# 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

## 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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