remove index column in SeriesGroupBy.nlargest

[RainFung]

Code Sample, a copy-pastable example if possible

# Your code here
pdf = pd.DataFrame({
    'a': [1, 1, 1, 2, 2, 2, 3, 3, 3],
    'b': [1, 2, 2, 2, 3, 3, 3, 4, 4]}, columns=['a', 'b'])

pdf.groupby(['a'])['b'].nlargest(1)
a   
1  1    2
2  4    3
3  7    4
Name: b, dtype: int64

Problem description

It raise the index to column(1, 4, 7) above. But we dont need it most time.

Expected Output

pdf.groupby(['a'])['b'].nlargest(1)
a   
1     2
2    3
3    4

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.7.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-693.5.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: zh_CN.utf8
LANG: None
LOCALE: zh_CN.UTF-8

pandas: 0.24.2
pytest: 5.0.1
pip: 18.1
setuptools: 41.0.1
Cython: 0.29.10
numpy: 1.17.0
scipy: 1.1.0
pyarrow: 0.14.1
xarray: None
IPython: 7.2.0
sphinx: 2.1.2
patsy: 0.5.1
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: 1.2.1
tables: 3.5.1
numexpr: 2.6.9
feather: 0.4.0
matplotlib: 3.1.1
openpyxl: 2.6.1
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.8
lxml.etree: 4.2.5
bs4: 4.7.1
html5lib: 1.0.1
sqlalchemy: 1.3.5
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

[TomAugspurger]

I don't think we'll change this. It can be useful, matches the Series.nlargest behavior, and changing it would be API breaking.

If you don't need it then you can drop that level of the index afterwards.