● Explored Covid trends using Python to highlight relationships between death and vaccination rates by joining two datasets that varied from 50,000 to over 1,000,000 cases consisting of Covid-19 deaths and Vaccines Administered throughout the U.S
● Produced plots showing the progression of Covid cases throughout February 2020 to February 2023

● Utilized Python and PySpark on two 400,000 - 500,000 row dataset to cross - analyze voter turnout and party traits.
● Used machine learning classifiers such as Logistic Regression, Decision Tree, Random Forest, and Naive Bayes to train the model and predict voting trends.