This was the first full project I made during my Python study on DataCamp.The project is part of the Data Scientist track.
Technology: Python
Python Prerequisites: Intermediate Python
Topics:
- Data Manipulation
- Data Visualization
- Importing & Cleaning Data
Project Description:
Whether or not you like football, the Super Bowl is a spectacle. There's drama in the form of blowouts, comebacks, and controversy in the games themselves. There are the ridiculously expensive ads, some hilarious, others gut-wrenching, thought-provoking, and weird. The half-time shows with the biggest musicians in the world, sometimes riding giant mechanical tigers or leaping from the roof of the stadium. And in this project, you will find out how some of the elements of this show interact with each other.
Questions like:
- What are the most extreme game outcomes?
- How does the game affect television viewership?
- How have viewership, TV ratings, and ad cost evolved over time?
- Who are the most prolific musicians in terms of halftime show performances?
The dataset used in this project was scraped and polished from Wikipedia. It is made up of three CSV files, one with game data, one with TV data, and one with halftime musician data for all 52 Super Bowls through 2018.
Project Tasks:
- TV, halftime shows, and the Big Game
- Taking note of dataset issues
- Combined points distribution
- Point difference distribution
- Do blowouts translate to lost viewers?
- Viewership and the ad industry over time
- Halftime shows weren't always this great
- Who has the most halftime show appearances?
- Who performed the most songs in a halftime show?
- Conclusion
Tasks were created by David Venturi, Data Science Educator.
More about David Venturi:
David graduated from Queen's University with a dual degree in Chemical Engineering and Economics. After working for a year, he discovered online education (in the early MOOC era) and became enamored with its potential. He has since created content to help people navigate the space, including a DIY data science master's program, Class Central's Data Science Career Guide, courses for Udacity's Data Analyst Nanodegree program, and several DataCamp courses and projects. Visit his website to say hi!