# Numpy recarray.argsort() function | Python

In numpy, arrays may have a data-types containing fields, analogous to columns in a spreadsheet. An example is `[(a, int), (b, float)]`, where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as `arr['a'] and arr['b']`.

Record arrays allow the fields to be accessed as members of the array, using `arr.a and arr.b`. `numpy.recarray.argsort() ` function returns the indices that would sort this array.

Syntax : `numpy.recarray.argsort(arr, axis=-1, kind='quicksort', order=None)`

Parameters:
arr : Input Record array.
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 : [‘quicksort’, ‘mergesort’, ‘heapsort’]Selection algorithm. Default is ‘quicksort’.
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 : [index_array, ndarray] Array of indices that sort arr along the specified axis.

Code #1 :

 `# Python program explaining ` `# numpy.recarray.argsort() method  ` ` `  `# importing numpy as geek ` `import` `numpy as geek ` ` `  `# creating input array with 2 different field  ` `in_arr ``=` `geek.array([[(``5.0``, ``2``), (``3.0``, ``-``4``), (``6.0``, ``9``)], ` `                     ``[(``9.0``, ``1``), (``5.0``, ``4``), (``-``12.0``, ``-``7``)]], ` `                     ``dtype ``=``[(``'a'``, ``float``), (``'b'``, ``int``)]) ` `print` `(``"Input array : "``, in_arr) ` ` `  `# convert it to a record array,  ` `# using arr.view(np.recarray) ` `rec_arr ``=` `in_arr.view(geek.recarray) ` `print``(``"Record array of float: "``, rec_arr.a) ` `print``(``"Record array of int: "``, rec_arr.b) ` ` `  `# applying recarray.argsort methods  ` `# to float record array along axis 1 ` `out_arr ``=` `geek.recarray.argsort(rec_arr.a, axis ``=` `1``) ` `print` `(``"Output sorted array indices along axis 1: "``, out_arr)  ` ` `  `# applying recarray.argsort methods to ` `# int record array along axis 0 ` `out_arr ``=` `geek.recarray.argsort(rec_arr.b, axis ``=` `0``) ` `print` `(``"Output sorted array indices array along axis 0: "``, out_arr)  `

Output:

```Input array :  [[(5.0, 2) (3.0, -4) (6.0, 9)]
[(9.0, 1) (5.0, 4) (-12.0, -7)]]
Record array of float:  [[  5.   3.   6.]
[  9.   5. -12.]]
Record array of int:  [[ 2 -4  9]
[ 1  4 -7]]
Output sorted array indices along axis 1:  [[1 0 2]
[2 1 0]]
Output sorted array indices array along axis 0:  [[1 0 1]
[0 1 0]]
```

Code #2 :

We are applying `numpy.recarray.argsort()` to whole record array.

 `# Python program explaining ` `# numpy.recarray.argsort() method  ` ` `  `# importing numpy as geek ` `import` `numpy as geek ` ` `  `# creating input array with 2 different field  ` `in_arr ``=` `geek.array([[(``5.0``, ``2``), (``3.0``, ``4``), (``6.0``, ``-``7``)], ` `                     ``[(``9.0``, ``1``), (``6.0``, ``4``), (``-``2.0``, ``-``7``)]], ` `                     ``dtype ``=``[(``'a'``, ``float``), (``'b'``, ``int``)]) ` `print` `(``"Input array : "``, in_arr) ` ` `  `# convert it to a record array,  ` `# using arr.view(np.recarray) ` `rec_arr ``=` `in_arr.view(geek.recarray) ` ` `  `# applying recarray.argsort methods to  record array ` `out_arr ``=` `geek.recarray.argsort(rec_arr, kind ``=``'heapsort'``) ` ` `  `print` `(``"Output array : "``, out_arr) `

Output:

```Input array :  [[(5.0, 2) (3.0, 4) (6.0, -7)]
[(9.0, 1) (6.0, 4) (-2.0, -7)]]
Output sorted array indices :  [[1 0 2]
[2 1 0]]
```

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