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--- day1_practice3 [2017/12/12 11:49] – ↷ Page name changed from day1_practice_3 to day1_practice3 hyjeong
+++ day1_practice3 [2021/03/17 13:09] (current) – external edit 127.0.0.1
@@ Line 1: / Line 1: @@
+  # " " – 공백 (default: sep=" ")
+  myname <- "Jason Bourne"
+  paste("My name is", myname, sep=" ")
+  # file name
+  file_id = 1533
+  paste("Dataset_",file_id, ".txt",sep="")
+  # vector arguments
+  paste(LETTERS[1:5],1:5)
+  # vector 인수들을 원소별로 결합 후 collapse 정의 문자로 구분
+  # (default) collapse = NULL
+  paste("A","B",collapse='/')
+  paste(c("A","B"),collapse='/')
+  paste(c("A","B"),1:2,collapse='/')
+  paste(c("A","B"),1:2,sep='?', collapse='/')
+  # paste(vector1, ..., sep=‘’,collapse= NULL)
+  paste(c("A","B"),1:2,sep='',collapse='/')
+  paste0(c("A","B"),1:2,collapse='/')
+  paste0(LETTERS[1:5],letters[1:5])
+  test <- c("abcdefg", "AFFY1245820")
+  nchar(test)
+  f_name <- "AFFY1245820"
+  substr(f_name,5,nchar(f_name))
+  strtrim("ABCDEF",3)
+  strtrim(rep("abcdef", 3), c(1,4,10))
+  strsplit(c("a,b,c,d","cd,e"),split=',')
+  strsplit(c("010-1234-1111","010-1222-3434"),split='-')
+  x <- c("asfef", "yuiop[", "b", "stuff.blah.yech")
+  strsplit(x, "e")
+  strsplit(x,"[a-e]")
+  strsplit(x,"[aleu]")
+  unlist(strsplit("a.b.c", "."))
+  unlist(strsplit("a.b.c", "[.]"))
+  unlist(strsplit("a.b.c", ".", fixed = TRUE))
+  test = dir("./")
+  grep("^[A-Ca-c][a-z]",test,value=T)
+  grep(".exe$",test,value=T)
+  dir("./")
+  getwd()
+  setwd("../")
+  dir()
+  dir.create('./test'); dir()
+  x <- c(1,3,2,4)
+  xmat <- matrix(c(1,2,4,5,2,1),3,2)
+  dat = data.frame() # 비어있는 데이터 프레임
+  dat = edit(dat)
+  a = readline("Input any integer: ")
+  a
+  b = readline("Input two integers with comma :")
+  # Input two integers with comma : 3,5
+  as.numeric(unlist(strsplit(b,"[,]")))
+  setwd('/BiO/example/dataset')
+  x = scan(file="input_noh.txt",what=numeric())
+  head(x)
+  x = scan(file="input_noh.txt",what=character())
+  head(x)
+  x = scan(file="input_noh.txt")
+  head(x)
+  x = scan(file="input_h.txt")
+  head(x)
+  x = scan(file="input_h.txt",what=character())
+  head(x)
+  dat = read.table(file="input_noh.txt")
+  dat2 = read.table(file="input_noh.txt",header=T)
+  dat3 = read.table(file="input_h.txt",header=F)
+  dat4 = read.table(file="input_h.txt",header=T)
+  x <- 1:10
+  cat(x,file="x.txt",sep="\n") # output to a file
+  cat(x,sep="\t") # output to a screen
+  cat("\n ",1,"st element of x = ",x[1])
+  # "\n" – 줄바꿈, "\t" – 탭
+  x1 <- 1:20
+  x2 <- rep(c("A","B","B","A"),5)
+  x3 <- rep(c(T,F),each=10)
+  dat <- cbind(x1,x2,x3) # 문자열로 모두 변환됨.
+  dat <- data.frame(x1,x2,x3)
+  write.table(dat,file="test1.txt",row.names=T,
+              col.names=T,quote=T,sep="\t")
+  write.table(dat,file="test2.txt",row.names=F,
+              col.names=F,quote=F,sep="\n")
+  write.table(dat,file="test3.txt",sep=",")
+  library(xlsx)
+  dat = read.xlsx(file='food.xlsx',sheetIndex=1,
+                  as.data.frame=T,header=T,startRow=1)
+  head(dat)
+  save(list=ls(),file='test.rdata')
+  load(file = 'test.rdata')
+  x <- matrix(c(NA, 1, 3, NA, NA, 2),3,2)
+  is.na(x)
+  sum(is.na(x)) # number of missing values
+  which(is.na(x)) # 1차원 위치
+  which(is.na(x),arr.ind = T) # 2 차원 위치
+  which(is.na(x),T) # 2차원 위치
+  v = c("a,b,c,b,e","a,b","d,e,f")
+  lapply(v,nchar)
+  sp = strsplit(v,',')
+  sp
+  lapply(sp,length)
+  lapply(sp,paste0,3)
+  v = c("a,b,c,b,e","a,b","d,e,f")
+  sapply(v,nchar)
+  sp = strsplit(v,',')
+  sp
+  sapply(sp,length)
+  ?mtcars
+  head(mtcars)
+  tapply(mtcars$mpg,mtcars$cyl,mean)
+  tapply(mtcars$mpg,mtcars$am,mean)
+  library(dplyr)
+  filter(mtcars,cyl==4,am==1)
+  filter(mtcars,wt>2,cyl==8)
+  names(mtcars)
+  select(mtcars,mpg,cyl,wt)
+  select(mtcars,mpg,-hp,-gear)
+  mtf = select(mtcars,mpg,cyl,hp,wt)
+  mutate(mtf,hw_rat=hp/wt)
+  mutate(mtf,hw_rat=hp/wt,cw_rat=cyl/wt)
+  mtf = select(mtcars,mpg,am,cyl,wt)
+  arrange(mtf,mpg,desc(cyl))
+  arrange(mtf,am,cyl,wt)
+  summarize(mtcars,m_mpg=mean(mpg),v_mpg=var(mpg))
+  summarize(mtcars,md_mpg=median(mpg),md_wt=median(wt))
+  summarize(mtcars,trows=range(mpg))
+  mt_gr = group_by(mtcars,cyl)
+  head(mt_gr)
+  summarize(mtcars,m_mpg=mean(mpg),m_wt=mean(wt))
+  summarize(mt_gr,m_mpg=mean(mpg),m_wt=mean(wt))
+  dat <- group_by(mtcars, cyl)
+  dat <- select(dat, mpg, wt, cyl)
+  dat <- summarize(dat, m_mpg = mean(mpg))
+  dat <- filter(dat, m_mpg > 16)
+  dat
+  dat2 <- mtcars %>%
+          group_by(cyl) %>%
+          select(mpg, wt, cyl) %>%
+          summarize(m_mpg = mean(mpg)) %>%
+          filter(m_mpg > 16)
+  dat2