Learning R - Resources

Last Update : 25-July/2020

Cursos

• Listas de cursos https://www.learnr4free.com/en/index.html

R Programming

• CRAN Contributed Documentation https://cran.r-project.org/
• What they forgot to teach you about R Jenny Bryan https://rstats.wtf/

Books

• R Programming for Data Science Roger D. Peng 2016-12-22 http://bit.ly/2AbQRhd
• R for Data Science Garrett Grolemund & Hadley Wickham http://bit.ly/2AaFWEw
• Efficient R programming Colin Gillespie & Robin Lovelace http://bit.ly/2AaGKcw
• Hands-On Programming with R Garrett Grolemund http://bit.ly/2QYJRJZ
• Advanced R Hadley Wickham http://bit.ly/2AapVhT
• Wikibook R Programming https://en.wikibooks.org/wiki/R_Programming
• Learning statistics with R: A tutorial for psychology students and other beginners Danielle Navarro http://bit.ly/2DaYoig
• The Tidynomicon A Brief Introduction to R for Python Programmers Greg Wilson http://bit.ly/2IEh4t8
• Rad R for academics http://bit.ly/2UufM8b

Español

• El arte de programar en R Julio Sergio Santana & Efraín Mateos Farfán http://bit.ly/2N2Y1Y8
• R para Principiantes Juan Bosco Mendoza Vega http://bit.ly/2Zg0I3M

Rstudio webinars

Data Manipulation

tidyr and dplyr Packages

• Tidy evaluation is one of the major feature of the latest versions of dplyr and tidyr [Video] http://bit.ly/2AbXJLs
• Tidy eval: Programming with dplyr, tidyr, and ggplot2 Hadley Wickham [Video] http://bit.ly/2QR07N5
• Data wrangling with R and RStudio [Video] http://bit.ly/2AaocZX slides: http://bit.ly/2QSr7vS
• Wrangling data in the Tidyverse [Video] (useR! 2018 Conf) [Part 1] http://bit.ly/2SEHDBc [Part 2] http://bit.ly/2SK9EHt
• dplyr tutorials Suzan Baert http://bit.ly/2AbSHi2
• Getting more out of dplyr SatRday Amsterdam 2018 slides Suzan Baert http://bit.ly/2QXf28I
• dplyr 10 tips and tricks Suzan Baert (RoCur WeAreRLadies) http://bit.ly/2AaWb4k
• STAT 545 Course https://stat545.com/tidy-data.html
• Let the Data Flow: Pipelines in R with dplyr and magrittr http://bit.ly/2AaVDvz
• Data Processing with dplyr & tidyr (Rpubs) http://bit.ly/2Aah7Zd
• Introducción a tidyr: Datos ordenados en R (Rpubs) [español] http://bit.ly/2AaWV9T
• dplyr Rstudio cheatsheet http://bit.ly/2IEwRcM
• tidylog Tidylog provides feedback about basic dplyr operations http://bit.ly/2MJJUvq

Joins

• Vignettes for Joins - http://bit.ly/2Zhdsaj
• Join Functions Jenny Bryan http://bit.ly/2AbUZ0C
• Joining Data in R with dplyr (Rpubs) http://bit.ly/2ZjTwnm
• Gif for differrent types of Joins http://bit.ly/2ZixS2L

data.table Package

• Intro to data.table Package http://bit.ly/2Aa6Yf3
• Wrangling with data.table http://bit.ly/2QQfLIy
• R studio cheatsheet (data.table) http://bit.ly/2IEwRcM
• Data crunching with data.table (Rpubs) http://bit.ly/2AbNCGz
• Best packages for data manipulation in R (dplyr & data.table) http://bit.ly/2AenZox
• A data.table and dplyr tour http://bit.ly/2IDlIYd

String manipulation and stringr package

• String Manipulation in R with stringr (Rpubs) http://bit.ly/2SzLyiR
• Regular Expression in R Gloria Li and Jenny Bryan http://bit.ly/2SD74Dg

Data Visualization

ggplot2 Package

• R Graph Gallery http://bit.ly/2UmD3ZN
• DataCarpentry resources: http://bit.ly/2Aaiwz2
• Visualización estática e interactiva con ggplot2 y plotly [español] http://bit.ly/2xI2dqH
• Data Visualization in R http://bit.ly/2AaKzy9
• R graphics with ggplot2 workshop notes http://bit.ly/2AavgG4
• Data visualization using ggplot2 http://bit.ly/2Aal7ZT
• ggplot2 package by Hadley Wickham (Rpubs) http://bit.ly/2AaaeqN
• 7 Visualizations You Should Learn in R http://bit.ly/2NwhCBf
• How to make fancy graphs with ggplot2 (Medium post) http://bit.ly/2PTV51W
• Designing ggplots making clear figures that communicate bit.ly/ggplots
• Drawing anything with ggplot2 https://github.com/thomasp85/ggplot2_workshop

