Histograms are graphical representations of a probability distribution. In fact, a histogram is just a specific kind of a bar chart. We could easily use matplotlib's bar chart function and do some statistics to generate histograms. However, histograms are so useful that matplotlib provides a function just for them. In this recipe, we are going to see how to use this histogram function.
The following script draws 1000 values from a normal distribution and then generates histograms with 20 bins:
import numpy as np import matplotlib.pyplot as plt X = np.random.randn(1000) plt.hist(X, bins = 20) plt.show()
The histogram will change a bit each time we run the script as the dataset is randomly generated. The preceding script will display the following graph:
The pyplot.hist() function takes a list of values as the input. The range of the values will be divided into equal-sized bins (10 bins by default). The pyplot.hist() function will generate a bar chart, one bar for one bin. The height of one bar is the number of values following in the corresponding bin. The number of bins is determined by the optional parameter bins. By setting the optional parameter normed to True, the bar height is normalized and the sum of all bar heights is equal to 1.