R

data types

data type 확인하려면

> typeof(var)

Matrix

> y <- matrix(1:20,nrow=5,ncol=4)
> y
     [,1] [,2] [,3] [,4]
[1,]    1    6   11   16
[2,]    2    7   12   17
[3,]    3    8   13   18
[4,]    4    9   14   19
[5,]    5   10   15   20 

1에서 20까지의 숫자를 5개의 행, 4개의 열로 저장

Vector

> a <- c(1,2,5.3,6,-2,4) # numeric vector
> a
[1]  1.0  2.0  5.3  6.0 -2.0  4.0
> b <- c("one","two","three") # character vector
> b
[1] "one"   "two"   "three"
> c <- c(TRUE,TRUE,TRUE,FALSE,TRUE,FALSE) #logical vector
> c
[1]  TRUE  TRUE  TRUE FALSE  TRUE FALSE

Dataframe

> d <- c(1,2,3,4)
> e <- c("red", "white", "red", NA)
> f <- c(TRUE,TRUE,TRUE,FALSE)
> mydata <- data.frame(d,e,f)
> mydata
  d     e     f
1 1   red  TRUE
2 2 white  TRUE
3 3   red  TRUE
4 4  <NA> FALSE

Vector들을 옆으로 쭉 붙여놓는것,

> names(mydata) <- c("ID","Color","Passed")
> mydata
  ID Color Passed
1  1   red   TRUE
2  2 white   TRUE
3  3   red   TRUE
4  4  <NA>  FALSE

이름도 달 수 있다.

Lists

# example of a list with 4 components - 
# a string, a numeric vector, a matrix, and a scaler 
w <- list(name="Fred", mynumbers=a, mymatrix=y, age=5.3)
> w
$name
[1] "Fred"

$mynumbers
[1]  1.0  2.0  5.3  6.0 -2.0  4.0 

$mymatrix
     [,1] [,2] [,3] [,4]
[1,]    1    6   11   16
[2,]    2    7   12   17
[3,]    3    8   13   18
[4,]    4    9   14   19
[5,]    5   10   15   20

$age
[1] 5.3

Factor

> gender <- c(rep("male",20), rep("female", 30)) # c(ref("x",20)) 은 x를 20개 반복해서 백터를 만들어라는 명령
> gender
 [1] "male"   "male"   "male"   "male"   "male"   "male"   "male"   "male"  
 [9] "male"   "male"   "male"   "male"   "male"   "male"   "male"   "male"  
[17] "male"   "male"   "male"   "male"   "female" "female" "female" "female"
[25] "female" "female" "female" "female" "female" "female" "female" "female"
[33] "female" "female" "female" "female" "female" "female" "female" "female"
[41] "female" "female" "female" "female" "female" "female" "female" "female"
[49] "female" "female"
> gender <- factor(gender)
> gender
 [1] male   male   male   male   male   male   male   male   male   male  
[11] male   male   male   male   male   male   male   male   male   male  
[21] female female female female female female female female female female
[31] female female female female female female female female female female
[41] female female female female female female female female female female
Levels: female male
> summary(gender)
female   male 
    30     20