R Programming Language | Tutorial #1

What Will I Learn?

• Simple Main Concepts
• Data Types (Generally)

Requirements

• RStudio

Difficulty

• Basic

Tutorial Contents

R is a free and open source software which is programming language developed as a statistical computing and graphical environment. RStudio is a powerful and open source integrated development environment for R. In this tutorial, I will explain the R programming Language in a simple way. It will be a long series of tutorials and I will mention all the details you need in R Programming Language.

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Simple Main Concepts

print("Hello World")
[1] "Hello World"

# mathematical operations

1 + 2
[1] 3
3 * 3
[1] 9
10 / 5
[1] 2
(3 + 5) ^ 2
[1] 64
3 ^ 4
[1] 81
4 - 1
[1] 3
print(15.7 + 4.3)
[1] 20
coinbaba <- "I Love utopian.io <3"
print(coinbaba)
[1] "I Love utopian.io <3"
# or
coinbaba
[1] "I Love utopian.io <3"

Here I wrote simple text and mathematical operations. "<-" can be used instead of "=". I will use "<-" throughout the entire tutorial. I created a new value and applied the printing process that I determined with the "print" function. The print ( print() ) function can print any value.

Data Types (Generally)

I'll briefly explain the six data types. In my next tutorial, I will explain the data types in detail. There 6 types of data: Factors, Lists, Data Frames, Arrays, Vectors, and Matrices.

Data Type	Example
Numeric	25, 7, 29, 28.7
Logical	FALSE, TRUE
Integer	2L, 0L
Character	"coin", "baba", "coinbaba", "2018"
Complex	1+1i
Raw	"coinbaba" is stored as 63 6f 69 6e 62 61 62 61

With the print (class (x)) function, we can learn the data type of any value.

numaricexample <- 25
print(class(numaricexample))
[1] "numeric"

logicalExample <- FALSE
print(class(logicalExample))
[1] "logical"

integerExample <- 2L
print(class(integerExample))
[1] "integer"

characterExample <- "coinbaba"
print(class(characterExample))
[1] "character"

complexExample <- 1+1i
 print(class(complexExample))
[1] "complex"

rawExample <- charToRaw("coinbaba")
 print(class(rawExample))
[1] "raw"
 rawExample
[1] 63 6f 69 6e 62 61 62 61

Note: Data types are not limited to the six examples shown above. More data types are available. As an example, I showed six.

Factors

Factors are r objects created using a vector. Factors are constructed using the factor () function, and the Nlevels functions give the number of levels.

#factors

factorExample <- factor(steemit)
factorExample
[1] steem sbd   sp   
Levels: sbd sp steem
print(nlevels(factorExample))
[1] 3

Lists

A list is an R object that can contain many different types of elements, such as function, vectors and even other lists.

#Lists
 
listExample <- list(c(1,7,5),10)
listExample
[[1]]
[1] 1 7 5

[[2]]
[1] 10

Data Frames

Data frames are data objects. Unlike a matrix in the data frame, each column can contain different data modes. Data Frames are created using the data.frame () function.

#dataframe
 
dataframeExample <- data.frame(
+     gender = c("Male", "Female","Female"), 
+     height = c(180, 155.5, 173), 
+     weight = c(90,55, 75),
+     Age = c(32,18,23)
+ )

dataframeExample
  gender height weight Age
1   Male  180.0     90  32
2 Female  155.5     55  18
3 Female  173.0     75  23

Arrays

Matrices may be limited to two dimensions, and arrays may be of any dimensions. The array function receives a dim attribute that creates the required number of dimensions.

#arrayExample
 
arrayExample <- array(c('coin','baba'),dim = c(3,2,2))
arrayExample
, , 1

     [,1]   [,2]  
[1,] "coin" "baba"
[2,] "baba" "coin"
[3,] "coin" "baba"

, , 2

     [,1]   [,2]  
[1,] "coin" "baba"
[2,] "baba" "coin"
[3,] "coin" "baba"

Vectors

If you want to create a vector with more than one item, you must use the c() function to combine elements into one value.

#Vectors

steemit <- c("steem","sbd","sp")

steemit
[1] "steem" "sbd"   "sp"  

Matrices

A matrix is a two-dimensional rectangular data set. The matrix function can be created using a vector entry.

#matrix

matrixExample = matrix( c('1','1','2','3','4','1'), nrow = 2, ncol = 3, byrow = TRUE)
matrixExample
     [,1] [,2] [,3]
[1,] "1"  "1"  "2" 
[2,] "3"  "4"  "1" 

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