# numpy.vsplit() function | Python

• Last Updated : 22 Apr, 2020

`numpy.vsplit()` function split an array into multiple sub-arrays vertically (row-wise). vsplit is equivalent to split with axis=0 (default), the array is always split along the first axis regardless of the array dimension.

Syntax : numpy.vsplit(arr, indices_or_sections)
Parameters :
arr : [ndarray] Array to be divided into sub-arrays.
indices_or_sections : [int or 1-D array] If indices_or_sections is an integer, N, the array will be divided into N equal arrays along axis.
If indices_or_sections is a 1-D array of sorted integers, the entries indicate where along axis the array is split
Return : [ndarray] A list of sub-arrays.

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Code #1 :

 `# Python program explaining``# numpy.vsplit() function`` ` `# importing numpy as geek ``import` `numpy as geek`` ` `arr ``=` `geek.arange(``9.0``).reshape(``3``, ``3``)`` ` `gfg ``=` `geek.vsplit(arr, ``1``)`` ` `print` `(gfg)`

Output :

```[array([[ 0.,  1.,  2.],
[ 3.,  4.,  5.],
[ 6.,  7.,  8.]])]
```

Code #2 :

 `# Python program explaining``# numpy.vsplit() function`` ` `# importing numpy as geek ``import` `numpy as geek`` ` `arr ``=` `geek.arange(``36.0``).reshape(``6``, ``6``)`` ` `gfg ``=` `geek.vsplit(arr, ``2``)`` ` `print` `(gfg)`

Output :

```[array([[  0.,   1.,   2.,   3.,   4.,   5.],
[  6.,   7.,   8.,   9.,  10.,  11.],
[ 12.,  13.,  14.,  15.,  16.,  17.]]), array([[ 18.,  19.,  20.,  21.,  22.,  23.],
[ 24.,  25.,  26.,  27.,  28.,  29.],
[ 30.,  31.,  32.,  33.,  34.,  35.]])]
```

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