I use a variety of data manipulation techniques to explore different aspects of Lego's history.
Project Description:
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!
Technology: Python
Topics:
- Data Manipulation
- Data Visualization
- Importing & Cleaning Data
Python Prerequisites: Data Manipulation with pandas
Project Tasks:
- Introduction
- Reading Data
- Exploring Colors
- Transparent Colors in Lego Sets
- Explore Lego Sets
- Lego Themes Over Years
- Wrapping It All Up!
Tasks were created by Ramnath Vaidyanathan, VP of Product Research at DataCamp.
About Ramnath Vaidyanathan:
He is the VP of Product Research at DataCamp, where he drives product innovation and data-driven development. He has 10+ years experience doing statistical modeling, machine learning, optimization, retail analytics, and interactive visualizations. He brings a unique perspective to product development, having worked in diverse industries like management consulting, academia, and enterprise softwares.
Prior to joining DataCamp, he worked as a data scientist at Alteryx, leading the roadmap for interactive visualizations and dashboards for predictive analytics. Prior to Alteryx, he was an Assistant Professor of Operations Management in the Desautels Faculty of Management at McGill University. His research primarily focused on the application of predictive analytics and optimization methodologies to improve operational decisions in retailing. He got his Ph.D. in Operations Management from the Wharton School.