more linting and triple zeros

getwilds · Mar 7, 2024 · 3b58631 · 3b58631
1 parent cc4ffd1
commit 3b58631
Show file tree

Hide file tree

Showing 39 changed files with 772 additions and 241 deletions.
diff --git a/R/demo-education.R b/R/demo-education.R
@@ -95,7 +95,11 @@ demo_education <- function(area, areatype, education, sex = NULL, race = NULL) {
 
   resp <- process_response(resp)
 
-  areatype_map <- c("county" = "County", "hsa" = "Health_Service_Area", "state" = "State")
+  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]

diff --git a/R/demo-insurance.R b/R/demo-insurance.R
@@ -1,6 +1,7 @@
 #' Access to Insurance Data
 #'
-#' This function returns a data frame about insurance demographics from State Cancer Profiles.
+#' This function returns a data frame about insurance demographics
+#' from State Cancer Profiles.
 #'
 #' @param area A state/territory abbreviation or USA.
 #' @param areatype One of the following values:
@@ -24,15 +25,17 @@
 #' - `"both sexes"`
 #' - `"male"`
 #' - `"female"`.
-#' @param age If you specified `"both sexes"` for `sex` choose one of the following values:
+#' @param age If you specified `"both sexes"` for `sex`
+#' choose one of the following values:
 #' - `"under 19 years"`
 #' - `"18 to 64 years"`
 #' - `"21 to 64 years"`
 #' - `"40 to 64 years"`
 #' - `"50 to 64 years"`
 #' - `"under 65 years"`.
 #'
-#' Otherwise if you specified `"male"` or `"female"` for `sex`, choose one of the following values:
+#' Otherwise if you specified `"male"` or `"female"` for `sex`,
+#' choose one of the following values:
 #' - `"18 to 64 years"`
 #' - `"40 to 64 years"`
 #' - `"50 to 64 years"`
@@ -48,7 +51,8 @@
 #' @importFrom httr2 req_url_query req_perform
 #' @importFrom cli cli_abort
 #'
-#' @returns A data frame with the following columns: Area Type, Area Code, Percent, People, Rank.
+#' @returns A data frame with the following columns:
+#' Area Type, Area Code, Percent, People, Rank.
 #'
 #' @export
 #'
@@ -125,7 +129,11 @@ demo_insurance <- function(area, areatype, insurance, sex, age, race = NULL) {
 
   resp <- process_response(resp)
 
-  areatype_map <- c("county" = "County", "hsa" = "Health_Service_Area", "state" = "State")
+  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")

diff --git a/R/incidence-cancer.R b/R/incidence-cancer.R
@@ -1,6 +1,7 @@
 #' Access to Cancer Incident Data
 #'
-#' This function returns a data frame about cancer incidence from State Cancer Profiles.
+#' This function returns a data frame about cancer incidence
+#' from State Cancer Profiles.
 #'
 #' @param area A state/territory abbreviation or USA.
 #' @param areatype One of the following values:
@@ -57,9 +58,10 @@
 #' - `"latest 5 year average"`
 #' - `"latest single year (us by state)"`.
 #'
-#' @returns A data frame with the 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.
+#' @returns A data frame with the 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.
 #'
 #' @export
 #'
@@ -100,13 +102,24 @@
 #' }
 incidence_cancer <- function(area, areatype, cancer, race, sex, age, stage, year) {
   allstage_cancer <- c(
-    "all cancer sites", "breast (female in situ)", "childhood (ages <15, all sites)",
-    "childhood (ages <20, all sites)", "leukemia"
+    "all cancer sites",
+    "breast (female in situ)",
+    "childhood (ages <15, all sites)",
+    "childhood (ages <20, all sites)",
+    "leukemia"
   )
 
-  female_cancer <- c("breast (female)", "breast (female in situ)", "ovary", "uterus (corpus & uterus, nos)")
+  female_cancer <- c(
+    "breast (female)",
+    "breast (female in situ)",
+    "ovary",
+    "uterus (corpus & uterus, nos)"
+  )
 
-  childhood_cancer <- c("childhood (ages <15, all sites)", "childhood (ages <20, all sites)")
+  childhood_cancer <- c(
+    "childhood (ages <15, all sites)",
+    "childhood (ages <20, all sites)"
+  )
 
   if ((areatype == "county" || areatype == "hsa") && year == "latest single year (us by state)") {
     cli_abort("For year latest single year (us by state), areatype must be state")
@@ -158,17 +171,45 @@ incidence_cancer <- function(area, areatype, cancer, race, sex, age, stage, year
   resp <- process_incidence(resp)
 
