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# numpy.diff

`numpy.``diff`(a, n=1, axis=-1)

  Calculate the n-th order discrete difference along given axis.

  The first order difference is given by `out[n] = a[n+1] - a[n]` along the given axis, higher order differences are calculated by using diff recursively.

  Parameters : | a : array_like Input array n : int, optional The number of times values are differenced. axis : int, optional The axis along which the difference is taken, default is the last axis.
  Returns : | out : ndarray The n order differences. The shape of the output is the same as a except along axis where the dimension is smaller by n.

  See also

  `gradient`, `ediff1d`

  Examples

      >>> x = np.array([1, 2, 4, 7, 0])
      >>> np.diff(x)
      array([ 1,  2,  3, -7])
      >>> np.diff(x, n=2)
      array([  1,   1, -10])

      >>> x = np.array([[1, 3, 6, 10], [0, 5, 6, 8]])
      >>> np.diff(x)
      array([[2, 3, 4],
             [5, 1, 2]])
      >>> np.diff(x, axis=0)
      array([[-1,  2,  0, -2]])

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