Coding-For-MBA

We’ve seen lists for ordered data and tuples for immutable data. Now we’ll learn about sets, which are powerful for two main business reasons: ensuring uniqueness and performing membership analysis.

What is a Set?

A set is an unordered collection of unique items.

This de-duplication feature is one of the most common uses for sets in data analysis.

Set Operations: The Foundation of Segmentation

The true power of sets comes from their mathematical operations, which are invaluable for customer segmentation and cohort analysis.

Operation Python Operator Business Question Answered
Union A | B What is the total unique audience for two groups?
Intersection A & B Which customers are in both Group A and Group B?
Difference A - B Which customers are in Group A but not in Group B?

Environment Setup

Before you begin, ensure you have followed the setup instructions in the main README.md to set up your virtual environment and install the required libraries.

Exploring the Refactored Code

The script for this lesson, sets.py, has been refactored into functions to make the logic for de-duplication and segmentation reusable and testable.

  1. Review the Code: Open Day_07_Sets/sets.py. Notice the functions get_unique_items(), analyze_visitor_segments(), and upgrade_plan_features().
  2. Run the Script: From the root directory of the project (Coding-For-MBA), run the script to see the functions in action: 
    python Day_07_Sets/sets.py
  3. Run the Tests: You can run the tests for this lesson to verify the correctness of each function: 
    pytest tests/test_day_07.py

💻 Exercises: Day 7

  1. Find Unique Customer Cities:

    • In a new script (my_solutions_07.py), you have a list of cities: order_cities = ["New York", "Los Angeles", "Chicago", "New York", "Boston", "Los Angeles"].
    • Import the get_unique_items function from the lesson script.
    • Call the function with your list to get a set of unique cities and print the result.

  2. Analyze Website Visitor Activity:

    • You have two sets of user IDs:
      • pricing_visitors = {"user1", "user3", "user5", "user7"}
      • contact_visitors = {"user2", "user3", "user4", "user5"}
    • Import the analyze_visitor_segments function.
    • Call the function with these two sets.
    • Print the intersection and difference_a_b from the returned dictionary to find highly engaged users and users who only viewed pricing.

  3. Manage Product Features:

    • Your “Standard Plan” has a set of features: standard_features = {"reporting", "data_export", "basic_support"}.
    • You want to add ["api_access", "priority_support"] for the “Pro Plan”.
    • Import and use the upgrade_plan_features function to create the new feature set for the Pro Plan.
    • Print the resulting Pro Plan feature set.

🎉 Well done! Sets are a specialized but incredibly efficient tool. When you need to de-duplicate a list or analyze the overlap between two groups, sets are the best tool for the job.

Interactive Notebooks

Run this lesson’s code interactively in your browser:

!!! tip “About JupyterLite” JupyterLite runs entirely in your browser using WebAssembly. No installation or server required! Note: First launch may take a moment to load.

