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pandas-dev / pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
https://pandas.pydata.org
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BUG: pd.to_numeric(timedelta_scalar) raises TypeError #59944

Open sfc-gh-mvashishtha opened 2 hours ago

sfc-gh-mvashishtha commented 2 hours ago

Pandas version checks

Reproducible Example

import pandas as pd

pd.to_numeric(pd.Timedelta(1))

Issue Description

Getting a TypeError

Expected Behavior

For the example above, I should get the integer 1. That would match the behavior of pd.to_numeric(pd.Series(pd.Timedelta(1)))

Installed Versions

``` INSTALLED VERSIONS ------------------ commit : 0691c5cf90477d3503834d983f69350f250a6ff7 python : 3.9.18 python-bits : 64 OS : Darwin OS-release : 23.6.0 Version : Darwin Kernel Version 23.6.0: Wed Jul 31 20:48:52 PDT 2024; root:xnu-10063.141.1.700.5~1/RELEASE_ARM64_T6020 machine : arm64 processor : arm byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 2.2.3 numpy : 1.26.3 pytz : 2023.3.post1 dateutil : 2.8.2 pip : 23.3.1 Cython : None sphinx : None IPython : 8.18.1 adbc-driver-postgresql: None adbc-driver-sqlite : None bs4 : None blosc : None bottleneck : None dataframe-api-compat : None fastparquet : None fsspec : None html5lib : None hypothesis : None gcsfs : None jinja2 : None lxml.etree : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None psycopg2 : None pymysql : None pyarrow : None pyreadstat : None pytest : 8.3.2 python-calamine : None pyxlsb : None s3fs : None scipy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlsxwriter : None zstandard : None tzdata : 2023.4 qtpy : None pyqt5 : None ```
rhshadrach commented 2 hours ago

Thanks for the report, confirmed on main. With a Series, to_numeric has logic for NumPy dtypes "mM" to handle this case, but there is no corresponding logic for scalars. Further investigations and PRs to fix are welcome!