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 :

# 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 :

# 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)  