SciPy

numpy.zeros

numpy.zeros(shape, dtype=float, order='C')

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.

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')])

Previous topic

numpy.ones_like

Next topic

numpy.zeros_like