How to normalize a histogram in python?
When you plot a normalized histogram, it is not the height that should sum up to one, but the area underneath the curve should sum up to one:
In [44]:import matplotlib.pyplot as pltk=(3,3,3,3)x, bins, p=plt.hist(k, density=True) # used to be normed=True in older versionsfrom numpy import *plt.xticks( arange(10) ) # 10 ticks on x axisplt.show() In [45]:print bins[ 2.5 2.6 2.7 2.8 2.9 3. 3.1 3.2 3.3 3.4 3.5]Here, this example, the bin width is 0.1, the area underneath the curve sums up to one (0.1*10).
To have the sum of height to be 1, add the following before plt.show():
for item in p: item.set_height(item.get_height()/sum(x))
You could use the solution outlined here:
weights = np.ones_like(myarray)/float(len(myarray))plt.hist(myarray, weights=weights)
One way is to get the probabilities on your own, and then plot with plt.bar:
In [91]: from collections import Counter ...: c=Counter(k) ...: print cCounter({1: 2, 3: 1, 4: 1})In [92]: plt.bar(c.keys(), c.values()) ...: plt.show()result: