zeros¶
Documentation¶
Numpy Version Related
This documentation is based on numpy.zeros in numpy v1.24.4. Its arguments’ arrangements depend on the version of numpy you installed.
If some arguments listed here are not working properly, please check your numpy’s version with the following command and find its documentation.
1 | python -c 'import numpy as np;print(np.__version__)' |
The arguments and keyword arguments supported in numpy v1.24.4 is listed below.
Description From Numpy v1.24¶
-
numpy.
zeros
(shape, dtype=float, order='C', *, like=None)¶ 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)
or2
.- dtype : data-type, optional
The desired data-type for the array, e.g., numpy.int8. Default is numpy.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.
- like : array_like, optional
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.New in version 1.20.0.
Returns¶
- out : ndarray
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')])