day1_practice2
real <- 3.5
as.integer(real)
intg <- 3
is.integer(intg)
intg2 <- 1:5
is.integer(intg2)
intg3 <- 1.5:3
is.integer(intg3)
real <- 3
is.double(real)
is.numeric(1:3)
is.numeric(3.5)
ch <- c("red","blue", "yellow")
ch2 <- c('a','b',"c")
test <- c(TRUE,FALSE,TRUE)
is.logical(test)
test2 <- c(T,F,T)
as.numeric(test2)
as.logical(c(0,1,2,-1))
x <- "char"
mode(x)
x <- 5
is.character(x)
is.numeric(x)
is.double(x)
x <- "abc"
as.double(x)
x <- 1
as.character(x)
as.character(123)
vec <- c(1,3,4,2,5) # vector 정의는 c() 함수를 이용
vec
vec[1]
vec[3]
num <- c(1,2,3) # numeric type
ch <- c("red","blue","yellow") #character type
lo <- c(T,F,F,T) #logical type
num2 <- c(1,2,"red","blue") # character type
lo2 <- c(T,F,T,1,3) #numeric
lo3 <- c(T,F,"abc") #character type
assign("x",1:10)
x
for(i in 1:5) assign(paste0("x",i),1:5)
ls(); x2
x1 <- 1:10 (x=1:10) # local assign
x1
x2 = 5:1
x3 <<- 1:10 # global assign
x <- c(1,2,3)
y <- c(1,2,3,4)
v <- 2*x + y +1 # x=c(1,2,3,1) , 1 = (1,1,1,1)
a = 3
b <- 2
c <- 3 + 3
a + b + c
a - b * c
a / b - c
a ^ b * c
a ^ (b + c)
a %% b
c %% b
A <- T; B<- F
C <- c(T,T); D<- c(F,T)
A & B
A && B
C & D
C && D
A <- T; B <- F
C <- c(T,T); D <- c(F,T)
A | B
A || B
C | D
C || D
a <- c(1,2); b <- c(2,2)
a < b
a <= b
a > b
a >= b
A <- c(T,T); B <- c(F,T); C <- c(F,F)
A == B
B == C
all(A==B)
any(A==B)
any(A==C)
A <- c(T,T); B <- c(F,T); C <- c(F,F)
A != B
B != C
all(A!=B)
any(A!=B)
any(A!=C)
3 ^ 2 %% 4
3 * 2 %% 4
a = 1
a = a + 2
a
d = 5
3 + 10 * ( 2 + 3 ) / 5 %% (d-1)
3 + 10 * ( 2 + 3 ) / (5 %% (d-1))
log(10) # 다른 밑 x를 갖는 경우: log(10, base=x)
log10(10)
log(exp(1))
exp(1)
exp(2)
sin(30)
sin(pi/6)
x <- c(1,3,2,5,10)
max(x)
min(x)
x <- c(-5,10,2,5,8,9)
range(x)
sum(x)
prod(x)
mean(x)
var(x)
x <- c(1,5,3,2,4) ; sort(x)
#sort(x, decreasing = T)로 하면 내림차순
order(x) # 2의 경우 원래 4번째에 위치
# x[order(x)]=1 2 3 4 5
y <- c("A","A","B","B","A")
y[order(x)] # x의 정렬 반영
x <- 1:10
y <- 3.3:8
x; y;
rep(c(1,2),times=3)
rep(c(1,2),each=3)
seq(from=10,to=1)
seq(from=1,to=10) #seq(1,10) default by=1
seq(length=10,from=-5,by=3)
seq(length=6 , to=10, by=2)
vec <- vector() # 비어있는 객체 생성
vec <- c(3,6) # 숫자형 벡터
vec2 <- c("abc","def") # 문자형 벡터
vec3 <- c(T,F,F,T) # 논리형 벡터
names(vec) <- c("first", "second")
vec4 <- vector()
vec4[1] <- 1; vec4[2] <- 5; vec4
x1 <- matrix(1:10,nrow=5,ncol=2,byrow=T)
x1
x2 <- matrix(1:10,5,2,byrow=F) # default = F
x2
cbind(x1,x2) #행을 기준으로 열을 덧붙임.
rbind(x1,x2) #열을 기준으로 행을 덧붙임.
