If you know us (you honestly don’t even need to know us all that well), it’s no secret that Lynsey and I love coffee. You also might be aware that we recently moved our family to Philadelphia…had we mentioned that? Post move, the first task of this coffee loving set of parents was to FIND ALL THE COFFEE Philly has to offer. Sure, we could have simply done a survey or asked some people we know in the area, but that’s crazy talk. As a wannabe data scientist, I like things quantified and analyzed and sometimes overly complicated. So why not scrape some coffee shop data off Yelp? Naturally! I spent a few hours writing some R code and was able to extract Yelp records on 816 coffee establishments in the city of Philadelphia. Once I had the name, address, average rating, price, and a number of reviews for each shop, I geolocated the address to find out which Philly neighborhood they belonged to using the Phillyhoods.net API. The results…the Tableau dashboard below, chock full of all the caffeinated details a Philly parent could need on any given Saturday morning.
You’ll notice via the heat map that University City and Rittenhouse have the monopoly on the number of coffee dealers. Joe Coffee in University City being my personal go-to when I’m at work…sorry Lynsey! I highlighted the number of Dunkin Donuts + Starbucks in order to put into perspective the number of more authentic coffee shops on the list (not that we don’t appreciate the two chains). The variated bar chart shows the average rating of coffee shop by neighborhood. Mt. Airy is nestled at the top in the first 10, and we can vouch for this rating thanks to the amazing High Point Cafe we have come to adore. There’s a ton of information and conclusions you can gather from this viz. Now that we have these data, I am excited to dig in and start analyzing…and sipping. Have a look around, read the tool tips and dive in…it’s delicious.
Whether it’s coffee consumption, wine preferences, family habits or some other lifestyle quantifiable question…we’re always on the lookout for MORE DATA. Specifically, we’re searching for members to join our Everyday Data Team. It’s fun, simple and silly…CLICK below + fill out the short survey to join!