Merge pull request #74 from getwilds/test

Test
getwilds · Mar 15, 2024 · 91dd098 · 91dd098
2 parents bf44abe + 6a1c190
commit 91dd098
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,10 +1,10 @@
 Package: cancerprof
-Title: Open Cancer Informatics
+Title: API Client for State Cancer Profiles
 Version: 0.0.0.9000
 Authors@R: 
     person("Brian", "Park", , "joon.brianpark@gmail.com", role = c("aut", "cre"),
            comment = c(ORCID = "YOUR-ORCID-ID"))
-Description: What the package does (one paragraph).
+Description: An API Client for accessing data from State Cancer Profiles for programmable analysis.
 License: MIT + file LICENSE
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)

diff --git a/NAMESPACE b/NAMESPACE
@@ -23,6 +23,7 @@ export(risk_women_health)
 importFrom(cdlTools,fips)
 importFrom(cli,cli_abort)
 importFrom(dplyr,across)
+importFrom(dplyr,all_of)
 importFrom(dplyr,filter)
 importFrom(dplyr,mutate)
 importFrom(dplyr,mutate_all)

diff --git a/R/demo-crowding.R b/R/demo-crowding.R
@@ -35,7 +35,7 @@
 #' \dontrun{
 #' demo_crowding(
 #'   area = "WA",
-#'   areatype = "hsa",
+#'   areatype = "county",
 #'   crowding = "household with >1 person per room",
 #'   race = "All Races (includes Hispanic)"
 #' )
@@ -74,19 +74,13 @@ demo_crowding <- function(area, areatype, crowding, race) {
 
   resp <- process_resp(resp, "demographics")
 
-  areatype_map <- c(
-    "county" = "County", "hsa" = "Health_Service_Area",
-    "state" = "State"
-  )
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-
-  areatype_title <- areatype_map[areatype]
-  areacode_title <- areacode_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   resp %>%
     setNames(c(
-      areatype_title,
-      areacode_title,
+      area_type,
+      area_code,
       "Percent",
       "Households",
       "Rank"

diff --git a/R/demo-education.R b/R/demo-education.R
@@ -96,21 +96,14 @@ demo_education <- function(area, areatype, education, sex = NULL, race = NULL) {
     req_perform()
 
   resp <- process_resp(resp, "demographics")
-
-  areatype_map <- c(
-    "county" = "County",
-    "hsa" = "Health_Service_Area",
-    "state" = "State"
-  )
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-
-  areatype_title <- areatype_map[areatype]
-  areacode_title <- areacode_map[areatype]
+
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   resp %>%
     setNames(c(
-      areatype_title,
-      areacode_title,
+      area_type,
+      area_code,
       "Percent",
       "Households",
       "Rank"

diff --git a/R/demo-food-access.R b/R/demo-food-access.R
@@ -77,19 +77,18 @@ demo_food <- function(area, areatype, food, race = NULL) {
   resp <- req_draft %>%
     req_perform()
 
-  resp <- process_resp(resp, "demographics") %>%
-    mutate(Value..Percent. = as.integer(Value..Percent.))
+  resp <- process_resp(resp, "demographics")
 
-  areatype_map <- c("county" = "County", "state" = "State")
-  areatype_title <- areatype_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   if (food == "limited access to healthy food") {
     resp %>%
-      setNames(c(areatype_title, "FIPS", "Percent", "People")) %>% 
+      setNames(c(area_type, area_code, "Percent", "People")) %>% 
       mutate(across(c("Percent", "People"), \(x) as.numeric(x)))
   } else if (food == "food insecurity") {
     resp %>%
-      setNames(c(areatype_title, "FIPS", "Percent")) %>% 
+      setNames(c(area_type, area_code, "Percent")) %>% 
       mutate(across(c("Percent"), \(x) as.numeric(x)))
   }
 }
diff --git a/R/demo-income.R b/R/demo-income.R
@@ -66,13 +66,12 @@ demo_income <- function(area, areatype, income, race) {
     ) %>%
     req_perform()
 
-  resp <- process_resp(resp, "demographics") %>%
-    mutate(Value..Dollars. = as.integer(Value..Dollars.))
+  resp <- process_resp(resp, "demographics")
 
