From d1b0cdb3cab9c69b3ca861f9b0a47c0dbfcb1ae3 Mon Sep 17 00:00:00 2001
From: realbp <72233714+realbp@users.noreply.github.com>
Date: Tue, 2 Apr 2024 20:29:42 +0000
Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20getwilds?=
 =?UTF-8?q?/cancerprof@47d7c006043c2b4b3a544baef7c0ffa4477c8c30=20?=
 =?UTF-8?q?=F0=9F=9A=80?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 404.html                                 | 2 +-
 CONTRIBUTING.html                        | 2 +-
 LICENSE-text.html                        | 2 +-
 LICENSE.html                             | 2 +-
 articles/demographics-vignette.html      | 2 +-
 articles/incidence-vignette.html         | 2 +-
 articles/index.html                      | 2 +-
 articles/mortality-vignette.html         | 2 +-
 articles/risks-vignette.html             | 2 +-
 authors.html                             | 6 +++---
 index.html                               | 2 +-
 pkgdown.yml                              | 2 +-
 reference/cancerprof-package.html        | 2 +-
 reference/demo_crowding.html             | 2 +-
 reference/demo_education.html            | 2 +-
 reference/demo_food.html                 | 2 +-
 reference/demo_income.html               | 2 +-
 reference/demo_insurance.html            | 2 +-
 reference/demo_language.html             | 2 +-
 reference/demo_mobility.html             | 2 +-
 reference/demo_population.html           | 2 +-
 reference/demo_poverty.html              | 2 +-
 reference/demo_svi.html                  | 2 +-
 reference/demo_workforce.html            | 2 +-
 reference/incidence_cancer.html          | 2 +-
 reference/index.html                     | 2 +-
 reference/mortality_cancer.html          | 2 +-
 reference/pipe.html                      | 2 +-
 reference/risk_alcohol.html              | 2 +-
 reference/risk_colorectal_screening.html | 2 +-
 reference/risk_diet_exercise.html        | 2 +-
 reference/risk_smoking.html              | 2 +-
 reference/risk_vaccines.html             | 2 +-
 reference/risk_women_health.html         | 2 +-
 search.json                              | 2 +-
 35 files changed, 37 insertions(+), 37 deletions(-)

diff --git a/404.html b/404.html
index de05e94..d742871 100644
--- a/404.html
+++ b/404.html
@@ -24,7 +24,7 @@
     
     <a class="navbar-brand me-2" href="http://getwilds.org/cancerprof/index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/CONTRIBUTING.html b/CONTRIBUTING.html
index d26d379..376c38f 100644
--- a/CONTRIBUTING.html
+++ b/CONTRIBUTING.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/LICENSE-text.html b/LICENSE-text.html
index 03ce1f8..f626d88 100644
--- a/LICENSE-text.html
+++ b/LICENSE-text.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/LICENSE.html b/LICENSE.html
index bfec384..99779d5 100644
--- a/LICENSE.html
+++ b/LICENSE.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/articles/demographics-vignette.html b/articles/demographics-vignette.html
index 41d4fd0..1440230 100644
--- a/articles/demographics-vignette.html
+++ b/articles/demographics-vignette.html
@@ -26,7 +26,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/articles/incidence-vignette.html b/articles/incidence-vignette.html
index e902a74..e8144ba 100644
--- a/articles/incidence-vignette.html
+++ b/articles/incidence-vignette.html
@@ -26,7 +26,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/articles/index.html b/articles/index.html
index 72a2193..794499c 100644
--- a/articles/index.html
+++ b/articles/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/articles/mortality-vignette.html b/articles/mortality-vignette.html
index 6bbc1ae..719e737 100644
--- a/articles/mortality-vignette.html
+++ b/articles/mortality-vignette.html
@@ -26,7 +26,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/articles/risks-vignette.html b/articles/risks-vignette.html
index e538500..5b1410d 100644
--- a/articles/risks-vignette.html
+++ b/articles/risks-vignette.html
@@ -26,7 +26,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/authors.html b/authors.html
index c5b3280..e6d4076 100644
--- a/authors.html
+++ b/authors.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -64,13 +64,13 @@ <h2 id="citation">Citation</h2>
 
       <p>Park B (2024).
 <em>cancerprof: API Client for State Cancer Profiles</em>.
-R package version 0.0.0.9000, http://getwilds.org/cancerprof/, <a href="https://github.com/getwilds/cancerprof" class="external-link">https://github.com/getwilds/cancerprof</a>. 
+R package version 0.1.0, http://getwilds.org/cancerprof/, <a href="https://github.com/getwilds/cancerprof" class="external-link">https://github.com/getwilds/cancerprof</a>. 
 </p>
       <pre>@Manual{,
   title = {cancerprof: API Client for State Cancer Profiles},
   author = {Brian Park},
   year = {2024},
-  note = {R package version 0.0.0.9000, http://getwilds.org/cancerprof/},
+  note = {R package version 0.1.0, http://getwilds.org/cancerprof/},
   url = {https://github.com/getwilds/cancerprof},
 }</pre>
     </div>
diff --git a/index.html b/index.html
index 060d818..ed1b253 100644
--- a/index.html
+++ b/index.html
@@ -26,7 +26,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/pkgdown.yml b/pkgdown.yml
index 484d7a1..e936332 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -6,7 +6,7 @@ articles:
   incidence-vignette: incidence-vignette.html
   mortality-vignette: mortality-vignette.html
   risks-vignette: risks-vignette.html
-last_built: 2024-04-01T19:08Z
+last_built: 2024-04-02T20:29Z
 urls:
   reference: http://getwilds.org/cancerprof/reference
   article: http://getwilds.org/cancerprof/articles
diff --git a/reference/cancerprof-package.html b/reference/cancerprof-package.html
index 78c88e9..40e5709 100644
--- a/reference/cancerprof-package.html
+++ b/reference/cancerprof-package.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_crowding.html b/reference/demo_crowding.html
index cca4968..5e5ca99 100644
--- a/reference/demo_crowding.html
+++ b/reference/demo_crowding.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_education.html b/reference/demo_education.html
index 200dbd4..0a58815 100644
--- a/reference/demo_education.html
+++ b/reference/demo_education.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_food.html b/reference/demo_food.html
index 82b66b2..56dc0ce 100644
--- a/reference/demo_food.html
+++ b/reference/demo_food.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_income.html b/reference/demo_income.html
index 60273e1..eb9b6cd 100644
--- a/reference/demo_income.html
+++ b/reference/demo_income.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_insurance.html b/reference/demo_insurance.html
index dfefbe4..682b70e 100644
--- a/reference/demo_insurance.html
+++ b/reference/demo_insurance.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_language.html b/reference/demo_language.html
index 970931d..67f4b2b 100644
--- a/reference/demo_language.html
+++ b/reference/demo_language.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_mobility.html b/reference/demo_mobility.html
index 1bfd525..5a63a97 100644
--- a/reference/demo_mobility.html
+++ b/reference/demo_mobility.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_population.html b/reference/demo_population.html
index 8cb89c3..7a1fd09 100644
--- a/reference/demo_population.html
+++ b/reference/demo_population.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_poverty.html b/reference/demo_poverty.html
index 73b751e..69c3680 100644
--- a/reference/demo_poverty.html
+++ b/reference/demo_poverty.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_svi.html b/reference/demo_svi.html
index 32bd40b..101fed6 100644
--- a/reference/demo_svi.html
+++ b/reference/demo_svi.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/demo_workforce.html b/reference/demo_workforce.html
index 3c371bc..a3e1dc6 100644
--- a/reference/demo_workforce.html
+++ b/reference/demo_workforce.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/incidence_cancer.html b/reference/incidence_cancer.html
index 0de17a6..c56f3c8 100644
--- a/reference/incidence_cancer.html
+++ b/reference/incidence_cancer.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/index.html b/reference/index.html
index 2e228f7..715ae1f 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/mortality_cancer.html b/reference/mortality_cancer.html
index 0e86e6b..4adf5b7 100644
--- a/reference/mortality_cancer.html
+++ b/reference/mortality_cancer.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/pipe.html b/reference/pipe.html
index 932111b..e21bf86 100644
--- a/reference/pipe.html
+++ b/reference/pipe.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/risk_alcohol.html b/reference/risk_alcohol.html
index 56c5328..81535f9 100644
--- a/reference/risk_alcohol.html
+++ b/reference/risk_alcohol.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/risk_colorectal_screening.html b/reference/risk_colorectal_screening.html
index 8ab8baf..cdbcebc 100644
--- a/reference/risk_colorectal_screening.html
+++ b/reference/risk_colorectal_screening.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/risk_diet_exercise.html b/reference/risk_diet_exercise.html
index 9f454c9..5b7c9ad 100644
--- a/reference/risk_diet_exercise.html
+++ b/reference/risk_diet_exercise.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/risk_smoking.html b/reference/risk_smoking.html
index 46343dc..f3adc16 100644
--- a/reference/risk_smoking.html
+++ b/reference/risk_smoking.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/risk_vaccines.html b/reference/risk_vaccines.html
index c49ecf9..69b588c 100644
--- a/reference/risk_vaccines.html
+++ b/reference/risk_vaccines.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/risk_women_health.html b/reference/risk_women_health.html
index 311eb95..bb90c7b 100644
--- a/reference/risk_women_health.html
+++ b/reference/risk_women_health.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cancerprof</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.0.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/search.json b/search.json
index d1c0990..7e43720 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing","title":"Contributing","text":"outlines propose change usethis. detailed info contributing , WILDS projects, please see WILDS Contributing Guide.","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"fixing-typosdocs-changes","dir":"","previous_headings":"","what":"Fixing typos/docs changes","title":"Contributing","text":"can fix typos, spelling mistakes, grammatical errors documentation directly using GitHub web interface, long changes made source file.","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"bigger-changes","dir":"","previous_headings":"","what":"Bigger changes","title":"Contributing","text":"want make bigger change, ’s good idea first file issue make sure someone team agrees ’s needed. ’ve found bug, please file issue illustrates bug minimal reproducible example (reprex R, reprexpy Python).","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"Bigger changes","what":"Pull request process","title":"Contributing","text":"Fork package clone onto computer Create Git branch pull request (PR) title PR briefly describe change. body PR contain Fixes #issue-number. user-facing changes, add bullet changelog file one. NEWS.md R package, likely Changelog.md Changelog.rst Python package.","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"code-style","dir":"","previous_headings":"Bigger changes","what":"Code style","title":"Contributing","text":"New code R Python packages follow style guide.","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing","text":"Please note project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"http://getwilds.org/cancerprof/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 cancerprof authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"load-the-package","dir":"Articles","previous_headings":"","what":"Load the package","title":"Demographics","text":"","code":"library(cancerprof)"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"retrieving-data","dir":"Articles","previous_headings":"","what":"Retrieving Data","title":"Demographics","text":"demographics category cancerprof contains 11 unique functions pull data demographics page State Cancer Profile. functions : demo_crowding(), demo_education(), demo_food(), demo_income(), demo_insurance(), demo_mobility(), demo_non_english_language(), demo_population(), demo_poverty(), demo_svi(), demo_workforce() functions require various parameters must specified pull data. Please refer function documentation details.","code":""},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-crowding","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Crowding","title":"Demographics","text":"Demo crowding Always requires 4 arguments: area, areatype, crowding, race","code":"crowding <- demo_crowding(   area = \"WA\",   areatype = \"county\",   crowding = \"household with >1 person per room\",   race = \"All Races (includes Hispanic)\" ) head(crowding, n = 3) #>             County  FIPS Percent Households         Rank #> 1  Columbia County 53013     1.4         25 2111 of 3143 #> 2 Jefferson County 53031     1.4        211 2095 of 3143 #> 3   Whitman County 53075     1.4        246 2090 of 3143"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-education","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Education","title":"Demographics","text":"Demo education 5 arguments: area, areatype, education, sex, race. Depending education argument, required arguments change","code":"# at least high school - requires arguments: area, areatype, education, sex education1 <- demo_education(   area = \"wa\",   areatype = \"county\",   education = \"at least high school\",   sex = \"males\" )  head(education1, n = 3) #>           County  FIPS Percent Households         Rank #> 1 Whitman County 53075    95.5      11789 3037 of 3143 #> 2  Kitsap County 53035    95.1      91509 3012 of 3143 #> 3  Island County 53029    95.0      29073 2995 of 3143  # at least bachelors degree - requires arguments: # area, areatype, education, sex, race education2 <- demo_education(   area = \"usa\",   areatype = \"state\",   education = \"at least bachelors degree\",   sex = \"both sexes\",   race = \"all races (includes hispanic)\" )  head(education2, n = 3) #>           State  FIPS Percent Households     Rank #> 1 West Virginia 54000    21.8     278281 52 of 52 #> 2   Mississippi 28000    23.2     458928 51 of 52 #> 3      Arkansas 05000    24.3     491269 50 of 52  # less than 9th grade - requires arguments: area, areatype, education education3 <- demo_education(   area = \"pr\",   areatype = \"hsa\",   education = \"less than 9th grade\" )  head(education3, n = 3) #>   Health_Service_Area HSA_Code Percent Households       Rank #> 1         Puerto Rico     0995    14.1     337405 935 of 950"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-food","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Food","title":"Demographics","text":"Demo food 4 arguments: area, areatype, food, race.","code":"# limited access to healthy food - requires arguments: area, areatype, food food1 <- demo_food(   area = \"usa\",   areatype = \"state\",   food = \"limited access to healthy food\" )  head(food1, n = 3) #>         State  FIPS Percent People #> 1  New Mexico 35000      13 268515 #> 2   Louisiana 22000      11 483383 #> 3 Mississippi 28000      11 337505  # food insecurity - requires arguments: area, areatype, food, race food2 <- demo_food(   area = \"pr\",   areatype = \"county\",   food = \"food insecurity\",   race = \"all races (includes hispanic)\" )  head(food2, n = 3) #>        County  FIPS Percent #> 1 Puerto Rico 72001      NA"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-income","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Income","title":"Demographics","text":"Demo income Always requires 4 arguments: area, areatype, income, race.","code":"# limited access to healthy food - requires arguments: area, areatype, food income1 <- demo_income(   area = \"wa\",   areatype = \"county\",   income = \"median household income\",   race = \"all races (includes hispanic)\" )  head(income1, n = 3) #>            County  FIPS Dollars         Rank #> 1  Whitman County 53075   43613 2700 of 3142 #> 2    Ferry County 53019   45907 2529 of 3142 #> 3 Garfield County 53023   50625 2168 of 3142  # food insecurity - requires arguments: area, areatype, food, race income2 <- demo_income(   area = \"usa\",   areatype = \"state\",   income = \"median family income\",   race = \"all races (includes hispanic)\" )  head(income2, n = 3) #>         State  FIPS Dollars     Rank #> 1 Puerto Rico 72001   26745 52 of 52 #> 2 Mississippi 28000   62802 51 of 52 #> 3    Arkansas 05000   65673 50 of 52"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-insurance","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Insurance","title":"Demographics","text":"Demo insurance 6 arguments: area, areatype, insurance, sex, age, race. Please note age arguments \"sexes\" different “Males ”Females” Check function documentations details Areatype \"state\" can select Race, otherwise race always \"races (includes hispanic)\"","code":"insurance1 <- demo_insurance(   area = \"usa\",   areatype = \"state\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"both sexes\",   age = \"18 to 64 years\",   race = \"white (non-hispanic)\" )  head(insurance1, n = 3) #>         State  FIPS Percent  People     Rank #> 1    Oklahoma 40000    84.6 1256749 51 of 51 #> 2 Mississippi 28000    85.2  809125 50 of 51 #> 3     Wyoming 56000    85.4  238655 49 of 51  insurance2 <- demo_insurance(   area = \"wa\",   areatype = \"county\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"males\",   age = \"18 to 64 years\" )  head(insurance2, n = 3) #>          County  FIPS Percent People         Rank #> 1  Adams County 53001    73.8   4073 2890 of 3141 #> 2 Yakima County 53077    77.2  54771 2679 of 3141 #> 3  Grant County 53025    79.4  23081 2464 of 3141"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-mobility","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Mobility","title":"Demographics","text":"Demo mobility Always requires 3 arguments: area, areatype, mobility. function defaults \"races\", \"sexes\", \"ages 1+\"","code":"mobility1 <- demo_mobility(   area = \"usa\",   areatype = \"state\",   mobility = \"moved, same county (in past year)\" )  head(mobility1, n = 3) #>                  State  FIPS Percent People     Rank #> 1               Nevada 32000    10.6 321900 51 of 51 #> 2              Arizona 04000    10.2 716304 50 of 51 #> 3 District of Columbia 11001    10.2  68557 49 of 51   mobility2 <- demo_mobility(   area = \"WA\",   areatype = \"county\",   mobility = \"moved, different county, same state (in past year)\" )  head(mobility2, n = 3) #>                County  FIPS Percent People         Rank #> 1     Kittitas County 53037    12.7   5563 3114 of 3142 #> 2      Whitman County 53075    10.9   5224 3093 of 3142 #> 3 Grays Harbor County 53027     5.8   4314 2619 of 3142"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-language","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Language","title":"Demographics","text":"Demo Language Always requires 3 arguments: area, areatype, language. function defaults \"races\", \"sexes\", \"ages 14+\"","code":"non_english1 <- demo_language(   area = \"wa\",   areatype = \"county\",   language = \"language isolation\" )  head(non_english1, n = 3) #>            County  FIPS Percent Households         Rank #> 1    Adams County 53001    18.9       1165 3127 of 3142 #> 2 Franklin County 53021    