# numpy.vsplit() function | Python

`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.
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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