Created
March 23, 2019 20:36
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matplotlib.axes.Axes.bar does not support stacking out of the box. pandas.DataFrame.plot.bar does support stacking, but not ordered stacking. Here is an implementation of ordered stacking.
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import matplotlib.pyplot as plt | |
import pandas as pd | |
import numpy as np | |
a = pd.DataFrame({'a':[0.25, 0.5, 0.15, 0], 'b':[0.15, 0.25, 0.35, 0.15], | |
'c':[0.50, 0.15, 0.5, 0.35], 'd':[0.35, 0.35, 0.25, 0.5],}) | |
fig, ax = plt.subplots() | |
x = a.index | |
indexes = np.argsort(a.values).T | |
heights = np.sort(a.values).T | |
order = -1 | |
bottoms = heights[::order].cumsum(axis=0) | |
bottoms = np.insert(bottoms, 0, np.zeros(len(bottoms[0])), axis=0) | |
mpp_colors = dict(zip(a.columns, plt.rcParams['axes.prop_cycle'].by_key()['color'])) | |
for btms, (idxs, vals) in enumerate(list(zip(indexes, heights))[::order]): | |
mps = np.take(np.array(a.columns), idxs) | |
ax.bar(x, height=vals, bottom=bottoms[btms], color=[mpp_colors[m] for m in mps]) | |
ax.set_ylim(bottom=0, top=2) | |
plt.legend((np.take(np.array(a.columns), np.argsort(a.values)[0]))[::order], loc='upper right') |
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