Creating MultiIndex DataFrames in Pandas - Try It Yourself

Creating MultiIndex DataFrames

📖 Scenario: You work in a company that tracks sales data across different regions and product categories. You want to organize this data in a clear way so you can analyze sales by region and category easily.

🎯 Goal: Build a pandas DataFrame with a MultiIndex using region and category as the two levels of the index.

📋 What You'll Learn

Create a pandas DataFrame with sales data for different regions and categories

Use a MultiIndex with two levels: 'Region' and 'Category'

Display the final DataFrame with the MultiIndex

💡 Why This Matters

🌍 Real World

MultiIndex DataFrames help organize complex data with multiple categories, like sales by region and product type, making analysis easier.

💼 Career

Data scientists and analysts often use MultiIndex DataFrames to handle hierarchical data and perform detailed group analysis.

1

Create the sales data dictionary

Create a dictionary called sales_data with these exact keys and values: 'Region' with the list ['North', 'North', 'South', 'South'], 'Category' with the list ['Electronics', 'Furniture', 'Electronics', 'Furniture'], and 'Sales' with the list [2500, 1500, 2000, 1200].

Pandas

# Create the sales_data dictionary with Region, Category, and Sales lists
# Your code here

Need a hint?

Use a dictionary with keys 'Region', 'Category', and 'Sales'. Each key should have a list of values.

2

Create the DataFrame from the dictionary

Create a pandas DataFrame called df from the sales_data dictionary.

Pandas

sales_data = {
    'Region': ['North', 'North', 'South', 'South'],
    'Category': ['Electronics', 'Furniture', 'Electronics', 'Furniture'],
    'Sales': [2500, 1500, 2000, 1200]
}

# Create the DataFrame df from sales_data
# Your code here

Need a hint?

Use pd.DataFrame() with sales_data as the argument.

3

Set MultiIndex using Region and Category

Use df.set_index() with the list ['Region', 'Category'] and inplace=True to set a MultiIndex on df.

Pandas

import pandas as pd

sales_data = {
    'Region': ['North', 'North', 'South', 'South'],
    'Category': ['Electronics', 'Furniture', 'Electronics', 'Furniture'],
    'Sales': [2500, 1500, 2000, 1200]
}

df = pd.DataFrame(sales_data)

# Set MultiIndex on df using Region and Category
# Your code here

Need a hint?

Use df.set_index(['Region', 'Category'], inplace=True) to create the MultiIndex.

4

Display the MultiIndex DataFrame

Write a print() statement to display the DataFrame df with the MultiIndex.

Pandas

import pandas as pd

sales_data = {
    'Region': ['North', 'North', 'South', 'South'],
    'Category': ['Electronics', 'Furniture', 'Electronics', 'Furniture'],
    'Sales': [2500, 1500, 2000, 1200]
}

df = pd.DataFrame(sales_data)

df.set_index(['Region', 'Category'], inplace=True)

# Print the DataFrame df
# Your code here

Need a hint?

Use print(df) to show the DataFrame with the MultiIndex.