# numpy.ma.sort¶

numpy.ma.sort(a, axis=-1, kind='quicksort', order=None, endwith=True, fill_value=None)[source]

Sort the array, in-place

Parameters: a : array_like Array to be sorted. axis : int, optional 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’}, optional Sorting algorithm. Default is ‘quicksort’. order : list, optional When a is a structured array, this argument specifies which fields to compare first, second, and so on. This list does not need to include all of the fields. endwith : {True, False}, optional Whether missing values (if any) should be forced in the upper indices (at the end of the array) (True) or lower indices (at the beginning). When the array contains unmasked values of the largest (or smallest if False) representable value of the datatype the ordering of these values and the masked values is undefined. To enforce the masked values are at the end (beginning) in this case one must sort the mask. fill_value : {var}, optional Value used internally for the masked values. If fill_value is not None, it supersedes endwith. sorted_array : ndarray Array of the same type and shape as a.

ndarray.sort
Method to sort an array in-place.
argsort
Indirect sort.
lexsort
Indirect stable sort on multiple keys.
searchsorted
Find elements in a sorted array.

Notes

See sort for notes on the different sorting algorithms.

Examples

```>>> a = ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
>>> # Default
>>> a.sort()
>>> print(a)
[1 3 5 -- --]
```
```>>> a = ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
>>> # Put missing values in the front
>>> a.sort(endwith=False)
>>> print(a)
[-- -- 1 3 5]
```
```>>> a = ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
>>> # fill_value takes over endwith
>>> a.sort(endwith=False, fill_value=3)
>>> print(a)
[1 -- -- 3 5]
```

numpy.ma.argsort