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How to rename multiple column headers in a Pandas DataFrame?

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Here we are going to rename multiple column headers using the rename() method. The rename method is used to rename a single column as well as rename multiple columns at a time. And pass columns that contain the new values and in place = true as an argument. We pass inplace = true because we just modify the working data frame if we pass inplace = false then it returns a new dataframe.

Ways to Rename Pandas Columns in Python

There are various ways of renaming multiple column headers in a Pandas Dataframe, we are discussing some important methods which are the following

  • Rename multiple column headers using rename() method
  • Rename Multiple Columns by Names in Pandas
  • Changing Multiple Column Names By Index
  • Rename Multiple Columns using a Dictionary
  • Rename Multiple Columns using str.replace()

Rename multiple column headers using rename() method

In this example, we Rename a Column in Pandas DataFrame, the below code creates a Pandas DataFrame with columns for names, locations, and pay. It then renames the columns and displays both the original and modified data.

Python

# import pandas
import pandas as pd
 
# create data frame
df = pd.DataFrame({'First Name': ["Mukul", "Rohan", "Mayank",
                                  "Vedansh", "Krishna"],
                    
                   'Location': ["Saharanpur", "Rampur", "Agra",
                                "Saharanpur", "Noida"],
                    
                   'Pay': [56000.0, 55000.0, 61000.0, 45000.0, 62000.0]})
 
# print original data frame
display(df)
 
# create a dictionary
# key = old name
# value = new name
dict = {'First Name': 'Name',
        'Location': 'City',
        'Pay': 'Salary'}
 
# call rename () method
df.rename(columns=dict,
          inplace=True)
 
# print Data frame after rename columns
display(df)

                    

Output:

Original DataFrame:
  First Name   Location     Pay
0      Mukul  Saharanpur  56000.0
1      Rohan      Rampur  55000.0
2     Mayank        Agra  61000.0
3    Vedansh  Saharanpur  45000.0
4    Krishna       Noida  62000.0
DataFrame after renaming columns by index:
      name      address     Pay
0    Mukul  Saharanpur  56000.0
1    Rohan      Rampur  55000.0
2   Mayank        Agra  61000.0
3  Vedansh  Saharanpur  45000.0
4  Krishna       Noida  62000.0

Rename Multiple Columns by Names in Pandas

In this example, Assigning List of new column names. Rename and Modify Column in Pandas DataFrame , the below code involves the creation of a Pandas DataFrame, initial display, renaming of columns, and subsequent modification with a second set of column names, followed by the final display of the modified DataFrame.

Python3

# import pandas
import pandas as pd
 
# create data frame
df = pd.DataFrame({'First Name': ["Mukul", "Rohan", "Mayank",
                                  "Vedansh", "Krishna"],
                    
                   'Location': ["Saharanpur", "Rampur",
                                "Agra", "Saharanpur", "Noida"],
                    
                   'Pay': [56000.0, 55000.0, 61000.0, 45000.0, 62000.0]})
 
print("Original DataFrame")
 
# print original data frame
display(df)
 
# create a dictionary
# key = old name
# value = new name
dict = {'First Name': 'Name',
        'Location': 'City',
        'Pay': 'Salary'}
 
print("\nAfter rename")
# call rename () method
df.rename(columns=dict,
          inplace=True)
 
# print Data frame after rename columns
display(df)
 
# create a dictionary
# key = old name
# value = new name
dict = {'Name': 'Full Name',
        'City': 'Address',
        'Salary': 'Amount'}
 
# call rename () method
df.rename(columns=dict,
          inplace=True)
 
display(df)

                    

Output:

Original DataFrame
  First Name   Location     Pay
0      Mukul  Saharanpur  56000.0
1      Rohan      Rampur  55000.0
2     Mayank        Agra  61000.0
3    Vedansh  Saharanpur  45000.0
4    Krishna       Noida  62000.0
After rename
      Name        City   Salary
0    Mukul  Saharanpur  56000.0
1    Rohan      Rampur  55000.0
2   Mayank        Agra  61000.0
3  Vedansh  Saharanpur  45000.0
4  Krishna       Noida  62000.0

Changing Multiple Column Names By Index

In this example the below code uses the pandas library in Python to create a DataFrame, print the original DataFrame, and then rename the first two columns (“First Name” and “Location”) by index. Below is the expected output of the code:

Python3

# import pandas
import pandas as pd
 
# create data frame
df = pd.DataFrame({'First Name': ["Mukul", "Rohan", "Mayank",
                                  "Vedansh", "Krishna"],
                    
                   'Location': ["Saharanpur", "Rampur", "Agra",
                                "Saharanpur", "Noida"],
                    
                   'Pay': [56000.0, 55000.0, 61000.0, 45000.0, 62000.0]})
 
# print original data frame
display(df)
 
# renaming the column by index
df.columns.values[0:2] =["name", "address" ]
 
# print Data frame after rename columns
display(df)

                    

Output:

    First Name    Location    Pay
0    Mukul    Saharanpur    56000.0
1    Rohan    Rampur    55000.0
2    Mayank    Agra    61000.0
3    Vedansh    Saharanpur    45000.0
4    Krishna    Noida    62000.0

name    address    Pay
0    Mukul    Saharanpur    56000.0
1    Rohan    Rampur    55000.0
2    Mayank    Agra    61000.0
3    Vedansh    Saharanpur    45000.0
4    Krishna    Noida    62000.0

Rename Multiple Columns using a Dictionary

In this example we use the columns attribute of the DataFrame along with a dictionary to rename multiple column headers. This approach allows you to map the old column names to the new ones. below code creates a Pandas DataFrame and renames columns ‘A’ to ‘X’, ‘B’ to ‘Y’, ‘C’ to ‘Z’, then prints the result.

Python3

import pandas as pd
 
# Sample DataFrame
data = {'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]}
df = pd.DataFrame(data)
 
# Create a dictionary to map old column names to new ones
column_mapping = {'A': 'X', 'B': 'Y', 'C': 'Z'}
 
# Rename columns using the dictionary and columns attribute
df.columns = [column_mapping[col] if col in column_mapping else col for col in df.columns]
 
# Display the modified DataFrame
print(df)

                    

Output :

   X  Y  Z
0  1  4  7
1  2  5  8
2  3  6  9

Rename Multiple Columns using str.replace()

In this example we use the str.replace method on the column names to replace specific substrings with new ones. This method is useful when you want to perform simple string replacements. Below code utilizes Pandas to create a DataFrame, renaming columns by replacing ‘Product_A_’ with ‘Item_’ using `str.replace`, and prints the modified DataFrame.

Python3

import pandas as pd
 
# Sample DataFrame
data = {'Product_A_Name': [1, 2, 3], 'Product_B_Price': [4, 5, 6], 'Product_C_Quantity': [7, 8, 9]}
df = pd.DataFrame(data)
 
# Use str.replace to rename columns by replacing substrings
df.columns = df.columns.str.replace('Product_A_', 'Item_').str.replace('Product_B_', 'Price_').str.replace('Product_C_', 'Qty_')
 
# Display the modified DataFrame
print(df)

                    

Output :

 Item_Name  Price_Price  Qty_Quantity
0          1            4             7
1          2            5             8
2          3            6             9


Last Updated : 04 Dec, 2023
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