R Notes for Professionals

by GoalKicker

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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

Subject
Computer Science
Publisher
GoalKicker
Published
2018
Pages
474
Edition
1
Language
English
PDF Size
6.6 MB
License
CC BY-SA

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