sciPy stats.histogram() function | Python

scipy.stats.histogram(a, numbins, defaultreallimits, weights, printextras) works to segregate the range into several bins and then returns the number of instances in each bin. This function is used to build the histogram.

Parameters :
arr : [array_like] input array.
numbins : [int] number of bins to use for the histogram. [Default = 10]
defaultlimits : (lower, upper) range of the histogram.
weights : [array_like] weights for each array element.
printextras : [array_like] to print the no, if extra points to the standard output, if true

Results :
– cumulative frequency binned values
– width of each bin
– lower real limit
– extra points.

Code #1:

# building the histogram
import scipy
import numpy as np
import matplotlib.pyplot as plt

hist, bin_edges = scipy.histogram([1, 1, 2, 2, 2, 2, 3],
                                       bins = range(5))

# Checking the results
print ("No. of points in each bin : ", hist)
print ("Size of the bins          : ", bin_edges)

# plotting the histogram
plt.bar(bin_edges[:-1], hist, width = 1)
plt.xlim(min(bin_edges), max(bin_edges))
plt.show()

Output :

No. of points in each bin :  [0 2 4 1]
Size of the bins          :  [0 1 2 3 4]