Finally! I use pandas all the time particularly for handling strings (dna/aa sequences), and tuples (often nested). Some of the most annoying bugs I encounter in my code are a result of random dtype changes in pandas. Things like it auto-converting str -> np.string (which is NOT a string) during pivot operations.
There's also all types of annoying workarounds you have to do while tuples as indexes resulting from it converting to a MultiIndex. For example
srs = pd.Series({('a'):1,('b','c'):2})
is a len(2) Series. srs.loc[('b','c')] throws an error while srs.loc[('a')] and srs.loc[[('b','c')]] do not. Not to vent my frustrations, but this maybe gives an idea of why this change is important and I very much look forward to improvements in the area!
There's also all types of annoying workarounds you have to do while tuples as indexes resulting from it converting to a MultiIndex. For example
srs = pd.Series({('a'):1,('b','c'):2})
is a len(2) Series. srs.loc[('b','c')] throws an error while srs.loc[('a')] and srs.loc[[('b','c')]] do not. Not to vent my frustrations, but this maybe gives an idea of why this change is important and I very much look forward to improvements in the area!