The problem that occurred to me is due to inconsistent types outputted by for values, match_df in df.groupby(names) - if names is a list of length >1, then values can be a tuple. Otherwise it's an element type, which can be e.g. string.
I had a bug where I iterating over values resulted in going over characters of a string, together with zip it just discarded most of the field.
Whenever df.groupby is called with a list, output a tuple of values found. Specifically when called with a list of length 1, output a tuple of length 1 instead of unwrapped element.
API breaking implicationsThis would change how existing code behaves.
Describe alternatives you've consideredLeave things as they are. Unfortunately it means people need to write special case handling ifs around groupby to get consistent types outputted.
Additional contextimport pandas as pd
df = pd.DataFrame(columns=['a','b','c'], index=['x','y'])
df.loc['y'] = pd.Series({'a':1, 'b':5, 'c':2})
print(df)
values, _ = next(iter(df.groupby(['a', 'b'])))
print(type(values)) # <class 'tuple'>
values, _ = next(iter(df.groupby(['a'])))
print(type(values)) # <class 'int'> # IMHO should be 'tuple'!
values, _ = next(iter(df.groupby('a')))
print(type(values)) # <class 'int'>
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