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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 {arcgeocoder} package for geocoding

{arcgeocoder} package for geocoding

arcgeocoder is an R package that serves as a lightweight interface for geocoding and reverse geocoding using the ArcGIS REST API Geocoding Service. It allows R users to easily convert addresses to geographic coordinates and vice versa without needing an API key. The package is designed to work with base R functions, avoiding dependencies like curl, making it accessible in environments where curl isn't available. arcgeocoder is advantageous when quick and simple access to geocoding services is needed, and it includes functions like arc_geo() for geocoding and arc_reverse_geo() for reverse geocoding.

Screenshot of {ggborderline}

{ggborderline}

The ggborderline package enhances ggplot2 line plots with geoms that add an outlined effect, improving clarity for plots with overlapping lines. It's ideal for visualizing 'worm' style data. Users can replace ggplot2 line geoms with border equivalents to achieve a white outline where lines intersect, with settings for borderwidth and bordercolour these subtle enhancements can be adjusted. Additionally, the package makes the borders visible in the plot's legend. Installation instructions include CRAN and GitHub options, inspired by a need to avoid indistinct lines in complex visualizations, offering an aesthetic alternative to ggplot2's capabilities.

Screenshot of {Ra11y} package: Collection of accessibility functions for R

{Ra11y} package: Collection of accessibility functions for R

Ra11y is a public GitHub repository created by user nicucalcea, which hosts a collection of accessibility functions designed for R programming. The project aims to enhance accessibility within R and contains resources for developers to utilize these functions in their work. With 18 stars and 1 fork, the repository appears to be modestly popular within the community. The repository is fully coded in R and provides documentation to help users understand and implement the functions for their accessibility needs.

Screenshot of 10 years of rio

10 years of rio

This is a blog post titled '10 years of rio' by Chung-hong Chan. It discusses the history and development of the R language package 'rio', which is similar to stringr. The author talks about the motivation behind creating the package and the design principles used. The package provides functions for importing and exporting data in various formats, with a consistent API. The post also mentions the compatibility of the package with older versions of R.

Screenshot of 10+ Guidelines for Better Tables in R

10+ Guidelines for Better Tables in R

The MockUp - 10+ Guidelines for Better Tables in R

Screenshot of 30 Day Map Challenge

30 Day Map Challenge

Building a Map a Day with (Mostly) R is a 30-day challenge where each day, a map is created using R. The challenge covers various map types and techniques using different data sources. The tutorial provides step-by-step instructions on how to create each map and includes code examples. The challenge is suitable for those who are familiar with R and want to enhance their mapping skills.

3D city building maps with R - YouTube

This YouTube video is about creating 3D city building maps using R.

Screenshot of A beginner’s guide to building a simple website with Quarto & Netlify

A beginner’s guide to building a simple website with Quarto & Netlify

This content is a tutorial for beginners on creating a simple website using Quarto and deploying it with Netlify. It guides users through the installation of RStudio and Quarto, the process of creating a Quarto website, and understanding the necessary files. The guide highlights the benefits of using Quarto and Netlify over other website platforms and provides a stress-free approach for those without web development experience. It includes step-by-step instructions to ensure even complete novices can achieve a professional online presence quickly and easily.

Screenshot of A ggplot2 Tutorial for Beautiful Plotting in R

A ggplot2 Tutorial for Beautiful Plotting in R

A ggplot2 tutorial for beautiful plotting in R by Cédric Scherer

Screenshot of a gRadual intRoduction to Shiny

a gRadual intRoduction to Shiny

A gradual introduction to Shiny is a two-hour workshop that introduces the basic concepts of Shiny, a web application framework for R. The workshop covers the basic architecture of Shiny apps, how the server and UI communicate, adding ggplot2 code to an app, creating reactive datasets, and adding tooltips with plotly. The workshop is designed for intermediate R users and students familiar with ggplot2, dplyr, and functions.

Screenshot of A Scientist's Guide to R: Step 1. Getting Data into R

A Scientist's Guide to R: Step 1. Getting Data into R

A tutorial on getting data into R, covering various file formats like .csv, .txt, .xlsx, etc.

Screenshot of A Scientist's Guide to R: Step 2.1. Data Transformation - Part 1

A Scientist's Guide to R: Step 2.1. Data Transformation - Part 1

This post is part of the Scientist's Guide to R series and focuses on data transformation techniques for wrangling, tidying, and cleaning data. It introduces the core functions of the dplyr package, as well as other relevant functions in base R. The post covers topics such as selecting columns, filtering rows, modifying columns, obtaining descriptive summaries of data, assigning grouping structures, and arranging data frames. The post also mentions the data.table package for working with large datasets. The examples in the post demonstrate how to use the select() function from the dplyr package to subset columns from a data frame.