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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)

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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


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)


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


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")
# use the np.intersect1d method
c = np.intersect1d(a,b)
# Display result
print("Common values",c)


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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