R language eBook for professionals

Download free R language tutorial course in PDF, training file in 127 chapters and 475 pages. Free unaffiliated ebook created from Stack OverFlow contributor.

Table of contents

  • About
  • Getting started with R Language
  • Installing R
  • Hello World!
  • Getting Help
  • Interactive mode and R scripts
  • Variables
  • Variables, data structures and basic Operations
  • Arithmetic Operators
  • Range and addition
  • Addition and subtraction
  • Matrices
  • Creating matrices
  • Formula
  • The basics of formula
  • Reading and writing strings
  • Printing and displaying strings
  • Capture output of operating system command
  • Reading from or writing to a ?le connection
  • String manipulation with stringi package
  • Count pattern inside string
  • Duplicating strings
  • Paste vectors
  • Splitting text by some ?xed pattern
  • Classes
  • Inspect classes
  • Vectors and lists
  • Vectors
  • Lists
  • Introduction to lists
  • Quick Introduction to Lists
  • Serialization: using lists to pass information
  • Hashmaps
  • Environments as hash maps
  • package:hash
  • package:listenv
  • Creating vectors
  • Vectors from build in constants: Sequences of letters & month names
  • Creating named vectors
  • Sequence of numbers
  • seq()
  • Vectors
  • Expanding a vector with the rep() function
  • Date and Time
  • Current Date and Time
  • Variables
  • Matrices
  • Reading and writing strings
  • Classes
  • Hashmaps
  • Date and Time
  • Date-time classes (POSIXct and POSIXlt)
  • Numeric classes and storage modes
  • Data frames
  • Reading and writing tabular data in plain-text files (CSV, TSV, etc.)
  • Linear Models (Regression)
  • Pivot and unpivot with data.table
  • Base Plotting
  • ggplot2
  • Pattern Matching and Replacement
  • Speeding up tough-to-vectorize code
  • Set operations
  • Rcpp
  • Parallel processing
  • Debugging
  • Inspecting packages
  • Using pipe assignment in your own package %<>%: How to ?
  • Distribution Functions
  • spatial analysis
  • Code profiling
  • Column wise operation
  • RODBC
  • Time Series and Forecasting
  • Web scraping and parsing
  • Reshaping data between long and wide forms
  • Scope of variables
  • Performing a Permutation Test
  • xgboost
  • R code vectorization best practices
  • Missing values
  • Hierarchical Linear Modeling
  • *apply family of functions (functionals)
  • Text mining
  • ANOVA
  • Raster and Image Analysis
  • Survival analysis
  • Fault-tolerant/resilient code
  • Reproducible R
  • Fourier Series and Transformations
  • .Rprofile
  • dplyr
  • caret
  • Extracting and Listing Files in Compressed Archives
  • Probability Distributions with R
  • R in LaTeX with knitr
  • Web Crawling in R
  • Creating reports with RMarkdown
  • GPU-accelerated computing
  • heatmap and heatmap.2
  • Network analysis with the igraph package
  • Functional programming
  • Get user input
  • Spark API (SparkR)
  • Meta: Documentation Guidelines
  • Input and output
  • I/O for foreign tables (Excel, SAS, SPSS, Stata)
  • I/O for database tables
  • I/O for geographic data (shapefiles, etc.)
  • I/O for raster images
  • I/O for R's binary format
  • Recycling
  • Expression: parse + eval
  • Regular Expression Syntax in R
  • Regular Expressions (regex)
  • Combinatorics
  • Solving ODEs in R
  • Feature Selection in R -- Removing Extraneous Features
  • Bibliography in RMD
  • Writing functions in R
  • Color schemes for graphics
  • Hierarchical clustering with hclust
  • Random Forest Algorithm
  • RESTful R Services
  • Machine learning
  • Using texreg to export models in a paper-ready way
  • Publishing
  • Implement State Machine Pattern using S4 Class
  • Reshape using tidyr
  • Modifying strings by substitution
  • Non-standard evaluation and standard evaluation
  • Randomization
  • Object-Oriented Programming in R
  • Coercion
  • Standardize analyses by writing standalone R scripts
  • Analyze tweets with R
  • Natural language processing
  • R Markdown Notebooks (from RStudio)
  • Aggregating data frames
  • Data acquisition
  • R memento by examples
  • Updating R version

It is a free R language ebook created for beginners. The content is extracted from Stack Overflow pltaform, which is written by many R language developers and contributors.

The content is released under Creative Commons BY-SA

Size : 6.47 MB
File type : pdf
Downloads: 97
Created: 2019-04-30

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