library(dplyr)
exam <- read.csv("csv_exam.csv")

exam %>% arrange(math)
exam %>% arrange(desc(math))
exam %>% arrange(class,math)

mpg <- as.data.frame(ggplot2 :: mpg)

mpg %>% filter(manufacturer=="audi") %>%  arrange(desc(hwy))

head(mpg)

exam %>% mutate(total = math + english + science) %>% head

exam %>% mutate(total = math + english + science, mean = (math + english + science)/3) %>% head

exam %>%group_by(class) %>% 
  summarise(mean_math = mean(math))

exam %>%group_by(class) %>% 
  summarise(mean_sci = mean(science))

exam %>%group_by(class) %>% 
  summarise(mean_math = mean(math),
            sum_math = sum(math),
            median_math = median(math),
            n = n())


test1 <- data.frame(id=c(1,2,3,4,5),
                    midterm = c(60,70,80,90,95))

test2 <- data.frame(id=c(1,2,3,4,5),
                    final = c(60,70,80,90,95))
total <- left_join(test1,test2,by = "id")
total

group_a <- data.frame(id=c(1,2,3,4,5),
                      test = c(60,70,80,90,97))

group_b <- data.frame(id=c(6,7,8,9,10),
                      test=c(70,80,90,12,56))

group_all <- bind_rows(group_a,group_b)