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With Intermediate Python under your belt, you can already analyze and extract meaningful insights from various sources. For this set of projects, you will use a combination of data manipulation and visualization to explore television data. In this project's guided variant, you will look at Super Bowl Data, generating insights into game outcomes, viewership, and even halftime shows. In the unguided variant of this project, you'll develop an informative plot that helps to visualize the viewership and quality of The Office throughout its nine seasons.
- 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?
Data Science Educator
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!
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