Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
How to Recreate this NY Times Chart in R
Spencer Schien walks through the process of recreating a professional New York Times chart using R. This type of tutorial is invaluable for learning advanced data visualization techniques by studying and replicating the work of professional data journalists with ggplot.
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How to Split Data into Equal Sized Groups in R: A Comprehensive Guide for Beginners
This guide instructs beginners on splitting data into equal-sized groups in R, essential for cross-validation and balanced datasets. Using the split() function, cut_number() from ggplot2, and group_split() from dplyr, it provides syntax and examples for various data types. Detailed explanations and practical examples aid in mastering data manipulation for model evaluation and analysis.
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How to Turn Messy PDFs into Clean Data Frames with R and Elmer
Albert Rapp demonstrates how to use the {ellmer} package to leverage AI models for extracting data from messy PDF files. If you’ve ever struggled with getting clean data out of PDFs, you know how challenging this task can be. This tutorial shows how AI can streamline this traditionally painful process, making it much easier to transform unstructured PDF content into usable data frames in R.
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How to use a histogram as a legend in {ggplot2}
Andrew Heiss demonstrates how to create choropleth maps in 'ggplot2' with an integrated histogram as a legend to provide additional context for the data. This approach helps to counter visual bias, such as large areas with similar colors obscuring the true distribution of data. Heiss highlights the issue using unemployment rates across U.S. counties, where larger counties can appear to have a disproportionate impact. To address this, he uses the 'ggplot2' and 'patchwork' packages in R, offering a programmatic solution as opposed to the manual process of using D3, Excel, and Figma outlined in Joey Cherdarchuk's original post.
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How to use R to dig for story ideas
The tutorial details the use of R for data journalism, particularly for investigating datasets to uncover story ideas. Highlighted at the Investigative Reporters and Editors conference by Charles Minshew, it emphasizes using R scripts, Tidyverse, and readxl packages to explore a dataset of Boston government employee earnings. By questioning datasets with basic R code, journalists can extract information such as salary attributes, department sizes, and common job titles. It also suggests using descriptive statistics to identify leads for stories, like discovering high earners within the data.
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How to write an R package
R packages are great for organizing your own work and sharing with others. This article provides a step-by-step guide on how to write an R package using tools like devtools, usethis, and roxygen2.
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How to write your own R package and publish it on CRAN
A tutorial on how to write your own R package and publish it on CRAN
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How To: Diamond Plots in R - by Owen Phillips - The F5
Owen Phillips provides a comprehensive tutorial on creating Diamond Plots in R, tailored for both casual and paid subscribers of The F5 newsletter. The tutorial emphasizes the aesthetic appeal and functional utility of Diamond Plots, which are used for visualizing NFL season data. Starting with package loading for data wrangling and plotting, the guide walks users through the process of calculating offensive and defensive EPA per play for NFL teams, data joining, and ensuring plot symmetry to effectively present the data. Owen also mentions renewing paid subscriptions and offers temporary access through coffee purchases, reinforcing the newsletter's interactive community aspect.
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I ❤️ Leaflet: Using Plots as Markers
This blog post is part of the 'I love leaflet' series and provides tips and tricks for working with the leaflet R package. The post showcases how to create a map showing the results of the 2019 UK General election in Oxfordshire using the leaflet package.
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I Made R Text For Me
Brenden Smith shares his experience tackling procrastination in his personal life by using R to automate monthly utility bill calculations and notifications for his roommates. He created an R script connected to a Google Sheets spreadsheet to automatically handle and split the bills, and even set up cron jobs to ensure the process runs without his intervention. His project shows how programming can be applied to simplify and optimize mundane tasks, turning them into efficient, automated systems.
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I Vibe Coded an R Package
Jonathan Carroll documents his journey of creating an R package to visualize similar kanji characters. After starting to learn Japanese with his daughter, he couldn't find an existing solution to visually compare kanji characters for his studies. Utilizing Claude Code, Carroll developed a package in just $20 and one afternoon, complete with full documentation, mocked tests, API coverage, caching, and graph visualizations. The resulting network diagram displays kanji with similarities, aiding memory and recognition. This personal project showcases an efficient approach to language learning tool development in R.
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I wrote this talk with an LLM
In this keynote presentation from useR! 2025, Hadley Wickham explores how AI can augment rather than replace data science workflows. As the Chief Scientist at Posit and creator of the tidyverse, Wickham shares insights on the evolving relationship between humans and AI in data analysis. The talk demonstrates practical ways that large language models can enhance productivity while maintaining the critical thinking and domain expertise that data scientists bring to their work.
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