In Python, we can implement a matrix as a nested list (list inside a list). We can treat each element as a row of the matrix.

For example `X = [[1, 2], [4, 5], [3, 6]]`

would represent a 3x2 matrix. The first row can be selected as `X[0]`

. And, the element in the first-row first column can be selected as `X[0][0]`

.

Transpose of a matrix is the interchanging of rows and columns. It is denoted as `X'`. The element at `ith` row and `jth` column in `X` will be placed at `jth` row and `ith` column in `X'`. So if `X` is a 3x2 matrix, `X'` will be a 2x3 matrix.

Here are a couple of ways to accomplish this in Python.

## Matrix Transpose using Nested Loop

```
# Program to transpose a matrix using a nested loop
X = [[12,7],
[4 ,5],
[3 ,8]]
result = [[0,0,0],
[0,0,0]]
# iterate through rows
for i in range(len(X)):
# iterate through columns
for j in range(len(X[0])):
result[j][i] = X[i][j]
for r in result:
print(r)
```

**Output**

[12, 4, 3] [7, 5, 8]

In this program, we have used nested `for`

loops to iterate through each row and each column. At each point we place the `X[i][j]` element into `result[j][i]`.

## Matrix Transpose using Nested List Comprehension

```
''' Program to transpose a matrix using list comprehension'''
X = [[12,7],
[4 ,5],
[3 ,8]]
result = [[X[j][i] for j in range(len(X))] for i in range(len(X[0]))]
for r in result:
print(r)
```

The output of this program is the same as above. We have used nested list comprehension to iterate through each element in the matrix.

To learn more, visit Python List Comprehension.

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