emm, not sure, could take a look, but probably will change few functions as well. This looks indeed a bit complex, but I found out there are quite few issues around it:

1. allow lambda in groupby.agg
2. correctly order different lambda functions and dataset which involves different lambdas on same column, mixed lambda and aggfunc.
3. potentially could remove duplication warning, right now, if gb.agg(a=(col, 'min'), b=(col, 'min')) would raise an error, but gb.agg(a=(col, 'min'), b=(col, lambda x: np.min(x))) won't. Users might actually want to do it, so that they could use b column for other ops while based on np.min result. There is also an error test in test_aggregate.py which could be potentially removed.
   But I will take a look tomorrow to see if I can come up with a simpler version. @TomAugspurger

Hello @charlesdong1991! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

There are currently no PEP 8 issues detected in this Pull Request. Cheers! 🍻

Comment last updated at 2019-08-26 18:03:11 UTC

Hi, @TomAugspurger I simplified the code quite a lot, but still in _normalize_keyword_aggregation because i feel it is better than changing _maybe_mangle_lambdas. Right now, hopefully it wont look too complex. And I also add more complex test cases to prove the lambda works in different scenarios and order of columns is correct. It looks all good locally so feel free to take a look. ^^

wanna give a follow-up review? @TomAugspurger

Thanks!