Hyukjin Kwon

This is likely because of default index, see also https://koalas.readthedocs.io/en/latest/user_guide/best_practices.html#use-distributed-or-distributed-sequence-default-index

If performing Koalas' `transpose` is expensive, we should switch it to pandas'. The results to transpose is small so I wonder how it makes it slow though.

Yeah, object type is not supported.

Can you show the types of your DataFrame? It's possible that your DataFrame does not have any numeric types: ```python >>> df = ks.DataFrame({'a': ["a", "b", "c"]}) >>> df.describe() Traceback...

It works in pandas so we should probably fix too.

Oh hm.. should I close #419 for now?

Hey @jreback. Thanks for some input here :-). Sounds like user defined type which PySpark has as well (but similarly rather internal and experimental). `pyarrow` has nested types, yes but...

Ah, thanks for details. I look forward that project to be public. One problem we face is that currently the data itself, for instance, a `pandas` instance is purely transferred...

That would be nice to have it! I wonder how the types will be handled when they are roundtriped in non-Python ends (JVM for instance because that's what we do)....

@beobest2 can you fix the test?