A <- matrix(1:12,4,3)
rownames(A) <- c("n1","n2","n3","n4")
colnames(A) <- paste0("x",1:3)
A
A['n1',]
A[,"x3"]
rname <- paste0("n",1:4)
cname <- paste0("x",1:3)
B <- matrix(1:12,4,3, dimnames=list(rname,cname))
B
A <- matrix(1:12,4,3)
A[1,2]
A[2,3]
A[1,] # 1행 선택
A[,2] # 2행 선택
A[c(1,3),] # 1,3 행의 선택
A[, 1:2] # 1,2 열의 선택
A[,-3] # 3열을 제외하고 선택
A <- matrix(1:12,4,3); B<- matrix(1,4,3)
A + B; A - B
A <- matrix(1:6,2,3); B <- matrix(1,3,2)
A%*%B # 3x3 행렬
A <- matrix(1:4,2,2)
solve(A)
A <- matrix(1:12,4,3); B<- matrix(1,4,3)
t(A); t(B)
A <- matrix(1:9,3,3)
sum(diag(A))
# diag(벡터): 대각행렬, diag(행렬):대각성분
x <- c(1,2,3); y<- c(1,2,3)
sum(x*y) # 벡터에 대한 내적은 간단히 sum을 이용하여 계산
A <- matrix(1:4,2,2)
det(A)
A <- matrix(1:4,2,2)
eigen(A)
eigen(A)$values
eigen(A)$vectors
lst1 = list(a = 1:10, b= matrix(1:4,2,2))
lst2 <- list()
lst2[[1]] <- matrix(1:10,5,2)
lst2[[2]] <- lst1
lst1$a
lst1$b
lst1[1] #리스트 객체로 반환
lst1[[1]] #리스트의 원소를 나타낸다. (lst1$a와 동일)
lst2[[1]]
lst2[[1]][3] #인덱스의 이중 사용 가능
lst2[[2]][[1]] #인덱스의 이중 사용 가능
grade <- c("A","A","B","C","B","B")
f.grade <- factor(grade)
summary(f.grade)
# order = T: 순서형, order=F: 명목형
grade <- c("A","A","B","C","B","B")
f2.grade <- factor(grade, order=T)
f2.grade
#원하는 순서를 나타내기 위해 작은 값 순서로 levels에 정의
lev <- c("C","B","A")
f3.grade <- factor(grade,levels=lev,order=T)
f3.grade
levels(f2.grade)
levels(f3.grade) # 순서에 대한 정보는 없다.
x1 = 1:4
x2 <- c("Kim","Lee","Jeong","Park")
dat = data.frame(x1,x2)
dat2 = data.frame(num=x1, name=x2)
dat; dat2
dat2$no
dat2$name #문자형 변수는 기본적으로 factor로 변환
# stringsAsFactors=F 를 이용 factor 자동변환 방지
dat3 = data.frame(x1,x2,stringsAsFactors=F)
#행렬의 인덱스 형태의 사용
dat[,1]; dat[,2]
dat[1,]; dat[2,]
dat[2,1]; dat[3,2]; dat3[3,2]
dat[1]; dat[2]
dat[[1]]; dat[[2]]
dat[[1]][2]; dat[[2]][1]
dat[,1:2]
dat[,-1]
dat[-1,-2]
dat[-1,c(2,4)]
x1 <- array(1:24,dim=c(4,3,2))
x2 <- array(1:32,dim=c(2,2,4,2))
x1[,,1] # 4 x 3 행렬
x1[,,2] # 4 x 3 행렬
x2[,,3,1] # 2 x 2 행렬
x <- 1:100 ; sum1 <- sum(x[13:100])
x <- c(1:5,10:20,30:45,2:5,11:30)
x>12
sum2 <- sum(x[x>12])
# sum all values between 10 and 20
sum3 <- sum(x[x>10 & x<20])
# Logical operator
# & : and, | : or, == : equal, != : not equal
# select elements at even positions in x
x <- 1:100
x[seq(2,100,by=2)]
x_mat <- matrix(x,20,5)
# select column 1,3,5 in x_mat
x[,c(1,3,5)] # x[,seq(1,5,by=2)]
# select rows 2,4 in x_mat
x[c(2,4),] # x[seq(2,4,by=2),]
# For matrix, (i,j)th element of A = A[i,j]
x_mat <- matrix(rnorm(100),20,5)
# Calculate mean values of each columns
apply(x_mat,2,mean)
# Calculate mean values of each rows
apply(x_mat,1,sum)
# Calculate variance values of each columns
apply(x_mat,2,var)
# Calculate variance values of each rows
apply(x_mat,1,var)
day1_practice2.txt · Last modified: 2021/03/17 13:09 by 127.0.0.1