Visualizing missing data

ID<-c(16762,16439,16211,16790,16443,16998,
      16543,16779,16945,16111,16224,16980,
      16779,16000,16111,16224,16400,16327)
Name<-c(NA,NA,"Ibraheem","Fahd",
        "Majeda",NA,"Mohammed","Remas",
        "Rteel","Abdalrhman",NA,"Tala",
        "Remas","Nadiah",NA,"Mhdi",
        "Lila",NA)
Age<-c(30,NA,29,NA,27,9,32,9,NA,29,28,9,
       9,30,NA,28,42,NA )
Sex<-c("M","M","M","M","F","F","M","F",
       "F","M","M","F","F","F","M","M",
       "F","F")

data<-data.frame(ID,Name,Age,Sex)

library(naniar)
library(UpSetR)
vis_miss(data)

gg_miss_upset(data)

gg_miss_var(data)

## Warning: It is deprecated to specify `guide = FALSE` to remove a guide. Please
## use `guide = "none"` instead.

gg_miss_var(data,facet = Sex)

## Warning: It is deprecated to specify `guide = FALSE` to remove a guide. Please
## use `guide = "none"` instead.

gg_miss_case(data)

gg_miss_case(data, facet = Sex)

gg_miss_which(data)