In the Spring of 2023, the Texas A&M Institute of Data Science held a competition for students to perform analysis on wildfire data and address challenges provided to the competitors. This project focused on the need for improved avenues of communication for individuals concerned about wildfires in their local proximity.

PHYS 216: Lab 3
The official title of this course was Experimental Physics and Engineering - Mechanics and the lab covered Frictional Forces. In this experiment, the coefficients of kinetic and static friction were calculated by analyzing the position, velocity, and acceleration data collected by a data aquisition unit (DAQ). The linked code files were created to analyze, plot, and perform calculations on the data. Most people used Excel to perform these tasks.

This project demonstrates an understanding in object-oriented programming with the use of class inheritance and abstract base classes. Using the Pandas library, dataframes were created, cleaned, analyzed, and had columnwise calculations performed on them. Plots created using Matplotlib and tables created using Pandas were configured aesthetically to best communicate the data. Equations were displayed using LaTeX.

PHYS 217: Lab 2
The official title of this course was Experimental Physics and Engineering - Electricity and Magnetism and the lab covered Electric Fields. In this experiment, the electric field produced by four differently shaped metal plates was plotted after taking a voltage readings accross the region with a DAQ.

This notebook required much of the same skills as the above. The Dataclasses library was used in this lab for its simple implementation of model-like objects. The electric fields were visualized using Matplotlib's quiver plot and imshow.