numpy.zeros#

numpy.zeros(shapedtype=Noneorder='C'*device=Nonelike=None)#

Return a new array of given shape and typefilled with zeros.

Parameters:
shapeint or tuple of ints

Shape of the new arraye.g.(2, 3) or 2.

dtypedata-typeoptional

The desired data-type for the arraye.g.numpy.int8. Default is numpy.float64.

order{‘C’‘F’}optionaldefault: ‘C’

Whether to store multi-dimensional data in row-major (C-) or column-major (Fortran-) order in memory.

devicestroptional

The device on which to place the created array. Default: None. For Array-API interoperability onlyso must be "cpu" if passed.

New in version 2.0.0.

likearray_likeoptional

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__ protocolthe result will be defined by it. In this caseit 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 shapedtypeand 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

>>> import numpy as np
>>> np.zeros(5)
array([ 0. 0. 0. 0. 0.])

>>> np.zeros((5,), dtype=int)
array([00000])

>>> 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([(00)(00)],
      dtype=[('x''<i4')('y''<i4')])
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