How to rename a Pandas DataFrame Column Names

If you want to rename the column names of a DataFrame, you can make use of DataFrame.rename function from the pandas module.

Let's take a look at some code examples:

Example 1:

>>> import pandas as pd
>>> df = pd.DataFrame({"Column1": ["2023-01",32.2], "Column2": ["2023-02", 31.1]})
>>> df.rename(columns={"Column1": "Year-Month", "Column2": "Temperature"})

  Year-Month Temperature
0    2023-01     2023-02
1       32.2        31.1

Example 2:

import pandas as pd

code2care_data = {
    'Year': [2020, 2021, 2022, 2023],
    'Country': ['United States', 'India', 'United Kingdom', 'Germany'],
    'City': ['New York', 'Mumbai', 'London', 'Berlin'],
    'Mobile': [312125, 2234010, 150125, 413822],
    'Desktop': [353871, 427896, 374675, 258976],
    'Search Engine': ['Google', 'Bing', 'Google', 'Yahoo']
}

df = pd.DataFrame(code2care_data)

print("\nDataFrame before renaming Column Names:")
print(df)

# Renaming the columns
new_column_names = {
    'Country': 'Visitor Country',
    'City': 'Visitor City',
    'Mobile': 'Mobile Visits',
    'Desktop': 'Desktop Visits',
    'Search Engine': 'Search Engine Source'
}

df = df.rename(columns=new_column_names)

print("\nDataFrame after renaming Column Names:")
print(df)

Output:

DataFrame before renaming Column Names:

   Year         Country      City   Mobile  Desktop Search Engine
0  2020   United States  New York   312125   353871        Google
1  2021           India    Mumbai  2234010   427896          Bing
2  2022  United Kingdom    London   150125   374675        Google
3  2023         Germany    Berlin   413822   258976         Yahoo



DataFrame after renaming Column Names:

   Year Visitor Country Visitor City  Mobile Visits  Desktop Visits  \
0  2020   United States     New York         312125          353871   
1  2021           India       Mumbai        2234010          427896   
2  2022  United Kingdom       London         150125          374675   
3  2023         Germany       Berlin         413822          258976   

  Search Engine Source  
0               Google  
1                 Bing  
2               Google  
3                Yahoo