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There would be no changes to user facing behavior, I'm not sure about the internal complexity involved in implementation.
Alternative Solutions
The current numpy datetime dtype can be used in merge_asof operations, but when your dataframe is read from parquet files this can be an expensive translation step.
Additional Context
No response
The text was updated successfully, but these errors were encountered:
Feature Type
Adding new functionality to pandas
Changing existing functionality in pandas
Removing existing functionality in pandas
Problem Description
I would like to be able to use pyarrow timestamp dtypes as the merge column/index in merge_asof operations.
This code currently raises
KeyError: 'timestamp[ns][pyarrow]_t|object'
Feature Description
There would be no changes to user facing behavior, I'm not sure about the internal complexity involved in implementation.
Alternative Solutions
The current numpy datetime dtype can be used in merge_asof operations, but when your dataframe is read from parquet files this can be an expensive translation step.
Additional Context
No response
The text was updated successfully, but these errors were encountered: