Phill Me In

What is Phill Me In?

Phill Me In is a web application that rates locations in Philadelphia based on a number of factors. The data is mostly from the OpenDataPhilly portal, which has collections of CSV's filled with the city's data. However, this data is not easily accessible to most people; it's tedious to filter through relevant datasets, and further, make sense of latitudes, longitudes, and figure out what's really around you.

This is why we created Phill Me In: it does all the hard work for you. We've fed in datasets on a variety of topics, which accumulate to over 80,000 rows of data. All that we ask the user to do is to enter an address in Philly, and Phill Me In will look through the megabytes of data to show you what's relevant. It rates neighborhoods based on a number of parameters, such as:

Security
Emergency Services
Sanitation
Air Pollution
Health Services
Education
Parks and Recreation

You can even choose one of these seven parameters instead of entering an address, and we'll show you a heat map of that parameter overlaid on the map of Philly (some of these visualizations actually have very interesting geographical trends).

Why would I use this?

It's a great tool if you're a house-hunting student in Philly, or want to analyze local trends as a government official. The aim of Phill Me In is to simplify the process of looking through huge datasets and various sources of information to pick out what you need: and further, present it to the user through intuitive visualizations (like heat maps and bar graphs).

Even if you don't fall into any of those categories, it's still a good way to get to know your neighborhood -- there's a good chance you'll find out things about where you live that you never knew before!

Technical Challenges

Our biggest problem was that we had too much data. We didn't want it to go to waste, of course, but wanted to keep the computations quick at the same time. For example, we have a dataset with over 70,000 Crime Reports from 2014. To create a heat map for the safety parameter, we would have to run through all these rows for every locality in Philly (~300 of them). Fortunately, we found a couple of hacks around this (caching the results certainly helps) eventually.

The other challenge was making sense of the data that we had. For example, how would we convert data from Air Monitoring Stations into Air Pollution scores for the entire city?

What's next for Phill Me In

A system like this will only improve when there's more sources of data, as well as continuously updated data to work with. Phill Me In's simplicity allows us to scale to include new data sets relatively easily. After making Phill Me In, we hope to see more cities make their data openly available for similar use. We hope that products like these will improve governments' efficiency and strengthen the communication between citizens and their elected representatives.