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 dtypearray([(0, 0), (0, 0)],   dtype=[('x', '<i4'), ('y', '<i4')])########################################################zeros(shape, dtype=float, order='C')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 dtypearray([(0, 0), (0, 0)],   dtype=[('x', '<i4'), ('y', '<i4')])Type:   builtin_function_or_method