Merge pull request #77 from getwilds/add-dot-lintr

Add dot lintr

.lintr

@@ -0,0 +1,4 @@
+linters: linters_with_defaults(
+    line_length_linter(120),
+    cyclocomp_linter(complexity_limit = 150)
+  )

R/demo-crowding.R

@@ -26,7 +26,7 @@
 #'
 #' @returns A data frame with the following columns: Area, Area Code,
 #' Percent, Households, Rank.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -55,7 +55,6 @@
 #' )
 #' }
 demo_crowding <- function(area, areatype, crowding, race) {
-
   req <- create_request("demographics")
 
   resp <- req %>%

R/demo-education.R

@@ -31,7 +31,7 @@
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Percent, Households, Rank.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -96,7 +96,7 @@ demo_education <- function(area, areatype, education, sex = NULL, race = NULL) {
     req_perform()
 
   resp <- process_resp(resp, "demographics")
-  
+
   area_type <- get_area(areatype)[1]
   area_code <- get_area(areatype)[2]
 
@@ -107,6 +107,6 @@ demo_education <- function(area, areatype, education, sex = NULL, race = NULL) {
       "Percent",
       "Households",
       "Rank"
-    )) %>% 
+    )) %>%
     mutate(across(c("Percent", "Households"), \(x) as.numeric(x)))
 }

R/demo-food-access.R

@@ -21,7 +21,7 @@
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Value, People.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -84,11 +84,11 @@ demo_food <- function(area, areatype, food, race = NULL) {
 
   if (food == "limited access to healthy food") {
     resp %>%
-      setNames(c(area_type, area_code, "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(area_type, area_code, "Percent")) %>% 
+      setNames(c(area_type, area_code, "Percent")) %>%
       mutate(across(c("Percent"), \(x) as.numeric(x)))
   }
 }

R/demo-income.R

@@ -21,7 +21,7 @@
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Dollars, Rank.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -72,6 +72,6 @@ demo_income <- function(area, areatype, income, race) {
   area_code <- get_area(areatype)[2]
 
   resp %>%
-    setNames(c(area_type, area_code, "Dollars", "Rank")) %>% 
+    setNames(c(area_type, area_code, "Dollars", "Rank")) %>%
     mutate(across(c("Dollars"), \(x) as.numeric(x)))
 }

R/demo-insurance.R

@@ -55,7 +55,7 @@
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Percent, People, Rank.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -136,6 +136,6 @@ demo_insurance <- function(area, areatype, insurance, sex, age, race = NULL) {
   area_code <- get_area(areatype)[2]
 
   resp %>%
-    setNames(c(area_type, area_code, "Percent", "People", "Rank")) %>% 
+    setNames(c(area_type, area_code, "Percent", "People", "Rank")) %>%
     mutate(across(c("Percent", "People"), \(x) as.numeric(x)))
 }

R/demo-mobility.R

@@ -21,7 +21,7 @@
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Percent, People, Rank.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -74,6 +74,6 @@ demo_mobility <- function(area, areatype, mobility) {
       "Percent",
       "People",
       "Rank"
-    )) %>% 
+    )) %>%
     mutate(across(c("Percent", "People"), \(x) as.numeric(x)))
 }

R/demo-non-english-language.R

@@ -17,7 +17,7 @@
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Percent, Households, Rank.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -68,6 +68,6 @@ demo_language <- function(area, areatype, language) {
       "Percent",
       "Households",
       "Rank"
-    )) %>% 
+    )) %>%
     mutate(across(c("Percent", "Households"), \(x) as.numeric(x)))
 }

R/demo-population.R

@@ -44,7 +44,7 @@
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Percent, Households, Rank.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -87,8 +87,8 @@ demo_population <- function(area, areatype, population, race = NULL, sex = NULL)
     cli_abort("for males, Race must not be NULL and Sex must be NULL")
   } else if (population == "foreign born" && (is.null(race) || is.null(sex))) {
     cli_abort("for foreign born, race and sex must not be NULL")
-  } else if ((population == "american indian/alaska native" || population == "asian/pacific islander" || population == "black" ||
-    population == "hispanic" || population == "non-hispanic (origin recode)" ||
+  } else if ((population == "american indian/alaska native" || population == "asian/pacific islander" || 
+              population == "black" || population == "hispanic" || population == "non-hispanic (origin recode)" ||
     population == "white") && (is.null(sex) || !is.null(race))) {
     cli_abort("for races other than foreign born, Sex must not be NULL and race must be NULL")
   }
@@ -117,7 +117,7 @@ demo_population <- function(area, areatype, population, race = NULL, sex = NULL)
 
