Created
June 26, 2017 10:49
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""" | |
========================================================= | |
Demo of the histogram (hist) function with a few features | |
========================================================= | |
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: | |
http://docs.astropy.org/en/stable/visualization/histogram.html | |
""" | |
import numpy as np | |
import matplotlib.mlab as mlab | |
import matplotlib.pyplot as plt | |
np.random.seed(0) | |
# 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, normed=1) | |
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() |
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