Avoid superseded tidyselect::one_of() and use tidyselect::all_of()

rstudio · Nov 26, 2024 · a85658b · a85658b
1 parent 66c42d6
commit a85658b
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Showing 5 changed files with 10 additions and 14 deletions.
diff --git a/R/get_sundered_data.R b/R/get_sundered_data.R
@@ -382,13 +382,13 @@ get_sundered_data <- function(
       tbl_check_join <- 
         tbl_check_join %>%
         dplyr::select(
-          dplyr::one_of(by_cols), dplyr::starts_with("pb_is_good_")
+          dplyr::all_of(by_cols), dplyr::starts_with("pb_is_good_")
         ) %>%
         dplyr::left_join(
           tbl_check_join_r %>%
             dplyr::rename(!!new_col_ii := pb_is_good_) %>%
             dplyr::select(
-              dplyr::one_of(by_cols), dplyr::starts_with("pb_is_good_")
+              dplyr::all_of(by_cols), dplyr::starts_with("pb_is_good_")
             ),
           by = by_cols
         ) %>%
@@ -425,7 +425,7 @@ get_sundered_data <- function(
   tbl_check_join <- 
     tbl_check_join %>%
     dplyr::mutate(pb_is_good_ = !!rlang::parse_expr(columns_str_add)) %>%
-    dplyr::select(-dplyr::one_of(columns_str_vec)) %>%
+    dplyr::select(-dplyr::all_of(columns_str_vec)) %>%
     dplyr::mutate(pb_is_good_ = dplyr::case_when(
       pb_is_good_ == validation_n ~ TRUE,
       TRUE ~ FALSE

diff --git a/R/interrogate.R b/R/interrogate.R
@@ -426,7 +426,7 @@ interrogate <- function(
 
         tbl_checked %>%
           dplyr::mutate(pb_is_good_ = !!rlang::parse_expr(columns_str_add)) %>%
-          dplyr::select(-dplyr::one_of(columns_str_vec)) %>%
+          dplyr::select(-dplyr::all_of(columns_str_vec)) %>%
           dplyr::mutate(pb_is_good_ = dplyr::case_when(
             pb_is_good_ == validation_n ~ TRUE,
             TRUE ~ FALSE

diff --git a/R/scan_data.R b/R/scan_data.R
@@ -1301,7 +1301,7 @@ probe_interactions <- function(data) {
       columns_char, FUN.VALUE = integer(1), USE.NAMES = FALSE,
       FUN = function(x) {
         data %>%
-          dplyr::select(dplyr::one_of(x)) %>%
+          dplyr::select(dplyr::all_of(x)) %>%
           dplyr::distinct() %>%
           dplyr::count() %>%
           dplyr::pull(n)
@@ -1317,7 +1317,7 @@ probe_interactions <- function(data) {
   # Create a ggplot2 plot matrix with the data
   plot_matrix <-
     data %>%
-    dplyr::select(dplyr::one_of(col_names)) %>%
+    dplyr::select(dplyr::all_of(col_names)) %>%
     ggplot2::ggplot(ggplot2::aes(x = .panel_x, y = .panel_y)) + 
     ggplot2::geom_point(alpha = 0.50, shape = 16, size = 1) + 
     ggforce::geom_autodensity() +
@@ -1388,7 +1388,7 @@ probe_correlations <- function(data) {
     )
   }
 
-  data_corr <- dplyr::select(data, dplyr::one_of(columns_numeric))
+  data_corr <- dplyr::select(data, dplyr::all_of(columns_numeric))
 
   corr_pearson <- 
     stats::cor(data_corr, method = "pearson", use = "pairwise.complete.obs")

diff --git a/R/tbl_from_db.R b/R/tbl_from_db.R
@@ -513,8 +513,6 @@ db_tbl <- function(
   x
 }
 
-# nolint start
-
 RPostgres_driver <- function() {
   rlang::check_installed("RPostgres", "to access a PostgreSQL table.")
   RPostgres::Postgres()
@@ -540,8 +538,6 @@ RSQLite_driver <- function() {
   RSQLite::SQLite()
 }
 
-# nolint end
-
 unknown_driver <- function() {
 
     stop(

diff --git a/R/utils-profiling.R b/R/utils-profiling.R
@@ -384,7 +384,7 @@ get_tbl_dbi_missing_tbl <- function(data) {
 
               missing_n_span <- 
                 data %>% 
-                dplyr::select(1, dplyr::one_of(x__))
+                dplyr::select(1, dplyr::all_of(x__))
 
               if (ncol(missing_n_span) == 1) {
 
@@ -460,7 +460,7 @@ get_tbl_df_missing_tbl <- function(data) {
       col_names,
       FUN = function(x__) {
 
-        data <- dplyr::select(data, dplyr::one_of(x__))
+        data <- dplyr::select(data, dplyr::all_of(x__))
         data <- tibble::rowid_to_column(data)
         data <- 
           dplyr::mutate(data, `::cut_group::` = dplyr::case_when(
@@ -524,7 +524,7 @@ get_missing_by_column_tbl <- function(data) {
       col_names,
       FUN = function(x__) {
 
-        data <- dplyr::select(data, dplyr::one_of(x__))
+        data <- dplyr::select(data, dplyr::all_of(x__))
         data <- dplyr::group_by(data)
         data <- 
           dplyr::summarize_all(