Nashville, TN is known for its robust concert experience. With numerous stages at varying sizes, a live band is easy to find any night of the week. The saturation of music in Nashville is high, and it might be tough to imagine what else you might do for fun aside from going to see a band. I wanted to challenge the notion of Nashville as the "Music City" and quantify the popularity of events.

In order to create a database of events in Nashville I used the website www.Nashville-Theatre.com because it provides a wide variety of events across most of the major venues in the area. To get my data, I used a series of complex web-scraping packages available in Python - requests, BeautifulSoup, Pandas, Regular Expressions, and literal_eval.

This project required a combination of Python coding skills and familiarization with both HTML and JavaScript. The principle challenge in this scraping project was the URLs. How a URL is built dramatically changes how scraping can be automates through a website, and because of the way Nashville-Theatre.com uses URLs, my code needed to be written differently for various parts of the website in order to complete my dataset (e.g. ticketing information was not in the same area as categorical information).

Limitations

This study is not a conclusive review of all events in Nashville, and the project is based solely on the events listed on this website. Categorical information was only provided for about half of the listings, and appear to be reserved for the most popular events/venues (I believe that this is a paid advertising feature). At times I will refer to the number of events, which is all events in my database, and at times I will refer to category (concerts, theatre, etc.) and I will only be able to use about half of the events in my database to make categorical inferences.

Capacity in this analysis refers to the number of seats that a venue could potentially sell, and this project does not attempt to determine ticket sales, revenue, or remaining seats available.