.pop()

In Pandas, the .pop() method removes a single specified column from a DataFrame object. In the process, the original DataFrame object gets modified and the removed column is returned as a Pandas Series object.

Syntax

pandas.DataFrame.pop(column_label)

• DataFrame: Refers to the DataFrame object from which a column is removed.
• column_label: Represents the label of the column to be removed. This should be a string representing the column name.

Example

This example shows the .pop() method in use:

import pandas as pd

d = {
    'col 1': [1, 2, 3, 4],
    'col 2': ['Red', 'Blue', 'Green', 'Pink'],
    'col 3': ['Oval', 'Circle', 'Square', 'Star'],
    'col 4': ['Sweet', 'Sour', 'Bitter', 'Salty']
}

df = pd.DataFrame(data = d)
print(f"Original dataframe:\n{df}\n")

data_pop = df.pop('col 3')

print(f"Popped data:\n{data_pop}\n")
print(f"DataFrame after pop:\n{df}\n")

The output is shown below:

Original dataframe:
   col 1  col 2   col 3   col 4
0      1    Red    Oval   Sweet
1      2   Blue  Circle    Sour
2      3  Green  Square  Bitter
3      4   Pink    Star   Salty

Popped data:
0      Oval
1    Circle
2    Square
3      Star
Name: col 3, dtype: object

DataFrame after pop:
   col 1  col 2   col 4
0      1    Red   Sweet
1      2   Blue    Sour
2      3  Green  Bitter
3      4   Pink   Salty

The code above creates a pandas DataFrame df from a dictionary d, prints the DataFrame, uses the .pop() method to remove the column col 3 and return it as a Pandas Series object, and then prints the popped data and the modified DataFrame.

Note: If the specified column label is not found in the DataFrame, a KeyError will be raised.

To remove multiple columns at once, use the .drop() method.