> For the complete documentation index, see [llms.txt](https://r-pedia.gitbook.io/cevi/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://r-pedia.gitbook.io/cevi/r-data/r-object.md).
# -R object
#### **There are many types of R-objects. The frequently used ones are Vectors, Matrices, Arrays, Data frame, List, and Factor**
#### Vectors:
A vector is a sequence of same datatype elements
```r
a <-c(1,2,3,4.9,10,2,4) # numeric
vectorb <-c("one","two","three") # character
vectorc <-c(TRUE,FALSE) #logical vectora;b;c
```
Get the position of the elements using vector\[c(postion)]
```r
b[c(1,2)] # 1st and 2nd elements of vector b
```
#### Matrix:
A matrix is two-dimensional vector. The matrix elements must be of the same data type
```r
c<- matrix(
c(1:6), # the data elements
nrow=2, # number of rows
ncol=3, # number of columns
byrow = TRUE) # fill matrix by rows
c # print the matrix
#####################
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 4 5 6
```
#### Array:
An array is matrix with more than 2-dimensions (n-matrix)
```r
a<-array(
c(1:9), # the data elements
dim=c(3,3,2) # 2-matrix from 3 row and 3 column )
a #print array a
#########################
, , 1
[,1] [,2] [,3]
[1,] 1 4 7
[2,] 2 5 8
[3,] 3 6 9
, , 2
[,1] [,2] [,3]
[1,] 1 4 7
[2,] 2 5 8
[3,] 3 6 9
# Get the position of the elements using array[c(postion)]
a[c(1,8)]
##########
[1] 1 8
```
#### Data frame:
A data frame is tabular store system. The column must be same length. Data frame used as the by most of **R**'s modeling software
```r
name<-c("cevi","Julia","Marissa")
class<-c(1,2,3)
note<-c(1,1.7,2.3)
student<-data.frame(name,class,note)
print(student)
##############
name class note
1 cevi 1 1.0
2 Julia 2 1.7
3 Marissa 3 2.3
```
#### List:
A list is a vector containing other objects. Every object can be different length and datatype
```r
x<-c(1:10)
y<-c(TRUE,FALSE)
z<-c("cevi","Julia","Marissa")
thelist<-list(x,y,z)
print(thelist)
############
[[1]]
[1] 1 2 3 4 5 6 7 8 9 10
[[2]]
[1] TRUE, FALSE
[[3]][1] "cevi" "Julia" "Marissa"
```
#### Factor and Order
Factor create a distinct value from the data and ordered() create a ordinal structure of the data (based on alphabetical or numerical value)
```r
gender <-c("male","male","female")
genderfactor(gender)
##############
[1] male male female
Levels: female male
#ordered()
rating<-c(1,2,2,3,4,5,6,6,6,4)
ordered(rating)
################
[1] 1 2 2 3 4 5 6 6 6 4
Levels: 1 < 2 < 3 < 4 < 5 < 6
```
---
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