dRecords) or not.

    Examples
    --------
    >>> from numpy.lib import recfunctions as rfn
    >>> rfn.merge_arrays((np.array([1, 2]), np.array([10., 20., 30.])))
    array([( 1, 10.), ( 2, 20.), (-1, 30.)],
          dtype=[('f0', '<i8'), ('f1', '<f8')])

    >>> rfn.merge_arrays((np.array([1, 2], dtype=np.int64),
    ...         np.array([10., 20., 30.])), usemask=False)
     array([(1, 10.0), (2, 20.0), (-1, 30.0)],
             dtype=[('f0', '<i8'), ('f1', '<f8')])
    >>> rfn.merge_arrays((np.array([1, 2]).view([('a', np.int64)]),
    ...               np.array([10., 20., 30.])),
    ...              usemask=False, asrecarray=True)
    rec.array([( 1, 10.), ( 2, 20.), (-1, 30.)],
              dtype=[('a', '<i8'), ('f1', '<f8')])

    Notes
    -----
    * Without a mask, the missing value will be filled with something,
      depending on what its corresponding type:

      * ``-1``      for integers
      * ``-1.0``    for floating point numbers
      * ``'-'``     for characters
      * ``'-1'``    for strings
      * ``True``    for boolean values
    * XXX: I just obtained these values empirically
    rK