importmatplotlib.pyplotasplt

categories= ['A','B']

data0= [1.0,3.0]

data1= [1.4,3.4]

data2= [1.8,3.8]

fig,ax=plt.subplots(figsize=(4,2.2))

ax.grouped_bar(

[data0,data1,data2],

tick_labels=categories,

labels=['dataset 0','dataset 1','dataset 2'],

colors=['#1f77b4','#58a1cf','#abd0e6'],

)

ax.legend()

Axes.bar

Axes.barh

Axes.bar_label

Axes.grouped_bar

Axes.stem

Axes.eventplot

bar

barh

bar_label

grouped_bar

stem

eventplot

pie

Grouped bar charts

The new method `~.Axes.grouped_bar()` simplifies the creation of grouped bar charts

significantly. It supports different input data types (lists of datasets, dicts of

datasets, data in 2D arrays, pandas DataFrames), and allows for easy customization

of placement via controllable distances between bars and between bar groups.

Example:

..plot::

:include-source: true

import matplotlib.pyplot as plt

categories = ['A', 'B']

datasets = {

'dataset 0': [1.0, 3.0],

'dataset 1': [1.4, 3.4],

'dataset 2': [1.8, 3.8],

}

fig, ax = plt.subplots(figsize=(4, 2.2))

ax.grouped_bar(datasets, tick_labels=categories)

ax.legend()