Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
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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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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Your first R package in 1 hour
This blog post provides a step-by-step guide on how to create an R package in just one hour. It covers the use of devtools and usethis packages to automate folder structure and file creation in package development.
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zipcodeR
zipcodeR is an R package that makes working with ZIP codes in R easier. It provides data on all U.S. ZIP codes using multiple open data sources, making it easier for social science researchers and data scientists to work with ZIP code-level data in data science projects using R.
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