R resources (free courses, books, tutorials, & cheat sheets)

川长思鸟来 2022-05-28 05:21 268阅读 0赞

![i2-wp-combigdatasciencetraining-comwp-contentuploads201607importance-of-learning-r-30e49bf00fcc57f39db94df59c306537448f0110.jpg_w_601][]

Date: [10 August 2017][] Author: [Paul van der Laken][] [14 Comments][]

Below is a list of free books, tutorials, packages, cheat sheets and other material to learn programming in R and improve your workflow. There are separate overviews for [Python resources][], [SQL resources][], and general [Data Science, Machine Learning, & Statistics resources][Data Science_ Machine Learning_ _ Statistics resources]. If you have additions, please comment below or [contact me][]!

Completely new to R? → [Start here!][Start here]

##### LAST UPDATED: 26-03-2018 #####

## R Basics ##

### Cheat Sheets: ###

*  [Base R cheat sheet by Mhairi McNeill][]\*\*\*
 *  [Base R Functions cheat sheet by Tom Short][]
 *  [Basic R cheat sheet by Quandl.com][]
 *  [R Function Abbreviations Explained by Jeromy Anglim][]
 *  [RStudio cheat sheet by RStudio][]
 *  [RStudio Keyboard Shortcuts by RStudio][]\*\*\*
 *  [Data Management in R cheat sheet][]
 *  [`data.table` wide cheat sheet by DataCamp.com][data.table_ wide cheat sheet by DataCamp.com]
 *  [`data.table` long cheat sheet by DataCamp.com][data.table_ long cheat sheet by DataCamp.com]
 *  [Advanced R cheat sheet by Arianne Colton & Sean Chen][Advanced R cheat sheet by Arianne Colton _ Sean Chen]
 *  [`tidyverse cheat sheet by DataCamp.com`][tidyverse cheat sheet by DataCamp.com]
 *  [Data Import cheat sheet by RStudio][] with `readr`, `tibble`, and `tidyr`
 *  [Factor Manipulation with `forcats` cheat sheet by Lise Vaudor][Factor Manipulation with _forcats_ cheat sheet by Lise Vaudor]
 *  [Data Transformation cheat sheet by Rstudio][] with `dplyr`
 *  [Data Transformation cheat sheet 2 by Daniel Lüdecke][Data Transformation cheat sheet 2 by Daniel L_decke] with `dplyr` and `sjmisc`
 *  [Data Wrangling cheat sheet by RStudio][] with `dplyr` and `tidyr`
 *  [Character String Manipulation cheat sheet by RStudio][] with `stringr`
 *  [Dates and Times cheat sheet by RStudio][] with `lubridate`
 *  [Split-Apply-Combine cheat sheet by Ernest Adrogue Calvera][]
 *  [`purr` Functional Programming cheat sheet by RStudio][purr_ Functional Programming cheat sheet by RStudio]
 *  [Tidy Evaluation by Edwin Thoen][]
 *  [R Syntax Comparison cheat sheet by Amelia McNamara][]
 *  [RStudio cheat sheet GitHub][]

### Introductory Books: ###

*  [Introduction to R (R Core Team, 1999)][Introduction to R _R Core Team_ 1999]
 *  [R Language Definition (Manual) (R Core Team, 2000)][R Language Definition _Manual_ _R Core Team_ 2000]
 *  [Data Import/Export (R Core Team, 2000)][Data Import_Export _R Core Team_ 2000]
 *  [SimpleR (Verzani, 2001-2)][SimpleR _Verzani_ 2001-2]
 *  [R for Beginners (Paradis, 2002)][R for Beginners _Paradis_ 2002]
 *  [Introduction to R (Spector, 2004)][Introduction to R _Spector_ 2004]
 *  [Ecological Models and Data in R (Bolker, 2007)][Ecological Models and Data in R _Bolker_ 2007]
 *  [Software for Data Analysis: Programming with R (Chambers, 2008)][Software for Data Analysis_ Programming with R _Chambers_ 2008]
 *  [Econometrics in R (Farnsworth, 2008)][Econometrics in R _Farnsworth_ 2008]
 *  [The Art of R Programming (Matloff, 2009)][The Art of R Programming _Matloff_ 2009]
 *  [R in a Nutshell (Adler, 2010)][R in a Nutshell _Adler_ 2010]
 *  [R in Action: Data Analysis and Graphics with R (Kabacoff, 2011)][R in Action_ Data Analysis and Graphics with R _Kabacoff_ 2011]
 *  [R for Psychology Experiments and Questionnaires (Baron, 2011)][R for Psychology Experiments and Questionnaires _Baron_ 2011]
 *  [The R Inferno (Burns, 2011)][The R Inferno _Burns_ 2011]
 *  [Cookbook for R (Chang, ???)][Cookbook for R _Chang_]
 *  [The R Book (Crawley, 2013)][The R Book _Crawley_ 2013]
 *  [Introduction to Statistical Thought (Lavine, 2013)][Introduction to Statistical Thought _Lavine_ 2013]
 *  [A (very) short introduction to R (Torfs & Bauer, 2014)][A _very_ short introduction to R _Torfs _ Bauer_ 2014]\*\*\*
 *  [Advanced R (Wickham, 2014)][Advanced R _Wickham_ 2014]
 *  [Introduction to R (Vaidyanathan, 2014)][Introduction to R _Vaidyanathan_ 2014]
 *  [Learning statistics with R: A tutorial for psychology students and other beginners (Navarro, 2014)][Learning statistics with R_ A tutorial for psychology students and other beginners _Navarro_ 2014]
 *  [Introduction to R (Venables, Smith, & R Core Team, 2017)][Introduction to R _Venables_ Smith_ _ R Core Team_ 2017]
 *  [The R Language Definition (R Core Team, 2017)][The R Language Definition _R Core Team_ 2017]
 *  [YaRrr! The Pirate’s Guide to R (Phillips, 2017)][YaRrr_ The Pirate_s Guide to R _Phillips_ 2017]\*\*\*

### Online Courses: Introductory & Advanced: ###

*  `swirl()`\*\*\*
 *  [Try R by Code School][]
 *  [Learn R by R-Exercises][]
 *  [R Tutorial by Cyclismo & DataCamp][R Tutorial by Cyclismo _ DataCamp]
 *  [100 Tutorials for Learning R][]
 *  [Introduction to R by DataCamp][]
 *  [YaRrr! The Pirate’s Guide to R (Video)][YaRrr_ The Pirate_s Guide to R _Video]
 *  [R for Cats][]
 *  [A Psychologist’s Guide to R][A Psychologist_s Guide to R] ([pdf][]) by Sean Chris Murphy
 *  [Social Sciences: Critically Analyze Research and Results Using R by Coursera][Social Sciences_ Critically Analyze Research and Results Using R by Coursera]
 *  [A Hands-on Introduction to Statistics with R by DataCamp.com][]
 *  [R Course in Statistics by PagePiccini.com][]
 *  [Mini courses in R by UCLA][]
 *  [Data Science: R Basics @edX][Data Science_ R Basics _edX]
 *  [Introduction to R for Data Science @edX][Introduction to R for Data Science _edX]
 *  [Data Analysis and Visualization Using R @VarianceExplained][Data Analysis and Visualization Using R _VarianceExplained]
 *  [R Programming @Coursera][R Programming _Coursera]\*\*\* by Roger Peng, Jeff Leek, & Brian Caffo
 *  [DIY: 37 Youtube R Tutorials Overview by Flavio Azevedo][DIY_ 37 Youtube R Tutorials Overview by Flavio Azevedo]\*\*\*

### Style Guides: ###

*  [Google’s R Style Guide][Google_s R Style Guide]
 *  [Advanced R Style Guide][] by Hadley Wickham
 *  [A guide for switching from base R to the `tidyverse`][A guide for switching from base R to the _tidyverse].