 
-  areatype_map <- c("county" = "County", "hsa" = "Health Service Area", "state" = "State")
+  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]
 
   if (stage == "all stages") {
     resp %>%
-      setNames(c(areatype_title, areacode_title, "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"))
+      setNames(c(
+        areatype_title,
+        areacode_title,
+        "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"
+      ))
   } else if (stage == "late stage (regional & distant)") {
     resp %>%
-      setNames(c(areatype_title, areacode_title, "Age Adjusted Incidence Rate", "Lower 95% CI", "Upper 95% CI", "CI Rank", "Lower CI Rank", "Upper CI Rank", "Annual Average Count", "Percentage of Cases with Late Stage"))
+      setNames(c(
+        areatype_title,
+        areacode_title,
+        "Age Adjusted Incidence Rate",
+        "Lower 95% CI",
+        "Upper 95% CI",
+        "CI Rank",
+        "Lower CI Rank",
+        "Upper CI Rank",
+        "Annual Average Count",
+        "Percentage of Cases with Late Stage"
+      ))
   }
 }
diff --git a/R/mortality-cancer.R b/R/mortality-cancer.R
@@ -1,6 +1,7 @@
 #' Access to Cancer Mortality Data
 #'
-#' This function returns a data frame about cancer mortality from State Cancer Profiles.
+#' This function returns a data frame about cancer mortality
+#' from State Cancer Profiles.
 #'
 #' @param area A state/territory abbreviation or USA.
 #' @param areatype One of the following values:
@@ -52,10 +53,11 @@
 #' - `"latest 5 year average"`
 #' - `"latest single year (us by state)"`.
 #'
-#' @returns A data frame with the following columns: Area Type, Area Code, Met Healthy People Objective of ***?,
-#'          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.
+#' @returns A data frame with the following columns:
+#' Area Type, Area Code, Met Healthy People Objective of ***?,
+#' 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.
 #'
 #' @export
 #'
@@ -92,9 +94,16 @@
 #' )
 #' }
 mortality_cancer <- function(area, areatype, cancer, race, sex, age, year) {
-  female_cancer <- c("breast (female)", "ovary", "uterus (corpus & uterus, nos)")
+  female_cancer <- c(
+    "breast (female)",
+    "ovary",
+    "uterus (corpus & uterus, nos)"
+  )
 
-  childhood_cancer <- c("childhood (ages <15, all sites)", "childhood (ages <20, all sites)")
+  childhood_cancer <- c(
+    "childhood (ages <15, all sites)",
+    "childhood (ages <20, all sites)"
+  )
 
   if ((areatype == "county" || areatype == "hsa") && year == "latest single year (us by state)") {
     cli_abort("For year latest single year (us by state), areatype must be state")
@@ -140,16 +149,31 @@ mortality_cancer <- function(area, areatype, cancer, race, sex, age, year) {
 
   resp <- process_mortality(resp)
 
-  areatype_map <- c("county" = "County", "hsa" = "Health_Service_Area", "state" = "State")
+  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]
 
   resp %>%
     setNames(c(
-      areatype_title, areacode_title, "Met Healthy People Objective of ***?", "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"
+      areatype_title,
+      areacode_title,
+      "Met Healthy People Objective of ***?",
+      "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"
     ))
 }
diff --git a/R/risk-alcohol.R b/R/risk-alcohol.R
@@ -1,6 +1,7 @@
 #' Access to Alcohol Screening and Risk Data
 #'
-#' This function returns a data frame about alcohol risks from State Cancer Profiles.
+#' This function returns a data frame about alcohol risks
+#' from State Cancer Profiles.
 #'
 #' @param alcohol The only permissible value is
 #' `"binge drinking (4+ drinks on one occasion for women, 5+ drinks for one occasion for men), ages 21+"`.
@@ -16,7 +17,9 @@
 #' - `"male"`
 #' - `"female"`.
 #'
-#' @returns A data frame with the following columns: Area Type, Area Code, Percent, Lower 95% CI, Upper 95% CI, Number of Respondents.
+#' @returns A data frame with the following columns:
+#' Area Type, Area Code, Percent, Lower 95% CI,
+#' Upper 95% CI, Number of Respondents.
 #'
 #' @export
 #'
@@ -50,5 +53,12 @@ risk_alcohol <- function(alcohol, race, sex) {
   resp <- process_screening(resp)
 
