데이터 유형

데이터 전처리에 있어 dplyr을 주로 사용하다보니 list, dataframe, matrix 사용법과 의미를 잊어 버리곤 한다.

list, matrix를 자주 사용하진 않는데 용할 일이 꼭 생긴다. 그럴때마다 구글링을 하는건 좋은 방법이 아닌 것 같다.

Vectors

a <- c(1,2,5.3,6,-2,4) # numeric vector
b <- c("one","two","three") # character vector
c <- c(TRUE,TRUE,TRUE,FALSE,TRUE,FALSE) #logical vector

a[c(2,4)] # 2nd and 4th elements of vector

Matrix

# generates 5 x 4 numeric matrix 
y<-matrix(1:20, nrow=5,ncol=4)

# another example
cells <- c(1,26,24,68)
rnames <- c("R1", "R2")
cnames <- c("C1", "C2") 
mymatrix <- matrix(cells, nrow=2, ncol=2, byrow=TRUE,
  dimnames=list(rnames, cnames))

x[,4] # 4th column of matrix
x[3,] # 3rd row of matrix 
x[2:4,1:3] # rows 2,3,4 of columns 1,2,3

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)
names(mydata) <- c("ID","Color","Passed") # variable names

myframe[3:5] # columns 3,4,5 of data frame
myframe[c("ID","Age")] # columns ID and Age from data frame
myframe$X1 # variable x1 in the data frame

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)

# example of a list containing two lists 
v <- c(list1,list2)

mylist[[2]] # 2nd component of the list
mylist[["mynumbers"]] # component named mynumbers in list

Factors

Tell R that a variable is nominal by making it a factor. The factor stores the nominal values as a vector of integers in the range [ 1... k ] (where k is the number of unique values in the nominal variable), and an internal vector of character strings (the original values) mapped to these integers.

# variable gender with 20 "male" entries and 
# 30 "female" entries 
gender <- c(rep("male",20), rep("female", 30)) 
gender <- factor(gender) 
# stores gender as 20 1s and 30 2s and associates
# 1=female, 2=male internally (alphabetically)
# R now treats gender as a nominal variable 
summary(gender)

# variable rating coded as "large", "medium", "small'
rating <- ordered(rating)
# recodes rating to 1,2,3 and associates
# 1=large, 2=medium, 3=small internally
# R now treats rating as ordinal

http://www.statmethods.net/input/datatypes.html