Additional Materials

???+ example “sets.py” View on GitHub

```python title="sets.py"
"""
Day 7: Using Sets for Unique Data and Segmentation (Refactored)

This script demonstrates how to use sets to de-duplicate data
and perform segmentation analysis on business data. This version
is refactored into functions for better organization and testability.
"""


def get_unique_items(items_list):
    """Converts a list to a set to get unique items."""
    return set(items_list)


def analyze_visitor_segments(set_a, set_b):
    """
    Performs intersection, difference, and union operations on two sets.
    Returns a dictionary with the results.
    """
    intersection = set_a.intersection(set_b)
    difference = set_a.difference(set_b)
    union = set_a.union(set_b)

    return {"intersection": intersection, "difference_a_b": difference, "union": union}


def upgrade_plan_features(base_features, new_features_list):
    """
    Adds new features to a base set of features.
    """
    upgraded_plan = base_features.copy()
    upgraded_plan.update(new_features_list)
    return upgraded_plan


if __name__ == "__main__":
    # --- Using a Set to Find Unique Items ---
    print("--- Finding Unique Customer Cities ---")
    order_cities_list = [
        "New York",
        "Los Angeles",
        "Chicago",
        "New York",
        "Boston",
        "Los Angeles",
        "Chicago",
    ]
    print(f"Original list of cities: {order_cities_list}")
    unique_cities_set = get_unique_items(order_cities_list)
    print(f"Unique cities set: {unique_cities_set}")
    print(f"Number of unique cities: {len(unique_cities_set)}")
    print("-" * 20)

    # --- Using Set Operations for Customer Segmentation ---
    print("--- Analyzing Website Visitor Segments ---")
    pricing_page_visitors = {"user1", "user3", "user5", "user7", "user8"}
    contact_page_visitors = {"user2", "user3", "user4", "user5", "user9"}

    segment_analysis = analyze_visitor_segments(
        pricing_page_visitors, contact_page_visitors
    )

    print(
        f"Users who visited Pricing AND Contact pages: {segment_analysis['intersection']}"
    )
    print(
        f"Users who only visited the Pricing page: {segment_analysis['difference_a_b']}"
    )
    print(f"All unique visitors to either page: {segment_analysis['union']}")
    print("-" * 20)

    # --- Modifying Sets to Manage Product Plans ---
    print("--- Managing Product Plan Features ---")
    standard_plan_features = {"reporting", "data_export", "basic_support"}
    print(f"Standard Plan Features: {standard_plan_features}")

    features_to_add_for_pro = ["api_access", "priority_support", "24/7_monitoring"]
    pro_plan_features = upgrade_plan_features(
        standard_plan_features, features_to_add_for_pro
    )

    print(f"Pro Plan Features: {pro_plan_features}")

    pro_only = pro_plan_features.difference(standard_plan_features)
    print(f"Features unique to the Pro Plan: {pro_only}")
    print("-" * 20)
```

???+ example “solutions.py” View on GitHub

```python title="solutions.py"
"""
Day 7: Solutions to Exercises
"""

# --- Exercise 1: Find Unique Customer Cities ---
print("--- Solution to Exercise 1 ---")
order_cities = [
    "New York",
    "Los Angeles",
    "Chicago",
    "New York",
    "Boston",
    "Los Angeles",
]
print(f"Original list of cities: {order_cities}")

# Converting the list to a set automatically removes duplicates
unique_cities = set(order_cities)

print(f"Set of unique cities: {unique_cities}")
print(f"Number of unique cities where orders were placed: {len(unique_cities)}")
print("-" * 20)


# --- Exercise 2: Analyze Website Visitor Activity ---
print("--- Solution to Exercise 2 ---")
pricing_visitors = {"user1", "user3", "user5", "user7"}
contact_visitors = {"user2", "user3", "user4", "user5"}

print(f"Pricing Page Visitors: {pricing_visitors}")
print(f"Contact Page Visitors: {contact_visitors}")

# Intersection: users who did both
both_pages_visitors = pricing_visitors.intersection(contact_visitors)
print(f"Users who visited BOTH pages: {both_pages_visitors}")

# Difference: users who visited pricing but not contact
pricing_only_visitors = pricing_visitors.difference(contact_visitors)
print(f"Users who visited Pricing but NOT Contact: {pricing_only_visitors}")

# Union: all unique users who visited either page
all_visitors = pricing_visitors.union(contact_visitors)
print(f"All unique visitors to either page: {all_visitors}")
print("-" * 20)


# --- Exercise 3: Manage Product Features ---
print("--- Solution to Exercise 3 ---")
standard_features = {"reporting", "data_export", "basic_support"}
print(f"Standard Plan Features: {standard_features}")

# Create a copy to avoid modifying the original set
pro_features = standard_features.copy()

# New features to add
new_pro_features = ["api_access", "priority_support"]
pro_features.update(new_pro_features)

print(f"Pro Plan Features after update: {pro_features}")
print("-" * 20)
```
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