-  areatype_map <- c("county" = "County", "state" = "State")
-  areatype_title <- areatype_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   resp %>%
-    setNames(c(areatype_title, "FIPS", "Dollars", "Rank")) %>% 
+    setNames(c(area_type, area_code, "Dollars", "Rank")) %>% 
     mutate(across(c("Dollars"), \(x) as.numeric(x)))
 }
diff --git a/R/demo-insurance.R b/R/demo-insurance.R
@@ -132,17 +132,10 @@ demo_insurance <- function(area, areatype, insurance, sex, age, race = NULL) {
 
   resp <- process_resp(resp, "demographics")
 
-  areatype_map <- c(
-    "county" = "County",
-    "hsa" = "Health_Service_Area",
-    "state" = "State"
-  )
-  areatype_title <- areatype_map[areatype]
-
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-  areacode_title <- areacode_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   resp %>%
-    setNames(c(areatype_title, areacode_title, "Percent", "People", "Rank")) %>% 
+    setNames(c(area_type, area_code, "Percent", "People", "Rank")) %>% 
     mutate(across(c("Percent", "People"), \(x) as.numeric(x)))
 }
diff --git a/R/demo-mobility.R b/R/demo-mobility.R
@@ -64,20 +64,13 @@ demo_mobility <- function(area, areatype, mobility) {
 
   resp <- process_resp(resp, "demographics")
 
-  areatype_map <- c(
-    "county" = "County",
-    "hsa" = "Health_Service_Area",
-    "state" = "State"
-  )
-  areatype_title <- areatype_map[areatype]
-
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-  areacode_title <- areacode_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   resp %>%
     setNames(c(
-      areatype_title,
-      areacode_title,
+      area_type,
+      area_code,
       "Percent",
       "People",
       "Rank"

diff --git a/R/demo-non-english-language.R b/R/demo-non-english-language.R
@@ -58,21 +58,13 @@ demo_language <- function(area, areatype, language) {
 
   resp <- process_resp(resp, "demographics")
 
-  areatype_map <- c(
-    "county" = "County",
-    "hsa" = "Health_Service_Area",
-    "state" = "State"
-  )
-
-  areatype_title <- areatype_map[areatype]
-
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-  areacode_title <- areacode_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   resp %>%
     setNames(c(
-      areatype_title,
-      areacode_title,
+      area_type,
+      area_code,
       "Percent",
       "Households",
       "Rank"

diff --git a/R/demo-population.R b/R/demo-population.R
@@ -120,20 +120,13 @@ demo_population <- function(area, areatype, population, race = NULL, sex = NULL)
 
   resp <- process_resp(resp, "demographics")
 
-  areatype_map <- c(
-    "county" = "County",
-    "hsa" = "Health_Service_Area",
-    "state" = "State"
-  )
-  areatype_title <- areatype_map[areatype]
-
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-  areacode_title <- areacode_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   resp %>%
     setNames(c(
-      areatype_title,
-      areacode_title,
+      area_type,
+      area_code,
       "Percent",
       "People",
       "Rank"

diff --git a/R/demo-poverty.R b/R/demo-poverty.R
@@ -101,28 +101,21 @@ demo_poverty <- function(area, areatype, poverty, race = NULL, sex = NULL) {
 
   resp <- process_resp(resp, "demographics")
 
-  areatype_map <- c(
-    "county" = "County",
-    "hsa" = "Health_Service_Area",
-    "state" = "State"
-  )
-  areatype_title <- areatype_map[areatype]
-
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-  areacode_title <- areacode_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   if (poverty == "persistent poverty") {
     resp %>%
       setNames(c(
-        areatype_title,
-        areacode_title,
+        area_type,
+        area_code,
         "Persistent Poverty"
       ))
   } else {
     resp %>%
       setNames(c(
-        areatype_title,
-        areacode_title,
+        area_type,
+        area_code,
         "Percent",
         "People",
         "Rank"

diff --git a/R/demo-workforce.R b/R/demo-workforce.R
@@ -79,20 +79,13 @@ demo_workforce <- function(area, areatype, workforce, race, sex) {
 
   resp <- process_resp(resp, "demographics")
 
