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bundles / numpy 2.4.3 / numpy / zeros

built-in

numpy:zeros

Signature

built-in zeros ( shape dtype = None order = C * device = None like = None )

Summary

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) or 2.

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.

device : str, optional

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

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.

Returns

out : ndarray

Array of zeros with the given shape, dtype, and order.

Examples

import numpy as np
np.zeros(5)
np.zeros((5,), dtype=int)
np.zeros((2, 1))
s = (2,2)
np.zeros(s)
np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype

See also

empty

Return a new uninitialized array.

full

Return a new array of given shape filled with value.

ones

Return a new array setting values to one.

zeros_like

Return an array of zeros with shape and type of input.

Aliases

  • numpy.zeros

Referenced by