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# numpy.ma.zeros

`numpy.ma.``zeros`(shape, dtype=float, order='C') = <numpy.ma.core._convert2ma instance at 0x42450dac>

  Return a new array of given shape and type, filled with zeros.

  Parameters: | shape : int or sequence of ints Shape of the new array, e.g., `(2, 3)` or `2`. dtype : data-type, optional The desired data-type for the array, e.g., `numpy.int8`. Default is `numpy.float64`. order : {‘C’, ‘F’}, optional Whether to store multidimensional data in C- or Fortran-contiguous (row- or column-wise) order in memory.
  Returns: | out : ndarray Array of zeros with the given shape, dtype, and order.

  See also

  `zeros_like`
    Return an array of zeros with shape and type of input.
  `ones_like`
    Return an array of ones with shape and type of input.
  `empty_like`
    Return an empty array with shape and type of input.
  `ones`
    Return a new array setting values to one.
  `empty`
    Return a new uninitialized array.

  Examples

      >>> np.zeros(5)
      array([ 0.,  0.,  0.,  0.,  0.])

      >>> np.zeros((5,), dtype=np.int)
      array([0, 0, 0, 0, 0])

      >>> np.zeros((2, 1))
      array([[ 0.],
             [ 0.]])

      >>> s = (2,2)
      >>> np.zeros(s)
      array([[ 0.,  0.],
             [ 0.,  0.]])

      >>> np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype
      array([(0, 0), (0, 0)],
            dtype=[('x', '<i4'), ('y', '<i4')])