Number of observations in a plot panel

stat_panel_counts() counts the number of observations in each panel. stat_group_counts() counts the number of observations in each group. By default they add one or more text labels to the top right corner of each panel. Grouping is ignored by stat_panel_counts(). If no grouping exists, the two statistics behave similarly.

Usage

stat_panel_counts(
  mapping = NULL,
  data = NULL,
  geom = "text_npc",
  position = "identity",
  label.x = "right",
  label.y = "top",
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE,
  ...
)

stat_group_counts(
  mapping = NULL,
  data = NULL,
  geom = "text_npc",
  position = "identity",
  label.x = "right",
  label.y = "top",
  hstep = 0,
  vstep = NULL,
  digits = 2,
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping: The aesthetic mapping, usually constructed with aes or aes_. Only needs to be set at the layer level if you are overriding the plot defaults.
data: A layer specific dataset. Rarely used, as you will not want to override the plot defaults.
geom: The geometric object to use display the data
position: The position adjustment to use on this layer
label.x, label.y: numeric Coordinates (in npc units) to be used for absolute positioning of the labels.
na.rm: a logical indicating whether NA values should be stripped before the computation proceeds.
show.legend: logical. Should this layer be included in the legends? NA, the default, includes it if any aesthetics are mapped. FALSE never includes, and TRUE always includes.
inherit.aes: If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and should not inherit behaviour from the default plot specification, e.g., borders.
...: other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details.
hstep, vstep: numeric in npc units, the horizontal and vertical step used between labels for different groups.
digits: integer Number of digits for fraction and percent labels.

Value

A plot layer instance. Using as output data the counts of observations in each plot panel or per group in each plot panel.

Details

These statistics can be used to automatically count observations in each panel of a plot, and by default add these counts as text labels. These statistics, unlike stat_quadrant_counts() requires only one of x or y aesthetics and can be used together with statistics that have the same requirement, like stat_density().

The default position of the label is in the top right corner. When using facets even with free limits for x and y axes, the location of the labels is consistent across panels. This is achieved by use of geom = "text_npc" or geom = "label_npc". To pass the positions in native data units to label.x and label.y, pass also explicitly geom = "text", geom = "label" or some other geometry that use the x and/or y aesthetics. A vector with the same length as the number of panels in the figure can be used if needed.

Note

If a factor is mapped to x or to y aesthetics each level of the factor constitutes a group, in this case the default positioning and geom using NPC pseudo aesthetics will have to be overriden by passing geom = "text" and data coordinates used. The default for factors may change in the future.

Computed variables

Data frame with one or more rows, one for each group of observations for which counts are counted in data.

x,npcx: x value of label position in data- or npc units, respectively
y,npcy: y value of label position in data- or npc units, respectively
count: number of observations as an integer
count.label: number of observations as character

As shown in one example below geom_debug can be used to print the computed values returned by any statistic. The output shown includes also values mapped to aesthetics, like label in the example. x and y are included in the output only if mapped.

Examples


# generate artificial data with numeric x and y
set.seed(67821)
x <- 1:100
y <- rnorm(length(x), mean = 10)
group <- factor(rep(c("A", "B"), times = 50))
my.data <- data.frame(x, y, group)

# using automatically generated text labels

ggplot(my.data, aes(x, y)) +
  geom_point() +
  stat_panel_counts()


ggplot(my.data, aes(x, y, colour = group)) +
  geom_point() +
  stat_panel_counts()


ggplot(my.data, aes(x, y, colour = group)) +
  geom_point() +
  stat_group_counts()


ggplot(my.data, aes(x, y, colour = group)) +
  geom_point() +
  stat_group_counts(label.x = "left", hstep = 0.06, vstep = 0)


ggplot(my.data, aes(x, y, colour = group)) +
  geom_point() +
  stat_group_counts(aes(label = after_stat(pc.label)))


ggplot(my.data, aes(x, y, colour = group)) +
  geom_point() +
  stat_group_counts(aes(label = after_stat(pc.label)), digits = 3)


ggplot(my.data, aes(x, y, colour = group)) +
  geom_point() +
  stat_group_counts(aes(label = after_stat(fr.label)))


ggplot(my.data, aes(x, y, colour = group)) +
  geom_point() +
  stat_group_counts(aes(label = after_stat(dec.label)))


# one of x or y can be a factor
# label.x or label.y along the factor can be set to "factor" together
# with the use of geom_text()

ggplot(mpg,
       aes(factor(cyl), hwy)) +
  stat_boxplot() +
  stat_group_counts(geom = "text",
                    label.y = 10,
                    label.x = "factor") +
  stat_panel_counts()


# Numeric values can be used to build labels with alternative formats
# Here with sprintf(), but paste() and format() also work.

ggplot(my.data, aes(x, y)) +
 geom_point() +
 stat_panel_counts(aes(label = sprintf("%i observations",
                                       after_stat(count)))) +
 scale_y_continuous(expand = expansion(mult = c(0.05, 0.12)))


ggplot(mpg,
       aes(factor(cyl), hwy)) +
  stat_boxplot() +
  stat_group_counts(geom = "text",
                    aes(label = sprintf("(%i)", after_stat(count))),
                    label.y = 10,
                    label.x = "factor")


ggplot(mpg,
       aes(factor(cyl), hwy)) +
  stat_boxplot() +
  stat_group_counts(aes(label = sprintf("n[%i]~`=`~%i",
                                        after_stat(x), after_stat(count))),
                    parse = TRUE,
                    geom = "text",
                    label.y = 10,
                    label.x = "factor") +
  stat_panel_counts(aes(label = sprintf("sum(n[i])~`=`~%i",
                                        after_stat(count))),
                    parse = TRUE)


# label position

ggplot(my.data, aes(y)) +
  stat_panel_counts(label.x = "left") +
  stat_density(alpha = 0.5)


ggplot(my.data, aes(y, colour = group)) +
  stat_group_counts(label.y = "top") +
  stat_density(aes(fill = group), alpha = 0.3)


# The numeric value can be used as a label as is

ggplot(mpg,
       aes(factor(cyl), hwy)) +
  stat_boxplot() +
  stat_group_counts(geom = "text",
                    aes(label = after_stat(count)),
                    label.x = "factor",
                    label.y = 10) +
  annotate(geom = "text", x = 0.55, y = 10, label = "n[i]~`=`", parse = TRUE)


# We use geom_debug() to see the computed values

gginnards.installed <- requireNamespace("gginnards", quietly = TRUE)
if (gginnards.installed) {
  library(gginnards)

  ggplot(my.data, aes(x, y)) +
    geom_point() +
    stat_panel_counts(geom = "debug")
}

#> [1] "PANEL 1; group(s) NULL; 'draw_function()' input 'data' (head):"
#>   npcx npcy label PANEL     x        y count count.label
#> 1   NA   NA n=100     1 95.05 12.28333   100       n=100

if (gginnards.installed) {
  ggplot(my.data, aes(x, y, colour = group)) +
    geom_point() +
    stat_group_counts(geom = "debug")
}

#> [1] "PANEL 1; group(s) 1, 2; 'draw_function()' input 'data' (head):"
#>    colour npcx npcy label   x        y PANEL group count total count.label
#> 1 #F8766D   NA   NA  n=50 100 12.54082     1     1    50   100        n=50
#> 2 #00BFC4   NA   NA  n=50 100 12.28333     1     2    50   100        n=50
#>   pc.label dec.label fr.label
#> 1    p=50%    f=0.50 50 / 100
#> 2    p=50%    f=0.50 50 / 100