##  ##

## Data Visualization in R ##

*  [R Graph Gallery & Code Examples][R Graph Gallery _ Code Examples]\*\*\*
 *  [Fundamentals of Data Visualization (Wilke, 2018)][Fundamentals of Data Visualization _Wilke_ 2018]
 *  [R Base Plots Wiki Reference Guide][]
 *  [CRAN Task View – Graphics & Visualization][CRAN Task View _ Graphics _ Visualization]
 *  [R Graphical Parameters Cheatsheet by Flowingdata.com][]

### Colors ###

*  [R Color Guide][]\*\*\*
 *  [colourpicker][] – widget that allows users to choose colours
 *  [ggplot2 colour guide][]\*\*\*
 *  multicolored annotated text in ggplot2 [by Andrew Whitby][] & [Visuelle Data][]

### Interactive / HTML widgets: ###

*  [R HTML Widgets Gallery][]\*\*\*
 *  [plotly][] – interactive plots
 *  [d3heatmap][] – interactive d3 heatmaps
 *  [DT][] – interactive tables
 *  [DiagrammeR][] – interactive diagrams
 *  [dygraphs][] – interactive time series plots
 *  [formattable][] – formattable data structures
 *  [ggvis][] – interactive ggplot2
 *  [Highcharter][] – interactive Highcharts plots
 *  [leaflet][] – interactive maps
 *  [metricsgraphics][] – interactive JavaScript bare-bones line, scatterplot and bar charts
 *  [networkD3][] – interative d3 network graphs
 *  [scatterD3][] – interactive scatterplots with d3
 *  [rbokeh][] – interactive Bokeh plots
 *  [rCharts][] – interactive Javascript charts
 *  [rcdimple][] – interactive JavaScript bar charts and others
 *  [rglwidget][] – interactive 3d plots
 *  [threejs][] – interactive 3d plots and globes
 *  [visNetwork][] – interactive network graphs
 *  [wordcloud2][] – interface to wordcloud2.js.
 *  [timevis][] – interactive timelines

### ggplot2 ###

*  [Code examples of top-50 ggplot2 visualizations][]\*\*\*
 *  [ggplot2 Cheatsheet by RStudio][]
 *  [ggplot2 Quick Reference Guide ][ggplot2 Quick Reference Guide]
 *  [ggplot2 Code Snippets][]
 *  [ggplot2 Code Snippets 2][]
 *  [A practical introduction with R and ggplot2 (Healy, 2017)][A practical introduction with R and ggplot2 _Healy_ 2017]
 *  [Data Vizualization: A practical introduction (Healy, 2018)][Data Vizualization_ A practical introduction _Healy_ 2018]
 *  [Hitchhiker’s Guide to ggplot2 in R (Burchell & Vargas, 2016)][Hitchhiker_s Guide to ggplot2 in R _Burchell _ Vargas_ 2016]
 *  [Setting custom ggplot themes][] with `ggthemr`
 *  [Creating custom, reproducible color palettes][Creating custom_ reproducible color palettes] by [Simon Jackson][]
 *  [Rearranging values within ggplot2 facets][]
 *  Combine plots using `patchwork` or `cowplot`
 *  [ggplot2 extensions overview][]\*\*\*
    
     *  `ggthemes` – plot style themes
     *  `hrbrthemes` – opinionated, typographic-centric themes
     *  `ggmap` – maps with Google Maps, Open Street Maps, etc.
     *  `ggiraph` – interactive ggplots
     *  `ggstance` – horizontal versions of common plots
     *  `GGally` – scatterplot matrices
     *  `ggalt` – additional coordinate systems, geoms, etc.
     *  `ggforce` – additional geoms, etc.
     *  `ggrepel` – prevent plot labels from overlapping
     *  `ggraph` – graphs, networks, trees and more
     *  `ggpmisc` – photo-biology related extensions
     *  `geomnet` – network visualization
     *  `ggExtra` – marginal histograms for a plot
     *  `gganimate` – animations
     *  `ggspectra` – tools for plotting light spectra
     *  `ggnetwork` – geoms to plot networks
     *  `ggradar` – radar charts
     *  `ggsurvplot (survminer)` – survival curves
     *  `ggseas` – seasonal adjustment tools
     *  `ggtech` – style themes for plots
     *  `ggtern` – ternary diagrams
     *  `ggTimeSeries` – time series visualizations
     *  `ggtree` – tree visualizations
     *  `treemapify` – wilcox’s treemaps

### Miscellaneous ###

*  `coefplot` – visualizes model statistics
 *  [`circlize`][circlize] – circular visualizations for categorical data
 *  `quantmod` – candlestick financial charts
 *  `colorspace` – HSL based color palettes
 *  `viridis` – Matplotlib viridis color pallete for R
 *  `munsell` – Munsell color palettes for R.
 *  `Cairo` – high-quality display output
 *  `igraph` – Network Analysis and Visualization
 *  `lattice` – Trellis graphics
 *  `tmap` – thematic maps
 *  [`trelliscopejs`][trelliscopejs] – interactive alternative for ggplot2::facet\_wrap
 *  `rgl` – interactive 3D plots
 *  `corrplot` – graphical display of a correlation matrix
 *  `googleVis` – Google Charts API
 *  `plotROC` – interactive ROC plots
 *  `extrafont` – fonts in R graphics
 *  `showtext` – text using system fonts
 *  `animation` – animated graphics using [ImageMagick][].
 *  `misc3d` – 3d plots, isosurfaces, etc.
 *  `xkcd` – xkcd style graphics
 *  `imager` – CImg library to work with images

### Dashboards & Shiny ###

*  [Shiny Cheat Sheet by RStudio][]
 *  [More Shiny Resources by Rob Gilmore][]
 *  [More Shiny Resources for Statistics by Yingjie Hu][]
 *  [Shiny Tutorial][]
 *  [Building Shiny apps – an interactive tutorial][Building Shiny apps _ an interactive tutorial] by Dean Attali
 *  `flexdashboard` – dashboard creation simplified
 *  `colourpicker` – widget that allows users to choose colours.

