Description
Code Sample, a copy-pastable example if possible
Setup:
In [2]: ii = pd.interval_range(0, 4)
In [3]: df = pd.DataFrame(np.arange(12).reshape(4, 3), index=ii, columns=list('ABC'))
In [4]: df
Out[4]:
A B C
(0, 1] 0 1 2
(1, 2] 3 4 5
(2, 3] 6 7 8
(3, 4] 9 10 11Scalar and Interval objects raise an AttributeError:
In [5]: df.loc[0.5, 'A']
---------------------------------------------------------------------------
AttributeError: 'pandas._libs.interval.IntervalTree' object has no attribute 'get_value'
In [6]: df.loc[pd.Interval(0, 1), 'A']
---------------------------------------------------------------------------
AttributeError: 'pandas._libs.interval.IntervalTree' object has no attribute 'get_value'It works fine if column labels aren't passed, or if a list-like is passed:
In [7]: df.loc[0.5]
Out[7]:
A 0
B 1
C 2
Name: (0, 1], dtype: int32
In [8]: df.loc[pd.Interval(0, 1)]
Out[8]:
A 0
B 1
C 2
Name: (0, 1], dtype: int32
In [9]: df.loc[0.5, ['A']]
Out[9]:
A 0
Name: (0, 1], dtype: int32
In [10]: df.loc[pd.Interval(0, 1), ['B', 'C']]
Out[10]:
B 1
C 2
Name: (0, 1], dtype: int32Problem description
Indexing with loc fails.
Expected Output
I'd expect loc to return the appropriate value.
Output of pd.show_versions()
INSTALLED VERSIONS
commit: 0bfb61b
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.23.0.dev0+422.g0bfb61b
pytest: 3.1.2
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.13.3
scipy: 1.0.0
pyarrow: 0.6.0
xarray: 0.9.6
IPython: 6.1.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: 3.4.2
numexpr: 2.6.4
feather: 0.4.0
matplotlib: 2.0.2
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 0.9.8
lxml: 3.8.0
bs4: None
html5lib: 0.999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: 0.1.0
pandas_gbq: None
pandas_datareader: None