This study applies five foundational data analytics techniques to a Foreign Exchange (FX) trading blotter comprising 27,000 trade records executed between April 2023 and March 2024 at Union Bank of Nigeria. The dataset captures customer-facing FX spot, forward, and swap transactions across multiple currencies, client categories, and funding sources

Point pattern analysis of pharmacy locations in Warsaw using OpenStreetMap data. We test for spatial clustering (Ripley's K/L functions, quadrat test) and model pharmacy intensity as a function of distance to hospitals using an inhomogeneous Poisson process model. Data: 586 pharmacies, 270 hospitals/clinics, Warsaw administrative boundary (EPSG:2180). Methods: KDE, CSR envelopes, rhohat, ppm(). Course project for Point and Line Pattern Analysis, WNE UW, 2025/26.

This portfolio highlights selected work from my Spring 2026 semester taking POSC497: Categorical Data Visualization and Data Visualization. I chose 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. Across these labs, I used R to clean data, summarize patterns, build visualizations, create interactive maps, and apply machine learning models.

Autores Anano Bakradze Ana María López Hernando Ester Querol Cebrian Aina Ruiz Andújar Alejandro Garcia

Este proyecto examina cuantitativamente cómo la era digital redefinió la industria musical a nivel global. A través de cinco ejes de análisis, evolución de formatos, modelos de ingresos, concentración del mercado, consumo regional en México y el fenómeno de la música latina, se exploran los datos que explican por qué el streaming domina hoy el 85% de los ingresos mundiales, cómo los algoritmos y las plataformas digitales moldean la identidad de las nuevas generaciones, y qué factores distinguen estadísticamente a las canciones más exitosas. Un recorrido por los números detrás de la música que escuchamos.