This presentation introduces the Ethiopian Kale Altitude Explorer, a Shiny application designed to visualize and filter Ethiopian kale accessions based on altitude. The app allows users to interactively select altitude ranges, view accession locations on a Leaflet map, and explore summary statistics and accession details. Built for accessibility and clarity, the app supports ecological research and breeding efforts by highlighting altitude-adapted accessions. This 5-slide pitch outlines the problem, features, embedded R code, and future directions for expanding the tool’s impact.

This case study explores historical forex data from 2008–2023 to answer a key business question: Which major currency pairs provide the best balance of profitability and consistency for retail traders? Using data cleaning, transformation, and analysis in R, I evaluated daily returns and volatility for EUR/USD, GBP/USD, and USD/JPY. The study includes visualizations of trends, distributions, and volatility comparisons, and concludes with actionable insights for traders, educators, and prop firms. This project demonstrates my ability to:  Define a business problem  Clean and prepare real-world financial data  Perform return and volatility analysis  Communicate insights clearly with visualizations and recommendations