Matplotlib now allows Vectorized hist style parameters

[EwoutH]

Matplotlib now allows Vectorized hist style parameters, which might be useful for the Seaborn implementation of histplot.

• https://matplotlib.org/devdocs/users/next_whats_new/histogram_vectorized_parameters.html

The parameters hatch, edgecolor, facecolor, linewidth and linestyle of the hist method are now vectorized. This means that you can pass in individual parameters for each histogram when the input x has multiple datasets.

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(19680801)

fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(9, 9))

data1 = np.random.poisson(5, 1000)
data2 = np.random.poisson(7, 1000)
data3 = np.random.poisson(10, 1000)

labels = ["Data 1", "Data 2", "Data 3"]

ax1.hist([data1, data2, data3], bins=range(17), histtype="step", stacked=True,
         edgecolor=["red", "green", "blue"], linewidth=[1, 2, 3])
ax1.set_title("Different linewidths")
ax1.legend(labels)

ax2.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
         hatch=["/", ".", "*"])
ax2.set_title("Different hatch patterns")
ax2.legend(labels)

ax3.hist([data1, data2, data3], bins=range(17), histtype="bar", fill=False,
         edgecolor=["red", "green", "blue"], linestyle=["--", "-.", ":"])
ax3.set_title("Different linestyles")
ax3.legend(labels)

ax4.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
         facecolor=["red", "green", "blue"])
ax4.set_title("Different facecolors")
ax4.legend(labels)

plt.show()

[mwaskom]

Neat — but histplot does not use ax.hist under the hood.

[EwoutH]

Thanks, didn’t know that