lintr, styler

R/center.R

@@ -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_argscheck)) {
+    vals <- rep(0, length(my_argsvals)) # If only unique value
   } else {
-    vals <- as.vector(args$vals - args$center)
+    vals <- as.vector(my_argsvals - my_argscenter)
   }
 
-  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_argsvalid_x))
+  centered_x[my_argsvalid_x] <- vals
+  attr(centered_x, "center") <- my_argscenter
   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

@@ -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/data_group.R

@@ -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_relocate.R

@@ -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_rename.R

@@ -43,7 +43,8 @@
 #' - 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()], [extract_column_names()]

R/data_rescale.R

@@ -202,16 +202,16 @@ rescale.grouped_df <- function(x,
   # create the new variables and updates "select", so new variables are processed
   if (!isFALSE(append)) {
     # process arguments
-    args <- .process_append(
+    my_args <- .process_append(
       x,
       select,
       append,
       append_suffix = "_r",
       preserve_value_labels = TRUE
     )
     # update processed arguments
-    x <- args$x
-    select <- args$select
+    x <- my_args$x
+    select <- my_args$select
   }
 
   x <- as.data.frame(x)
@@ -263,15 +263,15 @@ rescale.data.frame <- function(x,
   # create the new variables and updates "select", so new variables are processed
   if (!isFALSE(append)) {
     # process arguments
-    args <- .process_append(
+    my_args <- .process_append(
       x,
       select,
       append,
       append_suffix = "_r"
     )
     # update processed arguments
-    x <- args$x
-    select <- args$select
+    x <- my_args$x
+    select <- my_args$select
   }
 
   # Transform the range so that it is a list now

R/select_nse.R

@@ -149,7 +149,7 @@
 # 3 types of symbols:
 # - unquoted variables
 # - objects that need to be evaluated, e.g data_find(iris, i) where
-#   i is a function arg or is defined before. This can also be a 
+#   i is a function arg or is defined before. This can also be a
 #   vector of names or positions.
 # - functions (without parenthesis)