A comparison of Data Formats using books I like

This analysis examines Wrexham AFC’s performance across three seasons spanning multiple divisions of English Football, from League Two (E3) through League One (E2) to the Championship (E1). The analysis focuses on identifying Wrexham’s closest competitors in each season and evaluating their competitive positioning.

An example of taking untidy data from https://glaad.org/trump-accountability-tracker/ and processing it into a form that makes analysis more accessible

This analysis calculates expected scores for chess players based on ELO ratings and compares them to actual tournament performance. The analysis uses the ELO expected score formula from Glickman’s “A Comprehensive Guide To Chess Ratings” paper.

This analysis examines a large dataset of political news articles to develop automated classification methods for identifying Trump-related and Fox News-related content. The dataset spans multiple years of political coverage during a period of significant media activity and political events. This work builds upon research in automated news categorization and applies scalable text processing techniques to handle large-scale news corpora. The methodology demonstrates efficient processing of substantial datasets while maintaining classification accuracy for media bias detection and political sentiment tracking.