Merge pull request #618 from ropensci/develop

Develop to master

DESCRIPTION

@@ -91,7 +91,11 @@ Authors@R:
       person(given = "Kyle", 
              family = "Butts",
              role ="ctb",
-             email = "[email protected]"))
+             email = "[email protected]"),
+      person(given = "Bastian", 
+             family = "Torges",
+             role ="ctb",
+             email = "[email protected]"))
 Description: A simple to use summary function that can be used with pipes
     and displays nicely in the console. The default summary statistics may
     be modified by the user as can the default formatting.  Support for
@@ -119,7 +123,7 @@ Imports:
     stringr (>= 1.1),
     tibble (>= 2.0.0),
     tidyr (>= 1.0),
-    tidyselect (>= 0.2.5),
+    tidyselect (>= 1.0.0),
     withr
 Suggests:
     covr,

R/skim.R

@@ -60,6 +60,7 @@
 #' # Use tidyselect
 #' skim(iris, Species)
 #' skim(iris, starts_with("Sepal"))
+#' skim(iris, where(is.numeric))
 #'
 #' # Skim also works groupwise
 #' iris %>%

R/skim_with.R

@@ -88,14 +88,11 @@ skim_with <- function(...,
       data <- as.data.frame(data)
     }
     stopifnot(inherits(data, "data.frame"))
-
-    .vars <- rlang::quos(...)
-    cols <- names(data)
-    if (length(.vars) == 0) {
-      selected <- cols
-    } else {
-      selected <- tidyselect::vars_select(cols, !!!.vars)
-    }
+
+    selected <- names(tidyselect::eval_select(rlang::expr(c(...)), data))
+    if (length(selected) == 0) {
+      selected <- names(data)
+    } 
 
     grps <- dplyr::groups(data)
     if (length(grps) > 0) {
@@ -321,13 +318,19 @@ skim_by_type <- function(mangled_skimmers, variable_names, data) {
 skim_by_type.grouped_df <- function(mangled_skimmers, variable_names, data) {
   group_columns <- dplyr::groups(data)
   grouped <- dplyr::group_by(data, !!!group_columns)
-  skimmed <- dplyr::summarize_at(grouped, variable_names, mangled_skimmers$funs)
+  skimmed <- dplyr::summarize(
+    grouped,
+    dplyr::across(variable_names, mangled_skimmers$funs)
+  )
   build_results(skimmed, variable_names, group_columns)
 }
 
 #' @export
 skim_by_type.data.frame <- function(mangled_skimmers, variable_names, data) {
-  skimmed <- dplyr::summarize_at(data, variable_names, mangled_skimmers$funs)
+  skimmed <- dplyr::summarize(
+    data,
+    dplyr::across(variable_names, mangled_skimmers$funs)
+  )
   build_results(skimmed, variable_names, NULL)
 }
 
@@ -358,7 +361,7 @@ reshape_skimmed <- function(column, skimmed, groups) {
   out <- dplyr::select(
     as.data.frame(skimmed),
     !!!groups,
-    tidyselect::starts_with(delim_name)
+    tidyselect::starts_with(delim_name, ignore.case = FALSE)
   )
   set_clean_names(out)
 }

tests/testthat/test-get_skimmers.R

@@ -2,7 +2,7 @@ context("Get skimmers")
 
 test_that("get_sfl() behaves correctly", {
   my_sfl <- get_sfl("numeric")
-  expect_is(my_sfl, "skimr_function_list")
+  expect_s3_class(my_sfl, "skimr_function_list")
   expect_equal(my_sfl$skim_type, "numeric")
   expect_named(my_sfl$funs, c(
     "mean", "sd", "p0", "p25", "p50", "p75", "p100", "hist"

tests/testthat/test-reshape.R

@@ -3,7 +3,7 @@ context("Reshaping a skim_df")
 test_that("You can parition a skim_df", {
   skimmed <- skim(iris)
   input <- partition(skimmed)
-  expect_is(input, "skim_list")
+  expect_s3_class(input, "skim_list")
   expect_length(input, 2)
   expect_named(input, c("factor", "numeric"))
   attrs <- attributes(input)
@@ -20,15 +20,15 @@ test_that("You can parition a skim_df", {
   )
 
   # Subtables
-  expect_is(input$factor, c("one_skim_df", "tbl_df", "tbl", "data.frame"))
+  expect_s3_class(input$factor, c("one_skim_df", "tbl_df", "tbl", "data.frame"))
   expect_n_rows(input$factor, 1)
   expect_n_columns(input$factor, 6)
   expect_named(input$factor, c(
     "skim_variable", "n_missing", "complete_rate", "ordered", "n_unique",
     "top_counts"
   ))
 
-  expect_is(input$numeric, c("one_skim_df", "tbl_df", "tbl", "data.frame"))
+  expect_s3_class(input$numeric, c("one_skim_df", "tbl_df", "tbl", "data.frame"))
   expect_n_rows(input$numeric, 4)
   expect_n_columns(input$numeric, 11)
   expect_named(input$numeric, c(
@@ -48,7 +48,7 @@ test_that("Partitioning works in a round trip", {
 test_that("You can yank a subtable from a skim_df", {
   skimmed <- skim(iris)
   input <- yank(skimmed, "numeric")
-  expect_is(input, c("one_skim_df", "tbl_df", "tbl", "data.frame"))
+  expect_s3_class(input, c("one_skim_df", "tbl_df", "tbl", "data.frame"))
   expect_n_rows(input, 4)
   expect_n_columns(input, 11)
   expect_named(input, c(

tests/testthat/test-sfl.R

@@ -11,13 +11,13 @@ test_that("Zero-length sfl's supported", {
 
 test_that("The interface for sfl's separates keep and drop functions", {
   input <- sfl(mad = mad, hist = NULL, skim_type = "test")
-  expect_is(input, "skimr_function_list")
+  expect_s3_class(input, "skimr_function_list")
   expect_length(input, 2)
   expect_named(input, c("funs", "skim_type"))
   expect_identical(input$skim_type, "test")
 
   funs <- input$funs
-  expect_is(funs, "list")
+  expect_type(funs, "list")
   expect_named(funs, c("mad", "hist"))
 })