RODBC::sqlQuery(
+ channel = channel,
+ query = "SELECT *FROM user_mview_comments") %>%
+ data.frame() %>%
+ dplyr::rename(TABLE_NAME = MVIEW_NAME)
)
-
+
# Collect all column metadata for all table locations
str00 <- c()
for (i in 1:length(locations)) {
@@ -168,18 +168,18 @@ ORDER BY table_name") %>%
# strsplit(x = locations[i], split = ".", fixed = TRUE)[[1]]]
if (grepl(pattern = "This table was created by", x = metadata_table)) {
- metadata_table <- str_extract(metadata_table, "^.+(?= This table was created by)")
+ metadata_table <- str_extract(metadata_table, "^.+(?= This table was created by)")
}
- # Putting universal metadata language at top of page
+ # Putting universal metadata language at top of page
if (i == 1) {
if (!is.na(metadata_table) && length(metadata_table) != 0) {
data_usage <- str_extract(metadata_table, "This table was created by .+$")
if(!is.na(data_usage)){
- str00 <- paste0(
- "## Data usage \n\n", data_usage,
- "\n\n", "## Data tables", "\n\n") %>%
- str_replace("This table was", "These tables were") %>%
- str_replace("survey code books \\(https", "[survey code books]\\(https")
+ str00 <- paste0(
+ "## Data usage \n\n", data_usage,
+ "\n\n", "## Data tables", "\n\n") %>%
+ str_replace("This table was", "These tables were") %>%
+ str_replace("survey code books \\(https", "[survey code books]\\(https")
}
}
@@ -187,18 +187,18 @@ ORDER BY table_name") %>%
str00 <- paste0("## Data tables", "\n\n")
}
}
-
+
metadata_table <- ifelse(is.na(metadata_table) | length(metadata_table) == 0,
- "[There is currently no description for this table.]",
- metadata_table
+ "[There is currently no description for this table.]",
+ metadata_table
)
-
+
# temp <- file.size(here::here("data", paste0(locations[i], ".csv")))
temp_rows <- RODBC::sqlQuery(
channel = channel,
query = paste0("SELECT COUNT(*) FROM GAP_PRODUCTS.", locations[i], ";")
)
-
+
# temp_data <- RODBC::sqlQuery(channel = channel,
# query = paste0("SELECT *
# FROM ", locations[i], "
@@ -206,17 +206,17 @@ ORDER BY table_name") %>%
#
# temp_cols <- temp_data %>%
# ncol()
-
+
temp_colnames <- RODBC::sqlQuery(
channel = channel,
query = paste0("SELECT owner, column_name
- FROM all_tab_columns
- WHERE table_name = '", locations[i], "'
- AND owner = 'GAP_PRODUCTS';")
+FROM all_tab_columns
+WHERE table_name = '", locations[i], "'
+AND owner = 'GAP_PRODUCTS';")
)
-
+
temp_cols <- nrow(temp_colnames)
-
+
# get metadata
temp_data <- RODBC::sqlQuery(
channel = channel,
@@ -232,7 +232,7 @@ ORDER BY table_name") %>%
"Oracle data type" = metadata_datatype,
"Column description" = metadata_colname_desc
)
-
+
str00 <- paste0(
str00,
"### ", locations[i], "\n\n",
@@ -297,20 +297,20 @@ theme_flextable_nmfstm <- function(x,
if (!inherits(x, "flextable")) {
stop("theme_flextable_nmfstm supports only flextable objects.")
}
-
+
FitFlextableToPage <- function(x, pgwidth = 6) {
# https://stackoverflow.com/questions/57175351/flextable-autofit-in-a-rmarkdown-to-word-doc-causes-table-to-go-outside-page-mar
ft_out <- x %>% flextable::autofit()
-
+
ft_out <- flextable::width(ft_out, width = dim(ft_out)$widths * pgwidth / (flextable::flextable_dim(ft_out)$widths))
return(ft_out)
}
-
+
std_b <- officer::fp_border(width = 2, color = "grey10")
thin_b <- officer::fp_border(width = 0.5, color = "grey10")
-
+
x <- flextable::border_remove(x)
-
+
if (row_lines == TRUE) {
x <- flextable::hline(x = x, border = thin_b, part = "body")
}
@@ -330,8 +330,8 @@ theme_flextable_nmfstm <- function(x,
# unit = "in")
x <- FitFlextableToPage(x = x, pgwidth = pgwidth)
# x <- flextable::line_spacing(x = x, space = spacing, part = "all")
-
+
x <- flextable::fix_border_issues(x = x)
-
+
return(x)
}
diff --git a/content/intro-news.qmd b/content/intro-news.qmd
index 8682e59..96d05da 100644
--- a/content/intro-news.qmd
+++ b/content/intro-news.qmd
@@ -2,10 +2,6 @@
title: News
---
-## Future plans
-
-[insert text if section is appropriate]
-
## News/change logs
```{r news-source-pull}
diff --git a/docs/GAP-Production-Data-Documentation.docx b/docs/GAP-Production-Data-Documentation.docx
index 694a82d..bbb1180 100644
Binary files a/docs/GAP-Production-Data-Documentation.docx and b/docs/GAP-Production-Data-Documentation.docx differ
diff --git a/docs/GAP-Production-Data-Documentation.pdf b/docs/GAP-Production-Data-Documentation.pdf
index 5caf569..fa3472e 100644
Binary files a/docs/GAP-Production-Data-Documentation.pdf and b/docs/GAP-Production-Data-Documentation.pdf differ
diff --git a/docs/content/akfin-oracle-sql-r.html b/docs/content/akfin-oracle-sql-r.html
index 5a9f302..96c6e45 100644
--- a/docs/content/akfin-oracle-sql-r.html
+++ b/docs/content/akfin-oracle-sql-r.html
@@ -326,14 +326,15 @@
You can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the R environment.
locations <-c(
@@ -419,108 +420,159 @@
}
-
-
7.0.3 Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod.
+
+
7.0.3 Ex. CPUE for all EBS and NBS stations with associated haul, cruise, and species information.
-
dat <- RODBC::sqlQuery(channel = channel,
-query =
+
a <- RODBC::sqlQuery(channel = channel, # NOT RACEBASE.HAUL
+query =paste0("-- Select columns for output data
-SELECT
-HAULJOIN,
-SPECIES_CODE,
-STRATUM,
-LATITUDE_DD_START,
-LONGITUDE_DD_START,
-CPUE_KGKM2,
-GEAR_TEMPERATURE_C
-
--- Identify what tables to pull data from
-FROM GAP_PRODUCTS.AKFIN_CPUE cpue
-LEFT JOIN GAP_PRODUCTS.AKFIN_HAUL haul
-USING (HAULJOIN)
-
--- Filter for P. Cod observations
-WHERE SPECIES_CODE IN (21720)
-
--- Select all stratum within the area_id 919 (INPFC Shumagin region)
-AND haul.STRATUM IN
-(
-SELECT
-STRATUM
-FROM GAP_PRODUCTS.AKFIN_STRATUM_GROUPS
-WHERE AREA_ID = 919
-);")
+SELECT
+cr.CRUISEJOIN,
+cr.CRUISE,
+cr.YEAR,
+cr.SURVEY_DEFINITION_ID,
+cr.SURVEY_NAME,
+cr.VESSEL_ID,
+cr.VESSEL_NAME,
+cp.HAULJOIN,
+cp.SPECIES_CODE,
+tt.SPECIES_NAME,
+tt.COMMON_NAME,
+cp.WEIGHT_KG,
+cp.COUNT,
+cp.AREA_SWEPT_KM2,
+cp.CPUE_KGKM2,
+cp.CPUE_NOKM2,
+hh.HAUL,
+hh.STATION
+
+-- Identify what tables to pull data from
+FROM GAP_PRODUCTS.AKFIN_HAUL hh
+LEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cr
+ON hh.CRUISEJOIN = cr.CRUISEJOIN
+LEFT JOIN GAP_PRODUCTS.AKFIN_CPUE cp
+ON hh.HAULJOIN = cp.HAULJOIN
+LEFT JOIN GAP_PRODUCTS.TAXONOMIC_CLASSIFICATION tt
+ON cp.SPECIES_CODE = tt.SPECIES_CODE
+
+-- Filter for EBS and NBS observations
+WHERE SURVEY_DEFINITION_ID IN (143, 98) -- 143 NBS, 98 EBS
+AND tt.SURVEY_SPECIES = 1
+
+-- Only return the first 3 rows because otherwise this would be a huge table!
+FETCH FIRST 3 ROWS ONLY;"))
+
+flextable::flextable(head(a)) %>%theme_zebra()
+
+
+
Ex.: CPUE for all EBS and NBS stations with associated haul, cruise,
+and species information.
Ex. 8: CPUE for all stations contained in the Shumagin region
-(AREA_ID = 919).
HAULJOIN
STRATUM
SPECIES_CODE
LATITUDE_DD_START
LONGITUDE_DD_START
CPUE_KGKM2
GEAR_TEMPERATURE_C
-22,239
12
21720
55.43748
-160.1269
717.63085
4.5
-22,215
13
21720
54.58732
-161.1945
76.90763
4.3
-22,168
11
21720
54.45823
-163.0872
2,004.49628
4.9
-22,204
110
21720
54.51804
-160.7493
0.00000
4.7
-22,188
210
21720
54.38733
-159.6986
0.00000
5.5
-22,183
210
21720
54.09314
-161.6996
0.00000
5.3
+
Ex. 8: CPUE for all stations contained in the Shumagin region
+(AREA_ID = 919).
