When applying an aggregation to a grouped pandas DataFrame, the aggregated output appears to contains different values for aggregated all-missing-value-columns, depending on the type of the dataframe column. Below is a minimal example, containing one non-missing-value (an integer, a string and a tuple), one NaN, and one None each: