Resources

usethis is a workflow package that automates repetitive tasks that arise during project setup and development, both for R packages and non-package projects.

Using the tidyverse with Databases - Part I is a tutorial that provides an introduction to using databases in R with Tidyverse tools. The tutorial covers topics such as motivation, connecting to a database, using DBI and dplyr functions, executing queries with dbplyr, and more.

Create tabs of View() output for each chained pipe

Andrew Heiss explores {dplyr} functions like mutate(), summarize(), group_by(), and ungroup() through handmade animations. Heiss illustrates the complexities of data manipulation workflow steps that are not immediately obvious when performing operations like adding new columns or summarizing data. This tutorial helps conceptualize the impact of these functions on data frames by visualizing their behind-the-scenes mechanics. The animations serve as an effective teaching tool to demystify what happens to data during different stages of the tidyverse's split/apply/combine paradigm, using handcrafted illustrations to make the learning process more intuitive.

vroom is a package in R that provides the fastest delimited reader. It uses lazy loading and multiple threads for improved performance. It supports various parsing features, such as delimiter guessing, custom delimiters, column types specification, and more.

This text demonstrates the usage of arrow geometries in ggplot2 for creating custom arrowheads.

This YouTube video provides an explanation of the meaning of 'deprecated' and discusses the package lifecycle and the process of deprecation.

This article explains the process of tidying Census data using R and tidyverse packages.

This is a webinar titled 'Tabular reporting with the flextable package' by D. Gohel. It is a part of the 'Why R?' webinar series and is available on YouTube.

A YouTube video about wildfires in southern Italy in the last 10 days.

Working with categorical data in R without losing your mind - This talk outlines common problems arising from categorical variable transformations in R, and shows strategies to avoid them, using both base R and the Tidyverse.

This is a tutorial on how to work with strings in R using the 'stringr' package and the 'rebus' package. The tutorial uses the 'Seattle Pet Names' dataset from TidyTuesday and focuses on the names given to cats and dogs. It demonstrates the manipulation of strings by removing punctuation and excess white space from the names.