Is there a pythonic way to do a contingency table in Pandas?

Question

Given a dataframe that looks like this:

            A   B      
2005-09-06  5  -2  
2005-09-07 -1   3  
2005-09-08  4   5 
2005-09-09 -8   2
2005-09-10 -2  -         


        

Answer 1

Let us call your dataframe data. Try

a = data['A']>0
b = data['B']>0
data.groupby([a,b]).count()