groupby() basics in Data Analysis Python - Mini Project: Build & Apply

groupby() basics

📖 Scenario: You work in a small store and have a list of sales records. Each record shows the product sold and the quantity sold. You want to find out how many items of each product were sold in total.

🎯 Goal: Use the groupby() function from pandas to group sales by product and calculate the total quantity sold for each product.

📋 What You'll Learn

Create a pandas DataFrame with sales data

Create a variable for grouping the data by product

Use groupby() and sum() to calculate total quantities

Print the grouped result showing total quantity per product

💡 Why This Matters

🌍 Real World

Stores and businesses often need to summarize sales data by product to understand what sells best.

💼 Career

Data analysts and scientists use grouping and aggregation to prepare reports and find insights from data.

1

Create the sales data DataFrame

Import pandas as pd and create a DataFrame called sales with these exact columns and rows:
product: 'apple', 'banana', 'apple', 'orange', 'banana'
quantity: 10, 5, 7, 8, 3

Data Analysis Python

# Import pandas and create the sales DataFrame
# Your code here

Hint

Use pd.DataFrame with a dictionary containing the columns and their values.

2

Create a group variable by product

Create a variable called grouped that groups the sales DataFrame by the product column using groupby().

Data Analysis Python

import pandas as pd
sales = pd.DataFrame({
    'product': ['apple', 'banana', 'apple', 'orange', 'banana'],
    'quantity': [10, 5, 7, 8, 3]
})
# Group the sales DataFrame by product
# Your code here

Hint

Use sales.groupby('product') and assign it to grouped.

3

Calculate total quantity per product

Create a variable called total_quantity that uses the grouped variable to calculate the sum of quantity for each product.

Data Analysis Python

import pandas as pd
sales = pd.DataFrame({
    'product': ['apple', 'banana', 'apple', 'orange', 'banana'],
    'quantity': [10, 5, 7, 8, 3]
})
grouped = sales.groupby('product')
# Calculate total quantity per product
# Your code here

Hint

Use grouped['quantity'].sum() to get the total quantity per product.

4

Print the total quantity per product

Print the total_quantity variable to display the total quantity sold for each product.

Data Analysis Python

import pandas as pd
sales = pd.DataFrame({
    'product': ['apple', 'banana', 'apple', 'orange', 'banana'],
    'quantity': [10, 5, 7, 8, 3]
})
grouped = sales.groupby('product')
total_quantity = grouped['quantity'].sum()
# Print the total quantity per product
# Your code here

Hint

Use print(total_quantity) to show the result.