I have this data below. I would like to impute the large value of income by 10 times the value of the median.
This is done using the following code:

```
df$income_imputed = ifelse(df$income > (10* median(df$income,na.rm = T)), (10* median(df$income,na.rm = T)), df$income)

```

However, i would like to do that for each country and year separately and not to the whole dataset. I know `group_by` could be helpful with such tasks, but i am not sure how to include both functions together.

```
    country  year   income
     <dbl> <dbl>    <dbl>
 1       1  1999     5000
 2       1  1999     5000
 3       1  1999 10000000
 4       1  1999     3000
 5       1  2000     4000
 6       1  2000     4000
 7       1  2000 20000000
 8       1  2000     4000
 9       2  1999    10000
10       2  1999    10000
11       2  1999 30000000
12       2  1999     4000
13       2  2000    12000
14       2  2000    12000
15       2  2000 40000000

df= structure(list(country = c(1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 
2, 2, 2), year = c(1999, 1999, 1999, 1999, 2000, 2000, 2000, 
2000, 1999, 1999, 1999, 1999, 2000, 2000, 2000), income = c(5000, 
5000, 1e+07, 3000, 4000, 4000, 2e+07, 4000, 10000, 10000, 3e+07, 
4000, 12000, 12000, 4e+07), income2 = c(5000, 5000, 1e+05, 3000, 
4000, 4000, 1e+05, 4000, 10000, 10000, 1e+05, 4000, 12000, 12000, 
1e+05)), row.names = c(NA, -15L), class = c("tbl_df", "tbl", 
"data.frame"))

```