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
-
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.Note
The
like
keyword is an experimental feature pending on acceptance of NEP 35.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/1.20/reference/generated/numpy.zeros.html