styling comprehensively with styler

R/expand.R

@@ -138,7 +138,6 @@ crossing <- function(...) {
       "Each element must be either an atomic vector or a data frame.
        Problems: {problems}."
     ))
-
   }
 
   # turn each atomic vector into single column data frame

R/extract.R

@@ -84,7 +84,7 @@ extract.data.frame <- function(data, col, into, regex = "([[:alnum:]]+)",
 #' @inheritParams extract
 #' @export
 extract_ <- function(data, col, into, regex = "([[:alnum:]]+)", remove = TRUE,
-                      convert = FALSE, ...) {
+                     convert = FALSE, ...) {
   UseMethod("extract_")
 }
 #' @export

R/gather.R

@@ -132,7 +132,8 @@ gather.data.frame <- function(data, key = "key", value = "value", ...,
   args <- normalize_melt_arguments(data, gather_idx, factorsAsStrings = TRUE)
   valueAsFactor <- "factor" %in% class(args$attr_template)
 
-  out <- melt_dataframe(data,
+  out <- melt_dataframe(
+    data,
     id_idx - 1L,
     gather_idx - 1L,
     as.character(key_var),
@@ -159,7 +160,6 @@ gather.data.frame <- function(data, key = "key", value = "value", ...,
 
 ## Get the attributes if common, NULL if not.
 normalize_melt_arguments <- function(data, measure.ind, factorsAsStrings) {
-
   measure.attributes <- map(measure.ind, function(i) {
     attributes(data[[i]])
   })
@@ -172,7 +172,8 @@ normalize_melt_arguments <- function(data, measure.ind, factorsAsStrings) {
   } else {
     warn(glue(
       "attributes are not identical across measure variables;
-       they will be dropped"))
+       they will be dropped"
+    ))
     attr_template <- NULL
   }
 

R/replace_na.R

@@ -43,8 +43,9 @@ replace_na.data.frame <- function(data, replace = list(), ...) {
 
 check_replacement <- function(x, var) {
   n <- length(x)
-  if (n == 1)
+  if (n == 1) {
     return()
+  }
 
   abort(glue("Replacement for `{var}` is length {n}, not length 1"))
 }

R/unnest.R

@@ -84,7 +84,6 @@ unnest.default <- function(data, ..., .drop = NA, .id = NULL, .sep = NULL, .pres
 #' @export
 unnest.data.frame <- function(data, ..., .drop = NA, .id = NULL,
                               .sep = NULL, .preserve = NULL) {
-
   preserve <- tidyselect::vars_select(names(data), !!! enquo(.preserve))
   quos <- quos(...)
   if (is_empty(quos)) {
@@ -122,13 +121,16 @@ unnest.data.frame <- function(data, ..., .drop = NA, .id = NULL,
 
   unnested_dataframe <- map(nest_types$dataframe %||% list(), dplyr::bind_rows, .id = .id)
   if (!is_null(.sep)) {
-    unnested_dataframe <- imap(unnested_dataframe,
+    unnested_dataframe <- imap(
+      unnested_dataframe,
       function(df, name) {
         set_names(df, paste(name, names(df), sep = .sep))
-      })
+      }
+    )
   }
-  if (length(unnested_dataframe) > 0)
+  if (length(unnested_dataframe) > 0) {
     unnested_dataframe <- dplyr::bind_cols(unnested_dataframe)
+  }
 
   # Keep list columns by default, only if the rows aren't expanded
   if (identical(.drop, NA)) {

R/utils.R

@@ -58,8 +58,9 @@ extract_numeric <- function(x) {
 NULL
 
 list_indices <- function(x, max = 20) {
-  if (length(x) > max)
+  if (length(x) > max) {
     x <- c(x[seq_len(max)], "...")
+  }
 
   paste(x, collapse = ", ")
 }

tests/testthat/test-fill.R

@@ -34,7 +34,6 @@ test_that("missings filled down for each atomic vector", {
     dbl = c(1, NA),
     chr = c("a", NA),
     lst = list(1:5, NULL)
-
   )
 
   out <- fill(df, tidyselect::everything())

tests/testthat/test-gather.R

@@ -46,7 +46,7 @@ test_that("key preserves column ordering when factor_key = TRUE", {
 
 test_that("preserve class of input", {
   dat <- data.frame(x = 1:2)
-  dat %>% as_tibble %>% gather %>% expect_is("tbl_df")
+  dat %>% as_tibble() %>% gather() %>% expect_is("tbl_df")
 })
 
 test_that("additional inputs control which columns to gather", {
@@ -95,8 +95,10 @@ test_that("factors coerced to characters, not integers", {
     v2 = factor(letters[1:3])
   )
 
