Why end-to-end analysis matters in Pandas - See It in Action

Why End-to-End Analysis Matters

📖 Scenario: You work as a data analyst for a small online store. You want to understand how different products perform from the moment they are listed to the final sales. This means looking at the entire process, not just one part.End-to-end analysis helps you see the full story, so you can make better decisions.

🎯 Goal: Build a simple analysis that starts with product data, adds a filter for popular products, calculates total sales, and then shows the final results.

📋 What You'll Learn

Create a pandas DataFrame with product names, prices, and units sold

Add a filter to select products with units sold above a threshold

Calculate total sales for filtered products

Print the total sales value

💡 Why This Matters

🌍 Real World

End-to-end analysis helps businesses understand the full journey of their products, from listing to sales, enabling smarter decisions.

💼 Career

Data analysts and scientists use end-to-end analysis to provide insights that improve product strategies and increase revenue.

1

Create the product data

Create a pandas DataFrame called products with these exact columns and values:
'Product': ['Pen', 'Notebook', 'Eraser', 'Pencil', 'Marker']
'Price': [1.5, 3.0, 0.5, 1.0, 2.0]
'Units_Sold': [100, 50, 150, 200, 80]

Pandas

# Create the products DataFrame with the given data
# Your code here

Need a hint?

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

2

Set the sales threshold

Create a variable called sales_threshold and set it to 100 to filter popular products.

Pandas

import pandas as pd

products = pd.DataFrame({
    'Product': ['Pen', 'Notebook', 'Eraser', 'Pencil', 'Marker'],
    'Price': [1.5, 3.0, 0.5, 1.0, 2.0],
    'Units_Sold': [100, 50, 150, 200, 80]
})

# Create sales_threshold variable and set it to 100
# Your code here

Need a hint?

Just create a variable named sales_threshold and assign the number 100.

3

Filter popular products and calculate total sales

Create a new DataFrame called popular_products by filtering products where Units_Sold is greater than sales_threshold. Then create a variable called total_sales that sums the product of Price and Units_Sold for popular_products.

Pandas

import pandas as pd

products = pd.DataFrame({
    'Product': ['Pen', 'Notebook', 'Eraser', 'Pencil', 'Marker'],
    'Price': [1.5, 3.0, 0.5, 1.0, 2.0],
    'Units_Sold': [100, 50, 150, 200, 80]
})

sales_threshold = 100

# Filter products with Units_Sold > sales_threshold into popular_products
# Calculate total_sales as sum of Price * Units_Sold for popular_products
# Your code here

Need a hint?

Use boolean indexing to filter rows, then multiply columns and use .sum() to get total sales.

4

Display the total sales

Print the value of total_sales using print(total_sales).

Pandas

import pandas as pd

products = pd.DataFrame({
    'Product': ['Pen', 'Notebook', 'Eraser', 'Pencil', 'Marker'],
    'Price': [1.5, 3.0, 0.5, 1.0, 2.0],
    'Units_Sold': [100, 50, 150, 200, 80]
})

sales_threshold = 100

popular_products = products[products['Units_Sold'] > sales_threshold]
total_sales = (popular_products['Price'] * popular_products['Units_Sold']).sum()

# Print the total_sales value
# Your code here

Need a hint?

Use print(total_sales) to show the final number.