HAULJOIN
STRATUM
SPECIES_CODE
LATITUDE_DD_START
LONGITUDE_DD_START
CPUE_KGKM2
GEAR_TEMPERATURE_C
-22,270
13
21720
55.11515
-159.3512
209.28994
4.3
-22,250
13
21720
55.05143
-159.9679
8,700.92017
5.1
-22,238
13
21720
55.11365
-159.4264
363.17325
4.4
-22,214
13
21720
54.78608
-160.0008
63.71506
4.6
-22,202
111
21720
54.48341
-159.7261
618.72120
4.7
-22,247
112
21720
55.59093
-160.0740
114.73042
4.0
-
-
7.0.4 Ex. EBS Pacific Ocean perch CPUE and akgfmaps map
+
+
7.0.5 Ex. EBS Pacific Ocean perch CPUE and akgfmaps map
Pacific Ocean perch catch-per-unit-effort estimates for EBS in 2021 from GAP_PRODUCTS.AKFIN_CPUE and map constructed using akgfmaps. Here, we’ll use AKFIN HAUL and CRUISES data also included in this repo, for convenience, though they are very similar to their RACEBASE analogs.
-
dat <- RODBC::sqlQuery(channel = channel,
-query =
-"
--- Select columns for output data
-SELECT
-(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares
-hh.LATITUDE_DD_START LATITUDE,
-hh.LONGITUDE_DD_START LONGITUDE
-
--- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin
-FROM GAP_PRODUCTS.AKFIN_CPUE cp
-LEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh
-ON cp.HAULJOIN = hh.HAULJOIN
-
--- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID
-LEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc
-ON hh.CRUISEJOIN = cc.CRUISEJOIN
-
--- Filter data
-WHERE cp.SPECIES_CODE = 30060
-AND cc.SURVEY_DEFINITION_ID = 98
-AND cc.YEAR = 2021;")
+
dat <- RODBC::sqlQuery(channel = channel,
+query =
+"
+-- Select columns for output data
+SELECT
+(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares
+hh.LATITUDE_DD_START LATITUDE,
+hh.LONGITUDE_DD_START LONGITUDE
+
+-- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin
+FROM GAP_PRODUCTS.AKFIN_CPUE cp
+LEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh
+ON cp.HAULJOIN = hh.HAULJOIN
+
+-- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID
+LEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc
+ON hh.CRUISEJOIN = cc.CRUISEJOIN
+
+-- Filter data
+WHERE cp.SPECIES_CODE = 30060
+AND cc.SURVEY_DEFINITION_ID = 98
+AND cc.YEAR = 2021;")
-
flextable::flextable(head(dat)) %>%theme_zebra()
+
flextable::flextable(head(dat)) %>%theme_zebra()
-
Ex. 6: EBS Pacific Ocean perch CPUE and akgfmaps
-map.
CPUE_KGHA
LATITUDE
LONGITUDE
0.0000000
58.75863
-174.9285
0.2813533
57.32545
-173.3217
0.0000000
57.64161
-172.7963
0.0000000
59.67831
-172.5754
0.0000000
60.96936
-174.8760
0.0000000
58.64012
-173.5922
+
Ex. 6: EBS Pacific Ocean perch CPUE and akgfmaps
+map.
CPUE_KGHA
LATITUDE
LONGITUDE
0.00000000
60.67043
-178.0946
0.00000000
60.31361
-176.0138
0.00000000
60.35098
-175.3850
0.00000000
60.99712
-177.6638
0.00000000
60.96495
-176.2634
0.02416379
58.97844
-175.7204
-
# devtools::install_github("afsc-gap-products/akgfmaps", build_vignettes = TRUE)
-library(akgfmaps)
-
-figure <- akgfmaps::make_idw_map(
-x = dat, # Pass data as a data frame
-region ="bs.south", # Predefined EBS area
-set.breaks ="jenks", # Gets Jenks breaks from classint::classIntervals()
-in.crs ="+proj=longlat", # Set input coordinate reference system
-out.crs ="EPSG:3338", # Set output coordinate reference system
-grid.cell =c(20000, 20000), # 20x20km grid
-key.title ="Pacific Ocean perch") # Include in the legend title
+
# devtools::install_github("afsc-gap-products/akgfmaps", build_vignettes = TRUE)
+library(akgfmaps)
+
+figure <- akgfmaps::make_idw_map(
+x = dat, # Pass data as a data frame
+region ="bs.south", # Predefined EBS area
+set.breaks ="jenks", # Gets Jenks breaks from classint::classIntervals()
+in.crs ="+proj=longlat", # Set input coordinate reference system
+out.crs ="EPSG:3338", # Set output coordinate reference system
+grid.cell =c(20000, 20000), # 20x20km grid
+key.title ="Pacific Ocean perch") # Include in the legend title
7.0.5 Ex. GOA Pacific Ocean perch biomass and abundance
+
+
7.0.6 Ex. GOA Pacific Ocean perch biomass and abundance
Biomass and abundance for Pacific Ocean perch from 1990 – 2023 for the western/central/eastern GOA management areas as well as for the entire region.
-
dat <- RODBC::sqlQuery(channel = channel,
-query =
-"
--- Manipulate data to join to
-WITH FILTERED_STRATA AS (
-SELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA
-WHERE TYPE in ('REGULATORY_AREA', 'REGION')
-AND SURVEY_DEFINITION_ID = 47)
-
--- Select columns for output data
-SELECT
-BIOMASS_MT,
-POPULATION_COUNT,
-YEAR,
-DESCRIPTION
-
--- Identify what tables to pull data from
-FROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS
-JOIN FILTERED_STRATA STRATA
-ON STRATA.AREA_ID = BIOMASS.AREA_ID
-
--- Filter data results
-WHERE BIOMASS.SPECIES_CODE = 30060")
+
dat <- RODBC::sqlQuery(channel = channel,
+query =
+"
+-- Manipulate data to join to
+WITH FILTERED_STRATA AS (
+SELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA
+WHERE AREA_TYPE in ('REGULATORY_AREA', 'REGION')
+AND SURVEY_DEFINITION_ID = 47)
+
+-- Select columns for output data
+SELECT
+BIOMASS_MT,
+POPULATION_COUNT,
+YEAR,
+DESCRIPTION
+
+-- Identify what tables to pull data from
+FROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS
+JOIN FILTERED_STRATA STRATA
+ON STRATA.AREA_ID = BIOMASS.AREA_ID
+
+-- Filter data results
+WHERE BIOMASS.SPECIES_CODE = 30060")
7.0.6 Ex. AI rock sole size compositions and ridge plot
+
+
7.0.7 Ex. AI rock sole size compositions and ridge plot
Northern and Southern rock sole size composition data from 1991 – 2022 for the Aleutian Islands, with Ridge plot from ggridges.
-
dat <- RODBC::sqlQuery(channel = channel,
-query =
-"
--- Manipulate data to join to
-WITH FILTERED_STRATA AS (
-SELECT
-AREA_ID,
-DESCRIPTION
-
--- Identify what tables to pull data from
-FROM GAP_PRODUCTS.AKFIN_AREA
-WHERE TYPE = 'REGION'
-AND SURVEY_DEFINITION_ID = 52)
-
--- Select columns for output data
-SELECT
-LENGTH_MM,
-YEAR
-FROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP
-JOIN FILTERED_STRATA STRATA
-ON STRATA.AREA_ID = SIZECOMP.AREA_ID
-
--- Filter data results
-WHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52
-AND SIZECOMP.SPECIES_CODE IN (10261, 10262)")
+
dat <- RODBC::sqlQuery(channel = channel,
+query =
+"
+-- Manipulate data to join to
+WITH FILTERED_STRATA AS (
+SELECT
+AREA_ID,
+DESCRIPTION
+
+-- Identify what tables to pull data from
+FROM GAP_PRODUCTS.AKFIN_AREA
+WHERE AREA_TYPE = 'REGION'
+AND SURVEY_DEFINITION_ID = 52)
+
+-- Select columns for output data
+SELECT
+LENGTH_MM,
+YEAR
+FROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP
+JOIN FILTERED_STRATA STRATA
+ON STRATA.AREA_ID = SIZECOMP.AREA_ID
+
+-- Filter data results
+WHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52
+AND SIZECOMP.SPECIES_CODE IN (10261, 10262)")
7.0.7 Ex. EBS Walleye Pollock Age Compositions and Age Pyramid
+
+
7.0.8 Ex. EBS Walleye Pollock Age Compositions and Age Pyramid
Walleye pollock age composition for the EBS Standard Area from 1982 – 2022 and the EBS + NW Area from 1987 – 2022, with age pyramid plot.
