Pandas Pop is the sound a column makes when it’s removed from a dataset…pop!

Popping a column in pandas is no different. We use pd.DataFrame.pop when we want to remove a column.

What is Pandas Pop?

Pop will is the pandas function to:

• Remove your column from a dataframe
• Return that column you’re dropping as a series so you can use it (if you want)

df.pop() is very similar to df.drop(), but .drop() will return the DataFrame with the column removed. Whereas .pop() will return the column.

I use pop when I’m creating a dummy column. A column that will only temporarily be used and I don’t want my dataframe to become sloppy.

If you need to remove multiple columns from your dataset, you can either .pop() multiple times, or use pandas .drop() instead. With .drop() you can pass a list of columns (or rows) and they’ll be dropped from your DataFrame.

Pop doesn’t take any extra arguments so you don’t need to worry about changing anything. Did you know that pop is also used with regular vanilla python? Check out python pop.

Make sure to make a ‘popping’ sound whenever you call df.pop()

import pandas as pd

df = pd.DataFrame([('Foreign Cinema', 'Restaurant', 289.0),
                   ('Liho Liho', 'Restaurant', 224.0),
                   ('500 Club', 'bar', 80.5),
                   ('The Square', 'bar', 25.30)],
           columns=('name', 'type', 'AvgBill')
                 )
df

x = df.pop('type')

df

x

0    Restaurant
1    Restaurant
2           bar
3           bar
Name: type, dtype: object

Link to code above

Check out more Pandas functions on our Pandas Page

Official Documentation