1022-2

data("airquality")
names(airquality)

## [1] "Ozone"   "Solar.R" "Wind"    "Temp"    "Month"   "Day"

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

names(airquality)<-tolower(names(airquality))
table(is.na(airquality))

## 
## FALSE  TRUE 
##   874    44

table(is.na(airquality$ozone))

## 
## FALSE  TRUE 
##   116    37

summary(is.na(airquality))

##    ozone          solar.r           wind            temp        
##  Mode :logical   Mode :logical   Mode :logical   Mode :logical  
##  FALSE:116       FALSE:146       FALSE:153       FALSE:153      
##  TRUE :37        TRUE :7                                        
##    month            day         
##  Mode :logical   Mode :logical  
##  FALSE:153       FALSE:153      
## 

sum(airquality$ozone)

## [1] NA

mean(airquality$ozone)

## [1] NA

sum(airquality$ozone, na.rm=TRUE)

## [1] 4887

mean(airquality$ozone, na.rm=TRUE)

## [1] 42.12931

airquality<-na.omit(airquality)
table(is.na(airquality))

## 
## FALSE 
##   666

names(airquality)<-tolower(names(airquality))
airquality %>% filter(!is.na(ozone)) %>% head(3)

##   ozone solar.r wind temp month day
## 1    41     190  7.4   67     5   1
## 2    36     118  8.0   72     5   2
## 3    12     149 12.6   74     5   3

airquality %>% filter(!is.na(ozone)&!is.na(solar.r)) %>% head(3)

##   ozone solar.r wind temp month day
## 1    41     190  7.4   67     5   1
## 2    36     118  8.0   72     5   2
## 3    12     149 12.6   74     5   3

airquality$ozone <- ifelse(is.na(airquality$ozone), 42.0991, airquality$ozone)
table(is.na(airquality$ozone))

## 
## FALSE 
##   111

ott7 <- data.frame(gender=c("1","1","2","2","2","3"), income=c(200,250,200,300,200,150))
summary(ott7)

##     gender              income     
##  Length:6           Min.   :150.0  
##  Class :character   1st Qu.:200.0  
##  Mode  :character   Median :200.0  
##                     Mean   :216.7  
##                     3rd Qu.:237.5  
##                     Max.   :300.0

table(ott7$gender)

## 
## 1 2 3 
## 2 3 1

boxplot(iris$Sepal.Width)$stats

##      [,1]
## [1,]  2.2
## [2,]  2.8
## [3,]  3.0
## [4,]  3.3
## [5,]  4.0