Merge pull request #231 from QuantEcon/reorganizing-chapters

Reorganizing chapters

lectures/_config.yml

@@ -18,6 +18,7 @@ sphinx:
   config:
     suppress_warnings: ["mystnb.unknown_mime_type"]
     nb_mime_priority_overrides: [
+        # HTML
        ['html', 'application/vnd.jupyter.widget-view+json', 10],
        ['html', 'application/javascript', 20],
        ['html', 'text/html', 30],
@@ -27,6 +28,25 @@ sphinx:
        ['html', 'image/jpeg', 70],
        ['html', 'text/markdown', 80],
        ['html', 'text/plain', 90],
+       # Jupyter Notebooks
+       ['jupyter', 'application/vnd.jupyter.widget-view+json', 10],
+       ['jupyter', 'application/javascript', 20],
+       ['jupyter', 'text/html', 30],
+       ['jupyter', 'text/latex', 40],
+       ['jupyter', 'image/svg+xml', 50],
+       ['jupyter', 'image/png', 60],
+       ['jupyter', 'image/jpeg', 70],
+       ['jupyter', 'text/markdown', 80],
+       ['jupyter', 'text/plain', 90],
+       # LaTeX
+       ['latex', 'text/latex', 10],
+       ['latex', 'application/pdf', 20],
+       ['latex', 'image/png', 30],
+       ['latex', 'image/jpeg', 40],
+       ['latex', 'text/markdown', 50],
+       ['latex', 'text/plain', 60],
+       # Link Checker
+       ['linkcheck', 'text/plain', 10],
      ]
     html_favicon: _static/lectures-favicon.ico
     html_static_path: ['_static']

lectures/_toc.yml

@@ -36,16 +36,19 @@ parts:
     - file: pandas/merge
     - file: pandas/groupby
     - file: pandas/timeseries
-    - file: pandas/matplotlib
+- caption: Data Science Tools
+  chapters:
+    - file: tools/index
+    - file: tools/matplotlib
+    - file: tools/maps
+    - file: tools/visualization_rules
+    - file: tools/regression
+    - file: tools/classification
 - caption: Applications
   chapters:
     - file: applications/index
-    - file: applications/visualization_rules
-    - file: applications/regression
-    - file: applications/recidivism
-    - file: applications/maps
-    - file: applications/classification
-    - file: applications/working_with_text
     - file: applications/ml_in_economics
-    - file: applications/heterogeneity
     - file: applications/networks
+    - file: applications/recidivism
+    - file: applications/working_with_text
+    - file: applications/heterogeneity

lectures/applications/heterogeneity.md

@@ -16,7 +16,7 @@ kernelspec:
 
 **Prerequisites**
 
-- {doc}`Regression <regression>`
+- {doc}`Regression <../tools/regression>`
 - {doc}`Machine Learning in Economics <ml_in_economics>`
 
 **Outcomes**

lectures/applications/index.md

@@ -15,20 +15,12 @@ In this part of the course, we will begin to apply the skills that you have lear
 includes using familiar tools in new applications and learning new tools that can be used for
 special types of analysis.
 
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Data Visualization: Rules and Guidelines](../applications/visualization_rules.md)
+## <i class="fas fa-chart-column" style="color:#ff9900"></i> [Machine Learning in Economics](../applications/ml_in_economics.md)
 
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Regression](../applications/regression.md)
+## <i class="fas fa-chart-column" style="color:#ff9900"></i> [Social and Economic Networks](../applications/networks.md)
 
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Case Study: Recidivism](../applications/recidivism.md)
+## <i class="fas fa-chart-column" style="color:#ff9900"></i> [Case Study: Recidivism](../applications/recidivism.md)
 
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Mapping in Python](../applications/maps.md)
+## <i class="fas fa-chart-column" style="color:#ff9900"></i> [Working with Text](../applications/working_with_text.md)
 
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Classification](../applications/classification.md)
-
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Working with Text](../applications/working_with_text.md)
-
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Machine Learning in Economics](../applications/ml_in_economics.md)
-
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Heterogeneous Effects](../applications/heterogeneity.md)
-
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Social and Economic Networks](../applications/networks.md)
+## <i class="fas fa-chart-column" style="color:#ff9900"></i> [Heterogeneous Effects](../applications/heterogeneity.md)

lectures/applications/ml_in_economics.md

@@ -16,7 +16,7 @@ kernelspec:
 
