xxxxxxxxxxurl <- "https://vincentarelbundock.github.io/Rdatasets/csv/datasets/AirPassengers.csv"x <- read.csv(url)head(x)결과 :
xxxxxxxxxx## X time value## 1 1 1949.000 112## 2 2 1949.083 118## 3 3 1949.167 132## 4 4 1949.250 129## 5 5 1949.333 121## 6 6 1949.417 135
변수 x의 데이터 구조 확인하기.
xxxxxxxxxxstr(x)결과 :
xxxxxxxxxx## 'data.frame': 144 obs. of 3 variables:## $ X : int 1 2 3 4 5 6 7 8 9 10 ...## $ time : num 1949 1949 1949 1949 1949 ...## $ value: int 112 118 132 129 121 135 148 148 136 119 ...
[힌트 : write.table() 함수 사용]
xxxxxxxxxxsetwd("C:/Temp")write.table(x, "AirPassengers.txt", sep=",")# 파일이 저장되었는지 확인list.files(pattern="AirPassengers.txt")dir(pattern="AirPassengers.txt")결과 :
xxxxxxxxxx## [1] "AirPassengers.txt"
xxxxxxxxxxx1 <- x$timehead(x1)결과 :
xxxxxxxxxx## [1] 1949.000 1949.083 1949.167 1949.250 1949.333 1949.417
xxxxxxxxxxx2 <- x$valuehead(x2)결과 :
xxxxxxxxxx## [1] 112 118 132 129 121 135
xxxxxxxxxxy <- cbind(x1, x2)head(y)결과 :
xxxxxxxxxx## x1 x2## [1,] 1949.000 112## [2,] 1949.083 118## [3,] 1949.167 132## [4,] 1949.250 129## [5,] 1949.333 121## [6,] 1949.417 135
xxxxxxxxxxnames <- c("time", "value")colnames(y) <- nameshead(y)결과 :
xxxxxxxxxx## time value## [1,] 1949.000 112## [2,] 1949.083 118## [3,] 1949.167 132## [4,] 1949.250 129## [5,] 1949.333 121## [6,] 1949.417 135
xxxxxxxxxxsum(y[,"value"])결과 :
xxxxxxxxxx## [1] 40363
xxxxxxxxxxlength(y[,"value"])결과 :
xxxxxxxxxx## [1] 144
xxxxxxxxxxmean(y[,"value"])결과 :
xxxxxxxxxx## [1] 280.2986
xxxxxxxxxxsd(y[,"value"])결과 :
xxxxxxxxxx## [1] 119.9663
xxxxxxxxxxsummary(y[,"value"])결과 :
xxxxxxxxxx## Min. 1st Qu. Median Mean 3rd Qu. Max.## 104.0 180.0 265.5 280.3 360.5 622.0