Solving Real-World Data Analysis Problems With Python Pandas - Lego Dataset Analysis

Explore a comprehensive data analysis project using Python Pandas to analyze a Lego dataset. Learn how to read CSV files, filter DataFrames based on conditional parameters, and group data by column values for aggregation. Walk through practical tasks, including determining the percentage of Star Wars-themed licensed sets, identifying years when Star Wars wasn't the most popular licensed theme, and calculating unique set releases per year from 1955 to 2017. Gain hands-on experience with real-world data analysis techniques while working with the extensive Rebrickable database, which contains information on every LEGO set ever sold.

- Introduction
- Getting started w/ Lego analysis project
- How to follow along if you are not a premium DataCamp subscriber GitHub
- Project tasks overview
- Basic exploration of the dataset
- Task #1: What percentage of all licensed sets ever released were Star Wars Themed?
- Task #2: In which year was Star Wars not the most popular licensed theme?
- Bonus Task: How many unique sets were released each year 1955-2017?
- Conclusion!