Renaming columns in Data Analysis Python - Mini Project: Build & Apply

Renaming columns

📖 Scenario: You have a small table of sales data with unclear column names. You want to rename the columns to more meaningful names so it is easier to understand and analyze.

🎯 Goal: Rename the columns of a pandas DataFrame to new names that clearly describe the data.

📋 What You'll Learn

Create a pandas DataFrame with given columns and data

Create a dictionary mapping old column names to new column names

Use the rename method with the dictionary to rename columns

Print the DataFrame after renaming columns

💡 Why This Matters

🌍 Real World

Renaming columns is common when working with data from different sources that use unclear or inconsistent column names. Clear names help you and others understand the data quickly.

💼 Career

Data analysts and scientists often rename columns to prepare data for analysis, reporting, or visualization. This skill is essential for cleaning and organizing data.

1

Create the initial DataFrame

Create a pandas DataFrame called df with these columns and data: 'A' with values [10, 20, 30], 'B' with values [100, 200, 300], and 'C' with values [1000, 2000, 3000].

Data Analysis Python

import pandas as pd
# Create the DataFrame df with columns 'A', 'B', 'C' and the specified values
# Your code here

Hint

Use pd.DataFrame with a dictionary where keys are column names and values are lists of column data.

2

Create the renaming dictionary

Create a dictionary called new_names that maps the old column names 'A', 'B', and 'C' to the new names 'Product_ID', 'Quantity', and 'Price' respectively.

Data Analysis Python

import pandas as pd

df = pd.DataFrame({
    'A': [10, 20, 30],
    'B': [100, 200, 300],
    'C': [1000, 2000, 3000]
})

# Create the dictionary new_names mapping old to new column names
# Your code here

Hint

Use a dictionary with old column names as keys and new column names as values.

3

Rename the columns using the dictionary

Use the rename method on df with the columns=new_names argument and inplace=True to rename the columns.

Data Analysis Python

import pandas as pd

df = pd.DataFrame({
    'A': [10, 20, 30],
    'B': [100, 200, 300],
    'C': [1000, 2000, 3000]
})

new_names = {'A': 'Product_ID', 'B': 'Quantity', 'C': 'Price'}

# Rename the columns of df using new_names with inplace=True
# Your code here

Hint

Use df.rename(columns=new_names, inplace=True) to rename columns directly in the DataFrame.

4

Print the DataFrame with renamed columns

Write a print statement to display the DataFrame df after renaming the columns.

Data Analysis Python

import pandas as pd

df = pd.DataFrame({
    'A': [10, 20, 30],
    'B': [100, 200, 300],
    'C': [1000, 2000, 3000]
})

new_names = {'A': 'Product_ID', 'B': 'Quantity', 'C': 'Price'}

df.rename(columns=new_names, inplace=True)

# Print the DataFrame df
# Your code here

Hint

Use print(df) to show the DataFrame with new column names.