 **Prerequisites**
 
-- {doc}`Regression <regression>`
+- {doc}`Regression <../tools/regression>`
 
 **Outcomes**
 

lectures/applications/recidivism.md

@@ -17,9 +17,9 @@ kernelspec:
 
 **Prerequisites**
 
-- {doc}`matplotlib Introduction <../pandas/matplotlib>`
-- {doc}`Visualization Rules <visualization_rules>`
-- {doc}`Regression <regression>`
+- {doc}`matplotlib Introduction <../tools/matplotlib>`
+- {doc}`Visualization Rules <../tools/visualization_rules>`
+- {doc}`Regression <../tools/regression>`
 
 **Outcomes**
 

lectures/applications/working_with_text.md

@@ -16,10 +16,10 @@ kernelspec:
 
 **Prerequisites**
 
-- {doc}`Visualization Rules <visualization_rules>`
-- {doc}`Regression <regression>`
-- {doc}`Classification <classification>`
-- {doc}`Maps <maps>`
+- {doc}`Visualization Rules <../tools/visualization_rules>`
+- {doc}`Regression <../tools/regression>`
+- {doc}`Classification <../tools/classification>`
+- {doc}`Maps <../tools/maps>`
 
 **Outcomes**
 

lectures/index.md

@@ -37,8 +37,11 @@ Basic Python programming
 ## <i class="fas fa-server" style="color:#d45f6c"></i> [Scientific Computing](../scientific/index.md)
 Numerical and scientific methods
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [Pandas](../pandas/index.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [Working With Data](../pandas/index.md)
 The "data" in data science
 
-## <i class="fas fa-cogs" style="color:#1665ad"></i> [Applications](../applications/index.md)
-Applications and statistical tools
+## <i class="fas fa-cogs" style="color:#9933ff"></i> [Data Science Tools](../tools/index.md)
+Putting everything together
+
+## <i class="fas fa-chart-column" style="color:#ff9900"></i> [Applications](../applications/index.md)
+Applying our skills to real economic data

lectures/pandas/index.md

@@ -9,7 +9,7 @@ kernelspec:
   name: python3
 ---
 
-# pandas
+# DataFrames and Series in Pandas
 
 This section of the workshop covers data ingestion, cleaning,
 manipulation, analysis, and visualization in Python.
@@ -40,22 +40,20 @@ The expression "practice makes perfect" is especially true here.
 As you work with these tools, both the time to write and the time to run
 your programs will fall dramatically.
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [Introduction](../pandas/intro.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [Introduction](../pandas/intro.md)
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [Basic Functionality](../pandas/basics.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [Basic Functionality](../pandas/basics.md)
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [The Index](../pandas/the_index.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [The Index](../pandas/the_index.md)
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [Storage Formats](../pandas/storage_formats.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [Storage Formats](../pandas/storage_formats.md)
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [Cleaning Data](../pandas/data_clean.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [Cleaning Data](../pandas/data_clean.md)
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [Reshape](../pandas/reshape.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [Reshape](../pandas/reshape.md)
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [Merge](../pandas/merge.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [Merge](../pandas/merge.md)
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [GroupBy](../pandas/groupby.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [GroupBy](../pandas/groupby.md)
 
-## <i class="fas fa-code" style="color:#6dae5c"></i> [Time series](../pandas/timeseries.md)
-
-## <i class="fas fa-code" style="color:#6dae5c"></i> [Intermediate Plotting](../pandas/matplotlib.md)
+## <i class="fas fa-database" style="color:#6dae5c"></i> [Time Series](../pandas/timeseries.md)

lectures/problem_sets/problem_set_7.md

@@ -21,7 +21,7 @@ import pandas as pd
 
 ## Question 1
 
-From {doc}`Data Visualization: Rules and Guidelines <../applications/visualization_rules>`
+From {doc}`Data Visualization: Rules and Guidelines <../tools/visualization_rules>`
 
 Create a bar chart of the below data on Canadian GDP growth.
 Use a non-red color for the years 2000 to 2008, red for
@@ -41,7 +41,7 @@ for side in ["right", "top", "left", "bottom"]:
 
 ## Question 2
 
-From {doc}`Data Visualization: Rules and Guidelines <../applications/visualization_rules>`
+From {doc}`Data Visualization: Rules and Guidelines <../tools/visualization_rules>`
 
 Draft another way to organize time and education by modifying the code below.
 That is, have two subplots (one for each