crosstab() for cross-tabulation in Pandas - Mini Project: Build & Apply

Using crosstab() for Cross-Tabulation in pandas

📖 Scenario: You work in a small store and have collected data about customers' gender and whether they bought a product or not. You want to see how many males and females bought or did not buy the product.

🎯 Goal: Build a simple cross-tabulation table using pandas crosstab() to count the number of customers by gender and purchase status.

📋 What You'll Learn

Create a pandas DataFrame with exact customer data

Create a variable for the DataFrame

Use pandas crosstab() with the correct columns

Print the resulting cross-tabulation table

💡 Why This Matters

🌍 Real World

Cross-tabulation helps businesses quickly see relationships between categories, like customer gender and buying behavior.

💼 Career

Data analysts and scientists use crosstab() to summarize and explore categorical data for reports and decision-making.

1

Create the customer data DataFrame

Create a pandas DataFrame called df with two columns: 'Gender' and 'Purchased'. Use these exact values: ['Male', 'Female', 'Female', 'Male', 'Female', 'Male'] for 'Gender' and ['Yes', 'No', 'Yes', 'No', 'Yes', 'Yes'] for 'Purchased'.

Pandas

import pandas as pd
# Create the DataFrame df with Gender and Purchased columns
# Your code here

Need a hint?

Use pd.DataFrame() with a dictionary for columns.

2

Set up the cross-tabulation variable

Create a variable called cross_tab and assign it to the result of pd.crosstab() using df['Gender'] as rows and df['Purchased'] as columns.

Pandas

import pandas as pd

df = pd.DataFrame({
    'Gender': ['Male', 'Female', 'Female', 'Male', 'Female', 'Male'],
    'Purchased': ['Yes', 'No', 'Yes', 'No', 'Yes', 'Yes']
})

# Create cross_tab using pd.crosstab with df['Gender'] and df['Purchased']
# Your code here

Need a hint?

Use pd.crosstab() with the two DataFrame columns as arguments.

3

Print the cross-tabulation table

Print the variable cross_tab to display the cross-tabulation table.

Pandas

import pandas as pd

df = pd.DataFrame({
    'Gender': ['Male', 'Female', 'Female', 'Male', 'Female', 'Male'],
    'Purchased': ['Yes', 'No', 'Yes', 'No', 'Yes', 'Yes']
})

cross_tab = pd.crosstab(df['Gender'], df['Purchased'])

# Print the cross_tab variable
# Your code here

Need a hint?

Use print(cross_tab) to show the table.

4

Add totals to the cross-tabulation table

Update the cross_tab variable to include row and column totals by adding margins=True inside pd.crosstab(). Then print cross_tab again.

Pandas

import pandas as pd

df = pd.DataFrame({
    'Gender': ['Male', 'Female', 'Female', 'Male', 'Female', 'Male'],
    'Purchased': ['Yes', 'No', 'Yes', 'No', 'Yes', 'Yes']
})

# Update cross_tab with margins=True
cross_tab = pd.crosstab(df['Gender'], df['Purchased'], margins=True)

# Print the updated cross_tab
# Your code here

Need a hint?

Add margins=True inside pd.crosstab() to get totals.