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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.,
(2, 3)or2.dtype : data-type, optional
The desired data-type for the array, e.g.,
numpy.int8. Default isnumpy.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
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zeros_like - Return an array of zeros with shape and type of input.
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ones_like - Return an array of ones with shape and type of input.
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empty_like - Return an empty array with shape and type of input.
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ones - Return a new array setting values to one.
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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')]) -
numpy.zeros()
2025-01-10 15:47:30
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