Grouping by index and column fails on DataFrame with single index (original) (raw)

Referenced in #5677

Example

The following snippet shows how a MultiIndex DataFrame (df) may be grouped by a combination of a column (B) and a named index level (inner) using a Grouper object.

import pandas as pd import numpy as np

idx = pd.MultiIndex.from_tuples([('a', 1), ('a', 2), ('a', 3), ('b', 1), ('b', 2), ('b', 3)]) idx.names = ['outer', 'inner'] df = pd.DataFrame({"A": np.arange(6), 'B': ['one', 'one', 'two', 'two', 'one', 'one']}, index=idx)

In [1]: df Out[1]: A B outer inner
a 1 0 one 2 1 one 3 2 two b 1 3 two 2 4 one 3 5 one

In [2]: df.groupby(['B', pd.Grouper(level='inner')]).mean() Out [2]: A B inner
one 1 0.0 2 2.5 3 5.0 two 1 3.0 3 2.0

However, when the DataFrame (df2) has only a single index level an AttributeError is thrown

In [3]: df2 = df.reset_index('outer')

In [4]: df2 Out [4]: outer A B inner
1 a 0 one 2 a 1 one 3 a 2 two 1 b 3 two 2 b 4 one 3 b 5 one

In [5]: df2.groupby(['B', pd.Grouper(level='inner')]).mean()

... AttributeError: 'Int64Index' object has no attribute 'labels'

Expected Output

In [2]: df2.groupby(['B', pd.Grouper(level='inner')]).mean() Out [2]: A B inner
one 1 0.0 2 2.5 3 5.0 two 1 3.0 3 2.0

Output of pd.show_versions()

Details

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Darwin
OS-release: 15.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 23.0.0
Cython: 0.24
numpy: 1.11.1
scipy: 0.17.1
statsmodels: 0.6.1
xarray: None
IPython: 4.2.0
sphinx: 1.4.1
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.4
blosc: 1.4.1
bottleneck: 1.1.0
tables: 3.2.2
numexpr: 2.6.0
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.2
lxml: 3.6.0
bs4: 4.4.1
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.40.0
pandas_datareader: None