I'm working on an unbalanced panel dataset. Data came from a game and for every user (`user_id`) in the record I have data for every level (`level`) of the game. As recording data started some time after introduction of the game, for some users I don't have data regarding the first levels, that's why I want to throw them out in a first step.

I've tried the complete.cases-function, but it only excludes the rows with the missing values (NAs), but not data for the whole user with missing values in level 1.

```
panel <- panel[complete.cases(panel), ] 

```

That's why I need a code that excludes every user who has no record in level 1 (which in my dataset means he has an "NA" at one of the dependent variables, i.e. number of activities).

Update #1:
Data looks like this (thanks to thc):

```
> game_data <- data.frame(player = c(1,1,1,2,2,2,3,3,3), level = c(1,2,3,1,2,3,1,2,3), score=c(0,150,170,80,100,110,75,100,0))
> game_data
  player level score
1      1     1     0
2      1     2   150
3      1     3   170
4      2     1    80
5      2     2   100
6      2     3   110
7      3     1    75
8      3     2   100
9      3     3     0

```

I now want to exclude data from player 1, because he has a score of 0 in level 1.