Using R

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R is a popular programming language most commonly used for data cleaning, statistics, and data visualization. Both the R program and R-Studio are open source. Below are some books and online resources to get you started. Many of the online vendors listed under “Training Courses” offer free or low-cost classes in R.

Datajournalism.com offers this introduction to R tutorial by German data journalist Marie-Louise Timcke. 

How Do I? This is the companion site to Sharon Machlis’s book Practical R for Mass Communication and Journalism. It is a free, searchable index of common tasks in R, with code instructions and references to chapters in the book. (Free online, book is available for purchase)

Intro to R tutorial from long-time US data journalist Ron Campbell.

Practical R for Mass Communication and Journalism (2018) by US journalist Sharon Machlis. This is a great starter guide for using R for journalism by a long-time champion for using R in newsrooms. Six chapters are online for free here. (Partially free online)

MaryJo Webster’s training materials (2019)  Training materials by a US data journalist and educator that could used by someone wishing to learn on their own (includes exercises).

RDDJ offers a compilation of R reference materials, training and tips. It covers everything from getting started to creating visualizations.

R for Data Science (2016, online version updated 2018) by Garrett Grolemund and Hadley Wickham is a must-have for anyone interested in using the Tidyverse libraries for data analysis or visualization. Wickham is a statistician who is originally from New Zealand, but currently based at Rice University in Texas. Grolemund is a data scientist and master instructor for Rstudio. You can purchase the book, but it also is free online here.

This site is a compilation of training materials from US data journalist Andrew Ba Tran. Tran also created a MOOC training in R. 

This Twitter thread (2019) contains links to a variety of free online resources for coding, statistical analysis, and data visualization in R. It was mainly curated by R-Ladies Global, a world-wide organization promoting gender diversity in the R programming community. 

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