Books

• Data Visualization A practical introduction Kieran Healy http://bit.ly/2AaF9n2
• Data Visualization with R. Rob Kabacoff http://bit.ly/2A9pLaj
• ggplot2: Elegant Graphics for Data Analysis Hadley Wickham https://ggplot2-book.org/

Visualization Courses

• CS 448B Visualization. Stanford CS course on data visualization techniques (Fall 2018) http://bit.ly/2IDzfyW

Modeling

Broom

• Broom vignette http://bit.ly/2M42z5y
• Convenient analysis with broom - Alex Hayes - http://bit.ly/2ZdV7e4
• broom: a package for tidying statistical models into data frames http://bit.ly/2Wi0FBZ

Tidymodels

• A gentle introduction to tidymodels http://bit.ly/2G176QI
• Tutorial on tidymodels for Machine Learning https://bit.ly/37iyQwC

H2o.ai

• Auto Machine Learning with H2o.ai #LatinR2019 Erin Ledell http://bit.ly/35nDEQ7
• Youtube Channel http://bit.ly/2ogLiep

Data Modeling

• Hands-on Machine Learning with R http://bit.ly/2IBxTEM
• Feature Engineering and Selection: A Practical Approach for Predictive Models http://bit.ly/2IEf2Jw

Shiny Web Application

• Rstudio Resources http://bit.ly/2QOovPq
• Introduction to Shiny [video] http://bit.ly/2Aat9BQ
• Testing Shiny applications with Shinytest - Shiny developers now have tools for automated testing of complete applications [video] http://bit.ly/2AauJUq
• Understanding PCA using Shiny and Stack Overflow data Julia Silge [video] http://bit.ly/2QLmG5K
• Developing and deploying large scale Shiny applications Herman Sontrop [video] http://bit.ly/2QT8rMx
• Understanding Shiny Modules [video] http://bit.ly/2AaTuzS
• Interactive Graphics with Shiny [video] http://bit.ly/2Aau45h
• Interactive web-based data visualization with R, plotly, and shiny https://plotly-r.com/
• Javascript for Shiny Users https://github.com/rstudio-conf-2020/js-for-shiny
• Interactive web applications with Shiny - meetup material https://bit.ly/2B0Eacq
• Production-grade Shiny Apps with golem - rstudio::conf2019 talk https://bit.ly/30G685J
• Building Big Shiny Apps — A Workflow – 1/2 2/2
• Building a Shiny App as a Package https://bit.ly/30EgTpb
• Testing shiny Apss https://speakerdeck.com/colinfay/erum-2020-testing-shiny-why-what-and-how
• A gRadual introduction to Shiny. https://laderast.github.io/gradual_shiny/index.html

Books

• Mastering Shiny Hadley Wickham http://bit.ly/2z89f9l
• Interactive web-based data visualization with R, plotly, and shiny http://bit.ly/2IBuR3m
• Engineering Production-Grade Shiny Apps https://engineering-shiny.org/

R Markdown

• R Markdown Gallery http://bit.ly/2QPHxoI
• R Markdown articles http://bit.ly/2A9LfEe
• R Markdown Rstudio lessons http://bit.ly/2A9Ln6G
• R Markdown and knitr make it easy to intermingle code and text to generate compelling reports and presentations that are never out of date. [video] http://bit.ly/2A9MH9E
• Beyond static reports with R Markdown [video] http://bit.ly/2Ac2jtd
• Introducing Notebooks with R Markdown [video] http://bit.ly/2AaYPXH
• RMarkdown Tips and Tricks - An Introduction to RMarkdown http://bit.ly/2P1NjaA
• RMarkdwon Workshop http://bit.ly/2P3kYkt
• Reproducible Reporting http://bit.ly/2A9MH9E
• 15 Tips on Making Better Use of R Markdown Yihui Xie https://slides.yihui.org/2019-dahshu-rmarkdown#1

Books

• R Markdown: The Definitive Guide Yihui Xie, J. J. Allaire, Garrett Grolemund http://bit.ly/2QNTISX
• Introduction to RMarkdown http://bit.ly/2P59GMo
• RMarkdown for Scientists http://bit.ly/2T2Uca8

Bookdown & Blogdown

• Introducing bookdown [video] http://bit.ly/2AbArpc
• Introducing blogdown, a new R package to make blogs and websites with R Markdown [video] http://bit.ly/2AamVSt
• A week of blogdown for RStudio's summer 2019 interns Alison Hill https://summer-of-blogdown.netlify.com/

Books

• bookdown: Authoring Books and Technical Documents with R Markdown Yihui Xie http://bit.ly/2QLTZWq
• blogdown: Creating Websites with R Markdown Yihui Xie, Amber Thomas, Alison Presmanes Hill http://bit.ly/2QPjCpm

