R Programming Practical 1.1

1. Introduction:

R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. R is a programming language developed by Ross Ihaka and Robert Gentleman at the University of Auckland in 1993

Why use R for statistical computing and graphics?

• It runs on all platforms.
• It is the popular programming language and increasing in popularity.
• It is an open-source and free programming language.
• It is being used by the biggest tech giants.
• R and its libraries implement a wide variety of statistical and graphical techniques.
• It is easily extensible through functions and extensions.
• R community is noted for its active contributions in terms of packages.

Application of R programming in the real world

• Social Media: Behavior analysis, Sentiment Analysis
• IT: Business Intelligence Software Development and Machine learning Product
• Finance: Stock Market Modeling and Fraud Detection
• Government: Weather Forecasting and Record-Keeping
• Research and Academic
• E-Commerce
• Banking Sector
• Health Care
• Manufacturing Industry

How to download & install R, R studio

• R can be downloaded for free from https://www.r-project.org/

• R Studio allows the user to run R in a more user-friendly environment. It is open-source (i.e. free) and available at https://rstudio.com/products/rstudio/download/

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1.1 R as a calculator

1.1.1 Performing variuos arithmetic operations: Addition(+),Subtraction(-), multiplication(*), exponent(^) etc

25+3

## [1] 28

25-3

## [1] 22

25*3

## [1] 75

25/3   # division

## [1] 8.333333

25%/%3 # given the integer value when 25 is divided by 3

## [1] 8

2**3

## [1] 8

2^3

## [1] 8

1.1.2 Builtin functions

Built-in functions refer to a set of pre-defined functions

exp(6)

## [1] 403.4288

sqrt(36) #square root of 36

## [1] 6

sum(2,3,4,5,6)

## [1] 20

log(64)

## [1] 4.158883

log(10,2) #log 10 to base 2

## [1] 3.321928

log(42,10)#log 42 to the base 10

## [1] 1.623249

log(5,3)

## [1] 1.464974

factorial(5) # 5!= 1*2*3*4*5

## [1] 120

abs(-8.5)#absolute value

## [1] 8.5

floor(3.8)  #greatest integer less than 3.8

## [1] 3

ceiling(3.2) #next integer to 3.2

## [1] 4

rep(35,times=10) #repeate 35 10 times

##  [1] 35 35 35 35 35 35 35 35 35 35

rep("Happy", times=5)

## [1] "Happy" "Happy" "Happy" "Happy" "Happy"

## [1] "Happy" "Happy" "Happy" "Happy" "Happy"
5:9  # display numbers from 5 to 9

## [1] 5 6 7 8 9

1:100

##   [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
##  [19]  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
##  [37]  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
##  [55]  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
##  [73]  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
##  [91]  91  92  93  94  95  96  97  98  99 100

seq(5,9) # generates a sequence of numbers from 5 to 9,

## [1] 5 6 7 8 9

seq(5,10,0.5) #generates a sequence of numbers starting from 5, incrementing by 0.5 till 10

##  [1]  5.0  5.5  6.0  6.5  7.0  7.5  8.0  8.5  9.0  9.5 10.0

seq(1,50,5)

##  [1]  1  6 11 16 21 26 31 36 41 46

1.1.3 Relational Operators

Relational operators in R are used to compare values and determine the relationship between them.

2<5

## [1] TRUE

3>9

## [1] FALSE

2+3==6 #to check whether 'is equal to'

## [1] FALSE

2!=3 #to check whether 'not equal to'

## [1] TRUE

1.2 Assigning value to a variable

we can assign a value to a variable using the assignment operator <- or the equal sign = syntax: variable_name <- value

x <- 48  # x is assigned the value 48
print(x)

## [1] 48

x/5

## [1] 9.6

x*2

## [1] 96

y<-"Happy"
rm(x) #to remove x from memory
rm(y)

1.3 Vectors

In R, a vector is a fundamental data structure that can hold a collection of values of the same data type. Vectors are essential in R and are used extensively in data analysis, statistics, and programming. c() is used to create vectors.