# numpy.ma.masked_array.reshape

`masked_array.``reshape`(*s, **kwargs)

  Give a new shape to the array without changing its data.

  Returns a masked array containing the same data, but with a new shape. The result is a view on the original array; if this is not possible, a ValueError is raised.

  Parameters: | shape : int or tuple of ints The new shape should be compatible with the original shape. If an integer is supplied, then the result will be a 1-D array of that length. order : {‘C’, ‘F’}, optional Determines whether the array data should be viewed as in C (row-major) or FORTRAN (column-major) order.
  Returns: | reshaped_array : array A new view on the array.

  See also

  `reshape`
    Equivalent function in the masked array module.
  `numpy.ndarray.reshape`
    Equivalent method on ndarray object.
  `numpy.reshape`
    Equivalent function in the NumPy module.

  Notes

  The reshaping operation cannot guarantee that a copy will not be made, to modify the shape in place, use `a.shape = s`

  Examples

      >>> x = np.ma.array([[1,2],[3,4]], mask=[1,0,0,1])
      >>> print(x)
      [[-- 2]
       [3 --]]
      >>> x = x.reshape((4,1))
      >>> print(x)
      [[--]
       [2]
       [3]
       [--]]