Having trouble writing a query where I can get the top 10 of a top 10 based on a count
My starting table from this query:
top_10_cars = 'CH', 'DA', 'AG', 'DC', 'LA', 'NY', 'SA', 'SE', 'DE', 'MI'
df = pd.read_sql("select\
count(*) as count\
,ID\
,CAR\
from "+db+"\
where pop in ('"+ "','".join(top_10_cars) +"')\
group by\
pop\
,asn\
order by reqs desc\
",conn)
Result is a list with all the IDs for every car grouping sorted by count:
Count ID CAR
67210048 7922 CH
2081655 20001 LA
488850583 7018 AG
567585985 7018 DA
450991 7922 SA
41123124 7018 CH
4135532 11427 DA
...
..
.
The dataframe above is too big. I only one that top 10 Ids for each car.
For example CH:
Count ID CAR
67210048 7922 CH
25100548 7546 CH
465100 8542 CH
67254828 5622 CH
1251048 3522 CH
...
..
.
The resulting table should look like this
Count ID CAR
67210048 7922 CH
25100548 7546 CH
..
.
7210048 1546 DA
251005 5678 DA
25100548 7546 DA
465100 8542 DA
...
..
67254828 5622 DA
and
so
on.. 'AG', 'DC', 'LA', 'NY', 'SA', 'SE', 'DE', 'MI'