Inspiration
- Struggling as beginner data scientists to run high-level data analysis
- A need for a user-friendly and precise application
What it does
Given a path to a csv data file and some inputs relevant to the desired statistical method, our application performs and visualizes K-Means Clustering, Simple Linear Regression, and Decision Trees.
How we built it
We used Kivy to provide us with an application and a window. We then used python scripts to read the csv data file, normalize the data, clean the data, and store it in a database structure. From there we have python and r scripts that perform various statistical methods. For visualization, we used r for the statistical methods.
Challenges we ran into
- Managing the flow of data through kivy, python, and r processes
- Formatting in kivy
Accomplishments that we're proud of
- Being able to implement 3 full algorithms
- Getting a simple and intuitive UI
What we learned
How to create an app combining python, r, and kivy
What's next for Stats Machine
- Implementing more statistical methods
- Handle more bad user inputs
- Drag and Drop csv functionality
- Supporting excel, text, and pdf files
- Package the application for easy downloading and installing
Log in or sign up for Devpost to join the conversation.