BUG: Using NamedTuples with .iloc fails

[tomaarsen]

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• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
import numpy as np

# A df with two level MultiIndex
df = pd.DataFrame(np.arange(120).reshape(6, -1))

# Indexing with a normal tuple works as expected:
# normal subset
print(df.iloc[1, 2])  # <- Works
print(df.iloc[(1, 2)])  # <- Works

# Now the same with a named tuple
from collections import namedtuple

indexer_tuple = namedtuple("Indexer", ["x", "y"])

# simple subset with named tuple
print(df.iloc[indexer_tuple(x=1, y=2)])  # <- Does not work
# Raises:
# TypeError: Cannot index by location index with a non-integer key
# Converting to a tuple works again
print(df.iloc[tuple(indexer_tuple(x=1, y=2))])  # <- Works

Issue Description

The output of the prior snippet is:

22
22
Traceback (most recent call last):
  File "/workspaces/pandas/#48124.py", line 19, in <module>
    print(df.iloc[indexer_tuple(x=1, y=2)])  # <- Does not work
  File "/workspaces/pandas/pandas/core/indexing.py", line 1074, in __getitem__
    return self._getitem_axis(maybe_callable, axis=axis)
  File "/workspaces/pandas/pandas/core/indexing.py", line 1620, in _getitem_axis
    raise TypeError("Cannot index by location index with a non-integer key")
TypeError: Cannot index by location index with a non-integer key

In short, indexing (with iloc) works with a tuple, but not with a namedtuple.
This issue also persists when using MultiIndex.

See #48124 for a similar issue.

cc @phofl

Expected Behavior

I would expect indexing with a namedtuple to produce the same results as a regular tuple. In short, I would expect the code above to produce:

22
22
22
22

Installed Versions

INSTALLED VERSIONS

commit : 221f636
python : 3.8.13.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.72-microsoft-standard-WSL2
Version : #1 SMP Wed Oct 28 23:40:43 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : C.UTF-8
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.5.0.dev0+1349.g221f6362bc
numpy : 1.22.4
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 65.0.2
pip : 22.2.2
Cython : 0.29.32
pytest : 7.1.2
hypothesis : 6.47.1
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.9.1
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.3
jinja2 : 3.0.3
IPython : 8.4.0
pandas_datareader: 0.10.0
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 0.8.1
fsspec : 2022.7.1
gcsfs : 2022.7.1
matplotlib : 3.5.3
numba : 0.55.2
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : 0.17.6
pyarrow : 8.0.1
pyreadstat : 1.1.9
pyxlsb : 1.0.9
s3fs : 0.6.0
scipy : 1.9.0
snappy :
sqlalchemy : 1.4.40
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.6.0
xlrd : 2.0.1
xlwt : 1.3.0
zstandard : 0.18.0
tzdata : None

[rhshadrach]

Thanks for the report. Looks like this is due to

pandas/pandas/core/indexing.py

Line 1180 in 612823e

if type(key) is tuple:

That check goes back at least 11 years, and likely we should be using isinstance instead. Further investigations and PRs to fix are welcome.

[EltonGohJH]

Can I give this a try?

[Deadlica]

take