Environmental Data Analysis

One of the graphs from our country analysis

Inspiration

We all hail from across the United States, and among us, have seen many different parts of the world. As a result, doing a project centralized on helping society and the environment, through data visualizations, spoke to us, and this is our work on it.

What it does

The first part of this project is focused on looking at ESG (Environmental, Societal, and Governance) metrics for various countries around the globe, while the second part builds a machine learning model predicting revenue based on financial data in conjunction with company-specific ESG scores.

How we built it

We built the project completely in Kaggle, with assistance from various HackGT mentors and Stack Overflow.

Challenges we ran into

Initially, we planned on creating a robot which could play a game enhancing teamwork and communication among kids, using Java and C, however, due to various hardware and software problems, we had to rapidly pivot our idea. As a result, although we had many setbacks, I am very proud of our final product.

Accomplishments that we're proud of

I'm proud of all of us for building this project, especially as it was all of our first times at a hackathon, and so, everything was new to us. We were often pushed to our limits, but we persevered, learned a lot, and created a project that we are all very happy with, and one that we hope you all enjoy as well!

What we learned

We learned various data science and machine learning concepts, and how best to apply them to various contexts. We also learned how to know when things are going wrong, and how to keep pushing without running into a wall and preventing successful progress. Finally, we all grew closer as a team.

What's next for Environmental Data Analysis

We hope to enhance the machine learning model through more specific weights, and potentially changing the base model as well. Furthermore, if we could get more data, and add that to our model, that would greatly help with making sure that the information provided is accurate.