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Showing content from https://github.com/pandas-dev/pandas/issues/49521 below:

.iloc requires numeric indexers, got [0 1 2 3] · Issue #49521 · pandas-dev/pandas · GitHub

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

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

>>> df = pd.DataFrame([[0,1,2,3,4],[5,6,7,8,9]])
>>> df.iloc[:, pd.Series([0,1,2,3], dtype = pd.Int64Dtype())]
IndexError: .iloc requires numeric indexers, got [0 1 2 3]

# From stack trace
#    1475 # check that the key has a numeric dtype
#    1476 if not is_numeric_dtype(arr.dtype):
# -> 1477     raise IndexError(f".iloc requires numeric indexers, got {arr}")
#    1479 # check that the key does not exceed the maximum size of the index
#    1480 if len(arr) and (arr.max() >= len_axis or arr.min() < -len_axis):

>>> df.iloc[:, pd.Series([0,1,2,3])]
# Works

# Check dtypes. Note int64 vs Int64Dtype
>>> pd.Series([0,1,2,3]).dtype                                 
dtype('int64')                                                                         
>>> pd.Series([0,1,2,3], dtype = pd.Int64Dtype()).dtype        
Int64Dtype()

# Series.iloc works
pd.Series([1,2,3,4,5,6]).iloc[pd.Series([0,1,2,3], dtype = pd.Int64Dtype())]

Pandas.DataFrame.iloc doesn't understand that Pandas pd.Int64Dtype is numeric, and refuses to index with it.
Pandas.Series.iloc works.

That pd.DataFrame.iloc would recognise that pd.Int64Dtype is numeric and correctly index with it.

commit : 91111fd
python : 3.9.6.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.16.3-microsoft-standard-WSL2
Version : #1 SMP Fri Apr 2 22:23:49 UTC 2021
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.5.1
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
setuptools : 58.3.0
pip : 22.3
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 8.5.0
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.5.1
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None

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