**by Stack Overflow Community**

DescriptionTable of ContentsDetailsHashtagsReport an issue ### Book Description

R is a programming language and free software environment for statistical computing and graphics. It is an unofficial and free R ebook created for educational purposes. All the content is extracted from Stack Overflow Documentation, which is written by many hardworking individuals at Stack Overflow. ### Table of Contents

### Book Details

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This open book is licensed under a Creative Commons License (CC BY-SA). You can download Learning R ebook for free in PDF format (10.2 MB).

Chapter 1

Getting started with R Language

Chapter 2

*apply family of functions (functionals)

Chapter 3

.Rprofile

Chapter 4

Aggregating data frames

Chapter 5

Analyze tweets with R

Chapter 6

ANOVA

Chapter 7

Arima Models

Chapter 8

Arithmetic Operators

Chapter 9

Bar Chart

Chapter 10

Base Plotting

Chapter 11

Bibliography in RMD

Chapter 12

boxplot

Chapter 13

caret

Chapter 14

Classes

Chapter 15

Cleaning data

Chapter 16

Code profiling

Chapter 17

Coercion

Chapter 18

Color schemes for graphics

Chapter 19

Column wise operation

Chapter 20

Combinatorics

Chapter 21

Control flow structures

Chapter 22

Creating packages with devtools

Chapter 23

Creating reports with RMarkdown

Chapter 24

Creating vectors

Chapter 25

Data acquisition

Chapter 26

Data frames

Chapter 27

data.table

Chapter 28

Date and Time

Chapter 29

Date-time classes (POSIXct and POSIXlt)

Chapter 30

Debugging

Chapter 31

Distribution Functions

Chapter 32

dplyr

Chapter 33

Expression: parse + eval

Chapter 34

Extracting and Listing Files in Compressed Archives

Chapter 35

Factors

Chapter 36

Fault-tolerant/resilient code

Chapter 37

Feature Selection in R - Removing Extraneous Features

Chapter 38

Formula

Chapter 39

Fourier Series and Transformations

Chapter 40

Functional programming

Chapter 41

Generalized linear models

Chapter 42

Get user input

Chapter 43

ggplot2

Chapter 44

GPU-accelerated computing

Chapter 45

Hashmaps

Chapter 46

heatmap and heatmap.2

Chapter 47

Hierarchical clustering with hclust

Chapter 48

Hierarchical Linear Modeling

Chapter 49

I/O for database tables

Chapter 50

I/O for foreign tables (Excel, SAS, SPSS, Stata)

Chapter 51

I/O for geographic data (shapefiles, etc.)

Chapter 52

I/O for raster images

Chapter 53

I/O for R's binary format

Chapter 54

Implement State Machine Pattern using S4 Class

Chapter 55

Input and output

Chapter 56

Inspecting packages

Chapter 57

Installing packages

Chapter 58

Introduction to Geographical Maps

Chapter 59

Introspection

Chapter 60

JSON

Chapter 61

Linear Models (Regression)

Chapter 62

Lists

Chapter 63

lubridate

Chapter 64

Machine learning

Chapter 65

Matrices

Chapter 66

Meta: Documentation Guidelines

Chapter 67

Missing values

Chapter 68

Modifying strings by substitution

Chapter 69

Natural language processing

Chapter 70

Network analysis with the igraph package

Chapter 71

Non-standard evaluation and standard evaluation

Chapter 72

Numeric classes and storage modes

Chapter 73

Object-Oriented Programming in R

Chapter 74

Parallel processing

Chapter 75

Pattern Matching and Replacement

Chapter 76

Performing a Permutation Test

Chapter 77

Pipe operators (%>% and others)

Chapter 78

Pivot and unpivot with data.table

Chapter 79

Probability Distributions with R

Chapter 80

Publishing

Chapter 81

R code vectorization best practices

Chapter 82

R in LaTeX with knitr

Chapter 83

R Markdown Notebooks (from RStudio)

Chapter 84

R memento by examples

Chapter 85

Random Forest Algorithm

Chapter 86

Random Numbers Generator

Chapter 87

Randomization

Chapter 88

Raster and Image Analysis

Chapter 89

Rcpp

Chapter 90

Reading and writing strings

Chapter 91

Reading and writing tabular data in plain-text files (CSV, TSV, etc.)

Chapter 92

Recycling

Chapter 93

Regular Expression Syntax in R

Chapter 94

Regular Expressions (regex)

Chapter 95

Reproducible R

Chapter 96

Reshape using tidyr

Chapter 97

Reshaping data between long and wide forms

Chapter 98

RESTful R Services

Chapter 99

RMarkdown and knitr presentation

Chapter 100

RODBC

Chapter 101

roxygen2

Chapter 102

Run-length encoding

Chapter 103

Scope of variables

Chapter 104

Set operations

Chapter 105

Shiny

Chapter 106

Solving ODEs in R

Chapter 107

Spark API (SparkR)

Chapter 108

spatial analysis

Chapter 109

Speeding up tough-to-vectorize code

Chapter 110

Split function

Chapter 111

sqldf

Chapter 112

Standardize analyses by writing standalone R scripts

Chapter 113

String manipulation with stringi package

Chapter 114

strsplit function

Chapter 115

Subsetting

Chapter 116

Survival analysis

Chapter 117

Text mining

Chapter 118

The character class

Chapter 119

The Date class

Chapter 120

The logical class

Chapter 121

tidyverse

Chapter 122

Time Series and Forecasting

Chapter 123

Updating R and the package library

Chapter 124

Updating R version

Chapter 125

Using pipe assignment in your own package %<>%: How to ?

Chapter 126

Using texreg to export models in a paper-ready way

Chapter 127

Variables

Chapter 128

Web Crawling in R

Chapter 129

Web scraping and parsing

Chapter 130

Writing functions in R

Chapter 131

xgboost

Subject

Computer Science

Publisher

RIP Tutorial

Published

2019

Pages

619

Edition

1

Language

English

PDF Size

10.2 MB

License

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