Digital Mapping
This project maps the locations of approximately 130 sports statues nationwide. It includes details, images, and histories of each utilizing data from the research of Ashley Loup, PhD. It is written in Python using libraries such as Dash, Pandas, and Plotly.
Formula 1 Dashboard
Here, I have built a data visualization dashboard using Formula 1 data from the FastF1 API. It incorporates several types of visualizations adapted for use in Dash and Plotly. It is not currently deployed to the web due to it’s memory requirements exceeding Heroku’s basic dyno service. A screenshot can be viewed on GitHub, and it can easily be cloned and run locally.
Finn CDI Project Database
Here, I established a SQL database for Finn CDI projects and implemented it using Bootstrap architecture. The database is written using MySQL while the site was developed with HTML, CSS, and PHP. The initial version of the site was a final project for a Database Design and Management course at Rutgers University. The project is ongoing and the current site has limited functionality; although, the framework is proven and functional.
Report on D3.js
This final project for a Data Visualization course is a full Bootstrap website examining d3.js as a tool for data visualization in the modern landscape. It includes analysis of the d3.js library as well as comparisons between d3.js code and Observable code. It also looks at how to integrate d3.js with Javascript frameworks like React and considers the usefulness and application of d3.js in current data visualization practices.
InkyPi Plugins
These fun projects employ data wrangling and visualization techniques to showcase WNBA and Formula 1 event data on Raspberry Pi powered E-Ink displays. The plugins are written in Python, Django, and HTML.
WNBA Finals Dashboard
This data visualization dashboard uses data from the 2025 WNBA Finals. It uses bar charts to display total data over the four final games for the top ten individual players in each category. Users can then click on individual athletes to see their data plotted across all four games. The dashboard can be viewed by clicking below and the code can be accessed via GitHub.