Chapter 3: Lab $Unwind Am I submitting the answer correctly

I’ve taken a look at this lab a few times and even extracted out the data and manually manipulated it in Excel to check my answer so I’m pretty confident I have it right. I can only assume I’m submitting it incorrectly through the interface.
I’ve reversed the sort order on my query so this isn’t the actual answer, but if it was
{ “_id” : “James Lee Miller”, “numFilms” : 1, “average” : 7.1 }
what do I submit as an answer?

Hi @PopeA if you’re absolutely confident that your answer is correct, then the only thing I can see that could be wrong is your quotation mark (“), this is not the same as (").
Suggest you copy the template line provided in the lab and replace the values alone.

You’re right with those characters being different, however in the submission I’m definitely using "
In my first attempt I copied the template line provided and replaced with the correct values.
In my second attempt I added in additional spaces between the field values and the colon as returned through the mongodb shell.
The Heat is on to get it right with my last try.

The answers you provided are most likely inaccurate. I had no problems on my first submission.

Can you see anything in your logic that might be wrong?

The only contentious logic is that I’m not using $trunc due to the version of the database being 4.0.12
As I understand it there is no rounding when using $trunc
So, for instance 1.95 would truncate to 1.9 and not 2.0
The logic is pretty straight forward, even if I flatten out the two arrays first, filter the results then group I get the same answer.

Yes, $trunc just chops off the other digits. What’s the number of films for your 3rd highest cast member?

Third highest is 49 films

That’s a bit low @PopeA.

Right, thanks @007_jb

I actually gave up and submitted another try so I could see the answer, when I ran the query in the solution against my data and I got the same result. Clearly my data is incorrect, I’ll have to go back over the chapters to see where I’ve gone wrong.

Hopefully you won’t need to do that for the remaining labs because the labs count towards your final score.

Do you get 44,497 documents when you run db.movies.count()?

Ha, like now I feel the fool. Somehow I’ve reverted to using a connection to the sample_mflix collection from the labs in M220JS. I confirmed my original aggregate query returned the right answer. Thanks for your help, sorry for wasting your time.