groupby.rank 'na_option="bottom"' Usage Clarification

[peterpanmj]

Code Sample, a copy-pastable example if possible

In [1]: import pandas as pd
   ...: import numpy as np
   ...: df = pd.DataFrame({'val': [2, np.nan, 2, 8, 2, np.nan, 6]})
   ...: df["key"] = pd.Series(["foo"]*7)

In [2]: df
Out[2]:
   val  key
0  2.0  foo
1  NaN  foo
2  2.0  foo
3  8.0  foo
4  2.0  foo
5  NaN  foo
6  6.0  foo

In [5]: df.groupby("key").rank(na_option="not bottom")
Out[5]:
   val
0  2.0
1  6.5
2  2.0
3  5.0
4  2.0
5  6.5
6  4.0

Problem description

When an invalid value is passed to groupby.rank for na_option argument. It didn't raise a ValueError as expected. The same behavior will raise a ValueError("na_option must be one of 'keep', 'top', or 'bottom'") in DataFrame.rank or Series.rank
The expected output is derived from #19499

Expected Output

In [1]: import pandas as pd
   ...: import numpy as np
   ...: df = pd.DataFrame({'val': [2, np.nan, 2, 8, 2, np.nan, 6]})
   ...: df["key"] = pd.Series(["foo"]*7)
   ...:

In [2]: df.rank(na_option="no bottom")
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-2-ec2afc565a7d> in <module>()
----> 1 df.rank(na_option="no bottom")

C:\Users\Public\pandas-peter\pandas\core\generic.py in rank(self, axis, method,
numeric_only, na_option, ascending, pct)
   7523         if na_option not in {'keep', 'top', 'bottom'}:
   7524             msg = "na_option must be one of 'keep', 'top', or 'bottom'"
-> 7525             raise ValueError(msg)
   7526
   7527         def ranker(data):

ValueError: na_option must be one of 'keep', 'top', or 'bottom'

Output of pd.show_versions()

INSTALLED VERSIONS

commit: d30c4a0
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: zh_CN.UTF-8
LOCALE: None.None

pandas: 0.24.0.dev0+377.gd30c4a069
pytest: 3.3.2
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.28.4
numpy: 1.14.0
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.6.7
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.1.2
openpyxl: 2.4.10
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.1
pymysql: 0.7.11.None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None