How can I use pandas drop column functionality to delete a column from a DataFrame?

General Discussions
1

How can I use pandas drop column functionality to delete a column from a DataFrame? I can successfully remove a column using:

del df['column_name']

But why doesn’t the following work?

del df.column_name

Since it’s possible to access a Series via df.column_name, I expected this approach to be valid.

2

The del statement works when specifying the column name as a dictionary key, as DataFrame columns are stored in a dictionary-like structure:

import pandas as pd

df = pd.DataFrame({'a': [1, 2], 'b': [3, 4], 'c': [5, 6]})

del df['b']  # Correct way to delete a column
print(df)
3

A more flexible approach is using .drop(), which allows you to remove a column without modifying the original DataFrame unless specified:

df = df.drop(columns=['b'])  # This applies the pandas drop column method
print(df)

To modify df in place, set inplace=True:
df.drop(columns=['b'], inplace=True)
4

Using .pop()

If you need to delete a column and retain its values separately, .pop() is useful:

removed_column = df.pop(‘b’) # Removes and returns the column print(df)

print(removed_column)

Although df.column_name works for accessing columns, it doesn’t support deletion because attribute access doesn’t modify the underlying DataFrame structure.

Using pandas drop column methods like .drop() or del ensures safe and reliable column removal.