Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
A First Look at Positron
Julia Silge provides a comprehensive overview of Positron, the next-generation data science IDE built by the creators of RStudio. Presented at the recent useR! conference, this video gives you everything you need to know about Positron’s features and capabilities. If you’re considering making the switch from RStudio to Positron, this is an excellent resource to help inform your decision.
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A personal history of the tidyverse
This content presents a personal history of the tidyverse, a collection of R packages for data science, as seen through the eyes of the creator, Hadley Wickham. The article traces the evolution of the tidyverse from its early beginnings to its current status as a major tool in the R ecosystem. It reflects on the growth from individual projects to a collaborative community effort, supported by both Posit (formerly RStudio) and users worldwide, spanning almost 20 years and over 500 releases. The tidyverse's defining features, its significance, and the future vision are all discussed, emphasizing its open-source philosophy and contribution to data analysis and data warehousing.
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A quick tour of Positron
The content is an introduction to Positron, a free data science IDE that supports both R and Python. Built as a fork of VS Code, Positron offers features such as a built-in data explorer, AI assistance, and interpreter management, facilitating a streamlined workflow for data professionals. The blog outlines key components like the Activity Bar, Editor, and Panels for navigation. It also provides a guide to managing interpreters, using the Data Explorer, database connections, Positron Assistant for AI-powered code generation, and accessing documentation. The post serves as an invitation to download and explore Positron.
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Creating messy datasets for teaching purposes with {truffle}
The {truffle} R package, designed by Ian Hussey for educational purposes, helps users learn data processing by generating 'messy' datasets. It provides tools to create both 'truffles'—deliberate known effects to be uncovered—and 'dirt'—intentional complications that resemble common data issues. The package allows customization of demographics and Likert-scale items, and embeds effects such as group differences, correlations, and specific reliability coefficients. However, {truffle} has limitations in flexibility, error handling, and study design scope. It is compared with other R packages like {lavaan}, {latent2likert}, and {wakefield}, highlighting its unique focus on creating challenging datasets for data-wrangling education.
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Dependency-light hex stickers with {gex}
Rostrum.blog introduced a new R package, {gex}, formerly known as {hexbase}, for creating hexagon stickers. It aims to be lightweight by including only 'gridverse' packages. 'Gex' is a play on 'grid' and 'hex'. The post explains how {gex} differs from {hexbase} in creating hex stickers with R's grid system, using functions like add_border() that applies a cut-out effect for borders. Users can add text and images to hexagon shapes with a sequence of commands. The example demonstrates hex creation for the {gex} logo with image manipulation using {magick} and showcases loops for multiple images and text effects.
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Exploring Complex Survey Data Analysis Using R
This content outlines a comprehensive guide on analyzing complex survey data using R. It begins with an introduction to survey analysis in R, prerequisites, and the datasets used, followed by detailed sections on survey design, data collection, and post-survey processing including data cleaning, weighting, and documentation. The book further delves into practical aspects like getting started with R packages, performing descriptive analyses and statistical tests, building models, and effective communication of results. Additionally, it emphasizes reproducible research with project-based workflows and version control, catering to both beginners and advanced users.
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Porting my favorite RStudio color theme to Positron
This post details the process of adapting the popular Tomorrow Night Bright RStudio theme for use in Positron. The authors discuss their personal journey with the theme, its origins, and how it was ported to other editors. By navigating through RStudio's source code, they found the color palette for rainbow parentheses, which was uniquely developed in R. The post also explores the customizability offered by Positron's Open VSX Registry extension mechanism. The authors introduce 'Tomorrow Night Bright (R Classic),' a new theme extension available for Positron and VS Code, sharing screenshots and experiences from the porting process.
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Posit Generative AI Solutions
Posit GenAI Solutions offers versatile packages for integrating LLMs into R and Python. It features ellmer and chatlas for LLM communication, shinychat for chatbots in Shiny, and ragnar for Retrieval-Augmented Generation. Additional tools include querychat for natural language data querying, chores for automating coding tasks, and gander for in-line chat integration in data science workflows. The mall package efficiently applies LLM predictions to data frames, while lang translates documentation. Positron Assistant and GitHub Copilot enhance IDEs with AI. Packages like otel provide observability via OpenTelemetry, and mcptools implements the MCP for R sessions.
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Reproducible Data Science in R: Say the quiet part out loud with assertion tests
This blog post explores the role of assertion tests in reproducible data science when using R. The author, Anthony Martinez, walks through a tutorial on improving the robustness of R functions with assertions, beginning with basic checks and evolving to more expressive error messages. The post, intended for novice and intermediate R users, is part of a series on functional programming and reproducibility using the targets package. It highlights the importance of failing early with clear messages in multi-person projects and offers examples using the geoconnex.us database to retrieve Hydrologic Unit boundary polygons.
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resouRces
This content encompasses a comprehensive list of R-related educational materials, packages, tutorials, and datasets with projected dates ranging up to the year 2025. It includes various titles that focus on learning R programming, data analysis, data visualization, geospatial mapping, and statistical methods. Significant emphasis is placed on resources for learning R, such as introductions to R, books, courses, and video tutorials. Additionally, specific packages for data wrangling, statistical modeling, and visualization are mentioned, indicating the evolution and specialization of R's ecosystem to cater to diverse data science needs.
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RStudio to Positron
This overview is designed for current RStudio users considering a switch to Positron, a new IDE. It explains similarities between RStudio and Positron and highlights changes users can expect. By leveraging Code OSS, the same foundation as Visual Studio Code, Positron offers features tailored for data science. This guide, alongside additional resources, aims to ease the transition with a focus on keybindings, feature comparisons, and using Positron's user interface effectively. Tips include using the migration guide and exploring the Command Palette, a central element differing from RStudio's traditional layout.
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rtweet
rtweet is an R package that allows for interacting with Twitter's APIs to collect and analyze Twitter data.
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