[R] missing and replace

[Ng Bo Lin]

Hi Val,

You could do this by nesting 2 for loops, and defining a function such that it returns the mean of the column when the value is ‘NA’.

df1 <- data.frame(x = c(25, 30, 40, 26, 60), y = c(122, 135, NA, 157, 195), z = c(352, 376, 350, NA, 360)); df2 <- df1[0, ]

means <- sapply(df1, mean, na.rm = T); return_mean_if_NA <- function(x, y) { if (is.na(x)){ x <- y } else { return(x) } }

for (i in 1:ncol(df1)){
        for (j in 1:nrow(df1)){
                df2[j, i] <- return_mean_if_NA(df1[j, i], means[i])
        }
}


Hope this helps!

Regards,
Bo Lin

> On 27 Apr 2017, at 8:45 AM, Val <valkremk at gmail.com> wrote:
> 
> HI all,
> 
> I have a data frame with three variables. Some of the variables do
> have missing values and I want to replace those missing values
> (1represented by NA) with the mean value of that variable. In this
> sample data,  variable z and y do have missing values. The mean value
> of y  and z are152. 25  and 359.5, respectively . I want replace those
> missing values  by the respective mean value ( rounded to the nearest
> whole number).
> 
> DF1 <- read.table(header=TRUE, text='ID1 x y z
> 1  25  122    352
> 2  30  135    376
> 3  40   NA    350
> 4  26  157    NA
> 5  60  195    360')
> mean x= 36.2
> mean y=152.25
> mean z= 359.5
> 
> output
> ID1  x  y  z
> 1   25 122   352
> 2   30 135   376
> 3   40 152   350
> 4   26 157   360
> 5   60 195   360
> 
> 
> Thank you in advance
> 
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