About Me
Hi, I’m Andrew Gafford.I’m a data analyst and data engineer with a background in mathematics and computer science. I specialize in transforming complex data into clear insights and reliable systems through building pipelines, analyzing patterns, and creating visualizations that support better decisions.My career has spanned multiple disciplines, but the common thread has always been storytelling through systems. Whether working with data models, analytics dashboards, or software, I focus on uncovering the structure behind complex problems and translating it into something meaningful, actionable, and easy to understand.
Featured Projects
This portfolio is more than a snapshot. It's a living, evolving showcase of my journey. New projects, insights, and creative endeavors will be added over time, reflecting my growth and curiosity. Check back often to see what's new and explore the latest chapters in my story.
Education Attendance EDA
Built an end-to-end attendance analysis using Python and Tableau to support school leadership decision-making. Integrated multiple student datasets, engineered attendance metrics, and designed interactive dashboards enabling school comparison, grade-level analysis, and student risk identification. Findings highlighted system-wide attendance challenges and revealed differing absenteeism drivers across schools, informing targeted intervention strategies.
Healthcare analytics
This project explores a synthetic healthcare admissions dataset to uncover patterns in patient billing, admission types, and cost variability. The work demonstrates an end-to-end analytical workflow, beginning with data ingestion and cleaning, progressing through SQL-driven exploration, and culminating in interactive visualizations and machine learning plans for predictive modeling.The dataset includes patient admissions over multiple years, with fields such as admission type, medical condition, billing amount, and date of admission. The goal is to derive actionable insights into cost drivers, detect outliers, and identify temporal trends in hospital billing.
This project transforms a synthetic healthcare admissions dataset into an interactive Tableau dashboard, enabling exploration of key metrics like patient visits, average length of stay, and total billed amounts. Users can analyze monthly trends and drill down into categories such as admission type, department, and insurance provider, surfacing operational and financial patterns for informed decision-making.The work demonstrates how SQL-based analysis can be combined with interactive visualization to turn raw data into actionable insights, with future opportunities for predictive analytics and deeper operational exploration.
AP Statistics Performance Tracker
A multi-table, relational Google Sheets system to analyze AP Statistics performance data. Built automated workflows, pivot-table reporting, and a dynamic dashboard to track student trends across quizzes and tests.This project highlights transferable skills in data modeling, cleaning, automation, and insight generation, directly aligned with real-world analytics and BI tasks.
Colorado Rockies
Loss Tracker
Streamlit web app documenting the progression of the 2025 Colorado Rockies, who are on pace to break the record for most losses in a season (121).Read about the making of the web app on my baseball analysis Substack!
Amazon Sales
This project analyzes Amazon product pricing, sales, and ratings data, applying data preprocessing, exploratory analysis, and modeling techniques to uncover trends and relationships in the dataset.The major milestone of this project was a model using categorical variables like rating and department and quantitative variables like actual_price to predict the discounted_price of an item.This project uses the Python libraries pandas, numpy, and scikit-learn, and displays my abilities at running queries using SQL.
Seattle Airbnb
This project visualizes pricing and geospatial trends of Airbnb's in Seattle with this interactive Tableau dashboard.The project reveals ideal locations for potential renters by zip code, pricing trends based on the number of bedrooms and time of the year, and simple linear model for pricing based on the square footage of the rental.
Reached on Error
Reached on Error is my baseball analysis blog dedicated to making sabermetrics accessible and engaging for fans of all levels, whether you're new to the game or a lifelong devotee. With a blend of in-depth insights and light-hearted storytelling, I break down complex statistics into relatable narratives that bring America's Pastime to life. From exploring iconic plays to uncovering hidden trends, Reached on Error is where baseball's numbers meet its soul.
Thank you!
I appreciate you taking the time to view my portfolio!I would love to chat and discuss working together. Feel free to use the form below to reach out to me directly via email.