R code Best Practices

• R Best Practices: R you writing the R way! http://bit.ly/2P2TkE3
• R Code – Best practices http://bit.ly/2P13Mfq
• Best Practices for Writing R Code [The Carpentries] http://bit.ly/2P3485h

R Package Development

• Write your first R Package (STAT 545 Course) Jenny Bryan http://bit.ly/2OjiBs2
• You can make a package in 20 minutes Jim Hester [Video] http://bit.ly/2QR3K5D
• What makes a great R package? Joseph Rickert [Video] http://bit.ly/2QLS9Vw
• How to develop good R packages (for open science) Maëlle Salmon http://bit.ly/2QTXgmP
• Writing an R package from scratch (Not so Standard deviations blogpost) Hilary Parker http://bit.ly/2QOlONO
• R Package Development Pictorial http://bit.ly/2QP5tbW
• Developing Packages with RStudio http://bit.ly/2QOav8v
• Writing an R package from scratch http://bit.ly/2QTWZAj
• Reproducible Research: Writing an R Package. http://bit.ly/2AarXi0
• Advanced R Course (Chapter 6: R Packages) Florian Privé http://bit.ly/2QT53kN
• rOpenSci Packages: Development, Maintenance, and Peer Review http://bit.ly/2P3k7QN
• R Package Development Tutorial #LatinR2019 Hadley Wickham https://github.com/hadley/pkg-dev
• Make an R Package - the easy way - Matt Dray http://bit.ly/2PCEhQh
• Usethis package development workflow http://bit.ly/2pzuoIg

Books

• R Packages Hadley Wickham http://r-pkgs.had.co.nz/

purrr Package - Functional Programming

• Happy R Users Purrr – Tutorial Charlotte Wickham [Video] http://bit.ly/2AakkIv
• Purrr tutorial - Charlotte Wickham http://bit.ly/2AaDCNO
• Purrr tutorial - Jenny Bryan http://bit.ly/2QSVoLC
• Package CRAN Documentation http://bit.ly/2zbuSFz
• Purrr as part of the tidyverse http://bit.ly/2z6gFcO
• The joy of Functional Programming Hadley Wickham http://bit.ly/2IC2qCk
• Purrr - tips and tricks https://bit.ly/2AWODF6
• Two examples of iteration with purrr - Class for the R-Studio certification https://bit.ly/3dzWKoK

How to write functions in R.

• Jenny Bryan's STAT 545 Course http://bit.ly/2QGCtnc
• Jenny Bryan's Talk in RLadies Bs As Writing R functions for fun and profit http://bit.ly/2xMqhsu

R-Spatial

• Spatial Data Analysis and Modeling with R http://rspatial.org/
• Spatial modelling using ‘raster’ package (useR! Conf 2018) - [Part 1] http://bit.ly/2SJ9PTB [Part 2] http://bit.ly/2SIJgOr
• Spatial Data Science Edzer Pebesma, Roger Bivand https://keen-swartz-3146c4.netlify.com/

Reproducible Research

• Best Practices for Scientific Computing Greg Wilson … Paul Wilson | PLoS Biology 2014 http://bit.ly/2SHZqrs
• Good enough practices in scientific computing Greg Wilson ... Tracy Teal| PlOS Computational Biology 2017 http://bit.ly/2zhSSXW
• Reproducibility in Science - ROpenSci - http://bit.ly/2P18DgA
• The drake R Package User Manual http://bit.ly/2P4n9nK
• rrtools: Tools for Writing Reproducible Research in R - http://bit.ly/2zhMekA
• Use of an R package to facilitate reproducible research - http://bit.ly/2zhP8G0

Metaprogramming - TidyEval

• Tidy evaluation Lionel Henry & Hadley Wickham http://bit.ly/2P5oRFy
• Lazy evaluation Jenny Bryan [video Rstudio conf 2019] http://bit.ly/2P82pvn [material] http://bit.ly/2PgphbY

Tutorials from different topics

• The coding club http://bit.ly/2SJzTy7
• The R class R programming for biologists http://bit.ly/2SD71HA
• R for NFL analysis http://bit.ly/2ICmqoo

R Courses with Tidyverse

• Tidy Data Science Workshop (Jun-2019) http://bit.ly/2ID1mhV
• RaukR-2019 http://rstd.io/raukr
• UC Business Analytics R Programming Guide http://uc-r.github.io/
• STAT 545A/547M: Exploratory Data Analysis - Jenny Bryan - http://bit.ly/31fsz0t
• Data Science in a Box - Mine Çetinkaya-Rundel - http://bit.ly/2PcydPU
• R for learning and teaching R List of resources http://bit.ly/2PaIqwc
• BIMS8382 Spring 2018 https://bims8382.github.io/2018/
• Course materials for Applied Machine Learning course in 2019 in London https://github.com/topepo/aml-london-2019