Inspiration
The inspiration for "Dino Nuggies" stemmed from a curiosity about the connection between the prehistoric world and the modern energy landscape. We were intrigued by the idea that the geographical distribution of dinosaur fossils could potentially align with current fossil fuel reserves, thus offering insights into natural resource locations and the Earth's geological history.
What it does
"Dino Nuggies" analyzes the geographical distribution of dinosaur fossils and compares it with current global oil, coal, and gas production data. We provide plots that visualize these relationships, and a predictive model forecasts potential oil production in 2025 based on dinosaur bone discoveries and historical data.
How we built it
We built this project using Python for data analysis, employing libraries like pandas for data manipulation, matplotlib and seaborn for plotting, and Plotly for interactive visualizations. The web interface was created with HTML and CSS, with Flask serving as the backend to integrate our Python scripts and present the findings on a web platform.
Challenges we ran into
One of the main challenges was gathering and harmonizing data from various sources to ensure accuracy and relevance. Additionally, creating a predictive model that accurately reflects the potential correlation between fossil discoveries and fossil fuel production posed significant analytical challenges.
Accomplishments that we're proud of
We are proud of developing a comprehensive analysis tool that bridges historical dinosaur fossil data with modern energy production metrics. The creation of an intuitive and informative web platform to visualize these complex relationships is a significant achievement for our team.
What we learned
Throughout this project, we learned about the complexities of geological and energy data and how to analyze and visualize these datasets effectively. We also gained experience in integrating various technologies to create a cohesive and interactive application.
What's next for Dino Nuggies
For the future, we aim to refine our predictive models, incorporate more extensive datasets, and perhaps extend our analysis to other types of prehistoric data. Additionally, we plan to enhance the web platform's interactivity and user engagement, potentially developing features that allow users to input their datasets for custom analysis.
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