geom_hist_ | R Documentation |
More general histogram (geom_histogram
) or bar plot (geom_bar
).
Both x
and y
could be accommodated. See details
geom_hist_(
mapping = NULL,
data = NULL,
stat = "hist_",
position = "stack_",
...,
scale.x = NULL,
scale.y = c("data", "group", "variable"),
as.mix = FALSE,
binwidth = NULL,
bins = NULL,
positive = TRUE,
prop = 0.9,
na.rm = FALSE,
orientation = NA,
show.legend = NA,
inherit.aes = TRUE
)
geom_histogram_(
mapping = NULL,
data = NULL,
stat = "bin_",
position = "stack_",
...,
scale.x = NULL,
scale.y = c("data", "group"),
as.mix = FALSE,
positive = TRUE,
prop = 0.9,
binwidth = NULL,
bins = NULL,
na.rm = FALSE,
orientation = NA,
show.legend = NA,
inherit.aes = TRUE
)
geom_bar_(
mapping = NULL,
data = NULL,
stat = "count_",
position = "stack_",
...,
scale.x = NULL,
scale.y = c("data", "group"),
positive = TRUE,
prop = 0.9,
na.rm = FALSE,
orientation = NA,
show.legend = NA,
inherit.aes = TRUE
)
stat_hist_(
mapping = NULL,
data = NULL,
geom = "bar_",
position = "stack_",
...,
binwidth = NULL,
bins = NULL,
center = NULL,
boundary = NULL,
breaks = NULL,
closed = c("right", "left"),
pad = FALSE,
width = NULL,
na.rm = FALSE,
orientation = NA,
show.legend = NA,
inherit.aes = TRUE
)
stat_bin_(
mapping = NULL,
data = NULL,
geom = "bar_",
position = "stack_",
...,
binwidth = NULL,
bins = NULL,
center = NULL,
boundary = NULL,
breaks = NULL,
closed = c("right", "left"),
pad = FALSE,
na.rm = FALSE,
orientation = NA,
show.legend = NA,
inherit.aes = TRUE
)
stat_count_(
mapping = NULL,
data = NULL,
geom = "bar_",
position = "stack_",
...,
width = NULL,
na.rm = FALSE,
orientation = NA,
show.legend = NA,
inherit.aes = TRUE
)
mapping |
Set of aesthetic mappings created by | ||||||
data |
The data to be displayed in this layer. There are three options: If A A | ||||||
position |
Position adjustment, either as a string, or the result of a call to a position adjustment function.
Function | ||||||
... |
Other arguments passed on to | ||||||
scale.x |
A sorted length 2 numerical vector representing the range of the whole data will be scaled to. The default value is (0, 1). | ||||||
scale.y |
one of
If the | ||||||
as.mix |
Logical. Within each group, if | ||||||
binwidth |
The width of the bins. Can be specified as a numeric value
or as a function that calculates width from unscaled x. Here, "unscaled x"
refers to the original x values in the data, before application of any
scale transformation. When specifying a function along with a grouping
structure, the function will be called once per group.
The default is to use the number of bins in The bin width of a date variable is the number of days in each time; the bin width of a time variable is the number of seconds. | ||||||
bins |
Number of bins. Overridden by | ||||||
positive |
If | ||||||
prop |
adjust the proportional maximum height of the estimate (density, histogram, ...). | ||||||
na.rm |
If | ||||||
orientation |
The orientation of the layer. The default ( | ||||||
show.legend |
logical. Should this layer be included in the legends?
| ||||||
inherit.aes |
If | ||||||
geom , stat |
Use to override the default connection between geom_hist_()/geom_histogram_()/geom_bar_() and stat_hist_()/stat_bin_()/stat_count_(). | ||||||
center , boundary |
bin position specifiers. Only one, | ||||||
breaks |
Alternatively, you can supply a numeric vector giving
the bin boundaries. Overrides | ||||||
closed |
One of | ||||||
pad |
If | ||||||
width |
Bar width. By default, set to 90% of the |
x
(or y
) is a group variable (categorical) and y
(or x
) a target variable (numerical) to be plotted.