-
dat <- RODBC::sqlQuery(channel = channel,
-query =
-"
--- Manipulate data to join to
-WITH FILTERED_STRATA AS (
-SELECT
-AREA_ID,
-DESCRIPTION
-FROM GAP_PRODUCTS.AKFIN_AREA
-WHERE TYPE = 'REGION' AND
-SURVEY_DEFINITION_ID = 98)
-
--- Select columns for output data
-SELECT
-AGECOMP.AGE,
-AGECOMP.POPULATION_COUNT,
-AGECOMP.SEX
-
--- Identify what tables to pull data from
-FROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP
-JOIN FILTERED_STRATA STRATA
-ON STRATA.AREA_ID = AGECOMP.AREA_ID
-
--- Filter data results
-WHERE SPECIES_CODE = 21740
-AND AGE >= 0")
+
dat <- RODBC::sqlQuery(channel = channel,
+query =
+"
+-- Manipulate data to join to
+WITH FILTERED_STRATA AS (
+SELECT
+AREA_ID,
+DESCRIPTION
+FROM GAP_PRODUCTS.AKFIN_AREA
+WHERE AREA_TYPE = 'REGION' AND
+SURVEY_DEFINITION_ID = 98)
+
+-- Select columns for output data
+SELECT
+AGECOMP.AGE,
+AGECOMP.POPULATION_COUNT,
+AGECOMP.SEX
+
+-- Identify what tables to pull data from
+FROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP
+JOIN FILTERED_STRATA STRATA
+ON STRATA.AREA_ID = AGECOMP.AREA_ID
+
+-- Filter data results
+WHERE SPECIES_CODE = 21740
+AND AGE >= 0")
-
dat0 <- dat %>%
- janitor::clean_names() %>%
- dplyr::filter(sex %in%c(1,2)) %>%
- dplyr::mutate(
-sex =ifelse(sex ==1, "M", "F"),
-population_count =# change male population to negative
-ifelse(sex=="M", population_count*(-1), population_count*1)/1e9)
-
-flextable::flextable(head(dat)) %>%theme_zebra()
+
dat0 <- dat %>%
+ janitor::clean_names() %>%
+ dplyr::filter(sex %in%c(1,2)) %>%
+ dplyr::mutate(
+sex =ifelse(sex ==1, "M", "F"),
+population_count =# change male population to negative
+ifelse(sex=="M", population_count*(-1), population_count*1)/1e9)
+
+flextable::flextable(head(dat)) %>%theme_zebra()
-
Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid.
AGE
POPULATION_COUNT
SEX
9
39,371
3
10
32,156
3
11
15,200
3
12
9,976
3
13
1,957
3
1
131,950,343
1
+
Ex. 3: EBS Walleye Pollock Age Compositions and Age Pyramid.
Pacific cod biomass and abundance data for the NBS by stratum.
-
dat <- RODBC::sqlQuery(channel = channel,
-query =
-"
--- Manipulate data to join to
-WITH FILTERED_STRATA AS (
-SELECT
-AREA_ID,
-AREA_NAME,
-DESCRIPTION
-FROM GAP_PRODUCTS.AKFIN_AREA
-WHERE TYPE in ('STRATUM') AND
-SURVEY_DEFINITION_ID = 143)
-
--- Select columns for output data
-SELECT
-BIOMASS.BIOMASS_MT,
-BIOMASS.POPULATION_COUNT,
-BIOMASS.YEAR,
-STRATA.AREA_NAME
-
--- Identify what tables to pull data from
-FROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS
-JOIN FILTERED_STRATA STRATA
-ON STRATA.AREA_ID = BIOMASS.AREA_ID
-
--- Filter data results
-WHERE BIOMASS.SURVEY_DEFINITION_ID IN 143
-AND BIOMASS.SPECIES_CODE = 21720")
+
dat <- RODBC::sqlQuery(channel = channel,
+query =
+"
+-- Manipulate data to join to
+WITH FILTERED_STRATA AS (
+SELECT
+AREA_ID,
+AREA_NAME,
+DESCRIPTION
+FROM GAP_PRODUCTS.AKFIN_AREA
+WHERE AREA_TYPE in ('STRATUM') AND
+SURVEY_DEFINITION_ID = 143)
+
+-- Select columns for output data
+SELECT
+BIOMASS.BIOMASS_MT,
+BIOMASS.POPULATION_COUNT,
+BIOMASS.YEAR,
+STRATA.AREA_NAME
+
+-- Identify what tables to pull data from
+FROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS
+JOIN FILTERED_STRATA STRATA
+ON STRATA.AREA_ID = BIOMASS.AREA_ID
+
+-- Filter data results
+WHERE BIOMASS.SURVEY_DEFINITION_ID IN 143
+AND BIOMASS.SPECIES_CODE = 21720")
set.breaks ="jenks", # Gets Jenks breaks from classint::classIntervals()in.crs ="+proj=longlat", # Set input coordinate reference systemout.crs ="EPSG:3338", # Set output coordinate reference system
-grid.cell =c(20000, 20000), # 20x20km grid
-key.title ="Pacific Ocean perch") # Include in the legend title
The plan will be, once all are satisfied with the new GAP_PRODUCTS schema and tables, to sunset the historic product tables in 2024 and proceed with only GAP_PRODUCTS for the 2024 post-survey stock assessment season.
-
-
December 2023 - March 2024: Meeting between GAP and stock assessment groups in early December 2023 to update progress on the GAP_PRODUCTS testing phase. Deadline for Comments and Feedback on GAP_PRODUCTS data structures is March 8, 2024.
-
September 2024: GAP will only release data products according to the new standard. Current, historical data product tables will be archived in a new schema called "GAP_ARCHIVE".
-
-
-
-
-
Previous updates
-
-
September 2023: Provisional data product tables – CPUE, BIOMASS, SIZECOMP, and AGECOMP – as well as provisional support tables – AREA, STRATUM_GROUPS, METADATA_COLUMN, SPECIES_YEAR, SURVEY_DESIGN – are available in the GAP_PRODUCTS Oracle schema with updated 2023 GOA and EBS survey data.
-
-
Additionally, the inclusion of mock data for the under the new 2025 GOA stratified random survey (labeled in the GAP_PRODUCTS tables as YEAR 2025) will provide stock authors with the opportunity to interact with data from the new survey design to be implemented in 2025.
-
Provisional AKFIN and FOSS tables are also available in the GAP_PRODUCTS Oracle schema. These include: AKFIN_AGECOMP, AKFIN_AREA, AKFIN_BIOMASS, AKFIN_CATCH, AKFIN_CPUE, AKFIN_CRUISE, AKFIN_HAUL, AKFIN_LENGTH, AKFIN_METADATA_COLUMN, AKFIN_SIZECOMP, AKFIN_SPECIMEN, AKFIN_SURVEY_DESIGN, AKFIN_STRATUM_GROUPS, FOSS_CATCH, FOSS_CPUE_PRESONLY, FOSS_HAUL, and FOSS_TAXON_GROUP.
-
-
May 2023: Release of new, draft, standard data product tables, including restratified GOA data. Stock assessment authors will have the opportunity to explore differences between datasets, test workflows, and provide comments and issues during summer 2023.
-
February 2023: Decision was made to include the mock restratified GOA data with the development of the new consolidated standard data products.
-
December 2022: GAP and SSMA discuss integration of the restratification of the GOA survey design into standard data products.
-
-
Stock assessors requested a "dry run" test to work with new mock restratified GOA survey data before implementation of the new survey design.
-
This prompted the postponement of the restratified GOA design to 2025.
-
-
October 2022: The data processes and index computation working group convened to address the development of standard survey data products (e.g., biomass/abundance, size composition, age composition, CPUE).
-
-
Index Computation Working Group: consolidation of index computation methods between the Bering Sea and AI-GOA regions.
-
Data Processes Working Group: consolidation, clean up, and reorganization of survey oracle schemata, tables, and other data for all surveys.
– GAP_PRODUCTS ChangeLog (last produced on 2023-11-14) using gapindex v2.1.1: A new version of gapindex (v2.1.1) was used to produced these data. There was a slight change to how subarea biomass totals are calculated. The modified biomass records reflect this change. New 2022 otolith data were available since the last iteration of the GAP_PRODUCTS for Aleutian Island Pacific ocean perch and northern rockifsh and Eastern Bering Sea northern rock sole. Zero-filled CPUE records for four GOA species codes (SPECIES_CODE: 21210, 30010, 30360, 77102, 98101) were added due to how the 1990 data were integrated in the last production run of GAP_PRODUCTS. Two Arctic cod (SPECIES_CODE: 21725) and one plain sculpin (SPECIES_CODE: 21371) count records were modified in the NBS data, which changes the numerical CPUE estimates for those hauls which changes the estimated population abundance and size composition for those species.
