Section 1
##### What is R?

Section 2
##### Basic Operations in R

7

Expressions: Basic Idea

8

Constant Values: Numeric and Non-Numeric

9

Arithmetic: Operations and BODMAS

10

Conditions: Equality, Greater Than, Less Than, etc

11

Function Calls: Introduction to R Functions

12

Symbols and Assignment

13

Keywords: NA, Inf, NaN, NULL, TRUE, FALSE

14

Naming a Variable: Generally accepted conventions

Section 3
##### Data Types and Data Structures

Section 4
##### Subsetting in R

17

Vector Subsetting

18

c() function: Creation of Vectors

19

Using rep() and seq() functions

20

Using factor() to covert vectors to factors

21

Using data.frame() to create data frames

22

Meta data access: dimnames(), rownames(), colnames()

23

Using matrix() to create matrices

24

Using array() to create arrays

25

Subsetting data frames: row subset, column subset, using subset() function

26

Assigning to a subset

27

Using is.na() to detect NA

28

Subsetting factors

Section 5
##### Additional Topics on Data structures

29

The recycling rule: Uneven arithmetic operation on vectors

30

Type coercion: Character to Numeric

31

Automatic Type coercion

32

Coercing factors: Using as.factor() function

33

Changing factor levels

34

Attributes: attribute(), attr(), names() functions

35

Classes: Idea of OOP in R

36

Dates: As a special class

37

Formulas: As a special class

38

Exploring Objects: summary(), str(), dim() functions

39

Generic functions

Section 6
##### Data Import and Export

40

Text formats: Reading Delimited Files

41

read.table() function

42

Using read.fwf() function for fixed width files

43

Using readLines() for reading lines

44

Using write.csv() function to store data as CSV files

45

Reading Excel file: Package XLConnect

46

Reading SPSS file: Package Foreign

47

Reading SAS data file: Package sas7bdat

48

Database connection: The ideas of ODBC connecting in Windows

49

RODBC package: Create and Query database from R

50

Basic SQL

Section 7
##### Control Structures and User Defined Functions

51

Conditional Statements

52

If statement: The Structure

53

If Else statement: The Structure

54

Ifelse() function

55

Iteration

56

The for loop

57

The while loop

58

The repeat statement

59

lapply() function

60

sapply() function

61

apply() function

62

User defined function

63

Variable scooping: Global and Local Variables

64

Using user defined functions inside function definition

Section 8
##### Data Visualisation: Charting with R

65

The plot function

66

plot.new() function: Generating new plot object

67

plot.window() function: Creating window

68

points() function: Plotting points

69

axis() function: Generating Axis

70

box() function: Creating enclosure

71

title() function: Assigning title

72

par() function: Fixing plotting parameters

73

lines() function: Adding connector lines

74

Multi figure layout: Creating multiple charts in the same window

75

hist() function: Plotting histograms

76

Kernel Density Plot: The non-parametric probability distribution

77

Comparing Groups via Kernel Density: Comparing two different probability distributions

78

Simple Bar Plot: Visualizing categorical data

79

Staked Bar Plot: Understating category composition

80

Grouped Bar Plot

81

Line Charts

82

Pie Charts

83

Boxplots: Understanding data distributions and outliers

84

Using Google Chart Tools with R (Package googleVis)

85

Geo Charts

86

Motion Charts

Section 9
##### Visualisation on R using Google Vis

Section 10
##### Visualization in R using GGPLOT2

Graphical User Interface of R

The GUI (Graphical User Interface) that comes with R is widely used. But for different needs we can use different GUIs.

• RStudio: This is the widely used GUI/ IDE (Integrated Development Environment) for R. In our course we will be using this software. RStudio includes a wide range of productivity enhancing features and runs on all major platforms

Features include:

• Customizable workbench with all of the tools required to work with R in one place

• Syntax highlighting editor with code completion.

• Execute code directly from the source editor (line, selection, or file)

• Searchable history.

• Retrieve previous commands.

• Keyboard shortcuts.

• Easy installation of new packages

• Runs on all major platforms and can also be run as a server, enabling multiple users to access the RStudio IDE using a web browser

• Integrated help functionality.

• RStudio works with the manipulate package to add interactive capabilities to standard R plots.

Features include:

• Extensive collection of R packages.

• File Inputs: CSV, TXT, Excel, R Dataset, etc

• Statistics: Min, Max, Quartiles, Mean, St Dev, Missing, Sum, Variance, etc

• Statistical tests: Correlation, t-Test, F-Test, and Wilcoxon Signed Rank.

• Clustering: KMeans, Clara, Hierarchical, and BiCluster.

• Modelling: Decision Trees, Random Forests, Logistic Regression, etc

• Evaluation: Confusion Matrix, Risk Charts, ROC

• Charts: Box Plot, Histogram, Correlations, Dendrograms, Cumulative, etc