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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 ViewPipeSteps

ViewPipeSteps

Create tabs of View() output for each chained pipe

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vroom

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.

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W. Joel Schneider

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

What does deprecated mean? Package lifecycle and the process of deprecation. - YouTube

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

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What is Takes to Tidy Census Data

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

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.

Wildfires in southern Italy🇮🇹 in the last 10 days!

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

Screenshot of Working with categorical data in R without losing your mind

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.

Screenshot of Working with Strings in R: Seattle Pet Names

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.

Screenshot of Wrangling categorical data in R

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.

Screenshot of Writing an R package from scratch

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.

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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.