Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
Enhance Quarto Project Workflows and Standards • froggeR
froggeR is an R package designed to enhance Quarto project workflows for R users. It provides a suite of functions that automate project setup tasks, enforce consistent documentation, and allow users to focus on analysis rather than configuration. The package includes features for creating Quarto projects with custom templates, managing YAML headers, applying git protection with a comprehensive .gitignore, styling documents with SCSS templates, and generating structured project documentation. It's particularly useful for R users managing multiple Quarto projects, encouraging collaboration, and standardizing project structures.
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Extract Data from Professional Volleyball Leagues in North America with {rvolleydata}
The R package {rvolleydata} is designed for those interested in analyzing professional volleyball data, providing a simple interface to collect structured data from North American leagues such as League One Volleyball Pro (LOVB), Athletes Unlimited Pro Volleyball (AUPVB), and Major League Volleyball (MLV). The package can be installed from CRAN for stable use or from GitHub for the development version. Comprehensive usage guidelines are available in the package vignette, which helps users employ {rvolleydata} effectively to obtain clean and tidy volleyball league data for their analyses.
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FakeDataR
FakeDataR is an R package designed for locally generating synthetic copies of real datasets, thereby enhancing privacy and enabling secure data sharing without exposing sensitive information. It preserves the original structure, including schema, types, factor levels, numeric ranges, and missingness, while offering heuristics for masking sensitive fields. The package supports direct integration with R for seamless LLM workflows and reproducible examples. It comes with features like bundled exports for easy sharing and database schema compatibility for data synthesis. Use FakeDataR when needing shape-consistent synthetic data while avoiding privacy breaches, not for formal privacy guarantees or statistical benchmarks.
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flair
flair is an R package that provides tools for formatting R code in knitted R Markdown files.
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flextable
The flextable package provides a framework for easily creating tables for reporting and publications in R. It allows for easy formatting and customization of tables, and supports various output formats including HTML, PDF, Word, PowerPoint, and more. The package also provides functions for tabular reporting of statistical models and the creation of complex cross tabulations.
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Flowcharts with ggplot2 • ggflowchart
The {ggflowchart} package for R is a specialized tool designed to create flowcharts using the {ggplot2} framework with simplicity and minimal effort. You can install either the stable CRAN release or the development version from GitHub. Users can generate basic flowcharts by defining start and end points of edges within a data frame, and then invoking the ggflowchart() function. Additional customization is possible through aesthetic mappings such as fill, text color, and future updates may introduce further options. The package also encourages contributions, setting guidelines for pull requests including passing checks and following best practices in development.
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formattable
This package is designed for applying formatting on vectors and data frames to make data presentation easier, richer, more flexible and hopefully convey more information.
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Formatted Spreadsheets to gts • forgts
The forgts package provides a way to convert spreadsheets into gt tables while preserving cell and text formatting from the original file. It supports a variety of format attributes, including font styles, cell fills, and borders, but intentionally ignores header formatting. This tool iterates over the gt defaults to apply necessary styling. Useful in data reporting and visualization, forgts allows easy installation from GitHub and seamless integration with RMarkdown and Quarto, completed by exporting functionalities with gt::gtsave(). It facilitates creating visually consistent tables for analysis and presentation within the R ecosystem.
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Full-Stack Survey Research with SurveyMonkey • svmkR
svmkR is an R package that provides a comprehensive toolkit for managing SurveyMonkey surveys within the R programming environment. It enables users to create, upload, download, and analyze surveys directly from R. Users can calculate margins of error, apply statistical survey weights through raking, and generate SurveyMonkey-style banner presentations for polls. The package is installed from GitHub and serves as a full-stack survey research solution. The source is available on GitHub, and the package was developed by a team of contributors, building on the surveymonkey package by enhancing and refactoring it.
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Full-Stack Survey Research with SurveyMonkey • svmkR
This package provides a suite of tools to work with SurveyMonkey surveys in R.
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