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I use a Polars' query/dataframe to do some ETL, then convert it to a Pandas' dataframe so I can do some manipulation that requires recursion that Polars can't easily handle. The issue I found was converting from Polars to Pandas. The command: self.DataFrame==DverseTableQuery.co...
(because UTC acknowledges leap seconds and POSIX time is just a linear number of seconds), with the timezone string being considered as informative and possibly subject to future extension. With regards to how they affect days-to-seconds duration handling, though, you may have a point, but ...
I use a Polars' query/dataframe to do some ETL, then convert it to a Pandas' dataframe so I can do some manipulation that requires recursion that Polars can't easily handle. The issue I found was converting from Polars to Pandas. The command: self.DataFrame==DverseTableQuery.collec...
max_items_per_column: int = ..., max_colname_length: int = ..., return_as_string: bool, ) -> str | None: ... ) -> str | None: ...def glimpse( self, @@ -8249,10 +8278,12 @@ def get_columns(self) -> list[Series]: ...
My use case basically considers recent data more important so I want's to ensure data that might be orphaned (See itemsAandJin examples below) occurs at the beginning (chronologically speaking) instead of the end. Current thinking I'm currently approaching this by thinking I want to groupby_...
asset_key.to_user_string()} in job {context.job_name} in run {context.run_id}", allow_empty=True, ) if has_items( self.repository.branch(self.source_branch_name).diff( step_branch_name, max_amount=1, ), ): self.repository.branch(step_branch_name).merge_into( self.source_branch_...
asset_key.to_user_string()} in job {context.job_name} in run {context.run_id}", allow_empty=True, ) if has_items( self.repository.branch(self.source_branch_name).diff( step_branch_name, max_amount=1, ), ): self.repository.branch(step_branch_name).merge_into( self.source_branch_...
multiple times to add items to a list. 51.3s 34 FutureWarning, 51.3s 35 [NbConvertApp] Converting notebook __notebook__.ipynb to notebook 51.6s 36 [NbConvertApp] Writing 58628 bytes to __notebook__.ipynb 54.2s 37 /opt/conda/lib/python3.7/site-packages/traitlets/traitlets.py:2758...