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# numpy.ma.asarray

`numpy.ma.``asarray`(a, dtype=None, order=None)

  Convert the input to a masked array of the given data-type.

  No copy is performed if the input is already an ndarray. If a is a subclass of `MaskedArray`, a base class `MaskedArray` is returned.

  Parameters: | a : array_like Input data, in any form that can be converted to a masked array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists, ndarrays and masked arrays. dtype : dtype, optional By default, the data-type is inferred from the input data. order : {‘C’, ‘F’}, optional Whether to use row-major (‘C’) or column-major (‘FORTRAN’) memory representation. Default is ‘C’.
  Returns: | out : MaskedArray Masked array interpretation of a.

  See also

  `asanyarray`
    Similar to `asarray`, but conserves subclasses.

  Examples

      >>> x = np.arange(10.).reshape(2, 5)
      >>> x
      array([[ 0.,  1.,  2.,  3.,  4.],
             [ 5.,  6.,  7.,  8.,  9.]])
      >>> np.ma.asarray(x)
      masked_array(data =
       [[ 0.  1.  2.  3.  4.]
       [ 5.  6.  7.  8.  9.]],
                   mask =
       False,
             fill_value = 1e+20)
      >>> type(np.ma.asarray(x))
      <class 'numpy.ma.core.MaskedArray'>