Preface
1
What is R?
1.1
Why should we learn R?
1.2
Installing R and RStudio on Windows
1.3
RStudio GUI/IDE
1.4
Installing Packages
1.5
Getting Help
1.6
Task Views in R-Introduction & Installation
1.7
R core packages
1.8
Example-1 Hello R!
2
R Data Types and Data Structures
2.1
Data Types
2.1.1
Double
2.1.2
Integer
2.1.3
Logical
2.1.4
Character
2.1.5
Factor
2.1.6
Date & Time
2.2
Data Structures in R
2.2.1
Vector
2.2.2
Matrices
2.2.3
Arrays
2.2.4
Data Frames
2.2.5
Lists
2.3
Data Import/Export in R
2.3.1
Reading Data from a Text File
2.3.2
Reading Data from CSV files
2.3.3
Reading from Excel Files
2.3.4
Reading from Data Files from other Statistical Systems
2.3.5
Importing Data using RStudio
3
R Programming - Short Introduction
3.1
Programming Control Flow
3.1.1
if-else Conditional Statements
3.1.2
Loops
3.1.3
\(\mathtt{while}\)
loop
3.1.4
\(\mathtt{repeat}\)
loop
3.2
Functions in R
4
Data Exploration
4.1
Data Preprocessing
4.1.1
Extracting Data
4.1.2
Combining Data Frames
4.1.3
Sub setting and Logical Data Selection
4.2
Data Transformation from Wide to Long (or vice versa)
4.3
Summary Statistics
4.3.1
Example-Descriptive Statistics of Stock Returns
5
Graphics in R (Part-I)
5.1
Basic Plots in R
5.1.1
Scatter Plot
5.1.2
Line Plot
5.1.3
Bar Plot
5.1.4
Pie Chart
5.1.5
Scatter Plot
5.2
R Graphical Parameters
5.3
Introduction to ggplot2
5.3.1
\(\mathtt{qplot}\)
5.3.2
Layered graphics using
\(\mathtt{ggplot}\)
5.3.3
Arranging plots using gridExtra
6
Graphics in R (Part-II)
6.1
Interactive Plots using Plotly
6.2
Animation using gganimate
6.3
Plot Maps
7
Final Words
References
R for Research
Chapter 2
R Data Types and Data Structures
When human judgement and big data intersect there are some funny things that happen.
-Nate Silver