Build a Customer Data Filter with Pandas

Level: Beginner

Your task for today is to create a script that filters customer data from a CSV file based on specific criteria and exports the results to a new CSV file.

Project Task

Create a customer data filter and exporter that:

• Uses pandas to read customer data from a CSV file

• Filters customers based on purchase amount (e.g., customers who spent over $1000)

• Filters by customer location (e.g., customers from a specific country)

• Displays the filtered results in the console

• Exports the filtered data to a new CSV file

• Shows summary statistics (total customers found, average purchase amount)

This project gives you hands-on practice with data filtering, CSV operations, and data analysis — essential skills for working with real-world business data.

Data Source

You can use this customers.csv file for this project.

Expected Output

Customer Data Filter & Exporter
================================

Loading customer data from ‘customers.csv’...
Total customers loaded: 150

Applying filters:
- Purchase amount > $1000
- Country: USA

Filtered Results:
-----------------
   Customer_ID         Name  Purchase_Amount Country
5           6    John Smith          1250.50     USA
12         13   Sarah Jones          1500.00     USA
28         29  Michael Brown         2100.75     USA
45         46   Emily Davis          1350.25     USA

Summary Statistics:
-------------------
Total customers found: 4
Average purchase amount: $1550.38

Exporting to ‘filtered_customers.csv’...
Export complete!

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Skeleton and Solution

Below you will find both a downloadable skeleton.py file to help you code the project with comment guides and the downloadable solution.py file containing the correct solution.

Get the code skeleton here:

Get the code solution here: