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Peng_ 2016-12-22 http://bit.ly/2AbQRhd\n* R for Data Science _Garrett Grolemund \u0026 Hadley Wickham_ http://bit.ly/2AaFWEw\n* Efficient R programming _Colin Gillespie \u0026 Robin Lovelace_ http://bit.ly/2AaGKcw\n* Hands-On Programming with R _Garrett Grolemund_ http://bit.ly/2QYJRJZ\n* Advanced R _Hadley Wickham_ http://bit.ly/2AapVhT\n* Wikibook R Programming https://en.wikibooks.org/wiki/R_Programming\n* Learning statistics with R: A tutorial for psychology students and other beginners _Danielle Navarro_ http://bit.ly/2DaYoig\n* The Tidynomicon A Brief Introduction to R for Python Programmers _Greg Wilson_ http://bit.ly/2IEh4t8\n* Rad _R for academics_ http://bit.ly/2UufM8b\n\n#### _Español_\n* El arte de programar en R _Julio Sergio Santana \u0026 Efraín Mateos Farfán_   http://bit.ly/2N2Y1Y8\n* R para Principiantes _Juan Bosco Mendoza Vega_ http://bit.ly/2Zg0I3M\n\n## Rstudio [webinars](https://rstudio.com/resources/webinars/)\n\n## Data Manipulation \n### tidyr and dplyr Packages\n* Tidy evaluation is one of the major feature of the latest versions of dplyr and tidyr [Video] http://bit.ly/2AbXJLs\n* Tidy eval: Programming with dplyr, tidyr, and ggplot2 _Hadley Wickham_ [Video] http://bit.ly/2QR07N5\n* Data wrangling with R and RStudio [Video] http://bit.ly/2AaocZX slides: http://bit.ly/2QSr7vS\n* Wrangling data in the Tidyverse [Video] (useR! 2018 Conf) [Part 1] http://bit.ly/2SEHDBc [Part 2] http://bit.ly/2SK9EHt\n* dplyr tutorials _Suzan Baert_ http://bit.ly/2AbSHi2\n* Getting more out of dplyr SatRday Amsterdam 2018 slides _Suzan Baert_ http://bit.ly/2QXf28I\n* dplyr 10 tips and tricks _Suzan Baert (RoCur WeAreRLadies)_ http://bit.ly/2AaWb4k\n* STAT 545 Course https://stat545.com/tidy-data.html\n* Let the Data Flow: Pipelines in R with dplyr and magrittr http://bit.ly/2AaVDvz\n* Data Processing with dplyr \u0026 tidyr (Rpubs) http://bit.ly/2Aah7Zd\n* Introducción a tidyr: Datos ordenados en R (Rpubs) [español] http://bit.ly/2AaWV9T\n* dplyr Rstudio cheatsheet http://bit.ly/2IEwRcM\n* tidylog _Tidylog provides feedback about basic dplyr operations_ http://bit.ly/2MJJUvq\n\n#### Joins\n* Vignettes for Joins - http://bit.ly/2Zhdsaj\n* Join Functions _Jenny Bryan_  http://bit.ly/2AbUZ0C\n* Joining Data in R with dplyr (Rpubs) http://bit.ly/2ZjTwnm\n* Gif for differrent types of Joins http://bit.ly/2ZixS2L\n\n### data.table Package \n* Intro to data.table Package http://bit.ly/2Aa6Yf3\n* Wrangling with data.table http://bit.ly/2QQfLIy\n* R studio cheatsheet (data.table) http://bit.ly/2IEwRcM\n* Data crunching with data.table (Rpubs) http://bit.ly/2AbNCGz\n* Best packages for data manipulation in R (dplyr \u0026 data.table) http://bit.ly/2AenZox\n* A data.table and dplyr tour http://bit.ly/2IDlIYd\n\n### String manipulation and stringr package \n* String Manipulation in R with stringr (Rpubs) http://bit.ly/2SzLyiR\n* Regular Expression in R _Gloria Li and Jenny Bryan_ http://bit.ly/2SD74Dg\n\n## Data Visualization\n### ggplot2 Package\n* R Graph Gallery http://bit.ly/2UmD3ZN\n* DataCarpentry resources: http://bit.ly/2Aaiwz2\n* Visualización estática e interactiva con ggplot2 y plotly [español] http://bit.ly/2xI2dqH\n* Data Visualization in R http://bit.ly/2AaKzy9\n* R graphics with ggplot2 workshop notes http://bit.ly/2AavgG4\n* Data visualization using ggplot2 http://bit.ly/2Aal7ZT\n* ggplot2 package by Hadley Wickham (Rpubs) http://bit.ly/2AaaeqN\n* 7 Visualizations You Should Learn in R http://bit.ly/2NwhCBf\n* How to make fancy graphs with ggplot2 (Medium post) http://bit.ly/2PTV51W\n* Designing ggplots making clear figures that communicate bit.ly/ggplots\n* Drawing anything with ggplot2 https://github.com/thomasp85/ggplot2_workshop \n\n#### Books \n* Data Visualization A practical introduction _Kieran Healy_ http://bit.ly/2AaF9n2\n* Data Visualization with R. _Rob Kabacoff_ http://bit.ly/2A9pLaj\n* ggplot2: Elegant Graphics for Data Analysis _Hadley Wickham_ https://ggplot2-book.org/\n\n\n#### Visualization Courses\n* CS 448B Visualization. Stanford CS course on data visualization techniques (Fall 2018) http://bit.ly/2IDzfyW\n\n## Modeling\n### Broom\n* Broom vignette http://bit.ly/2M42z5y\n* Convenient analysis with broom - Alex Hayes - http://bit.ly/2ZdV7e4\n* broom: a package for tidying statistical models into data frames http://bit.ly/2Wi0FBZ\n### Tidymodels\n* A gentle introduction to tidymodels http://bit.ly/2G176QI\n* Tutorial on tidymodels for Machine Learning https://bit.ly/37iyQwC\n\n\n### H2o.ai\n* Auto Machine Learning with H2o.ai #LatinR2019 _Erin Ledell_ http://bit.ly/35nDEQ7\n* Youtube Channel http://bit.ly/2ogLiep\n\n### Data Modeling \n* Hands-on Machine Learning with R http://bit.ly/2IBxTEM\n* Feature Engineering and Selection: A Practical Approach for Predictive Models http://bit.ly/2IEf2Jw \n\n\n## Shiny Web Application\n* Rstudio Resources http://bit.ly/2QOovPq\n* Introduction to Shiny [video] http://bit.ly/2Aat9BQ\n* Testing Shiny applications with Shinytest - Shiny developers now have tools for automated testing of complete applications [video] http://bit.ly/2AauJUq\n* Understanding PCA using Shiny and Stack Overflow data _Julia Silge_ [video] http://bit.ly/2QLmG5K\n* Developing and deploying large scale Shiny applications _Herman Sontrop_ [video] http://bit.ly/2QT8rMx\n* Understanding Shiny Modules [video] http://bit.ly/2AaTuzS\n* Interactive Graphics with Shiny [video] http://bit.ly/2Aau45h\n* Interactive web-based data visualization with R, plotly, and shiny https://plotly-r.com/\n* Javascript for Shiny Users https://github.com/rstudio-conf-2020/js-for-shiny \n* Interactive web applications with Shiny - meetup material https://bit.ly/2B0Eacq\n* Production-grade Shiny Apps with golem - rstudio::conf2019 talk https://bit.ly/30G685J\n* Building Big Shiny Apps — A Workflow – [1/2](https://bit.ly/32Hr0MN) [2/2](https://bit.ly/3jvlxP8) \n* Building a Shiny App as a Package https://bit.ly/30EgTpb\n* Testing shiny Apss https://speakerdeck.com/colinfay/erum-2020-testing-shiny-why-what-and-how \n* A gRadual introduction to Shiny. https://laderast.github.io/gradual_shiny/index.html\n\n#### Books\n* Mastering Shiny _Hadley Wickham_ http://bit.ly/2z89f9l\n* Interactive web-based data visualization with R, plotly, and shiny http://bit.ly/2IBuR3m\n* Engineering Production-Grade Shiny Apps https://engineering-shiny.org/\n\n## R Markdown\n* R Markdown Gallery http://bit.ly/2QPHxoI\n* R Markdown articles http://bit.ly/2A9LfEe\n* R Markdown Rstudio lessons http://bit.ly/2A9Ln6G\n* 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\n* Beyond static reports with R Markdown [video] http://bit.ly/2Ac2jtd\n* Introducing Notebooks with R Markdown [video] http://bit.ly/2AaYPXH\n* RMarkdown Tips and Tricks - An Introduction to RMarkdown http://bit.ly/2P1NjaA\n* RMarkdwon Workshop http://bit.ly/2P3kYkt\n* Reproducible Reporting http://bit.ly/2A9MH9E\n* 15 Tips on Making Better Use of R Markdown _Yihui Xie_ https://slides.yihui.org/2019-dahshu-rmarkdown#1\n\n### Books\n* R Markdown: The Definitive Guide _Yihui Xie, J. J. Allaire, Garrett Grolemund_ http://bit.ly/2QNTISX\n* Introduction to RMarkdown http://bit.ly/2P59GMo\n* RMarkdown for Scientists http://bit.ly/2T2Uca8\n\n\n## Bookdown \u0026 Blogdown\n* Introducing bookdown [video] http://bit.ly/2AbArpc\n* Introducing blogdown, a new R package to make blogs and websites with R Markdown [video] http://bit.ly/2AamVSt\n* A week of blogdown for RStudio's summer 2019 interns _Alison Hill_ https://summer-of-blogdown.netlify.com/\n### Books\n* bookdown: Authoring Books and Technical Documents with R Markdown _Yihui Xie_ http://bit.ly/2QLTZWq\n* blogdown: Creating Websites with R Markdown _Yihui Xie, Amber Thomas, Alison Presmanes Hill_ http://bit.ly/2QPjCpm\n\n## R code Best Practices\n* R Best Practices: R you writing the R way! http://bit.ly/2P2TkE3\n* R Code – Best practices http://bit.ly/2P13Mfq\n* Best Practices for Writing R Code [The Carpentries] http://bit.ly/2P3485h\n\n## R Package Development\n* Write your first R Package (STAT 545 Course) _Jenny Bryan_ http://bit.ly/2OjiBs2\n* You can make a package in 20 minutes _Jim Hester_ [Video] http://bit.ly/2QR3K5D\n* What makes a great R package? _Joseph Rickert_ [Video] http://bit.ly/2QLS9Vw\n* How to develop good R packages (for open science) _Maëlle Salmon_ http://bit.ly/2QTXgmP\n* Writing an R package from scratch (Not so Standard deviations blogpost) _Hilary Parker_ http://bit.ly/2QOlONO\n* R Package Development Pictorial http://bit.ly/2QP5tbW\n* Developing Packages with RStudio http://bit.ly/2QOav8v\n* Writing an R package from scratch http://bit.ly/2QTWZAj\n* Reproducible Research: Writing an R Package. http://bit.ly/2AarXi0 \n* Advanced R Course (Chapter 6: R Packages) _Florian Privé_ http://bit.ly/2QT53kN\n* rOpenSci Packages: Development, Maintenance, and Peer Review http://bit.ly/2P3k7QN\n* R Package Development Tutorial #LatinR2019 _Hadley Wickham_ https://github.com/hadley/pkg-dev\n* Make an R Package - the easy way - _Matt Dray_  http://bit.ly/2PCEhQh\n* Usethis