jimwhite opened a new issue, #44030:
URL: https://github.com/apache/arrow/issues/44030
### Describe the usage question you have. Please include as many useful
details as possible.
I have data from a commercial vendor that is delivered in compressed CSV
files (.csv.gz). The timestamps are Unix timestamps as decimal integer and
come in two flavors, either millisecond (`pa.timestamp('ms', tz='UTC')`) or
nanosecond (`pa.timestamp('ns', tz='UTC')`). I've learned that the CSV
conversion for these integer timestamps doesn't work because strptime(3) does
not have a format option for them.
My workaround is to cast after reading:
```python
table.set_column(
table.column_names.index('window_start'),
'window_start',
table.column("window_start").cast(pa.timestamp('ns', tz='UTC'))
)
```
My question is whether I'm missing something about how to do this during the
`pa.csv.read_csv` (these files are large and I want/need to process them
incrementally) and if not whether I should raise this an enhancement request
(I've looked at many issues around timestamps and haven't found any about this
kind of format).
### Component(s)
Python
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