LEC. 1: INTRODUCTION TO R PROGRAMMING -PART I

Instructor: SANG-HOON CHO

DEPT. OF STATISTICS AND ACTUARIAL SCIENCES

Soongsil University

1 / 27

1. Getting Started

Why use R?

Public domain (a so called GNU) project

Implementation of the commercial S language and environment developed at Bell Lab. byJohn Chambers and colleagues

Freeware and lots of help available online

Powerful language and environment for statistical computing and graphics

User-friendly and Objective Oriented Programming(OOP)

Popular for big data analysis

2 / 27

3 / 27

1. Getting Started

Installation of R

https://www.r-project.org

4 / 27

1. Getting Started

Installation of RStudio

https://www.rstudio.com

5 / 27

1. Getting Started

RStudio Layout

NOTE: Ctrl + R or Ctrl + Enter

pass lines or highlighted blocks from Editor Window to Console Window

6 / 27

1. Getting Started

R Version

R.Version(), version, getRversion()

> R.Version()$version.string[1] "R version 3.3.1 (2016-06-21)"> version

_platform x86_64-apple-darwin13.4.0arch x86_64os darwin13.4.0system x86_64, darwin13.4.0statusmajor 3minor 3.1year 2016month 06day 21svn rev 70800language Rversion.string R version 3.3.1 (2016-06-21)nickname Bug in Your Hair> getRversion()[1] 3.3.1

7 / 27

1. Getting Started

Working Directory

getwd(), setwd(), dir()Your working directory is the folder on your computer in which you are currently working.

When you ask R to open a certain file, it will look in the working directory for this file, and when you tell R to save

a data file or figure, it will save it in the working directory.

Before you start working, set your working directory to where all your data and script files are or should be stored.

> getwd() # checking current working directory[1] "/Users/SHCHO"> setwd("/Users/SHCHO/Desktop/R/") # setting current working directory> dir() # print files in the current working directory

Can use a hasmark (#) for a comment

8 / 27

2. Some First Examples of R Commands

R as a calculator

102 +e2 +sin(π)+36

log10(100)+ log2(4)+ ln(e2)

√100+

√4

1/1001/2

> 10ˆ2 + exp(2) + sin(pi) + 36[1] 143.3891> log10(100) + log2(4) + log(exp(2))[1] 6> sqrt(100) + sqrt(4)[1] 12> (1/100)/(1/2)[1] 0.02

9 / 27

2. Some First Examples of R Commands

Objects & Workspace

objects()Can save a calculated result as a variable and use it later

> res1 <- 10ˆ2 + exp(2) + sin(pi) + 36 # "<-" means assign. can be replaced by "="> res1[1] 143.3891> objects()[1] "res1"

Can see that res1 appears in Workspace Window

> res2 <- log10(100) + log2(4) + log(exp(2))> res2[1] 6> res3 <- sqrt(100) + sqrt(4)> res3[1] 12> objects()[1] "res1" "res2" "res3"

Can see that res2 and res3 appear as well in Workspace Window

10 / 27

2. Some First Examples of R Commands

Objects & Workspace

Can calculate a new value using res1

If assign a new value to res1 again, it will forget what value it had before

> res1[1] 143.3891> res1 * 50[1] 7169.453> res1 <- res1 + 50> res1[1] 193.3891

11 / 27

2. Some First Examples of R Commands

Objects & Workspace

rm()Can clear some or all variables in Workspace Window

> rm(res1, res2)> objects()[1] "res3"> rm(list=ls())> objects()character(0)

12 / 27

2. Some First Examples of R Commands

Objects & Workspace

R is an expression language with a very simple syntax

It is case sensitive so A and a are different symbols and would refer to different variables

> A <- 1:10> a <- 2:11> A[1] 1 2 3 4 5 6 7 8 9 10

> a[1] 2 3 4 5 6 7 8 9 10 11

Commands are separated either by a semi-colon (;) or a newline

> A; a[1] 1 2 3 4 5 6 7 8 9 10[1] 2 3 4 5 6 7 8 9 10 11

13 / 27

2. Some First Examples of R Commands

Help & Documentation

help(),?There is a very useful help facility in R that you can learn R functions by yourselves

> help(var) # help facility invoked by the function "help"> ?var # a faster alternative> ?sin> ?sqrt

For a feature specified by special characters, the argument must be enclosed in double or single quotes

> help("?") # Read the help page about how to use help> ?’?’ # a faster alternative> help(">")starting httpd help server ... done

14 / 27

3. R Objects and Classes

Objects

Everything in R is an object

Every object in R has a class

The entities R operates on are technically known as objects

Data, intermediate results, functions, and even the results of a regression fit are stored as objects

15 / 27

3. R Objects and Classes

Types of Objects

vectors: a single entity consisting of an ordered collection of numbers

matrices or arrays: multi-dimensional generalizations of vectors

factors: sets of labelled observations with a pre-defined set of labels

lists: a vector of R objects

data frames: matrix-like structures in which the columns can be of different types

functions

16 / 27

3. R Objects and Classes

Vectors and Classes (Modes)

