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This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.

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Screenshot of Best Practices for Data Visualisation

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.

Screenshot of Big Book of R at 400 [New milestone!]

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.

Screenshot of Book announcement R 4 Social Network Analysis

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.

Screenshot of Branding and automating your work with R Markdown

Branding and automating your work with R Markdown

This video is about branding and automating work with R Markdown. It discusses how a team of data scientists uses advanced features in RStudio to brand reports and presentations for clients. The speaker highlights lessons learned in areas like version control and automation, including how a few lines of code allowed them to create a specialized report on crime for every county in Utah.

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Break your chain at the cursor line. Run the first bit. See the output. Be free.

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Convert Statistical Objects into Tidy Tibbles


bs4Dash is a Bootstrap 4 version of shinydashboard, a package for creating dashboards with Shiny in R. This article provides information on how to upgrade from shinydashboard to bs4Dash.

Screenshot of bsplus


Adds functionality to the R Markdown + Shiny Bootstrap Framework

Screenshot of Build Advanced Charts in R Online Class | LinkedIn Learning, formerly

Build Advanced Charts in R Online Class | LinkedIn Learning, formerly

This online class on LinkedIn Learning (formerly teaches users how to build advanced charts in R for data visualization. The course covers topics such as lollipop plots, sparklines, dot charts, slope charts, and chord diagrams. It also includes information on creating a theme function, combining multiple plots, and addressing accessibility and annotations. The instructor, Rita Giordano, is a data visualization consultant and LinkedIn Instructor.

Building R packages with devtools and usethis | RStudio - YouTube

This YouTube video provides a tutorial on building R packages using devtools and usethis in RStudio.