diff --git a/docs/search.json b/docs/search.json
index 37ae29c..68a333b 100644
--- a/docs/search.json
+++ b/docs/search.json
@@ -70,18 +70,11 @@
"text": "Data levels\nGAP produces numerous data products that are subjected to different levels of processing, ranging from raw to highly-derived. The suitability of these data products for analysis varies and there is ambiguity about which data products can be used for which purpose. This ambiguity can create challenges in communicating about data products and potentially lead to misunderstanding and misuse of data. One approach to communicating about the level of processing applied to data products and their suitability for analysis is to describe data products using a Data Processing Level system. Data Processing Level systems are widely used in earth system sciences to characterize the extent of processing that has been applied to data products. For example, the NOAA National Centers for Environmental Information (NCEI) Satellite Program uses a Data Processing Level system to describe data on a scale of 0-4, where Level 0 is raw data and Level 4 is model output or results from analysis. Example of how NASA remote sensing data products are shared through a public data portal with levels of data processing and documentation.\nFor more information, see Sean Rohan’s October 2022 SCRUGS presentation on the topic.\n\nLevel 0: Raw and unprocessed data. Ex: Data on the G drive, some tables in RACE_DATA\nLevel 1A: Data products with QA/QC applied that may or may not be expanded to analysis units, but either not georeferenced or does not include full metadata. Ex: Some tables in RACE_DATA and RACEBASE\nLevel 2: Analysis-ready data products that are derived for a standardized extent and account for zeros and missing/bad data. Ex: CPUE tables, some data products in public-facing archives and repositories\nLevel 3: Data products that are synthesized across a standardized extent, often inputs in a higher-level analytical product. Ex: Abundance indices, some data products in public-facing archives and repositories\nLevel 4: Analytically generated data products that are derived from lower-level data, often to inform management. Ex: Biological reference points from stock assessments, Essential Fish Habitat layers, indicators in Ecosystem Status Reports and Ecosystem and Socioeconomic Profiles"
},
{
- "objectID": "content/intro-news.html#future-plans",
- "href": "content/intro-news.html#future-plans",
+ "objectID": "content/intro-news.html#newschange-logs",
+ "href": "content/intro-news.html#newschange-logs",
"title": "News",
- "section": "Future plans",
- "text": "Future plans\n\nGOA 2025 Restratification – Mock Data for Testing\nThe plan will be, once all are satisfied with the new GAP_PRODUCTS schema and tables, to sunset the historic product tables in 2024 and proceed with only GAP_PRODUCTS for the 2024 post-survey stock assessment season.\n\nDecember 2023 - March 2024: Meeting between GAP and stock assessment groups in early December 2023 to update progress on the GAP_PRODUCTS testing phase. Deadline for Comments and Feedback on GAP_PRODUCTS data structures is March 8, 2024.\nSeptember 2024: GAP will only release data products according to the new standard. Current, historical data product tables will be archived in a new schema called \"GAP_ARCHIVE\"."
- },
- {
- "objectID": "content/intro-news.html#previous-updates",
- "href": "content/intro-news.html#previous-updates",
- "title": "News",
- "section": "Previous updates",
- "text": "Previous updates\n\nSeptember 2023: Provisional data product tables – CPUE, BIOMASS, SIZECOMP, and AGECOMP – as well as provisional support tables – AREA, STRATUM_GROUPS, METADATA_COLUMN, SPECIES_YEAR, SURVEY_DESIGN – are available in the GAP_PRODUCTS Oracle schema with updated 2023 GOA and EBS survey data.\n\nAdditionally, the inclusion of mock data for the under the new 2025 GOA stratified random survey (labeled in the GAP_PRODUCTS tables as YEAR 2025) will provide stock authors with the opportunity to interact with data from the new survey design to be implemented in 2025.\nProvisional AKFIN and FOSS tables are also available in the GAP_PRODUCTS Oracle schema. These include: AKFIN_AGECOMP, AKFIN_AREA, AKFIN_BIOMASS, AKFIN_CATCH, AKFIN_CPUE, AKFIN_CRUISE, AKFIN_HAUL, AKFIN_LENGTH, AKFIN_METADATA_COLUMN, AKFIN_SIZECOMP, AKFIN_SPECIMEN, AKFIN_SURVEY_DESIGN, AKFIN_STRATUM_GROUPS, FOSS_CATCH, FOSS_CPUE_PRESONLY, FOSS_HAUL, and FOSS_TAXON_GROUP.\n\nMay 2023: Release of new, draft, standard data product tables, including restratified GOA data. Stock assessment authors will have the opportunity to explore differences between datasets, test workflows, and provide comments and issues during summer 2023.\nFebruary 2023: Decision was made to include the mock restratified GOA data with the development of the new consolidated standard data products.\nDecember 2022: GAP and SSMA discuss integration of the restratification of the GOA survey design into standard data products.\n\nStock assessors requested a \"dry run\" test to work with new mock restratified GOA survey data before implementation of the new survey design.\nThis prompted the postponement of the restratified GOA design to 2025.\n\nOctober 2022: The data processes and index computation working group convened to address the development of standard survey data products (e.g., biomass/abundance, size composition, age composition, CPUE).\n\nIndex Computation Working Group: consolidation of index computation methods between the Bering Sea and AI-GOA regions.\nData Processes Working Group: consolidation, clean up, and reorganization of survey oracle schemata, tables, and other data for all surveys."
+ "section": "News/change logs",
+ "text": "News/change logs\n– Run 2023-06-01 gapindex v2.1.0: Initial compiling and planning notes\n– GAP_PRODUCTS ChangeLog (last produced on 2023-11-14) using gapindex v2.1.1: A new version of gapindex (v2.1.1) was used to produced these data. There was a slight change to how subarea biomass totals are calculated. The modified biomass records reflect this change. New 2022 otolith data were available since the last iteration of the GAP_PRODUCTS for Aleutian Island Pacific ocean perch and northern rockifsh and Eastern Bering Sea northern rock sole. Zero-filled CPUE records for four GOA species codes (SPECIES_CODE: 21210, 30010, 30360, 77102, 98101) were added due to how the 1990 data were integrated in the last production run of GAP_PRODUCTS. Two Arctic cod (SPECIES_CODE: 21725) and one plain sculpin (SPECIES_CODE: 21371) count records were modified in the NBS data, which changes the numerical CPUE estimates for those hauls which changes the estimated population abundance and size composition for those species.\n– GAP_PRODUCTS ChangeLog (last produced on 2023-11-17) using gapindex v2.1.2: A new version of gapindex (v2.1.2) was used to produced these data. There was a slight change to how subarea biomass totals are calculated that was not fully addressed in v2.1.1. The modified biomass records reflect this change."
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"objectID": "content/intro-code-of-conduct.html#what-are-codes-of-conduct",
@@ -158,7 +151,7 @@
"href": "content/akfin-oracle-sql-r.html#data-sql-query-examples",
"title": "Access data",
"section": "Data SQL Query Examples:",
- "text": "Data SQL Query Examples:\n\nlibrary(gapindex)\nlibrary(RODBC)\nlibrary(flextable)\nlibrary(ggplot2)\nlibrary(magrittr)\nlibrary(dplyr)\n\n\n7.0.2 Ex. Select all data from a table\nYou can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the R environment.\n\nlocations <- c(\n \"GAP_PRODUCTS.AKFIN_AGECOMP\", \n \"GAP_PRODUCTS.AKFIN_AREA\", \n \"GAP_PRODUCTS.AKFIN_BIOMASS\", \n \"GAP_PRODUCTS.AKFIN_CATCH\", \n \"GAP_PRODUCTS.AKFIN_CPUE\", \n \"GAP_PRODUCTS.AKFIN_CRUISE\", \n \"GAP_PRODUCTS.AKFIN_HAUL\", \n \"GAP_PRODUCTS.AKFIN_LENGTH\", \n \"GAP_PRODUCTS.AKFIN_METADATA_COLUMN\", \n \"GAP_PRODUCTS.AKFIN_SIZECOMP\", \n \"GAP_PRODUCTS.AKFIN_SPECIMEN\", \n \"GAP_PRODUCTS.AKFIN_STRATUM_GROUPS\", \n \"GAP_PRODUCTS.AKFIN_SURVEY_DESIGN\", \n \"GAP_PRODUCTS.AKFIN_TAXONOMIC_CLASSIFICATION\"\n)\n\nfor (i in 1:length(locations)) {\n print(locations[i])\n a <- RODBC::sqlQuery(channel, paste0(\"SELECT * FROM \", locations[i]))\n write.csv(x = a, file = here::here(\"data\", paste0(locations[i], \".csv\")))\n}\n\n\n\n7.0.3 Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod.\n\ndat <- RODBC::sqlQuery(channel = channel,\n query =\n\"\n-- Select columns for output data\nSELECT \nHAULJOIN, \nSPECIES_CODE, \nSTRATUM, \nLATITUDE_DD_START, \nLONGITUDE_DD_START,\nCPUE_KGKM2, \nGEAR_TEMPERATURE_C\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_CPUE cpue\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL haul\nUSING (HAULJOIN) \n\n-- Filter for P. Cod observations\nWHERE SPECIES_CODE IN (21720)\n\n-- Select all stratum within the area_id 919 (INPFC Shumagin region)\nAND haul.STRATUM IN\n(\nSELECT \nSTRATUM\nFROM GAP_PRODUCTS.AKFIN_STRATUM_GROUPS \nWHERE AREA_ID = 919\n);\")\n\n\ndat <- dat %>% \n dplyr::select(HAULJOIN, STRATUM, SPECIES_CODE, LATITUDE_DD_START, LONGITUDE_DD_START, CPUE_KGKM2, GEAR_TEMPERATURE_C) %>% \n dplyr::mutate(SPECIES_CODE = as.character(SPECIES_CODE), \n STRATUM = as.character(STRATUM)) %>% \n dplyr::arrange(SPECIES_CODE)\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n\n\nEx. 8: CPUE for all stations contained in the Shumagin region\n(AREA_ID = 919).HAULJOINSTRATUMSPECIES_CODELATITUDE_DD_STARTLONGITUDE_DD_STARTCPUE_KGKM2GEAR_TEMPERATURE_C-22,239122172055.43748-160.1269717.630854.5-22,215132172054.58732-161.194576.907634.3-22,168112172054.45823-163.08722,004.496284.9-22,2041102172054.51804-160.74930.000004.7-22,1882102172054.38733-159.69860.000005.5-22,1832102172054.09314-161.69960.000005.3\n\n\n\n\n7.0.4 Ex. EBS Pacific Ocean perch CPUE and akgfmaps map\nPacific Ocean perch catch-per-unit-effort estimates for EBS in 2021 from GAP_PRODUCTS.AKFIN_CPUE and map constructed using akgfmaps. Here, we’ll use AKFIN HAUL and CRUISES data also included in this repo, for convenience, though they are very similar to their RACEBASE analogs.