##  ##

## Regular Expressions in R ##

*   *  [R Regular Expression Cheatsheet by Lise Vaudor][]
     *  [R Regular Expression Cheatsheet][]
     *  [R Regular Expression Cheatsheet (page 2) by RStudio][Character String Manipulation cheat sheet by RStudio]
     *  [Regular Expressions in R – Part 1: Introduction and base R functions][Regular Expressions in R _ Part 1_ Introduction and base R functions]
     *  [R Regular Expressions by Jon M. Calder in swirl()][R Regular Expressions by Jon M. Calder in swirl]
     *  [R Regular Expression Video Tutorial][] by Roger Peng
     *  General [Regular Expression Cheatsheet][]
     *  General [Regular Expression Video Tutorial][] by Roger Peng
     *  General [Regular Expression Cheatsheet by OverAPI.com][]

##  ##

## R Markdown & Documentation ##

*  [R Markdown Cheatsheet by RStudio][]
 *  [R Markdown Reference Guide by RStudio][]
 *  [R Markdown Basics][]
 *  [Markdown Tutorial by RStudio][]
 *  [Markdown Gallery by RStudio][]
 *  [The `knitr` book (Xie, 2015)][The _knitr_ book _Xie_ 2015]
 *  [Creating slides with R Markdown (Video)][Creating slides with R Markdown _Video] by Brian Caffo
 *  General [Markdown Cheatsheet][]
 *  [`blogdown`: Creating Websites with R Markdown (Xie, Thomas, & Hill, 2018)][blogdown_ Creating Websites with R Markdown _Xie_ Thomas_ _ Hill_ 2018]
 *  [`blogdown` tutorials][blogdown_ tutorials]
 *  Packages:
    
     *  `tidystats` – automating updating of model statistics
     *  `papaja` – preparing APA journal articles
     *  `blogdown` – build websites with Markdown & Hugo
     *  [`huxtable`][huxtable] – create Excel, html, & LaTeX tables

##  ##

## R Database Linking ##

*  [Tutorial: Database Queries with R][Tutorial_ Database Queries with R]
 *  [Introduction to `sparklyr` by DataCamp][Introduction to _sparklyr_ by DataCamp]
 *  [`dbplot`][dbplot] – leverages `dplyr` to process calculations of plot inside database

##  ##

## Functional Programming ##

*  [Functional Programming lecture by Duke University][]
 *  [Functional Programming: `purrr` tutorial by Jenny Bryan][Functional Programming_ _purrr_ tutorial by Jenny Bryan]
 *  [`purr` Functional Programming cheat sheet by RStudio][purr_ Functional Programming cheat sheet by RStudio]
 *  [Writing Function in R by DataCamp.com][]

##  ##

## Statistical Learning, Machine Learning, & Data Science ##

*  [Machine Learning with R: An Irresponsibly Fast Tutorial by Will Stanton][Machine Learning with R_ An Irresponsibly Fast Tutorial by Will Stanton]\*\*\*
 *  [CRAN Task View – Machine Learning & Statistical Learning][CRAN Task View _ Machine Learning _ Statistical Learning]
 *  [R Packages for Machine Learning][] by Joseph Misiti
 *  [Introduction to Data Science with R (Video)][Introduction to Data Science with R _Video]
 *  [Course: Introduction to R for Data Science @Microsoft][Course_ Introduction to R for Data Science _Microsoft]
 *  [Course: Introduction to R for Data Science @FutureLearn][Course_ Introduction to R for Data Science _FutureLearn] by Hadley Wickham
 *  [Introduction to Statistical Learning (James, Witten, Hastie, & Tibshirani, 2013)][Introduction to Statistical Learning _James_ Witten_ Hastie_ _ Tibshirani_ 2013]
 *  [Course: Introduction to Statistical Learning (Hastie & Tibshirani, 2014)][Course_ Introduction to Statistical Learning _Hastie _ Tibshirani_ 2014]\*\*\*
 *  [Data Science Live Book (Casas, 2017)][Data Science Live Book _Casas_ 2017]
 *  [100 Tutorials for Learning R][]
 *  [R Programming for Data Science (Peng, 2016)][R Programming for Data Science _Peng_ 2016]
 *  [R for Data Science (Grolemund & Wickham, 2017)][R for Data Science _Grolemund _ Wickham_ 2017]\*\*\*
 *  [Elements of Statistical Learning (Hastie, Tibshirani, & Friedman, 2001)][Elements of Statistical Learning _Hastie_ Tibshirani_ _ Friedman_ 2001]
 *  [Statistical Foundations of Machine Learning (Bontempi & Taieb, 2017)][Statistical Foundations of Machine Learning _Bontempi _ Taieb_ 2017]
 *  [Machine Learning with R (Lantz, 2013)][Machine Learning with R _Lantz_ 2013]
 *  [R Functions for Regression Analysis Cheatsheet by Vito Ricci][]
 *  [Regression Models for Data Science in R (Caffo, 2015)][Regression Models for Data Science in R _Caffo_ 2015]
 *  [Applied Biostatistical Analyses using R (Cox, 2017)][Applied Biostatistical Analyses using R _Cox_ 2017]
 *  [Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Williams, 2011)][Data Mining with Rattle and R_ The Art of Excavating Data for Knowledge Discovery _Williams_ 2011]
 *  [Machine Learning Algorithms R Implementation by Ajitesh Kumar][]
 *  [R Data Mining Reference Card][]
 *  [R Data Mining: Examples & Case Studies (Zhao, 2015)][R Data Mining_ Examples _ Case Studies _Zhao_ 2015]
 *  [Statistical modelling in R (Zhao, 2015)][Statistical modelling in R _Zhao_ 2015] @[RDataMining][]
 *  [Predictive modelling in R][] with `caret`
 *  [Machine Learning with `caret` cheat sheet by Max Kuhn][Machine Learning with _caret_ cheat sheet by Max Kuhn]
 *  [R `sparklyr` cheat sheet by RStudio][R _sparklyr_ cheat sheet by RStudio]
 *  [Machine Learning modelling cheat sheet by Arnaud Amsellem][]
 *  [Machine Learning with `mlr` cheat sheet by Aaron Coley][Machine Learning with _mlr_ cheat sheet by Aaron Coley]
 *  [Deep Learning with `keras` cheat sheet by RStudio][Deep Learning with _keras_ cheat sheet by RStudio]
 *  [R Interface to Keras][]

##  ##

## Natural Language Processing & Text Mining ##

*  [Text Mining Tutorial][] with `tm`
 *  [Tidy Text Mining (Silges & Robinson, 2017)][Tidy Text Mining _Silges _ Robinson_ 2017] with `tidytext`
 *  [Text Analysis with R for Students of Literature (Jockers, 2014)][Text Analysis with R for Students of Literature _Jockers_ 2014]
 *  [100 Tutorials for Learning R][]
 *  [21 Recipes for Mining Twitter Data (Rudis, 2017)][21 Recipes for Mining Twitter Data _Rudis_ 2017] with `rtweet`
 *  [Course: Introduction to Text Analytics with R][Course_ Introduction to Text Analytics with R] @DataScienceDojo
 *  [Course: Twitter Text Mining and Social Network Analysis (Zhoa, 2016)][Course_ Twitter Text Mining and Social Network Analysis _Zhoa_ 2016] @[RDataMining][] with `twitteR`
 *  [List of resources for NLP & Text Mining by Stephen Thomas][List of resources for NLP _ Text Mining by Stephen Thomas]
 *  Packages — for an overview: [CRAN Task View – Natural Language Processing][CRAN Task View _ Natural Language Processing]:
    