If only one of x
or y
is provided, it will treated as a target variable and
ggplot2::geom_histogram
will be executed. Several things should be noticed:
1. If both x
and y
are given, they can be one discrete one continuous or
two discrete. But they cannot be two continuous variables (which one will be considered as a group variable?).
2. geom_hist_
is a wrapper of geom_histogram_
and geom_count_
.
Suppose the y
is our interest (x
is the categorical variable),
geom_hist_()
can accommodate either continuous or discrete y
. While,
geom_histogram_()
only accommodates the continuous y
and
geom_bar_()
only accommodates the discrete y
.
3. There are four combinations of scale.y
and as.mix
.
scale.y
= "group" and as.mix
= FALSEThe density estimate area of each subgroup (represented by each color) within the same group is the same.
scale.y
= "group" and as.mix
= TRUEThe density estimate area of each subgroup (represented by each color) within the same group is proportional to its own counts.
scale.y
= "data" and as.mix
= FALSEThe sum of density estimate area of all groups is scaled to maximum of 1. and the density area for each group is proportional to the its count. Within each group, the area of each subgroup is the same.
scale.y
= "data" and as.mix
= TRUEThe sum of density estimate area of all groups is scaled to maximum of 1 and the area of each subgroup (represented by each color) is proportional to its own count.
See vignettes[https://great-northern-diver.github.io/ggmulti/articles/histogram-density-.html] for more intuitive explanation.
Note that, if it is a grouped bar chart (both x
and y
are categorical),
parameter 'as.mix' is meaningless.
This geom treats each axis differently and, thus, can thus have two orientations. Often the orientation is easy to deduce from a combination of the given mappings and the types of positional scales in use. Thus, ggplot2 will by default try to guess which orientation the layer should have. Under rare circumstances, the orientation is ambiguous and guessing may fail. In that case the orientation can be specified directly using the orientation
parameter, which can be either "x"
or "y"
. The value gives the axis that the geom should run along, "x"
being the default orientation you would expect for the geom.
geom_histogram
, geom_density_
if(require(dplyr) && require(tidyr)) {
# histogram
p0 <- mpg %>%
dplyr::filter(manufacturer %in% c("dodge", "ford", "toyota", "volkswagen")) %>%
ggplot(mapping = aes(x = manufacturer, y = cty))
p0 + geom_hist_()
## set position
#### default is "stack_"
p0 + geom_hist_(mapping = aes(fill = fl))
#### "dodge_"
p0 + geom_hist_(position = "dodge_",
mapping = aes(fill = fl))
#### "dodge2_"
p0 + geom_hist_(position = "dodge2_",
mapping = aes(fill = fl))
# bar chart
mpg %>%
ggplot(mapping = aes(x = drv, y = class)) +
geom_hist_(orientation = "y")
# scale.y as "group"
p <- iris %>%
tidyr::pivot_longer(cols = -Species,
names_to = "Outer sterile whorls",
values_to = "x") %>%
ggplot(mapping = aes(x = `Outer sterile whorls`,
y = x, fill = Species)) +
stat_hist_(scale.y = "group",
prop = 0.6,
alpha = 0.5)
p
# with density on the left
p + stat_density_(scale.y = "group",
prop = 0.6,
alpha = 0.5,
positive = FALSE)
########### only `x` or `y` is provided ###########
# that would be equivalent to call function
# `geom_histogram()` or `geom_bar()`
### histogram
diamonds %>%
dplyr::sample_n(500) %>%
ggplot(mapping = aes(x = price)) +
geom_hist_()
### bar chart
diamonds %>%
dplyr::sample_n(500) %>%
ggplot(mapping = aes(x = cut)) +
geom_hist_()
}
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