Resources
This carefully curated collection of resources will help you find packages and learning resources to help you on your R journey.
What is Takes to Tidy Census Data
This article explains the process of tidying Census data using R and tidyverse packages.
Go to Resource
Where are the 4+-car households?
Harald Kliems investigates the prevalence of 4+-car households in the 100 most populous US cities using data from the American Community Survey. The blog post highlights the spatial distribution of such households and contrasts the top and bottom ten cities in terms of the percentage of 4+-car ownership. Key R packages used in the analysis include tidyverse, tidycensus, tigris, gt, and tmap. This examination into the facets of American car ownership is accompanied by visualizations such as maps and tables, enabling deeper insights into the data.
Go to Resource
Why R? Webinar 037 - D. Gohel - Tabular reporting with the flextable package - YouTube
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.
Go to Resource
Wildfires in southern Italy🇮🇹 in the last 10 days!
A YouTube video about wildfires in southern Italy in the last 10 days.
Go to Resource
Working with categorical data in R without losing your mind
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.
Go to Resource
Working with Strings in R: Seattle Pet Names
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.
Go to Resource
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.
Go to Resource
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.
Go to Resource
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.
Go to Resource
xaringan
Presentation Ninja with xaringan - a tutorial and package for creating presentations in R using the xaringan package
Go to Resource
xaringanBuilder
renderthis is an R package for generating HTML slideshows using the xaringan package.
Go to Resource
