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Resources

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

Screenshot of Wrangling categorical data in R

Wrangling categorical data in R

This tutorial is a comprehensive guide on how to wrangle categorical data in R. It covers various techniques and functions to manipulate and analyze categorical data, including recoding, reordering, and summarizing categorical variables. The tutorial also provides step-by-step examples and case studies to illustrate the concepts.

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Screenshot of Writing an R package from scratch

Writing an R package from scratch

This tutorial provides a step-by-step guide on how to create an R package from scratch using the usethis package. It covers topics such as package setup, adding functions, and function documentation.

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Writing beautiful code

This content is a comprehensive guide on writing aesthetically pleasing and maintainable code, with a focus on R programming. The author, Ma"elle Salmon, explains the importance of beautiful code for readability and collaboration. The guide includes practical tips and tricks, and emphasizes adherence to coding styles, proper spacing, avoiding overly long lines, and creating descriptive functions. Additionally, the author discusses reducing unnecessary comments and documenting functions effectively. The guide also covers using tools like {styler} for automatic formatting and encourages learning from others' code to extend one's R vocabulary.

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xaringan

Presentation Ninja with xaringan - a tutorial and package for creating presentations in R using the xaringan package

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xaringanBuilder

renderthis is an R package for generating HTML slideshows using the xaringan package.

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xaringancolor

Uniform Colors in Xaringan Presentations

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xaringanExtra

xaringanExtra is a package in R that provides additional functionality and features for creating presentations using the xaringan package.

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xaringanthemer

Custom xaringan CSS Themes for styling xaringan slides in RMarkdown with xaringanthemer

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xlcharts

xlcharts is an R package that serves as an interface to the OpenPyXL Python library, enabling the creation of native Excel charts within R. Aimed at overcoming the limitations of existing R packages in terms of Excel chart creation and customization, xlcharts allows users to generate Excel charts and perform advanced Excel file manipulations. Users can install xlcharts and its dependencies (Miniconda and OpenPyXL), access and edit workbook cells, and create various types of charts such as bar, bubble, and pie. It supports styles, conditional formatting, worksheet operations, pivot tables, comments, formulae, and workbook protection.

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yonder

yonder is a reactive web framework built on shiny. It features new reactive inputs and Bootstrap components on the UI side, and tools for alerts, modals, and more on the server side.

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You ‘tidyr::complete()’ me

Luis D. Verde Arregoitia's article demonstrates using the 'complete()' function from the tidyr package to expand a data frame's sequences based on start and end values within columns. The example showcases how to pivot data and use 'complete()' and 'full_seq()' functions for filling in sequences of days for different categories, while repeating longitude values accordingly. This technique is useful for managing tabular data in wide format, facilitating transformations into a long format ready for analysis. The article is instructional for those working with R in ecology, conservation, and biogeography, focusing on data wrangling challenges.

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Screenshot of You're Already Ready: Zen and the Art of R Package Development

You're Already Ready: Zen and the Art of R Package Development

R packages make it easier to write robust, reproducible code, and modern tools in R development like usethis make it easy to work with packages. In this video, Malcolm Barrett discusses why your project is already an R package, why you’re already an R package developer, and why you already have the skills to walk the path of development.

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