# install.packages(c("readxl","ggplot2","dplyr"))
library(readxl)
library(ggplot2)
library(dplyr)
library(ggplot2)
mpg <- as.data.frame(ggplot2 :: mpg)
mpg[c(10,14,58, 93), "drv"] <- "k"
mpg[c(29, 43, 129, 203), "cty"] <- c(3,4,39, 42)
You can also embed plots, for example:
table(mpg$drv)
##
## 4 f k r
## 100 106 4 24
library(dplyr)
mpg$drv <- ifelse(mpg$drv %in% c("4","f","r"), mpg$drv, NA)
table(mpg$drv)
##
## 4 f r
## 100 106 24
boxplot(mpg$cty)
boxplot(mpg$cty)$stats
## [,1]
## [1,] 9
## [2,] 14
## [3,] 17
## [4,] 19
## [5,] 26
값을 볼 수 있게 더해주기
9에서 26 사이 아니면 이상 값
mpg$cty <- ifelse(mpg$cty <9 | mpg$cty >26, NA, mpg$cty)
boxplot(mpg$cty)
##문제 3
library(dplyr)
mpg %>%
filter(!is.na(drv) & !is.na(cty)) %>%
group_by(drv) %>%
summarise(mean_cty = mean(cty))
## # A tibble: 3 × 2
## drv mean_cty
## <chr> <dbl>
## 1 4 14.2
## 2 f 19.5
## 3 r 14.0