install.packages("dplyr")
library(dplyr)
exam <-read.csv(csv_exam)
exam <-read.csv(csv_exam.csv)
exam <-read.csv("csv_exam.csv")
exam
exam %>% filter(class=1)
exam %>% filter(class==1)
exam %>% filter(class==2)
exam %>% filter(class==3)
exam %>% filter(class!=2)
exam %>% filter(math<50)
exam %>% filter(class==1 & math >=50)
exam %>% filter(class=2 & math>60)
exam %>% filter(class==2 & math>=60)
exam %>% filter(math>=90 | english >= 90)
exam %>% filter(english<90 | science < 50)
exam %>% filter(class==1 | class==2 | class==3)
class1 <- exam %>% filter(class==1)
class2 <- exam %>% filter(class==2)
mean(class1$math)
mean(class2$math)
sum(class1$math)
class5 <-exam %>% filter(class==5)
mean(class5$math)
## 3반의 영어 평균
class3 <- exam %>% filter(class==3)
mean(class3$english)
install.packages("ggplot2")
library(ggplot2)
mpg
mpg2 <- mpg %>% filter(displ>=5)
mean(mpg1)
mean(mpg1$hwy)
mpg1 <- mpg %>% filter(displ<=4)
mean(mpg1$hwy)
mean(mpg2$hwy)
audi<-mpg %>% filter(cty==audi)
audi<-mpg %>% filter(manufacturer==audi)
audi<-mpg %>% filter(manufacturer="audi")
audi<-mpg %>% filter(manufacturer=="audi")
audi
toyota <-mpg %>% filter(manufacturer=="toyota")
toyota
mean(audi)
mean(audi$cty)
mean(toyota$cty)
chevrolet <- mpg %>% filter(manufacturer=="chevrolet")
chevrolet
cfh <- mpg %>% filter(manufacturer=="chevrolet" | manufacturer=="ford" | manufacturer=="honda")
chf
cfh
mean(cfh$hwy)
exam %>% select(math)
exam %>% select(math|english)
exam %>% select(math,english)
exam %>% select(-math)
exam %>% filter(class==2) %>% select(math)
exam %>%  filter(class==2) %>% select(english)
exam %>% select(id,math) %>% head(10)
