Data types in R

Generally for any technology to understand or work as a beginner we need to understand the types/input predefined instruction of the language platform we start working. In this we will discuss the type with calling and code snippet for R

Data types in R which includes inbuilt primitives and structured

• vector
• list
• matrix
• data frame
• factors (we will avoid these, but they have their uses)
• tables
• logical
• integer
• numeric
• complex
• character

Vector

A vector can be a vector of characters, logical, integers or numeric. Creating object for Vector using vector() or c().

# Empty

Command::  v<-vector()

Print::          print(v)

Output  ::     logical(0)

# Predefined Length

 v <- vector(length = 10)

 print(v)

 [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE

#

 x <- c(1, 2, 3)

 print(x)

[1] 1 2 3

#

m <- c(1L, 2L, 3L)

 print(m)

[1] 1 2 3

#

y <- c(TRUE, TRUE, FALSE, FALSE)

> print(y)

[1]  TRUE  TRUE FALSE FALSE

#

> z <- c("Andrew", "Zach", "Mike")

> print(z)

[1] "Andrew" "Zach"   "Mike"

List

A list is an R-object which can contain many different types of elements inside it like vectors, functions and even another list inside it. Lists are sometimes called recursive vectors, because a list can contain other lists. This makes them fundamentally different from atomic vectors.

# Empty

Command::  x <- list(10, "ax", TRUE, 1+4i)

Print::          print(x)

Output  ::    

 [[1]]

[1] 10

[[2]]

[1] "ax"

[[3]]

[1] TRUE

[[4]]

[1] 1+4i

#Length of List

Command:: length(x)

[1] 4

Matrix

Matrices are a special vector in R which holds row and column attributes. It can be created using a vector input to the matrix function.

# Empty

Command::  m <- matrix(1:6, nrow=2, ncol =3)

Print::          print(m)

Output::

[,1] [,2] [,3]

[1,]    1    3    5

[2,]    2    4    6

We can also bind rows /column wise using the command cbind() and rbind()

 x <- 5:7

 y <- 6:8

 rbind(x,y)

  [,1] [,2] [,3]

x    5    6    7

y    6    7    8

 cbind(x,y)

     x y

[1,] 5 6

[2,] 6 7

[3,] 7 8

Array

Arrays can be of any number of dimensions opposed to matrix which is limited to  two dimensional. The array function takes a dim attribute which creates the required number of dimension.

)

# Command Prototype

Command:: a <- array(c('vegetable','Fruits'),dim = c(3,3,2))

> print(a)

, , 1

     [,1]        [,2]        [,3]      

[1,] "vegetable" "Fruits"    "vegetable"

[2,] "Fruits"    "vegetable" "Fruits"  

[3,] "vegetable" "Fruits"    "vegetable"

, , 2

     [,1]        [,2]        [,3]      

[1,] "Fruits"    "vegetable" "Fruits"  

[2,] "vegetable" "Fruits"    "vegetable"

[3,] "Fruits"    "vegetable" "Fruits"

Factor

Factor are a special vector in R. It can be ordered or unordered and are important when for modeling functions such as lm() and glm() and also in plot methods. Factors has to be pre-defined values.

.

# Empty

Command::  factor()

#Example

spectrum <- c('Red','green','yellow','Voilet','Cyan','Magenta','Orange')

factor_spectrum<-factor(spectrum)

print(factor_spectrum)

[1] Red     green   yellow  Voilet  Cyan    Magenta Orange

Levels: Cyan green Magenta Orange Red Voilet yellow

print(nlevels(factor_spectrum))

[1] 7

DataFrames

Data frames are data structure for most tabular data which we use for statistics in R. It has attributes rownames()which is used to annotate  the entity. Data frame is a special type of list where every element of a list has same length. Few additional built in function:-

·         data.matrix()

·         nrow(df) 

·         ncol(df)

·         cbind(df)

·         head()

·         tail()

·         Data frame is a special type of list where every element of a list has same length

# Empty

Command::  data.frame()

#Example

dFrame <- data.frame(id = letters[2:5], x = 2:5, y = rnorm(4))

 print(dFrame)

          id       x        y

1         b       2        0.3129572

2         c       3        1.6263950

3        d        4        0.8441991

4        e        5        1.0301756

cbind(dFrame, data.frame(z = 4))

  id x         y z

1  b 2 0.3129572 4

2  c 3 1.6263950 4

3  d 4 0.8441991 4

4  e 5 1.0301756 4

 head(dFrame,2)

          id       x         y

1        b        2        0.3129572

2        c        3        1.6263950

 tail(dFrame,2)

          id       x         y

3        d        4        0.8441991

4        e        5        1.0301756