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 tasks
  • 626 participants
  • 1,500 XP

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 or leaping from the roof of the stadium.

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?

This project gives you an opportunity to apply the skills from Introduction to the Tidyverse and Introduction to Data Visualization with ggplot2.

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

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

    Data ManipulationData VisualizationImporting & Cleaning Data