Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
Alternative ggplot2 use: Crochet Patterns
Ryan McShane, Ph.D. demonstrates an unconventional use of ggplot2 to aid in crochet pattern design decisions. While attending a virtual statistics conference, McShane's partner works on a Chicago flag-inspired crochet baby blanket. To assist with visualizing the design, McShane employs ggplot2 to represent different pattern possibilities for the granny square arrangement, effectively combining data visualization with crafting. The article includes code snippets and detailed explanations on how to implement this creative application of ggplot2, turning a statistical tool into an artistic aid.
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An Exploration of Simple Features for R
Introduction to GIS with R through the sp and sf packages.
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An Exploration of Simple Features for R
An exploration of the implementation of simple features standard by the sf package for R
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An Introduction to R
This content encompasses a comprehensive guide to R programming for beginners, covering the fundamentals of R language and its application in data analysis. Starting with installation instructions for R and RStudio, the book provides an orientation to the RStudio interface, discusses project management, and introduces R style guides. The book progresses to cover R's basic syntax, objects, and functions, as well as data management, including data types, structures, importing/exporting, and wrangling. It also delves into graphics with base R and ggplot2, simple statistics, programming structures in R, reproducible reports using R markdown, and version control with Git and GitHub. This primer is ideal for those new to R and aims to equip readers with the necessary skills for proficient data analysis with R tools.
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Analyzing my music listening data with Positron's Databot
Simon Couch explores his music listening data using Databot, an AI agent within Positron. He exports his iTunes Library metadata as an .xml file and uses the tidyverse in R to conduct a personalized analysis akin to Spotify Wrapped. Couch highlights Databot's ability to understand and manipulate the .xml data structure, converting it into a tidy tibble and performing various data wrangling tasks to identify top songs, artists, and albums. This post illuminates how Databot can simplify and accelerate exploratory data analysis, demonstrating its applications on actual personal data and providing insights into his musical preferences.
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Animated active fire maps using NASA FIRMS data in R
This video tutorial demonstrates how to create animated active fire maps using NASA's Fire Information for Resource Management System (FIRMS) data within R. Viewers will learn the techniques for importing and handling satellite-derived fire data, processing it, and then visualizing the active fire spots over time using animation tools in R. The tutorial is designed for data analysts, environmental researchers, and GIS specialists interested in mapping and geospatial analysis to monitor wildfires and understand spatial patterns using NASA's publicly available data sets in R programming environment.
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Apple Music Wrapped with R
Andrew Heiss demonstrates how to create an Apple Music Wrapped equivalent using R, providing a data-driven alternative for Apple Music users who lack the Spotify Wrapped feature. Heiss shares his personal preference for owning music files over streaming, utilizing iTunes/Apple Music and iTunes Match for cross-device access. The article details extracting song metadata from an XML file, which stores play counts and other information, to perform data analysis and visualization, mimicking the Spotify Wrapped experience. He criticizes the single-entry play count system but optimistically approaches creating personalized music data statistics.
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Applied Data Skills
The 'Applied Data Skills' book by Emily Nordmann and Lisa DeBruine is designed to teach the fundamentals of data processing and presentation using R. It guides learners through data import, cleaning, summarization, visualization, and report generation, aiming to provide skills for professional reporting and presenting. The book is part of a 10-week course with each chapter introducing new concepts and practical exercises. It emphasizes learning through practice, error resolution, and the efficient use of help resources rather than memorization. The goal is to enable learners to create automated, updateable reports and visualizations with R.
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Architecting a Data-Driven Meritocracy for Kenyan Baseball
Keith Karani, founder of Diamond Digest Labs, writes about building Basepoint, a data platform designed to close what he calls the “Visibility Gap” in sports analytics for emerging markets. In Kenya, valuable baseball performance data exists but sits fragmented across local spreadsheets and individual team devices, invisible to scouts and the wider world. Basepoint addresses this by migrating those raw, scattered statistics into a centralized, cloud-native database connected via Positron, turning hidden local data into a verified, scout-ready digital CV for Kenyan players.
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argonDash
Argon Shiny Dashboard Template is a Bootstrap4 dashboard template for creating Shiny applications. It requires the installation of the 'argonR' package. The template includes vertical and horizontal layouts and is based on the original argon dashboard HTML template designed by Creative Tim. The project has a Contributor Code of Conduct and is licensed under GPL-2. It is developed by David Granjon.
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Atmospheric Simulation in R
Tyler Morgan-Wall's 'Atmospheric Simulation in R' dives into the intriguing world of atmospheric models and data visualization within the R ecosystem. Part of the larger 'Rayverse' suite, this content includes extensive tutorials and package development insights for specialized R packages like Rayshader, Rayrender, Rayvertex, Rayimage, and skymodelr. It appeals to readers interested in simulating atmospheric phenomena and rendering them visually. Published in March 2026, it is a must-read for data scientists and enthusiasts keen on pushing the boundaries of 3D visualization and atmospheric simulation using R.
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