The most important type of objects in R is a vector

Vectors are known as atomic structures, i.e., their components are all of the same type

The most common classes (modes) of vectors are

character: a vector of character strings of varying (and unlimited) length

numeric: a vetcor of real numbers

integer: a vectcor of (signed) integers

logical: a vector of logical (true or false) values

complex: a vector of complex numbers

list: a vector of R objects

17 / 27

3. R Objects and Classes

Vectors: 1. Numeric

c()A simple way to construct a vector is to use the c (combine) function

> c(1,2,3,4)[1] 1 2 3 4> rev(c(1,2,3,4)) # reverse the order of elements in the vector[1] 4 3 2 1

:The sequence operator : also generates consecutive numbers

> 1:4[1] 1 2 3 4> 4:1[1] 4 3 2 1> -1:2[1] -1 0 1 2

18 / 27

3. R Objects and Classes

Vectors: 1. Numeric

seq()seq is the main function for generating numeric vectors

> seq(2, 8, by = 2) # specify an interval[1] 2 4 6 8> seq(0, 1, by = 0.1)[1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

> seq(0, 1, length = 11) # specify the number of elements[1] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

19 / 27

3. R Objects and Classes

Vectors: 1. Numeric

The standard arithmetic functions and operators apply to vectors on an element-wise basis

> c(1,2,3,4)/2[1] 0.5 1.0 1.5 2.0> c(1,2,3,4)/4:1[1] 0.2500000 0.6666667 1.5000000 4.0000000> log( c(0.1, 1, 10, 100), 10 )[1] -1 0 1 2

20 / 27

3. R Objects and Classes

Vectors: 1. Numeric

Recycling Rule

If the operands are of different lengths, then the shorter of the two is extended by repetition

> c(1,2,3,4) + c(4,3)[1] 5 5 7 7

21 / 27

3. R Objects and Classes

Vectors: 1. Numeric

Indexing

Indices are specified between square brackets [ ]

> v <- 10:1; v[1] 10 9 8 7 6 5 4 3 2 1

> v[2][1] 9> v[c(4,2,6)][1] 7 9 5> v[c(4,2,4)][1] 7 9 7> v[-c(2,4,5,8,10)][1] 10 8 5 4 2

22 / 27

3. R Objects and Classes

Vectors: 2. Logical

Logical Operators

Logical vectors can be created by using logical operators: &, |, !, ==, !=, <=,<,>,>=

> x <- seq(0, 10, by = 0.5); x[1] 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0

[18] 8.5 9.0 9.5 10.0> y <- x >= 5; y[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE

[15] TRUE TRUE TRUE TRUE TRUE TRUE TRUE> z <- x == 6; z[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE

[15] FALSE FALSE FALSE FALSE FALSE FALSE FALSE> which(z)[1] 13

23 / 27

3. R Objects and Classes

Vectors: 2. Logical

Indexing

Indices are specified between square brackets [ ]

> x[y][1] 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0

> x[which(z)][1] 6> v <- 10:1; v[1] 10 9 8 7 6 5 4 3 2 1

> v[v < 6][1] 5 4 3 2 1> v[ v <= 3 | v >= 9 ][1] 10 9 3 2 1> v[ v <= 3 & v >= 9 ]integer(0)> z <- -10:10> z[abs(z) <= 3][1] -3 -2 -1 0 1 2 3

24 / 27

3. R Objects and Classes

Vectors: 3. Character

> names <- c("John","Georges","Mary"); names[1] "John" "Georges" "Mary"> letters[1:5][1] "a" "b" "c" "d" "e"> LETTERS[1:5][1] "A" "B" "C" "D" "E"> state.name[10:15][1] "Georgia" "Hawaii" "Idaho" "Illinois" "Indiana" "Iowa"

25 / 27

3. R Objects and Classes

Vectors

rep()Another way to construct any type of vectors is to use the rep function

> rep(5,3)[1] 5 5 5> rep( c(1,2,3), 2 )[1] 1 2 3 1 2 3> rep(1:3, 3:1)[1] 1 1 1 2 2 3> rep( c("Rep", "Dem"), c(10,10) )[1] "Rep" "Rep" "Rep" "Rep" "Rep" "Rep" "Rep" "Rep" "Rep" "Rep" "Dem" "Dem" "Dem" "Dem"

[15] "Dem" "Dem" "Dem" "Dem" "Dem" "Dem"

26 / 27

3. R Objects and Classes

Vectors

mode(), length()For any object of R, you can apply two functions: mode and length

> mode(v)[1] "numeric"> length(v)[1] 10>> mode(y)[1] "logical"> length(y)[1] 21>> mode(names)[1] "character"> length(names)[1] 3

27 / 27