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# numpy.take

`numpy.``take`(a, indices, axis=None, out=None, mode='raise')

  Take elements from an array along an axis.

  This function does the same thing as “fancy” indexing (indexing arrays using arrays); however, it can be easier to use if you need elements along a given axis.

  Parameters: | a : array_like The source array. indices : array_like, int The indices of the values to extract. axis : int, optional The axis over which to select values. By default, the flattened input array is used. out : ndarray, optional If provided, the result will be placed in this array. It should be of the appropriate shape and dtype. mode : {‘raise’, ‘wrap’, ‘clip’}, optional Specifies how out-of-bounds indices will behave. ‘raise’ – raise an error ‘wrap’ – wrap around ‘clip’ – clip to the range
  Returns: | subarray : ndarray The returned array has the same type as a.

  See also

  `ndarray.take`
    equivalent method

  Examples

      >>> a = [4, 3, 5, 7, 6, 8]
      >>> indices = [0, 1, 4]
      >>> np.take(a, indices)
      array([4, 3, 6])

  In this example if a is a ndarray, “fancy” indexing can be used. >>> a = np.array(a) >>> a[indices] array([4, 3, 6])

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