numpy matrix operations | zeros() function

Last Updated : 21 Feb, 2019

numpy.matlib.zeros() is another function for doing matrix operations in numpy. It returns a matrix of given shape and type, filled with zeros.

Syntax : numpy.matlib.zeros(shape, dtype=None, order='C') Parameters : shape : [int, int] Number of rows and columns in the output matrix.If shape has length one i.e. (N, ), or is a scalar N, out becomes a single row matrix of shape (1, N). dtype : [optional] Desired output data-type. order : Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory. Return : Matrix of zeros of given shape, dtype, and order.

Code #1 :

Python3

# Python program explaining
# numpy.matlib.zeros() function

# importing matrix library from numpy
import numpy as geek
import numpy.matlib

# desired 3 x 4 zero output matrix 
out_mat = geek.matlib.zeros((3, 4)) 
print ("Output matrix : ", out_mat)

Output :

Output matrix :  [[ 0.  0.  0.  0.]
 [ 0.  0.  0.  0.]
 [ 0.  0.  0.  0.]]

Code #2 :

Python3

# Python program explaining
# numpy.matlib.zeros() function

# importing numpy and matrix library
import numpy as geek
import numpy.matlib

# desired 1 x 5 zero output matrix 
out_mat = geek.matlib.zeros(shape = 5, dtype = int) 
print ("Output matrix : ", out_mat)

Output :

Output matrix :  [[0 0 0 0 0]]

numpy matrix operations | ones() function

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numpy matrix operations | zeros() function

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