How To Rename Columns In Pandas (With Examples)

Renaming columns in pandas is a common task when working with data, and pandas makes it easy to do. Here are a few methods to rename columns in a pandas DataFrame, with examples for each.

Method 1: Using rename() Function

The rename() function is the most flexible way to rename columns. You can use it to rename a specific column or multiple columns at once.

Example: Renaming a Single Column

import pandas as pd

# Sample DataFrame
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6]
})

# Renaming column 'A' to 'Column1'
df = df.rename(columns={'A': 'Column1'})

print(df)

Output:

   Column1  B
0        1  4
1        2  5
2        3  6

Example: Renaming Multiple Columns

# Renaming columns 'A' to 'Column1' and 'B' to 'Column2'
df = df.rename(columns={'A': 'Column1', 'B': 'Column2'})

print(df)

Output:

Copy code

   Column1  Column2
0        1        4
1        2        5
2        3        6

Method 2: Using columns Attribute

If you want to rename all columns at once, you can directly assign a new list to the columns attribute of the DataFrame.

Example: Renaming All Columns

# Renaming all columns
df.columns = ['X', 'Y']

print(df)

Output:

   X  Y
0  1  4
1  2  5
2  3  6

Method 3: Using List Comprehension

If you want to apply a function or transformation to all column names, you can use list comprehension.

Example: Converting All Column Names to Lowercase

# Converting all column names to lowercase
df.columns = [col.lower() for col in df.columns]

print(df)

Output:

   column1  column2
0        1        4
1        2        5
2        3        6

Summary

• rename() Function: Best for renaming specific columns, offers flexibility.
• columns Attribute: Quick way to rename all columns at once.
• List Comprehension: Useful for applying transformations to all column names.

These methods give you the flexibility to rename columns in a way that best suits your data manipulation needs.