We are interested in learning how to analyze data in new and interesting ways.
What it does
Our program takes asks a user to log in to their Google account, in order to access their Gmail inbox. Then, it goes through the inbox and finds quantity and frequency of unique senders. The output is then visualized by use of the Initial-State visual API. The visuals generate a robust and stylized output that is easier to interpret.
How we built it
We started with Google's Gmail service, which has API's ready-to-use with near seamless integration. Using this API, we were able to access the user's Gmail account, scan through each email in their inbox, and retrieve the sender's domain.
All of the driving code was created using python.
Challenges we ran into
Figuring out exactly what data to display was a challenge, considering just how much the Google API can pull from an account. Inherit in emails, a sender's domain could very well be an alias, which would possibly skew our results.
Another obstacle was pulling the information from the Gmail API and sending it to Initial State. Luckily, Initial State had very helpful tutorials on our integration method (from Python).
One challenge, left unconquered, is incorporating our program in an html page.
Accomplishments that we're proud of
We were able to successfully integrate, not one, but two API's with little to no prior experience with them.
What we learned
multiple Python integrations
Initial State Visualization API
What's next for InboxAnalyzer
We look forward to the possibility of extending features, such as:
--publishing in the website where anyone can access our program
--linking together results from multiple users, in order to generate a broad report about domains' behavior
--generating a course of action in order to cut down on unwanted emails
--adding support for other email provider such as Yahoo and Hotmail
--and many more possibilities