Allow tz-aware timstamps in gaps.trim
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kandersolar
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Feb 8, 2024
pvanalytics/quality/gaps.py
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| mask.loc[start.date():end.date()] = True | ||
| mask.loc[pd.to_datetime(start.date()).tz_localize(series.index.tz): | ||
| pd.to_datetime(end.date()).tz_localize(series.index.tz)] = \ | ||
| True |
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The return values of start_stop_dates seem to always have timestamps at midnight. With that in mind, do we need to do any conversion like .date() here? Couldn't we just use start and end as-is?
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You are right mask.loc[start:end] = True would also works since adding .date() would change start and end from tz-aware to tz-naive, which made the Pandas error. I edited the code and have pushed your suggestion.
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@kandersolar we went through all of the examples and the QA notebooks and this was the only function throwing a pandas error (data shifts module didn't have issues). When this is merged in, we should be good to go with pandas>=2.0.0 |
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Updated quality.gaps.trim function for updated versions of Pandas 2.0
docs/api.rst.in
docs/whatsnewfor all changes. Includes link to the GitHub Issue with
:issue:`num`or this Pull Request with
:pull:`num`. Includes contributor nameand/or GitHub username (link with
:ghuser:`user`).