ethandbard,Ethan Bard,github

Hi there 👋

I'm a Data Scientist/ Analyst from Palm Harbor, Florida. 🌴

Now

👨‍💻 Institutional Research Analyst at Florida Polytechnic University in Lakeland, Florida.
👨‍🏫 Adjunct Instructor - Introduction to Data Science at Florida Poly
📃 Researching impact of social factors, medical factors, and religious attendance on prevalence of cardiovascular disease

Bio

🎓 Master's Degree in Computer Science - Data Analytics from Florida Polytechnic University
:computer: I use daily: .r .py .sql excel PowerBI tableau
📊 Interested in data analysis and visualization, dashboards, and data driven apps.

Portfolio

❤️ NHANES Religious Attendance and CVD - in progress
🌎 Covid-19 Variants Analysis and Forecast
💊 NHANES Hypertension EDA
🐶 Chewy.com Web Scrape - in progress
🏃 Boston Marathon Principal Component Analysis and Outlier Detecting with Clustering
⚙️ Shiny Root Finding
🍟 McDonalds Menu Data Principal Component Analysis and Clustering

Ethan Bard's Projects

bostonmarathonanalysis2017

Analysis of Boston Marathon 2017 Results

cap5735

Repository for work completed as part of CAP5735 Data Visualization and Reproductible Research

covariants

Real-time updates and information about key SARS-CoV-2 variants, plus the scripts that generate this information.

covid19

COVID19 Dataset analysis for graduate proejct

dataviz_final_project

Data Visualization and Reproducible Research final project

mcdonalds_analysis

Data Mining final project, Mcdonalds Menu

practice-repo-sp2023

This is a repo for practicing markdown and github operations for COP 2073 - Intro to data science.

religious_attendance_cvd

Data and R analysis of NHANES 2007-2008 data regarding cardiovascular disease and various demographic/risk factors including religious attendance.

The objective of this project is to incorporate various root finding methods into a demonstrative Shiny application using R. The application interface provides the user the ability to select a desired method and apply it to multiple example functions. The results generated from applying the selected method to the example function are displayed in a plot which indicates the root or fixed point of the function. Additionally, the user is able to modify the parameters relevant to the method being used so that multiple solutions may be found if present. The motivation of this project is primarily to serve as practice in developing application dashboards using Shiny while implementing some of the computational methods covered in this course.

Recommend Projects