Estudio estadístico de los pozos en Brasil, clasificando a sus operadores en categorías estratégicas (Estatales, Nacionales y Extranjeras). Incluye tablas de frecuencia, visualización gráfica y un modelo de probabilidad empírica para la inferencia de datos.

PCA

Clustering

This project applies association rule mining to a subset of the InBillo dataset in order to identify interpretable combinations of business characteristics associated with low customer trust. The analysis focused on non-score attributes such as firm age, size, legal form, financial transparency (debts) and online presence, using the Apriori algorithm to identify and extract repetitive patterns.

This report applies unsupervised learning methods to World Development Indicators (WDI) data to explore latent global development structures. Principal Component Analysis (PCA) is used to reduce dimensionality and identify interpretable development dimensions, followed by hierarchical clustering in the reduced space to derive stable country groups. The analysis emphasizes methodological justification, validation, and interpretability.

Reporting Flexdashboard – Analyse des vols NYC 2013