11.0       3044 3087 of 3142 #> 3    Grant County 53025     8.6       2810 3044 of 3142   non_english2 <- demo_language(   area = \"usa\",   areatype = \"state\",   language = \"language isolation\" )  head(non_english2, n = 3) #>        State  FIPS Percent Households     Rank #> 1 California 06000     8.5    1119486 51 of 51 #> 2   New York 36000     7.6     571749 50 of 51 #> 3      Texas 48000     7.1     731111 49 of 51"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-population","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Population","title":"Demographics","text":"Demo Population 5 arguments: area, areatype, population, race, sex. population argument used input population variable age, race, sex. Please note different race sex arguments different population variables default race, sex, age. select \"foreign born\" population, must provide another race race argument","code":"# population1 <- demo_population(   area = \"wa\",   areatype = \"county\",   population = \"foreign born\",   race = \"black\",   sex = \"females\" )  head(population1, n = 3) #>                County  FIPS Percent People         Rank #> 1     Columbia County 53013       0      0 1666 of 2885 #> 2 Grays Harbor County 53027       0      0 1666 of 2885 #> 3    Jefferson County 53031       0      0 1666 of 2885   population2 <- demo_population(   area = \"ca\",   areatype = \"county\",   population = \"males\",   race = \"all races (includes hispanic)\" )  head(population2, n = 3) #>          County  FIPS Percent People         Rank #> 1 Lassen County 06035    64.8  21361 3134 of 3143 #> 2  Kings County 06031    55.2  83872 3015 of 3143 #> 3   Mono County 06051    54.8   7284 2987 of 3143  population3 <- demo_population(   area = \"usa\",   areatype = \"state\",   population = \"age under 18\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" )  head(population3, n = 3) #>                  State  FIPS Percent People     Rank #> 1          Puerto Rico 72001    18.0 597277 52 of 52 #> 2 District of Columbia 11001    18.3 125022 51 of 52 #> 3              Vermont 50000    18.5 118889 50 of 52"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-poverty","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Poverty","title":"Demographics","text":"Demo poverty 5 arguments: area, areatype, poverty, race, sex. function defaults \"ages\" \"persistent poverty\" \"persons <150% poverty\" poverty argument default \"races\", \"sexes\", \"ages\". \"families poverty\" poverty argument require race argument default \"sexes\" \"ages\". \"persons poverty\" poverty argument require race argument sex argument, default \"ages\".","code":"# Persistent poverty poverty1 <- demo_poverty(   area = \"WA\",   areatype = \"county\",   poverty = \"persistent poverty\" )  head(poverty1, n = 3) #>           County  FIPS Persistent Poverty #> 1 Whitman County 53075                yes #> 2   Adams County 53001                 no #> 3  Asotin County 53003                 no  # Families below poverty poverty2 <- demo_poverty(   area = \"usa\",   areatype = \"state\",   poverty = \"families below poverty\",   race = \"black\" )  head(poverty2, n = 3) #>         State  FIPS Percent People     Rank #> 1 Puerto Rico 72001    40.9  33658 52 of 52 #> 2     Wyoming 56000    33.1    349 51 of 52 #> 3        Iowa 19000    26.6   6200 50 of 52  # Persons below poverty poverty3 <- demo_poverty(   area = \"usa\",   areatype = \"state\",   poverty = \"persons below poverty\",   race = \"black\",   sex = \"males\" )  head(poverty3, n = 3) #>         State  FIPS Percent People     Rank #> 1 Puerto Rico 72001    42.2  67037 52 of 52 #> 2   Louisiana 22000    28.3 188456 51 of 52 #> 3 Mississippi 28000    28.2 139358 50 of 52"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-social-vulnerability-index-svi","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Social Vulnerability Index (SVI)","title":"Demographics","text":"Demo svi Always requires 2 arguments: area, svi. function defaults \"races\", \"sexes\", \"ages\". Please note areatype argument available function areatype limited \"county\"","code":"svi1 <- demo_svi(   area = \"WA\",   svi = \"overall\" )  head(svi1, n = 3) #>            County  FIPS  Score #> 1    Adams County 53001 0.9656 #> 2   Yakima County 53077 0.9570 #> 3 Okanogan County 53047 0.9532   svi2 <- demo_svi(   area = \"usa\",   svi = \"socioeconomic status\" )  head(svi2, n = 3) #>                                       County  FIPS  Score #> 1 Oglala Lakota/Shannon County, South Dakota 46102 1.0000 #> 2                      Macon County, Georgia 13193 0.9997 #> 3              Humphreys County, Mississippi 28053 0.9994"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"workforce","dir":"Articles","previous_headings":"Retrieving Data","what":"Workforce","title":"Demographics","text":"Demo svi Always requires 5 arguments: area, areatype, workforce, race, sex. function defaults “ages 16+”","code":"workforce1 <- demo_workforce(   area = \"WA\",   areatype = \"county\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" )  head(workforce1, n = 3) #>             County  FIPS Percent People_Unemployed         Rank #> 1  Garfield County 53023    11.0               110 3045 of 3143 #> 2 Jefferson County 53031     7.6               953 2735 of 3143 #> 3   Whitman County 53075     7.5              1849 2700 of 3143   workforce2 <- demo_workforce(   area = \"usa\",   areatype = \"state\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"females\" )  head(workforce2, n = 3) #>                  State  FIPS Percent People_Unemployed     Rank #> 1          Puerto Rico 72001    14.5             85552 52 of 52 #> 2               Nevada 32000     7.2             50777 51 of 52 #> 3 District of Columbia 11001     7.1             14769 50 of 52"},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"load-the-package","dir":"Articles","previous_headings":"","what":"Load the package","title":"incidence-vignette","text":"","code":"library(cancerprof)"},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"retrieving-data","dir":"Articles","previous_headings":"","what":"Retrieving Data","title":"incidence-vignette","text":"Cancer Incidence category cancerprof contains single functions pull data Incidence page State Cancer Profile. function retrieving incidence data incidence_cancer()","code":""},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"incidence-cancer","dir":"Articles","previous_headings":"","what":"Incidence Cancer","title":"incidence-vignette","text":"Incidence cancer 23 cancer types choose . total, incidence cancer 8 arguments: area, areatype, cancer, race, sex, age, stage, year","code":""},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"argument-details","dir":"Articles","previous_headings":"Incidence Cancer","what":"Argument Details","title":"incidence-vignette","text":"\"latest single year (us state)\" argument year can selected area \"state\" following cancer types: “breast (female situ)”, “childhood (ages <15, sites)”, “childhood (ages <20, sites)”, “leukemia” stage argument must \"stages\" following cancer types: “breast (female)”, “breast (female situ)”, “ovary”, “uterus (corpus & uterus, nos)” sex argument must \"females\" \"prostate\" cancer, sex must \"males\" \"childhood (ages <15, sites)\", age must \"ages <15\" \"childhood (ages <20, sites)\", age must \"ages <20\"","code":""},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"examples","dir":"Articles","previous_headings":"Incidence Cancer","what":"Examples","title":"incidence-vignette","text":"","code":"incidence1 <- incidence_cancer(   area = \"usa\",   areatype = \"state\",   cancer = \"lung & bronchus\",   race = \"all races (includes hispanic)\",   sex = \"males\",   age = \"ages 50+\",   stage = \"late stage (regional & distant)\",   year = \"latest single year (us by state)\" ) head(incidence1, n = 3) #>               State  FIPS Age_Adjusted_Incidence_Rate Lower_95%_CI Upper_95%_CI CI_Rank Lower_CI_Rank Upper_CI_Rank Annual_Average_Count #> 1 US (SEER+NPCR)(1) 00000                       122.7        121.8        123.7      NA            NA            NA                65692 #> 2       Kentucky(3) 21000                       216.2        205.7        227.2       1             1             1                 1660 #> 3    Mississippi(2) 28000                       178.0        166.0        190.6       2             2             7                  868 #>   Percentage_of_Cases_with_Late_Stage #> 1                                67.0 #> 2                                70.3 #> 3                                68.3  incidence2 <- incidence_cancer(   area = \"wa\",   areatype = \"hsa\",   cancer = \"ovary\",   race = \"all races (includes hispanic)\",   sex = \"females\",   age = \"ages 50+\",   stage = \"late stage (regional & distant)\",   year = \"latest 5 year average\" ) head(incidence2, n = 3) #>          Health_Service_Area HSA_Code Age_Adjusted_Incidence_Rate Lower_95%_CI Upper_95%_CI CI_Rank Lower_CI_Rank Upper_CI_Rank #> 1              Washington(5)    53000                        20.5         19.4         21.6      NA             4            29 #> 2          US (SEER+NPCR)(1)    00000                        19.7         19.6         19.9      NA            NA            NA #> 3 Lewis, WA - Pacific, WA(6)     0832                        28.4         19.2         40.5       1             1             9 #>   Annual_Average_Count Percentage_of_Cases_with_Late_Stage #> 1                  278                                76.0 #> 2                11948                                73.5 #> 3                    7                                76.7  incidence3 <- incidence_cancer(   area = \"wa\",   areatype = \"county\",   cancer = \"all cancer sites\",   race = \"black (non-hispanic)\",   sex = \"both sexes\",   age = \"ages 65+\",   stage = \"all stages\",   year = \"latest 5 year average\" ) head(incidence3, n = 3) #>               County  FIPS Age_Adjusted_Incidence_Rate Lower_95%_CI Upper_95%_CI CI_Rank Lower_CI_Rank Upper_CI_Rank Annual_Average_Count #> 1      Washington(5) 53000                      1926.6       1847.1       2008.6      NA             5            32                  493 #> 2  US (SEER+NPCR)(1) 00000                      1898.1       1892.4       1903.8      NA            NA            NA                89582 #> 3 Thurston County(7) 53067                      2720.3       2140.8       3408.4       2             1             8                   18 #>   Recent_Trend Recent_5_Year_Trend Trend_Lower_95%_CI Trend_Upper_95%_CI #> 1      falling                -1.7               -2.4               -0.9 #> 2      falling                -0.5               -0.8               -0.2 #> 3         <NA>                  NA                 NA                 NA"},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"load-the-package","dir":"Articles","previous_headings":"","what":"Load the package","title":"mortality-vignette","text":"","code":"library(cancerprof)"},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"retrieving-data","dir":"Articles","previous_headings":"","what":"Retrieving Data","title":"mortality-vignette","text":"Cancer Mortality category cancerprof contains single functions pull data Mortality page State Cancer Profile. function retrieving incidence data mortality_cancer()","code":""},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"mortality-cancer","dir":"Articles","previous_headings":"","what":"Mortality Cancer","title":"mortality-vignette","text":"Mortality cancer 22 cancer types choose . total, incidence cancer 7 arguments: area, areatype, cancer, race, sex, age, year","code":""},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"argument-details","dir":"Articles","previous_headings":"Mortality Cancer","what":"Argument Details","title":"mortality-vignette","text":"\"latest single year (us state)\" argument year can selected area \"state\" following cancer types: “breast (female)”, “ovary”, “uterus (corpus & uterus, nos)” sex argument must \"females\" \"prostate\" cancer, sex must \"males\" \"childhood (ages <15, sites)\", age must \"ages <15\" \"childhood (ages <20, sites)\", age must \"ages <20\"","code":""},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"examples","dir":"Articles","previous_headings":"Mortality Cancer","what":"Examples","title":"mortality-vignette","text":"","code":"mortality1 <- mortality_cancer(   area = \"wa\",   areatype = \"county\",   cancer = \"all cancer sites\",   race = \"black (non-hispanic)\",   sex = \"both sexes\",   age = \"ages 65+\",   year = \"latest 5 year average\" ) head(mortality1, n = 3) #>            County  FIPS Met Healthy People Objective of ***? Age_Adjusted_Death_Rate Lower_95%_CI_Rate Upper_95%_CI_Rate CI_Rank Lower_CI_Rank #> 1   Yakima County 53077                                   No                  1676.3             947.3            2727.3       1             1 #> 2 Thurston County 53067                                   No                  1187.5             791.2            1704.8       2             1 #> 3   Pierce County 53053                                   No                  1099.3             971.9            1238.8       3             1 #>   Upper_CI_Rank Annual_Average_Count Recent_Trend Recent_5_Year_Trend Lower_95%_CI_Trend Upper_95%_CI_Trend #> 1             5                    3         <NA>                  NA                 NA                 NA #> 2             7                    7         <NA>                  NA                 NA                 NA #> 3             5                   59      falling                -0.9               -1.7               -0.1  mortality2 <- mortality_cancer(   area = \"usa\",   areatype = \"state\",   cancer = \"prostate\",   race = \"all races (includes hispanic)\",   sex = \"males\",   age = \"ages 50+\",   year = \"latest single year (us by state)\" ) head(mortality2, n = 3) #>                  State  FIPS Met Healthy People Objective of ***? Age_Adjusted_Death_Rate Lower_95%_CI_Rate Upper_95%_CI_Rate CI_Rank #> 1 District of Columbia 11001                                   No                    98.9              77.6             124.1       1 #> 2             Colorado 08000                                   No                    86.1              79.3              93.3       2 #> 3              Vermont 50000                                   No                    84.4              67.8             103.9       3 #>   Lower_CI_Rank Upper_CI_Rank Annual_Average_Count Recent_Trend Recent_5_Year_Trend Lower_95%_CI_Trend Upper_95%_CI_Trend #> 1             1            35                   76      falling                -3.3               -3.9               -2.8 #> 2             1             9                  623       stable                -0.1               -1.0                0.9 #> 3             1            46                   93       stable                 4.7               -3.8               13.9  mortality3 <- mortality_cancer(   area = \"wa\",   areatype = \"hsa\",   cancer = \"ovary\",   race = \"all races (includes hispanic)\",   sex = \"females\",   age = \"ages 50+\",   year = \"latest 5 year average\" ) head(mortality3, n = 3) #>           Health_Service_Area HSA_Code Met Healthy People Objective of ***? Age_Adjusted_Death_Rate Lower_95%_CI_Rate Upper_95%_CI_Rate #> 1 Clallam, WA - Jefferson, WA     0785                                  ***                    34.6              26.3              44.8 #> 2                 Whatcom, WA     0815                                  ***                    31.4              24.2              40.0 #> 3                  Pierce, WA     0794                                  ***                    24.6              21.1              28.6 #>   CI_Rank Lower_CI_Rank Upper_CI_Rank Annual_Average_Count Recent_Trend Recent_5_Year_Trend Lower_95%_CI_Trend Upper_95%_CI_Trend #> 1       1             1             4                   12       stable                -1.0               -2.4                0.3 #> 2       2             1             6                   14       stable                -0.7               -2.1                0.7 #> 3       3             2             9                   36      falling                -1.4               -2.0               -0.9"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"load-the-package","dir":"Articles","previous_headings":"","what":"Load the package","title":"Screening and Risk Factors","text":"","code":"library(cancerprof)"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"retrieving-data","dir":"Articles","previous_headings":"","what":"Retrieving Data","title":"Screening and Risk Factors","text":"Screening Risk Factors category cancerprof contains 6 unique functions pull data Screening Risk Factor page State Cancer Profile. functions : risk_alcohol(), risk_colorectal_screening(), risk_diet_exercise(), risk_smoking(), risk_vaccines(), risk_womens_health() functions require various parameters must specified pull data. Please refer function documentation details.","code":""},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-alcohol","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Alcohol","title":"Screening and Risk Factors","text":"Risk Alcohol requires 3 arguments: alcohol, race, sex","code":"alcohol1 <- risk_alcohol(   alcohol = paste(     \"binge drinking (4+ drinks on one occasion for women,\",     \"5+ drinks for one occasion for men), ages 21+\"   ),   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) head(alcohol1, n = 3) #>                  State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 District of Columbia 11001    26.2         23.9         28.4                   566 #> 2         North Dakota 38000    22.8         21.1         24.5                   676 #> 3                 Iowa 19000    21.9         20.7         23.1                  1515"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-colorectal-screening","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Colorectal Screening","title":"Screening and Risk Factors","text":"Risk Colorectal Screening 4 arguments: screening, race, sex, area \"home blood stool test past year, ages 45-75\" \"received least one recommended crc test, ages 45-75\" screening arguments requires race argument sex argument defaults \"direct estimates\", \"US state\". \"ever fobt, ages 50-75\", \"guidance sufficient crc, ages 50-75\", \"colonoscopy past 10 years, ages 50-75\" screening arguments defaults \"races\", \"sexes\", \"county level modeled estimates\".","code":"screening1 <- risk_colorectal_screening(   screening = \"home blood stool test in the past year, ages 45-75\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) head(screening1, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1     Wyoming 56000     3.0          2.2          3.7                    75 #> 2 Mississippi 28000     3.4          2.3          4.5                    64 #> 3    Delaware 10000     3.8          3.0          4.7                   106  screening2 <- risk_colorectal_screening(   screening = \"ever had fobt, ages 50-75\",   area = \"usa\" ) head(screening2, n = 3) #>               County  FIPS Model_Based_Percent (95%_Confidence_Interval) Lower_95%_CI Upper_95%_CI #> 1 New Hanover County 37129                                           0.2            0          1.2 #> 2    Columbus County 37047                                           0.3            0          1.5 #> 3       Dixon County 31051                                           0.3            0          1.5"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-diet-exercise","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Diet-Exercise","title":"Screening