BUG: Discrepancy between .is_numeric() and is_numeric_dtype for bool Index

[jrbourbeau]

Pandas version checks

• 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.

Reproducible Example

import pandas as pd
from pandas.api.types import is_numeric_dtype

idx = pd.Index([True], dtype=bool)

print(f"{idx.is_numeric() = }")
print(f"{is_numeric_dtype(idx) = }")

Issue Description

With the latest nightly wheel of pandas, the following deprecation message is given

FutureWarning: Index.is_numeric is deprecated. Use pandas.api.types.is_numeric_dtype instead

However, when accounting for this deprecation over in dask/dask, we observed that is_numeric() and is_numeric_dtype don't give the same result for and Index with bool data

Expected Behavior

I'd expect these to both give the same answer

Installed Versions

INSTALLED VERSIONS
------------------
commit           : f06c96a93fb2e21c9f801192d9ed5896c5ce3535
python           : 3.10.4.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 22.2.0
Version          : Darwin Kernel Version 22.2.0: Fri Nov 11 02:08:47 PST 2022; root:xnu-8792.61.2~4/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 2.0.0.dev0+1401.gf06c96a93f
numpy            : 1.24.1
pytz             : 2022.1
dateutil         : 2.8.2
setuptools       : 59.8.0
pip              : 22.0.4
Cython           : None
pytest           : 7.1.3
hypothesis       : None
sphinx           : 4.5.0
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 3.1.2
IPython          : 8.2.0
pandas_datareader: None
bs4              : 4.11.1
bottleneck       : None
brotli           :
fastparquet      : 2022.12.1.dev6
fsspec           : 2023.1.0+5.g012816b
gcsfs            : None
matplotlib       : 3.5.1
numba            : None
numexpr          : 2.8.0
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 11.0.0.dev316
pyreadstat       : None
pyxlsb           : None
s3fs             : 2022.10.0
scipy            : 1.9.0
snappy           :
sqlalchemy       : 1.4.35
tables           : 3.7.0
tabulate         : None
xarray           : 2022.3.0
xlrd             : None
zstandard        : None
tzdata           : None
qtpy             : None
pyqt5            : None

[phofl]

Hi, thanks for your report. I think the best suited function is not public right now. is_any_numeric_dtype is equivalent to is_numeric. @mroeschke do you know why this is private? Documentation looks like It could be public

[mroeschke]

Not sure, guessing is_any_numeric_dtype was more of a helper function initially so it was never made public. Could either make it public of add a keyword to is_numeric_dtype to include boolean

[phofl]

We would have to exclude complex as well, which would make the keyword name awkward I guess (or add 2, but not nice either).

Having said that, is_any_numeric_dtype is not a great name either. We could rename to is_any_real_numeric_dtype before making it public?

[ABCPAN-rank]

Hi I deprecate is_numeric . This is my first taste in contribution . I think is_any_numeric_dtype is a helpful function so it isn’t public. You can click here DEPR: deprecate Index.is_numeric #50769 for more information about it.

[phofl]

Ah thx, should have checked the git info.

Reading through the discussion, I think is_any_real_numeric_dtype() makes more sense, since it excludes complex numbers as you mentioned there.

Would you be interested in making a pr to rename and make public?

[ABCPAN-rank]

Yes, i'm interested in doing it. But I am a novice in contribution. If I want to make function public, what should I do ? Writing test for is_any_real_numeric_dtype and updating whatsnew ?

[ABCPAN-rank]

And I think is_real_dtype is a good name about the function . Because the same function which check number type is called is_xxx_dtype

[phofl]

I prefer is_any_real_numeric_dtype, is_real_dtype could mean anything, if the user is not aware that we are talking about numeric data.

• add a whatsnew
• add your function to pandas/core/dtypes/api.py
• change your FutureWarning to point to the new function
• add to section Partially validate docstrings (EX02) in ci/code_checks.sh
• add to Data type introspection in doc/source/reference/arrays.rst
• adding tests would be good as well

[ABCPAN-rank]

take