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 sequence 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

Whether to store multidimensional data in C- or Fortran-contiguous (row- or column-wise) 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.

ones_like

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

empty_like

Return an empty array with shape and type of input.

ones

Return a new array setting values to one.

empty

Return a new uninitialized array.

Examples

>>> np.zeros(5)
array([ 0.,  0.,  0.,  0.,  0.])

>>> np.zeros((5,), dtype=np.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')])