Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
Getting fonts to work in R
Getting fonts to work in R and RStudio can be tricky! This post walks through the different steps we need to follow to give ourselves the best chance of success.
Getting more out of dplyr
Video presentation by Suzan Baert on getting more out of dplyr at SatRday 2018 Amsterdam.
Getting started with theme()
This tutorial provides an introduction to the theme() function in ggplot2 and explains how to modify plot themes and elements using this function. It covers basic plot building, using built-in ggplot2 themes, modifying the legend position, and introduces the element_*() functions.
ggmagnify
ggmagnify, an R package, enhances ggplot visualizations by adding a 'magnifying glass' effect. It allows for the creation of magnified insets to highlight important areas of plots, offering flexible customization options like borders, shadows, and shapes (rectangular, elliptical, convex hull, arbitrary). The package, installable from GitHub or r-universe, provides functions to specify both the target region and the inset location using coordinates. The comprehensive examples cover various use cases, including faceting and maps, illustrating ggmagnify's capability to accentuate data points or regions for increased clarity in ggplot graphics.
ggplot2
ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics.
ggplot2 Theme Elements Demonstration | Henry Wang
This is a demonstration by Henry Wang about customizing theme elements in ggplot2, a powerful package in R for data visualizations. The demonstration provides step-by-step instructions on how to identify and modify theme elements in ggplot2.
ggplot2: elegant graphics for data analysis
This is the online version of the work-in-progress 3rd edition of 'ggplot2: Elegant Graphics for Data Analysis'. The book focuses on explaining the Grammar of Graphics used in ggplot2 and provides details on the underlying theory. It is written by Hadley Wickham, Danielle Navarro, and Thomas Lin Pedersen.
