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
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.
Want to learn more?
- 🚀 Practice Matplotlib Stepwise Histogram Tutorial
- 🌳 Learn the latest Matplotlib Skill Trees
- 📖 Read More Matplotlib Tutorials
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