Get tibble functions from dplyr

RichardMN · Nov 30, 2021 · 1c4ede0 · 1c4ede0
1 parent a499cc0
commit 1c4ede0
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Showing 24 changed files with 21 additions and 36 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -100,7 +100,6 @@ Imports:
     rlang,
     stringi,
     stringr,
-    tibble,
     tidyr (>= 1.0.0),
     tidyselect,
     vroom,

diff --git a/R/Belgium.R b/R/Belgium.R
@@ -57,13 +57,13 @@ Belgium <- R6::R6Class("Belgium",
     source_url = "https://epistat.wiv-isp.be/covid/",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble tribble
+    #' @importFrom dplyr tibble tribble
     set_region_codes = function() {
-      self$codes_lookup$`1` <- tibble::tibble(
+      self$codes_lookup$`1` <- tibble(
         level_1_region_code = c("BE-BRU", "BE-VLG", "BE-WAL"),
         level_1_region = c("Brussels", "Flanders", "Wallonia")
       )
-      self$codes_lookup$`2` <- tibble::tribble(
+      self$codes_lookup$`2` <- tribble(
         ~level_2_region_code, ~level_2_region, ~level_1_region_code,
         "BE-VAN", "Antwerpen", "BE-VLG",
         "BE-WBR", "BrabantWallon", "BE-WAL",
@@ -82,8 +82,7 @@ Belgium <- R6::R6Class("Belgium",
 
     #' @description Downloads data from source and (for Belgium)
     #' applies an initial data patch.
-    #' @importFrom dplyr select mutate filter bind_rows
-    #' @importFrom tibble tribble
+    #' @importFrom dplyr select mutate filter bind_rows tribble
     download = function() {
       # do the actual downloading using the parent download method
       super$download()
@@ -92,7 +91,7 @@ Belgium <- R6::R6Class("Belgium",
       # For now, we filter out the broken lines and replace them
       # with the following data shim
 
-      fixed_lines <- tibble::tribble(
+      fixed_lines <- tribble(
         ~DATE, ~PROVINCE, ~REGION, ~AGEGROUP, ~SEX, ~CASES,
         "2020-04-22", "Limburg", "Flanders", "50-59", "F", 10,
         "2021-02-17", "VlaamsBrabant", "Flanders", "10-19", "M", 12

diff --git a/R/Brazil.R b/R/Brazil.R
@@ -47,7 +47,7 @@ Brazil <- R6::R6Class("Brazil",
     source_url = "https://github.com/wcota/covid19br/blob/master/README.en.md",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tribble
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       self$codes_lookup <- tibble(
         state_name = c(

diff --git a/R/Canada.R b/R/Canada.R
@@ -44,7 +44,7 @@ Canada <- R6::R6Class("Canada",
     source_url = "https://open.canada.ca/data/en/dataset/261c32ab-4cfd-4f81-9dea-7b64065690dc", # nolint
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       canada_codes <- tibble(
         code = c(

diff --git a/R/Colombia.R b/R/Colombia.R
@@ -41,7 +41,6 @@ Colombia <- R6::R6Class("Colombia",
     source_url = "https://github.com/danielcs88/colombia_covid-19/",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
     #' @importFrom dplyr mutate
     set_region_codes = function() {
       self$codes_lookup$`1` <- covidregionaldata::colombia_codes

diff --git a/R/Cuba.R b/R/Cuba.R
@@ -42,7 +42,7 @@ Cuba <- R6::R6Class("Cuba",
 
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       self$codes_lookup$`1` <- tibble(
         code = c(

diff --git a/R/Estonia.R b/R/Estonia.R
@@ -43,7 +43,7 @@ Estonia <- R6::R6Class("Estonia",
 
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       self$codes_lookup$`1` <- tibble(
         code = c("EE-37",

diff --git a/R/France.R b/R/France.R
@@ -50,7 +50,6 @@ France <- R6::R6Class("France",
 
