I need to find all the combinations of rows where multiple conditions are met. I tried to use the powerset recipe from itertools and the answer here by adding multiple conditions but can't seem to get the conditions to work properly. The code I've come up with is:
def powerset(iterable):
"powerset([1,2,3]) --> () (1,) (2,) (3,) (1,2) (1,3) (2,3) (1,2,3)"
s = list(iterable)
return chain.from_iterable(combinations(s, r) for r in range(len(s)+1))
df_groups = pd.concat(
[data.reindex(l).assign(Group = n) for n, l in
enumerate(powerset(data.index)) ])
if ((data.loc[l, 'Account'] == 'COS').any() & (data.loc[l,'Amount'].sum() >= 100)
& (data.loc[l,'Account'] == 'Rev').any() & (data.loc[l, 'Amount'].sum() >= 150)
& (data.loc[l,'Account'] == 'Inv').any() and (data.loc[l, 'Amount'].sum() >= 60)))] )
What I'm trying to do above is find only those combinations where the the following thresholds are met/exceeded:
Account Amount COS 150 Rev 100 Inv 60
Sample data:
Entity Account Amount Location A10 Rev 60 A B01 Rev 90 B C11 Rev 80 C B01 COS 90 B C11 COS 80 C A10 Inv 60 A
Apologies in advance for the poor question writing etiquette, its the first time I haven't been able to find an answer on Stackoverflow and have had to ask a question.
Also, aware that this will get very slow as len(data) increases so any suggestions on that end are also greatly appreciated.
