Hey Brian,
I was running a backtest on a strategy without problems but out of nowhere I started getting an error. Any idea what it could be?
HTTPError: ('500 Server Error: INTERNAL SERVER ERROR for url: http://houston/zipline/backtests/12%%20Solution?data_frequency=daily&start_date=2008-1-15&end_date=2020-4-6&progress=M', {'status': 'error', 'msg': 'The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().'})
Algorithm support isn’t available through the support forum, but as a general pointer, you need to check the detailed logs for the traceback, which will point you to the line number in your code causing the error, and you can troubleshoot from there.
Pandas follows the numpy convention of raising an error when you try to convert something to a bool. This happens in a if or when using the boolean operations, and, or, or not. It is not clear what the result of.
example
5 == pd.Series([12,2,5,10])
The result you get is a Series of booleans, equal in size to the pd.Series in the right hand side of the expression. So, you get an error. The problem here is that you are comparing a pandas pd.Series with a value, so you'll have multiple True and multiple False values, as in the case above. This of course is ambiguous, since the condition is neither True or False. You need to further aggregate the result so that a single boolean value results from the operation. For that you'll have to use either any or all depending on whether you want at least one (any) or all values to satisfy the condition.
(5 == pd.Series([12,2,5,10])).all()
# False
or
(5 == pd.Series([12,2,5,10])).any()
# True