# numpy.ma.masked_array.sort

`masked_array.``sort`(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). 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]