   resp <- resp %>%
     req_perform()
-  
+
   resp <- process_resp(resp, "demographics")
 
   area_type <- get_area(areatype)[1]
@@ -130,6 +130,6 @@ demo_population <- function(area, areatype, population, race = NULL, sex = NULL)
       "Percent",
       "People",
       "Rank"
-    )) %>% 
+    )) %>%
     mutate(across(c("Percent", "People"), \(x) as.numeric(x)))
 }

R/demo-poverty.R

@@ -33,7 +33,7 @@
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Percent, Households, Rank.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -66,7 +66,8 @@ demo_poverty <- function(area, areatype, poverty, race = NULL, sex = NULL) {
   if (poverty == "persistent poverty" && (areatype == "hsa" || areatype == "state")) {
     cli_abort("For persistent poverty, areatype must be county")
   }
-  if ((poverty == "persistent poverty" || poverty == "persons < 150% of poverty") && (!is.null(race) || !is.null(sex))) {
+  if ((poverty == "persistent poverty" || poverty == "persons < 150% of poverty") &&
+        (!is.null(race) || !is.null(sex))) {
     cli_abort("for persistent poverty and persons < 150% of poverty, Race and Sex must be NULL")
   } else if ((poverty == "families below poverty") && (!is.null(sex) || is.null(race))) {
     cli_abort("for families below poverty, Sex must be NULL and Race must not be NULL")
@@ -119,7 +120,7 @@ demo_poverty <- function(area, areatype, poverty, race = NULL, sex = NULL) {
         "Percent",
         "People",
         "Rank"
-      )) %>% 
+      )) %>%
       mutate(across(c("Percent", "People"), \(x) as.numeric(x)))
   }
 }

R/demo-svi.R

@@ -16,7 +16,7 @@
 #' @importFrom dplyr mutate across
 #'
 #' @returns A data frame with the following columns: County, FIPS, Score.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -53,10 +53,10 @@ demo_svi <- function(area, svi) {
       output = 1
     ) %>%
     req_perform()
-  
+
   resp <- process_resp(resp, "demographics")
 
   resp %>%
-    setNames(c("County", "FIPS", "Score")) %>% 
+    setNames(c("County", "FIPS", "Score")) %>%
     mutate(across(c("Score"), \(x) as.numeric(x)))
 }

R/demo-workforce.R

@@ -28,7 +28,7 @@
 #'
 #' @returns A data frame with the following columns:
 #' Area Type, Area Code, Percent, People Unemployed, Rank.
-#' 
+#'
 #' @family demographics
 #'
 #' @export
@@ -89,6 +89,6 @@ demo_workforce <- function(area, areatype, workforce, race, sex) {
       "Percent",
       "People_Unemployed",
       "Rank"
-    )) %>% 
+    )) %>%
     mutate(across(c("Percent", "People_Unemployed"), \(x) as.numeric(x)))
 }

R/incidence-cancer.R

@@ -57,7 +57,7 @@
 #' @param year One of the following values:
 #' - `"latest 5 year average"`
 #' - `"latest single year (us by state)"`.
-#' 
+#'
 #' @importFrom httr2 req_url_query req_perform
 #' @importFrom cli cli_abort
 #' @importFrom stats setNames
@@ -174,7 +174,7 @@ incidence_cancer <- function(area, areatype, cancer, race, sex, age, stage, year
     req_perform()
 
   resp <- process_resp(resp, "incidence")
-  
+
   area_type <- get_area(areatype)[1]
   area_code <- get_area(areatype)[2]
 
