dragosmg commented on pull request #12357:
URL: https://github.com/apache/arrow/pull/12357#issuecomment-1034722439
To add to the conversation above. I think the right way to go is to extract
timezone from the timestamp metadata and not look at each individual value.
However, that could in a situation where a value is NA, but the column is a
`timestamp` which will result in something like:
``` r
suppressMessages(library(arrow))
suppressMessages(library(dplyr))
df <- tibble(
x = as.POSIXct(c("2022-02-07", NA), tz = "Pacific/Marquesas")
)
df %>%
record_batch() %>%
mutate(timezone_x = tz(x)) %>%
collect()
#> A tibble: 2 × 2
#> x timezone_x
#> <dttm> <chr>
#> 1 2022-02-07 00:00:00 Pacific/Marquesas
#> 2 NA Pacific/Marquesas
```
<sup>Created on 2022-02-10 by the [reprex
package](https://reprex.tidyverse.org) (v2.0.1)</sup>
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