Renaming columns in Pandas DataFrame

Python Pandas Numpy: Exercise-30 with Solution

Rename columns in a Pandas DataFrame.

Sample Solution:

Python Code:

import pandas as pd

# Create a sample DataFrame
data = {'Name': ['Imen', 'Karthika', 'Cosimo', 'Cathrine'],
        'Age': [25, 30, 22, 35],
        'Salary': [50000, 60000, 45000, 70000]}

df = pd.DataFrame(data)

# Rename columns
df.rename(columns={'Name': 'Full_Name', 'Age': 'Years', 'Salary': 'Income'}, inplace=True)

# Display the DataFrame with renamed columns
print(df)

Output:

  Full_Name  Years  Income
0      Imen     25   50000
1  Karthika     30   60000
2    Cosimo     22   45000
3  Cathrine     35   70000

Explanation:

Here's a breakdown of the above code:

• First we create a sample DataFrame (df) with columns 'Name', 'Age', and 'Salary'.
• The df.rename(columns={'Name': 'Full_Name', 'Age': 'Years', 'Salary': 'Income'}, inplace=True) line renames the specified columns using a dictionary.
• The inplace=True argument modifies the DataFrame in place without the need to create a new DataFrame.
• The resulting DataFrame is displayed with renamed columns.

Flowchart:

Python Code Editor:

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