Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/data-datum/learning_R

List of resources for learning R
https://github.com/data-datum/learning_R

books data-manipulation data-visualization datatable dplyr functions ggplot2 purrr r r-programming r-spatial reproducible-research rmarkdown rstudio shiny shiny-apps strings strings-manipulation tidyr webinars

Last synced: 9 days ago
JSON representation

List of resources for learning R

Awesome Lists containing this project

README 

        
# 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](https://rstudio.com/resources/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](https://bit.ly/32Hr0MN) [2/2](https://bit.ly/3jvlxP8) 

* 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