-  areatype_map <- c(
-    "county" = "County",
-    "hsa" = "Health_Service_Area",
-    "state" = "State"
-  )
-  areatype_title <- areatype_map[areatype]
-
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-  areacode_title <- areacode_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   resp %>%
     setNames(c(
-      areatype_title,
-      areacode_title,
+      area_type,
+      area_code,
       "Percent",
       "People_Unemployed",
       "Rank"

diff --git a/R/incidence-cancer.R b/R/incidence-cancer.R
@@ -61,7 +61,7 @@
 #' @importFrom httr2 req_url_query req_perform
 #' @importFrom cli cli_abort
 #' @importFrom stats setNames
-#' @importFrom dplyr mutate across
+#' @importFrom dplyr mutate across all_of
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Age Adjusted Incidence Rate, Lower 95% CI,
@@ -174,17 +174,9 @@ incidence_cancer <- function(area, areatype, cancer, race, sex, age, stage, year
     req_perform()
 
   resp <- process_resp(resp, "incidence")
-
-
-  areatype_map <- c(
-    "county" = "County",
-    "hsa" = "Health Service Area",
-    "state" = "State"
-  )
-  areatype_title <- areatype_map[areatype]
-
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-  areacode_title <- areacode_map[areatype]
+
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   shared_names_to_numeric <- c(
     "Age_Adjusted_Incidence_Rate",
@@ -198,8 +190,8 @@ incidence_cancer <- function(area, areatype, cancer, race, sex, age, stage, year
   if (stage == "all stages") {
     resp %>%
       setNames(c(
-        areatype_title,
-        areacode_title,
+        area_type,
+        area_code,
         shared_names_to_numeric,
         "Annual_Average_Count",
         "Recent_Trend",
@@ -208,22 +200,22 @@ incidence_cancer <- function(area, areatype, cancer, race, sex, age, stage, year
         "Trend_Upper_95%_CI"
       )) %>% 
       mutate(across(c(
-        shared_names_to_numeric,
+        all_of(shared_names_to_numeric),
         "Recent_5_Year_Trend",
         "Trend_Lower_95%_CI",
         "Trend_Upper_95%_CI"
       ), \(x) as.numeric(x)))
   } else if (stage == "late stage (regional & distant)") {
     resp %>%
       setNames(c(
-        areatype_title,
-        areacode_title,
+        area_type,
+        area_code,
         shared_names_to_numeric,
         "Annual_Average_Count",
         "Percentage_of_Cases_with_Late_Stage"
       )) %>% 
       mutate(across(c(
-        shared_names_to_numeric,
+        all_of(shared_names_to_numeric),
         "Percentage_of_Cases_with_Late_Stage"
       ), \(x) as.numeric(x)))
   }

diff --git a/R/mortality-cancer.R b/R/mortality-cancer.R
@@ -56,7 +56,7 @@
 #' @importFrom httr2 req_url_query req_perform
 #' @importFrom cli cli_abort
 #' @importFrom stats setNames
-#' @importFrom dplyr mutate across
+#' @importFrom dplyr mutate across all_of
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Met Healthy People Objective of ***?,
@@ -154,15 +154,8 @@ mortality_cancer <- function(area, areatype, cancer, race, sex, age, year) {
 
   resp <- process_resp(resp, "mortality")
 
-  areatype_map <- c(
-    "county" = "County",
-    "hsa" = "Health_Service_Area",
-    "state" = "State"
-  )
-  areatype_title <- areatype_map[areatype]
-
-  areacode_map <- c("county" = "FIPS", "state" = "FIPS", "hsa" = "HSA_Code")
-  areacode_title <- areacode_map[areatype]
+  area_type <- get_area(areatype)[1]
+  area_code <- get_area(areatype)[2]
 
   names_to_numeric <- c(
     "Age_Adjusted_Death_Rate",
@@ -175,8 +168,8 @@ mortality_cancer <- function(area, areatype, cancer, race, sex, age, year) {
 
   resp %>%
     setNames(c(
-      areatype_title,
-      areacode_title,
+      area_type,
+      area_code,
       "Met Healthy People Objective of ***?",
       "Age_Adjusted_Death_Rate",
       "Lower_95%_CI_Rate",
@@ -191,7 +184,7 @@ mortality_cancer <- function(area, areatype, cancer, race, sex, age, year) {
       "Upper_95%_CI_Trend"
     )) %>% 
     mutate(across(c(
-      names_to_numeric,
+      all_of(names_to_numeric),
       "Recent_5_Year_Trend",
       "Lower_95%_CI_Trend",
       "Upper_95%_CI_Trend"