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# How to create a constant matrix in Python with NumPy?

• Last Updated : 17 Dec, 2020

A matrix represents a collection of numbers arranged in the order of rows and columns. It is necessary to enclose the elements of a matrix in parentheses or brackets. A constant matrix is a type of matrix whose elements are the same i.e. the element does not change irrespective of any index value thus acting as a constant.

Examples:

M = [[ x, x, x ]

[ x ,x ,x]

[ x, x, x]]

Here M is the constant matrix and x is the constant element.

Below are some examples of Constant Matrix:

A = [[ 5 , 5]

[ 5, 5]]

B = [[ 12, 12, 12, 12, 12, 12]]

There are various methods in numpy module, which can be used to create a constant matrix such as numpy.full(), numpy.ones(), and numpy.zeroes().

### Using numpy.full() method

Syntax:

numpy.full(shape, fill_value, dtype = None, order = ‘C’)

Parameters:

• shape: Number of rows

• order: C_contiguous or F_contiguous

• dtype: [optional, float(by Default)] Data type of returned array.

• fill_value: [bool, optional] Value to fill in the array.

Returns:  ndarray of a given constant having given shape, order and datatype.

Example 1:

Here, we will create a constant matrix of size (2,2) (rows = 2, column = 2) with a constant value of 6.3

## Python3

 `# import required module``import` `numpy as np`` ` `# use full() with a``# constant value of 6.3``array ``=` `np.full((``2``, ``2``), ``6.3``)`` ` `# display matrix``print``(array)`

Output:

```[[6.3 6.3]
[6.3 6.3]]```

Example 2:

A similar example to the one showed above

## Python3

 `# import required module``import` `numpy as np`` ` `# use full() with a``# constant value of 60``array ``=` `np.full((``4``, ``3``), ``60``)`` ` `# display matrix``print``(array)`

Output:

```[[60 60 60]
[60 60 60]
[60 60 60]
[60 60 60]]```

### Using numpy.ones() method

Syntax:

numpy.ones(shape, dtype = None, order = ‘C’)

Parameters:

• shape: integer or sequence of integers
• order: C_contiguous or F_contiguous
• dtype: Data type of returned array.

Returns: ndarray of ones having given shape, order and datatype.

Example 1:

Now, suppose we want to print a matrix consisting of only ones(1s).

## Python3

 `# import required module``import` `numpy as np`` ` `# use ones() ``array ``=` `np.ones((``2``,``2``)) `` ` `# display matrix``print``(array)`

Output:

```[[1. 1.]
[1. 1.]]```

Here by-default, the data type is float, hence all the numbers are written as 1. An alteration, to the above code. Now, we want the data type to be of an integer.

## Python3

 `# import required module``import` `numpy as np`` ` `# use ones() with integer constant``array ``=` `np.ones((``2``, ``2``), dtype``=``np.uint8)`` ` `# display matrix``print``(array)`

Output:

```[[1 1]
[1 1]]```

Notice the change in the last two outputs, one of them shows, 1. And the other is showing 1 only, which means we converted the data type to integer in the second one. uint8 stands for an unsigned 8-bit integer which can represent values ranging from 0 to 255.

Example 2:

Here we create a one-dimensional matrix of only 1s.

## Python3

 `# import required module``import` `numpy as np`` ` `# use ones() with integer constant``array ``=` `np.ones((``5``), dtype``=``np.uint8)`` ` `# display matrix``print``(array)`

Output:

`[1 1 1 1 1]`

### Using numpy.zeroes() method

Syntax:

numpy.zeros(shape, dtype = None, order = ‘C’)

Parameters:

• shape: integer or sequence of integers
• order: C_contiguous or F_contiguous
• dtype: Data type of returned array.

Returns: ndarray of zeros having given shape, order and datatype.

Example 1:

Now that we made a matrix of ones, let’s make one for zeroes.

## Python3

 `# import required module``import` `numpy as np`` ` `# use zeroes()``array ``=` `np.zeros((``2``,``2``))`` ` `# display matrix``print``(array)`

Output:

```[[0. 0.]
[0. 0.]]```

To change it to an integer type,

## Python3

 `# import required module``import` `numpy as np`` ` `# use zeroes() with integer constant``array ``=` `np.zeros((``2``,``2``), dtype``=``np.uint8)`` ` `# display matrix``print``(array)`

Output:

```[[0 0]
[0 0]]```

Example 2:

Here is another example to create a constant one-dimensional matrix of zeroes.

## Python3

 `# import required module``import` `numpy as np`` ` `# use zeroes() with integer constant``array ``=` `np.zeros((``5``), dtype``=``np.uint8)   `` ` `# display matrix``print``(array)`

Output:

`[0 0 0 0 0]`

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