In this video we walkthrough a data analysis project on DataCamp. This project has us walk through a Lego dataset and answer a few questions. To do our analysis we use the Pandas library of Python.

Check out DataCamp!
https://bit.ly/KeithGalliDCFeb22

Link to my GitHub:
https://github.com/KeithGalli/legoan...

From the DataCamp website:
The Rebrickable database includes data on every LEGO set that has ever been sold; the names of the sets, what bricks they contain, what color the bricks are, etc. It might be small bricks, but this is big data! In this project, you will get to explore the Rebrickable database and answer a series of questions related to the history of Lego!

Link to Rebrickable database: https://rebrickable.com/downloads/

Some skills worked on in this video:
Reading CSV files with Python
Filtering DataFrame based on conditional parameters
Grouping data by column values and aggregating it

btw, I apologize at about the 25minute mark I started having microphone issues, I'll have it solved by my next video.

Thank you to DataCamp for sponsoring this video :)


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Practice your Python Pandas data science skills with problems on StrataScratch!
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Video Timeline!
0:00 Introduction
1:05 Getting started w/ Lego analysis project
2:33 How to follow along if you are not a premium DataCamp subscriber (GitHub)
4:01 Project tasks overview
5:40 Basic exploration of the dataset
9:45 Task #1: What percentage of all licensed sets ever released were Star Wars Themed?
24:23 Task #2: In which year was Star Wars not the most popular licensed theme?
34:00 Bonus Task: How many unique sets were released each year (19552017)?
42:26 Conclusion!