Counting duplicates in Pandas - Mini Project: Build & Apply

Counting duplicates

📖 Scenario: You work in a small bookstore. You have a list of books sold today, but some books appear more than once because multiple copies were sold. You want to find out how many times each book was sold.

🎯 Goal: Build a small program using pandas to count how many times each book title appears in the sales list.

📋 What You'll Learn

Create a pandas DataFrame with a column named Book containing the exact book titles given.

Create a variable called count_duplicates that counts how many times each book title appears.

Print the count_duplicates variable to see the counts.

💡 Why This Matters

🌍 Real World

Counting duplicates helps businesses understand which products sell more and manage inventory better.

💼 Career

Data analysts often count duplicates to summarize data and find popular items or repeated entries.

1

Create the sales data

Import pandas as pd and create a DataFrame called sales with one column named Book. The column should have these exact values in this order: 'Harry Potter', 'The Hobbit', 'Harry Potter', '1984', 'The Hobbit', 'The Hobbit'.

Pandas

import pandas as pd
# Create the DataFrame called sales with the Book column
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary where the key is 'Book' and the value is the list of book titles.

2

Set up counting duplicates

Create a variable called count_duplicates that counts how many times each book title appears in the sales DataFrame using the value_counts() method on the Book column.

Pandas

import pandas as pd
sales = pd.DataFrame({
    'Book': ['Harry Potter', 'The Hobbit', 'Harry Potter', '1984', 'The Hobbit', 'The Hobbit']
})
# Create count_duplicates using value_counts on sales['Book']
# Your code here

Need a hint?

Use sales['Book'].value_counts() to count duplicates.

3

Print the counts

Print the variable count_duplicates to display how many times each book title appears.

Pandas

import pandas as pd
sales = pd.DataFrame({
    'Book': ['Harry Potter', 'The Hobbit', 'Harry Potter', '1984', 'The Hobbit', 'The Hobbit']
})
count_duplicates = sales['Book'].value_counts()
# Print count_duplicates
# Your code here

Need a hint?

Use print(count_duplicates) to show the counts.

4

Filter books sold more than once

Create a variable called duplicates_more_than_one that filters count_duplicates to keep only books sold more than once (count > 1). Then print duplicates_more_than_one.

Pandas

import pandas as pd
sales = pd.DataFrame({
    'Book': ['Harry Potter', 'The Hobbit', 'Harry Potter', '1984', 'The Hobbit', 'The Hobbit']
})
count_duplicates = sales['Book'].value_counts()
print(count_duplicates)
# Filter count_duplicates for counts greater than 1 and assign to duplicates_more_than_one
# Print duplicates_more_than_one
# Your code here

Need a hint?

Use boolean indexing like count_duplicates[count_duplicates > 1] to filter.