Find common values between two NumPy arrays

Last Updated : 29 Aug, 2020

In this article, we are going to discuss how to find out the common values between 2 arrays. To find the common values, we can use the numpy.intersect1d(), which will do the intersection operation and return the common values between the 2 arrays in sorted order.

Syntax: numpy.intersect1d(arr1, arr2, assume_unique = False, return_indices = False)

Parameters :
arr1, arr2 : [array_like] Input arrays.
assume_unique : [bool] If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False.
return_indices : [bool] If True, the indices which correspond to the intersection of the two arrays are returned. The first instance of a value is used if there are multiple. Default is False.

Return : [ndarray] Sorted 1D array of common and unique elements.

Example #1: Finding common values between 1d arrays

Python3

import numpy as np 
  
  
# create 2 arrays 
a = np.array([2, 4, 7, 1, 4]) 
b = np.array([7, 2, 9, 0, 5]) 
  
# Display the arrays 
print("Original arrays", a, ' ', b) 
  
# use the np.intersect1d method 
c = np.intersect1d(a, b) 
  
# Display result 
print("Common values", c) 

Output:

Original arrays [2 4 7 1 4]   [7 2 9 0 5]  Common values [2 7]

Example #2: Finding common values between n-dimensional arrays

Python3

import numpy as np 
  
  
# create 2 arrays 
a = np.array([2,4,7,1,4,9]).reshape(3,2) 
b = np.array([7,2,9,0,5,3]).reshape(2,3) 
  
# Display the arrays 
print("Original arrays") 
print(a) 
print(b) 
  
# use the np.intersect1d method 
c = np.intersect1d(a,b) 
  
# Display result 
print("Common values",c)

Output:

Original arrays  [[2 4]   [7 1]   [4 9]]  [[7 2 9]   [0 5 3]]  Common values [2 7 9]

Note: No matter what dimension arrays are passed, the common values will be returned in a 1d flattened manner

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