Remove some aliases

NAMESPACE

@@ -272,6 +272,7 @@ export(distribution_coef_var)
 export(distribution_mode)
 export(empty_columns)
 export(empty_rows)
+export(extract_column_names)
 export(find_columns)
 export(format_text)
 export(get_columns)

NEWS.md

@@ -11,6 +11,12 @@ BREAKING CHANGES
   * `means_by_group()`
   * `rescale_weights()`
 
+* Following aliases are deprecated and will be removed in a future release (#504):
+
+  * `get_columns()`, use `data_select()` instead.
+  * `data_find()` and `find_columns()`, use `extract_column_names()` instead.
+  * `format_text()`, use `text_format()` instead.
+
 CHANGES
 
 * `recode_into()` is more relaxed regarding checking the type of `NA` values.

R/adjust.R

@@ -25,12 +25,12 @@
 #'   re-added. This avoids the centering around 0 that happens by default
 #'   when regressing out another variable (see the examples below for a
 #'   visual representation of this).
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #' @inheritParams standardize
 #'
 #' @return A data frame comparable to `data`, with adjusted variables.
 #'
 #' @examplesIf require("bayestestR", quietly = TRUE) && require("rstanarm", quietly = TRUE) && require("gamm4", quietly = TRUE)
 #' adjusted_all <- adjust(attitude)
 #' head(adjusted_all)
 #' adjusted_one <- adjust(attitude, effect = "complaints", select = "rating")

R/assign_labels.R

@@ -14,7 +14,7 @@
 #' `x`, the right-hand side (RHS) the associated value label. Non-matching
 #' labels are omitted.
 #' @param ... Currently not used.
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @inheritSection center Selection of variables - the `select` argument
 #'

R/categorize.R

@@ -45,7 +45,7 @@
 #'   variables are appended with new column names (using the defined suffix) to
 #'   the original data frame.
 #' @param ... not used.
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @inherit data_rename seealso
 #'

R/center.R

@@ -29,7 +29,7 @@
 #'   order, unless a named vector is given. In this case, names are matched
 #'   against the names of the selected variables.
 #' @param ... Currently not used.
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #' @inheritParams standardize
 #'
 #' @section Selection of variables - the `select` argument:
@@ -118,21 +118,21 @@ center.numeric <- function(x,
     center <- TRUE
   }
 
-  args <- .process_std_center(x, weights, robust, verbose, reference, center, scale = NULL)
+  my_args <- .process_std_center(x, weights, robust, verbose, reference, center, scale = NULL)
   dot_args <- list(...)
 
-  if (is.null(args)) {
+  if (is.null(my_args)) {
     # all NA?
     return(x)
-  } else if (is.null(args$check)) {
-    vals <- rep(0, length(args$vals)) # If only unique value
+  } else if (is.null(my_args$check)) {
+    vals <- rep(0, length(my_args$vals)) # If only unique value
   } else {
-    vals <- as.vector(args$vals - args$center)
+    vals <- as.vector(my_args$vals - my_args$center)
   }
 
-  centered_x <- rep(NA, length(args$valid_x))
-  centered_x[args$valid_x] <- vals
-  attr(centered_x, "center") <- args$center
+  centered_x <- rep(NA, length(my_args$valid_x))
+  centered_x[my_args$valid_x] <- vals
+  attr(centered_x, "center") <- my_args$center
   attr(centered_x, "scale") <- 1
   attr(centered_x, "robust") <- robust
   # labels
@@ -197,29 +197,29 @@ center.data.frame <- function(x,
   )
 
   # process arguments
-  args <- .process_std_args(x, select, exclude, weights, append,
+  my_args <- .process_std_args(x, select, exclude, weights, append,
     append_suffix = "_c", keep_factors = force, remove_na, reference,
     .center = center, .scale = NULL
   )
 
   # set new values
-  x <- args$x
+  x <- my_args$x
 
-  for (var in args$select) {
+  for (var in my_args$select) {
     x[[var]] <- center(
       x[[var]],
       robust = robust,
-      weights = args$weights,
+      weights = my_args$weights,
       verbose = FALSE,
       reference = reference[[var]],
-      center = args$center[var],
+      center = my_args$center[var],
       force = force,
       add_transform_class = FALSE
     )
   }
 
