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# numpy.char.chararray.sort

method

char.chararray.sort(axis=-1, kind=None, order=None, *, stable=None, descending=None)

  Sort an array in-place. Refer to `numpy.sort` for full documentation.

  Parameters:
    axis int, optional

      Axis along which to sort. Default is -1, which means sort along the last axis.

    kind{‘quicksort’, ‘mergesort’, ‘heapsort’, ‘stable’}, optional

      Sorting algorithm. The default is ‘quicksort’. Note that both ‘stable’ and ‘mergesort’ use timsort under the covers and, in general, the actual implementation will vary with datatype. The ‘mergesort’ option is retained for backwards compatibility.

    order str or list of str, optional

      When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not all fields need be specified, but unspecified fields will still be used, in the order in which they come up in the dtype, to break ties.

    stable bool, optional

      Sort stability. If `True`, the returned array will maintain the relative order of `a` values which compare as equal. If `False` or `None`, this is not guaranteed. Internally, this option selects `kind='stable'`. Default: `None`.

      New in version 2.0.0.

  See also

  `numpy.sort`

    Return a sorted copy of an array.

  `numpy.argsort`

    Indirect sort.

  `numpy.lexsort`

    Indirect stable sort on multiple keys.

  `numpy.searchsorted`

    Find elements in sorted array.

  `numpy.partition`

    Partial sort.

  Notes

  See `numpy.sort` for notes on the different sorting algorithms.

  Examples

      >>> import numpy as np
      >>> a = np.array([[1,4], [3,1]])
      >>> a.sort(axis=1)
      >>> a
      array([[1, 4],
             [1, 3]])
      >>> a.sort(axis=0)
      >>> a
      array([[1, 3],
             [1, 4]])

  Use the order keyword to specify a field to use when sorting a structured array:

      >>> a = np.array([('a', 2), ('c', 1)], dtype=[('x', 'S1'), ('y', int)])
      >>> a.sort(order='y')
      >>> a
      array([(b'c', 1), (b'a', 2)],
            dtype=[('x', 'S1'), ('y', '<i8')])