Pandas version checks
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[X] I have checked that this issue has not already been reported.
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[X] I have confirmed this bug exists on the latest version of pandas.
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[X] 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
Comment From: 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
Comment From: 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
Comment From: 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?
Comment From: 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.
Comment From: 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?
Comment From: 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
?
Comment From: 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
Comment From: 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
Comment From: ABCPAN-rank
take