# Python | Transpose elements of a two-dimensional list

In Python, a matrix can be interpreted as a list of lists. Each element is considered as a row of the matrix. For example, m = [[10, 20], [40, 50], [30, 60]] is a matrix of 3 rows and 2 columns. The first item in the list — m [0] and the item on the first row, the first column — m [0] [0].

Example :

`  Input:  l1 = [[4, 5, 3, 9], [7, 1, 8, 2], [5, 6, 4, 7]]  Output:  lt = [[4, 7, 5], [5, 1, 6] , [3, 8, 4], [9, 2, 7]] `

Method # 1: Using Loops

 ` # Python transpose program ` ` # list items of two dimensions ` ` def ` ` transpose (l1, l2): `   ` # iterate over the list l1 to the length of the element ` ` for ` ` i ` ` in ` ` range ` ` (` ` len ` ` (l1 [` ` 0 ` `])): ` ` # print (s) ` ` row ` ` = ` ` [] ` ` for ` ` item ` ` in ` ` l1: ` ` # add to a new list with index values ​​and positions ` ` # i contains index position and element contains values ​​` ` row.append (item [i]) ` ` l2.append (row) ` ` ` ` return ` ` l2 `   ` # Driver code ` ` l1 ` ` = ` ` [ [` ` 4 ` `, ` ` 5 ` `, ` ` 3 ` `, ` ` 9 ` `], [` ` 7 ` `, ` ` 1 ` `, ` ` 8 ` `, ` ` 2 ` `], [` ` 5 ` `, ` ` 6 ` `, ` ` 4 ` `, ` ` 7 ` `]] ` ` l2 ` ` = ` [] ` print ` ` (transpose (l1, l2)) `

Exit:

` [[4, 7, 5], [5, 1, 6], [3, 8, 4], [9, 2, 7]] `

Method # 2: Using list views

` `

` # Python transpose program # list items of two dimensions def transpose (l1, l2):     # we have nested loops in understandings # i is assigned using inner loop # then the element value is routed by the string [i]   # and added to l2 l2 = [[row [i] for row in l1] for i in range ( len (l1 [ 0 ]))] return l2    # Driver code l1 = [[ 4 , 5 , 3 , 9 ], [ 7 , 1 , 8 , 2 ], [ 5 , 6 , 4 , 7 ]] l2 = [] print (transpose (l1, l2)) `

` ` Output:

``` [[4, 7, 5], [5, 1, 6], [3, 8, 4], [9, 2, 7]] < / pre>   Method # 3:  Using NumPy           ` # Python transpose program `  ` # list items of two dimensions `   ` import ` ` numpy `      ` l1 ` ` = ` ` [[` ` 4 ` `, ` ` 5 ` `, ` ` 3 ` `, ` ` 9 ` `], [` ` 7 ` `, ` ` 1 ` `, ` ` 8 ` `, ` ` 2 ` `], [` ` 5 ` `, ` ` 6 ` `, ` ` 4 ` `, ` ` 7 ` `]] `   ` print ` ` (numpy.transpose (l1)) `        Exit:  [[4 7 5] [5 1 6] [3 8 4] [ 9 2 7]]