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Aug 16, 2018
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example file for making a bar of pie chart #11865

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1 change: 1 addition & 0 deletions .flake8
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Original file line number Diff line number Diff line change
Expand Up @@ -182,6 +182,7 @@ per-file-ignores =
examples/misc/table_demo.py: E201
examples/mplot3d/voxels.py: E501
examples/mplot3d/wire3d_zero_stride.py: E501
examples/pie_and_polar_charts/bar_of_pie.py: E402
examples/pie_and_polar_charts/nested_pie.py: E402
examples/pie_and_polar_charts/pie_and_donut_labels.py: E402
examples/pie_and_polar_charts/pie_demo2.py: E402
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92 changes: 92 additions & 0 deletions examples/pie_and_polar_charts/bar_of_pie.py
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"""
==========
Bar of pie
==========
Make a "bar of pie" chart where the first slice of the pie is
"exploded" into a bar chart with a further breakdown of said slice's
characteristics. The example demonstrates using a figure with multiple
sets of axes and using the axes patches list to add two ConnectionPatches
to link the subplot charts.
"""

import matplotlib.pyplot as plt
from matplotlib.patches import ConnectionPatch
import numpy as np

# make figure and assign axis objects
fig = plt.figure(figsize=(9, 5.0625))
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
fig.subplots_adjust(wspace=0)

# pie chart parameters
ratios = [.27, .56, .17]
labels = ['Approve', 'Disapprove', 'Undecided']
explode = [0.1, 0, 0]
# rotate so that first wedge is split by the x-axis
angle = -180 * ratios[0]
ax1.pie(ratios, autopct='%1.1f%%', startangle=angle,
labels=labels, explode=explode)

# bar chart parameters

xpos = 0
bottom = 0
ratios = [.33, .54, .07, .06]
width = .2
colors = [[.1, .3, .5], [.1, .3, .3], [.1, .3, .7], [.1, .3, .9]]

for j in range(len(ratios)):
height = ratios[j]
ax2.bar(xpos, height, width, bottom=bottom, color=colors[j])
ypos = bottom + ax2.patches[j].get_height() / 2
bottom += height
ax2.text(xpos, ypos, "%d%%" % (ax2.patches[j].get_height() * 100),
ha='center')

ax2.set_title('Age of approvers')
ax2.legend(('50-65', 'Over 65', '35-49', 'Under 35'))
ax2.axis('off')
ax2.set_xlim(- 2.5 * width, 2.5 * width)

# use ConnectionPatch to draw lines between the two plots
# get the wedge data
theta1, theta2 = ax1.patches[0].theta1, ax1.patches[0].theta2
center, r = ax1.patches[0].center, ax1.patches[0].r
bar_height = sum([item.get_height() for item in ax2.patches])

# draw top connecting line
x = r * np.cos(np.pi / 180 * theta2) + center[0]
y = np.sin(np.pi / 180 * theta2) + center[1]
con = ConnectionPatch(xyA=(- width / 2, bar_height), xyB=(x, y),
coordsA="data", coordsB="data", axesA=ax2, axesB=ax1)
con.set_color([0, 0, 0])
con.set_linewidth(4)
ax2.add_artist(con)

# draw bottom connecting line
x = r * np.cos(np.pi / 180 * theta1) + center[0]
y = np.sin(np.pi / 180 * theta1) + center[1]
con = ConnectionPatch(xyA=(- width / 2, 0), xyB=(x, y), coordsA="data",
coordsB="data", axesA=ax2, axesB=ax1)
con.set_color([0, 0, 0])
ax2.add_artist(con)
con.set_linewidth(4)

plt.show()

#############################################################################
#
# ------------
#
# References
# """"""""""
#
# The use of the following functions, methods, classes and modules is shown
# in this example:

import matplotlib
matplotlib.axes.Axes.pie
matplotlib.axes.Axes.bar
matplotlib.pyplot
matplotlib.patches.ConnectionPatch