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
     #' @importFrom dplyr select
     set_region_codes = function() {
       self$codes_lookup$`1` <- france_codes %>%

diff --git a/R/Germany.R b/R/Germany.R
@@ -44,8 +44,7 @@ Germany <- R6::R6Class("Germany",
 
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
-    #' @importFrom dplyr mutate
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       self$codes_lookup$`1` <- tibble(
         code = c(

diff --git a/R/India.R b/R/India.R
@@ -37,7 +37,7 @@ India <- R6::R6Class("India",
     source_url = "https://www.covid19india.org",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       self$codes_lookup$`1` <- tibble(
         code = c(

diff --git a/R/Italy.R b/R/Italy.R
@@ -42,7 +42,7 @@ Italy <- R6::R6Class("Italy",
     source_url = "https://github.com/pcm-dpc/COVID-19/blob/master/README_EN.md",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       self$codes_lookup$`1` <- tibble(
         code = c(

diff --git a/R/JHU.R b/R/JHU.R
@@ -84,7 +84,6 @@ JHU <- R6::R6Class("JHU", # rename to country name
     source_url = "https://github.com/CSSEGISandData/COVID-19/",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
     set_region_codes = function() {
       self$codes_lookup$`1` <- JHU_codes
     },

diff --git a/R/Mexico.R b/R/Mexico.R
@@ -54,7 +54,6 @@ Mexico <- R6::R6Class("Mexico",
     source_url = "https://datos.covid-19.conacyt.mx",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
     #' @importFrom dplyr select
     set_region_codes = function() {
       self$codes_lookup$`1` <- covidregionaldata::mexico_codes %>%

diff --git a/R/Netherlands.R b/R/Netherlands.R
@@ -46,7 +46,6 @@ Netherlands <- R6::R6Class("Netherlands",
     source_url = "https://data.rivm.nl/covid-19/",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
     set_region_codes = function() {
 
     },

diff --git a/R/SouthAfrica.R b/R/SouthAfrica.R
@@ -41,7 +41,7 @@ SouthAfrica <- R6::R6Class("SouthAfrica",
     source_url = "https://github.com/dsfsi/covid19za",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       self$codes_lookup$`1` <- tibble(
         code = c(

diff --git a/R/Switzerland.R b/R/Switzerland.R
@@ -69,7 +69,7 @@ Switzerland <- R6::R6Class("Switzerland",
     source_url = "https://github.com/openZH/covid_19/",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       self$codes_lookup$`1` <- tibble(
         code = c(

diff --git a/R/UK.R b/R/UK.R
@@ -450,8 +450,7 @@ UK <- R6::R6Class("UK",
     #'     Section 2, "2. Estimated new hospital cases"
     #' @importFrom lubridate year month
     #' @importFrom readxl read_excel cell_limits
-    #' @importFrom tibble as_tibble
-    #' @importFrom dplyr mutate select %>% group_by summarise left_join
+    #' @importFrom dplyr mutate select %>% group_by summarise left_join as_tibble
     #' @importFrom tidyr pivot_longer
     #' @param clean_data Cleaned UK covid-19 data
     #' @param nhs_data NHS region data

diff --git a/R/USA.R b/R/USA.R
@@ -49,7 +49,7 @@ USA <- R6::R6Class("USA",
     source_url = "https://github.com/nytimes/covid-19-data",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tribble
+    #' @importFrom dplyr tibble
     set_region_codes = function() {
       self$codes_lookup <- usa_codes <- tibble(
         level_1_region_code = c(

diff --git a/R/Vietnam.R b/R/Vietnam.R
@@ -47,7 +47,6 @@ Vietnam <- R6::R6Class("Vietnam",
     source_url = "https://covid19.ncsc.gov.vn",
 
