What It Does When we started this project, we wanted to find a way for users to get more use from the data they generate from their purchases. Our application has a user sign into their Capital One account and then provides them with a map that has the various vendors that they have made purchases at. Markers are colored differently depending on how frequently they are used (red meaning frequently and green meaning infrequently). Users can use this information to see their shopping trends and become more informed of their spending. Users are also able to long press on any of the vendors they have shopped at and quickly share that vendors information through multiple social media outlets.

We provided the ability to sort the displayed purchases by cost of the purchase, by a date range, or by purchase type (food,entertainment,etc.). The user can also go to the summary page of their app where it will tell them what merchant the user goes to most frequently, what merchant the user spends the most money at, which purchase cost the user the most, and the total money the user has spent.

By combining our filtering with our summary the user can do useful things like figure out their favorite place to eat by filtering by the food category and seeing which vendor they frequent the most. Another example is the user can filter by date and see how much they spent since their last paycheck.

Our Biggest Challenges One major problem we had was figuring out how to cache data in our application so we wouldn't have to make so many requests to the API every time we needed data. Once we figured out how to store the data, our app worked much better without as many network requests. We are also proud of all the filtering we can do on the map because we believe it provides a lot of potential use to the users. It took us a while to figure out how to make the app user friendlyBesides that, just figuring out the Capital One API and how to make an android application that utilized maps was challenging.

Future Work In the future, we see this application using machine learning to understand a user's purchases so it can provide suggestions similar to what the user already uses.

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