plotnine.geom_bar

Bar plot

geom_bar(
    mapping=None,
    data=None,
    *,
    stat="count",
    position="stack",
    na_rm=False,
    inherit_aes=True,
    show_legend=None,
    raster=False,
    just=0.5,
    width=None,
    **kwargs
)

Parameters

mapping : aes = None

Aesthetic mappings created with aes. If specified and inherit_aes=True, it is combined with the default mapping for the plot. You must supply mapping if there is no plot mapping.

Aesthetic	Default value
x
y
alpha	`1`
color	`None`
fill	`'#595959'`
group
linetype	`'solid'`
size	`0.5`

The bold aesthetics are required.

data : DataFrame = None

The data to be displayed in this layer. If None, the data from from the ggplot() call is used. If specified, it overrides the data from the ggplot() call.

stat : str | stat = "count"

The statistical transformation to use on the data for this layer. If it is a string, it must be the registered and known to Plotnine.

position : str | position = "stack"

Position adjustment. If it is a string, it must be registered and known to Plotnine.

na_rm : bool = False

If False, removes missing values with a warning. If True silently removes missing values.

inherit_aes : bool = True

If False, overrides the default aesthetics.

show_legend : bool | dict = None

Whether this layer should be included in the legends. None the default, includes any aesthetics that are mapped. If a bool, False never includes and True always includes. A dict can be used to exclude specific aesthetis of the layer from showing in the legend. e.g show_legend={'color': False}, any other aesthetic are included by default.

raster : bool = False

If True, draw onto this layer a raster (bitmap) object even ifthe final image is in vector format.

just : float = 0.5

How to align the column with respect to the axis breaks. The default 0.5 aligns the center of the column with the break. 0 aligns the left of the of the column with the break and 1 aligns the right of the column with the break.

width : float = None

Bar width. If None, the width is set to 90% of the resolution of the data.

**kwargs : Any

Aesthetics or parameters used by the stat.

Examples


from plotnine import ggplot, aes, geom_bar, labs, coord_flip, theme_classic
from plotnine.data import mpg

Bar chart

geom_bar() makes the height of the bar proportional to the number of cases in each group

mpg.head()

	manufacturer	model	displ	year	cyl	trans	drv	cty	hwy	fl	class
0	audi	a4	1.8	1999	4	auto(l5)	f	18	29	p	compact
1	audi	a4	1.8	1999	4	manual(m5)	f	21	29	p	compact
2	audi	a4	2.0	2008	4	manual(m6)	f	20	31	p	compact
3	audi	a4	2.0	2008	4	auto(av)	f	21	30	p	compact
4	audi	a4	2.8	1999	6	auto(l5)	f	16	26	p	compact

Bar Plot with Counts

# Gallery, distributions
ggplot(mpg) + geom_bar(aes(x="class"))

Sorting the bars

We can use the internal function reorder to sort the bars depending on the size of each group. In this case we create a variable class2 with values equal to those of class so because class is a reserved name and:

reorder(class, class, len)

is not a valid python expression, while:

reorder(class2, class2, len)

is a valid python expression.

mpg["class2"] = mpg["class"]

(
    ggplot(mpg)
    + geom_bar(aes(x="reorder(class2, class2, len)"))
    + labs(x="class")
)

And in descending order

(
    ggplot(mpg)
    + geom_bar(
        aes(x="reorder(class2, class2, len, ascending=False)")
    )
    + labs(x="class")
)

(
    ggplot(mpg)
    + geom_bar(aes(x="class", fill="drv"))
)

Horizontal Bar Plot with Counts

# Gallery, distributions
(
    ggplot(mpg) 
    + geom_bar(aes(x="class", fill="drv"))
    + coord_flip()
    + theme_classic()
)

Source: Bar chart