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# numpy.ma.sort

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

  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`.
  Returns: | sorted_array : ndarray Array of the same type and shape as a.

  See also

  `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]