Minor documentation edits (#2727)

Author: Dana Paige Seidel

R/aes.r

@@ -9,7 +9,7 @@ NULL
 #'
 #' This function also standardises aesthetic names by performing partial
 #' matching, converting color to colour, and translating old style R names to
-#' ggplot names (eg. pch to shape, cex to size).
+#' ggplot names (e.g. pch to shape, cex to size).
 #'
 #' @section Quasiquotation:
 #'
@@ -165,7 +165,7 @@ is_position_aes <- function(vars) {
   aes_to_scale(vars) %in% c("x", "y")
 }
 
-#' Define aesthetic mappings programatically
+#' Define aesthetic mappings programmatically
 #'
 #' Aesthetic mappings describe how variables in the data are mapped to visual
 #' properties (aesthetics) of geoms. [aes()] uses non-standard

R/facet-.r

@@ -66,9 +66,9 @@ NULL
 #'
 #'   - `draw_labels`: Given the gtable returned by `draw_panels`,
 #'   add axis titles to the gtable. The default is to add one title at each side
-#'   depending on the position and existance of axes.
+#'   depending on the position and existence of axes.
 #'
-#' All extension methods recieve the content of the params field as the params
+#' All extension methods receive the content of the params field as the params
 #' argument, so the constructor function will generally put all relevant
 #' information into this field. The only exception is the `shrink`
 #' parameter which is used to determine if scales are retrained after Stat

R/facet-grid-.r

@@ -103,7 +103,7 @@ NULL
 #'
 #' # Margins ----------------------------------------------------------
 #' \donttest{
-#' # Margins can be specified by logically (all yes or all no) or by specific
+#' # Margins can be specified logically (all yes or all no) or for specific
 #' # variables as (character) variable names
 #' mg <- ggplot(mtcars, aes(x = mpg, y = wt)) + geom_point()
 #' mg + facet_grid(vs + am ~ gear, margins = TRUE)

R/fortify-map.r

@@ -85,7 +85,7 @@ map_data <- function(map, region = ".", exact = FALSE, ...) {
 #' @param regions map region
 #' @param fill fill colour
 #' @param colour border colour
-#' @param xlim,ylim latitudinal and logitudinal range for extracting map
+#' @param xlim,ylim latitudinal and longitudinal ranges for extracting map
 #'   polygons, see [maps::map()] for details.
 #' @inheritDotParams geom_polygon
 #' @export

R/geom-bar.r

@@ -1,12 +1,13 @@
 #' Bar charts
 #'
-#' There are two types of bar charts: `geom_bar` makes the height of the
+#' There are two types of bar charts: `geom_bar()` and `geom_col()`.
+#' `geom_bar()` makes the height of the
 #' bar proportional to the number of cases in each group (or if the
 #' `weight` aesthetic is supplied, the sum of the weights). If you want the
 #' heights of the bars to represent values in the data, use
-#' \link{geom_col} instead. `geom_bar` uses `stat_count` by
-#' default: it counts the number of cases at each x position. `geom_col`
-#' uses `stat_identity`: it leaves the data as is.
+#' `geom_col()` instead. `geom_bar()` uses `stat_count()` by
+#' default: it counts the number of cases at each x position. `geom_col()`
+#' uses `stat_identity()`: it leaves the data as is.
 #'
 #' A bar chart uses height to represent a value, and so the base of the
 #' bar must always be shown to produce a valid visual comparison. Naomi Robbins
@@ -25,16 +26,16 @@
 #' @seealso
 #'   [geom_histogram()] for continuous data,
 #'   [position_dodge()] and [position_dodge2()] for creating side-by-side
-#'   barcharts.
+#'   bar charts.
 #' @export
 #' @inheritParams layer
 #' @inheritParams geom_point
 #' @param width Bar width. By default, set to 90\% of the resolution of the data.
-#' @param binwidth `geom_bar` no longer has a binwidth argument - if
+#' @param binwidth `geom_bar()` no longer has a binwidth argument - if
 #'   you use it you'll get an warning telling to you use
 #'   [geom_histogram()] instead.
-#' @param geom,stat Override the default connection between `geom_bar` and
-#'   `stat_count`.
+#' @param geom,stat Override the default connection between `geom_bar()` and
+#'   `stat_count()`.
 #' @examples
 #' # geom_bar is designed to make it easy to create bar charts that show
 #' # counts (or sums of weights)

