ENH/BUG groupby nth now filters, works with DataFrames

[hayd]

fixes #5552

partial for #5264

In [101]: df = pd.DataFrame([[1, np.nan], [1, 4], [5, 6]], columns=['A', 'B'])

In [102]: g = df.groupby('A')

In [103]: g.nth(0)
Out[103]:
   A   B
0  1 NaN
2  5   6

In [104]: g.nth(1)
Out[104]:
   A  B
1  1  4

In [105]: g.nth(-1)
Out[105]:
   A  B
1  1  4
2  5  6

In [106]: g.nth(0, dropna='any')  # old behaviour-like
Out[106]:
   B
A
1  4
5  6

In [107]: g.nth(1, dropna='any')  # old behaviour-like
Out[107]:
    B
A
1 NaN
5 NaN

[hayd]

Also note old behaviour was not stable/correct for negative (now fixed with PR&dropna):

In [9]: g.nth(-3,)
Out[9]:
               B
A
1  2.144760e-314
5  2.124748e-314

In [10]: g.B.nth(-3,)
Out[10]:
A
1    2.144760e-314
5    2.144337e-314
Name: B, dtype: float64

[jreback]

If you get around to it; I suspect the new method is MUCH faster than the old, so maybe add a vbench

[hayd]

will append a vbench. Is much faster except when applying to dataframe with dropna (old-style) it's a little slower, but that was previously borked.

Um, obviously there is overlap with first and last methods, they be got with nth(0) and nth(-1) but not tested the differences yet... you reckon these should change too?

[jreback]

yes I think you should blow away first/last code and just alias them to nth(0) and nth(-1).

reminds me that pls put some tests that deal with different types (because first/last have this convert arg..though not sure why)

[jreback]

though maybe nth(0) (first) and (iloc[0]) deserver a fast-path as it doesn't need the machinery of cumcount

[hayd]

there was/is a weird test for types of first/last/nth, I tweaked it a little but is still there...

I can iterate tests over a few of the same df (but with different column types), is that what you mean?

Yea, re fast path (will see how they compare the the cumcount for now)...

[jreback]

hmm.....this should have actually raised a SettingWithCopy (as the test suite sets it to raise)...wierd

[hayd]

Added vbench, is about 40 times faster with not-including the setup of the groupby (which is included in the bench)

[jreback]

awesome!