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Description
Pandas version checks
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import io
import pandas as pd
buf = io.StringIO("date,value\n2024-01-01 00:00:00,1\n2024-02-01 00:00:00,2")
df = pd.read_csv(buf, parse_dates=["date"])
df.set_index("date").loc["2024-01"] # works
buf = io.StringIO("date,value\n2024-01-01 00:00:00,1\n2024-02-01 00:00:00,2")
df = pd.read_csv(buf, parse_dates=["date"], dtype_backend="pyarrow", engine="pyarrow")
df.set_index("date").loc["2024-01"] # KeyError
### Issue Description
The pyarrow timestamp type gets put into a generic `Index` when assigned via set_index, so the datetime overloads do not work correctly
### Expected Behavior
The pyarrow timestamp type should be wrapped by a DatetimeIndex
### Installed Versions
3.0.0.dev0+1696.gfae3e8034f'
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pyarrow functionalitypyarrow functionalityDatetime data dtypeDatetime data dtypeRelated to the Index class or subclassesRelated to the Index class or subclasses