homework

혼자서 해보기 1번

library(dplyr)

## 
## 다음의 패키지를 부착합니다: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

mpg <- as.data.frame(ggplot2::mpg)
mpg_a <- mpg %>% filter(displ <= 4)
mpg_b <- mpg %>% filter(displ >= 5)
mean(mpg_a$hwy)

## [1] 25.96319

mean(mpg_b$hwy)

## [1] 18.07895

mpg_audi<- mpg %>% filter(manufacturer == "audi") 
mpg_toyota <- mpg %>% filter(manufacturer == "toyota")
mean(mpg_audi$cty)

## [1] 17.61111

mean(mpg_toyota$cty)

## [1] 18.52941

mpg_new<-mpg %>% filter(manufacturer %in% c("chevrolet", "ford", "honda"))
mean(mpg_new$hwy)

## [1] 22.50943

혼자서 해보기 2번

mpg <- as.data.frame(ggplot2::mpg) 
df <- mpg %>% select(class, cty)
head(df)

##     class cty
## 1 compact  18
## 2 compact  21
## 3 compact  20
## 4 compact  21
## 5 compact  16
## 6 compact  18

df_suv <- df %>% filter(class == "suv") 
df_compact <- df %>% filter(class == "compact") 
mean(df_suv$cty) 

## [1] 13.5

mean(df_compact$cty)

## [1] 20.12766

혼자서 해보기 3번

mpg <- as.data.frame(ggplot2::mpg) 
mpg %>% filter(manufacturer == "audi") %>%
  arrange(desc(hwy))%>%head(5)

##   manufacturer      model displ year cyl      trans drv cty hwy fl   class
## 1         audi         a4   2.0 2008   4 manual(m6)   f  20  31  p compact
## 2         audi         a4   2.0 2008   4   auto(av)   f  21  30  p compact
## 3         audi         a4   1.8 1999   4   auto(l5)   f  18  29  p compact
## 4         audi         a4   1.8 1999   4 manual(m5)   f  21  29  p compact
## 5         audi a4 quattro   2.0 2008   4 manual(m6)   4  20  28  p compact

혼자서 해보기4번

mpg <- as.data.frame(ggplot2::mpg)
mpg_new <- mpg 
mpg_new <- mpg_new %>% mutate(total = cty + hwy)

mpg_new <- mpg_new %>% mutate(mean = total/2) 

mpg_new %>%
 arrange(desc(mean)) %>% head(3)

##   manufacturer      model displ year cyl      trans drv cty hwy fl      class
## 1   volkswagen new beetle   1.9 1999   4 manual(m5)   f  35  44  d subcompact
## 2   volkswagen      jetta   1.9 1999   4 manual(m5)   f  33  44  d    compact
## 3   volkswagen new beetle   1.9 1999   4   auto(l4)   f  29  41  d subcompact
##   total mean
## 1    79 39.5
## 2    77 38.5
## 3    70 35.0

mpg %>%
 mutate(total = cty + hwy,mean = total/2) %>%
  arrange(desc(mean)) %>%head(3)

##   manufacturer      model displ year cyl      trans drv cty hwy fl      class
## 1   volkswagen new beetle   1.9 1999   4 manual(m5)   f  35  44  d subcompact
## 2   volkswagen      jetta   1.9 1999   4 manual(m5)   f  33  44  d    compact
## 3   volkswagen new beetle   1.9 1999   4   auto(l4)   f  29  41  d subcompact
##   total mean
## 1    79 39.5
## 2    77 38.5
## 3    70 35.0

혼자서 해보기 5번

mpg <- as.data.frame(ggplot2::mpg) 
mpg %>%
 group_by(class) %>% summarise(mean_cty = mean(cty))

## # A tibble: 7 × 2
##   class      mean_cty
##   <chr>         <dbl>
## 1 2seater        15.4
## 2 compact        20.1
## 3 midsize        18.8
## 4 minivan        15.8
## 5 pickup         13  
## 6 subcompact     20.4
## 7 suv            13.5

mpg %>%
 group_by(class) %>%
 summarise(mean_cty = mean(cty)) %>%
 arrange(desc(mean_cty))

## # A tibble: 7 × 2
##   class      mean_cty
##   <chr>         <dbl>
## 1 subcompact     20.4
## 2 compact        20.1
## 3 midsize        18.8
## 4 minivan        15.8
## 5 2seater        15.4
## 6 suv            13.5
## 7 pickup         13

mpg %>%
 group_by(manufacturer) %>% 
 summarise(mean_hwy = mean(hwy)) %>%
 arrange(desc(mean_hwy)) %>%
 head(3)

## # A tibble: 3 × 2
##   manufacturer mean_hwy
##   <chr>           <dbl>
## 1 honda            32.6
## 2 volkswagen       29.2
## 3 hyundai          26.9

mpg %>%
 filter(class == "compact") %>%
 group_by(manufacturer) %>%
 summarise(count = n()) %>%
 arrange(desc(count))

## # A tibble: 5 × 2
##   manufacturer count
##   <chr>        <int>
## 1 audi            15
## 2 volkswagen      14
## 3 toyota          12
## 4 subaru           4
## 5 nissan           2