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
import pyarrow as pa

decimal_type = pd.ArrowDtype(pa.decimal128(3, scale=2))

series = pd.Series([1, None], dtype=decimal_type)

pd.to_numeric(series, errors="coerce")

Issue Description

pandas.to_numeric fails to coerce Pyarrow Decimal series that contain NA values due to those NA values getting dropped, leading to an index mismatch:

import pandas as pd
import pyarrow as pa

decimal_type = pd.ArrowDtype(pa.decimal128(3, scale=2))

series = pd.Series([1, None], dtype=decimal_type)

pd.to_numeric(series, errors="coerce")
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[13], line 8
      4 decimal_type = pd.ArrowDtype(pa.decimal128(3, scale=2))
      6 series = pd.Series([1, None], dtype=decimal_type)
----> 8 pd.to_numeric(series, errors="coerce")

File /opt/homebrew/lib/python3.13/site-packages/pandas/core/tools/numeric.py:319, in to_numeric(arg, errors, downcast, dtype_backend)
    316         values = ArrowExtensionArray(values.__arrow_array__())
    318 if is_series:
--> 319     return arg._constructor(values, index=arg.index, name=arg.name)
    320 elif is_index:
    321     # because we want to coerce to numeric if possible,
    322     # do not use _shallow_copy
    323     from pandas import Index

File /opt/homebrew/lib/python3.13/site-packages/pandas/core/series.py:575, in Series.__init__(self, data, index, dtype, name, copy, fastpath)
    573     index = default_index(len(data))
    574 elif is_list_like(data):
--> 575     com.require_length_match(data, index)
    577 # create/copy the manager
    578 if isinstance(data, (SingleBlockManager, SingleArrayManager)):

File /opt/homebrew/lib/python3.13/site-packages/pandas/core/common.py:573, in require_length_match(data, index)
    569 """
    570 Check the length of data matches the length of the index.
    571 """
    572 if len(data) != len(index):
--> 573     raise ValueError(
    574         "Length of values "
    575         f"({len(data)}) "
    576         "does not match length of index "
    577         f"({len(index)})"
    578     )

ValueError: Length of values (1) does not match length of index (2)

This seems to be due to this conversion to a numpy type setting the dtype to object, which causes this condition to be false, which skips re-adding the NA values, leading to a final values array shorter than the original index.

Expected Behavior

I'd expect the series to get converted (to values of decimal.Decimal type, with dtype=object) without raising an exception, preserving the null elements.

Installed Versions

INSTALLED VERSIONS ------------------ commit : 0691c5c python : 3.13.2 python-bits : 64 OS : Darwin OS-release : 24.5.0 Version : Darwin Kernel Version 24.5.0: Tue Apr 22 19:53:27 PDT 2025; root:xnu-11417.121.6~2/RELEASE_ARM64_T6041 machine : arm64 processor : arm byteorder : little LC_ALL : en_CA.UTF-8 LANG : None LOCALE : en_CA.UTF-8

pandas : 2.2.3
numpy : 2.2.2
pytz : 2025.1
dateutil : 2.9.0.post0
pip : 25.0
Cython : None
sphinx : None
IPython : 8.32.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.13.4
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2025.2.0
html5lib : None
hypothesis : 6.125.2
gcsfs : None
jinja2 : 3.1.5
lxml.etree : None
matplotlib : 3.10.3
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 19.0.0
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.15.2
sqlalchemy : 2.0.38
tables : None
tabulate : None
xarray : 2025.1.2
xlrd : None
xlsxwriter : None
zstandard : 0.23.0
tzdata : 2025.1
qtpy : None
pyqt5 : None

Confirmed on main. PRs and investigations are welcome. From a quick look I do think that .dropna() from your link above does cause this issue.

Thanks for raising this!