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Keywords {🔍}

datetime, marcogorelli, pandas, objects, format, aaossa, issue, lines, pdtodatetime, iresulti, sign, pull, requests, type, member, commented, pandaspandascoretoolsdatetimespy, bbbcdf, res, skip, projects, bug, description, functionality, data, added, dtype, fmt, npynat, continue, navigation, solutions, actions, security, fail, parsing, pydatetime, feature, existing, date, columns, import, parse, pdtodatetimes, exception, match, datetimedatetime, alternative, enhancement, triage,

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pandas/pandas/core/tools/datetimes pandas/pandas/_libs/tslibs/strptime marcogorelli edits member pandas/_libs/tslibs/strptime /pandas/_libs/tslibs/strptime personal information bug datetime import datetime datetime objects differently reading excel files comment metadata assignees skip datetime objects type projects parsing pydatetime objects alternative solutions ndarray[object] values /python/cpython/issues/59648 import pandas pyx index 6287c2fbc5 bint exact=true datetime objects triage issue projects milestone parsed datetime handle datetime datetime cimport tz=tz format datetime type timestamp objects implementation dayfirst=true issue wrong results alternative solution raw loop element individually additional context make sense unit=unit yearfirst=yearfirst correct place directly construct diff --git processing applied year = year month = month day = day hour = hour min = minute proper tests

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DiscussionForumPosting:
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      headline:BUG: Do not fail when parsing pydatetime objects in pd.to_datetime
      articleBody:### Feature Type - [ ] Adding new functionality to pandas - [X] Changing existing functionality in pandas - [ ] Removing existing functionality in pandas ### Problem Description When reading excel files I often get date columns looking like ``` python import pandas as pd from datetime import datetime s = pd.Series(["01/02/01", datetime(2001, 2, 2)]) ``` When trying to parse those columns using ``` pd.to_datetime(s, format="%d/%m/%y") ``` the Exception `ValueError("time data '2001-02-02 00:00:00' does not match format '%d/%m/%y' (match)")` is raised. The origin of this issue is that the already parsed `datetime` is converted to a string in isoformat and then an attempt to parse it in the given format is made. Using `pd.to_datetime` without a format leads to wrong results since the format is ambiguous. ### Feature Description `pd.to_datetime` should either get an option to handle `datetime.datetime` objects differently or do so by default. ### Alternative Solutions The only alternative solution I could think off currently is a raw loop and checking the type of each element individually. ### Additional Context _No response_
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      headline:BUG: Do not fail when parsing pydatetime objects in pd.to_datetime
      articleBody:### Feature Type - [ ] Adding new functionality to pandas - [X] Changing existing functionality in pandas - [ ] Removing existing functionality in pandas ### Problem Description When reading excel files I often get date columns looking like ``` python import pandas as pd from datetime import datetime s = pd.Series(["01/02/01", datetime(2001, 2, 2)]) ``` When trying to parse those columns using ``` pd.to_datetime(s, format="%d/%m/%y") ``` the Exception `ValueError("time data '2001-02-02 00:00:00' does not match format '%d/%m/%y' (match)")` is raised. The origin of this issue is that the already parsed `datetime` is converted to a string in isoformat and then an attempt to parse it in the given format is made. Using `pd.to_datetime` without a format leads to wrong results since the format is ambiguous. ### Feature Description `pd.to_datetime` should either get an option to handle `datetime.datetime` objects differently or do so by default. ### Alternative Solutions The only alternative solution I could think off currently is a raw loop and checking the type of each element individually. ### Additional Context _No response_
      author:
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