Merge pull request #26 from tidyverse/master

Sync Fork from Upstream Repo

Author: sthagen

.github/workflows/R-CMD-check.yaml

@@ -30,7 +30,6 @@ jobs:
           - {os: ubuntu-16.04,   r: '3.5',   vdiffr: false, xref: true,   rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           - {os: ubuntu-16.04,   r: '3.4',   vdiffr: false, xref: true,   rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           - {os: ubuntu-16.04,   r: '3.3',   vdiffr: false, xref: true,   rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
-          - {os: ubuntu-16.04,   r: '3.2',   vdiffr: false, xref: false,  rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
 
     env:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true

DESCRIPTION

@@ -25,7 +25,7 @@ Authors@R: c(
     person("RStudio", role = c("cph", "fnd"))
     )
 Depends:
-    R (>= 3.2)
+    R (>= 3.3)
 Imports: 
     digest,
     glue,

NEWS.md

@@ -22,6 +22,8 @@
 
 * `stat_bin()`'s computed variable `width` is now documented (#3522).
 
+* ggplot2 now requires R >= 3.3 (#4247).
+
 # ggplot2 3.3.2
 This is a small release focusing on fixing regressions introduced in 3.3.1.
 

R/data.R

@@ -48,16 +48,21 @@
 
 #' Midwest demographics
 #'
-#' Demographic information of midwest counties
+#' Demographic information of midwest counties from 2000 US census
+#'
+#' Note: this dataset is included for illustrative purposes. The original
+#' descriptions were not documented and the current descriptions here are based
+#' on speculation. For more accurate and up-to-date US census data, see the
+#' [`acs` package](https://cran.r-project.org/package=acs).
 #'
 #' @format A data frame with 437 rows and 28 variables:
 #' \describe{
-#'  \item{PID}{}
-#'  \item{county}{}
-#'  \item{state}{}
-#'  \item{area}{}
-#'  \item{poptotal}{Total population}
-#'  \item{popdensity}{Population density}
+#'  \item{PID}{Unique county identifier.}
+#'  \item{county}{County name.}
+#'  \item{state}{State to which county belongs to.}
+#'  \item{area}{Area of county (units unknown).}
+#'  \item{poptotal}{Total population.}
+#'  \item{popdensity}{Population density (person/unit area).}
 #'  \item{popwhite}{Number of whites.}
 #'  \item{popblack}{Number of blacks.}
 #'  \item{popamerindian}{Number of American Indians.}
@@ -69,17 +74,17 @@
 #'  \item{percasian}{Percent Asian.}
 #'  \item{percother}{Percent other races.}
 #'  \item{popadults}{Number of adults.}
-#'  \item{perchsd}{}
+#'  \item{perchsd}{Percent with high school diploma.}
 #'  \item{percollege}{Percent college educated.}
-#'  \item{percprof}{Percent profession.}
-#'  \item{poppovertyknown}{}
-#'  \item{percpovertyknown}{}
-#'  \item{percbelowpoverty}{}
-#'  \item{percchildbelowpovert}{}
-#'  \item{percadultpoverty}{}
-#'  \item{percelderlypoverty}{}
-#'  \item{inmetro}{In a metro area.}
-#'  \item{category}{}
+#'  \item{percprof}{Percent with professional degree.}
+#'  \item{poppovertyknown}{Population with known poverty status.}
+#'  \item{percpovertyknown}{Percent of population with known poverty status.}
+#'  \item{percbelowpoverty}{Percent of people below poverty line.}
+#'  \item{percchildbelowpovert}{Percent of children below poverty line.}
+#'  \item{percadultpoverty}{Percent of adults below poverty line.}
+#'  \item{percelderlypoverty}{Percent of elderly below poverty line.}
+#'  \item{inmetro}{County considered in a metro area.}
+#'  \item{category}{Miscellaneous.}
 #' }
 #'
 "midwest"

R/geom-polygon.r

@@ -167,7 +167,7 @@ GeomPolygon <- ggproto("GeomPolygon", Geom,
 
   },
 
-  default_aes = aes(colour = "NA", fill = "grey20", size = 0.5, linetype = 1,
+  default_aes = aes(colour = NA, fill = "grey20", size = 0.5, linetype = 1,
     alpha = NA, subgroup = NULL),
 
   handle_na = function(data, params) {

R/stat-smooth.r

@@ -25,7 +25,9 @@
 #' @param level Level of confidence interval to use (0.95 by default).
 #' @param span Controls the amount of smoothing for the default loess smoother.
 #'   Smaller numbers produce wigglier lines, larger numbers produce smoother
-#'   lines.
+#'   lines. Only used with loess, i.e. when `method = "loess"`,
+#'   or when `method = NULL` (the default) and there are fewer than 1,000
+#'   observations.
 #' @param n Number of points at which to evaluate smoother.
 #' @param method.args List of additional arguments passed on to the modelling
 #'   function defined by `method`.

R/stat-summary.r

@@ -31,7 +31,7 @@
 #' number, but is somewhat less flexible. If your summary function computes
 #' multiple values at once (e.g. min and max), use `fun.data`.
 #'
-#' `fun.data` will recieve data as if it was oriented along the x-axis and
+#' `fun.data` will receive data as if it was oriented along the x-axis and
 #' should return a data.frame that corresponds to that orientation. The layer
 #' will take care of flipping the input and output if it is oriented along the
 #' y-axis.
@@ -270,13 +270,18 @@ mean_sdl <- wrap_hmisc("smean.sdl")
 #' @rdname hmisc
 median_hilow <- wrap_hmisc("smedian.hilow")
 
-#' Calculate mean and standard error
+#' Calculate mean and standard error of the mean
 #'
 #' For use with [stat_summary()]
 #'
-#' @param x numeric vector
-#' @param mult number of multiples of standard error
-#' @return A data frame with columns `y`, `ymin`, and `ymax`.
+#' @param x numeric vector.
+#' @param mult number of multiples of standard error.
+#' @return A data frame with three columns:
+#' \describe{
+#'     \item{`y`}{ The mean.}
+#'     \item{`ymin`}{ The mean minus the multiples of the standard error.}
+#'     \item{`ymax`}{ The mean plus the multiples of the standard error.}
+#' }
 #' @export
 #' @examples
 #' x <- rnorm(100)

man/geom_smooth.Rd

@@ -125,10 +125,10 @@ test_that("facet_grid() accepts vars()", {
   expect_identical(grid$params$rows, quos(foo = foo))
   expect_identical(grid$params$cols, quos(bar = bar))
 
-  expect_equal(facet_grid(vars(am, vs)), facet_grid(am + vs ~ .))
-  expect_equal(facet_grid(vars(am, vs), vars(cyl)), facet_grid(am + vs ~ cyl))
-  expect_equal(facet_grid(NULL, vars(cyl)), facet_grid(. ~ cyl))
-  expect_equal(facet_grid(vars(am, vs), TRUE), facet_grid(am + vs ~ ., margins = TRUE))
+  expect_equal(facet_grid(vars(am, vs))$params, facet_grid(am + vs ~ .)$params)
+  expect_equal(facet_grid(vars(am, vs), vars(cyl))$params, facet_grid(am + vs ~ cyl)$params)
+  expect_equal(facet_grid(NULL, vars(cyl))$params, facet_grid(. ~ cyl)$params)
+  expect_equal(facet_grid(vars(am, vs), TRUE)$params, facet_grid(am + vs ~ ., margins = TRUE)$params)
 })
 
 test_that("facet_grid() fails if passed both a formula and a vars()", {