-  expect_warning(out <- gather(df, k, v),
-    "attributes are not identical across measure variables")
+  expect_warning(
+    out <- gather(df, k, v),
+    "attributes are not identical across measure variables"
+  )
 
   expect_equal(out$v, c(1:3, letters[1:3]))
 })
@@ -121,8 +123,10 @@ test_that("varying attributes are dropped with a warning", {
     date1 = as.POSIXct(Sys.Date()),
     date2 = Sys.Date() + 10
   )
-  expect_warning(gather(df, k, v),
-    "attributes are not identical across measure variables")
+  expect_warning(
+    gather(df, k, v),
+    "attributes are not identical across measure variables"
+  )
 })
 
 test_that("gather preserves OBJECT bit on e.g. POSIXct", {

tests/testthat/test-spread.R

@@ -74,7 +74,8 @@ test_that("drop = FALSE spread all levels including NA (#254)", {
   df <- data.frame(
     x = factor(c("a", "b", "c", NA), levels = l),
     y = c("a", "b", "c", "d"),
-    z = c("a", "b", "a", "b"))
+    z = c("a", "b", "a", "b")
+  )
   out <- df %>% spread(x, y, drop = FALSE)
   expect_equal(nrow(out), 2)
   expect_equal(ncol(out), 6)
@@ -92,10 +93,12 @@ test_that("preserve class of input", {
 })
 
 test_that("dates are spread into columns (#62)", {
-  df <- data.frame(id = c("a", "a", "b", "b"),
-                   key = c("begin", "end", "begin", "end"),
-                   date = Sys.Date() + 0:3,
-                   stringsAsFactors = FALSE)
+  df <- data.frame(
+    id = c("a", "a", "b", "b"),
+    key = c("begin", "end", "begin", "end"),
+    date = Sys.Date() + 0:3,
+    stringsAsFactors = FALSE
+  )
   out <- spread(df, key, date)
   expect_identical(names(out), c("id", "begin", "end"))
   expect_is(out$begin, "Date")
@@ -106,40 +109,50 @@ test_that("spread can produce mixed variable types (#118)", {
   df <- data.frame(
     row = rep(1:2, 3),
     column = rep(1:3, each = 2),
-    cell_contents = as.character(c(rep("Argentina", 2),
-                                   62.485, 64.399,
-                                   1952, 1957)),
+    cell_contents = as.character(c(
+      rep("Argentina", 2),
+      62.485, 64.399,
+      1952, 1957
+    )),
     stringsAsFactors = FALSE
   )
   out <- spread(df, column, cell_contents, convert = TRUE)
-  expect_equivalent(vapply(out, class, ""),
-                    c("integer", "character", "numeric", "integer"))
+  expect_equivalent(
+    vapply(out, class, ""),
+    c("integer", "character", "numeric", "integer")
+  )
 })
 
 test_that("factors can be used with convert = TRUE to produce mixed types", {
-  df <- data.frame(row = c(1, 2, 1, 2, 1, 2),
-                   column = c("f", "f", "g", "g", "h", "h"),
-                   contents = c("aa", "bb", "1", "2", "TRUE", "FALSE"),
-                   stringsAsFactors = FALSE)
+  df <- data.frame(
+    row = c(1, 2, 1, 2, 1, 2),
+    column = c("f", "f", "g", "g", "h", "h"),
+    contents = c("aa", "bb", "1", "2", "TRUE", "FALSE"),
+    stringsAsFactors = FALSE
+  )
   out <- df %>% spread(column, contents, convert = TRUE)
   expect_is(out$f, "character")
   expect_is(out$g, "integer")
   expect_is(out$h, "logical")
 })
 
 test_that("dates can be used with convert = TRUE", {
-  df <- data.frame(id = c("a", "a", "b", "b"),
-                   key = c("begin", "end", "begin", "end"),
-                   date = Sys.Date() + 0:3,
-                   stringsAsFactors = FALSE)
+  df <- data.frame(
+    id = c("a", "a", "b", "b"),
+    key = c("begin", "end", "begin", "end"),
+    date = Sys.Date() + 0:3,
+    stringsAsFactors = FALSE
+  )
   out <- spread(df, key, date, convert = TRUE)
   expect_is(out$begin, "character")
   expect_is(out$end, "character")
 })
 
 test_that("vars that are all NA are logical if convert = TRUE (#118)", {
-  df <- data.frame(row = c(1, 2, 1, 2), column = c("f", "f", "g", "g"),
-                   contents = c("aa", "bb", NA, NA), stringsAsFactors = FALSE)
+  df <- data.frame(
+    row = c(1, 2, 1, 2), column = c("f", "f", "g", "g"),
+    contents = c("aa", "bb", NA, NA), stringsAsFactors = FALSE
+  )
   out <- df %>% spread(column, contents, convert = TRUE)
   expect_is(out$g, "logical")
 })

tests/testthat/test-unnest.R

@@ -152,7 +152,6 @@ test_that("unnest respects .drop_lists", {
 
   expect_equal(df %>% unnest(y, .drop = TRUE) %>% names(), c("x", "y"))
   expect_equal(df %>% unnest(z, .drop = FALSE) %>% names(), c("x", "y", "z"))
-
 })
 
 test_that("grouping is preserved", {