Mastering Matplotlib Stepwise Histograms

Introduction

Matplotlib is a data visualization library in Python. It is widely used for creating a wide range of visualizations like line plots, scatter plots, bar plots, histograms, and more. This tutorial will focus on creating stepwise histograms using Matplotlib.

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Skills Graph

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Import the necessary libraries and modules

import matplotlib.pyplot as plt
import numpy as np

from matplotlib.patches import StepPatch

Prepare the data

np.random.seed(0)
h, edges = np.histogram(np.random.normal(5, 3, 5000),
                        bins=np.linspace(0, 10, 20))

Create a simple step histogram

plt.stairs(h, edges, label='Simple histogram')
plt.legend()
plt.show()

Modify the baseline of the step histogram

plt.stairs(h, edges + 5, baseline=50, label='Modified baseline')
plt.legend()
plt.show()

Create a step histogram without edges

plt.stairs(h, edges + 10, baseline=None, label='No edges')
plt.legend()
plt.show()

Create a filled histogram

plt.stairs(np.arange(1, 6, 1), fill=True,
              label='Filled histogram\nw/ automatic edges')
plt.legend()
plt.show()

Create a hatched histogram

plt.stairs(np.arange(1, 6, 1)*0.3, np.arange(2, 8, 1),
              orientation='horizontal', hatch='//',
              label='Hatched histogram\nw/ horizontal orientation')
plt.legend()
plt.show()

Create a StepPatch artist

patch = StepPatch(values=[1, 2, 3, 2, 1],
                  edges=range(1, 7),
                  label=('Patch derived underlying object\n'
                         'with default edge/facecolor behaviour'))
plt.gca().add_patch(patch)
plt.xlim(0, 7)
plt.ylim(-1, 5)
plt.legend()
plt.show()

Create stacked histograms

A = [[0, 0, 0],
     [1, 2, 3],
     [2, 4, 6],
     [3, 6, 9]]

for i in range(len(A) - 1):
    plt.stairs(A[i+1], baseline=A[i], fill=True)
plt.show()

Compare `.pyplot.step` and `.pyplot.stairs`

bins = np.arange(14)
centers = bins[:-1] + np.diff(bins) / 2
y = np.sin(centers / 2)

plt.step(bins[:-1], y, where='post', label='step(where="post")')
plt.plot(bins[:-1], y, 'o--', color='grey', alpha=0.3)

plt.stairs(y - 1, bins, baseline=None, label='stairs()')
plt.plot(centers, y - 1, 'o--', color='grey', alpha=0.3)
plt.plot(np.repeat(bins, 2), np.hstack([y[0], np.repeat(y, 2), y[-1]]) - 1,
         'o', color='red', alpha=0.2)

plt.legend()
plt.title('step() vs. stairs()')
plt.show()

Summary

This tutorial covered the basics of creating stepwise histograms using Matplotlib. We learned how to create simple step histograms, modify the baseline of histograms, create filled and hatched histograms, and create stacked histograms. We also compared the differences between .pyplot.step and .pyplot.stairs.

Matplotlib Stepwise Histogram Tutorial