In this post we will be creating a Python script that will create an empty column within an existing pandas DataFrame.
See below our DataFrame for this example, consisting of three columns ‘Rank’, ‘Name’ and ‘Platform’.
Rank Name Platform
0 1 Wii Sports Wii
1 2 Super Mario Bros. NES
2 3 Mario Kart Wii Wii
3 4 Wii Sports Resort Wii
4 5 Pokemon Red/Pokemon Blue GB
5 6 Tetris GB
6 7 New Super Mario Bros. DS
7 8 Wii Play Wii
8 9 New Super Mario Bros. Wii Wii
9 10 Duck Hunt NES
>>> Now what one defines as empty columns may differ, this could be a column with nothing inside or a column containing NaN values. In this post we will cover both.
See the snippet of code below where we create an empty column within our pandas DataFrame via empty cells.
import pandas as pd
df["Blank"] = ""
print(df)The above code would return the following list as output.
Rank Name Platform Blank
0 1 Wii Sports Wii
1 2 Super Mario Bros. NES
2 3 Mario Kart Wii Wii
3 4 Wii Sports Resort Wii
4 5 Pokemon Red/Pokemon Blue GB
5 6 Tetris GB
6 7 New Super Mario Bros. DS
7 8 Wii Play Wii
8 9 New Super Mario Bros. Wii Wii
9 10 Duck Hunt NES
>>> See the snippet of code below where we create an empty column within our DataFrame via NaN values.
import pandas as pd
import numpy as np
df=pd.read_csv('Sample.csv')
df["Blank"] = np.nan
print(df)
The above code would return the following list as output.
Rank Name Platform Blank
0 1 Wii Sports Wii NaN
1 2 Super Mario Bros. NES NaN
2 3 Mario Kart Wii Wii NaN
3 4 Wii Sports Resort Wii NaN
4 5 Pokemon Red/Pokemon Blue GB NaN
5 6 Tetris GB NaN
6 7 New Super Mario Bros. DS NaN
7 8 Wii Play Wii NaN
8 9 New Super Mario Bros. Wii Wii NaN
9 10 Duck Hunt NES NaN
>>> Take a look at some of our other content around the Python programming language here. Or check out our Pandas crash course by clicking here instead.