ENH: Support pyarrow timestamps in merge_asof

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'

import pandas as pd
import pyarrow as pa

df = pd.DataFrame(
    index=pd.Series([0, 1], dtype=pd.ArrowDtype(pa.timestamp('ns'))),
    data={'value': pd.Series(['a', 'b'], dtype=pd.ArrowDtype(pa.string()))},
)

pd.merge_asof(df, df, left_index=True, right_index=True)

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