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# numpy.intersect1d() function in Python

`numpy.intersect1d()` function find the intersection of two arrays and return the sorted, unique values that are in both of the input arrays.

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.

Code #1 :

 `# Python program explaining ` `# numpy.intersect1d() function ` `    `  `# importing numpy as geek  ` `import` `numpy as geek  ` `   `  `arr1 ``=` `geek.array([``1``, ``1``, ``2``, ``3``, ``4``]) ` `arr2 ``=` `geek.array([``2``, ``1``, ``4``, ``6``]) ` `   `  `gfg ``=` `geek.intersect1d(arr1, arr2) ` `   `  `print` `(gfg) `

Output :

```[1 2 4]
```

Code #2 :

 `# Python program explaining ` `# numpy.intersect1d() function ` `    `  `# importing numpy as geek  ` `import` `numpy as geek  ` `   `  `arr1 ``=` `[``1``, ``2``, ``3``, ``4``, ``5``, ``6``, ``7``, ``8``, ``9``] ` `arr2 ``=` `[``1``, ``3``, ``5``, ``7``, ``9``] ` `   `  `gfg ``=` `geek.intersect1d(arr1, arr2) ` `   `  `print` `(gfg) `

Output :

```[1 3 5 7 9]
```

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