     *  `tm` – text mining.
     *  `tidytext` – text mining using `tidyverse` principles
     *  `quanteda` – framework for quantitative text analysis
     *  `gutenbergr` – public domain works (free books to practice on)
     *  `corpora` – statistics and data sets for corpus frequency data.
     *  `tau` – Text Analysis Utilities
     *  `Sentiment140` – headache-free sentiment analysis
     *  `sentimentr` – sentiment analysis using text polarity
     *  `openNLP` – sentence detector, tokenizer, pos-tagger, shallow and full syntactic parser, named-entity detector, and maximum entropy models with [OpenNLP][].
     *  `cleanNLP` – natural language processing via tidy data models
     *  `RSentiment` – English lexicon-based sentiment analysis with negation and sarcasm detection functionalities.
     *  `RWeka` – data mining tasks with [Weka][]
     *  `wordnet` – a large lexical database of English with [WordNet ][WordNet].
     *  `stringi` – language processing wrappers
     *  `textcat` – provides support for n-gram based text categorization.
     *  `text2vec` – text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), and similarities.
     *  `lsa` – Latent Semantic Analysis
     *  `topicmodels` \-Latent Dirichlet Allocation (LDA) and Correlated Topics Models (CTM)
     *  `lda` \-Latent Dirichlet Allocation and related models

##  ##

## Time series ##

*  [CRAN Task View – TimeSeries][CRAN Task View _ TimeSeries]
 *  [R xts Cheatsheet][]
 *  [Forecasting: Principles and Practice (Hyndman & Athanasopoulos, 2017)][Forecasting_ Principles and Practice _Hyndman _ Athanasopoulos_ 2017]
 *  [A little book of R for time series (tutorial)][A little book of R for time series _tutorial]
 *  Tutorials: [Part 1][], [Part 2][], [Part 3][], & [Part 4][] of tidy time series [@Business-Science.io][Business-Science.io] with tidyquant

##  ##

## Survival analysis ##

*  [CRAN Task View – Survival][CRAN Task View _ Survival]
 *  [R Survival Analysis Cheatsheet by Przemysław Biecek][R Survival Analysis Cheatsheet by Przemys_aw Biecek]
 *  [survival][] – functionality for survival and hazard models
 *  [ggsurvplot (survminer)][ggsurvplot _survminer] – survival curves

##  ##

## Geographical / Spatial mapping ##

*  [Making Maps with R (tutorial)][Making Maps with R _tutorial] with ggmaps, maps, and mapdata
 *  [Importing OpenStreetMap data (tutorial)][Importing OpenStreetMap data _tutorial] with osmar

##  ##

## Other applications ##

*  [Image featurization][]
 *  [Introduction to Empirical Bayes (Robinson, ???)][Introduction to Empirical Bayes _Robinson_]
 *  [CRAN Task View – Bayesian Inference][CRAN Task View _ Bayesian Inference]

##  ##

## R Development, Optimization & Other ##

*  [R Package Development Cheatsheet][] with devtools
 *  [Mastering Software Development in R (Peng, Kross, & Anderson, 2017)][Mastering Software Development in R _Peng_ Kross_ _ Anderson_ 2017]
 *  [Efficient R Programming (Gillespie & Lovelace, 2017)][Efficient R Programming _Gillespie _ Lovelace_ 2017]
 *  [Happy Git and GitHub for the useR (Jenny Bryan, 2017)][Happy Git and GitHub for the useR _Jenny Bryan_ 2017]
 *  [RStudio Addins by Dean Attali][]

##  ##

## R Help, Connect, & Inspiration ##

*  [R Help Mailing List][]
 *  [R Seek][] – search engine for R-related websites
 *  [R site search][] – search engine for help files, manuals, and mailing lists
 *  [Nabble][] – mailing list archive and forum
 *  [R User Groups & Conferences][R User Groups _ Conferences]
 *  [Stack Overflow][] – a FAQ for all your R struggles (programming)
 *  [Cross Validated][] – a FAQ for all your R struggles (statistics)
 *  [CRAN Task Views][] – discover new packages per topic
 *  [The R Journal][] – open access, refereed journal of R
 *  Twitter: [\#rstats][rstats], [RStudio][], [Hadley Wickham][], [Yihui Xie][], [Mara Averick][], [Julia Silge][], [Jenny Bryan][], [David Smith][], [Hilary Parker][], [R-bloggers][]
 *  Facebook: [R Users Psychology][]
 *  Youtube: [Ben Lambert][], [Roger Peng][]
 *  Reddit: [rstats][rstats 1], [rstudio][], [statistics][], [machinelearning][], [dataisbeautiful][]

##  ##

## R Blogs ##

*  [http://adamleerich.com][http_adamleerich.com]
 *  [http://njtierney.github.io/][http_njtierney.github.io]
 *  [https://trinkerrstuff.wordpress.com][https_trinkerrstuff.wordpress.com]
 *  [https://rollingyours.wordpress.com][https_rollingyours.wordpress.com]
 *  [https://www.r-statistics.com][https_www.r-statistics.com]
 *  [https://beckmw.wordpress.com][https_beckmw.wordpress.com]
 *  [http://rgraphgallery.blogspot.com][http_rgraphgallery.blogspot.com]
 *  [http://onertipaday.blogspot.com][http_onertipaday.blogspot.com]
 *  [https://learnr.wordpress.com][https_learnr.wordpress.com]
 *  [http://padamson.github.io][http_padamson.github.io]
 *  [http://www.r-datacollection.com/blog/][http_www.r-datacollection.com_blog]
 *  [http://www.thertrader.com][http_www.thertrader.com]
 *  [https://fronkonstin.com][https_fronkonstin.com]
 *  [https://nicercode.github.io][https_nicercode.github.io]
 *  [http://www.rblog.uni-freiburg.de][http_www.rblog.uni-freiburg.de]
 *  [https://advanceddataanalytics.net][https_advanceddataanalytics.net]
 *  [http://r4stats.com/blog/][http_r4stats.com_blog]
 *  [http://blog.revolutionanalytics.com/][http_blog.revolutionanalytics.com]
 *  [http://www.r-bloggers.com/][http_www.r-bloggers.com]
 *  [http://kbroman.org/blog/][http_kbroman.org_blog]
 *  [https://juliasilge.com/blog/][https_juliasilge.com_blog]
 *  [http://andrewgelman.com/][http_andrewgelman.com]
 *  [http://www.statsblogs.com/author/eric-cai-the-chemical-statistician/][http_www.statsblogs.com_author_eric-cai-the-chemical-statistician]
 *  [https://www.statmethods.net/][https_www.statmethods.net]
 *  [http://www.stats-et-al.com/search/label/R][http_www.stats-et-al.com_search_label_R]

## R Jobs ##

*  [R Jobs on StackOverflow.com][]
 *  [R Jobs on R-users.com][]
 *  [Jobs on Kaggle][]

