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Running with Data
2019 Boston Marathon Analysis
There is less than a month until The TCS New York City Marathon, which has us runners thinking about how well we’ve prepared for the 26.2-mile journey through the five boroughs. While we all analyze the course, continue to train, and stress about weather on race day, I’ve wanted to do a statistical analysis on the 2019 Boston Marathon. I’ve chosen this marathon for 3 reasons: it is one of the largest marathons in the world, the April 15, 2019 results are released, and a lot of Boston Marathoners are from NY (you’ll see below).
There are approximately 570 marathons held in the United States every year. The Boston Marathon is the world’s oldest marathon which started in 1897. I wanted to start this project with statistical analysis. The analysis includes charts and descriptions followed by a conclusion of the data.
Web Scraping
I start the project by collecting the data from the web. The source used to web scrape the results of the race was https://www.baa.org/races/boston-marathon/results.
I used Beautiful Soup, a python library, to pull results into a list/dataframe. Then conducted statistics on the data.