and Risk Factors","text":"Risk Diet-Exercise requires 3 arguments: diet_exercise , race, sex","code":"diet_exercise1 <- risk_diet_exercise(   diet_exercise = \"bmi is healthy, ages 20+\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) head(diet_exercise1, n = 3) #>           State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 West Virginia 54000    22.5         21.0         24.0                  1061 #> 2   Mississippi 28000    24.8         23.0         26.6                   906 #> 3      Oklahoma 40000    25.1         23.6         26.5                  1304  diet_exercise2 <- risk_diet_exercise(   diet_exercise = \"bmi is obese, high school survey\",   race = \"all races (includes hispanic)\",   sex = \"males\" ) head(diet_exercise2, n = 3) #>           State  FIPS Percent Lower_95%_CI Upper_95%_CI #> 1 West Virginia 54000    29.5         20.6         40.2 #> 2   Mississippi 28000    28.0         25.2         30.9 #> 3         Texas 48000    25.7         22.4         29.3"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-smoking","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Smoking","title":"Screening and Risk Factors","text":"Risk Smoking arguments 5: smoking, race, sex, datatype, area. following smoking arguments: \"smoking laws ()\" \"smoking laws (bars)\" \"smoking laws (restaurants)\" \"smoking laws (workplace)\" \"smoking laws (workplace; restaurant; & bar)\" include smoking argument. race, sex, datatype, area defaulted \"races\", \"sexes\", \"direct estimates\", \"US State\" following smoking arguments: “smokers (stopped 1 day longer)”, “smoking allowed work (people)”, “smoking allowed home (people)” Select sex argument. \"sexes\" selected sex, select datatype argument. \"county level modeled estimates\" selected datatype, select area argument. race, always defaulted \"races\". datatype area always defaulted \"direct estimates\", \"US State\" sex “male” “female”. following smoking arguments: \"smoking allowed work (current smokers)\" \"smoking allowed work (former/never smokers)\" \"smoking allowed home (current smokers)\" \"smoking allowed home (former/never smokers)\" Select sex argument. race, datatype, area defaulted \"races\", \"direct estimates\", \"US State\". following smoking arguments: \"former smoker; ages 18+\" \"former smoker, quit 1 year+; ages 18+\" Select sex area argument. race datatype defaulted \"races\", \"direct estimates\" following smoking arguments: \"smokers (ever); ages 18+\" \"e-cigarette use; ages 18+\" Select race sex argument. datatype area defaulted \"direct estimates\" \"US State\". “smokers (current); ages 18+” Select race sex argument. \"races (includes hispanic)\" selected race, select datatype argument. \"county level modeled estimates\" selected datatype, select area argument. datatype area always defaulted \"direct estimates\", \"US State\" race \"races (includes hispanic)\".","code":"smoking1 <- risk_smoking(   smoking = \"smokers (stopped for 1 day or longer)\",   sex = \"both sexes\",   datatype = \"county level modeled estimates\",   area = \"wa\" ) head(smoking1, n = 3) #>            County  FIPS Percent Lower_95%_CI Upper_95%_CI #> 1    Grant County 53025    40.8         28.2         53.8 #> 2 Kittitas County 53037    41.4         29.0         54.3 #> 3 Thurston County 53067    41.7         29.2         54.3  smoking2 <- risk_smoking(   smoking = \"smoking not allowed at work (current smokers)\",   sex = \"both sexes\",   datatype = \"direct estimates\" ) head(smoking2, n = 3) #>     State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1  Nevada 32000    55.2         43.9         65.9                    55 #> 2 Wyoming 56000    57.9         47.1         68.0                    69 #> 3    Utah 49000    61.2         47.5         73.3                    39  smoking3 <- risk_smoking(   smoking = \"smokers (current); ages 18+\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\",   datatype = \"county level modeled estimates\",   area = \"wa\" ) head(smoking3, n = 3) #>           County  FIPS Percent Lower_95%_CI Upper_95%_CI #> 1   Mason County 53045    17.9         13.6         22.8 #> 2 Cowlitz County 53015    17.8         13.9         22.2 #> 3 Stevens County 53065    17.1         12.9         21.8"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-vaccines","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Vaccines","title":"Screening and Risk Factors","text":"Risk Vaccines requires 2 arguments: vaccines sex","code":"vaccines1 <- risk_vaccines(    vaccine = \"percent with up to date hpv vaccination coverage, ages 13-17\",    sex = \"females\" ) head(vaccines1, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 Mississippi 28000    32.6         23.9         42.6                    48 #> 2     Wyoming 56000    48.7         38.2         59.3                    70 #> 3    Kentucky 21000    48.9         37.2         60.7                    59  vaccines2 <- risk_vaccines(    vaccine = \"percent with up to date hpv vaccination coverage, ages 13-15\",    sex = \"both sexes\" ) head(vaccines2, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 Mississippi 28000    35.9         27.7         45.0                    59 #> 2     Wyoming 56000    44.0         34.9         53.5                    79 #> 3       Texas 48000    46.4         39.6         53.3                   318"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-womens-health","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Women’s Health","title":"Screening and Risk Factors","text":"Risk Women’s Health 4 arguments: women_health, race, datatype, area \"races (includes hispanic)\" selected race, select datatype argument. race selected, datatype area defaulted \"direct estimates\" \"US State\".","code":"vaccines1 <- risk_vaccines(    vaccine = \"percent with up to date hpv vaccination coverage, ages 13-17\",    sex = \"females\" ) head(vaccines1, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 Mississippi 28000    32.6         23.9         42.6                    48 #> 2     Wyoming 56000    48.7         38.2         59.3                    70 #> 3    Kentucky 21000    48.9         37.2         60.7                    59  vaccines2 <- risk_vaccines(    vaccine = \"percent with up to date hpv vaccination coverage, ages 13-15\",    sex = \"both sexes\" ) head(vaccines2, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 Mississippi 28000    35.9         27.7         45.0                    59 #> 2     Wyoming 56000    44.0         34.9         53.5                    79 #> 3       Texas 48000    46.4         39.6         53.3                   318"},{"path":"http://getwilds.org/cancerprof/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Brian Park. Author, maintainer.","code":""},{"path":"http://getwilds.org/cancerprof/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Park B (2024). cancerprof: API Client State Cancer Profiles. R package version 0.0.0.9000, http://getwilds.org/cancerprof/, https://github.com/getwilds/cancerprof.","code":"@Manual{,   title = {cancerprof: API Client for State Cancer Profiles},   author = {Brian Park},   year = {2024},   note = {R package version 0.0.0.9000, http://getwilds.org/cancerprof/},   url = {https://github.com/getwilds/cancerprof}, }"},{"path":[]},{"path":"http://getwilds.org/cancerprof/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"API Client for State Cancer Profiles","text":"Cancerprof designed allow programmable research data State Cancer Profiles","code":""},{"path":"http://getwilds.org/cancerprof/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"API Client for State Cancer Profiles","text":"can install development version cancerprof GitHub :","code":"# install.packages(\"pak\") pak::pak(\"getwilds/cancerprof\")"},{"path":"http://getwilds.org/cancerprof/index.html","id":"support","dir":"","previous_headings":"","what":"Support","title":"API Client for State Cancer Profiles","text":"questions, bugs, feature requests, please reach Brian Park joon.brianpark@gmail.com, open issue issue tracker","code":""},{"path":"http://getwilds.org/cancerprof/reference/cancerprof-package.html","id":null,"dir":"Reference","previous_headings":"","what":"cancerprof: API Client for State Cancer Profiles — cancerprof-package","title":"cancerprof: API Client for State Cancer Profiles — cancerprof-package","text":"API Client accessing data State Cancer Profiles programmable analysis.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/cancerprof-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"cancerprof: API Client for State Cancer Profiles — cancerprof-package","text":"Maintainer: Brian Park joon.brianpark@gmail.com (ORCID)","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Crowding Data — demo_crowding","title":"Access to Crowding Data — demo_crowding","text":"function returns data frame crowding demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Crowding Data — demo_crowding","text":"","code":"demo_crowding(area, areatype, crowding, race)"},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Crowding Data — demo_crowding","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". crowding permissible value \"household >1 person per room\". race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White Non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Crowding Data — demo_crowding","text":"data frame following columns: Area, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Crowding Data — demo_crowding","text":"","code":"if (FALSE) { demo_crowding(   area = \"WA\",   areatype = \"county\",   crowding = \"household with >1 person per room\",   race = \"All Races (includes Hispanic)\" )  demo_crowding(   area = \"usa\",   areatype = \"state\",   crowding = \"household with >1 person per room\",   race = \"All Races (includes Hispanic)\" )  demo_crowding(   area = \"pr\",   areatype = \"hsa\",   crowding = \"household with >1 person per room\",   race = \"black\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Education Data — demo_education","title":"Access to Education Data — demo_education","text":"function returns data frame education demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Education Data — demo_education","text":"","code":"demo_education(area, areatype, education, sex = NULL, race = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Education Data — demo_education","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". education One following values: \"less 9th grade\" \"least high school\" \"least bachelors degree\". sex One following values: \"sexes\" \"male\" \"female\". race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race).","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Education Data — demo_education","text":"data frame following columns: Area Type, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Education Data — demo_education","text":"","code":"if (FALSE) { demo_education(   area = \"wa\",   areatype = \"county\",   education = \"at least high school\",   sex = \"males\" )  demo_education(   area = \"usa\",   areatype = \"state\",   education = \"at least bachelors degree\",   sex = \"both sexes\",   race = \"all races (includes hispanic)\" )  demo_education(   area = \"pr\",   areatype = \"hsa\",   education = \"less than 9th grade\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Food Insecurity Data — demo_food","title":"Access to Food Insecurity Data — demo_food","text":"function returns data frame food demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Food Insecurity Data — demo_food","text":"","code":"demo_food(area, areatype, food, race = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Food Insecurity Data — demo_food","text":"area state/territory abbreviation USA. areatype Either \"county\" \"state\". food One following values: \"food insecurity\" \"limited access healthy food\". race One following values: \"Races (includes Hispanic)\" \"White non-Hispanic\" \"Black (includes Hispanic)\" \"Hispanic (Race).","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Food Insecurity Data — demo_food","text":"data frame following columns: Area Type, Area Code, Value, People.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Food Insecurity Data — demo_food","text":"","code":"if (FALSE) { demo_food(   area = \"wa\",   areatype = \"county\",   food = \"food insecurity\",   race = \"black\" )  demo_food(   area = \"usa\",   areatype = \"state\",   food = \"limited access to healthy food\" )  demo_food(   area = \"pr\",   areatype = \"county\",   food = \"food insecurity\",   race = \"all races (includes hispanic)\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Income Data — demo_income","title":"Access to Income Data — demo_income","text":"function returns data frame income demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Income Data — demo_income","text":"","code":"demo_income(area, areatype, income, race)"},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Income Data — demo_income","text":"area state/territory abbreviation USA. areatype Either \"county\" \"state\". income Either \"median family income\" \"median household income\". race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race).","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Income Data — demo_income","text":"data frame following columns: Area Type, Area Code, Dollars, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Income Data — demo_income","text":"","code":"if (FALSE) { demo_income(   area = \"wa\",   areatype = \"county\",   income = \"median household income\",   race = \"all races (includes hispanic)\" )  demo_income(   area = \"usa\",   areatype = \"state\",   income = \"median family income\",   race = \"all races (includes hispanic)\" )  demo_income(   area = \"pr\",   areatype = \"county\",   income = \"median family income\",   race = \"all races (includes hispanic)\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Insurance Data — demo_insurance","title":"Access to Insurance Data — demo_insurance","text":"function returns data frame insurance demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Insurance Data — demo_insurance","text":"","code":"demo_insurance(area, areatype, insurance, sex, age, race = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Insurance Data — demo_insurance","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". insurance One following values: \"% Insured demographic group, income levels\" \"% Insured demographic group, people 138% Poverty\" \"% Insured demographic group, people 200% Poverty\" \"% Insured demographic group, people 250% Poverty\" \"% Insured demographic group, people 400% Poverty\" \"% Insured demographic group, people 138% - 400% poverty\" \"% uninsured demographic group, income levels\" \"% uninsured demographic group, people 138% Poverty\" \"% uninsured demographic group, people 200% Poverty\" \"% uninsured demographic group, people 250% Poverty\" \"% uninsured demographic group, people 400% Poverty\" \"% uninsured demographic group, people 138% - 400% poverty\". sex One following values: \"sexes\" \"male\" \"female\". age specified \"sexes\" sex choose one following values: \"19 years\" \"18 64 years\" \"21 64 years\" \"40 64 years\" \"50 64 years\" \"65 years\". Otherwise specified \"male\" \"female\" sex, choose one following values: \"18 64 years\" \"40 64 years\" \"50 64 years\" \"65 years\". race specify race specified \"state\" areatype \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian (non-Hispanic)\" \"Hispanic (Race)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Insurance Data — demo_insurance","text":"data frame following columns: Area Type, Area Code, Percent, People, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Insurance Data — demo_insurance","text":"","code":"if (FALSE) { demo_insurance(   area = \"usa\",   areatype = \"state\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"both sexes\",   age = \"18 to 64 years\",   race = \"white (non-hispanic)\" )  demo_insurance(   area = \"wa\",   areatype = \"hsa\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"males\",   age = \"18 to 64 years\" )  demo_insurance(   area = \"dc\",   areatype = \"county\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"males\",   age = \"18 to 64 years\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Non-English Language — demo_language","title":"Access to Non-English Language — demo_language","text":"function returns data frame language demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Non-English Language — demo_language","text":"","code":"demo_language(area, areatype, language)"},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Non-English Language — demo_language","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". language permissible value \"language isolation\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Non-English Language — demo_language","text":"data frame following columns: Area Type, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Non-English Language — demo_language","text":"","code":"demo_language(   area = \"WA\",   areatype = \"county\",   language = \"language isolation\" ) #>                 County  FIPS Percent Households         Rank #> 1         Adams County 53001    18.9       1165 3127 of 3142 #> 2      Franklin County 53021    11.0       3044 3087 of 3142 #> 3         Grant County 53025     8.6       2810 3044 of 3142 #> 4        Yakima County 53077     8.0       6759 3020 of 3142 #> 5          King County 53033     5.7      51842 2934 of 3142 #> 6   Walla Walla County 53071     4.6       1040 2854 of 3142 #> 7        Chelan County 53007     4.4       1284 2840 of 3142 #> 8     Snohomish County 53061     4.3      13011 2835 of 3142 #> 9       Douglas County 53017     4.3        655 2831 of 3142 #> 10      Whitman County 53075     3.4        610 2735 of 3142 #> 11       Benton County 53005     3.0       2262 2685 of 3142 #> 12        Clark County 53011     2.8       5209 2638 of 3142 #> 13       Pierce County 53053     2.7       9204 2609 of 3142 #> 14     Okanogan County 53047     2.5        421 2557 of 3142 #> 15       Skagit County 53057     2.5       1278 2556 of 3142 #> 16 Grays Harbor County 53027     2.1        602 2419 of 3142 #> 17     Thurston County 53067     2.0       2299 2403 of 3142 #> 18     Columbia County 53013     1.9         36 2370 of 3142 #> 19        Mason County 53045     1.8        455 2308 of 3142 #> 20      Pacific County 53049     1.6        162 2222 of 3142 #> 21      Whatcom County 53073     1.3       1208 2056 of 3142 #> 22      Cowlitz County 53015     1.3        565 2032 of 3142 #> 23      Spokane County 53063     1.1       2395 1898 of 3142 #> 24       Island County 53029     1.0        366 1822 of 3142 #> 25       Kitsap County 53035     1.0       1058 1786 of 3142 #> 26    Jefferson County 53031     1.0        149 1751 of 3142 #> 27     Kittitas County 53037     1.0        179 1741 of 3142 #> 28     San Juan County 53055     0.8         71 1643 of 3142 #> 29        Lewis County 53041     0.8        251 1603 of 3142 #> 30    Klickitat County 53039     0.7         68 1508 of 3142 #> 31      Clallam County 53009     0.6        201 1337 of 3142 #> 32      Stevens County 53065     0.3         63  941 of 3142 #> 33        Ferry County 53019     0.3          9  888 of 3142 #> 34     Skamania County 53059     0.3         13  823 of 3142 #> 35       Asotin County 53003     0.1         13  552 of 3142 #> 36 Pend Oreille County 53051     0.1          6  479 of 3142 #> 37      Lincoln County 53043     0.0          2  380 of 