[i2-wp-combigdatasciencetraining-comwp-contentuploads201607importance-of-learning-r-30e49bf00fcc57f39db94df59c306537448f0110.jpg_w_601]: /images/20220528/a2cfc0eb26d04d97a11a93767f380c0f.png
[10 August 2017]: https://paulvanderlaken.com/2017/08/10/r-resources-cheatsheets-tutorials-books/
[Paul van der Laken]: https://paulvanderlaken.com/author/lakenp/
[14 Comments]: https://paulvanderlaken.com/2017/08/10/r-resources-cheatsheets-tutorials-books/#comments
[Python resources]: https://paulvanderlaken.com/2017/08/31/python-resources/
[SQL resources]: https://paulvanderlaken.com/2017/10/15/sql-resources/
[Data Science_ Machine Learning_ _ Statistics resources]: https://paulvanderlaken.com/2017/08/31/data-science-machine-learning-statistics-resources-free-books-courses/
[contact me]: https://paulvanderlaken.com/contact/
[Start here]: https://paulvanderlaken.com/2017/10/18/learn-r/
[Base R cheat sheet by Mhairi McNeill]: https://paulvanderlaken.files.wordpress.com/2017/08/base-r-cheetsheat.pdf
[Base R Functions cheat sheet by Tom Short]: https://paulvanderlaken.files.wordpress.com/2017/08/r-base-functions-reference-card.pdf
[Basic R cheat sheet by Quandl.com]: https://s3.amazonaws.com/quandl-static-content/Documents/Quandl+-+R+Cheat+Sheet.pdf
[R Function Abbreviations Explained by Jeromy Anglim]: http://jeromyanglim.blogspot.nl/2010/05/abbreviations-of-r-commands-explained.html
[RStudio cheat sheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/rstudio-ide.pdf
[RStudio Keyboard Shortcuts by RStudio]: https://support.rstudio.com/hc/en-us/articles/200711853-Keyboard-Shortcuts
[Data Management in R cheat sheet]: http://www.ualberta.ca/~ahamann/teaching/renr690/R_Cheat_Data.pdf
[data.table_ wide cheat sheet by DataCamp.com]: https://paulvanderlaken.files.wordpress.com/2017/08/datatable_cheat_sheet_r.pdf
[data.table_ long cheat sheet by DataCamp.com]: https://s3.amazonaws.com/assets.datacamp.com/img/blog/data+table+cheat+sheet.pdf
[Advanced R cheat sheet by Arianne Colton _ Sean Chen]: https://paulvanderlaken.files.wordpress.com/2017/08/advanced-r-cheatsheet.pdf
[tidyverse cheat sheet by DataCamp.com]: http://datacamp-community.s3.amazonaws.com/e63a8f6b-2aa3-4006-89e0-badc294b179c
[Data Import cheat sheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/data-import.pdf
[Factor Manipulation with _forcats_ cheat sheet by Lise Vaudor]: http://perso.ens-lyon.fr/lise.vaudor/manipulation-de-facteurs-avec-forcats/
[Data Transformation cheat sheet by Rstudio]: https://github.com/rstudio/cheatsheets/raw/master/data-transformation.pdf
[Data Transformation cheat sheet 2 by Daniel L_decke]: http://github.com/rstudio/cheatsheets/raw/master/sjmisc.pdf
[Data Wrangling cheat sheet by RStudio]: https://paulvanderlaken.files.wordpress.com/2017/08/ddplyr-cheatsheet-data-wrangling-plyr.pdf
[Character String Manipulation cheat sheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/strings.pdf
[Dates and Times cheat sheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/lubridate.pdf
[Split-Apply-Combine cheat sheet by Ernest Adrogue Calvera]: https://paulvanderlaken.files.wordpress.com/2017/08/split-apply-combine.pdf
[purr_ Functional Programming cheat sheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/purrr.pdf
[Tidy Evaluation by Edwin Thoen]: https://github.com/EdwinTh/EdwinTh.github.io/blob/master/_source/2017-08-24-dplyr-recipes.Rmd
[R Syntax Comparison cheat sheet by Amelia McNamara]: http://www.science.smith.edu/~amcnamara/Syntax-cheatsheet.pdf
[RStudio cheat sheet GitHub]: https://github.com/rstudio/cheatsheets/
[Introduction to R _R Core Team_ 1999]: https://cran.r-project.org/doc/manuals/R-intro.html
[R Language Definition _Manual_ _R Core Team_ 2000]: https://cran.r-project.org/doc/manuals/r-release/R-lang.html
[Data Import_Export _R Core Team_ 2000]: https://paulvanderlaken.files.wordpress.com/2017/08/r-data-import-export.pdf
[SimpleR _Verzani_ 2001-2]: https://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf
[R for Beginners _Paradis_ 2002]: https://paulvanderlaken.files.wordpress.com/2017/08/r-for-beginners.pdf
[Introduction to R _Spector_ 2004]: https://paulvanderlaken.files.wordpress.com/2017/08/r.pdf
[Ecological Models and Data in R _Bolker_ 2007]: https://ms.mcmaster.ca/~bolker/emdbook/book.pdf
[Software for Data Analysis_ Programming with R _Chambers_ 2008]: https://www.e-reading.club/bookreader.php/137398/Software_for_Data_Analysis_-_Programming_with_R.pdf
[Econometrics in R _Farnsworth_ 2008]: https://cran.r-project.org/doc/contrib/Farnsworth-EconometricsInR.pdf
[The Art of R Programming _Matloff_ 2009]: http://heather.cs.ucdavis.edu/~matloff/132/NSPpart.pdf
[R in a Nutshell _Adler_ 2010]: https://paulvanderlaken.files.wordpress.com/2017/08/r_in_a_nutshell.pdf
[R in Action_ Data Analysis and Graphics with R _Kabacoff_ 2011]: ftp://ftp.micronet-rostov.ru/linux-support/books/programming/R/Kabacoff%20Robert%20I.%20-%20R%20in%20Action%20-%202011.pdf
[R for Psychology Experiments and Questionnaires _Baron_ 2011]: http://www.psych.upenn.edu/~baron/rpsych/rpsych.html
[The R Inferno _Burns_ 2011]: http://www.burns-stat.com/pages/Tutor/R_inferno.pdf
[Cookbook for R _Chang_]: http://www.cookbook-r.com/
[The R Book _Crawley_ 2013]: https://www.cs.upc.edu/~robert/teaching/estadistica/TheRBook.pdf
[Introduction to Statistical Thought _Lavine_ 2013]: http://people.math.umass.edu/~lavine/Book/book.pdf
[A _very_ short introduction to R _Torfs _ Bauer_ 2014]: https://cran.r-project.org/doc/contrib/Torfs+Brauer-Short-R-Intro.pdf
[Advanced R _Wickham_ 2014]: http://adv-r.had.co.nz/
[Introduction to R _Vaidyanathan_ 2014]: https://ramnathv.github.io/pycon2014-r/
[Learning statistics with R_ A tutorial for psychology students and other beginners _Navarro_ 2014]: http://www.fon.hum.uva.nl/paul/lot2015/Navarro2014.pdf
[Introduction to R _Venables_ Smith_ _ R Core Team_ 2017]: https://paulvanderlaken.files.wordpress.com/2017/08/r-intro.pdf
[The R Language Definition _R Core Team_ 2017]: https://cran.r-project.org/doc/manuals/R-lang.pdf
[YaRrr_ The Pirate_s Guide to R _Phillips_ 2017]: https://bookdown.org/ndphillips/YaRrr/
[Try R by Code School]: http://tryr.codeschool.com/
