As of May 15, 2026

geoportal_DRER

Here is my portfolio for POSC497: Categorical Data and Data Visualization. I decided to highlight Lab 3: Exploring the Titanic Dataset with dplyr, Lab 5: Comparing Support for President Obama by Race, Lab 10: Interactive East Coast Election Map, and Lab 11: Machine Learning and Titanic Survival

In this project we extract CEL files on acute infectious mononucleosis (AIM) and chronic active Epstein-Barr virus (CAEBV), get top genes by fold change, use regex to extract the gene symbol from the platform using the bioconductor package, and then we tested these top 10 stimulated genes by fold change of AIM/healthy and CAEBV/healthy in random forest classification and found great results 100% accuracy in CAEBV genes on training and mixed results on AiM in training with only 2 classes 100% but the CAEBV class scored 67%, but both in this 3 class model of healthy, CAEBV, or AIM scored 75% accuracy on the hold out validation data using an 80/20 training/testing data split like most often. We will add these to the pathology database and Tableau to compare later. Our other mononucleosis project was with micro RNA that we could not use to compare to other EBV associated pathologies on Tableau. This will be nice to use.

Este proyecto presenta un análisis exploratorio del Chapel Hill Expert Survey (CHES) Latin America Expert-Level Dataset 2020, desarrollado en R y Quarto, utilizando técnicas de visualización y análisis de datos para examinar el posicionamiento ideológico y temático de distintos partidos políticos en Colombia.

Geoportal R - 2026

Teste de ainda não finalizado sobre imigração e poder de compra nas habitações em Portugal no ano de 2023.