Replace NA with grouped means in R? [duplicate]

Answer 1

I slightly changed your example, because the data frame you provided had columns of different lengths, but this should solve your problem:

First, I loaded the packages in tidyverse. Then I grouped data by month. The second pipe runs a mutate_all function so it automatically changes all columns.

library(tidyverse)

df <- tibble(x1 = c(13, NA, 16, 17, 16, 12), x2 = c(1, 4, 3, 5, NA, 4),
             month = c(1, 1, 1, 2, 2, 2))


new_df <- df %>%  group_by(month) %>%
  mutate_all(funs(ifelse(is.na(.), mean(., na.rm = TRUE),.)))

Let me know if this is of any help.

Answer 2

Here is a base R solution using ave, and sapply-ing to each column x1 and x2.

df[1:2] <- sapply(df[1:2], function(x){
  ave(x, df[[3]], FUN = function(.x) {
    .x[is.na(.x)] <- mean(.x, na.rm = TRUE)
    .x
  })
})


df
## A tibble: 6 x 3
#     x1    x2 month
#  <dbl> <dbl> <dbl>
#1  13       1     1
#2  14.5     4     1
#3  16       4     1
#4  17       3     2
#5  16       5     2
#6  12       4     2