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Mastering Matplotlib Stepwise Histograms

labby

Labby

Posted on June 29, 2024

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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Import the necessary libraries and modules 

import matplotlib.pyplot as plt
import numpy as np

from matplotlib.patches import StepPatch
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Prepare the data 

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

plt.stairs(h, edges, label='Simple histogram')
plt.legend()
plt.show()
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Modify the baseline of the step histogram 

plt.stairs(h, edges + 5, baseline=50, label='Modified baseline')
plt.legend()
plt.show()
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Create a step histogram without edges 

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

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

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labby
Labby

Posted on June 29, 2024

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