InstaFood

• 

  Our Data tree (D3.JS)

Inspiration

Every evening we went to our parents and asked the same question of what was for dinner and

eventually the answer started becoming the same thing and our parents sounded sick of it, so we

developed Instafood as a way to get our answer immediately and also make sure that it was different every time

What it does

Our project ask you questions and uses the answers to recommend a food that fits your profile.

How we built it

We gathered data on an excel sheet with a set of questions for each combination. We converted the spreadsheet to a CSV file. Next we used a python script to convert it to a JSON format. We used a D3.Js program that dynamically displays our data which is in a JSON format.

Challenges we ran into

Some challenges we ran to were the learning and python and D3.JS in 3 weeks

Accomplishments that we're proud of

Successfully learning to code in python, a little bit in D3.JS, and creating local python web server

What we learned

We learned in general python and how to use the libraries of D3.JS. Next we learned data gathering and data manipulation.

What's next for InstaFood

Once we get more comfortable with python we would like to use a rule based or AI based engines

to select the food choice. Furthermore, we would like to increase our library of dishes and making our user interface more dynamic. Also if possible we would like to host it on public servers so other users could try.

Built With

• d3.js
• jupyter
• notebook
• python
• webserver