I have a test dataframe `df` from which I want to drop duplicate values in the `Hits` column but not the rows associated with the duplicate values. The condition however is that the dropping is to be done only in some specific ranges of row indices.

```
df <- data.frame(
  Hits = c("#a", "#ID:987129470", "#b", "Hit1", "Hit1", "Hit2", "Hit3", "Hit3", "#a", "#ID:6971324987", "#b", "Hit1", "Hit2", "Hit2", "Hit3"),
  Category1 = c(NA, NA, NA, 0.001, 0.001, 0.002, 0.003, 0.003, NA, NA, NA, 0.023, 0.341, 0.341, 0.569),
  Category2 = c(NA, NA, NA, 100, 100, 99, 98, 98, NA, NA, NA, 100, 95, 95, 97),
  Category3 = c(NA, NA, NA, 100, 100, 99, 98, 98, NA, NA, NA, 98, 97, 97, 92))

```

`df` looks like this

[![enter image description here](https://i.stack.imgur.com/DaFqf.png)](https://i.stack.imgur.com/DaFqf.png)

The ranges of row indices in which the dropping operation is to be carried out are `4:8` and `12:15` in this case. Basically, the duplicate hits under each ID are to be dropped, keeping the associated values in the other columns intact. The output should look something like this

[![enter image description here](https://i.stack.imgur.com/SL3oz.png)](https://i.stack.imgur.com/SL3oz.png)

In the original dataframe (which has ~100k rows!) it is not possible to specify the ranges. How do I solve this issue?