Resources

Automate subset plots with ggplot2 and purrr

Cedric Scherer's blog post, 'Efficiency and Consistency: Automate Subset Graphics with ggplot2 and purrr,' guides readers through the process of automating the creation of subset graphics in R using the ggplot2 and purrr packages. It explains how to eliminate redundant work when generating explorative or explanatory charts for various data subsets by iterating over a vector of groups with a custom function. The post provides a practical tutorial on improving efficiency and consistency when visualizing relationships for different numeric variables, with a focus on polished charts and including examples and shortcuts for data exploration.

Baby got backreferences

This content is a written confession of a data practitioner about their struggle with and reluctant embrace of regular expressions. The author describes emotions and thoughts they undergo when considering the use of regular expressions for text manipulation tasks. The narrative is coupled with humorous references to fantasy elements such as Mordor and Sauron from 'The Lord of the Rings'. Despite self-admittedly not being an expert, the author offers a guide for regular expressions in R, beginning with loading the stringr package and reading song lyrics which serve as examples for pattern matching exercises.

BBC Visual and Data Journalism cookbook for R graphics

The BBC Visual and Data Journalism team has crafted an R package, complemented by a cookbook, designed to assist in generating graphics in the BBC's signature style using the ggplot2 library in R. This resource streamlines the creation of professional-looking visuals and eases the learning curve for newcomers to R. The cookbook outlines the procedures for installation and usage of the necessary R packages, including 'bbplot', which is available directly from GitHub. It includes detailed guidance on customizing plots with BBC style elements, such as text size, font, and axis formatting, through practical examples with gapminder data.

bbplot

R package that helps create and export ggplot2 charts in the style used by the BBC News data team

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Best Practices for Data Visualisation

This content outlines best practices for creating effective and accessible data visualisations. It provides insights, advice, and code examples to enhance the readability and impact of data presentations. Emphasizing both the art and science of data visualisation, it guides readers through core principles and elements of designing charts and tables. The guide also addresses the need for authorial choices in storytelling through data and the importance of customizing default settings to convey information effectively. Aimed at Royal Statistical Society contributors, the advice is broadly applicable and includes resources for chart selection and accessibility.

Big Book of R at 400 [New milestone!]

Oscar Baruffa's 'Big Book of R' has reached a new milestone with over 400 entries of mostly free R books, witnessing the growth of an invaluable resource for the R community. Acknowledging contributors and the support of visitors, Baruffa emphasizes the quality and impact of the collection. The announcement highlights the costs associated with hosting the 'Big Book of R' and encourages contributions. New additions cover topics like big data analytics, hierarchical compartmental reserving models, R package design, epidemiology, causal data science, and psychometrics, showcasing the diversity and depth of the resources available.

biscale

Bivariate choropleths are go!

This post explores bivariate choropleth maps, which blend two semi-transparent color schemes to represent two variables on a map. It delves into the practicalities of creating such maps with modern tools like R libraries, demonstrating the ease with which these visualizations can now be created. The post also touches on the modifiable areal unit problem (MAUP) and provides background on the development of bivariate choropleths in cartography. It offers a tutorial on using tmap to create these maps, referencing the work of Joshua Stevens and Cindy Brewer in the field.

Bluesky conversation analysis with local and frontier LLMs with R/Tidyverse

This content details the author's exploration of bluesky conversation analysis using R and the Tidyverse suite, specifically focusing on local and frontier large language models (LLMs). The author leverages R packages atrrr, ellmer in the tidyverse, mlverse/mall, and interfaces with models such as Claude & Ollama. Processes include summarizing posts, performing sentiment analysis, and posting summaries to GitHub via the gistr R package. Techniques include data retrieval, text analysis, and summarization, showcasing how open models can provide insights into community discussions on Bluesky, particularly within the R community's use of the #Rstats hashtag.

Book announcement R 4 Social Network Analysis

The blog post 'R 4 Social Network Analysis' announces an in-progress book aimed at introducing social network analysis (SNA) in R to practitioners. Authored by schochastics and Termeh Shafie, both of whom have extensive experience in SNA and R package development, the book will cover key SNA topics and demonstrate how to manage network analytical tasks in R. It addresses the scarcity and dispersal of current SNA learning materials and seeks to provide a central, up-to-date source. The book's practical focus is on applying R tools rather than delving into theory, making it suitable for those ready to apply SNA techniques. It is openly written on GitHub using quarto, inviting community feedback through issues.

Brand your docs, apps, and ggplots using LLMs

The {{brandthis}} R package addresses the challenge of branding statistical analytics in the realm of data science by simplifying the creation of branded documents and visualizations. Developed by Umar Dani, it leverages the capabilities of large language models (LLMs) to efficiently produce branded content. The package allows users to easily specify fonts, color palettes, and custom branding themes without in-depth design knowledge. It integrates with Google Fonts and Google Gemini API, providing a streamlined process to align data visualizations with personal or company branding guidelines, using an interactive interface for crafting brand files and enhancing ggplot2 visualizations.