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rdataframenamissing-data

Randomly insert NAs into dataframe proportionaly

I have a complete dataframe. I want to 20% of the values in the dataframe to be replaced by NAs to simulate random missing data. 

A <- c(1:10)
B <- c(11:20)
C <- c(21:30)
df<- data.frame(A,B,C)

Can anyone suggest a quick way of doing that?

Solution 
  • df <- data.frame(A = 1:10, B = 11:20, c = 21:30)
head(df)
##   A  B  c
## 1 1 11 21
## 2 2 12 22
## 3 3 13 23
## 4 4 14 24
## 5 5 15 25
## 6 6 16 26

as.data.frame(lapply(df, function(cc) cc[ sample(c(TRUE, NA), prob = c(0.85, 0.15), size = length(cc), replace = TRUE) ]))
##     A  B  c
## 1   1 11 21
## 2   2 12 22
## 3   3 13 23
## 4   4 14 24
## 5   5 NA 25
## 6   6 16 26
## 7  NA 17 27
## 8   8 18 28
## 9   9 19 29
## 10 10 20 30

    It's a random process, so it might not give 15% every time.