I have data with about 250 columns. A sample looks a bit like below:

| shop1\_freq | shop1\_enj | shop2\_freq | shop2\_enj |
| --- | --- | --- | --- |
| 0 | 9 | 3 | 6 |
| 999 | 9 | 2 | 1 |
| 3 | 2 | 999 | 2 |
| 4 | 1 | 3 | 4 |

I want to remove rows (which represent participants) if they have "999" scored in *any* column because this represents an incorrect response. I have tried some simple code below, but this does not work.

```
data %>%
  filter_all(!= 999)

```

A score of 999 is only possible from about column 67 to 167, but I thought it would be easier to just specify in the code across all columns in the data.

Are there any better approaches to this?