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sciPy stats.histogram() function | Python

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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]

Last Updated : 13 Feb, 2019
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