[BUG] Groupby, Apply

[jlimahaverford]

Code Sample, a copy-pastable example if possible

import pandas as pd
df = pd.DataFrame(dict(a=[0,0,0,1,1,1,2,2,2], b=[0,2,1,3,5,4,7,6,8]))
df

def f(x):
    x['c'] = 1
    return x.sort_values('b')

df.groupby('a', as_index=False).apply(f).reset_index(drop=True)

Expected Output

pd.DataFrame(dict(a=[0, 0, 0, 1, 1, 1, 2, 2, 2], 
                  b=[0, 1, 2, 3, 4, 5, 6, 7, 8], 
                  c=[1, 1, 1, 1, 1, 1, 1, 1, 1]))

output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-87-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 20.7.0
Cython: None
numpy: 1.11.0
scipy: 0.16.0
statsmodels: None
xarray: None
IPython: 4.2.0
sphinx: None
patsy: None
dateutil: 2.4.2
pytz: 2015.4
blosc: None
bottleneck: None
tables: None
numexpr: 2.4.3
matplotlib: None
openpyxl: 2.2.2
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: 2.6 (dt dec pq3 ext lo64)
jinja2: 2.8
boto: None
pandas_datareader: None

[jreback]

dupe of this: #12652

In [7]: def f(x):
   ...:     x = x.copy()
   ...:     x['c'] = 1
   ...:     return x.sort_values('b')
   ...: 

In [8]: df.groupby('a', as_index=False).apply(f).reset_index(drop=True)
Out[8]: 
   a  b  c
0  0  0  1
1  0  1  1
2  0  2  1
3  1  3  1
4  1  4  1
5  1  5  1
6  2  6  1
7  2  7  1
8  2  8  1

you know this is completely inefficient though, right? doing lots of things in groupby is a no-no

In [11]: df.assign(c=1).sort_values('b').reset_index(drop=True)
Out[11]: 
   a  b  c
0  0  0  1
1  0  1  1
2  0  2  1
3  1  3  1
4  1  4  1
5  1  5  1
6  2  6  1
7  2  7  1
8  2  8  1