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numpy.zeros
- numpy.zeros(shape, dtype=float, order='C', *, like=None)
-
Return a new array of given shape and type, filled with zeros.
- Parameters
-
- shapeint or tuple of ints
-
Shape of the new array, e.g.,
(2, 3)or2. - dtypedata-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.
- likearray_like, optional
-
Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as
likesupports 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
-
- outndarray
-
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')])
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https://numpy.org/doc/1.23/reference/generated/numpy.zeros.html