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match format '%d-%m-%y' format='%y-%m-%d' format='%d-%m-%y' dtype='datetime64[ns]' personal information bug comment metadata assignees type projects time data '2020-01-01' latest version bug exists triage issue projects milestone pandas bug issue main branch expected behavior give datetimeindex milestone relationships to_datetime fails github match to_datetime fails datetime64 sign skip jump np checked reported confirmed reproducible valueerror freq= reviewed removed free join conversation account development branches share

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      headline:BUG: to_datetime fails with np.datetime64 and non-ISO format
      articleBody:### Pandas version checks - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [X] I have confirmed this bug exists on the main branch of pandas. ### Reproducible Example ```python 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 <details> INSTALLED VERSIONS ------------------ commit : a85a386b780856842dd81155f7ea066df5ccca6d 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 </details>
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      headline:BUG: to_datetime fails with np.datetime64 and non-ISO format
      articleBody:### Pandas version checks - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [X] I have confirmed this bug exists on the main branch of pandas. ### Reproducible Example ```python 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 <details> INSTALLED VERSIONS ------------------ commit : a85a386b780856842dd81155f7ea066df5ccca6d 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 </details>
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