3142 #> 38     Garfield County 53023     0.0          0    1 of 3142 #> 39    Wahkiakum County 53069     0.0          0    1 of 3142  demo_language(   area = \"dc\",   areatype = \"hsa\",   language = \"language isolation\" ) #>    Health_Service_Area HSA_Code Percent Households       Rank #> 1 District of Columbia     0061     3.2       9986 799 of 949  demo_language(   area = \"usa\",   areatype = \"state\",   language = \"language isolation\" ) #>                   State  FIPS Percent Households     Rank #> 1            California 06000     8.5    1119486 51 of 51 #> 2              New York 36000     7.6     571749 50 of 51 #> 3                 Texas 48000     7.1     731111 49 of 51 #> 4            New Jersey 34000     6.9     233543 48 of 51 #> 5               Florida 12000     6.9     559135 47 of 51 #> 6         Massachusetts 25000     6.1     164605 46 of 51 #> 7                Hawaii 15000     5.6      26740 45 of 51 #> 8                Nevada 32000     5.4      61770 44 of 51 #> 9          Rhode Island 44000     5.3      22738 43 of 51 #> 10           New Mexico 35000     5.3      42339 42 of 51 #> 11          Connecticut 09000     5.2      73153 41 of 51 #> 12             Illinois 17000     4.3     211120 40 of 51 #> 13           Washington 53000     3.8     110765 39 of 51 #> 14              Arizona 04000     3.7      99159 38 of 51 #> 15             Maryland 24000     3.3      74920 37 of 51 #> 16 District of Columbia 11001     3.2       9986 36 of 51 #> 17              Georgia 13000     2.7     104353 35 of 51 #> 18             Virginia 51000     2.6      85864 34 of 51 #> 19             Nebraska 31000     2.6      20165 33 of 51 #> 20         Pennsylvania 42000     2.5     126940 32 of 51 #> 21             Colorado 08000     2.4      54213 31 of 51 #> 22               Kansas 20000     2.4      27336 30 of 51 #> 23             Delaware 10000     2.4       9080 29 of 51 #> 24               Oregon 41000     2.3      38081 28 of 51 #> 25               Alaska 02900     2.2       5798 27 of 51 #> 26            Minnesota 27000     2.2      48431 26 of 51 #> 27       North Carolina 37000     2.2      87133 25 of 51 #> 28                 Utah 49000     2.1      21249 24 of 51 #> 29             Oklahoma 40000     2.0      29432 23 of 51 #> 30                Idaho 16000     1.9      12563 22 of 51 #> 31                 Iowa 19000     1.8      23591 21 of 51 #> 32            Louisiana 22000     1.8      31553 20 of 51 #> 33              Indiana 18000     1.7      43281 19 of 51 #> 34             Michigan 26000     1.6      64810 18 of 51 #> 35             Arkansas 05000     1.6      18054 17 of 51 #> 36            Tennessee 47000     1.5      40538 16 of 51 #> 37            Wisconsin 55000     1.4      33923 15 of 51 #> 38                 Ohio 39000     1.4      66143 14 of 51 #> 39             Kentucky 21000     1.4      24306 13 of 51 #> 40       South Carolina 45000     1.3      26558 12 of 51 #> 41         North Dakota 38000     1.2       3953 11 of 51 #> 42              Alabama 01000     1.2      22804 10 of 51 #> 43        New Hampshire 33000     1.2       6267  9 of 51 #> 44             Missouri 29000     1.1      26952  8 of 51 #> 45         South Dakota 46000     1.1       3705  7 of 51 #> 46              Wyoming 56000     1.0       2214  6 of 51 #> 47                Maine 23000     0.9       4931  5 of 51 #> 48          Mississippi 28000     0.8       9338  4 of 51 #> 49              Vermont 50000     0.6       1629  3 of 51 #> 50              Montana 30000     0.4       1625  2 of 51 #> 51        West Virginia 54000     0.3       2194  1 of 51 #> 52          Puerto Rico 72001      NA         NA     <NA>"},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Mobility Data — demo_mobility","title":"Access to Mobility Data — demo_mobility","text":"function returns data frame mobility demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Mobility Data — demo_mobility","text":"","code":"demo_mobility(area, areatype, mobility)"},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Mobility Data — demo_mobility","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". mobility permissible values \"moved (past year)\" \"moved outside us (past year)\" \"moved, different state (past year)\" \"moved, different county, state (past year)\" \"moved, county (past year)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Mobility Data — demo_mobility","text":"data frame following columns: Area Type, Area Code, Percent, People, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Mobility Data — demo_mobility","text":"","code":"if (FALSE) { demo_mobility(   area = \"WA\",   areatype = \"county\",   mobility = \"moved, different county, same state (in past year)\" )  demo_mobility(   area = \"usa\",   areatype = \"state\",   mobility = \"moved, same county (in past year)\" )  demo_mobility(   area = \"dc\",   areatype = \"hsa\",   mobility = \"moved, same county (in past year)\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Population Data — demo_population","title":"Access to Population Data — demo_population","text":"function returns data frame population State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Population Data — demo_population","text":"","code":"demo_population(area, areatype, population, race = NULL, sex = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Population Data — demo_population","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". population One following values: \"age 18\" \"age 18-39\" \"age 40-64\" \"ages 40 \" \"ages 50 \" \"ages 60 \" \"american indian/alaska native\" \"asian/pacific islander\" \"black\" \"foreign born\" \"hispanic\" \"non-hispanic (origin recode)\" \"white\" \"males\" \"females\". race One following values: \"American Indian/Alaska Native\" \"Asian/Pacific Islander\" \"Black\" \"Hispanic\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Population Data — demo_population","text":"data frame following columns: Area Type, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Population Data — demo_population","text":"","code":"if (FALSE) { demo_population(   area = \"WA\",   areatype = \"county\",   population = \"males\",   race = \"all races (includes hispanic)\" )  demo_population(   area = \"dc\",   areatype = \"hsa\",   population = \"foreign born\",   race = \"black\",   sex = \"females\" )  demo_population(   area = \"usa\",   areatype = \"state\",   population = \"foreign born\",   race = \"hispanic (any race)\",   sex = \"females\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Poverty Data — demo_poverty","title":"Access to Poverty Data — demo_poverty","text":"function returns data frame poverty demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Poverty Data — demo_poverty","text":"","code":"demo_poverty(area, areatype, poverty, race = NULL, sex = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Poverty Data — demo_poverty","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". poverty One following values: \"families poverty\" \"persistent poverty\" \"persons poverty\" \"persons < 150% poverty\". race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race). sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Poverty Data — demo_poverty","text":"data frame following columns: Area Type, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Poverty Data — demo_poverty","text":"","code":"if (FALSE) { demo_poverty(   area = \"WA\",   areatype = \"county\",   poverty = \"persistent poverty\" )  demo_poverty(   area = \"usa\",   areatype = \"state\",   poverty = \"families below poverty\",   race = \"black\" )  demo_poverty(   area = \"dc\",   areatype = \"hsa\",   poverty = \"families below poverty\",   race = \"All Races (includes Hispanic)\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Social Vulnerability Index (SVI) Data — demo_svi","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"function returns data frame social vulnerability index (SVI) State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"","code":"demo_svi(area, svi)"},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"area state/territory abbreviation USA. svi One following values: \"Overall\" \"socioeconomic status\" \"household characteristics\" \"racial & ethinic minority status\" \"housing type & transportation\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"data frame following columns: County, FIPS, Score.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"","code":"if (FALSE) { demo_svi(   area = \"WA\",   svi = \"overall\" )  demo_svi(   area = \"usa\",   svi = \"overall\" )  demo_svi(   area = \"dc\",   svi = \"socioeconomic status\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Workforce Data — demo_workforce","title":"Access to Workforce Data — demo_workforce","text":"function returns data frame Workforce State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Workforce Data — demo_workforce","text":"","code":"demo_workforce(area, areatype, workforce, race, sex)"},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Workforce Data — demo_workforce","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". workforce permissible value \"unemployed\" race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race). sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Workforce Data — demo_workforce","text":"data frame following columns: Area Type, Area Code, Percent, People Unemployed, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Workforce Data — demo_workforce","text":"","code":"if (FALSE) { demo_workforce(   area = \"WA\",   areatype = \"county\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" )  demo_workforce(   area = \"usa\",   areatype = \"state\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"females\" )  demo_workforce(   area = \"pr\",   areatype = \"hsa\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Cancer Incident Data — incidence_cancer","title":"Access to Cancer Incident Data — incidence_cancer","text":"function returns data frame cancer incidence State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Cancer Incident Data — incidence_cancer","text":"","code":"incidence_cancer(area, areatype, cancer, race, sex, age, stage, year)"},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Cancer Incident Data — incidence_cancer","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". cancer One following values: \"cancer sites\" \"bladder\" \"brain & ons\" \"breast (female)\" \"breast (female situ)\" \"cervix\" \"childhood (ages <15, sites)\" \"childhood (ages <20, sites)\" \"colon & rectum\" \"esophagus\" \"kidney & renal pelvis\" \"leukemia\" \"liver & bile duct\" \"lung & bronchus\" \"melanoma skin\" \"non-hodgkin lymphoma\" \"oral cavity & pharynx\" \"ovary\" \"pancreas\" \"prostate\" \"stomach\" \"thyroid\" \"uterus (corpus & uterus, nos)\". race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\". age One following values: \"ages\" \"ages <50\" \"ages 50+\" \"ages <65\" \"ages 65+\" \"ages <15\" \"ages <20\". stage One following values: \"stages\" \"late stage (regional & distant)\". year One following values: \"latest 5 year average\" \"latest single year (us state)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Cancer Incident Data — incidence_cancer","text":"data frame following columns: Area Type, Area Code, Age Adjusted Incidence Rate, Lower 95% CI, Upper 95% CI, CI Rank, Lower CI Rank, Upper CI Rank, Annual Average Count, Recent Trend, Recent 5 Year Trend, Trend Lower 95% CI, Trend Upper 95% CI.","code":""},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Cancer Incident Data — incidence_cancer","text":"","code":"if (FALSE) { incidence_cancer(   area = \"wa\",   areatype = \"county\",   cancer = \"all cancer sites\",   race = \"black (non-hispanic)\",   sex = \"both sexes\",   age = \"ages 65+\",   stage = \"all stages\",   year = \"latest 5 year average\" )  incidence_cancer(   area = \"usa\",   areatype = \"state\",   cancer = \"lung & bronchus\",   race = \"all races (includes hispanic)\",   sex = \"males\",   age = \"ages 50+\",   stage = \"late stage (regional & distant)\",   year = \"latest single year (us by state)\" )  incidence_cancer(   area = \"wa\",   areatype = \"hsa\",   cancer = \"ovary\",   race = \"all races (includes hispanic)\",   sex = \"females\",   age = \"ages 50+\",   stage = \"late stage (regional & distant)\",   year = \"latest 5 year average\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Cancer Mortality Data — mortality_cancer","title":"Access to Cancer Mortality Data — mortality_cancer","text":"function returns data frame cancer mortality State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Cancer Mortality Data — mortality_cancer","text":"","code":"mortality_cancer(area, areatype, cancer, race, sex, age, year)"},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Cancer Mortality Data — mortality_cancer","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". cancer One following values: \"cancer sites\" \"bladder\" \"brain & ons\" \"breast (female)\" \"cervix\" \"childhood (ages <15, sites)\" \"childhood (ages <20, sites)\" \"colon & rectum\" \"esophagus\" \"kidney & renal pelvis\" \"leukemia\" \"liver & bile duct\" \"lung & bronchus\" \"melanoma skin\" \"non-hodgkin lymphoma\" \"oral cavity & pharynx\" \"ovary\" \"pancreas\" \"prostate\" \"stomach\" \"thyroid\" \"uterus (corpus & uterus, nos)\" race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\". age One following values: \"ages\" \"ages <50\" \"ages 50+\" \"ages <65\" \"ages 65+\" \"ages <15\" \"ages <20\". year One following values: \"latest 5 year average\" \"latest single year (us state)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Cancer Mortality Data — mortality_cancer","text":"data frame following columns: Area Type, Area Code, Met Healthy People Objective ***?, Age Adjusted Death Rate, Lower 95% CI Rate, Upper 95% CI Rate, CI Rank, Lower CI Rank, Upper CI Rank, Annual Average Count, Recent Trend, Recent 5 Year Trend, Lower 95% CI Trend, Upper 95% CI Trend.","code":""},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Cancer Mortality Data — mortality_cancer","text":"","code":"if (FALSE) { mortality_cancer(   area = \"wa\",   areatype = \"county\",   cancer = \"all cancer sites\",   race = \"black (non-hispanic)\",   sex = \"both sexes\",   age = \"ages 65+\",   year = \"latest 5 year average\" )  mortality_cancer(   area = \"usa\",   areatype = \"state\",   cancer = \"prostate\",   race = \"all races (includes hispanic)\",   sex = \"males\",   age = \"ages 50+\",   year = \"latest single year (us by state)\" )  mortality_cancer(   area = \"wa\",   areatype = \"hsa\",   cancer = \"ovary\",   race = \"all races (includes hispanic)\",   sex = \"females\",   age = \"ages 50+\",   year = \"latest 5 year average\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"http://getwilds.org/cancerprof/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"http://getwilds.org/cancerprof/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"http://getwilds.org/cancerprof/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Alcohol Screening and Risk Data — risk_alcohol","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"function returns data frame alcohol risks State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"","code":"risk_alcohol(alcohol, race, sex)"},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"alcohol permissible value `paste(\"binge drinking (4+ drinks one occasion women,\", \"5+ drinks one occasion men), ages 21+\") race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"data frame following columns: Area Type, Area Code, Percent, Lower 95% CI, Upper 95% CI, Number Respondents.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"","code":"if (FALSE) { risk_alcohol(   alcohol = paste(     \"binge drinking (4+ drinks on one occasion for women,\",     \"5+ drinks for one occasion for men), ages 21+\"   ),   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Colorectal Screening Data — risk_colorectal_screening","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"function returns data frame colorectal screening State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"","code":"risk_colorectal_screening(screening, race = NULL, sex = NULL, area = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"screening One following values: \"ever fobt, ages 50-75\" \"guidance sufficient crc, ages 50-75\" \"colonoscopy past 10 years, ages 50-75\" \"home blood stool test past year, ages 45-75\" \"received least one recommended crc test, ages 45-75\". race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\". area state/territory abbreviation USA.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"data frame following columns: Area Type, Area Code, Percent, People Unemployed, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"","code":"if (FALSE) { risk_colorectal_screening(   screening = \"home blood stool test in the past year, ages 45-75\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" )  risk_colorectal_screening(   screening = \"ever had fobt, ages 50-75\",   area = \"usa\" ) risk_colorectal_screening(   screening = \"received at least one recommended crc test, ages 45-75\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Diet & Exercise Screening Data — risk_diet_exercise","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"function returns data frame diet exercise risk State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"","code":"risk_diet_exercise(diet_exercise, race, sex)"},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"diet_exercise One following values: \"bmi healthy, ages 20+\" \"bmi obese, ages 20+\" \"bmi obese, high school survey\" \"bmi overweight, high school survey\" \"consumed 1 fruits per day\" \"consumed 1 vegetables per day\" \"leisure time physical activity\". race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"data frame following columns: Area Type, Area Code, Percent, Lower 95% CI, Upper 95% CI, Number Respondents.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"","code":"if (FALSE) { risk_diet_exercise(   diet_exercise = \"bmi is healthy, ages 20+\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) risk_diet_exercise(   diet_exercise = \"bmi is obese, high school survey\",   race = \"all races (includes hispanic)\",   sex = \"males\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Smoking Data — risk_smoking","title":"Access to Smoking Data — risk_smoking","text":"function returns data frame smoking risks State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Smoking Data — risk_smoking","text":"","code":"risk_smoking(smoking, race = NULL, sex = NULL, datatype = NULL, area = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Smoking Data — risk_smoking","text":"smoking permissible values \"smoking laws ()\" \"smoking laws (bars)\" \"smoking laws (restaurants)\" \"smoking laws (workplace)\" \"smoking laws (workplace; restaurant; & bar)\" \"smokers (stopped 1 day longer)\" \"smoking allowed work (people)\" \"smoking allowed home (people)\" \"smoking allowed work (current smokers)\" \"smoking allowed work (former/never smokers)\" \"smoking allowed home (current smokers)\" \"smoking allowed home (former/never smokers)\" \"former smoker; ages 18+\" \"former smoker, quit 1 year+; ages 18+\" \"smokers (ever); ages 18+\" \"e-cigarette use; ages 18+\" \"smokers (current); ages 18+\". race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\". datatype One following values: \"direct estimates\" \"county level modeled estimates\". area state/territory abbreviation USA.