[Learn R by R-Exercises]: http://www.r-exercises.com/start-here-to-learn-r/
[R Tutorial by Cyclismo _ DataCamp]: http://www.cyclismo.org/tutorial/R/index.html#
[100 Tutorials for Learning R]: https://www.listendata.com/p/r-programming-tutorials.html
[Introduction to R by DataCamp]: https://www.datacamp.com/courses/free-introduction-to-r
[YaRrr_ The Pirate_s Guide to R _Video]: https://www.youtube.com/playlist?list=PL9tt3I41HFS9gmeZFEuNrnu_7V_NFngfJ
[R for Cats]: https://rforcats.net/
[A Psychologist_s Guide to R]: https://github.com/seanchrismurphy/A-Psychologists-Guide-to-R
[pdf]: https://osf.io/v48zr/
[Social Sciences_ Critically Analyze Research and Results Using R by Coursera]: https://www.coursera.org/specializations/social-science
[A Hands-on Introduction to Statistics with R by DataCamp.com]: https://www.datacamp.com/introduction-to-statistics?utm_content=bufferd6325&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
[R Course in Statistics by PagePiccini.com]: https://pagepiccinini.com/r-course/
[Mini courses in R by UCLA]: http://scc.stat.ucla.edu/mini-courses/
[Data Science_ R Basics _edX]: https://www.edx.org/course/data-science-r-basics-harvardx-ph125-1x
[Introduction to R for Data Science _edX]: https://www.edx.org/course/introduction-r-data-science-microsoft-dat204x-6
[Data Analysis and Visualization Using R _VarianceExplained]: http://varianceexplained.org/RData/
[R Programming _Coursera]: https://www.coursera.org/learn/r-programming
[DIY_ 37 Youtube R Tutorials Overview by Flavio Azevedo]: http://flavioazevedo.com/stats-and-r-blog/2016/9/13/learning-r-on-youtube
[Google_s R Style Guide]: https://google.github.io/styleguide/Rguide.xml
[Advanced R Style Guide]: http://adv-r.had.co.nz/Style.html
[A guide for switching from base R to the _tidyverse]: http://www.significantdigits.org/2017/10/switching-from-base-r-to-tidyverse/
[R Graph Gallery _ Code Examples]: http://www.r-graph-gallery.com/
[Fundamentals of Data Visualization _Wilke_ 2018]: http://serialmentor.com/dataviz/index.html
[R Base Plots Wiki Reference Guide]: https://en.wikibooks.org/wiki/R_Programming/Graphics
[CRAN Task View _ Graphics _ Visualization]: https://cran.r-project.org/web/views/Graphics.html
[R Graphical Parameters Cheatsheet by Flowingdata.com]: http://flowingdata.com/2015/03/17/r-cheat-sheet-for-graphical-parameters/
[R Color Guide]: http://www.stat.columbia.edu/~tzheng/files/Rcolor.pdf
[colourpicker]: https://github.com/daattali/colourpicker/
[ggplot2 colour guide]: http://sape.inf.usi.ch/quick-reference/ggplot2/colour
[by Andrew Whitby]: https://andrewwhitby.com/2017/09/18/multi-color-text-ggplot2/
[Visuelle Data]: https://visuelledata.netlify.com/2017/10/20/2017-10-20-colorful-plot-annotations/
[R HTML Widgets Gallery]: http://gallery.htmlwidgets.org/
[plotly]: https://plot.ly/r/
[d3heatmap]: https://github.com/rstudio/d3heatmap
[DT]: http://rstudio.github.io/DT/
[DiagrammeR]: http://rich-iannone.github.io/DiagrammeR/
[dygraphs]: http://rstudio.github.io/dygraphs
[formattable]: http://renkun.me/formattable/
[ggvis]: http://ggvis.rstudio.com/
[Highcharter]: http://jkunst.com/highcharter/
[leaflet]: http://rstudio.github.io/leaflet/
[metricsgraphics]: http://hrbrmstr.github.io/metricsgraphics/
[networkD3]: http://christophergandrud.github.io/networkD3/
[scatterD3]: https://github.com/juba/scatterD3
[rbokeh]: http://hafen.github.io/rbokeh
[rCharts]: http://ramnathv.github.io/rCharts/
[rcdimple]: https://github.com/timelyportfolio/rcdimple
[rglwidget]: http://cran.at.r-project.org/web/packages/rglwidget/index.html
[threejs]: https://github.com/bwlewis/rthreejs
[visNetwork]: http://dataknowledge.github.io/visNetwork
[wordcloud2]: https://github.com/Lchiffon/wordcloud2
[timevis]: https://daattali.com/shiny/timevis-demo/
[Code examples of top-50 ggplot2 visualizations]: http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html
[ggplot2 Cheatsheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/data-visualization-2.1.pdf
[ggplot2 Quick Reference Guide]: http://sape.inf.usi.ch/quick-reference/ggplot2/geom
[ggplot2 Code Snippets]: http://www.computerworld.com/article/2935394/business-intelligence/my-ggplot2-cheat-sheet-search-by-task.html
[ggplot2 Code Snippets 2]: http://zevross.com/blog/2014/08/04/beautiful-plotting-in-r-a-ggplot2-cheatsheet-3/
[A practical introduction with R and ggplot2 _Healy_ 2017]: http://socviz.co/index.html#preface
[Data Vizualization_ A practical introduction _Healy_ 2018]: http://vissoc.co/
[Hitchhiker_s Guide to ggplot2 in R _Burchell _ Vargas_ 2016]: https://leanpub.com/hitchhikers_ggplot2
[Setting custom ggplot themes]: https://www.shanelynn.ie/themes-and-colours-for-r-ggplots-with-ggthemr/
[Creating custom_ reproducible color palettes]: https://drsimonj.svbtle.com/creating-corporate-colour-palettes-for-ggplot2
[Simon Jackson]: https://twitter.com/drsimonj
[Rearranging values within ggplot2 facets]: https://github.com/dgrtwo/drlib/blob/master/R/reorder_within.R
[ggplot2 extensions overview]: http://www.ggplot2-exts.org/gallery/?utm_content=buffer3c24b&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
[circlize]: http://zuguang.de/circlize_book/book/index.html
[trelliscopejs]: https://github.com/hafen/trelliscopejs
[ImageMagick]: http://imagemagick.org/
[Shiny Cheat Sheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/shiny.pdf
[More Shiny Resources by Rob Gilmore]: https://github.com/grabear/awesome-rshiny
[More Shiny Resources for Statistics by Yingjie Hu]: https://github.com/huyingjie/Awesome-shiny-apps-for-statistics
[Shiny Tutorial]: http://zevross.com/blog/2016/04/19/r-powered-web-applications-with-shiny-a-tutorial-and-cheat-sheet-with-40-example-apps/?utm_content=buffer608db&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
[Building Shiny apps _ an interactive tutorial]: https://deanattali.com/blog/building-shiny-apps-tutorial/
[R Regular Expression Cheatsheet by Lise Vaudor]: http://perso.ens-lyon.fr/lise.vaudor/Rfigures/Expressions_regulieres/regexp.png
[R Regular Expression Cheatsheet]: https://paulvanderlaken.files.wordpress.com/2017/08/r-regular-expression-cheetsheat.pdf