-  attr(x, "center") <- vapply(x[args$select], function(z) attributes(z)$center, numeric(1))
-  attr(x, "scale") <- vapply(x[args$select], function(z) attributes(z)$scale, numeric(1))
+  attr(x, "center") <- vapply(x[my_args$select], function(z) attributes(z)$center, numeric(1))
+  attr(x, "scale") <- vapply(x[my_args$select], function(z) attributes(z)$scale, numeric(1))
   attr(x, "robust") <- robust
   x
 }
@@ -249,19 +249,19 @@ center.grouped_df <- function(x,
     verbose = verbose
   )
 
-  args <- .process_grouped_df(
+  my_args <- .process_grouped_df(
     x, select, exclude, append,
     append_suffix = "_c",
     reference, weights, keep_factors = force
   )
 
-  for (rows in args$grps) {
-    args$x[rows, ] <- center(
-      args$x[rows, , drop = FALSE],
-      select = args$select,
+  for (rows in my_args$grps) {
+    my_args$x[rows, ] <- center(
+      my_args$x[rows, , drop = FALSE],
+      select = my_args$select,
       exclude = NULL,
       robust = robust,
-      weights = args$weights,
+      weights = my_args$weights,
       remove_na = remove_na,
       verbose = verbose,
       force = force,
@@ -272,8 +272,8 @@ center.grouped_df <- function(x,
     )
   }
   # set back class, so data frame still works with dplyr
-  attributes(args$x) <- args$info
-  args$x
+  attributes(my_args$x) <- my_args$info
+  my_args$x
 }
 
 

R/convert_na_to.R

@@ -145,7 +145,7 @@ convert_na_to.character <- function(x, replacement = NULL, verbose = TRUE, ...)
 #' @param replace_num Value to replace `NA` when variable is of type numeric.
 #' @param replace_char Value to replace `NA` when variable is of type character.
 #' @param replace_fac Value to replace `NA` when variable is of type factor.
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @rdname convert_na_to
 #' @export
@@ -160,10 +160,10 @@ convert_na_to.data.frame <- function(x,
                                      regex = FALSE,
                                      verbose = TRUE,
                                      ...) {
-  data <- x
+  my_data <- x
   select_nse <- .select_nse(
     select,
-    data,
+    data = my_data,
     exclude = exclude,
     ignore_case,
     regex = regex,

R/convert_to_na.R

@@ -12,7 +12,7 @@
 #' @param drop_levels Logical, for factors, when specific levels are replaced
 #'   by `NA`, should unused levels be dropped?
 #' @param ... Not used.
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @return
 #' `x`, where all values in `na` are converted to `NA`.

R/data_addprefix.R

@@ -1,5 +1,5 @@
 #' @rdname data_rename
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #' @examples
 #' # Add prefix / suffix to all columns
 #' head(data_addprefix(iris, "NEW_"))

R/data_codebook.R

@@ -22,7 +22,7 @@
 #' @param line_padding For HTML tables, the distance (in pixel) between lines.
 #' @param row_color For HTML tables, the fill color for odd rows.
 #' @inheritParams standardize.data.frame
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @return A formatted data frame, summarizing the content of the data frame.
 #' Returned columns include the column index of the variables in the original

R/data_duplicated.R

@@ -7,7 +7,7 @@
 #' values for that row, to help in the decision-making when
 #' selecting which duplicates to keep.
 #'
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @keywords duplicates
 #' @export

R/data_extract.R

@@ -26,7 +26,7 @@
 #' @param verbose Toggle warnings.
 #' @param ... For use by future methods.
 #'
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @details `data_extract()` can be used to select multiple variables or pull a
 #' single variable from a data frame. Thus, the return value is by default not
@@ -134,13 +134,13 @@ data_extract.data.frame <- function(data,
   }
 
   # we definitely should have a vector here when name not NULL
-  if (!is.null(name)) {
+  if (is.null(name)) {
+    data[, select, drop = !as_data_frame]
+  } else {
     # if name indicates a variable, extract values for naming now
     if (length(name) == 1L) {
       name <- data[[name]]
     }
     stats::setNames(data[[select]], name)
-  } else {
-    data[, select, drop = !as_data_frame]
   }
 }

R/data_group.R

@@ -6,7 +6,7 @@
 #' grouping information from a grouped data frame.
 #'
 #' @param data A data frame
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @return A grouped data frame, i.e. a data frame with additional information
 #' about the grouping structure saved as attributes.
@@ -41,26 +41,26 @@ data_group <- function(data,
     verbose = verbose
   )
   # create grid with combinations of all levels
-  grid <- as.data.frame(expand.grid(lapply(data[select], unique)))
+  my_grid <- as.data.frame(expand.grid(lapply(data[select], unique)))
   # sort grid
-  grid <- grid[do.call(order, grid), , drop = FALSE]
+  my_grid <- my_grid[do.call(order, my_grid), , drop = FALSE]
 