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Smoking Data — risk_smoking","text":"data frame following columns: Area Type, Area Code, Percent, Lower CI 95%, Upper CI 95%, Number Respondents.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Access to Smoking Data — risk_smoking","text":"Please note function requires specific arguments smoking type.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Smoking Data — risk_smoking","text":"","code":"if (FALSE) { risk_smoking(smoking = \"smoking laws (any)\")  risk_smoking(   smoking = \"smokers (stopped for 1 day or longer)\",   sex = \"both sexes\",   datatype = \"county level modeled estimates\",   area = \"wa\" )  risk_smoking(   smoking = \"smoking not allowed at work (current smokers)\",   sex = \"both sexes\",   datatype = \"direct estimates\" )  risk_smoking(   smoking = \"smokers (current); ages 18+\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\",   datatype = \"county level modeled estimates\",   area = \"wa\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Vaccines Data — risk_vaccines","title":"Access to Vaccines Data — risk_vaccines","text":"function returns data frame vaccines risks State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Vaccines Data — risk_vaccines","text":"","code":"risk_vaccines(vaccine, sex)"},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Vaccines Data — risk_vaccines","text":"vaccine One following values: \"percent date hpv vaccination coverage, ages 13-15\", \"percent date hpv vaccination coverage, ages 13-17\". sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Vaccines Data — risk_vaccines","text":"data frame following columns: Area Type, Area Code, Percent, Lower 95% CI, Upper 95% CI, Number Respondents.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Vaccines Data — risk_vaccines","text":"","code":"if (FALSE) { risk_vaccines(   vaccine = \"percent with up to date hpv vaccination coverage, ages 13-15\",   sex = \"both sexes\" )  risk_vaccines(   vaccine = \"percent with up to date hpv vaccination coverage, ages 13-17\",   sex = \"females\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Women's Health Data — risk_women_health","title":"Access to Women's Health Data — risk_women_health","text":"function returns data frame women's health risks State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Women's Health Data — risk_women_health","text":"","code":"risk_women_health(   women_health,   race,   datatype = \"direct estimates\",   area = NULL )"},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Women's Health Data — risk_women_health","text":"women_health One following values: \"mammogram past 2 years, ages 50-74\" \"mammogram past 2 years, ages 40+\" \"pap smear past 3 years, hysterectomy, ages 21-65\". race One following values \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". datatype One following values: \"direct estimates\" \"county level modeled estimates\". area state/territory abbreviation USA.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Women's Health Data — risk_women_health","text":"data frame following columns: Area Type, Area Code, Percent, People Unemployed, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Women's Health Data — risk_women_health","text":"","code":"if (FALSE) { risk_women_health(   women_health = \"mammogram in past 2 years, ages 50-74\",   race = \"all races (includes hispanic)\",   datatype = \"direct estimates\" )  risk_women_health(   women_health = \"pap smear in past 3 years, no hysterectomy, ages 21-65\",   race = \"all races (includes hispanic)\",   datatype = \"county level modeled estimates\",   area = \"wa\" )  risk_women_health(   women_health = \"pap smear in past 3 years, no hysteroetomy, ages 21-65\",   race = \"black (non-hispanic)\" ) }"}]
+[{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing","title":"Contributing","text":"outlines propose change usethis. detailed info contributing , WILDS projects, please see WILDS Contributing Guide.","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"fixing-typosdocs-changes","dir":"","previous_headings":"","what":"Fixing typos/docs changes","title":"Contributing","text":"can fix typos, spelling mistakes, grammatical errors documentation directly using GitHub web interface, long changes made source file.","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"bigger-changes","dir":"","previous_headings":"","what":"Bigger changes","title":"Contributing","text":"want make bigger change, ’s good idea first file issue make sure someone team agrees ’s needed. ’ve found bug, please file issue illustrates bug minimal reproducible example (reprex R, reprexpy Python).","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"Bigger changes","what":"Pull request process","title":"Contributing","text":"Fork package clone onto computer Create Git branch pull request (PR) title PR briefly describe change. body PR contain Fixes #issue-number. user-facing changes, add bullet changelog file one. NEWS.md R package, likely Changelog.md Changelog.rst Python package.","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"code-style","dir":"","previous_headings":"Bigger changes","what":"Code style","title":"Contributing","text":"New code R Python packages follow style guide.","code":""},{"path":"http://getwilds.org/cancerprof/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing","text":"Please note project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"http://getwilds.org/cancerprof/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 cancerprof authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"load-the-package","dir":"Articles","previous_headings":"","what":"Load the package","title":"Demographics","text":"","code":"library(cancerprof)"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"retrieving-data","dir":"Articles","previous_headings":"","what":"Retrieving Data","title":"Demographics","text":"demographics category cancerprof contains 11 unique functions pull data demographics page State Cancer Profile. functions : demo_crowding(), demo_education(), demo_food(), demo_income(), demo_insurance(), demo_mobility(), demo_non_english_language(), demo_population(), demo_poverty(), demo_svi(), demo_workforce() functions require various parameters must specified pull data. Please refer function documentation details.","code":""},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-crowding","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Crowding","title":"Demographics","text":"Demo crowding Always requires 4 arguments: area, areatype, crowding, race","code":"crowding <- demo_crowding(   area = \"WA\",   areatype = \"county\",   crowding = \"household with >1 person per room\",   race = \"All Races (includes Hispanic)\" ) head(crowding, n = 3) #>             County  FIPS Percent Households         Rank #> 1  Columbia County 53013     1.4         25 2111 of 3143 #> 2 Jefferson County 53031     1.4        211 2095 of 3143 #> 3   Whitman County 53075     1.4        246 2090 of 3143"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-education","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Education","title":"Demographics","text":"Demo education 5 arguments: area, areatype, education, sex, race. Depending education argument, required arguments change","code":"# at least high school - requires arguments: area, areatype, education, sex education1 <- demo_education(   area = \"wa\",   areatype = \"county\",   education = \"at least high school\",   sex = \"males\" )  head(education1, n = 3) #>           County  FIPS Percent Households         Rank #> 1 Whitman County 53075    95.5      11789 3037 of 3143 #> 2  Kitsap County 53035    95.1      91509 3012 of 3143 #> 3  Island County 53029    95.0      29073 2995 of 3143  # at least bachelors degree - requires arguments: # area, areatype, education, sex, race education2 <- demo_education(   area = \"usa\",   areatype = \"state\",   education = \"at least bachelors degree\",   sex = \"both sexes\",   race = \"all races (includes hispanic)\" )  head(education2, n = 3) #>           State  FIPS Percent Households     Rank #> 1 West Virginia 54000    21.8     278281 52 of 52 #> 2   Mississippi 28000    23.2     458928 51 of 52 #> 3      Arkansas 05000    24.3     491269 50 of 52  # less than 9th grade - requires arguments: area, areatype, education education3 <- demo_education(   area = \"pr\",   areatype = \"hsa\",   education = \"less than 9th grade\" )  head(education3, n = 3) #>   Health_Service_Area HSA_Code Percent Households       Rank #> 1         Puerto Rico     0995    14.1     337405 935 of 950"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-food","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Food","title":"Demographics","text":"Demo food 4 arguments: area, areatype, food, race.","code":"# limited access to healthy food - requires arguments: area, areatype, food food1 <- demo_food(   area = \"usa\",   areatype = \"state\",   food = \"limited access to healthy food\" )  head(food1, n = 3) #>         State  FIPS Percent People #> 1  New Mexico 35000      13 268515 #> 2   Louisiana 22000      11 483383 #> 3 Mississippi 28000      11 337505  # food insecurity - requires arguments: area, areatype, food, race food2 <- demo_food(   area = \"pr\",   areatype = \"county\",   food = \"food insecurity\",   race = \"all races (includes hispanic)\" )  head(food2, n = 3) #>        County  FIPS Percent #> 1 Puerto Rico 72001      NA"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-income","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Income","title":"Demographics","text":"Demo income Always requires 4 arguments: area, areatype, income, race.","code":"# limited access to healthy food - requires arguments: area, areatype, food income1 <- demo_income(   area = \"wa\",   areatype = \"county\",   income = \"median household income\",   race = \"all races (includes hispanic)\" )  head(income1, n = 3) #>            County  FIPS Dollars         Rank #> 1  Whitman County 53075   43613 2700 of 3142 #> 2    Ferry County 53019   45907 2529 of 3142 #> 3 Garfield County 53023   50625 2168 of 3142  # food insecurity - requires arguments: area, areatype, food, race income2 <- demo_income(   area = \"usa\",   areatype = \"state\",   income = \"median family income\",   race = \"all races (includes hispanic)\" )  head(income2, n = 3) #>         State  FIPS Dollars     Rank #> 1 Puerto Rico 72001   26745 52 of 52 #> 2 Mississippi 28000   62802 51 of 52 #> 3    Arkansas 05000   65673 50 of 52"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-insurance","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Insurance","title":"Demographics","text":"Demo insurance 6 arguments: area, areatype, insurance, sex, age, race. Please note age arguments \"sexes\" different “Males ”Females” Check function documentations details Areatype \"state\" can select Race, otherwise race always \"races (includes hispanic)\"","code":"insurance1 <- demo_insurance(   area = \"usa\",   areatype = \"state\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"both sexes\",   age = \"18 to 64 years\",   race = \"white (non-hispanic)\" )  head(insurance1, n = 3) #>         State  FIPS Percent  People     Rank #> 1    Oklahoma 40000    84.6 1256749 51 of 51 #> 2 Mississippi 28000    85.2  809125 50 of 51 #> 3     Wyoming 56000    85.4  238655 49 of 51  insurance2 <- demo_insurance(   area = \"wa\",   areatype = \"county\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"males\",   age = \"18 to 64 years\" )  head(insurance2, n = 3) #>          County  FIPS Percent People         Rank #> 1  Adams County 53001    73.8   4073 2890 of 3141 #> 2 Yakima County 53077    77.2  54771 2679 of 3141 #> 3  Grant County 53025    79.4  23081 2464 of 3141"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-mobility","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Mobility","title":"Demographics","text":"Demo mobility Always requires 3 arguments: area, areatype, mobility. function defaults \"races\", \"sexes\", \"ages 1+\"","code":"mobility1 <- demo_mobility(   area = \"usa\",   areatype = \"state\",   mobility = \"moved, same county (in past year)\" )  head(mobility1, n = 3) #>                  State  FIPS Percent People     Rank #> 1               Nevada 32000    10.6 321900 51 of 51 #> 2              Arizona 04000    10.2 716304 50 of 51 #> 3 District of Columbia 11001    10.2  68557 49 of 51   mobility2 <- demo_mobility(   area = \"WA\",   areatype = \"county\",   mobility = \"moved, different county, same state (in past year)\" )  head(mobility2, n = 3) #>                County  FIPS Percent People         Rank #> 1     Kittitas County 53037    12.7   5563 3114 of 3142 #> 2      Whitman County 53075    10.9   5224 3093 of 3142 #> 3 Grays Harbor County 53027     5.8   4314 2619 of 3142"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-language","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Language","title":"Demographics","text":"Demo Language Always requires 3 arguments: area, areatype, language. function defaults \"races\", \"sexes\", \"ages 14+\"","code":"non_english1 <- demo_language(   area = \"wa\",   areatype = \"county\",   language = \"language isolation\" )  head(non_english1, n = 3) #>            County  FIPS Percent Households         Rank #> 1    Adams County 53001    18.9       1165 3127 of 3142 #> 2 Franklin County 53021    11.0       3044 3087 of 3142 #> 3    Grant County 53025     8.6       2810 3044 of 3142   non_english2 <- demo_language(   area = \"usa\",   areatype = \"state\",   language = \"language isolation\" )  head(non_english2, n = 3) #>        State  FIPS Percent Households     Rank #> 1 California 06000     8.5    1119486 51 of 51 #> 2   New York 36000     7.6     571749 50 of 51 #> 3      Texas 48000     7.1     731111 49 of 51"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-population","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Population","title":"Demographics","text":"Demo Population 5 arguments: area, areatype, population, race, sex. population argument used input population variable age, race, sex. Please note different race sex arguments different population variables default race, sex, age. select \"foreign born\" population, must provide another race race argument","code":"# population1 <- demo_population(   area = \"wa\",   areatype = \"county\",   population = \"foreign born\",   race = \"black\",   sex = \"females\" )  head(population1, n = 3) #>                County  FIPS Percent People         Rank #> 1     Columbia County 53013       0      0 1666 of 2885 #> 2 Grays Harbor County 53027       0      0 1666 of 2885 #> 3    Jefferson County 53031       0      0 1666 of 2885   population2 <- demo_population(   area = \"ca\",   areatype = \"county\",   population = \"males\",   race = \"all races (includes hispanic)\" )  head(population2, n = 3) #>          County  FIPS Percent People         Rank #> 1 Lassen County 06035    64.8  21361 3134 of 3143 #> 2  Kings County 06031    55.2  83872 3015 of 3143 #> 3   Mono County 06051    54.8   7284 2987 of 3143  population3 <- demo_population(   area = \"usa\",   areatype = \"state\",   population = \"age under 18\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" )  head(population3, n = 3) #>                  State  FIPS Percent People     Rank #> 1          Puerto Rico 72001    18.0 597277 52 of 52 #> 2 District of Columbia 11001    18.3 125022 51 of 52 #> 3              Vermont 50000    18.5 118889 50 of 52"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-poverty","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Poverty","title":"Demographics","text":"Demo poverty 5 arguments: area, areatype, poverty, race, sex. function defaults \"ages\" \"persistent poverty\" \"persons <150% poverty\" poverty argument default \"races\", \"sexes\", \"ages\". \"families poverty\" poverty argument require race argument default \"sexes\" \"ages\". \"persons poverty\" poverty argument require race argument sex argument, default \"ages\".","code":"# Persistent poverty poverty1 <- demo_poverty(   area = \"WA\",   areatype = \"county\",   poverty = \"persistent poverty\" )  head(poverty1, n = 3) #>           County  FIPS Persistent Poverty #> 1 Whitman County 53075                yes #> 2   Adams County 53001                 no #> 3  Asotin County 53003                 no  # Families below poverty poverty2 <- demo_poverty(   area = \"usa\",   areatype = \"state\",   poverty = \"families below poverty\",   race = \"black\" )  head(poverty2, n = 3) #>         State  FIPS Percent People     Rank #> 1 Puerto Rico 72001    40.9  33658 52 of 52 #> 2     Wyoming 56000    33.1    349 51 of 52 #> 3        Iowa 19000    26.6   6200 50 of 52  # Persons below poverty poverty3 <- demo_poverty(   area = \"usa\",   areatype = \"state\",   poverty = \"persons below poverty\",   race = \"black\",   sex = \"males\" )  head(poverty3, n = 3) #>         State  FIPS Percent People     Rank #> 1 Puerto Rico 72001    42.2  67037 52 of 52 #> 2   Louisiana 22000    28.3 188456 51 of 52 #> 3 Mississippi 28000    28.2 139358 50 of 52"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"demo-social-vulnerability-index-svi","dir":"Articles","previous_headings":"Retrieving Data","what":"Demo Social Vulnerability Index (SVI)","title":"Demographics","text":"Demo svi Always requires 2 arguments: area, svi. function defaults \"races\", \"sexes\", \"ages\". Please note areatype argument available function areatype limited \"county\"","code":"svi1 <- demo_svi(   area = \"WA\",   svi = \"overall\" )  head(svi1, n = 3) #>            County  FIPS  Score #> 1    Adams County 53001 0.9656 #> 2   Yakima County 53077 0.9570 #> 3 Okanogan County 53047 0.9532   svi2 <- demo_svi(   area = \"usa\",   svi = \"socioeconomic status\" )  head(svi2, n = 3) #>                                       County  FIPS  Score #> 1 Oglala Lakota/Shannon County, South Dakota 46102 1.0000 #> 2                      Macon County, Georgia 13193 0.9997 #> 3              Humphreys County, Mississippi 28053 0.9994"},{"path":"http://getwilds.org/cancerprof/articles/demographics-vignette.html","id":"workforce","dir":"Articles","previous_headings":"Retrieving Data","what":"Workforce","title":"Demographics","text":"Demo svi Always requires 5 arguments: area, areatype, workforce, race, sex. function defaults “ages 16+”","code":"workforce1 <- demo_workforce(   area = \"WA\",   areatype = \"county\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" )  head(workforce1, n = 3) #>             County  FIPS Percent People_Unemployed         Rank #> 1  Garfield County 53023    11.0               110 3045 of 3143 #> 2 Jefferson County 53031     7.6               953 2735 of 3143 #> 3   Whitman County 53075     7.5              1849 2700 of 3143   workforce2 <- demo_workforce(   area = \"usa\",   areatype = \"state\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"females\" )  head(workforce2, n = 3) #>                  State  FIPS Percent People_Unemployed     Rank #> 1          Puerto Rico 72001    14.5             85552 52 of 52 #> 2               Nevada 32000     7.2             50777 51 of 52 #> 3 District of Columbia 11001     7.1             14769 50 of 52"},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"load-the-package","dir":"Articles","previous_headings":"","what":"Load the package","title":"incidence-vignette","text":"","code":"library(cancerprof)"},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"retrieving-data","dir":"Articles","previous_headings":"","what":"Retrieving Data","title":"incidence-vignette","text":"Cancer