R Notes for Professionals
by Stack Overflow Community
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Book Description
The R Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow.This open book is licensed under a Creative Commons License (CC BY-SA). You can download R Notes for Professionals ebook for free in PDF format (6.6 MB).
Table of Contents
Chapter 1
Getting started with R Language
Chapter 2
Variables
Chapter 3
Arithmetic Operators
Chapter 4
Matrices
Chapter 5
Formula
Chapter 6
Reading and writing strings
Chapter 7
String manipulation with stringi package
Chapter 8
Classes
Chapter 9
Lists
Chapter 10
Hashmaps
Chapter 11
Creating vectors
Chapter 12
Date and Time
Chapter 13
The Date class
Chapter 14
Date-time classes (POSIXct and POSIXlt)
Chapter 15
The character class
Chapter 16
Numeric classes and storage modes
Chapter 17
The logical class
Chapter 18
Data frames
Chapter 19
Split function
Chapter 20
Reading and writing tabular data in plain-text files (CSV, TSV, etc.)
Chapter 21
Pipe operators (%>% and others)
Chapter 22
Linear Models (Regression)
Chapter 23
data.table
Chapter 24
Pivot and unpivot with data.table
Chapter 25
Bar Chart
Chapter 26
Base Plotting
Chapter 27
boxplot
Chapter 28
ggplot2
Chapter 29
Factors
Chapter 30
Pattern Matching and Replacement
Chapter 31
Run-length encoding
Chapter 32
Speeding up tough-to-vectorize code
Chapter 33
Introduction to Geographical Maps
Chapter 34
Set operations
Chapter 35
tidyverse
Chapter 36
Rcpp
Chapter 37
Random Numbers Generator
Chapter 38
Parallel processing
Chapter 39
Subsetting
Chapter 40
Debugging
Chapter 41
Installing packages
Chapter 42
Inspecting packages
Chapter 43
Creating packages with devtools
Chapter 44
Using pipe assignment in your own package %<>%: How to ?
Chapter 45
Arima Models
Chapter 46
Distribution Functions
Chapter 47
Shiny
Chapter 48
spatial analysis
Chapter 49
sqldf
Chapter 50
Code profiling
Chapter 51
Control flow structures
Chapter 52
Column wise operation
Chapter 53
JSON
Chapter 54
RODBC
Chapter 55
lubridate
Chapter 56
Time Series and Forecasting
Chapter 57
strsplit function
Chapter 58
Web scraping and parsing
Chapter 59
Generalized linear models
Chapter 60
Reshaping data between long and wide forms
Chapter 61
RMarkdown and knitr presentation
Chapter 62
Scope of variables
Chapter 63
Performing a Permutation Test
Chapter 64
xgboost
Chapter 65
R code vectorization best practices
Chapter 66
Missing values
Chapter 67
Hierarchical Linear Modeling
Chapter 68
*apply family of functions (functionals)
Chapter 69
Text mining
Chapter 70
ANOVA
Chapter 71
Raster and Image Analysis
Chapter 72
Survival analysis
Chapter 73
Fault-tolerant/resilient code
Chapter 74
Reproducible R
Chapter 75
Fourier Series and Transformations
Chapter 76
.Rprofile
Chapter 77
dplyr
Chapter 78
caret
Chapter 79
Extracting and Listing Files in Compressed Archives
Chapter 80
Probability Distributions with R
Chapter 81
R in LaTeX with knitr
Chapter 82
Web Crawling in R
Chapter 83
Creating reports with RMarkdown
Chapter 84
GPU-accelerated computing
Chapter 85
heatmap and heatmap.2
Chapter 86
Network analysis with the igraph package
Chapter 87
Functional programming
Chapter 88
Get user input
Chapter 89
Spark API (SparkR)
Chapter 90
Meta: Documentation Guidelines
Chapter 91
Input and output
Chapter 92
I/O for foreign tables (Excel, SAS, SPSS, Stata)
Chapter 93
I/O for database tables
Chapter 94
I/O for geographic data (shapefiles, etc.)
Chapter 95
I/O for raster images
Chapter 96
I/O for R's binary format
Chapter 97
Recycling
Chapter 98
Expression: parse + eval
Chapter 99
Regular Expression Syntax in R
Chapter 100
Regular Expressions (regex)
Chapter 101
Combinatorics
Chapter 102
Solving ODEs in R
Chapter 103
Feature Selection in R -- Removing Extraneous Features
Chapter 104
Bibliography in RMD
Chapter 105
Writing functions in R
Chapter 106
Color schemes for graphics
Chapter 107
Hierarchical clustering with hclust
Chapter 108
Random Forest Algorithm
Chapter 109
RESTful R Services
Chapter 110
Machine learning
Chapter 111
Using texreg to export models in a paper-ready way
Chapter 112
Publishing
Chapter 113
Implement State Machine Pattern using S4 Class
Chapter 114
Reshape using tidyr
Chapter 115
Modifying strings by substitution
Chapter 116
Non-standard evaluation and standard evaluation
Chapter 117
Randomization
Chapter 118
Object-Oriented Programming in R
Chapter 119
Coercion
Chapter 120
Standardize analyses by writing standalone R scripts
Chapter 121
Analyze tweets with R
Chapter 122
Natural language processing
Chapter 123
R Markdown Notebooks (from RStudio)
Chapter 124
Aggregating data frames
Chapter 125
Data acquisition
Chapter 126
R memento by examples
Chapter 127
Updating R version
Book Details
Title
R Notes for Professionals
Subject
Computer Science
Publisher
GoalKicker
Published
2018
Pages
474
Edition
1
Language
English
PDF Size
6.6 MB
License
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