I'm trying to assign NA value in column `RAIN_15`, if any row in `RAIN_15` has value > 100 then all observations corresponding to that `gr` in `RAIN_15` will be replaced by `NA`. Sample data is as given below:

```
   TRGCODE RAIN   DATE    TIME gr RAIN_15
    6155   0.0 2015-06-18 0000 17     0.0
    6155   0.0 2015-06-18 0015 17     0.0
    6155   0.0 2015-06-18 0030 17     0.0
    6155   0.0 2015-06-18 0045 17     0.0
    6155   0.0 2015-06-18 0100 17     0.0
    6155   0.0 2015-06-18 0115 17     0.0
    6155   0.0 2015-06-18 0130 17     0.0
    6155   0.0 2015-06-18 0145 17     0.0
    6155   0.0 2015-06-18 0200 17     0.0
    6155   0.0 2015-06-18 0215 17     0.0
    6155   0.0 2015-06-18 0230 17     0.0
    6155   0.0 2015-06-18 0245 17     0.0
    6155   0.2 2015-06-18 0300 17     0.2
    6155 123.7 2015-06-18 0315 17   123.5
    6155 127.0 2015-06-18 0330 17     3.3
    6155 127.0 2015-06-18 0345 17     0.0
    6155 127.0 2015-06-18 0400 17     0.0
    6155 127.0 2015-06-18 0415 17     0.0
    6155 127.0 2015-06-18 0430 17     0.0
    6155 127.0 2015-06-18 0445 17     0.0
    6155 127.0 2015-06-18 0500 17     0.0
    6155 141.7 2015-06-18 0515 17    14.7
    6155 594.3 2015-06-18 0530 17   452.6
    6155    NA 2015-06-18 0545 17      NA
    6155    NA 2015-06-18 0600 17      NA

```

Data has thousands of such rows where `gr` is group based on `TIME`. Here `RAIN_15` has value > 100, so all observations in `RAIN_15` for corresponding to `gr` 17 should be replaced by `NA`.
I tried with

```
df_v1 <- df %>% group_by(TRGCODE, gr) %>% mutate(RAIN_15 = ifelse(any(RAIN_15 > 100), NA, RAIN_15)) 

```

but it is replacing RAIN\_15 values with 0. If I remove `any` in `ifelse` then it is just replacing values > 100 in `RAIN_15` by NA.