Where U.S. craft breweries are, and why: a spatial machine learning project

We analyse the spatial point pattern of Warsaw Veturilo bike-sharing stations in two contrasting districts — the dense historic core (Śródmieście) and a large mixed/peripheral district (Mokotów). Using kernel intensity estimation, Ripley’s K/L and the pair correlation function with Monte-Carlo envelopes, nonparametric covariate analysis (rhohat) and inhomogeneous Poisson process models (ppm), we test whether an inhomogeneous Poisson process explains the observed pattern. Apparent clustering in Śródmieście disappears once spatially varying intensity is accounted for; the pattern is well described by an inhomogeneous Poisson process driven primarily by metro proximity. Mokotów shows only weak, borderline inhomogeneity and is effectively consistent with a Poisson process at its smaller sample size.

This document presents a comprehensive visualization study of global development trends from 1952 to 2007 using the Gapminder dataset. The analysis demonstrates both foundational ggplot2 techniques and advanced visualization methods using extension packages.

This report analyzes global meat consumption patterns using Principal Component Analysis (PCA) to reduce dimensionality and identify dietary habit clusters.

This document details a Market Basket Analysis performed on a retail dataset using R and the arules package.