Group by using time grouper and 1 other column does not work

[namank]

Code Sample, a copy-pastable example if possible

list_of_dicts = [{
    'time': pandas.to_datetime('2016-12-03 18:00:00'),
    'building': 'tall',
    'type': 'steel'
}, {
    'time': pandas.to_datetime('2016-12-03 18:00:00'),
    'building': 'tall',
    'type': 'brick'
}]

df = pandas.DataFrame(list_of_dicts)

  building                time   type
0     tall 2016-12-03 18:00:00  steel
1     tall 2016-12-03 18:00:00  brick
    
    
df = df.groupby(['building', pandas.Grouper(key = 'time', freq = '1D')])

[(<pandas.tseries.resample.TimeGrouper at 0x2b1a5978aed0>,
    building                time   type
1     tall 2016-12-03 18:00:00  brick),
 ('building',
    building                time   type
0     tall 2016-12-03 18:00:00  steel)]

Problem description

Apparently this was fixed in #3794, but I am still seeing this issue. However, this goes away if I add 1 more grouper column to it, which is strange.

df.groupby(['building', pandas.Grouper(key = 'time', freq = '1D'), 'type'])

[(('tall', Timestamp('2016-12-03 00:00:00', offset='D'), 'brick'),
    building                time   type
1     tall 2016-12-03 18:00:00  brick),
 (('tall', Timestamp('2016-12-03 00:00:00', offset='D'), 'steel'),
    building                time   type
0     tall 2016-12-03 18:00:00  steel)]

Expected Output

If I give in the explicit list, it works correctly.

df.groupby([df['building'], pandas.Grouper(key = 'time', freq = '1D')])

[(('tall', Timestamp('2016-12-03 00:00:00', offset='D')),
    building                time   type
0     tall 2016-12-03 18:00:00  steel
1     tall 2016-12-03 18:00:00  brick)]

This should be the expected output by just using 'building' or even pandas.Grouper(key='building').

Output of pd.show_versions()

# Paste the output here pd.show_versions() here INSTALLED VERSIONS ------------------ commit: None python: 2.7.8.final.0 python-bits: 64 OS: Linux OS-release: 2.6.18-164.el5 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8

pandas: 0.15.2
nose: None
Cython: None
numpy: 1.9.0.dev-Unknown
scipy: 0.15.1
statsmodels: None
IPython: 0.13.2
sphinx: 1.3.1
patsy: None
dateutil: 2.4.2
pytz: 2013d
bottleneck: 0.8.0
tables: None
numexpr: None
matplotlib: 1.4.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
rpy2: None
sqlalchemy: None
pymysql: None
psycopg2: None

[jreback]

you are using a pretty old version. IIRC there were some addtiional fixes. try upgrading.