numpy.zeros — NumPy v2.2 Manual (original) (raw)
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)
or 2
.
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 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:
outndarray
Array of zeros with the given shape, dtype, and order.
See also
Return an array of zeros with shape and type of input.
Return a new uninitialized array.
Return a new array setting values to one.
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([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')])