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# numpy.amin

`numpy.``amin`(a, axis=None, out=None)

  Return the minimum along an axis.

  Parameters: | a : array_like Input data. axis : int, optional Axis along which to operate. By default a flattened input is used. out : ndarray, optional Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output.
  Returns: | amin : ndarray A new array or a scalar with the result, or a reference to out if it was specified.

  See also

  `nanmin`
    nan values are ignored instead of being propagated
  `fmin`
    same behavior as the C99 fmin function

  Notes

  NaN values are propagated, that is if at least one item is nan, the corresponding min value will be nan as well. To ignore NaN values (matlab behavior), please use nanmin.

  Examples

      >>> a = np.arange(4).reshape((2,2))
      >>> a
      array([[0, 1],
             [2, 3]])
      >>> np.amin(a)           # Minimum of the flattened array
      0
      >>> np.amin(a, axis=0)         # Minima along the first axis
      array([0, 1])
      >>> np.amin(a, axis=1)         # Minima along the second axis
      array([0, 2])

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