# numpy.zeros

numpy.zeros(shape, dtype=float, order='C', *, like=None)

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

  Parameters:
    shape int or tuple 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, default: ‘C’

      Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory.

    like array_like, optional

      Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as `like` supports the `__array_function__` protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.

      New in version 1.20.0.

  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.

  `empty`

    Return a new uninitialized array.

  `ones`

    Return a new array setting values to one.

  `full`

    Return a new array of given shape filled with value.

  Examples

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

      >>> np.zeros((5,), dtype=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')])