Incidence category cancerprof contains single functions pull data Incidence page State Cancer Profile. function retrieving incidence data incidence_cancer()","code":""},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"incidence-cancer","dir":"Articles","previous_headings":"","what":"Incidence Cancer","title":"incidence-vignette","text":"Incidence cancer 23 cancer types choose . total, incidence cancer 8 arguments: area, areatype, cancer, race, sex, age, stage, year","code":""},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"argument-details","dir":"Articles","previous_headings":"Incidence Cancer","what":"Argument Details","title":"incidence-vignette","text":"\"latest single year (us state)\" argument year can selected area \"state\" following cancer types: “breast (female situ)”, “childhood (ages <15, sites)”, “childhood (ages <20, sites)”, “leukemia” stage argument must \"stages\" following cancer types: “breast (female)”, “breast (female situ)”, “ovary”, “uterus (corpus & uterus, nos)” sex argument must \"females\" \"prostate\" cancer, sex must \"males\" \"childhood (ages <15, sites)\", age must \"ages <15\" \"childhood (ages <20, sites)\", age must \"ages <20\"","code":""},{"path":"http://getwilds.org/cancerprof/articles/incidence-vignette.html","id":"examples","dir":"Articles","previous_headings":"Incidence Cancer","what":"Examples","title":"incidence-vignette","text":"","code":"incidence1 <- incidence_cancer(   area = \"usa\",   areatype = \"state\",   cancer = \"lung & bronchus\",   race = \"all races (includes hispanic)\",   sex = \"males\",   age = \"ages 50+\",   stage = \"late stage (regional & distant)\",   year = \"latest single year (us by state)\" ) head(incidence1, n = 3) #>               State  FIPS Age_Adjusted_Incidence_Rate Lower_95%_CI Upper_95%_CI CI_Rank Lower_CI_Rank Upper_CI_Rank Annual_Average_Count #> 1 US (SEER+NPCR)(1) 00000                       122.7        121.8        123.7      NA            NA            NA                65692 #> 2       Kentucky(3) 21000                       216.2        205.7        227.2       1             1             1                 1660 #> 3    Mississippi(2) 28000                       178.0        166.0        190.6       2             2             7                  868 #>   Percentage_of_Cases_with_Late_Stage #> 1                                67.0 #> 2                                70.3 #> 3                                68.3  incidence2 <- incidence_cancer(   area = \"wa\",   areatype = \"hsa\",   cancer = \"ovary\",   race = \"all races (includes hispanic)\",   sex = \"females\",   age = \"ages 50+\",   stage = \"late stage (regional & distant)\",   year = \"latest 5 year average\" ) head(incidence2, n = 3) #>          Health_Service_Area HSA_Code Age_Adjusted_Incidence_Rate Lower_95%_CI Upper_95%_CI CI_Rank Lower_CI_Rank Upper_CI_Rank #> 1              Washington(5)    53000                        20.5         19.4         21.6      NA             4            29 #> 2          US (SEER+NPCR)(1)    00000                        19.7         19.6         19.9      NA            NA            NA #> 3 Lewis, WA - Pacific, WA(6)     0832                        28.4         19.2         40.5       1             1             9 #>   Annual_Average_Count Percentage_of_Cases_with_Late_Stage #> 1                  278                                76.0 #> 2                11948                                73.5 #> 3                    7                                76.7  incidence3 <- incidence_cancer(   area = \"wa\",   areatype = \"county\",   cancer = \"all cancer sites\",   race = \"black (non-hispanic)\",   sex = \"both sexes\",   age = \"ages 65+\",   stage = \"all stages\",   year = \"latest 5 year average\" ) head(incidence3, n = 3) #>               County  FIPS Age_Adjusted_Incidence_Rate Lower_95%_CI Upper_95%_CI CI_Rank Lower_CI_Rank Upper_CI_Rank Annual_Average_Count #> 1      Washington(5) 53000                      1926.6       1847.1       2008.6      NA             5            32                  493 #> 2  US (SEER+NPCR)(1) 00000                      1898.1       1892.4       1903.8      NA            NA            NA                89582 #> 3 Thurston County(7) 53067                      2720.3       2140.8       3408.4       2             1             8                   18 #>   Recent_Trend Recent_5_Year_Trend Trend_Lower_95%_CI Trend_Upper_95%_CI #> 1      falling                -1.7               -2.4               -0.9 #> 2      falling                -0.5               -0.8               -0.2 #> 3         <NA>                  NA                 NA                 NA"},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"load-the-package","dir":"Articles","previous_headings":"","what":"Load the package","title":"mortality-vignette","text":"","code":"library(cancerprof)"},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"retrieving-data","dir":"Articles","previous_headings":"","what":"Retrieving Data","title":"mortality-vignette","text":"Cancer Mortality category cancerprof contains single functions pull data Mortality page State Cancer Profile. function retrieving incidence data mortality_cancer()","code":""},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"mortality-cancer","dir":"Articles","previous_headings":"","what":"Mortality Cancer","title":"mortality-vignette","text":"Mortality cancer 22 cancer types choose . total, incidence cancer 7 arguments: area, areatype, cancer, race, sex, age, year","code":""},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"argument-details","dir":"Articles","previous_headings":"Mortality Cancer","what":"Argument Details","title":"mortality-vignette","text":"\"latest single year (us state)\" argument year can selected area \"state\" following cancer types: “breast (female)”, “ovary”, “uterus (corpus & uterus, nos)” sex argument must \"females\" \"prostate\" cancer, sex must \"males\" \"childhood (ages <15, sites)\", age must \"ages <15\" \"childhood (ages <20, sites)\", age must \"ages <20\"","code":""},{"path":"http://getwilds.org/cancerprof/articles/mortality-vignette.html","id":"examples","dir":"Articles","previous_headings":"Mortality Cancer","what":"Examples","title":"mortality-vignette","text":"","code":"mortality1 <- mortality_cancer(   area = \"wa\",   areatype = \"county\",   cancer = \"all cancer sites\",   race = \"black (non-hispanic)\",   sex = \"both sexes\",   age = \"ages 65+\",   year = \"latest 5 year average\" ) head(mortality1, n = 3) #>            County  FIPS Met Healthy People Objective of ***? Age_Adjusted_Death_Rate Lower_95%_CI_Rate Upper_95%_CI_Rate CI_Rank Lower_CI_Rank #> 1   Yakima County 53077                                   No                  1676.3             947.3            2727.3       1             1 #> 2 Thurston County 53067                                   No                  1187.5             791.2            1704.8       2             1 #> 3   Pierce County 53053                                   No                  1099.3             971.9            1238.8       3             1 #>   Upper_CI_Rank Annual_Average_Count Recent_Trend Recent_5_Year_Trend Lower_95%_CI_Trend Upper_95%_CI_Trend #> 1             5                    3         <NA>                  NA                 NA                 NA #> 2             7                    7         <NA>                  NA                 NA                 NA #> 3             5                   59      falling                -0.9               -1.7               -0.1  mortality2 <- mortality_cancer(   area = \"usa\",   areatype = \"state\",   cancer = \"prostate\",   race = \"all races (includes hispanic)\",   sex = \"males\",   age = \"ages 50+\",   year = \"latest single year (us by state)\" ) head(mortality2, n = 3) #>                  State  FIPS Met Healthy People Objective of ***? Age_Adjusted_Death_Rate Lower_95%_CI_Rate Upper_95%_CI_Rate CI_Rank #> 1 District of Columbia 11001                                   No                    98.9              77.6             124.1       1 #> 2             Colorado 08000                                   No                    86.1              79.3              93.3       2 #> 3              Vermont 50000                                   No                    84.4              67.8             103.9       3 #>   Lower_CI_Rank Upper_CI_Rank Annual_Average_Count Recent_Trend Recent_5_Year_Trend Lower_95%_CI_Trend Upper_95%_CI_Trend #> 1             1            35                   76      falling                -3.3               -3.9               -2.8 #> 2             1             9                  623       stable                -0.1               -1.0                0.9 #> 3             1            46                   93       stable                 4.7               -3.8               13.9  mortality3 <- mortality_cancer(   area = \"wa\",   areatype = \"hsa\",   cancer = \"ovary\",   race = \"all races (includes hispanic)\",   sex = \"females\",   age = \"ages 50+\",   year = \"latest 5 year average\" ) head(mortality3, n = 3) #>           Health_Service_Area HSA_Code Met Healthy People Objective of ***? Age_Adjusted_Death_Rate Lower_95%_CI_Rate Upper_95%_CI_Rate #> 1 Clallam, WA - Jefferson, WA     0785                                  ***                    34.6              26.3              44.8 #> 2                 Whatcom, WA     0815                                  ***                    31.4              24.2              40.0 #> 3                  Pierce, WA     0794                                  ***                    24.6              21.1              28.6 #>   CI_Rank Lower_CI_Rank Upper_CI_Rank Annual_Average_Count Recent_Trend Recent_5_Year_Trend Lower_95%_CI_Trend Upper_95%_CI_Trend #> 1       1             1             4                   12       stable                -1.0               -2.4                0.3 #> 2       2             1             6                   14       stable                -0.7               -2.1                0.7 #> 3       3             2             9                   36      falling                -1.4               -2.0               -0.9"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"load-the-package","dir":"Articles","previous_headings":"","what":"Load the package","title":"Screening and Risk Factors","text":"","code":"library(cancerprof)"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"retrieving-data","dir":"Articles","previous_headings":"","what":"Retrieving Data","title":"Screening and Risk Factors","text":"Screening Risk Factors category cancerprof contains 6 unique functions pull data Screening Risk Factor page State Cancer Profile. functions : risk_alcohol(), risk_colorectal_screening(), risk_diet_exercise(), risk_smoking(), risk_vaccines(), risk_womens_health() functions require various parameters must specified pull data. Please refer function documentation details.","code":""},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-alcohol","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Alcohol","title":"Screening and Risk Factors","text":"Risk Alcohol requires 3 arguments: alcohol, race, sex","code":"alcohol1 <- risk_alcohol(   alcohol = paste(     \"binge drinking (4+ drinks on one occasion for women,\",     \"5+ drinks for one occasion for men), ages 21+\"   ),   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) head(alcohol1, n = 3) #>                  State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 District of Columbia 11001    26.2         23.9         28.4                   566 #> 2         North Dakota 38000    22.8         21.1         24.5                   676 #> 3                 Iowa 19000    21.9         20.7         23.1                  1515"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-colorectal-screening","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Colorectal Screening","title":"Screening and Risk Factors","text":"Risk Colorectal Screening 4 arguments: screening, race, sex, area \"home blood stool test past year, ages 45-75\" \"received least one recommended crc test, ages 45-75\" screening arguments requires race argument sex argument defaults \"direct estimates\", \"US state\". \"ever fobt, ages 50-75\", \"guidance sufficient crc, ages 50-75\", \"colonoscopy past 10 years, ages 50-75\" screening arguments defaults \"races\", \"sexes\", \"county level modeled estimates\".","code":"screening1 <- risk_colorectal_screening(   screening = \"home blood stool test in the past year, ages 45-75\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) head(screening1, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1     Wyoming 56000     3.0          2.2          3.7                    75 #> 2 Mississippi 28000     3.4          2.3          4.5                    64 #> 3    Delaware 10000     3.8          3.0          4.7                   106  screening2 <- risk_colorectal_screening(   screening = \"ever had fobt, ages 50-75\",   area = \"usa\" ) head(screening2, n = 3) #>               County  FIPS Model_Based_Percent (95%_Confidence_Interval) Lower_95%_CI Upper_95%_CI #> 1 New Hanover County 37129                                           0.2            0          1.2 #> 2    Columbus County 37047                                           0.3            0          1.5 #> 3       Dixon County 31051                                           0.3            0          1.5"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-diet-exercise","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Diet-Exercise","title":"Screening and Risk Factors","text":"Risk Diet-Exercise requires 3 arguments: diet_exercise , race, sex","code":"diet_exercise1 <- risk_diet_exercise(   diet_exercise = \"bmi is healthy, ages 20+\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) head(diet_exercise1, n = 3) #>           State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 West Virginia 54000    22.5         21.0         24.0                  1061 #> 2   Mississippi 28000    24.8         23.0         26.6                   906 #> 3      Oklahoma 40000    25.1         23.6         26.5                  1304  diet_exercise2 <- risk_diet_exercise(   diet_exercise = \"bmi is obese, high school survey\",   race = \"all races (includes hispanic)\",   sex = \"males\" ) head(diet_exercise2, n = 3) #>           State  FIPS Percent Lower_95%_CI Upper_95%_CI #> 1 West Virginia 54000    29.5         20.6         40.2 #> 2   Mississippi 28000    28.0         25.2         30.9 #> 3         Texas 48000    25.7         22.4         29.3"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-smoking","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Smoking","title":"Screening and Risk Factors","text":"Risk Smoking arguments 5: smoking, race, sex, datatype, area. following smoking arguments: \"smoking laws ()\" \"smoking laws (bars)\" \"smoking laws (restaurants)\" \"smoking laws (workplace)\" \"smoking laws (workplace; restaurant; & bar)\" include smoking argument. race, sex, datatype, area defaulted \"races\", \"sexes\", \"direct estimates\", \"US State\" following smoking arguments: “smokers (stopped 1 day longer)”, “smoking allowed work (people)”, “smoking allowed home (people)” Select sex argument. \"sexes\" selected sex, select datatype argument. \"county level modeled estimates\" selected datatype, select area argument. race, always defaulted \"races\". datatype area always defaulted \"direct estimates\", \"US State\" sex “male” “female”. following smoking arguments: \"smoking allowed work (current smokers)\" \"smoking allowed work (former/never smokers)\" \"smoking allowed home (current smokers)\" \"smoking allowed home (former/never smokers)\" Select sex argument. race, datatype, area defaulted \"races\", \"direct estimates\", \"US State\". following smoking arguments: \"former smoker; ages 18+\" \"former smoker, quit 1 year+; ages 18+\" Select sex area argument. race datatype defaulted \"races\", \"direct estimates\" following smoking arguments: \"smokers (ever); ages 18+\" \"e-cigarette use; ages 18+\" Select race sex argument. datatype area defaulted \"direct estimates\" \"US State\". “smokers (current); ages 18+” Select race sex argument. \"races (includes hispanic)\" selected race, select datatype argument. \"county level modeled estimates\" selected datatype, select area argument. datatype area always defaulted \"direct estimates\", \"US State\" race \"races (includes hispanic)\".","code":"smoking1 <- risk_smoking(   smoking = \"smokers (stopped for 1 day or longer)\",   sex = \"both sexes\",   datatype = \"county level modeled estimates\",   area = \"wa\" ) head(smoking1, n = 3) #>            County  FIPS Percent Lower_95%_CI Upper_95%_CI #> 1    Grant County 53025    40.8         28.2         53.8 #> 2 Kittitas County 53037    41.4         29.0         54.3 #> 3 Thurston County 53067    41.7         29.2         54.3  smoking2 <- risk_smoking(   smoking = \"smoking not allowed at work (current smokers)\",   sex = \"both sexes\",   datatype = \"direct estimates\" ) head(smoking2, n = 3) #>     State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1  Nevada 32000    55.2         43.9         65.9                    55 #> 2 Wyoming 56000    57.9         47.1         68.0                    69 #> 3    Utah 49000    61.2         47.5         73.3                    39  smoking3 <- risk_smoking(   smoking = \"smokers (current); ages 18+\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\",   datatype = \"county level modeled estimates\",   area = \"wa\" ) head(smoking3, n = 3) #>           County  FIPS Percent Lower_95%_CI Upper_95%_CI #> 1   Mason County 53045    17.9         13.6         22.8 #> 2 Cowlitz County 53015    17.8         13.9         22.2 #> 3 Stevens County 53065    17.1         12.9         21.8"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-vaccines","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Vaccines","title":"Screening and Risk Factors","text":"Risk Vaccines requires 2 arguments: vaccines sex","code":"vaccines1 <- risk_vaccines(    vaccine = \"percent with up to date hpv vaccination coverage, ages 13-17\",    sex = \"females\" ) head(vaccines1, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 Mississippi 28000    32.6         23.9         42.6                    48 #> 2     Wyoming 56000    48.7         38.2         59.3                    70 #> 3    Kentucky 21000    48.9         37.2         60.7                    59  vaccines2 <- risk_vaccines(    vaccine = \"percent with up to date hpv vaccination coverage, ages 13-15\",    sex = \"both sexes\" ) head(vaccines2, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 Mississippi 28000    35.9         27.7         45.0                    59 #> 2     Wyoming 56000    44.0         34.9         53.5                    79 #> 3       Texas 48000    46.4         39.6         53.3                   318"},{"path":"http://getwilds.org/cancerprof/articles/risks-vignette.html","id":"risk-womens-health","dir":"Articles","previous_headings":"Retrieving Data","what":"Risk Women’s Health","title":"Screening and Risk Factors","text":"Risk Women’s Health 4 arguments: women_health, race, datatype, area \"races (includes hispanic)\" selected race, select datatype argument. race selected, datatype area defaulted \"direct estimates\" \"US State\".","code":"vaccines1 <- risk_vaccines(    vaccine = \"percent with up to date hpv vaccination coverage, ages 13-17\",    sex = \"females\" ) head(vaccines1, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 Mississippi 28000    32.6         23.9         42.6                    48 #> 2     Wyoming 56000    48.7         38.2         59.3                    70 #> 3    Kentucky 21000    48.9         37.2         60.7                    59  vaccines2 <- risk_vaccines(    vaccine = \"percent with up to date hpv vaccination coverage, ages 13-15\",    sex = \"both sexes\" ) head(vaccines2, n = 3) #>         State  FIPS Percent Lower_95%_CI Upper_95%_CI Number_of_Respondents #> 1 Mississippi 28000    35.9         27.7         45.0                    59 #> 2     Wyoming 56000    44.0         34.9         53.5                    79 #> 3       Texas 48000    46.4         39.6         53.3                   318"},{"path":"http://getwilds.org/cancerprof/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Brian Park. Author, maintainer.","code":""},{"path":"http://getwilds.org/cancerprof/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Park B (2024). cancerprof: API Client State Cancer Profiles. R package version 0.1.0, http://getwilds.org/cancerprof/, https://github.com/getwilds/cancerprof.","code":"@Manual{,   title = {cancerprof: API Client for State Cancer Profiles},   author = {Brian Park},   year = {2024},   note = {R package version 0.1.0, http://getwilds.org/cancerprof/},   url = {https://github.com/getwilds/cancerprof}, }"},{"path":[]},{"path":"http://getwilds.org/cancerprof/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"API Client for State Cancer Profiles","text":"Cancerprof designed allow programmable research data State Cancer Profiles","code":""},{"path":"http://getwilds.org/cancerprof/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"API Client for State Cancer Profiles","text":"can install development version cancerprof GitHub :","code":"# install.packages(\"pak\") pak::pak(\"getwilds/cancerprof\")"},{"path":"http://getwilds.org/cancerprof/index.html","id":"support","dir":"","previous_headings":"","what":"Support","title":"API Client for State Cancer Profiles","text":"questions, bugs, feature requests, please reach Brian Park joon.brianpark@gmail.com, open issue issue tracker","code":""},{"path":"http://getwilds.org/cancerprof/reference/cancerprof-package.html","id":null,"dir":"Reference","previous_headings":"","what":"cancerprof: API Client for State Cancer Profiles — cancerprof-package","title":"cancerprof: API Client for State Cancer Profiles — cancerprof-package","text":"API Client accessing data State Cancer Profiles programmable analysis.