[Regular Expressions in R _ Part 1_ Introduction and base R functions]: https://paulvanderlaken.com/2017/10/03/regular-expressions-in-r-part-1-introduction-and-base-r-functions/
[R Regular Expressions by Jon M. Calder in swirl]: http://joncalder.co.za/Regular_Expressions/?utm_content=bufferdfcdb&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
[R Regular Expression Video Tutorial]: https://www.youtube.com/watch?v=q8SzNKib5-4
[Regular Expression Cheatsheet]: https://paulvanderlaken.files.wordpress.com/2017/08/davechild_regular-expressions.pdf
[Regular Expression Video Tutorial]: https://www.youtube.com/watch?v=NvHjYOilOf8
[Regular Expression Cheatsheet by OverAPI.com]: https://paulvanderlaken.files.wordpress.com/2017/08/overapi-regex-cheatsheet.png
[R Markdown Cheatsheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/rmarkdown-2.0.pdf
[R Markdown Reference Guide by RStudio]: https://www.rstudio.com/wp-content/uploads/2015/03/rmarkdown-reference.pdf
[R Markdown Basics]: http://rmarkdown.rstudio.com/authoring_basics.html
[Markdown Tutorial by RStudio]: https://rmarkdown.rstudio.com/lesson-1.html
[Markdown Gallery by RStudio]: https://rmarkdown.rstudio.com/gallery.html
[The _knitr_ book _Xie_ 2015]: https://github.com/yihui/knitr-book
[Creating slides with R Markdown _Video]: https://www.youtube.com/watch?v=gkyjTcpCITM
[Markdown Cheatsheet]: https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet
[blogdown_ Creating Websites with R Markdown _Xie_ Thomas_ _ Hill_ 2018]: https://bookdown.org/yihui/blogdown/
[blogdown_ tutorials]: https://blogdown-demo.rbind.io/
[huxtable]: https://github.com/hughjonesd/huxtable
[Tutorial_ Database Queries with R]: https://rviews.rstudio.com/2017/10/18/database-queries-with-r/
[Introduction to _sparklyr_ by DataCamp]: https://campus.datacamp.com/courses/introduction-to-spark-in-r-using-sparklyr/tools-of-the-trade-advanced-dplyr-usage
[dbplot]: https://github.com/edgararuiz/dbplot
[Functional Programming lecture by Duke University]: http://www2.stat.duke.edu/~cr173/Sta523_Fa17/functional.html
[Functional Programming_ _purrr_ tutorial by Jenny Bryan]: https://jennybc.github.io/purrr-tutorial/
[Writing Function in R by DataCamp.com]: https://www.datacamp.com/community/blog/writing-functions-in-r-from-hadley-charlotte-wickham
[Machine Learning with R_ An Irresponsibly Fast Tutorial by Will Stanton]: http://will-stanton.com/machine-learning-with-r-an-irresponsibly-fast-tutorial/
[CRAN Task View _ Machine Learning _ Statistical Learning]: https://cran.r-project.org/web/views/MachineLearning.html
[R Packages for Machine Learning]: https://github.com/josephmisiti/awesome-machine-learning#r
[Introduction to Data Science with R _Video]: https://www.youtube.com/watch?v=32o0DnuRjfg
[Course_ Introduction to R for Data Science _Microsoft]: https://www.edx.org/course/introduction-r-data-science-microsoft-dat204x-5
[Course_ Introduction to R for Data Science _FutureLearn]: https://www.futurelearn.com/courses/data-science
[Introduction to Statistical Learning _James_ Witten_ Hastie_ _ Tibshirani_ 2013]: http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Seventh%20Printing.pdf
[Course_ Introduction to Statistical Learning _Hastie _ Tibshirani_ 2014]: http://www.dataschool.io/15-hours-of-expert-machine-learning-videos/
[Data Science Live Book _Casas_ 2017]: https://livebook.datascienceheroes.com/
[R Programming for Data Science _Peng_ 2016]: https://leanpub.com/rprogramming
[R for Data Science _Grolemund _ Wickham_ 2017]: http://r4ds.had.co.nz/
[Elements of Statistical Learning _Hastie_ Tibshirani_ _ Friedman_ 2001]: https://web.stanford.edu/~hastie/Papers/ESLII.pdf
[Statistical Foundations of Machine Learning _Bontempi _ Taieb_ 2017]: https://www.otexts.org/sfml
[Machine Learning with R _Lantz_ 2013]: https://vk.com/doc168073_317718618?hash=90cd2a2976f079b1e7&dl=43db8b80daa2831cc1
[R Functions for Regression Analysis Cheatsheet by Vito Ricci]: https://cran.r-project.org/doc/contrib/Ricci-refcard-regression.pdf
[Regression Models for Data Science in R _Caffo_ 2015]: https://leanpub.com/regmods
[Applied Biostatistical Analyses using R _Cox_ 2017]: https://www.otexts.org/biostat
[Data Mining with Rattle and R_ The Art of Excavating Data for Knowledge Discovery _Williams_ 2011]: https://mineriaddatos.wikispaces.com/file/view/Data+Mining+With+Rattle+and+R_+The+Art+of+Excavating+Data+for+Knowledge+Discovery+-+Graham+Williams.pdf
[Machine Learning Algorithms R Implementation by Ajitesh Kumar]: http://vitalflux.com/cheat-sheet-10-machine-learning-algorithms-r-commands/
[R Data Mining Reference Card]: https://paulvanderlaken.files.wordpress.com/2017/08/r-data-mining-reference-card.pdf
[R Data Mining_ Examples _ Case Studies _Zhao_ 2015]: http://www.rdatamining.com/docs/r-and-data-mining-examples-and-case-studies
[Statistical modelling in R _Zhao_ 2015]: https://paulvanderlaken.files.wordpress.com/2017/08/rdatamining-introduction-slides.pdf
[RDataMining]: http://www.rdatamining.com/
[Predictive modelling in R]: http://topepo.github.io/caret/index.html
[Machine Learning with _caret_ cheat sheet by Max Kuhn]: https://github.com/rstudio/cheatsheets/raw/master/caret.pdf
[R _sparklyr_ cheat sheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/sparklyr.pdf
[Machine Learning modelling cheat sheet by Arnaud Amsellem]: https://github.com/rstudio/cheatsheets/raw/master/Machine%20Learning%20Modelling%20in%20R.pdf
[Machine Learning with _mlr_ cheat sheet by Aaron Coley]: https://github.com/rstudio/cheatsheets/raw/master/mlr.pdf
[Deep Learning with _keras_ cheat sheet by RStudio]: https://github.com/rstudio/cheatsheets/raw/master/keras.pdf
[R Interface to Keras]: https://keras.rstudio.com/
[Text Mining Tutorial]: http://www.rdatamining.com/examples/text-mining
[Tidy Text Mining _Silges _ Robinson_ 2017]: http://tidytextmining.com/
[Text Analysis with R for Students of Literature _Jockers_ 2014]: https://paulvanderlaken.files.wordpress.com/2017/08/quantitative-methods-in-the-humanities-and-social-sciences-matthew-l-jockers-auth-text-analysis-with-r-for-students-of-literature-springer-international-publishing-2014.pdf
[21 Recipes for Mining Twitter Data _Rudis_ 2017]: https://rud.is/books/21-recipes/
[Course_ Introduction to Text Analytics with R]: https://www.youtube.com/playlist?list=PL8eNk_zTBST8olxIRFoo0YeXxEOkYdoxi
[Course_ Twitter Text Mining and Social Network Analysis _Zhoa_ 2016]: https://paulvanderlaken.files.wordpress.com/2017/08/rdatamining-slides-twitter-analysis.pdf
[List of resources for NLP _ Text Mining by Stephen Thomas]: https://github.com/stepthom/text_mining_resources
[CRAN Task View _ Natural Language Processing]: https://cran.r-project.org/web/views/NaturalLanguageProcessing.html
[OpenNLP]: http://opennlp.sourceforge.net/
[Weka]: http://www.cs.waikato.ac.nz/ml/weka/
[WordNet]: http://wordnet.princeton.edu/
[CRAN Task View _ TimeSeries]: https://cran.r-project.org/web/views/TimeSeries.html
[R xts Cheatsheet]: https://paulvanderlaken.files.wordpress.com/2017/08/r-xts-cheatsheet.pdf
[Forecasting_ Principles and Practice _Hyndman _ Athanasopoulos_ 2017]: https://www.otexts.org/fpp2/
[A little book of R for time series _tutorial]: http://a-little-book-of-r-for-time-series.readthedocs.io/en/latest/src/timeseries.html
[Part 1]: http://www.business-science.io/timeseries-analysis/2017/07/02/tidy-timeseries-analysis.html
[Part 2]: http://www.business-science.io/timeseries-analysis/2017/07/23/tidy-timeseries-analysis-pt-2.html
[Part 3]: http://www.business-science.io/timeseries-analysis/2017/07/30/tidy-timeseries-analysis-pt-3.html
[Part 4]: http://www.business-science.io/timeseries-analysis/2017/08/30/tidy-timeseries-analysis-pt-4.html?utm_source=feedburner&utm_medium=twitter&utm_campaign=Feed%3A+business-science+%28www.business-science.io%29
[Business-Science.io]: http://www.business-science.io/
[CRAN Task View _ Survival]: https://cran.r-project.org/web/views/Survival.html
[R Survival Analysis Cheatsheet by Przemys_aw Biecek]: https://paulvanderlaken.files.wordpress.com/2017/08/survminer_cheatsheet.pdf
[survival]: https://cran.r-project.org/web/packages/survival/survival.pdf
[ggsurvplot _survminer]: https://cran.r-project.org/web/packages/survminer/index.html
[Making Maps with R _tutorial]: http://eriqande.github.io/rep-res-web/lectures/making-maps-with-R.html
[Importing OpenStreetMap data _tutorial]: http://r-spatial.org/2017/07/14/Large_scale_OSM_in_R.html
[Image featurization]: https://github.com/delange/image2image
[Introduction to Empirical Bayes _Robinson_]: https://gumroad.com/l/empirical-bayes
[CRAN Task View _ Bayesian Inference]: https://cran.r-project.org/web/views/Bayesian.html
[R Package Development Cheatsheet]: https://github.com/rstudio/cheatsheets/raw/master/package-development.pdf
[Mastering Software Development in R _Peng_ Kross_ _ Anderson_ 2017]: https://leanpub.com/msdr?utm_content=bufferaf023&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer
[Efficient R Programming _Gillespie _ Lovelace_ 2017]: https://csgillespie.github.io/efficientR/
[Happy Git and GitHub for the useR _Jenny Bryan_ 2017]: http://happygitwithr.com/
[RStudio Addins by Dean Attali]: https://github.com/daattali/addinslist
[R Help Mailing List]: https://stat.ethz.ch/mailman/listinfo/r-help
[R Seek]: http://rseek.org/
[R site search]: http://finzi.psych.upenn.edu/search.html
[Nabble]: http://r.789695.n4.nabble.com/
[R User Groups _ Conferences]: https://jumpingrivers.github.io/meetingsR/r-user-groups.html
[Stack Overflow]: https://stackoverflow.com/questions/tagged/r
[Cross Validated]: https://stats.stackexchange.com/
[CRAN Task Views]: https://cran.r-project.org/web/views/
[The R Journal]: https://journal.r-project.org/
[rstats]: https://twitter.com/search?q=%23Rstats&src=tyah
[RStudio]: https://twitter.com/rstudio
[Hadley Wickham]: https://twitter.com/hadleywickham
[Yihui Xie]: https://twitter.com/xieyihui
[Mara Averick]: https://twitter.com/dataandme
[Julia Silge]: https://twitter.com/juliasilge
[Jenny Bryan]: https://twitter.com/JennyBryan
[David Smith]: https://twitter.com/revodavid
[Hilary Parker]: https://twitter.com/hspter
[R-bloggers]: https://twitter.com/Rbloggers
[R Users Psychology]: https://www.facebook.com/groups/346735129027556/
[Ben Lambert]: https://www.youtube.com/user/SpartacanUsuals
[Roger Peng]: https://www.youtube.com/user/rdpeng
[rstats 1]: https://www.reddit.com/r/rstats/
[rstudio]: https://www.reddit.com/r/RStudio/
[statistics]: https://www.reddit.com/r/statistics/
[machinelearning]: https://www.reddit.com/r/MachineLearning/
[dataisbeautiful]: https://www.reddit.com/r/dataisbeautiful/
[http_adamleerich.com]: http://adamleerich.com/
[http_njtierney.github.io]: http://njtierney.github.io/
[https_trinkerrstuff.wordpress.com]: https://trinkerrstuff.wordpress.com/
[https_rollingyours.wordpress.com]: https://rollingyours.wordpress.com/
[https_www.r-statistics.com]: https://www.r-statistics.com/
[https_beckmw.wordpress.com]: https://beckmw.wordpress.com/
[http_rgraphgallery.blogspot.com]: http://rgraphgallery.blogspot.com/
[http_onertipaday.blogspot.com]: http://onertipaday.blogspot.com/
[https_learnr.wordpress.com]: https://learnr.wordpress.com/
[http_padamson.github.io]: http://padamson.github.io/
[http_www.r-datacollection.com_blog]: http://www.r-datacollection.com/blog/
[http_www.thertrader.com]: http://www.thertrader.com/
[https_fronkonstin.com]: https://fronkonstin.com/
[https_nicercode.github.io]: https://nicercode.github.io/
[http_www.rblog.uni-freiburg.de]: http://www.rblog.uni-freiburg.de/
[https_advanceddataanalytics.net]: https://advanceddataanalytics.net/
[http_r4stats.com_blog]: http://r4stats.com/blog/
[http_blog.revolutionanalytics.com]: http://blog.revolutionanalytics.com/
[http_www.r-bloggers.com]: http://www.r-bloggers.com/
[http_kbroman.org_blog]: http://kbroman.org/blog/
[https_juliasilge.com_blog]: https://juliasilge.com/blog/
[http_andrewgelman.com]: http://andrewgelman.com/
[http_www.statsblogs.com_author_eric-cai-the-chemical-statistician]: http://www.statsblogs.com/author/eric-cai-the-chemical-statistician/
[https_www.statmethods.net]: https://www.statmethods.net/
[http_www.stats-et-al.com_search_label_R]: http://www.stats-et-al.com/search/label/R
[R Jobs on StackOverflow.com]: https://stackoverflow.com/jobs?sort=i&q=R
[R Jobs on R-users.com]: https://www.r-users.com/
[Jobs on Kaggle]: https://www.kaggle.com/jobs