Resources

How (and Why) I came to Use R for Data Analysis and Evaluation

Alberto Espinoza recounts his journey with R for data analysis and evaluation, marking his 10-year experience since first encountering R during his graduate assistantship. Initially clueless about R, he was tasked with assisting and leading statistics labs using R. Despite early challenges and a steep learning curve, he recognized R's power over software like SPSS or Excel. His continued use of R spanned graduate projects, market research, data preparation for Tableau, and Survey Monkey analysis. Espinoza outlines R's advantages: reproducibility, efficiency, clarity, and an extensive package ecosystem, underlining R's significance in his professional growth.

How to create CUSTOM Callout Boxes in Quarto - YouTube

This video tutorial demonstrates how to create custom callout boxes in Quarto, a document authoring system in R. Quarto allows you to customize your callout boxes to make your documents visually appealing and informative.

How to Make Slides in R Using xaringan

A tutorial on how to make slides in R using xaringan

Introduction to the Field of Statistics (and R Statistical Software)

Iterate parameterised {xaringan} reports

Learn how to iterate parameterised xaringan reports using R. This tutorial demonstrates how to create a parameterised R Markdown template and iterate over parameter values to generate multiple reports with different data.

Iterated fact sheets with R Markdown

This article explains how to use R Markdown to create iterated fact sheets. It provides an overview of R Markdown, discusses the necessary ingredients for creating multiple fact sheets, and provides examples using the bad_drivers dataset.

Mapping water insecurity in R with tidycensus

This content provides a comprehensive guide on utilizing the tidycensus package in R to map water insecurity based on American Community Survey data. It elaborates on setting up the tidycensus environment, exploring Census Bureau variables, and performing data processing. Techniques like data visualization with tigris and sf packages are also covered. The tutorial highlights differences in plumbing facilities and compares population versus plumbing access across Western U.S. counties. With practical code examples, it aids readers in understanding and visualizing the spatial variation of social vulnerability indicators affecting water insecurity.

Meet xaringan: making slides in RMarkdown

This is a tutorial on how to make slides with R Markdown using the xaringan package.

My word template for Quarto | Andrew Wheeler

Andrew Wheeler's blog post discusses creating a custom Word template for use with Quarto, which is beneficial for reports that require formatting suitable for email, printing, or post-generation editing. Starting with the command to generate a default Word template from Quarto, Wheeler explains how to modify styles for various document elements like titles, headings, and code snippets. The template supports markdown tables and features styling for page numbers, headers, and footers. His template also includes personal branding with a hyperlinked logo. The post is a resource for those who prefer Word over HTML or LaTeX for their Quarto-generated documents.

officedown

officedown is an R package that enhances the formatting of Microsoft Word and PowerPoint documents produced by R Markdown. It provides features such as compatibility with the functions of the package officer, the ability to use table styles and list styles defined in a Word template, and support for flextable output. officedown also enhances PowerPoint productions by providing a mechanism for placing results according to a slide template contained in the PowerPoint document. For more information, refer to the package documentation.

Parameterized Reporting with RMarkdown

Parameterized Reporting with RMarkdown is a tutorial that explains how to use parameterized reporting in RMarkdown to generate multiple reports at the same time.

Positron IDE - A new IDE for data science

Dr. Mowinckel reviews Positron IDE, a new data science-oriented IDE that's evolved from Visual Studio Code. The blog explores Positron's compatibility with R and discusses its features, such as integration with Rmd, Hugo websites, and RStudio projects. It analyzes the ease of transitioning from other IDEs, like RStudio, highlighting Positron's customizability, multi-language support, and environment setup. Comparisons are made with other IDEs, underscoring Positron's suitability for polyglot programmers and its potential as a preferred tool. The writer reflects on the learning curve and extensibility, giving insights into making Positron an effective data science environment.