   resp %>%
-    setNames(c("State", "FIPS", "Percent", "Lower_95%_CI", "Upper_95%_CI", "Number_of_Respondents"))
+    setNames(c(
+      "State",
+      "FIPS",
+      "Percent",
+      "Lower_95%_CI",
+      "Upper_95%_CI",
+      "Number_of_Respondents"
+    ))
 }
diff --git a/R/risk-colorectal-screening.R b/R/risk-colorectal-screening.R
@@ -97,9 +97,22 @@ risk_colorectal_screening <- function(screening, race = NULL, sex = NULL, area =
 
   if (screening %in% screening_type_1) {
     resp %>%
-      setNames(c("State", "FIPS", "Percent", "Lower_95%_CI", "Upper_95%_CI", "Number_of_Respondents"))
+      setNames(c(
+        "State",
+        "FIPS",
+        "Percent",
+        "Lower_95%_CI",
+        "Upper_95%_CI",
+        "Number_of_Respondents"
+      ))
   } else if (screening %in% screening_type_2) {
     resp %>%
-      setNames(c("County", "FIPS", "Model_Based_Percent (95%_Confidence_Interval)", "Lower_95%_CI", "Upper_95%_CI"))
+      setNames(c(
+        "County",
+        "FIPS",
+        "Model_Based_Percent (95%_Confidence_Interval)",
+        "Lower_95%_CI",
+        "Upper_95%_CI"
+      ))
   }
 }
diff --git a/R/risk-diet-exercise.R b/R/risk-diet-exercise.R
@@ -1,6 +1,7 @@
 #' Access to Diet & Exercise Screening Data
 #'
-#' This function returns a data frame about diet and exercise risk from State Cancer Profiles.
+#' This function returns a data frame about diet and exercise risk
+#' from State Cancer Profiles.
 #'
 #' @param diet_exercise One of the following values:
 #' - `"bmi is healthy, ages 20+"`
@@ -22,7 +23,9 @@
 #' - `"male"`
 #' - `"female"`.
 #'
-#' @returns A data frame with the following columns: Area Type, Area Code, Percent, Lower 95% CI, Upper 95% CI, Number of Respondents.
+#' @returns A data frame with the following columns:
+#' Area Type, Area Code, Percent,
+#' Lower 95% CI, Upper 95% CI, Number of Respondents.
 #'
 #' @export
 #'
@@ -64,9 +67,22 @@ risk_diet_exercise <- function(diet_exercise, race, sex) {
 
   if (diet_exercise %in% diet_exercise_type1) {
     resp %>%
-      setNames(c("State", "FIPS", "Percent", "Lower_95%_CI", "Upper_95%_CI"))
+      setNames(c(
+        "State",
+        "FIPS",
+        "Percent",
+        "Lower_95%_CI",
+        "Upper_95%_CI"
+      ))
   } else {
     resp %>%
-      setNames(c("State", "FIPS", "Percent", "Lower_95%_CI", "Upper_95%_CI", "Number_of_Respondents"))
+      setNames(c(
+        "State",
+        "FIPS",
+        "Percent",
+        "Lower_95%_CI",
+        "Upper_95%_CI",
+        "Number_of_Respondents"
+      ))
   }
 }
diff --git a/R/risk-smoking.R b/R/risk-smoking.R
@@ -208,13 +208,38 @@ risk_smoking <- function(smoking, race = NULL, sex = NULL, datatype = NULL, area
   if (smoking %in% smoking_group1) {
     resp %>%
       setNames(c("State", "FIPS", "Percent"))
-  } else if ((smoking %in% c(smoking_group2, smoking_group3, smoking_group4, smoking_group5, smoking_group6)) &&
+  } else if ((smoking %in% c(
+    smoking_group2,
+    smoking_group3,
+    smoking_group4,
+    smoking_group5,
+    smoking_group6
+  )) &&
     (datatype == "direct estimates")) {
     resp %>%
-      setNames(c("State", "FIPS", "Percent", "Lower_CI_95%", "Upper_CI_95%", "Number_of_Respondents"))
-  } else if ((smoking %in% c(smoking_group2, smoking_group3, smoking_group4, smoking_group5, smoking_group6) &&
+      setNames(c(
+        "State",
+        "FIPS",
+        "Percent",
+        "Lower_CI_95%",
+        "Upper_CI_95%",
+        "Number_of_Respondents"
+      ))
+  } else if ((smoking %in% c(
+    smoking_group2,
+    smoking_group3,
+    smoking_group4,
+    smoking_group5,
+    smoking_group6
+  ) &&
     datatype == "county level modeled estimates")) {
     resp %>%
-      setNames(c("County", "FIPS", "Percent", "Lower_CI_95%", "Upper_CI_95%"))
+      setNames(c(
+        "County",
+        "FIPS",
+        "Percent",
+        "Lower_CI_95%",
+        "Upper_CI_95%"
+      ))
   }
 }