Note

Click here to download the full example code

In addition to the basic histogram, this demo shows a few optional features:

Setting the number of data bins.
The normed flag, which normalizes bin heights so that the integral of the histogram is 1. The resulting histogram is an approximation of the probability density function.
Setting the face color of the bars.
Setting the opacity (alpha value).

Selecting different bin counts and sizes can significantly affect the shape of a histogram. The Astropy docs have a great section on how to select these parameters.

import matplotlib
import numpy as np
import matplotlib.pyplot as plt
np.random.seed(19680801)
# example data
mu = 100  # mean of distribution
sigma = 15  # standard deviation of distribution
x = mu + sigma * np.random.randn(437)
num_bins = 50
fig, ax = plt.subplots()
# the histogram of the data
n, bins, patches = ax.hist(x, num_bins, density=1)
# add a 'best fit' line
y = ((1 / (np.sqrt(2 * np.pi) * sigma)) *
     np.exp(-0.5 * (1 / sigma * (bins - mu))**2))
ax.plot(bins, y, '--')
ax.set_xlabel('Smarts')
ax.set_ylabel('Probability density')
ax.set_title(r'Histogram of IQ: $\mu=100$, $\sigma=15$')
# Tweak spacing to prevent clipping of ylabel
fig.tight_layout()
plt.show()

../../_images/sphx_glr_histogram_features_001.png

References¶

The use of the following functions and methods is shown in this example:

matplotlib.axes.Axes.hist
matplotlib.axes.Axes.set_title
matplotlib.axes.Axes.set_xlabel
matplotlib.axes.Axes.set_ylabel

Out:

<function Axes.set_ylabel at 0x7fb11b446c80>

Keywords: matplotlib code example, codex, python plot, pyplot Gallery generated by Sphinx-Gallery