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \n(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares\nhh.LATITUDE_DD_START LATITUDE,\nhh.LONGITUDE_DD_START LONGITUDE\n\n-- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin\nFROM GAP_PRODUCTS.AKFIN_CPUE cp\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh\nON cp.HAULJOIN = hh.HAULJOIN\n\n-- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc\nON hh.CRUISEJOIN = cc.CRUISEJOIN\n\n-- Filter data\nWHERE cp.SPECIES_CODE = 30060 \nAND cc.SURVEY_DEFINITION_ID = 98 \nAND cc.YEAR = 2021;\")\n\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n\n\nEx. 6: EBS Pacific Ocean perch CPUE and akgfmaps\nmap.CPUE_KGHALATITUDELONGITUDE0.000000058.75863-174.92850.281353357.32545-173.32170.000000057.64161-172.79630.000000059.67831-172.57540.000000060.96936-174.87600.000000058.64012-173.5922\n\n\n\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n x = dat, # Pass data as a data frame\n region = \"bs.south\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific Ocean perch\\nCPUE (kg/km2)\")) |> \n change_fill_color(new.scheme = \"grey\", show.plot = FALSE)\n\n\n\n\nEx. 6: EBS Pacific Ocean perch CPUE and akgfmaps map.\n\n\n\n\n\n\n7.0.5 Ex. GOA Pacific Ocean perch biomass and abundance\nBiomass and abundance for Pacific Ocean perch from 1990 – 2023 for the western/central/eastern GOA management areas as well as for the entire region.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE in ('REGULATORY_AREA', 'REGION') \nAND SURVEY_DEFINITION_ID = 47)\n\n-- Select columns for output data\nSELECT \nBIOMASS_MT,\nPOPULATION_COUNT, \nYEAR, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SPECIES_CODE = 30060\")\n\n\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = description) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = gsub(x = area, pattern = \" - \", replacement = \"\\n\"), \n area = gsub(x = area, pattern = \": \", replacement = \"\\n\"), \n type = sapply(X = strsplit(x = area, split = \"\\n\", fixed = TRUE), `[[`, 2)) %>% \n dplyr::arrange(type) %>% \n dplyr::mutate(\n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\n\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n\n\nEx. 1: GOA Pacific Ocean perch biomass and abundance.BIOMASS_MTPOPULATION_COUNTYEARDESCRIPTION483,622.6833,902,1611993GOA Region: All Strata483,622.6833,902,1611993GOA Region: All Strata771,412.81,252,616,6031996GOA Region: All Strata771,412.81,252,616,6031996GOA Region: All Strata727,063.51,212,034,9131999GOA Region: All Strata727,063.51,212,034,9131999GOA Region: All Strata\n\n\n\n# install.packages(\"scales\")\nlibrary(scales)\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(x = year, y = val, color = type)) +\n ggplot2::geom_point(size = 3) + \n ggplot2::facet_grid(cols = vars(area), rows = vars(var), scales = \"free_y\") + \n ggplot2::scale_x_continuous(name = \"Year\", n.breaks = 3) +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::labs(title = 'GOA Pacific Ocean perch biomass and abundance 1990 – 2023') + \n ggplot2::guides(color=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_color_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n\n\n\n\nEx. 1: GOA Pacific Ocean perch biomass and abundance.\n\n\n\n\n\n\n7.0.6 Ex. AI rock sole size compositions and ridge plot\nNorthern and Southern rock sole size composition data from 1991 – 2022 for the Aleutian Islands, with Ridge plot from ggridges.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE = 'REGION' \nAND SURVEY_DEFINITION_ID = 52)\n\n-- Select columns for output data\nSELECT \nLENGTH_MM, \nYEAR\nFROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = SIZECOMP.AREA_ID\n\n-- Filter data results\nWHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52 \nAND SIZECOMP.SPECIES_CODE IN (10261, 10262)\")\n\n\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::mutate(length_cm = length_mm/10)\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n\n\nEx. 2: AI Rock sole size compositions and ridge plot.LENGTH_MMYEAR180201419020142002014210201422020142302014\n\n\n\n# install.packages(\"ggridges\")\nlibrary(ggridges)\nfigure <- \n ggplot2::ggplot(\n data = dat0, \n mapping = aes(x = length_cm, y = as.factor(year), fill = stat(x))) +\n ggridges::theme_ridges(center_axis_labels = TRUE) + \n ggridges::geom_density_ridges_gradient(scale = 4, show.legend = FALSE) + \n ggplot2::scale_y_discrete(name = \"Year\", expand = c(0.01, 0)) +\n ggplot2::scale_x_continuous(name = \"Length (cm)\", expand = c(0.01, 0)) +\n # ggplot2::scale_fill_grey() +\n ggplot2::labs(title = 'AI Rock sole Size Compositions 1991 – 2022') \n\nfigure\n\n\n\n\nEx. 2: AI Rock sole size compositions and ridge plot.\n\n\n\n\n\n\n7.0.7 Ex. EBS Walleye Pollock Age Compositions and Age Pyramid\nWalleye pollock age composition for the EBS Standard Area from 1982 – 2022 and the EBS + NW Area from 1987 – 2022, with age pyramid plot.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE = 'REGION' AND \nSURVEY_DEFINITION_ID = 98)\n\n-- Select columns for output data\nSELECT \nAGECOMP.AGE, \nAGECOMP.POPULATION_COUNT, \nAGECOMP.SEX\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = AGECOMP.AREA_ID\n\n-- Filter data results\nWHERE SPECIES_CODE = 21740\nAND AGE >= 0\")\n\n\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::filter(sex %in% c(1,2)) %>%\n dplyr::mutate(\n sex = ifelse(sex == 1, \"M\", \"F\"),\n population_count = # change male population to negative\n ifelse(sex==\"M\", population_count*(-1), population_count*1)/1e9) \n\nflextable::flextable(head(dat)) %>% theme_zebra()\n\n\nEx. 3: EBS Walleye Pollock Age Compositions and Age Pyramid.AGEPOPULATION_COUNTSEX939,37131032,15631115,2003129,9763131,95731131,950,3431\n\n\n\nfigure <- ggplot2::ggplot(\n data = dat0, \n mapping = \n aes(x = age,\n y = population_count, \n fill = sex)) +\n ggplot2::scale_fill_grey() +\n ggplot2::geom_bar(stat = \"identity\") +\n ggplot2::coord_flip() +\n ggplot2::scale_x_continuous(name = \"Age\") +\n ggplot2::scale_y_continuous(name = \"Population (billions)\", labels = abs) +\n ggplot2::ggtitle(label = \"EBS Walleye Pollock Age Compositions 1982 – 2022\") + \n ggplot2::guides(fill = guide_legend(title = \"Sex\"))+\n ggplot2::theme_bw()\n\nfigure\n\n\n\n\nEx. 3: EBS Walleye Pollock Age Compositions and Age Pyramid.\n\n\n\n\n\n\n7.0.8 Ex. NBS Pacific cod biomass and abundance\nPacific cod biomass and abundance data for the NBS by stratum.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nAREA_NAME, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE TYPE in ('STRATUM') AND \nSURVEY_DEFINITION_ID = 143) \n\n-- Select columns for output data\nSELECT \nBIOMASS.BIOMASS_MT, \nBIOMASS.POPULATION_COUNT, \nBIOMASS.YEAR, \nSTRATA.AREA_NAME\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS \nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SURVEY_DEFINITION_ID IN 143 \nAND BIOMASS.SPECIES_CODE = 21720\")\n\n\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = area_name) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n\n\nEx. 4: NBS Pacific cod biomass and abundance.BIOMASS_MTPOPULATION_COUNTYEARAREA_NAME95,849.98368,767,4982021Inner Domain107,096.730102,734,1422019Inner Domain76,708.43339,605,8602023Inner Domain132,490.15266,187,2452017Inner Domain96,500.69760,433,1352022Inner Domain7,462.5594,724,1532010Inner Domain\n\n\n\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(y = val, x = year, fill = area)) + \n ggplot2::geom_bar(position=\"stack\", stat=\"identity\") + \n ggplot2::facet_grid(rows = vars(var), scales = \"free_y\") +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::scale_x_continuous(name = \"Year\", breaks = unique(dat0$year)) +\n ggplot2::labs(title = 'NBS Pacific cod biomass and abundance by stratum') + \n ggplot2::guides(fill=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_fill_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n\n\n\n\nEx. 4: NBS Pacific cod biomass and abundance.\n\n\n\n\n\n\n7.0.9 Ex. GOA Pacific Ocean perch biomass and line plot\nPacific Ocean perch biomass totals for GOA between 1984-2021 from GAP_PRODUCTS.AKFIN_BIOMASS\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \nSURVEY_DEFINITION_ID, \nBIOMASS_MT, \nBIOMASS_VAR, \nYEAR\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS\n\n-- Filter data results\nWHERE SPECIES_CODE = 30060 \nAND SURVEY_DEFINITION_ID = 47 \nAND AREA_ID = 99903 \nAND YEAR BETWEEN 1984 AND 2023;\") %>% \n janitor::clean_names() %>% \n dplyr::mutate(biomass_kmt = biomass_mt/1000, \n # **approximate** 95% confidence interval\n biomass_kci_up = (biomass_mt + (2*sqrt(biomass_var)))/1000, \n biomass_kci_dw = (biomass_mt - (2*sqrt(biomass_var)))/1000) \n\n\nflextable::flextable(head(dat)) %>%\n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\n\n\nEx. 5: GOA Pacific Ocean perch biomass and line plot.survey_definition_idbiomass_mtbiomass_varyearbiomass_kmtbiomass_kci_upbiomass_kci_dw47483,622.611,803,384,7871993483.6226700.9093266.3358147771,412.841,434,152,2021996771.41281,178.5204364.3051547727,063.5150,983,542,1781999727.06351,504.1955-50.0685447673,155.149,285,342,9222001673.15511,117.1611229.1490147457,421.65,186,126,5292003457.4216601.4511313.3920447764,901.421,499,807,0102005764.90141,058.1577471.64517\n\n\n\na_mean <- dat %>% \n dplyr::group_by(survey_definition_id) %>% \n dplyr::summarise(biomass_kmt = mean(biomass_kmt, na.rm = TRUE), \n minyr = min(year, na.rm = TRUE), \n maxyr = max(year, na.rm = TRUE)) \n\nfigure <-\n ggplot(data = dat, \n mapping = aes(x = year, \n y = biomass_kmt)) +\n ggplot2::geom_point(size = 2.5, color = \"grey40\") + \n ggplot2::scale_x_continuous(\n name = \"Year\", \n labels = scales::label_number(\n accuracy = 1, \n big.mark = \"\")) +\n ggplot2::scale_y_continuous(\n name = \"Biomass (Kmt)\", \n labels = comma) +\n ggplot2::geom_segment(\n data = a_mean,\n mapping = aes(x = minyr, \n xend = maxyr, \n y = biomass_kmt, \n yend = biomass_kmt),\n linetype = \"dashed\", \n linewidth = 2) +\n ggplot2::geom_errorbar(\n mapping = aes(ymin = biomass_kci_dw, ymax = biomass_kci_up),\n position = position_dodge(.9),\n alpha = 0.5, width=.2) +\n ggplot2::ggtitle(\n label = \"GOA Pacific Ocean Perch Biomass 1984-2021\", \n subtitle = paste0(\"Mean = \", \n formatC(x = a_mean$biomass_kmt, \n digits = 2, \n big.mark = \",\", \n format = \"f\"), \n \" Kmt\")) +\n ggplot2::theme_bw()\n\nfigure\n\n\n\n\nEx. 5: GOA Pacific Ocean perch biomass and line plot."
