# numpy.partition() in Python

`numpy.partition() `function is used to create a partitioned copy of input array with its elements rearranged in such a way that the value of the element in k-th position is in the position it would be in a sorted array. All elements smaller than the k-th element are moved before this element and all equal or greater are moved behind it. The ordering of the elements in the two partitions is undefined.

Syntax : numpy.partition(arr, kth, axis=-1, kind=’introselect’, order=None)

Parameters :
arr : [array_like] Input array.
kth : [int or sequence of ints ] Element index to partition by.
axis : [int or None] Axis along which to sort. If None, the array is flattened before sorting. The default is -1, which sorts along the last axis.
kind : Selection algorithm. Default is ‘introselect’.
order : [str or list of str] When arr is an array with fields defined, this argument specifies which fields to compare first, second, etc.

Return : [ndarray] Partitioned array of the same type and shape as arr.

Code #1 :

 `# Python program explaining ` `# partition() function ` `  `  `import` `numpy as geek ` ` `  `# input array ` `in_arr ``=` `geek.array([ ``2``, ``0``,  ``1``, ``5``, ``4``, ``9``]) ` `print` `(``"Input array : "``, in_arr)  ` ` `  `out_arr ``=` `geek.partition(in_arr, ``3``) ` `print` `(``"Output partitioned array : "``, out_arr) `

Output:

```Input array :  [2 0 1 5 4 9]
Output partitioned array :  [0 1 2 4 5 9]
```

Code #2 :

 `# Python program explaining ` `# partition() function ` `  `  `import` `numpy as geek ` ` `  `# input array ` `in_arr ``=` `geek.array([ ``2``, ``0``,  ``1``, ``5``, ``4``, ``9``, ``3``]) ` `print` `(``"Input array : "``, in_arr)  ` ` `  `out_arr ``=` `geek.partition(in_arr, (``0``, ``3``)) ` `print` `(``"Output partitioned array : "``, out_arr) `

Output:

```Input array :  [2 0 1 5 4 9 3]
Output partitioned array :  [0 1 2 3 4 9 5]
```

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