Learning R

by Stack Overflow Community

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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.

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).

Table of Contents

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
 

Book Details

Subject
Computer Science
Publisher
RIP Tutorial
Published
2019
Pages
619
Edition
1
Language
English
PDF Size
10.2 MB
License
CC BY-SA

Book Hashtags

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