Created
August 16, 2017 06:26
-
-
Save kevingduck/3c3643aaa9fb2cea10435f95c317322e to your computer and use it in GitHub Desktop.
Histogram Demo.py
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# coding: utf-8 | |
''' | |
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 a probability density. | |
* Setting the face color of the bars | |
* Setting the opacity (alpha value). | |
''' | |
import numpy as np | |
import matplotlib.mlab as mlab | |
import matplotlib.pyplot as plt | |
# example data | |
mu = 100 # mean of distribution | |
sigma = 15 # standard deviation of distribution | |
x = mu + sigma * np.random.randn(10000) | |
num_bins = 50 | |
# the histogram of the data | |
n, bins, patches = plt.hist(x, num_bins, normed=1, facecolor='green', alpha=0.5) | |
# add a 'best fit' line | |
y = mlab.normpdf(bins, mu, sigma) | |
plt.plot(bins, y, 'r--') | |
plt.xlabel('Smarts') | |
plt.ylabel('Probability') | |
plt.title(r'Histogram of IQ: $\mu=100$, $\sigma=15$') | |
# Tweak spacing to prevent clipping of ylabel | |
plt.subplots_adjust(left=0.15) | |
plt.show() |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment