# numpy matrix operations | zeros() function

`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)  `

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

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