lets say, we use the dataframe mtcars and I would like to add the column qsec_control which is calculated as the mean(qsec) of all rows that don’t have the same cyl as the current row (e.g. if cyl == 6, it would take mean(qsec[cyl != 6]) ).
The question feels somewhat dumb, but I cant figure out how to do this.

Thanks in advance

>Solution :

This solution groups by cyl, then uses dplyr::cur_group_rows() to index into mtcars$qsec:

library(dplyr)

mtcars %>%
  group_by(cyl) %>%
  mutate(
    qsec_control = mean(mtcars$qsec[-cur_group_rows()])
  ) %>%
  ungroup()

# A tibble: 32 × 12
     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb qsec_cont…¹
   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>       <dbl>
 1  21       6  160    110  3.9   2.62  16.5     0     1     4     4        17.8
 2  21       6  160    110  3.9   2.88  17.0     0     1     4     4        17.8
 3  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1        17.2
 4  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1        17.8
 5  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2        18.7
 6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1        17.8
 7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4        18.7
 8  24.4     4  147.    62  3.69  3.19  20       1     0     4     2        17.2
 9  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2        17.2
10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4        17.8
# … with 22 more rows, and abbreviated variable name ¹​qsec_control