import matplotlib.pyplot as plt

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.grouped_bar

grouped_bar

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()