@@ -198,7 +198,7 @@ incidence_cancer <- function(area, areatype, cancer, race, sex, age, stage, year
         "Recent_5_Year_Trend",
         "Trend_Lower_95%_CI",
         "Trend_Upper_95%_CI"
-      )) %>% 
+      )) %>%
       mutate(across(c(
         all_of(shared_names_to_numeric),
         "Recent_5_Year_Trend",
@@ -213,7 +213,7 @@ incidence_cancer <- function(area, areatype, cancer, race, sex, age, stage, year
         shared_names_to_numeric,
         "Annual_Average_Count",
         "Percentage_of_Cases_with_Late_Stage"
-      )) %>% 
+      )) %>%
       mutate(across(c(
         all_of(shared_names_to_numeric),
         "Percentage_of_Cases_with_Late_Stage"

R/mortality-cancer.R

@@ -52,7 +52,7 @@
 #' @param year One of the following values:
 #' - `"latest 5 year average"`
 #' - `"latest single year (us by state)"`.
-#' 
+#'
 #' @importFrom httr2 req_url_query req_perform
 #' @importFrom cli cli_abort
 #' @importFrom stats setNames
@@ -165,7 +165,7 @@ mortality_cancer <- function(area, areatype, cancer, race, sex, age, year) {
     "Lower_CI_Rank",
     "Upper_CI_Rank"
   )
-  
+
   resp %>%
     setNames(c(
       area_type,
@@ -182,7 +182,7 @@ mortality_cancer <- function(area, areatype, cancer, race, sex, age, year) {
       "Recent_5_Year_Trend",
       "Lower_95%_CI_Trend",
       "Upper_95%_CI_Trend"
-    )) %>% 
+    )) %>%
     mutate(across(c(
       all_of(names_to_numeric),
       "Recent_5_Year_Trend",

R/process-resp.R

@@ -8,7 +8,7 @@
 #' - "risks"
 #' - "incidence"
 #' - "mortality"
-#' 
+#'
 #' @importFrom httr2 resp_body_string
 #' @importFrom dplyr mutate_all na_if filter
 #' @importFrom rlang sym
@@ -24,23 +24,22 @@
 #' process_resp(resp, demographics)
 #' }
 process_resp <- function(resp, topic) {
-
   if (httr2::resp_content_type(resp) != "text/csv") {
     cli_abort("Invalid input, please check documentation for valid arguments.")
   }
- 
+
   nenv <- new.env()
   data("state", envir = nenv)
   state_name <- nenv$state.name
-  
+
   resp_lines <- resp %>%
     resp_body_string() %>%
     strsplit("\\n") %>%
     unlist()
-  
+
   if (topic == "demographics") {
     index_first_line_break <- which(resp_lines == "")[1]
-    index_second_line_break <- which(resp_lines == "")[2] 
+    index_second_line_break <- which(resp_lines == "")[2]
   } else if (topic == "risks") {
     index_first_line_break <- which(resp_lines == "")[3]
     index_second_line_break <- which(resp_lines == "")[4]
@@ -50,21 +49,20 @@ process_resp <- function(resp, topic) {
   } else {
     cli_abort("Incorrect topic argument, please ensure that correct.")
   }
-  
+
   resp <- resp_lines[
     (index_first_line_break + 1):
-      (index_second_line_break - 1)
+    (index_second_line_break - 1)
   ] %>%
     paste(collapse = "\n") %>%
     (
       \(x) {
         read.csv(textConnection(x),
-                 header = TRUE,
-                 colClasses = "character"
+          header = TRUE,
+          colClasses = "character"
         )
-      }
-    )()
-
+      })()
+
   column <- c(
     "Health.Service.Area",
     "County",
@@ -74,17 +72,17 @@ process_resp <- function(resp, topic) {
     "County",
     "State"
   ) %in% colnames(resp)]
-  
+
   resp <- resp %>%
     filter(!!sym(column) != "United States")
-  
+
   if (column %in% c("Health.Service.Area", "County")) {
     resp <- resp %>%
       filter(!(!!sym(column) %in% state_name))
   }
   resp %>%
-    mutate_all(stringr::str_trim) %>% 
+    mutate_all(stringr::str_trim) %>%
     mutate_all(\(x) na_if(x, "N/A")) %>%
-    mutate_all(\(x) na_if(x, "data not available")) %>% 
+    mutate_all(\(x) na_if(x, "data not available")) %>%
     mutate_all(\(x) na_if(x, "*"))
 }