-  .rows <- lapply(seq_len(nrow(grid)), function(i) {
+  .rows <- lapply(seq_len(nrow(my_grid)), function(i) {
     as.integer(data_match(
       data,
-      to = grid[i, , drop = FALSE],
+      to = my_grid[i, , drop = FALSE],
       match = "and",
       return_indices = TRUE,
       drop_na = FALSE
     ))
   })
-  grid[[".rows"]] <- .rows
+  my_grid[[".rows"]] <- .rows
 
   # remove data_match attributes
-  attr(grid, "out.attrs") <- NULL
-  attr(grid, ".drop") <- TRUE
+  attr(my_grid, "out.attrs") <- NULL
+  attr(my_grid, ".drop") <- TRUE
 
-  attr(data, "groups") <- grid
+  attr(data, "groups") <- my_grid
   class(data) <- unique(c("grouped_df", "data.frame"), class(data))
 
   data

R/data_modify.R

@@ -121,10 +121,10 @@
 #'   .modify = round
 #' )
 #'
-#' # combine "data_find()" and ".at" argument
+#' # combine "extract_column_names()" and ".at" argument
 #' out <- data_modify(
 #'   d,
-#'   .at = data_find(d, select = starts_with("Sepal")),
+#'   .at = extract_column_names(d, select = starts_with("Sepal")),
 #'   .modify = as.factor
 #' )
 #' # "Sepal.Length" and "Sepal.Width" are now factors

R/data_peek.R

@@ -9,7 +9,7 @@
 #' @param width Maximum width of line length to display. If `NULL`, width will
 #' be determined using `options()$width`.
 #' @param ... not used.
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @note To show only specific or a limited number of variables, use the
 #' `select` argument, e.g. `select = 1:5` to show only the first five variables.

R/data_relocate.R

@@ -15,7 +15,7 @@
 #'   character vector, indicating the name of the destination column, or a
 #'   numeric value, indicating the index number of the destination column.
 #'   If `-1`, will be added before or after the last column.
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #' @inheritParams data_rename
 #'
 #' @inherit data_rename seealso
@@ -97,6 +97,7 @@ data_relocate <- function(data,
   original_after <- after
 
   # Find new positions
+  # nolint start
   if (!is.null(before)) {
     before <- before[before %in% data_cols][1] # Take first that exists (if vector is supplied)
     if (length(before) != 1 || is.na(before)) {
@@ -123,6 +124,7 @@ data_relocate <- function(data,
     where <- 1
     position <- union(position, where)
   }
+  # nolint end
 
   # Set left and right side
   lhs <- setdiff(seq(1, where - 1), position)

R/data_remove.R

@@ -1,4 +1,4 @@
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #' @rdname data_relocate
 #' @examples
 #' # Remove columns

R/data_rename.R

@@ -43,10 +43,11 @@
 #' - Functions to rename stuff: [data_rename()], [data_rename_rows()], [data_addprefix()], [data_addsuffix()]
 #' - Functions to reorder or remove columns: [data_reorder()], [data_relocate()], [data_remove()]
 #' - Functions to reshape, pivot or rotate data frames: [data_to_long()], [data_to_wide()], [data_rotate()]
-#' - Functions to recode data: [rescale()], [reverse()], [categorize()], [recode_values()], [slide()]
+#' - Functions to recode data: [rescale()], [reverse()], [categorize()],
+#'   [recode_values()], [slide()]
 #' - Functions to standardize, normalize, rank-transform: [center()], [standardize()], [normalize()], [ranktransform()], [winsorize()]
 #' - Split and merge data frames: [data_partition()], [data_merge()]
-#' - Functions to find or select columns: [data_select()], [data_find()]
+#' - Functions to find or select columns: [data_select()], [extract_column_names()]
 #' - Functions to filter rows: [data_match()], [data_filter()]
 #'
 #' @export

R/data_replicate.R

@@ -13,7 +13,7 @@
 #' provided in `expand` are removed from the data frame. If `FALSE` and `expand`
 #' contains missing values, the function will throw an error.
 #' @param ... Currently not used.
-#' @inheritParams find_columns
+#' @inheritParams extract_column_names
 #'
 #' @return A dataframe with each row replicated as many times as defined in `expand`.
 #'