R/geom-boxplot.r

@@ -49,7 +49,7 @@
 #'   if the notches of two boxes do not overlap, this suggests that the medians
 #'   are significantly different.
 #' @param notchwidth For a notched box plot, width of the notch relative to
-#'   the body (default 0.5)
+#'   the body (defaults to `notchwidth = 0.5`).
 #' @param varwidth If `FALSE` (default) make a standard box plot. If
 #'   `TRUE`, boxes are drawn with widths proportional to the
 #'   square-roots of the number of observations in the groups (possibly

R/geom-linerange.r

@@ -9,7 +9,7 @@
 #'   `geom_pointrange()`.
 #' @seealso
 #'  [stat_summary()] for examples of these guys in use,
-#'  [geom_smooth()] for continuous analog,
+#'  [geom_smooth()] for continuous analogue,
 #'  [geom_errorbarh()] for a horizontal error bar.
 #' @export
 #' @inheritParams layer

R/geom-point.r

@@ -18,7 +18,7 @@
 #' There is no one solution to this problem, but there are some techniques
 #' that can help. You can add additional information with
 #' [geom_smooth()], [geom_quantile()] or
-#' [geom_density_2d()]. If you have few unique x values,
+#' [geom_density_2d()]. If you have few unique `x` values,
 #' [geom_boxplot()] may also be useful.
 #'
 #' Alternatively, you can
@@ -36,7 +36,7 @@
 #'   a warning. If `TRUE`, missing values are silently removed.
 #' @param ... Other arguments passed on to [layer()]. These are
 #'   often aesthetics, used to set an aesthetic to a fixed value, like
-#'   `color = "red"` or `size = 3`. They may also be parameters
+#'   `colour = "red"` or `size = 3`. They may also be parameters
 #'   to the paired geom/stat.
 #' @inheritParams layer
 #' @export
@@ -76,12 +76,6 @@
 #'   geom_point(colour = "pink", size = 4) +
 #'   geom_point(aes(shape = factor(cyl)))
 #'
-#' # These extra layers don't usually appear in the legend, but we can
-#' # force their inclusion
-#' p + geom_point(colour = "black", size = 4.5, show.legend = TRUE) +
-#'   geom_point(colour = "pink", size = 4, show.legend = TRUE) +
-#'   geom_point(aes(shape = factor(cyl)))
-#'
 #' # geom_point warns when missing values have been dropped from the data set
 #' # and not plotted, you can turn this off by setting na.rm = TRUE
 #' mtcars2 <- transform(mtcars, mpg = ifelse(runif(32) < 0.2, NA, mpg))

R/geom-ribbon.r

@@ -4,7 +4,7 @@
 #' by `ymin` and `ymax`. `geom_area` is a special case of
 #' `geom_ribbon`, where the `ymin` is fixed to 0.
 #'
-#' An area plot is the continuous analog of a stacked bar chart (see
+#' An area plot is the continuous analogue of a stacked bar chart (see
 #' [geom_bar()]), and can be used to show how composition of the
 #' whole varies over the range of x. Choosing the order in which different
 #' components is stacked is very important, as it becomes increasing hard to

R/geom-segment.r

@@ -12,7 +12,7 @@
 #' @inheritParams layer
 #' @inheritParams geom_point
 #' @param arrow specification for arrow heads, as created by arrow().
-#' @param arrow.fill fill color to use for the arrow head (if closed). `NULL`
+#' @param arrow.fill fill colour to use for the arrow head (if closed). `NULL`
 #'        means use `colour` aesthetic.
 #' @param lineend Line end style (round, butt, square).
 #' @param linejoin Line join style (round, mitre, bevel).