We can extract a column from a multi-dimensional array in Python using array slicing or indexing, depending on the type of array we are using.

Here are two common ways to do it:

### 1. Using NumPy arrays:

If we are working with NumPy arrays, we can use array slicing or indexing to extract a column. Here’s how we can do it:

```
import numpy as np
# Create a 2D NumPy array
array_2d = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
# Extract the second column (index 1)
column = array_2d[:, 1]
print("Extracted column:", column)
```

Output:

```
Extracted column: [2 5 8]
```

In this example, `array_2d[:, 1]`

extracts the second column (index 1) from the 2D NumPy array `array_2d`

.

### 2. Using nested lists:

If we are working with nested lists, we can use list comprehension or loops to extract a column.

To do this we write

```
# Create a 2D nested list
nested_list = [[1, 2, 3],
[4, 5, 6],
[7, 8, 9]]
# Extract the second column (index 1)
column = [row[1] for row in nested_list]
print("Extracted column:", column)
```

Output:

```
Extracted column: [2, 5, 8]
```

In this example, `[row[1] for row in nested_list]`

extracts the second element (index 1) from each sublist in the nested list `nested_list`

.

Choose the appropriate method based on whether we are working with NumPy arrays or nested lists.

If we are dealing with numerical data and plan to perform mathematical operations, using NumPy arrays is recommended for better performance and convenience.