icexelloss opened a new issue, #47400:
URL: https://github.com/apache/arrow/issues/47400
### Describe the enhancement requested
In Pandas, there is a way to do "day offset shift" that is day light saving
aware, e.g.
```
import pyarrow as pa
import pandas as pd
import pyarrow.compute as pc
begin = pd.Timestamp('20250308 9:30', tz='America/New_York')
print(begin)
print(begin + pd.DateOffset(days=1))
print(begin + pd.DateOffset(days=2))
```
Outputs:
```
2025-03-08 09:30:00-05:00
2025-03-09 09:30:00-04:00
2025-03-10 09:30:00-04:00
```
However, there is no way to do such operations as far as I am aware with
arrow compute, the closest I found is this
```
begin = pa.scalar(pd.Timestamp('20250309', tz='America/New_York'))
pc.add(begin, pa.scalar((0, 1, 0), type=pa.month_day_nano_interval()))
```
However, it seems not supported, I also didn't find any specific arrow
compute function to do this.
IMO this would be really useful to deal with time in non-UTC timezone.
### Component(s)
C++
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