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vec.name<-c("김지훈","이유진","박동현","김민지") 
vec.eng<-c(90,80,70,60)
vec.math<-c(50,60,200,30)
vec.class<-c(1,1,2,2)
df.score<-cbind.data.frame(vec.name,vec.eng,vec.math,vec.class) #앞에cbin:컬럼을 연결해라
df.score

id<-c(1:6)
class<-c(1,1,1,1,2,2)
math<-c(50,60,45,30,25,50)
eng<-c(50,60,45,30,25,50)
sci<-c(50,60,45,30,25,50)
score<-data.frame(id,class,math,eng,sci)
score

#전체학생 점수 데이터 보기-score입력(내가 정의한 데이터 프레임 이름)
#n번째 row까지만 보여주기 -head(df,n)
head(score,5)
#밑에서 n번째 row까지만 보여주기- tail(df,n)
tail(score,2)
#뷰어창에서 df확인 View(df) **V는 대문자

#df row&column count
dim(score)

#속성 파악하기 str
str(score)

#summary()요약
summary(score)

#package
#install.packages("ggplot2")  #전체 풀젝으로 불러오는 것
#library(ggplot2)  #이 파일로 불러오는 것

mpg<-as.data.frame(ggplot2::mpg)
head(mpg,3)
tail(mpg)
str(mpg)
summary(mpg)




#변수명 바꾸기 dplyr패키지의 rename 
#install.packages("dplyr")
#library(dplyr)

#score<-rename(score,id=아이디....)
library(data.table)
library(dplyr)
score
score %>%  #파이프 라인(ctrl+shift+m)---무슨뜻??: '내부에 있는' 이라는 뜻
data.table::setnames(old="class",new="클래스")
score
#data.table::setnames(old="class",new="클래스")#???안됨
score
score$total<-score$math+score$eng+score$sci
score
score$mean<-score$total/3
score
hist(score$mean)
hist(score$total)

#ifelse()조건문
# ifelse(score$mean>=50,"pass","fail")
score$test<-ifelse(score$mean>=50,"pass","fail")
table(score$test)
library(ggplot2)
ggplot2::qplot(score$test)#ggplot::이건 가독성 높이기 위해서 해주는거. 이 함수가 어느 패키지에서 나왔는지

score$등급<-ifelse(score$mean>=50,"A",ifelse(score$mean>=30,"B","C"))
score
table(score$등)  


###mpg데이터 직접 적용 해보기
library(ggplot2)
mpg<-as.data.frame(ggplot2::mpg)
head(mpg)                 
tail(mpg)
str(mpg)
summary(mpg)

#숫자변수--여섯가지 통계량/문자--값의 개수와 변수의 속성
# 
# manufacturer          model          
# Length:234         Length:234        
# Class :character   Class :character  
# Mode  :character   Mode  :character  
# 
# 
# 
# displ            year           cyl       
# Min.   :1.600   Min.   :1999   Min.   :4.000  
# 1st Qu.:2.400   1st Qu.:1999   1st Qu.:4.000  
# Median :3.300   Median :2004   Median :6.000  
# Mean   :3.472   Mean   :2004   Mean   :5.889  
# 3rd Qu.:4.600   3rd Qu.:2008   3rd Qu.:8.000  
# Max.   :7.000   Max.   :2008   Max.   :8.000  
# trans               drv           
# Length:234         Length:234        
# Class :character   Class :character  
# Mode  :character   Mode  :character  
# 
# 
# 
# cty             hwy             fl           
# Min.   : 9.00   Min.   :12.00   Length:234        
# 1st Qu.:14.00   1st Qu.:18.00   Class :character  
# Median :17.00   Median :24.00   Mode  :character  
# Mean   :16.86   Mean   :23.44                     
# 3rd Qu.:19.00   3rd Qu.:27.00                     
# Max.   :35.00   Max.   :44.00                     
# class          
# Length:234        
# Class :character  
# Mode  :character  
library(data.table)
library(dbplyr)
mpg
mpg %>% #여기서부터 에러
data.table::setnames(old="manufacturer",new="제조사")
df<-data.frame(mpg$제조사,mpg$year)
df$year<-year
df$mean<-mean(year)

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