How do you extract specific columns from multidimensional arrays in NumPy?

Retrieving Columns from Multidimensional Arrays in NumPy

In NumPy, a fundamental operation is accessing individual elements or subsets of data within a multidimensional array. While retrieving rows using the syntax test[i] is straightforward, extracting specific columns can be slightly different.

To access the ith column of a NumPy array, you can utilize the syntax test[:, i]. This will return a one-dimensional array containing the values from the ith column of the original matrix.

For instance, consider the following array:

test = np.array([[1, 2], [3, 4], [5, 6]])

To obtain the first column (containing the values 1, 3, and 5), you would use:

>>> test[:, 0]
array([1, 3, 5])

Similarly, to retrieve the second column (containing the values 2, 4, and 6), you would use:

>>> test[:, 1]
array([2, 4, 6])

Note that this operation is not particularly expensive computationally and is a common technique for working with multidimensional data in NumPy.

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