numpy.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., dtype : data-type, optional The desired data-type for the array, e.g., order : {‘C’, ‘F’}, optional Whether to store multidimensional data in C- or Fortran-contiguous (row- or column-wise) order in memory. |
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Returns: |
out : ndarray Array of zeros with the given shape, dtype, and order. |
See also
zeros_like
ones_like
empty_like
ones
empty
>>> 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')])
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.zeros.html