Setting columns as MultiIndex in Pandas - Mini Project: Build & Apply

Setting columns as MultiIndex

📖 Scenario: You work in a small company that tracks sales data. The data is organized by product categories and months. You want to organize the columns in a table to show this hierarchy clearly.

🎯 Goal: Create a pandas DataFrame with sales data, then set the columns as a MultiIndex to group by product category and month.

📋 What You'll Learn

Create a pandas DataFrame with sales data for two product categories and two months.

Create a MultiIndex for the columns using product categories and months.

Set the DataFrame columns to this MultiIndex.

Print the DataFrame to see the MultiIndex columns.

💡 Why This Matters

🌍 Real World

Organizing sales or financial data with multiple categories helps businesses analyze performance clearly.

💼 Career

Data analysts and scientists often use MultiIndex in pandas to handle complex datasets with hierarchical relationships.

1

Create the sales data DataFrame

Import pandas as pd. Create a DataFrame called sales with these columns and values: 'Product A_Jan': [100, 150], 'Product A_Feb': [120, 130], 'Product B_Jan': [90, 110], 'Product B_Feb': [95, 105]. Use index labels ['Store 1', 'Store 2'].

Pandas

# Import pandas and create the sales DataFrame with the specified columns and values
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary for columns and a list for the index.

2

Create the MultiIndex for columns

Create a MultiIndex called multi_cols from the list of tuples: [('Product A', 'Jan'), ('Product A', 'Feb'), ('Product B', 'Jan'), ('Product B', 'Feb')]. Use pd.MultiIndex.from_tuples().

Pandas

import pandas as pd

sales = pd.DataFrame({
    'Product A_Jan': [100, 150],
    'Product A_Feb': [120, 130],
    'Product B_Jan': [90, 110],
    'Product B_Feb': [95, 105]
}, index=['Store 1', 'Store 2'])

# Create the MultiIndex for columns
# Your code here

Need a hint?

Use pd.MultiIndex.from_tuples() with the list of tuples for product and month.

3

Set the DataFrame columns to the MultiIndex

Set the sales.columns to the MultiIndex variable multi_cols.

Pandas

import pandas as pd

sales = pd.DataFrame({
    'Product A_Jan': [100, 150],
    'Product A_Feb': [120, 130],
    'Product B_Jan': [90, 110],
    'Product B_Feb': [95, 105]
}, index=['Store 1', 'Store 2'])

multi_cols = pd.MultiIndex.from_tuples([
    ('Product A', 'Jan'),
    ('Product A', 'Feb'),
    ('Product B', 'Jan'),
    ('Product B', 'Feb')
])

# Set the sales DataFrame columns to the MultiIndex
# Your code here

Need a hint?

Assign multi_cols to sales.columns.

4

Print the DataFrame with MultiIndex columns

Print the sales DataFrame to display the columns as a MultiIndex.

Pandas

import pandas as pd

sales = pd.DataFrame({
    'Product A_Jan': [100, 150],
    'Product A_Feb': [120, 130],
    'Product B_Jan': [90, 110],
    'Product B_Feb': [95, 105]
}, index=['Store 1', 'Store 2'])

multi_cols = pd.MultiIndex.from_tuples([
    ('Product A', 'Jan'),
    ('Product A', 'Feb'),
    ('Product B', 'Jan'),
    ('Product B', 'Feb')
])

sales.columns = multi_cols

# Print the sales DataFrame
# Your code here

Need a hint?

Use print(sales) to show the DataFrame with MultiIndex columns.