+ "text": "Data SQL Query Examples:\n\nlibrary(gapindex)\nlibrary(RODBC)\nlibrary(flextable)\nlibrary(ggplot2)\nlibrary(magrittr)\nlibrary(dplyr)\n\n\n7.0.2 Ex. Select all data from tables\nYou can download all of the tables locally using a variation of the code below. Once connected, pull and save the tables of interest into the R environment.\n\nlocations <- c(\n \"GAP_PRODUCTS.AKFIN_AGECOMP\", \n \"GAP_PRODUCTS.AKFIN_AREA\", \n \"GAP_PRODUCTS.AKFIN_BIOMASS\", \n \"GAP_PRODUCTS.AKFIN_CATCH\", \n \"GAP_PRODUCTS.AKFIN_CPUE\", \n \"GAP_PRODUCTS.AKFIN_CRUISE\", \n \"GAP_PRODUCTS.AKFIN_HAUL\", \n \"GAP_PRODUCTS.AKFIN_LENGTH\", \n \"GAP_PRODUCTS.AKFIN_METADATA_COLUMN\", \n \"GAP_PRODUCTS.AKFIN_SIZECOMP\", \n \"GAP_PRODUCTS.AKFIN_SPECIMEN\", \n \"GAP_PRODUCTS.AKFIN_STRATUM_GROUPS\", \n \"GAP_PRODUCTS.AKFIN_SURVEY_DESIGN\", \n \"GAP_PRODUCTS.AKFIN_TAXONOMIC_CLASSIFICATION\"\n)\n\nfor (i in 1:length(locations)) {\n print(locations[i])\n a <- RODBC::sqlQuery(channel, paste0(\"SELECT * FROM \", locations[i]))\n write.csv(x = a, file = here::here(\"data\", paste0(locations[i], \".csv\")))\n}\n\n\n\n7.0.3 Ex. CPUE for all EBS and NBS stations with associated haul, cruise, and species information.\n\na <- RODBC::sqlQuery(channel = channel, # NOT RACEBASE.HAUL\n query = paste0(\n\"\n-- Select columns for output data\nSELECT\ncr.CRUISEJOIN,\ncr.CRUISE,\ncr.YEAR,\ncr.SURVEY_DEFINITION_ID,\ncr.SURVEY_NAME,\ncr.VESSEL_ID,\ncr.VESSEL_NAME,\ncp.HAULJOIN,\ncp.SPECIES_CODE,\ntt.SPECIES_NAME,\ntt.COMMON_NAME,\ncp.WEIGHT_KG,\ncp.COUNT,\ncp.AREA_SWEPT_KM2,\ncp.CPUE_KGKM2,\ncp.CPUE_NOKM2,\nhh.HAUL,\nhh.STATION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_HAUL hh\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cr\nON hh.CRUISEJOIN = cr.CRUISEJOIN\nLEFT JOIN GAP_PRODUCTS.AKFIN_CPUE cp\nON hh.HAULJOIN = cp.HAULJOIN\nLEFT JOIN GAP_PRODUCTS.TAXONOMIC_CLASSIFICATION tt\nON cp.SPECIES_CODE = tt.SPECIES_CODE\n\n-- Filter for EBS and NBS observations\nWHERE SURVEY_DEFINITION_ID IN (143, 98) -- 143 NBS, 98 EBS\nAND tt.SURVEY_SPECIES = 1\n\n-- Only return the first 3 rows because otherwise this would be a huge table!\nFETCH FIRST 3 ROWS ONLY;\")) \n\nflextable::flextable(head(a)) %>% theme_zebra()\n\n\nEx.: CPUE for all EBS and NBS stations with associated haul, cruise,\nand species information.CRUISEJOINCRUISEYEARSURVEY_DEFINITION_IDSURVEY_NAMEVESSEL_IDVESSEL_NAMEHAULJOINSPECIES_CODESPECIES_NAMECOMMON_NAMEWEIGHT_KGCOUNTAREA_SWEPT_KM2CPUE_KGKM2CPUE_NOKM2HAULSTATION80198,2031,98298Eastern Bering Sea Crab/Groundfish Bottom Trawl Survey1CHAPMAN8771fish egg unid.000.0420210021G-1080198,2031,98298Eastern Bering Sea Crab/Groundfish Bottom Trawl Survey1CHAPMAN8772fish larvae unid.000.0420210021G-1080198,2031,98298Eastern Bering Sea Crab/Groundfish Bottom Trawl Survey1CHAPMAN8773fish unid.000.0420210021G-10\n\n\n\n\n7.0.4 Ex. CPUE for all stations contained in the INPFC Shumagin region (AREA_ID = 919) for Pacific cod.\n\ndat <- RODBC::sqlQuery(channel = channel,\n query =\n\"\n-- Select columns for output data\nSELECT \nHAULJOIN, \nSPECIES_CODE, \nSTRATUM, \nLATITUDE_DD_START, \nLONGITUDE_DD_START,\nCPUE_KGKM2, \nGEAR_TEMPERATURE_C\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_CPUE cpue\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL haul\nUSING (HAULJOIN) \n\n-- Filter for P. Cod observations\nWHERE SPECIES_CODE IN (21720)\n\n-- Select all stratum within the area_id 919 (INPFC Shumagin region)\nAND haul.STRATUM IN\n(\nSELECT \nSTRATUM\nFROM GAP_PRODUCTS.AKFIN_STRATUM_GROUPS \nWHERE AREA_ID = 919\n);\")\n\n\ndat <- dat %>% \n dplyr::select(HAULJOIN, STRATUM, SPECIES_CODE, LATITUDE_DD_START, LONGITUDE_DD_START, CPUE_KGKM2, GEAR_TEMPERATURE_C) %>% \n dplyr::mutate(SPECIES_CODE = as.character(SPECIES_CODE), \n STRATUM = as.character(STRATUM)) %>% \n dplyr::arrange(SPECIES_CODE)\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n\n\nEx. 8: CPUE for all stations contained in the Shumagin region\n(AREA_ID = 919).HAULJOINSTRATUMSPECIES_CODELATITUDE_DD_STARTLONGITUDE_DD_STARTCPUE_KGKM2GEAR_TEMPERATURE_C-22,270132172055.11515-159.3512209.289944.3-22,250132172055.05143-159.96798,700.920175.1-22,238132172055.11365-159.4264363.173254.4-22,214132172054.78608-160.000863.715064.6-22,2021112172054.48341-159.7261618.721204.7-22,2471122172055.59093-160.0740114.730424.0\n\n\n\n\n7.0.5 Ex. EBS Pacific Ocean perch CPUE and akgfmaps map\nPacific Ocean perch catch-per-unit-effort estimates for EBS in 2021 from GAP_PRODUCTS.AKFIN_CPUE and map constructed using akgfmaps. Here, we’ll use AKFIN HAUL and CRUISES data also included in this repo, for convenience, though they are very similar to their RACEBASE analogs.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \n(cp.CPUE_KGKM2/100) CPUE_KGHA, -- akgfmaps is expecting hectares\nhh.LATITUDE_DD_START LATITUDE,\nhh.LONGITUDE_DD_START LONGITUDE\n\n-- Use HAUL data to obtain LATITUDE & LONGITUDE and connect to cruisejoin\nFROM GAP_PRODUCTS.AKFIN_CPUE cp\nLEFT JOIN GAP_PRODUCTS.AKFIN_HAUL hh\nON cp.HAULJOIN = hh.HAULJOIN\n\n-- Use CRUISES data to obtain YEAR and SURVEY_DEFINITION_ID\nLEFT JOIN GAP_PRODUCTS.AKFIN_CRUISE cc\nON hh.CRUISEJOIN = cc.CRUISEJOIN\n\n-- Filter data\nWHERE cp.SPECIES_CODE = 30060 \nAND cc.SURVEY_DEFINITION_ID = 98 \nAND cc.YEAR = 2021;\")\n\n\nflextable::flextable(head(dat)) %>% theme_zebra()\n\n\nEx. 6: EBS Pacific Ocean perch CPUE and akgfmaps\nmap.CPUE_KGHALATITUDELONGITUDE0.0000000060.67043-178.09460.0000000060.31361-176.01380.0000000060.35098-175.38500.0000000060.99712-177.66380.0000000060.96495-176.26340.0241637958.97844-175.7204\n\n\n\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n x = dat, # Pass data as a data frame\n region = \"bs.south\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific Ocean perch\\nCPUE (kg/km2)\")) |> \n change_fill_color(new.scheme = \"grey\", show.plot = FALSE)\n\n\n\n\nEx. 6: EBS Pacific Ocean perch CPUE and akgfmaps map.\n\n\n\n\n\n\n7.0.6 Ex. GOA Pacific Ocean perch biomass and abundance\nBiomass and abundance for Pacific Ocean perch from 1990 – 2023 for the western/central/eastern GOA management areas as well as for the entire region.