homework

혼자서 해보기 1번

library(ggplot2)
ggplot(data = mpg, aes(x = cty, y = hwy)) + geom_point()

2.

ggplot(data = midwest, aes(x = poptotal, y = popasian)) +
 geom_point() +
 xlim(0, 500000) +
 ylim(0, 10000)

## Warning: Removed 15 rows containing missing values (`geom_point()`).

혼자서 해보기 2번

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

df <- mpg %>%
 filter(class == "suv") %>%
 group_by(manufacturer) %>%
 summarise(mean_cty = mean(cty)) %>%
 arrange(desc(mean_cty)) %>%
 head(5)
ggplot(data = df, aes(x = reorder(manufacturer, -mean_cty),
 y = mean_cty)) + geom_col()

2.

ggplot(data = mpg, aes(x = class)) + geom_bar()

혼자서 해보기 3번

ggplot(data = economics, aes(x = date, y = psavert)) + geom_line()

혼자서 해보기 4번

class_mpg <- mpg %>%
 filter(class %in% c("compact", "subcompact", "suv"))
ggplot(data = class_mpg, aes(x = class, y = cty)) + geom_boxplot()