BUG: to_datetime with out-of-bounds np.datetime64 and errors='ignore' doesn't return input · Issue #50587 · pandas-dev/pandas (original) (raw)

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Description

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

In [4]: to_datetime([np.datetime64('9999-01-01')], errors='ignore')[0] Out[4]: datetime.date(9999, 1, 1)

In [5]: to_datetime([np.datetime64('9999-01-01')], errors='ignore', format='%Y-%m-%d')[0] Out[5]: numpy.datetime64('9999-01-01')

Issue Description

The docs say that with errors='ignore', the input will be returned, but that's not happening here

Expected Behavior

Just return the input

Installed Versions

INSTALLED VERSIONS

commit : 8acd314
python : 3.8.16.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.102.1-microsoft-standard-WSL2
Version : #1 SMP Wed Mar 2 00:30:59 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 2.0.0.dev0+1049.g8acd31495a
numpy : 1.23.5
pytz : 2022.7
dateutil : 2.8.2
setuptools : 65.6.3
pip : 22.3.1
Cython : 0.29.32
pytest : 7.2.0
hypothesis : 6.61.0
sphinx : 5.3.0
blosc : 1.11.1
feather : None
xlsxwriter : 3.0.6
lxml.etree : 4.9.2
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.5
jinja2 : 3.1.2
IPython : 8.8.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 2022.12.0
fsspec : 2022.11.0
gcsfs : 2022.11.0
matplotlib : 3.6.2
numba : 0.56.4
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 10.0.1
pyreadstat : 1.2.0
pyxlsb : 1.0.10
s3fs : 2022.11.0
scipy : 1.10.0
snappy :
sqlalchemy : 1.4.46
tables : 3.8.0
tabulate : 0.9.0
xarray : 2022.12.0
xlrd : 2.0.1
zstandard : 0.19.0
tzdata : 2022.7
qtpy : None
pyqt5 : None
None