package development workflow http://bit.ly/2pzuoIg\n\n### Books \n* R Packages _Hadley Wickham_ http://r-pkgs.had.co.nz/\n\n## purrr Package - Functional Programming\n* Happy R Users Purrr – Tutorial _Charlotte Wickham_ [Video] http://bit.ly/2AakkIv\n* Purrr tutorial - _Charlotte Wickham_ http://bit.ly/2AaDCNO\n* Purrr tutorial - _Jenny Bryan_ http://bit.ly/2QSVoLC\n* Package CRAN Documentation http://bit.ly/2zbuSFz\n* Purrr as part of the tidyverse http://bit.ly/2z6gFcO\n* The joy of Functional Programming _Hadley Wickham_ http://bit.ly/2IC2qCk\n* Purrr - tips and tricks https://bit.ly/2AWODF6\n* Two examples of iteration with purrr - Class for the R-Studio certification  https://bit.ly/3dzWKoK\n\n\n## How to write functions in R. \n* Jenny Bryan's STAT 545 Course http://bit.ly/2QGCtnc \n* Jenny Bryan's Talk in RLadies Bs As _Writing R functions for fun and profit_ http://bit.ly/2xMqhsu\n\n## R-Spatial \n* Spatial Data Analysis and Modeling with R http://rspatial.org/\n* Spatial modelling using ‘raster’ package (useR! Conf 2018) - [Part 1] http://bit.ly/2SJ9PTB [Part 2] http://bit.ly/2SIJgOr\n* Spatial Data Science _Edzer Pebesma, Roger Bivand_ https://keen-swartz-3146c4.netlify.com/\n\n## Reproducible Research \n* Best Practices for Scientific Computing _Greg Wilson … Paul Wilson_ | *PLoS Biology 2014* http://bit.ly/2SHZqrs\n* Good enough practices in scientific computing _Greg Wilson ... Tracy Teal_| *_PlOS Computational Biology 2017_* http://bit.ly/2zhSSXW\n* Reproducibility in Science - ROpenSci -  http://bit.ly/2P18DgA\n* The drake R Package User Manual http://bit.ly/2P4n9nK\n* rrtools: Tools for Writing Reproducible Research in R - http://bit.ly/2zhMekA\n* Use of an R package to facilitate reproducible research - http://bit.ly/2zhP8G0\n\n\n## Metaprogramming - TidyEval \n* Tidy evaluation _Lionel Henry \u0026 Hadley Wickham_ http://bit.ly/2P5oRFy\n* Lazy evaluation _Jenny Bryan_  [video Rstudio conf 2019] http://bit.ly/2P82pvn [material] http://bit.ly/2PgphbY\n\n## Tutorials from different topics\n* The coding club http://bit.ly/2SJzTy7\n* The R class _R programming for biologists_ http://bit.ly/2SD71HA\n* R for NFL analysis http://bit.ly/2ICmqoo\n\n## R Courses with Tidyverse\n* Tidy Data Science Workshop (Jun-2019) http://bit.ly/2ID1mhV\n* RaukR-2019 http://rstd.io/raukr\n* UC Business Analytics R Programming Guide http://uc-r.github.io/\n* STAT 545A/547M: Exploratory Data Analysis - Jenny Bryan -  http://bit.ly/31fsz0t\n* Data Science in a Box - Mine Çetinkaya-Rundel - http://bit.ly/2PcydPU \n* R for learning and teaching R _List of resources_ http://bit.ly/2PaIqwc\n* BIMS8382 Spring 2018 https://bims8382.github.io/2018/\n* Course materials for Applied Machine Learning course in 2019 in London https://github.com/topepo/aml-london-2019\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdata-datum%2Flearning_R","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdata-datum%2Flearning_R","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdata-datum%2Flearning_R/lists"}