How to get column in Numpy array?

Let’s learn how to get a column in a Numpy array. This is what allows you to manipulate data in the Numpy Python library.

We have such a Numpy array:

[1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 1.10],
[2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 2.10],
[3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10]

How to get a single column?

How to get only the elements from the fourth column? Like that:

import numpy as np

my_array = np.array((
    [1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 1.10],
    [2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 2.10],
    [3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10]))

chosen_elements = my_array[:, 3]

print(chosen_elements)

chosen_elements = my_array [:, 3] each (colon) element from the fourth column is returned (3 means fourth column because computers start counting from 0).

How to get one value from given column and row?

Keep moving further.

How to get elements from the second row and fourth column?

import numpy as np

my_array = np.array((
    [1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 1.10],
    [2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 2.10],
    [3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10]))

chosen_elements = my_array[1, 3]

print(chosen_elements)

chosen_elements = my_array[1, 3] returned second row and fourth column.

How to get multiple columns?

So, how do you get a lot of columns? Let’s get columns two through six.

import numpy as np

my_array = np.array((
    [1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 1.10],
    [2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 2.10],
    [3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10]))

chosen_elements = my_array[:, 1:6]

print(chosen_elements)

chosen_elements = my_array[:, 1:6] is returning columns second to sixth thanks to colon. A colon denotes a range of 1 to 6 columns, 2 to 6.

How to get every few columns

One more tip.

How to get many columns from a step? Let’s return to columns second to sixth, but every second column.

import numpy as np

my_array = np.array((
    [1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 1.10],
    [2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 2.10],
    [3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10]))

chosen_elements = my_array[:, 1:6:2]

print(chosen_elements)

chosen_elements = my_array[:, 1:6:2] as you can notice added a step. Another colon is doing that, and digit 2 tells how big the step is.

Now you can get columns in Numpy arrays.

How to get a column in a NumPy array using slicing?

You can use slicing to get a column in a NumPy array. Slicing is a way to select a subset of elements from an array. To get a column in a NumPy array using slicing, you can use the following syntax:

array_name[:, column_index]

Where array_name is the name of the NumPy array, and column_index is the index of the column you want to get. The column index starts at 0, so to get the first column, you would use column_index=0.

For example, the following code gets the first column from the NumPy array my_array:

import numpy as np

my_array = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

first_column = my_array[:, 0]

print(first_column)

As you can see, the code has successfully returned the first column from the NumPy array.