assignment

혼자서 해보기1

Q1.

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

Q2.

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 해보기2

Q1.

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()

Q2.

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

혼자서 해보기3

Q1.

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

혼자서 해보기4

Q1.

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

한국어 데이터를 이용해 그래프그리기

library(readxl)                 
korean <- read_excel("C:\\Users\\user\\Documents\\20220124\\korean_data_ANSI.xls")                       
ggplot(data = korean, aes(x = gender , y= response)) + geom_boxplot() 

boxplot(korean$response)$stats

##      [,1]
## [1,]    1
## [2,]    1
## [3,]    4
## [4,]    7
## [5,]    7

25% 값: 1 , median: 4 , 75% 값: 7