Comparing pd.Series and getting, what appears to be, unusual results when the series contains None

This is by design:

see the warnings box: http://pandas.pydata.org/pandas-docs/stable/missing_data.html

This was done quite a while ago to make the behavior of nulls consistent, in that they don't compare equal. This puts None and np.nan on an equal (though not-consistent with python, BUT consistent with numpy) footing.

So this is not a bug, rather a consequence of stradling 2 conventions.

I suppose the documentation could be slightly enhanced.

For equality of series containing null values, use pd.Series.equals:

pd.Series(['x', 'y', None]).equals(pd.Series(['x', 'y', None]))  # True