R Data Science Tutorials

This repo contains a curated list of R tutorials and packages for Data Science, NLP and Machine Learning. This also serves as a reference guide for several common data analysis tasks.

Curated list of Python tutorials for Data Science, NLP and Machine Learning.
Learning R
 Online Courses
 Free resources for learning R
 R for Data Science  Hadley Wickham
 Advanced R  Hadley Wickham
 swirl: Learn R, in R
 Data Analysis and Visualization Using R
 MANY R PROGRAMMING TUTORIALS
 A Handbook of Statistical Analyses Using R, Find Other Chapters
 **Cookbook for R **
 Learning R in 7 simple steps
More Resources
 AwesomeR Repository on GitHub
 R Reference Card: Cheatsheet
 R bloggers: blog aggregator
 R Resources on GitHub
 Awesome R resources
 Data Mining with R
 Rob J Hyndman's R Blog
 Simple R Tricks and Tools (Video)
 RStudio GitHub Repo
 Tidying Messy Data in R Video
 Baseball Research with R
 600 websites about R
 Implementation of 17 classification algorithms in R
 Cohort Analysis and LifeCycle Grids mixed segmentation with R
 Using R and Tableau
 COMPREHENSIVE VIEW ON CRAN PACKAGES
 Using R for Statistical Tables and Plotting Distributions
 Extended Model Formulas in R: Multiple Parts and Multiple Responses
 R vs Python: head to head data analysis
 R for Data Science: Hadley Wickham's Book
 R Study Group at UPenn
 ProgramDefined Functions in R
Important Questions
 In R, why is bracket better than
subset
?  Subsetting Data in R
 Vectorization in R: Why?
 Quickly reading very large tables as dataframes in R
 Using R to show data
 How can I view the source code for a function?
 How to make a great R reproducible example?
 R Grouping functions: sapply vs. lapply vs. apply. vs. tapply vs. by vs. aggregate
 Tricks to manage the available memory in an R session
 Difference between Assignment operators '=' and '<' in R
 What is the difference between require() and library()?
 How can I view the source code for a function?
 How can I change fonts for graphs in R?
Common DataFrame Operations
 Create an empty data.frame
 Sort a dataframe by column(s)
 Merge/Join data frames (inner, outer, left, right)
 Drop data frame columns by name
 Remove rows with NAs in data.frame
 Quickly reading very large tables as dataframes in R
 Drop factor levels in a subsetted data frame
 Convert R list to data frame
 Convert data.frame columns from factors to characters
 Extracting specific columns from a data frame
Caret Package in R
 Ensembling Models with caret
 Model Training and Tuning
 Caret Model List
 relationshipbetweendatasplittingandtraincontrol
 Specify model generation parameters
 Tutorial, Paper
 Ensembling models with R, Ensembling Regression Models in R
R Cheatsheets
 Data Wrangling in R
 ggplot2 Cheatsheet
 Shiny Cheatsheet
 devtools Cheatsheet
 markdown Cheatsheet, reference
 Data Exploration Cheatsheet
Reference Slides
 Awesome R Reference Card
 Association Rule Mining
 Time Series Analysis
 Data Exploration and Visualisation
 Regression and Classification
 Text Mining on Twitter Data
Using R for Multivariate Analysis
 Little Book of R for Multivariate Analysis!
 THE FREQPARCOORD PACKAGE FOR MULTIVARIATE VISUALIZATION
 Use of freqparcoord for Regression Diagnostics
Time Series Analysis
 Time Series Forecasting (Online Book)
 A Little Book of Time Series Analysis in R
 Quick R: Time Series and Forecasting
 Components of Time Series Data
 Unobserved Component Models using R
 The HoltWinters Forecasting Method
 CRAN Task View: Time Series Analysis
Bayesian Inference
Machine Learning using R
 Machine Learning with R
 Using R for Multivariate Analysis (Online Book)
 CRAN Task View: Machine Learning & Statistical Learning
 Machine Learning Using R (Online Book)
 Linear Regression and Regularization Code
 Cheatsheet
 Multinomial and Ordinal Logistic Regression in R
 Evaluating Logistic Regression Models in R
Neural Networks in R
 Visualizing Neural Nets in R
 nnet package
 Fitting a neural network in R; neuralnet package
 Neural Networks with R – A Simple Example
 NeuralNetTools 1.0.0 now on CRAN
 Introduction to Neural Networks in R
 Step by Step Neural Networks using R
 R for Deep Learning
 Neural Networks using package neuralnet, Paper
Sentiment Analysis
 Different Approaches
 Sentiment analysis with machine learning in R
 First shot: Sentiment Analysis in R
 qdap package, code
 sentimentr package
 tm.plugin.sentiment package
 Packages other than sentiment
 Sentiment Analysis and Opinion Mining
 tm_term_score
 vaderSentiment Paper, vaderSentiment code
Imputation in R
 Imputation in R
 Imputation with Random Forests
 How to Identify and Impute Multiple Missing Values using R
 MICE
NLP and Text Mining in R
 What algorithm I need to find ngrams?
 NLP R Tutorial
 Introduction to the tm Package Text Mining in R
 Adding stopwords in R tm
 Text Mining
 Word Stemming in R
 Classification of Documents using Text Mining Package “tm”
 Text mining tools techniques and applications
 Text Mining: Overview,Applications and Issues
 Text Mining pdf
 Text Mining Another pdf
 Good PPT
 Scraping Twitter and Web Data Using R
Visualisation in R
 ggplot2 tutorial
 SHINY EXAMPLES
 Top 50 ggplot2 Visualizations
 Comprehensive Guide to Data Visualization in R
 Interactive visualizations with R – a minireview
 Beginner's guide to R: Painless data visualization
 Data Visualization in R with ggvis
 Multiple Visualization Articles in R
Statistics with R
 Using R for Biomedical Statistics (Online Book)
 Elementary Statistics with R
 A Handson Introduction to Statistics with R
 Quick R: Basic Statistics
 Quick R: Descriptive Statistics
 Explore Statistics with R  edX
Useful R Packages
 TIDY DATA HADLEY PAPER
 Package ‘tidyr’: tidyr is an evolution of reshape2. It's design specifically for data tidying (not general reshaping or aggregating) and works well with dplyr data pipelines.
 BROOM
 plyr, stringr, reshape2 tutorial Video, CODE
 dplyr
 ggplot2
 A speed test comparison of plyr, data.table, and dplyr
 data.table
 Other Packages
 Package 'e1071'
 Package ‘AppliedPredictiveModeling’
 Package ‘stringr’: stringr is a set of simple wrappers that make R's string functions more consistent, simpler and easier to use.
 Package ‘stringdist’: Implements an approximate string matching version of R's native 'match' function. Can calculate various string distances based on edits (dameraulevenshtein, hamming, levenshtein, optimal sting alignment), qgrams or heuristic metrics
 Package ‘FSelector’: This package provides functions for selecting attributes from a given dataset
 Ryacas – an R interface to the yacas computer algebra system
 Scatterplot3d – an R package for Visualizing Multivariate Data
 tm.plugin.webmining intro
 Solving Differential Equations in R  ODE examples
 Structural Equation Modeling With the sem Package in R
 prettyScree  prettyGraphs