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/cancerprof-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"cancerprof: API Client for State Cancer Profiles — cancerprof-package","text":"Maintainer: Brian Park joon.brianpark@gmail.com (ORCID)","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Crowding Data — demo_crowding","title":"Access to Crowding Data — demo_crowding","text":"function returns data frame crowding demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Crowding Data — demo_crowding","text":"","code":"demo_crowding(area, areatype, crowding, race)"},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Crowding Data — demo_crowding","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". crowding permissible value \"household >1 person per room\". race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White Non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Crowding Data — demo_crowding","text":"data frame following columns: Area, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_crowding.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Crowding Data — demo_crowding","text":"","code":"if (FALSE) { demo_crowding(   area = \"WA\",   areatype = \"county\",   crowding = \"household with >1 person per room\",   race = \"All Races (includes Hispanic)\" )  demo_crowding(   area = \"usa\",   areatype = \"state\",   crowding = \"household with >1 person per room\",   race = \"All Races (includes Hispanic)\" )  demo_crowding(   area = \"pr\",   areatype = \"hsa\",   crowding = \"household with >1 person per room\",   race = \"black\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Education Data — demo_education","title":"Access to Education Data — demo_education","text":"function returns data frame education demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Education Data — demo_education","text":"","code":"demo_education(area, areatype, education, sex = NULL, race = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Education Data — demo_education","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". education One following values: \"less 9th grade\" \"least high school\" \"least bachelors degree\". sex One following values: \"sexes\" \"male\" \"female\". race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race).","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Education Data — demo_education","text":"data frame following columns: Area Type, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_education.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Education Data — demo_education","text":"","code":"if (FALSE) { demo_education(   area = \"wa\",   areatype = \"county\",   education = \"at least high school\",   sex = \"males\" )  demo_education(   area = \"usa\",   areatype = \"state\",   education = \"at least bachelors degree\",   sex = \"both sexes\",   race = \"all races (includes hispanic)\" )  demo_education(   area = \"pr\",   areatype = \"hsa\",   education = \"less than 9th grade\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Food Insecurity Data — demo_food","title":"Access to Food Insecurity Data — demo_food","text":"function returns data frame food demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Food Insecurity Data — demo_food","text":"","code":"demo_food(area, areatype, food, race = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Food Insecurity Data — demo_food","text":"area state/territory abbreviation USA. areatype Either \"county\" \"state\". food One following values: \"food insecurity\" \"limited access healthy food\". race One following values: \"Races (includes Hispanic)\" \"White non-Hispanic\" \"Black (includes Hispanic)\" \"Hispanic (Race).","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Food Insecurity Data — demo_food","text":"data frame following columns: Area Type, Area Code, Value, People.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_food.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Food Insecurity Data — demo_food","text":"","code":"if (FALSE) { demo_food(   area = \"wa\",   areatype = \"county\",   food = \"food insecurity\",   race = \"black\" )  demo_food(   area = \"usa\",   areatype = \"state\",   food = \"limited access to healthy food\" )  demo_food(   area = \"pr\",   areatype = \"county\",   food = \"food insecurity\",   race = \"all races (includes hispanic)\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Income Data — demo_income","title":"Access to Income Data — demo_income","text":"function returns data frame income demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Income Data — demo_income","text":"","code":"demo_income(area, areatype, income, race)"},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Income Data — demo_income","text":"area state/territory abbreviation USA. areatype Either \"county\" \"state\". income Either \"median family income\" \"median household income\". race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race).","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Income Data — demo_income","text":"data frame following columns: Area Type, Area Code, Dollars, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_income.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Income Data — demo_income","text":"","code":"if (FALSE) { demo_income(   area = \"wa\",   areatype = \"county\",   income = \"median household income\",   race = \"all races (includes hispanic)\" )  demo_income(   area = \"usa\",   areatype = \"state\",   income = \"median family income\",   race = \"all races (includes hispanic)\" )  demo_income(   area = \"pr\",   areatype = \"county\",   income = \"median family income\",   race = \"all races (includes hispanic)\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Insurance Data — demo_insurance","title":"Access to Insurance Data — demo_insurance","text":"function returns data frame insurance demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Insurance Data — demo_insurance","text":"","code":"demo_insurance(area, areatype, insurance, sex, age, race = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Insurance Data — demo_insurance","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". insurance One following values: \"% Insured demographic group, income levels\" \"% Insured demographic group, people 138% Poverty\" \"% Insured demographic group, people 200% Poverty\" \"% Insured demographic group, people 250% Poverty\" \"% Insured demographic group, people 400% Poverty\" \"% Insured demographic group, people 138% - 400% poverty\" \"% uninsured demographic group, income levels\" \"% uninsured demographic group, people 138% Poverty\" \"% uninsured demographic group, people 200% Poverty\" \"% uninsured demographic group, people 250% Poverty\" \"% uninsured demographic group, people 400% Poverty\" \"% uninsured demographic group, people 138% - 400% poverty\". sex One following values: \"sexes\" \"male\" \"female\". age specified \"sexes\" sex choose one following values: \"19 years\" \"18 64 years\" \"21 64 years\" \"40 64 years\" \"50 64 years\" \"65 years\". Otherwise specified \"male\" \"female\" sex, choose one following values: \"18 64 years\" \"40 64 years\" \"50 64 years\" \"65 years\". race specify race specified \"state\" areatype \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian (non-Hispanic)\" \"Hispanic (Race)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Insurance Data — demo_insurance","text":"data frame following columns: Area Type, Area Code, Percent, People, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_insurance.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Insurance Data — demo_insurance","text":"","code":"if (FALSE) { demo_insurance(   area = \"usa\",   areatype = \"state\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"both sexes\",   age = \"18 to 64 years\",   race = \"white (non-hispanic)\" )  demo_insurance(   area = \"wa\",   areatype = \"hsa\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"males\",   age = \"18 to 64 years\" )  demo_insurance(   area = \"dc\",   areatype = \"county\",   insurance = \"% Insured in demographic group, all income levels\",   sex = \"males\",   age = \"18 to 64 years\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Non-English Language — demo_language","title":"Access to Non-English Language — demo_language","text":"function returns data frame language demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Non-English Language — demo_language","text":"","code":"demo_language(area, areatype, language)"},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Non-English Language — demo_language","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". language permissible value \"language isolation\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Non-English Language — demo_language","text":"data frame following columns: Area Type, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_language.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Non-English Language — demo_language","text":"","code":"demo_language(   area = \"WA\",   areatype = \"county\",   language = \"language isolation\" ) #>                 County  FIPS Percent Households         Rank #> 1         Adams County 53001    18.9       1165 3127 of 3142 #> 2      Franklin County 53021    11.0       3044 3087 of 3142 #> 3         Grant County 53025     8.6       2810 3044 of 3142 #> 4        Yakima County 53077     8.0       6759 3020 of 3142 #> 5          King County 53033     5.7      51842 2934 of 3142 #> 6   Walla Walla County 53071     4.6       1040 2854 of 3142 #> 7        Chelan County 53007     4.4       1284 2840 of 3142 #> 8     Snohomish County 53061     4.3      13011 2835 of 3142 #> 9       Douglas County 53017     4.3        655 2831 of 3142 #> 10      Whitman County 53075     3.4        610 2735 of 3142 #> 11       Benton County 53005     3.0       2262 2685 of 3142 #> 12        Clark County 53011     2.8       5209 2638 of 3142 #> 13       Pierce County 53053     2.7       9204 2609 of 3142 #> 14     Okanogan County 53047     2.5        421 2557 of 3142 #> 15       Skagit County 53057     2.5       1278 2556 of 3142 #> 16 Grays Harbor County 53027     2.1        602 2419 of 3142 #> 17     Thurston County 53067     2.0       2299 2403 of 3142 #> 18     Columbia County 53013     1.9         36 2370 of 3142 #> 19        Mason County 53045     1.8        455 2308 of 3142 #> 20      Pacific County 53049     1.6        162 2222 of 3142 #> 21      Whatcom County 53073     1.3       1208 2056 of 3142 #> 22      Cowlitz County 53015     1.3        565 2032 of 3142 #> 23      Spokane County 53063     1.1       2395 1898 of 3142 #> 24       Island County 53029     1.0        366 1822 of 3142 #> 25       Kitsap County 53035     1.0       1058 1786 of 3142 #> 26    Jefferson County 53031     1.0        149 1751 of 3142 #> 27     Kittitas County 53037     1.0        179 1741 of 3142 #> 28     San Juan County 53055     0.8         71 1643 of 3142 #> 29        Lewis County 53041     0.8        251 1603 of 3142 #> 30    Klickitat County 53039     0.7         68 1508 of 3142 #> 31      Clallam County 53009     0.6        201 1337 of 3142 #> 32      Stevens County 53065     0.3         63  941 of 3142 #> 33        Ferry County 53019     0.3          9  888 of 3142 #> 34     Skamania County 53059     0.3         13  823 of 3142 #> 35       Asotin County 53003     0.1         13  552 of 3142 #> 36 Pend Oreille County 53051     0.1          6  479 of 3142 #> 37      Lincoln County 53043     0.0          2  380 of 3142 #> 38     Garfield County 53023     0.0          0    1 of 3142 #> 39    Wahkiakum County 53069     0.0          0    1 of 3142  demo_language(   area = \"dc\",   areatype = \"hsa\",   language = \"language isolation\" ) #>    Health_Service_Area HSA_Code Percent Households       Rank #> 1 District of Columbia     0061     3.2       9986 799 of 949  demo_language(   area = \"usa\",   areatype = \"state\",   language = \"language isolation\" ) #>                   State  FIPS Percent Households     Rank #> 1            California 06000     8.5    1119486 51 of 51 #> 2              New York 36000     7.6     571749 50 of 51 #> 3                 Texas 48000     7.1     731111 49 of 51 #> 4            New Jersey 34000     6.9     233543 48 of 51 #> 5               Florida 12000     6.9     559135 47 of 51 #> 6         Massachusetts 25000     6.1     164605 46 of 51 #> 7                Hawaii 15000     5.6      26740 45 of 51 #> 8                Nevada 32000     5.4      61770 44 of 51 #> 9          Rhode Island 44000     5.3      22738 43 of 51 #> 10           New Mexico 35000     5.3      42339 42 of 51 #> 11          Connecticut 09000     5.2      73153 41 of 51 #> 12             Illinois 17000     4.3     211120 40 of 51 #> 13           Washington 53000     3.8     110765 39 of 51 #> 14              Arizona 04000     3.7      99159 38 of 51 #> 15             Maryland 24000     3.3      74920 37 of 51 #> 16 District of Columbia 11001     3.2       9986 36 of 51 #> 17              Georgia 13000     2.7     104353 35 of 51 #> 18             Virginia 51000     2.6      85864 34 of 51 #> 19             Nebraska 31000     2.6      20165 33 of 51 #> 20         Pennsylvania 42000     2.5     126940 32 of 51 #> 21             Colorado 08000     2.4      54213 31 of 51 #> 22               Kansas 20000     2.4      27336 30 of 51 #> 23             Delaware 10000     2.4       9080 29 of 51 #> 24               Oregon 41000     2.3      38081 28 of 51 #> 25               Alaska 02900     2.2       5798 27 of 51 #> 26            Minnesota 27000     2.2      48431 26 of 51 #> 27       North Carolina 37000     2.2      87133 25 of 51 #> 28                 Utah 49000     2.1      21249 24 of 51 #> 29             Oklahoma 40000     2.0      29432 23 of 51 #> 30                Idaho 16000     1.9      12563 22 of 51 #> 31                 Iowa 19000     1.8      23591 21 of 51 #> 32            Louisiana 22000     1.8      31553 20 of 51 #> 33              Indiana 18000     1.7      43281 19 of 51 #> 34             Michigan 26000     1.6      64810 18 of 51 #> 35             Arkansas 05000     1.6      18054 17 of 51 #> 36            Tennessee 47000     1.5      40538 16 of 51 #> 37            Wisconsin 55000     1.4      33923 15 of 51 #> 38                 Ohio 39000     1.4      66143 14 of 51 #> 39             Kentucky 21000     1.4      24306 13 of 51 #> 40       South Carolina 45000     1.3      26558 12 of 51 #> 41         North Dakota 38000     1.2       3953 11 of 51 #> 42              Alabama 01000     1.2      22804 10 of 51 #> 43        New Hampshire 33000     1.2       6267  9 of 51 #> 44             Missouri 29000     1.1      26952  8 of 51 #> 45         South Dakota 46000     1.1       3705  7 of 51 #> 46              Wyoming 56000     1.0       2214  6 of 51 #> 47                Maine 23000     0.9       4931  5 of 51 #> 48          Mississippi 28000     0.8       9338  4 of 51 #> 49              Vermont 50000     0.6       1629  3 of 51 #> 50              Montana 30000     0.4       1625  2 of 51 #> 51        West Virginia 54000     0.3       2194  1 of 51 #> 52          Puerto Rico 72001      NA         NA     <NA>"},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Mobility Data — demo_mobility","title":"Access to Mobility Data — demo_mobility","text":"function returns data frame mobility demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Mobility Data — demo_mobility","text":"","code":"demo_mobility(area, areatype, mobility)"},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Mobility Data — demo_mobility","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". mobility permissible values \"moved (past year)\" \"moved outside us (past year)\" \"moved, different state (past year)\" \"moved, different county, state (past year)\" \"moved, county (past year)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Mobility Data — demo_mobility","text":"data frame following columns: Area Type, Area Code, Percent, People, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_mobility.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Mobility Data — demo_mobility","text":"","code":"if (FALSE) { demo_mobility(   area = \"WA\",   areatype = \"county\",   mobility = \"moved, different county, same state (in past year)\" )  demo_mobility(   area = \"usa\",   areatype = \"state\",   mobility = \"moved, same county (in past year)\" )  demo_mobility(   area = \"dc\",   areatype = \"hsa\",   mobility = \"moved, same county (in past year)\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Population Data — demo_population","title":"Access to Population Data — demo_population","text":"function returns data frame population State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Population Data — demo_population","text":"","code":"demo_population(area, areatype, population, race = NULL, sex = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Population Data — demo_population","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". population One following values: \"age 18\" \"age 18-39\" \"age 40-64\" \"ages 40 \" \"ages 50 \" \"ages 60 \" \"american indian/alaska native\" \"asian/pacific islander\" \"black\" \"foreign born\" \"hispanic\" \"non-hispanic (origin recode)\" \"white\" \"males\" \"females\". race One following values: \"American Indian/Alaska Native\" \"Asian/Pacific Islander\" \"Black\" \"Hispanic\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Population Data — demo_population","text":"data frame following columns: Area Type, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_population.