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In this chapter, we will discuss about NumPy resize. This function returns a new array with the specified size. If the new size is greater than the original, the repeated copies of entries in the original are contained. The function takes the following parameters.

numpy.resize(arr, shape)

Where,

Sr.No.	Parameter & Description
1	arrInput array to be resized
2	shape new shape of the resulting array

Example Of NumPy resize

import numpy as np 
a = np.array([[1,2,3],[4,5,6]]) 

print 'First array:' 
print a 
print '\n'

print 'The shape of first array:' 
print a.shape 
print '\n'  
b = np.resize(a, (3,2)) 

print 'Second array:' 
print b 
print '\n'  

print 'The shape of second array:' 
print b.shape 
print '\n'  
# Observe that first row of a is repeated in b since size is bigger 

print 'Resize the second array:' 
b = np.resize(a,(3,3)) 
print b

The above program will produce the following output −

First array:
[[1 2 3]
 [4 5 6]]

The shape of first array:
(2, 3)

Second array:
[[1 2]
 [3 4]
 [5 6]]

The shape of second array:
(3, 2)

Resize the second array:
[[1 2 3]
 [4 5 6]
 [1 2 3]]