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issue, jbrockmendel, member, marcogorelli, sign, todatetime, unit, strings, vals, pdtodatetimevals, pandas, projects, commented, navigation, pull, requests, actions, security, api, interpreted, closed, units, datetimeindex, dtypedatetimens, freqnone, float, bug, triage, reviewed, team, github, type, milestone, footer, skip, content, menu, product, solutions, resources, open, source, enterprise, pricing, search, jump, pandasdev, public, notifications, fork,

Topics {✒️}

personal information api assigned labels bug string behavior unchanged treat floats/ints comment metadata assignees dtype='datetime64[ns]' marcogorelli closed type projects triage issue projects milestone milestone relationships cast strings casting strings github vals ns vals2 unit unit= strings sign ] pd skip jump to_datetime datetimeindex freq= pass array_with_unit_to_datetime float parse makes sense affect reviewed depr updated 👍 react yah free join conversation account development branches share

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DiscussionForumPosting:
      context:https://schema.org
      headline:API: to_datetime with unit changes how strings are interpreted
      articleBody:```python vals = ["2016-01-02 03:04:05"] pd.to_datetime(vals) # <- works pd.to_datetime(vals, unit="s") # <- raises vals2 = ["20160102"] >>> pd.to_datetime(vals2) DatetimeIndex(['2016-01-02'], dtype='datetime64[ns]', freq=None) >>> pd.to_datetime(vals2, unit="s") DatetimeIndex(['1970-08-22 08:01:42'], dtype='datetime64[ns]', freq=None) ``` if you pass a unit (other than "ns") to to_datetime we go through array_with_unit_to_datetime and cast strings to float instead of trying to parse them. I think it makes more sense to keep the string behavior unchanged and only affect how we treat floats/ints.
      author:
         url:https://github.com/jbrockmendel
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      datePublished:2023-01-13T16:44:22.000Z
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      url:https://github.com/50735/pandas/issues/50735
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      headline:API: to_datetime with unit changes how strings are interpreted
      articleBody:```python vals = ["2016-01-02 03:04:05"] pd.to_datetime(vals) # <- works pd.to_datetime(vals, unit="s") # <- raises vals2 = ["20160102"] >>> pd.to_datetime(vals2) DatetimeIndex(['2016-01-02'], dtype='datetime64[ns]', freq=None) >>> pd.to_datetime(vals2, unit="s") DatetimeIndex(['1970-08-22 08:01:42'], dtype='datetime64[ns]', freq=None) ``` if you pass a unit (other than "ns") to to_datetime we go through array_with_unit_to_datetime and cast strings to float instead of trying to parse them. I think it makes more sense to keep the string behavior unchanged and only affect how we treat floats/ints.
      author:
         url:https://github.com/jbrockmendel
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