BUG: to_datetime fails with np.datetime64 and non-ISO format · Issue #50036 · pandas-dev/pandas (original) (raw)

Pandas version checks

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• 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

to_datetime(['2001-01-01', np.datetime64('2020-01-01')], format='%Y-%m-%d') # works to_datetime(['01-01-2001', np.datetime64('2020-01-01')], format='%d-%m-%Y') # errors

Issue Description

the second fails with

ValueError: time data '2020-01-01' does not match format '%d-%m-%Y' (match)

Expected Behavior

both should give

DatetimeIndex(['2001-01-01', '2020-01-01'], dtype='datetime64[ns]', freq=None)

Installed Versions

INSTALLED VERSIONS

commit : a85a386
python : 3.8.15.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+831.ga85a386b78
numpy : 1.23.5
pytz : 2022.6
dateutil : 2.8.2
setuptools : 65.5.1
pip : 22.3.1
Cython : 0.29.32
pytest : 7.2.0
hypothesis : 6.59.0
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.9.1
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.3
jinja2 : 3.0.3
IPython : 8.7.0
pandas_datareader: 0.10.0
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 2022.11.0
fsspec : 2021.11.0
gcsfs : 2021.11.0
matplotlib : 3.6.2
numba : 0.56.4
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.9
pyarrow : 9.0.0
pyreadstat : 1.2.0
pyxlsb : 1.0.10
s3fs : 2021.11.0
scipy : 1.9.3
snappy :
sqlalchemy : 1.4.44
tables : 3.7.0
tabulate : 0.9.0
xarray : 2022.11.0
xlrd : 2.0.1
zstandard : 0.19.0
tzdata : None
qtpy : None
pyqt5 : None
None