     #' @description Set up a table of region codes for clean data
-    #' @importFrom tibble tibble
     set_region_codes = function() {
       self$codes_lookup$`1` <- covidregionaldata::vietnam_codes
     },

diff --git a/R/get_available_datasets.R b/R/get_available_datasets.R
@@ -18,7 +18,6 @@
 #' @family interface
 #' @importFrom rlang .data
 #' @importFrom dplyr select bind_rows filter
-#' @importFrom tibble as_tibble
 #' @export
 #' @examples
 #' # see all available datasets

diff --git a/R/get_linelist.R b/R/get_linelist.R
@@ -24,7 +24,6 @@
 #' @importFrom lifecycle deprecate_warn
 #' @importFrom dplyr if_else select mutate filter
 #' @importFrom lubridate dmy
-#' @importFrom tibble as_tibble
 #' @importFrom utils download.file untar
 #' @examples
 #' \dontrun{

diff --git a/R/processing.R b/R/processing.R
@@ -7,7 +7,7 @@
 #' @return A tibble with relevant NA columns added
 #' @family compulsory_processing
 #' @concept compulsory_processing
-#' @importFrom tibble tibble add_column
+#' @importFrom dplyr mutate
 #' @importFrom rlang !!!
 add_extra_na_cols <- function(data) {
   expected_col_names <- c(
@@ -17,7 +17,7 @@ add_extra_na_cols <- function(data) {
 
   new_cols <- rep(list(NA_real_), length(expected_col_names))
   names(new_cols) <- expected_col_names
-  data <- add_column(
+  data <- mutate(
     data,
     !!!new_cols[!(names(new_cols) %in% names(data))]
   )
@@ -50,7 +50,6 @@ set_negative_values_to_zero <- function(data) {
 #' @return A tibble with rows of NAs added.
 #' @family compulsory_processing
 #' @concept compulsory_processing
-#' @importFrom tibble tibble
 #' @importFrom tidyr complete full_seq nesting
 #' @importFrom tidyselect starts_with
 #' @importFrom rlang !!! syms
@@ -103,7 +102,6 @@ complete_cumulative_columns <- function(data) {
 #' @importFrom purrr walk2
 #' @importFrom tidyr replace_na
 #' @importFrom tidyselect ends_with
-#' @importFrom tibble tibble
 #' @importFrom rlang !! :=
 calculate_columns_from_existing_data <- function(data) {
   possible_counts <- c("cases", "deaths", "hosp", "recovered", "tested")
@@ -150,7 +148,6 @@ calculate_columns_from_existing_data <- function(data) {
 #' @param data A data table
 #' @return A data table, totalled up
 #' @importFrom dplyr left_join group_by summarise select arrange
-#' @importFrom tibble tibble
 #' @family optional_processing
 #' @concept optional_processing
 totalise_data <- function(data) {

diff --git a/R/shared-methods.R b/R/shared-methods.R
@@ -505,7 +505,7 @@ DataClass <- R6::R6Class(
 
     #' @description Create a table of summary information for the data set
     #' being processed.
-    #' @importFrom tibble tibble
+    #' @importFrom dplyr tibble
     #' @return Returns a single row summary tibble containing the origin of the
     #' data source, class, level 1 and 2 region names, the type of data,
     #' the urls of the raw data and the columns present in the raw data.

diff --git a/R/utils.R b/R/utils.R
@@ -16,7 +16,7 @@ rlang::`.data`
 #' @return A data table
 #' @importFrom memoise memoise cache_filesystem
 #' @importFrom vroom vroom
-#' @importFrom tibble tibble
+#' @importFrom dplyr tibble
 #' @importFrom withr with_envvar
 #' @concept utility
 csv_reader <- function(file, verbose = FALSE, guess_max = 1000, ...) {
@@ -50,7 +50,7 @@ csv_reader <- function(file, verbose = FALSE, guess_max = 1000, ...) {
 #' @param ... extra parameters to be passed to jsonlite::fromJSON
 #' @inheritParams message_verbose
 #' @return A data table
-#' @importFrom tibble tibble
+#' @importFrom dplyr tibble
 #' @importFrom jsonlite fromJSON
 #' @concept utility
 json_reader <- function(file, verbose = FALSE, ...) {