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT AREA_ID, DESCRIPTION FROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE in ('REGULATORY_AREA', 'REGION') \nAND SURVEY_DEFINITION_ID = 47)\n\n-- Select columns for output data\nSELECT \nBIOMASS_MT,\nPOPULATION_COUNT, \nYEAR, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SPECIES_CODE = 30060\")\n\n\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = description) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = gsub(x = area, pattern = \" - \", replacement = \"\\n\"), \n area = gsub(x = area, pattern = \": \", replacement = \"\\n\"), \n type = sapply(X = strsplit(x = area, split = \"\\n\", fixed = TRUE), `[[`, 2)) %>% \n dplyr::arrange(type) %>% \n dplyr::mutate(\n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\n\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n\n\nEx. 1: GOA Pacific Ocean perch biomass and abundance.BIOMASS_MTPOPULATION_COUNTYEARDESCRIPTION157,295.1317,129,4081990GOA Region: All Strata157,295.1317,129,4081990GOA Region: All Strata483,622.6833,902,1611993GOA Region: All Strata483,622.6833,902,1611993GOA Region: All Strata771,412.81,252,616,6031996GOA Region: All Strata771,412.81,252,616,6031996GOA Region: All Strata\n\n\n\n# install.packages(\"scales\")\nlibrary(scales)\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(x = year, y = val, color = type)) +\n ggplot2::geom_point(size = 3) + \n ggplot2::facet_grid(cols = vars(area), rows = vars(var), scales = \"free_y\") + \n ggplot2::scale_x_continuous(name = \"Year\", n.breaks = 3) +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::labs(title = 'GOA Pacific Ocean perch biomass and abundance 1990 – 2023') + \n ggplot2::guides(color=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_color_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n\n\n\n\nEx. 1: GOA Pacific Ocean perch biomass and abundance.\n\n\n\n\n\n\n7.0.7 Ex. AI rock sole size compositions and ridge plot\nNorthern and Southern rock sole size composition data from 1991 – 2022 for the Aleutian Islands, with Ridge plot from ggridges.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE = 'REGION' \nAND SURVEY_DEFINITION_ID = 52)\n\n-- Select columns for output data\nSELECT \nLENGTH_MM, \nYEAR\nFROM GAP_PRODUCTS.AKFIN_SIZECOMP SIZECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = SIZECOMP.AREA_ID\n\n-- Filter data results\nWHERE SIZECOMP.SURVEY_DEFINITION_ID IN 52 \nAND SIZECOMP.SPECIES_CODE IN (10261, 10262)\")\n\n\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::mutate(length_cm = length_mm/10) %>% \n head() %>% \n flextable::flextable() %>% \n flextable::theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\ndat0\n\n\nEx. 2: AI Rock sole size compositions and ridge plot.length_mmyearlength_cm110199711130199713140199714150199715160199716170199717\n\n\n\n# install.packages(\"ggridges\")\nlibrary(ggridges)\nfigure <- \n ggplot2::ggplot(\n data = dat, \n mapping = aes(x = LENGTH_MM, y = as.factor(YEAR), fill = stat(x))) +\n ggridges::theme_ridges(center_axis_labels = TRUE) + \n ggridges::geom_density_ridges_gradient(scale = 4, show.legend = FALSE) + \n ggplot2::scale_y_discrete(name = \"Year\", expand = c(0.01, 0)) +\n ggplot2::scale_x_continuous(name = \"Length (cm)\", expand = c(0.01, 0)) +\n # ggplot2::scale_fill_grey() +\n ggplot2::labs(title = 'AI Rock sole Size Compositions 1991 – 2022') \n\nfigure\n\n\n\n\nEx. 2: AI Rock sole size compositions and ridge plot.\n\n\n\n\n\n\n7.0.8 Ex. EBS Walleye Pollock Age Compositions and Age Pyramid\nWalleye pollock age composition for the EBS Standard Area from 1982 – 2022 and the EBS + NW Area from 1987 – 2022, with age pyramid plot.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE = 'REGION' AND \nSURVEY_DEFINITION_ID = 98)\n\n-- Select columns for output data\nSELECT \nAGECOMP.AGE, \nAGECOMP.POPULATION_COUNT, \nAGECOMP.SEX\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_AGECOMP AGECOMP\nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = AGECOMP.AREA_ID\n\n-- Filter data results\nWHERE SPECIES_CODE = 21740\nAND AGE >= 0\")\n\n\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::filter(sex %in% c(1,2)) %>%\n dplyr::mutate(\n sex = ifelse(sex == 1, \"M\", \"F\"),\n population_count = # change male population to negative\n ifelse(sex==\"M\", population_count*(-1), population_count*1)/1e9) \n\nflextable::flextable(head(dat)) %>% theme_zebra()\n\n\nEx. 3: EBS Walleye Pollock Age Compositions and Age Pyramid.AGEPOPULATION_COUNTSEX1148,791,451212120,673,58021342,580,05421447,229,37821525,140,52321619,473,2552\n\n\n\nfigure <- ggplot2::ggplot(\n data = dat0, \n mapping = \n aes(x = age,\n y = population_count, \n fill = sex)) +\n ggplot2::scale_fill_grey() +\n ggplot2::geom_bar(stat = \"identity\") +\n ggplot2::coord_flip() +\n ggplot2::scale_x_continuous(name = \"Age\") +\n ggplot2::scale_y_continuous(name = \"Population (billions)\", labels = abs) +\n ggplot2::ggtitle(label = \"EBS Walleye Pollock Age Compositions 1982 – 2022\") + \n ggplot2::guides(fill = guide_legend(title = \"Sex\"))+\n ggplot2::theme_bw()\n\nfigure\n\n\n\n\nEx. 3: EBS Walleye Pollock Age Compositions and Age Pyramid.\n\n\n\n\n\n\n7.0.9 Ex. NBS Pacific cod biomass and abundance\nPacific cod biomass and abundance data for the NBS by stratum.\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Manipulate data to join to\nWITH FILTERED_STRATA AS (\nSELECT \nAREA_ID, \nAREA_NAME, \nDESCRIPTION \nFROM GAP_PRODUCTS.AKFIN_AREA\nWHERE AREA_TYPE in ('STRATUM') AND \nSURVEY_DEFINITION_ID = 143) \n\n-- Select columns for output data\nSELECT \nBIOMASS.BIOMASS_MT, \nBIOMASS.POPULATION_COUNT, \nBIOMASS.YEAR, \nSTRATA.AREA_NAME\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS BIOMASS \nJOIN FILTERED_STRATA STRATA \nON STRATA.AREA_ID = BIOMASS.AREA_ID\n\n-- Filter data results\nWHERE BIOMASS.SURVEY_DEFINITION_ID IN 143 \nAND BIOMASS.SPECIES_CODE = 21720\")\n\n\ndat0 <- dat %>% \n janitor::clean_names() %>% \n dplyr::select(biomass_mt, population_count, year, area = area_name) %>%\n pivot_longer(cols = c(\"biomass_mt\", \"population_count\"), \n names_to = \"var\", \n values_to = \"val\") %>% \n dplyr::mutate(\n val = ifelse(var == \"biomass_mt\", val/1e6, val/1e9), \n var = ifelse(var == \"biomass_mt\", \"Biomass (Mmt)\", \"Population (B)\"), \n area = factor(area, levels = unique(area), labels = unique(area), ordered = TRUE))\nflextable::flextable(head(dat)) %>% \n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"YEAR\", big.mark = \"\")\n\n\nEx. 4: NBS Pacific cod biomass and abundance.BIOMASS_MTPOPULATION_COUNTYEARAREA_NAME7,462.5594,724,1532010Inner Domain95,849.98368,767,4982021Inner Domain107,096.730102,734,1422019Inner Domain76,708.43339,605,8602023Inner Domain132,490.15266,187,2452017Inner Domain96,500.69760,433,1352022Inner Domain\n\n\n\nfigure <- ggplot2::ggplot(\n dat = dat0, \n mapping = aes(y = val, x = year, fill = area)) + \n ggplot2::geom_bar(position=\"stack\", stat=\"identity\") + \n ggplot2::facet_grid(rows = vars(var), scales = \"free_y\") +\n ggplot2::scale_y_continuous(name = \"Estimate\", labels = comma) +\n ggplot2::scale_x_continuous(name = \"Year\", breaks = unique(dat0$year)) +\n ggplot2::labs(title = 'NBS Pacific cod biomass and abundance by stratum') + \n ggplot2::guides(fill=guide_legend(title = \"Region Type\"))+\n ggplot2::scale_fill_grey() +\n ggplot2::theme_bw() +\n ggplot2::theme(legend.direction = \"horizontal\", \n legend.position = \"bottom\")\n\nfigure\n\n\n\n\nEx. 4: NBS Pacific cod biomass and abundance.