How to delete a column of a dataframe using the 'pop' function in Python?

A Pandas DataFrame is a two-dimensional data structure where data is stored in tabular format with rows and columns. It can be visualized as an SQL table or Excel sheet. The pop() function provides an efficient way to delete a column while simultaneously returning its values.

Syntax

DataFrame.pop(item)

Parameters:

• item − The column name to be removed

Returns: The removed column as a Series

Example

Let's create a DataFrame and delete a column using the pop() function ?

import pandas as pd

my_data = {
    'ab': pd.Series([1, 8, 7], index=['a', 'b', 'c']),
    'cd': pd.Series([1, 2, 0, 9], index=['a', 'b', 'c', 'd']),
    'ef': pd.Series([56, 78, 32], index=['a', 'b', 'c']),
    'gh': pd.Series([66, 77, 88, 99], index=['a', 'b', 'c', 'd'])
}

my_df = pd.DataFrame(my_data)
print("Original DataFrame:")
print(my_df)

print("\nDeleting column 'cd' using pop() function:")
removed_column = my_df.pop('cd')
print(my_df)

print("\nRemoved column values:")
print(removed_column)

Original DataFrame:
    ab  cd    ef  gh
a  1.0   1  56.0  66
b  8.0   2  78.0  77
c  7.0   0  32.0  88
d  NaN   9   NaN  99

Deleting column 'cd' using pop() function:
    ab    ef  gh
a  1.0  56.0  66
b  8.0  78.0  77
c  7.0  32.0  88
d  NaN   NaN  99

Removed column values:
a    1
b    2
c    0
d    9
Name: cd, dtype: int64

Key Points

• The pop() function modifies the original DataFrame in-place
• It returns the removed column as a Series, which can be stored for later use
• If the column doesn't exist, it raises a KeyError
• NaN values appear when indices don't align across different Series

Comparison with Other Methods

Conclusion

The pop() function is ideal when you need to remove a column and use its values elsewhere. It modifies the DataFrame in-place and returns the removed column as a Series for further processing.