How to Rename Column Names in Pandas?

Problem Formulation

• Given a Pandas DataFrame with column labels, and
• a list of new column names as strings.

How to change the column names to replace the original ones?

Here’s an example using the following DataFrame:

   Col_A  Col_B  Col_C
0      1      3      5
1      2      4      6

You want to rename the column names ['Col_A', 'Col_B', 'Col_C'] to ['a', 'b', 'c'] so that the resulting DataFrame is:

   a  b  c
0  1  3  5
1  2  4  6

Method 1: Changing the DataFrame.columns Attribute

Given a list of strings that are the new column names. To change the original column names of a given DataFrame, assign the new column names to the attribute df.columns using df.columns = <new column names>.

Here’s how you’d solve the example given above:

>>> df.columns = ['a', 'b', 'c']
>>> df
   a  b  c
0  1  3  5
1  2  4  6

For ease of copy&paste, here’s the full source code to change the column names in an existing DataFrame:

import pandas as pd

df = pd.DataFrame({'Col_A': [1, 2],
                   'Col_B': [3, 4],
                   'Col_C': [5, 6]})
print(df)
'''
   Col_A  Col_B  Col_C
0      1      3      5
1      2      4      6
'''

df.columns = ['a', 'b', 'c']
print(df)
'''
   a  b  c
0  1  3  5
1  2  4  6
'''

Method 2: Renaming Specific Attributes with DataFrame.rename()

To rename a specific subset of column names {'old_1': 'new_1', 'old_2': 'new_2', ...}, use the DataFrame.rename() method and pass a dictionary with the {old : new} mappings into the method.

• df.rename(columns = {'old_1': 'new_1', 'old_2': 'new_2', ...}, inplace=True) to replace the original DataFrame, or
• df = df.rename(columns = {'old_1': 'new_1', 'old_2': 'new_2', ...}) to create a new DataFrame and assign the result to the original variable df.

Here’s a practical example:

import pandas as pd

df = pd.DataFrame({'Col_A': [1, 2],
                   'Col_B': [3, 4],
                   'Col_C': [5, 6]})
print(df)
'''
   Col_A  Col_B  Col_C
0      1      3      5
1      2      4      6
'''

df.rename(columns = {'Col_A': 'a', 'Col_C': 'c'}, inplace=True)
print(df)
'''
   a  Col_B  c
0  1      3  5
1  2      4  6
'''

Note that the rename() method can also take a function to change the column names programmatically as specified by the function:

import pandas as pd

df = pd.DataFrame({'Col_A': [1, 2],
                   'Col_B': [3, 4],
                   'Col_C': [5, 6]})
print(df)
'''
   Col_A  Col_B  Col_C
0      1      3      5
1      2      4      6
'''

df = df.rename(columns = lambda x: x[-1].lower())
print(df)
'''
   a  b  c
0  1  3  5
1  2  4  6
'''

If you need a refresher on lambda functions, feel free to check out the following article.

Related Tutorial: Python Lambda Functions

Method 3: Reassign Column Headers using DataFrame.set_axis()

Use df.set_axis(new_col_names, axis=1, inplace=True) to change the original DataFrame with replaced headers. If you don’t want to overwrite the original DataFrame, use inplace=False in which case the method will return a new DataFrame copy with replace headers.

import pandas as pd

df = pd.DataFrame({'Col_A': [1, 2],
                   'Col_B': [3, 4],
                   'Col_C': [5, 6]})
print(df)
'''
   Col_A  Col_B  Col_C
0      1      3      5
1      2      4      6
'''

df.set_axis(['a', 'b', 'c'], axis=1, inplace=True)
print(df)
'''
   a  b  c
0  1  3  5
1  2  4  6
'''

Summary

There are three main ways to rename the column names ['Col_A', 'Col_B', 'Col_C'] with ['a', 'b', 'c'] in a given Pandas DataFrame:

1. df.columns = ['a', 'b', 'c']
2. df.rename(columns = {'Col_A': 'a', 'Col_C': 'c'}, inplace=True)
3. df.set_axis(['a', 'b', 'c'], axis=1, inplace=True)

Only the second method is suitable to partially replace the column names.

Chris

While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.

To help students reach higher levels of Python success, he founded the programming education website Finxter.com. He’s author of the popular programming book Python One-Liners (NoStarch 2020), coauthor of the Coffee Break Python series of self-published books, computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.

His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.