Premium project

TV, Halftime Shows, and the Big Game

Load, clean, and explore Super Bowl data in the age of soaring ad costs and flashy halftime shows.

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10 Tasks1,500 XP

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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 halftime shows with the biggest musicians in the world, sometimes [riding a giant mechanical tiger](https://youtu.be/ZD1QrIe--_Y?t=14) or [leaping from the roof of the stadium](https://youtu.be/mjrdywp5nyE?t=62). In this project, you will find out how some of the elements interact with each other. * What are the most extreme game outcomes? * How does point difference affect television viewership? * How have viewership, TV ratings, and advertisement costs evolved? * 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](https://en.wikipedia.org/wiki/List_of_Super_Bowl_champions), one with [TV data](https://en.wikipedia.org/wiki/Super_Bowl_television_ratings), and one with [halftime musician data](https://en.wikipedia.org/wiki/List_of_Super_Bowl_halftime_shows) for all 52 Super Bowls through 2018.

Project Tasks

  1. 1
    TV, halftime shows, and the Big Game
  2. 2
    Taking note of dataset issues
  3. 3
    Combined points distribution
  4. 4
    Point difference distribution
  5. 5
    Do blowouts translate to lost viewers?
  6. 6
    Viewership and the ad industry over time
  7. 7
    Halftime shows weren't always this great
  8. 8
    Who has the most halftime show appearances?
  9. 9
    Who performed the most songs in a halftime show?
  10. 10
    Conclusion
Technologies
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Topics
Data ManipulationData VisualizationImporting & Cleaning Data
Erin LaBrecque Headshot

Erin LaBrecque

Instructor at DataCamp
Erin is a marine geospatial research ecologist who combines physical and biological spatiotemporal data to understand marine ecosystems. She received her Ph.D. in Marine Science and Conservation from Duke University and is passionate about science communication and data visualization. When she is not playing with environmental and species datasets, Erin can be found hiking with her dog.
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