Dropping entire subject if single observation meets criterion in panel data - stata

Question

I have some panel data of the form...
id | amount
-----------
1 | 10
1 | 10
1 | 100
2 | 10
2 | 15
2 | 10
3 | 100
What I'm looking to do seems like it should be fairly simple, but my experience with Stata is limited and I'm used to programming in languages similar to C/Java. Essentially, I want to drop an entire person (id) if any of their individual observations ever exceed a certain amount. So let's say I set this amount to 50, I want to drop all the observations from id 1 and id 3 such that the data will then only contain observations from id 2.
The pseudo-code in Java would be fairly straightforward...
for(int i = 0; i < dataset_length; i++) {
if dataset[i].amount > 50 {
int drop_id = dataset[i].id;
for(int j = 0; j < dataset_length; j++) {
if dataset[j].id == drop_id {
delete observation
}
}
}
}
What would the Stata equivalent of something akin to this be? I'm surely missing something and making it more complicated than it ought to be, but I cannot figure it out.

Answer 1

If there are no missings on amount this is just
bysort id (amount) : drop if amount[_N] > 50
If there are missings, then
gen ismissing = -missing(amount)
bysort id (ismissing amount): drop if amount[_N] > 50 & amount[_N] < .
would be one kind of check, although it's hard to see how the missings could be interesting or useful.
The machinery here (for one introduction see here) in effect builds in a loop over identifiers, and over the observations for each identifier. Literal translation using models from mainstream programming languages could only result in lengthier and less efficient code.