numpy.zeros — NumPy v1.15 Manual (original) (raw)
numpy. zeros(shape, dtype=float, order='C')¶
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 isnumpy.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. |
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| Returns: | out : ndarray Array of zeros with the given shape, dtype, and order. |
See also
Return an array of zeros with shape and type of input.
Return a new uninitialized array.
Return a new array setting values to one.
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')])