rok commented on issue #41132:
URL: https://github.com/apache/arrow/issues/41132#issuecomment-2052555361
Hey @nikfio, sorry I didn't use your raw data. This works for me on your
example:
```python
import pyarrow as pa
import pyarrow.compute as pc
ts = pa.array(["20090101 185956123"], pa.string())
ts2 = pc.strptime(pc.utf8_slice_codeunits(ts, 0, 15), format="%Y%m%d
%H%M%S", unit="ms")
d = pc.utf8_slice_codeunits(ts, 15,
99).cast(pa.int64()).cast(pa.duration("ms"))
pc.add(ts2, d)
```
```
<pyarrow.lib.TimestampArray object at 0x73006a846680>
[
2009-01-01 18:59:56.123
]
```
Your Pandas/numpy workaround looks good. I'm not sure which approach would
be better for your usecase.
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