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Population Data — demo_population","text":"","code":"if (FALSE) { demo_population(   area = \"WA\",   areatype = \"county\",   population = \"males\",   race = \"all races (includes hispanic)\" )  demo_population(   area = \"dc\",   areatype = \"hsa\",   population = \"foreign born\",   race = \"black\",   sex = \"females\" )  demo_population(   area = \"usa\",   areatype = \"state\",   population = \"foreign born\",   race = \"hispanic (any race)\",   sex = \"females\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Poverty Data — demo_poverty","title":"Access to Poverty Data — demo_poverty","text":"function returns data frame poverty demographics State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Poverty Data — demo_poverty","text":"","code":"demo_poverty(area, areatype, poverty, race = NULL, sex = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Poverty Data — demo_poverty","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". poverty One following values: \"families poverty\" \"persistent poverty\" \"persons poverty\" \"persons < 150% poverty\". race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race). sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Poverty Data — demo_poverty","text":"data frame following columns: Area Type, Area Code, Percent, Households, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_poverty.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Poverty Data — demo_poverty","text":"","code":"if (FALSE) { demo_poverty(   area = \"WA\",   areatype = \"county\",   poverty = \"persistent poverty\" )  demo_poverty(   area = \"usa\",   areatype = \"state\",   poverty = \"families below poverty\",   race = \"black\" )  demo_poverty(   area = \"dc\",   areatype = \"hsa\",   poverty = \"families below poverty\",   race = \"All Races (includes Hispanic)\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Social Vulnerability Index (SVI) Data — demo_svi","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"function returns data frame social vulnerability index (SVI) State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"","code":"demo_svi(area, svi)"},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"area state/territory abbreviation USA. svi One following values: \"Overall\" \"socioeconomic status\" \"household characteristics\" \"racial & ethinic minority status\" \"housing type & transportation\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"data frame following columns: County, FIPS, Score.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_svi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Social Vulnerability Index (SVI) Data — demo_svi","text":"","code":"if (FALSE) { demo_svi(   area = \"WA\",   svi = \"overall\" )  demo_svi(   area = \"usa\",   svi = \"overall\" )  demo_svi(   area = \"dc\",   svi = \"socioeconomic status\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Workforce Data — demo_workforce","title":"Access to Workforce Data — demo_workforce","text":"function returns data frame Workforce State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Workforce Data — demo_workforce","text":"","code":"demo_workforce(area, areatype, workforce, race, sex)"},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Workforce Data — demo_workforce","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". workforce permissible value \"unemployed\" race One following values: \"Races (includes Hispanic)\" \"White (includes Hispanic)\" \"White non-Hispanic\" \"Black\" \"Amer. Indian/Alaskan Native (includes Hispanic)\" \"Asian Pacific Islander (includes Hispanic)\" \"Hispanic (Race). sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Workforce Data — demo_workforce","text":"data frame following columns: Area Type, Area Code, Percent, People Unemployed, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/demo_workforce.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Workforce Data — demo_workforce","text":"","code":"if (FALSE) { demo_workforce(   area = \"WA\",   areatype = \"county\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" )  demo_workforce(   area = \"usa\",   areatype = \"state\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"females\" )  demo_workforce(   area = \"pr\",   areatype = \"hsa\",   workforce = \"unemployed\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Cancer Incident Data — incidence_cancer","title":"Access to Cancer Incident Data — incidence_cancer","text":"function returns data frame cancer incidence State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Cancer Incident Data — incidence_cancer","text":"","code":"incidence_cancer(area, areatype, cancer, race, sex, age, stage, year)"},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Cancer Incident Data — incidence_cancer","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". cancer One following values: \"cancer sites\" \"bladder\" \"brain & ons\" \"breast (female)\" \"breast (female situ)\" \"cervix\" \"childhood (ages <15, sites)\" \"childhood (ages <20, sites)\" \"colon & rectum\" \"esophagus\" \"kidney & renal pelvis\" \"leukemia\" \"liver & bile duct\" \"lung & bronchus\" \"melanoma skin\" \"non-hodgkin lymphoma\" \"oral cavity & pharynx\" \"ovary\" \"pancreas\" \"prostate\" \"stomach\" \"thyroid\" \"uterus (corpus & uterus, nos)\". race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\". age One following values: \"ages\" \"ages <50\" \"ages 50+\" \"ages <65\" \"ages 65+\" \"ages <15\" \"ages <20\". stage One following values: \"stages\" \"late stage (regional & distant)\". year One following values: \"latest 5 year average\" \"latest single year (us state)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Cancer Incident Data — incidence_cancer","text":"data frame following columns: Area Type, Area Code, Age Adjusted Incidence Rate, Lower 95% CI, Upper 95% CI, CI Rank, Lower CI Rank, Upper CI Rank, Annual Average Count, Recent Trend, Recent 5 Year Trend, Trend Lower 95% CI, Trend Upper 95% CI.","code":""},{"path":"http://getwilds.org/cancerprof/reference/incidence_cancer.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Cancer Incident Data — incidence_cancer","text":"","code":"if (FALSE) { incidence_cancer(   area = \"wa\",   areatype = \"county\",   cancer = \"all cancer sites\",   race = \"black (non-hispanic)\",   sex = \"both sexes\",   age = \"ages 65+\",   stage = \"all stages\",   year = \"latest 5 year average\" )  incidence_cancer(   area = \"usa\",   areatype = \"state\",   cancer = \"lung & bronchus\",   race = \"all races (includes hispanic)\",   sex = \"males\",   age = \"ages 50+\",   stage = \"late stage (regional & distant)\",   year = \"latest single year (us by state)\" )  incidence_cancer(   area = \"wa\",   areatype = \"hsa\",   cancer = \"ovary\",   race = \"all races (includes hispanic)\",   sex = \"females\",   age = \"ages 50+\",   stage = \"late stage (regional & distant)\",   year = \"latest 5 year average\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Cancer Mortality Data — mortality_cancer","title":"Access to Cancer Mortality Data — mortality_cancer","text":"function returns data frame cancer mortality State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Cancer Mortality Data — mortality_cancer","text":"","code":"mortality_cancer(area, areatype, cancer, race, sex, age, year)"},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Cancer Mortality Data — mortality_cancer","text":"area state/territory abbreviation USA. areatype One following values: \"county\" \"hsa\" (Health Service Area) \"state\". cancer One following values: \"cancer sites\" \"bladder\" \"brain & ons\" \"breast (female)\" \"cervix\" \"childhood (ages <15, sites)\" \"childhood (ages <20, sites)\" \"colon & rectum\" \"esophagus\" \"kidney & renal pelvis\" \"leukemia\" \"liver & bile duct\" \"lung & bronchus\" \"melanoma skin\" \"non-hodgkin lymphoma\" \"oral cavity & pharynx\" \"ovary\" \"pancreas\" \"prostate\" \"stomach\" \"thyroid\" \"uterus (corpus & uterus, nos)\" race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\". age One following values: \"ages\" \"ages <50\" \"ages 50+\" \"ages <65\" \"ages 65+\" \"ages <15\" \"ages <20\". year One following values: \"latest 5 year average\" \"latest single year (us state)\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Cancer Mortality Data — mortality_cancer","text":"data frame following columns: Area Type, Area Code, Met Healthy People Objective ***?, Age Adjusted Death Rate, Lower 95% CI Rate, Upper 95% CI Rate, CI Rank, Lower CI Rank, Upper CI Rank, Annual Average Count, Recent Trend, Recent 5 Year Trend, Lower 95% CI Trend, Upper 95% CI Trend.","code":""},{"path":"http://getwilds.org/cancerprof/reference/mortality_cancer.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Cancer Mortality Data — mortality_cancer","text":"","code":"if (FALSE) { mortality_cancer(   area = \"wa\",   areatype = \"county\",   cancer = \"all cancer sites\",   race = \"black (non-hispanic)\",   sex = \"both sexes\",   age = \"ages 65+\",   year = \"latest 5 year average\" )  mortality_cancer(   area = \"usa\",   areatype = \"state\",   cancer = \"prostate\",   race = \"all races (includes hispanic)\",   sex = \"males\",   age = \"ages 50+\",   year = \"latest single year (us by state)\" )  mortality_cancer(   area = \"wa\",   areatype = \"hsa\",   cancer = \"ovary\",   race = \"all races (includes hispanic)\",   sex = \"females\",   age = \"ages 50+\",   year = \"latest 5 year average\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"http://getwilds.org/cancerprof/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"http://getwilds.org/cancerprof/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"http://getwilds.org/cancerprof/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Alcohol Screening and Risk Data — risk_alcohol","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"function returns data frame alcohol risks State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"","code":"risk_alcohol(alcohol, race, sex)"},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"alcohol permissible value `paste(\"binge drinking (4+ drinks one occasion women,\", \"5+ drinks one occasion men), ages 21+\") race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"data frame following columns: Area Type, Area Code, Percent, Lower 95% CI, Upper 95% CI, Number Respondents.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_alcohol.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Alcohol Screening and Risk Data — risk_alcohol","text":"","code":"if (FALSE) { risk_alcohol(   alcohol = paste(     \"binge drinking (4+ drinks on one occasion for women,\",     \"5+ drinks for one occasion for men), ages 21+\"   ),   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Colorectal Screening Data — risk_colorectal_screening","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"function returns data frame colorectal screening State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"","code":"risk_colorectal_screening(screening, race = NULL, sex = NULL, area = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"screening One following values: \"ever fobt, ages 50-75\" \"guidance sufficient crc, ages 50-75\" \"colonoscopy past 10 years, ages 50-75\" \"home blood stool test past year, ages 45-75\" \"received least one recommended crc test, ages 45-75\". race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\". area state/territory abbreviation USA.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"data frame following columns: Area Type, Area Code, Percent, People Unemployed, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_colorectal_screening.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Colorectal Screening Data — risk_colorectal_screening","text":"","code":"if (FALSE) { risk_colorectal_screening(   screening = \"home blood stool test in the past year, ages 45-75\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" )  risk_colorectal_screening(   screening = \"ever had fobt, ages 50-75\",   area = \"usa\" ) risk_colorectal_screening(   screening = \"received at least one recommended crc test, ages 45-75\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Diet & Exercise Screening Data — risk_diet_exercise","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"function returns data frame diet exercise risk State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"","code":"risk_diet_exercise(diet_exercise, race, sex)"},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"diet_exercise One following values: \"bmi healthy, ages 20+\" \"bmi obese, ages 20+\" \"bmi obese, high school survey\" \"bmi overweight, high school survey\" \"consumed 1 fruits per day\" \"consumed 1 vegetables per day\" \"leisure time physical activity\". race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"data frame following columns: Area Type, Area Code, Percent, Lower 95% CI, Upper 95% CI, Number Respondents.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_diet_exercise.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Diet & Exercise Screening Data — risk_diet_exercise","text":"","code":"if (FALSE) { risk_diet_exercise(   diet_exercise = \"bmi is healthy, ages 20+\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\" ) risk_diet_exercise(   diet_exercise = \"bmi is obese, high school survey\",   race = \"all races (includes hispanic)\",   sex = \"males\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Smoking Data — risk_smoking","title":"Access to Smoking Data — risk_smoking","text":"function returns data frame smoking risks State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Smoking Data — risk_smoking","text":"","code":"risk_smoking(smoking, race = NULL, sex = NULL, datatype = NULL, area = NULL)"},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Smoking Data — risk_smoking","text":"smoking permissible values \"smoking laws ()\" \"smoking laws (bars)\" \"smoking laws (restaurants)\" \"smoking laws (workplace)\" \"smoking laws (workplace; restaurant; & bar)\" \"smokers (stopped 1 day longer)\" \"smoking allowed work (people)\" \"smoking allowed home (people)\" \"smoking allowed work (current smokers)\" \"smoking allowed work (former/never smokers)\" \"smoking allowed home (current smokers)\" \"smoking allowed home (former/never smokers)\" \"former smoker; ages 18+\" \"former smoker, quit 1 year+; ages 18+\" \"smokers (ever); ages 18+\" \"e-cigarette use; ages 18+\" \"smokers (current); ages 18+\". race One following values: \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". sex One following values: \"sexes\" \"male\" \"female\". datatype One following values: \"direct estimates\" \"county level modeled estimates\". area state/territory abbreviation USA.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Smoking Data — risk_smoking","text":"data frame following columns: Area Type, Area Code, Percent, Lower CI 95%, Upper CI 95%, Number Respondents.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Access to Smoking Data — risk_smoking","text":"Please note function requires specific arguments smoking type.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_smoking.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Smoking Data — risk_smoking","text":"","code":"if (FALSE) { risk_smoking(smoking = \"smoking laws (any)\")  risk_smoking(   smoking = \"smokers (stopped for 1 day or longer)\",   sex = \"both sexes\",   datatype = \"county level modeled estimates\",   area = \"wa\" )  risk_smoking(   smoking = \"smoking not allowed at work (current smokers)\",   sex = \"both sexes\",   datatype = \"direct estimates\" )  risk_smoking(   smoking = \"smokers (current); ages 18+\",   race = \"all races (includes hispanic)\",   sex = \"both sexes\",   datatype = \"county level modeled estimates\",   area = \"wa\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Vaccines Data — risk_vaccines","title":"Access to Vaccines Data — risk_vaccines","text":"function returns data frame vaccines risks State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Vaccines Data — risk_vaccines","text":"","code":"risk_vaccines(vaccine, sex)"},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Vaccines Data — risk_vaccines","text":"vaccine One following values: \"percent date hpv vaccination coverage, ages 13-15\", \"percent date hpv vaccination coverage, ages 13-17\". sex One following values: \"sexes\" \"male\" \"female\".","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Vaccines Data — risk_vaccines","text":"data frame following columns: Area Type, Area Code, Percent, Lower 95% CI, Upper 95% CI, Number Respondents.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_vaccines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Vaccines Data — risk_vaccines","text":"","code":"if (FALSE) { risk_vaccines(   vaccine = \"percent with up to date hpv vaccination coverage, ages 13-15\",   sex = \"both sexes\" )  risk_vaccines(   vaccine = \"percent with up to date hpv vaccination coverage, ages 13-17\",   sex = \"females\" ) }"},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":null,"dir":"Reference","previous_headings":"","what":"Access to Women's Health Data — risk_women_health","title":"Access to Women's Health Data — risk_women_health","text":"function returns data frame women's health risks State Cancer Profiles.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access to Women's Health Data — risk_women_health","text":"","code":"risk_women_health(   women_health,   race,   datatype = \"direct estimates\",   area = NULL )"},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Access to Women's Health Data — risk_women_health","text":"women_health One following values: \"mammogram past 2 years, ages 50-74\" \"mammogram past 2 years, ages 40+\" \"pap smear past 3 years, hysterectomy, ages 21-65\". race One following values \"Races (includes Hispanic)\" \"White (non-Hispanic)\" \"Black (non-Hispanic)\" \"American Indian / Alaska Native (non-Hispanic)\" \"Asian / Pacific Islander (non-Hispanic)\" \"Hispanic (Race)\". datatype One following values: \"direct estimates\" \"county level modeled estimates\". area state/territory abbreviation USA.","code":""},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Access to Women's Health Data — risk_women_health","text":"data frame following columns: Area Type, Area Code, Percent, People Unemployed, Rank.","code":""},{"path":[]},{"path":"http://getwilds.org/cancerprof/reference/risk_women_health.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Access to Women's Health Data — risk_women_health","text":"","code":"if (FALSE) { risk_women_health(   women_health = \"mammogram in past 2 years, ages 50-74\",   race = \"all races (includes hispanic)\",   datatype = \"direct estimates\" )  risk_women_health(   women_health = \"pap smear in past 3 years, no hysterectomy, ages 21-65\",   race = \"all races (includes hispanic)\",   datatype = \"county level modeled estimates\",   area = \"wa\" )  risk_women_health(   women_health = \"pap smear in past 3 years, no hysteroetomy, ages 21-65\",   race = \"black (non-hispanic)\" ) }"}]