replace NA with groups mean in a non specified number of columns [duplicate]

Answer 1

If you don't mind using dplyr:

library(dplyr)

dat %>% 
  group_by(ID) %>% 
  mutate_if(is.numeric, function(x) ifelse(is.na(x), mean(x, na.rm = TRUE), x))
#> # A tibble: 7 x 5
#> # Groups:   ID [2]
#>      id         ID length width extra
#>   <int>     <fctr>  <dbl> <dbl> <dbl>
#> 1   101 collembola    2.1  0.90     1
#> 2   102       mite    1.5  0.70     3
#> 3   103       mite    1.1  0.80     2
#> 4   104 collembola    1.0  0.70     3
#> 5   105 collembola    1.5  0.50     4
#> 6   106       mite    1.5  0.75     3
#> 7   106       mite    1.9  0.75     4

Answer 2

Try

library(plyr)
impute.mean <- function(x) replace(x, is.na(x), mean(x, na.rm = TRUE))
dat2 <- ddply(dat, ~ ID, transform, length = impute.mean(length),
          width = impute.mean(width), extra = impute.mean(extra))