\n\n\n\n\n\n\n7.0.10 Ex. GOA Pacific Ocean perch biomass and line plot\nPacific Ocean perch biomass totals for GOA between 1984-2021 from GAP_PRODUCTS.AKFIN_BIOMASS\n\ndat <- RODBC::sqlQuery(channel = channel, \n query = \n\"\n-- Select columns for output data\nSELECT \nSURVEY_DEFINITION_ID, \nBIOMASS_MT, \nBIOMASS_VAR, \nYEAR\n\n-- Identify what tables to pull data from\nFROM GAP_PRODUCTS.AKFIN_BIOMASS\n\n-- Filter data results\nWHERE SPECIES_CODE = 30060 \nAND SURVEY_DEFINITION_ID = 47 \nAND AREA_ID = 99903 \nAND YEAR BETWEEN 1984 AND 2023;\") %>% \n janitor::clean_names() %>% \n dplyr::mutate(biomass_kmt = biomass_mt/1000, \n # **approximate** 95% confidence interval\n biomass_kci_up = (biomass_mt + (2*sqrt(biomass_var)))/1000, \n biomass_kci_dw = (biomass_mt - (2*sqrt(biomass_var)))/1000) \n\n\nflextable::flextable(head(dat)) %>%\n theme_zebra() %>%\n flextable::colformat_num(x = ., j = \"year\", big.mark = \"\")\n\n\nEx. 5: GOA Pacific Ocean perch biomass and line plot.survey_definition_idbiomass_mtbiomass_varyearbiomass_kmtbiomass_kci_upbiomass_kci_dw47157,295.12,221,176,9681990157.2951251.553863.0363847483,622.611,803,384,7871993483.6226700.9093266.3358147771,412.841,434,152,2021996771.41281,178.5204364.3051547727,063.5150,983,542,1781999727.06351,504.1955-50.0685447673,155.149,285,342,9222001673.15511,117.1611229.1490147457,421.65,186,126,5292003457.4216601.4511313.39204\n\n\n\na_mean <- dat %>% \n dplyr::group_by(survey_definition_id) %>% \n dplyr::summarise(biomass_kmt = mean(biomass_kmt, na.rm = TRUE), \n minyr = min(year, na.rm = TRUE), \n maxyr = max(year, na.rm = TRUE)) \n\nfigure <-\n ggplot(data = dat, \n mapping = aes(x = year, \n y = biomass_kmt)) +\n ggplot2::geom_point(size = 2.5, color = \"grey40\") + \n ggplot2::scale_x_continuous(\n name = \"Year\", \n labels = scales::label_number(\n accuracy = 1, \n big.mark = \"\")) +\n ggplot2::scale_y_continuous(\n name = \"Biomass (Kmt)\", \n labels = comma) +\n ggplot2::geom_segment(\n data = a_mean,\n mapping = aes(x = minyr, \n xend = maxyr, \n y = biomass_kmt, \n yend = biomass_kmt),\n linetype = \"dashed\", \n linewidth = 2) +\n ggplot2::geom_errorbar(\n mapping = aes(ymin = biomass_kci_dw, ymax = biomass_kci_up),\n position = position_dodge(.9),\n alpha = 0.5, width=.2) +\n ggplot2::ggtitle(\n label = \"GOA Pacific Ocean Perch Biomass 1984-2021\", \n subtitle = paste0(\"Mean = \", \n formatC(x = a_mean$biomass_kmt, \n digits = 2, \n big.mark = \",\", \n format = \"f\"), \n \" Kmt\")) +\n ggplot2::theme_bw()\n\nfigure\n\n\n\n\nEx. 5: GOA Pacific Ocean perch biomass and line plot."
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@@ -263,7 +256,7 @@
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"title": "Access via API and R",
"section": "Ex. 7: Visualize CPUE data in distribution map",
- "text": "Ex. 7: Visualize CPUE data in distribution map\nPacific cod catch-per-unit-effort estimates for NBS in 2021 and map constructed using akgfmaps.\n\n# res <- httr::GET(\n# url = paste0(api_link, \"?offset=0&limit=10000\"), \n# query = list(year = 2021, srvy = \"EBS\", species_code = 30060))\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\",\"species_code\":21720}'))\ndata_catch <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, cpue_kgkm2) \n\n# zero-fill data (imperfectly, but effective for this example)\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\"}offset=0&limit=10000'))\ndata_haul <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, latitude_dd, longitude_dd) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>% \n dplyr::distinct()\n\ndata <- dplyr::left_join(data_haul, data_catch) %>% \n dplyr::mutate(cpue_kgkm2 = ifelse(is.na(cpue_kgkm2), 0, cpue_kgkm2), \n dplyr::across(dplyr::everything(), as.numeric)) \n\nflextable::flextable(data[1:3,]) %>% \n flextable::theme_zebra() \n\n\nEx. 7: Visualize CPUE data in distribution map.stratumstationlatitude_ddlongitude_ddcpue_kgkm28161.66434-172.26552,895.2588162.33740-173.17021,235.5457062.03713-171.65280.000\n\n\n\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n CPUE_KGHA = data$cpue_kgkm2, # calculates the same, regardless of units. \n LATITUDE = data$latitude_dd, \n LONGITUDE = data$longitude_dd, \n region = \"bs.north\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000), # 20x20km grid\n key.title = \"Pacific Ocean perch\") # Include in the legend title\n\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]\n\nfigure$plot + \n ggplot2::guides(fill=guide_legend(title = \"Pacific cod\\nCPUE (kg/km2)\"))\n\n\n\n\nEx. 7: Visualize CPUE data in distribution map."
+ "text": "Ex. 7: Visualize CPUE data in distribution map\nPacific cod catch-per-unit-effort estimates for NBS in 2021 and map constructed using akgfmaps.\n\n# res <- httr::GET(\n# url = paste0(api_link, \"?offset=0&limit=10000\"), \n# query = list(year = 2021, srvy = \"EBS\", species_code = 30060))\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\",\"species_code\":21720}'))\ndata_catch <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, cpue_kgkm2) \n\n# zero-fill data (imperfectly, but effective for this example)\nres <- httr::GET(\n url = paste0(api_link, '?q={\"year\":2021,\"srvy\":\"NBS\"}offset=0&limit=10000'))\ndata_haul <- jsonlite::fromJSON(base::rawToChar(res$content))$items %>% \n dplyr::select(stratum, station, latitude_dd, longitude_dd) %>%\n dplyr::mutate(across(where(is.numeric), round, 3)) %>% \n dplyr::distinct()\n\ndata <- dplyr::left_join(data_haul, data_catch) %>% \n dplyr::mutate(cpue_kgkm2 = ifelse(is.na(cpue_kgkm2), 0, cpue_kgkm2), \n dplyr::across(dplyr::everything(), as.numeric)) \n\nflextable::flextable(data[1:3,]) %>% \n flextable::theme_zebra() \n\n\nEx. 7: Visualize CPUE data in distribution map.stratumstationlatitude_ddlongitude_ddcpue_kgkm28161.66434-172.26552,895.2588162.33740-173.17021,235.5457062.03713-171.65280.000\n\n\n\n# devtools::install_github(\"afsc-gap-products/akgfmaps\", build_vignettes = TRUE)\nlibrary(akgfmaps)\n\nfigure <- akgfmaps::make_idw_map(\n CPUE_KGHA = data$cpue_kgkm2, # calculates the same, regardless of units. \n LATITUDE = data$latitude_dd, \n LONGITUDE = data$longitude_dd, \n region = \"bs.north\", # Predefined EBS area\n set.breaks = \"jenks\", # Gets Jenks breaks from classint::classIntervals()\n in.crs = \"+proj=longlat\", # Set input coordinate reference system\n out.crs = \"EPSG:3338\", # Set output coordinate reference system\n grid.cell = c(20000, 20000))$plot + # 20x20km grid\n ggplot2::guides(fill=guide_legend(title = \"Pacific cod\\nCPUE (kg/km2)\"))\n\n[inverse distance weighted interpolation]\n[inverse distance weighted interpolation]"
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diff --git a/docs/sitemap.xml b/docs/sitemap.xml
index cde5a04..8b3f559 100644
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