# Python | Matrix creation of n*n

Many times while working with numbers in data science we come across the problem in which we need to work with data science we need to transform a number to a matrix of consecutive numbers and hence this problem has a good application. Let’s discuss certain ways in which this problem can be solved.

Method #1 : Using list comprehension
List comprehension can be used to accomplish this particular task by using the range function for each list that needs to be constructed consecutively.

 `# Python3 code to demonstrate ` `# matrix creation of n * n ` `# using list comprehension ` ` `  `# initializing N ` `N ``=` `4` ` `  `# printing dimension ` `print``(``"The dimension : "` `+` `str``(N)) ` ` `  `# using list comprehension ` `# matrix creation of n * n ` `res ``=` `[``list``(``range``(``1` `+` `N ``*` `i, ``1` `+` `N ``*` `(i ``+` `1``))) ` `                            ``for` `i ``in` `range``(N)] ` ` `  `# print result ` `print``(``"The created matrix of N * N: "` `+` `str``(res)) `

Output :

```The dimension : 4
The created matrix of N*N: [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
```

Method #2 : Using `next() + itertools.count()`
The count function can be used start the count of numbers and next function does the task of creation of sublist consecutively. List comprehension handles the processing.

 `# Python3 code to demonstrate ` `# matrix creation of n * n ` `# using next() + itertools.count() ` `import` `itertools ` ` `  `# initializing N ` `N ``=` `4` ` `  `# printing dimension ` `print``(``"The dimension : "` `+` `str``(N)) ` ` `  `# using next() + itertools.count() ` `# matrix creation of n * n ` `temp ``=` `itertools.count(``1``)  ` `res ``=` `[[``next``(temp) ``for` `i ``in` `range``(N)] ``for` `i ``in` `range``(N)] ` ` `  `# print result ` `print``(``"The created matrix of N * N: "` `+` `str``(res)) `

Output :

```The dimension : 4
The created matrix of N*N: [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
```

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