Skip to content

BUG: Series(mixed_tz_datetime_objs, dtype=dt64tz) #49432

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom
Closed
wants to merge 3 commits into from
Closed

BUG: Series(mixed_tz_datetime_objs, dtype=dt64tz) #49432

wants to merge 3 commits into from

Conversation

jbrockmendel
Copy link
Member

@jbrockmendel jbrockmendel commented Oct 31, 2022 •
edited
Loading

Side-notes:

  1. This also means we allow pretty much any mix of types e.g. [Timestamp, pydatetime, int, float, pd.NaT, str]
  2. The implementation here is super-naive. It can be optimized if it becomes an issue. But given the mess that array_to_datetime currently is, i'm happy erring on the side of simplicty.

@mroeschke mroeschke added Datetime Datetime data dtype Timezones Timezone data dtype Series Series data structure labels Nov 1, 2022
@jbrockmendel
Copy link
Member Author

superceded by #49454

@jbrockmendel jbrockmendel deleted the mixed-tzs branch November 3, 2022 17:04
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Reviewers
No reviews
Assignees
No one assigned
Labels
Datetime Datetime data dtype Series Series data structure Timezones Timezone data dtype
Projects
None yet
Milestone
No milestone
Development

Successfully merging this pull request may close these issues.

DataFrame.astype does not handle multiple timezone aware Timestamps
2 participants
@jbrockmendel @mroeschke