A comprehensive end-to-end data analysis of 10 million retail receipts using R. This report covers large-scale data cleaning, exploratory data analysis (EDA), and key business insights.

In-class Assignment: Business Intelligence

Supplemental Growth Curve Model for Bartholow et al. paper

A quantitative analysis of 45 S&P 500 market leaders across 9 major sectors. This project utilizes K-Means Clustering (Unsupervised Machine Learning) to identify risk/return regimes automatically. It features a Facet-Wrapped visualization to demonstrate how volatility profiles differ significantly between Defensive sectors (Utilities, Staples) and Growth sectors (Technology). Built using R, ggplot2, and quantmod.