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ENH: Add grouped_bar() method #28560

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15 changes: 15 additions & 0 deletions doc/_embedded_plots/grouped_bar.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,15 @@
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()
1 change: 1 addition & 0 deletions doc/api/axes_api.rst
Original file line number Diff line number Diff line change
Expand Up @@ -67,6 +67,7 @@ Basic
Axes.bar
Axes.barh
Axes.bar_label
Axes.grouped_bar

Axes.stem
Axes.eventplot
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1 change: 1 addition & 0 deletions doc/api/pyplot_summary.rst
Original file line number Diff line number Diff line change
Expand Up @@ -61,6 +61,7 @@ Basic
bar
barh
bar_label
grouped_bar
stem
eventplot
pie
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26 changes: 26 additions & 0 deletions doc/users/next_whats_new/grouped_bar.rst
Original file line number Diff line number Diff line change
@@ -0,0 +1,26 @@
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
:alt: Diagram of a grouped bar chart of 3 datasets with 2 categories.

import matplotlib.pyplot as plt

categories = ['A', 'B']
datasets = {
'dataset 0': [1, 11],
'dataset 1': [3, 13],
'dataset 2': [5, 15],
}

fig, ax = plt.subplots()
ax.grouped_bar(datasets, tick_labels=categories)
ax.legend()
16 changes: 4 additions & 12 deletions galleries/examples/lines_bars_and_markers/barchart.py
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,6 @@
# data from https://allisonhorst.github.io/palmerpenguins/

import matplotlib.pyplot as plt
import numpy as np

species = ("Adelie", "Chinstrap", "Gentoo")
penguin_means = {
Expand All @@ -19,22 +18,15 @@
'Flipper Length': (189.95, 195.82, 217.19),
}

x = np.arange(len(species)) # the label locations
width = 0.25 # the width of the bars
multiplier = 0

fig, ax = plt.subplots(layout='constrained')

for attribute, measurement in penguin_means.items():
offset = width * multiplier
rects = ax.bar(x + offset, measurement, width, label=attribute)
ax.bar_label(rects, padding=3)
multiplier += 1
res = ax.grouped_bar(penguin_means, tick_labels=species, group_spacing=1)
for container in res.bar_containers:
ax.bar_label(container, padding=3)

# Add some text for labels, title and custom x-axis tick labels, etc.
# Add some text for labels, title, etc.
ax.set_ylabel('Length (mm)')
ax.set_title('Penguin attributes by species')
ax.set_xticks(x + width, species)
ax.legend(loc='upper left', ncols=3)
ax.set_ylim(0, 250)

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