emkornfield commented on a change in pull request #7604:
URL: https://github.com/apache/arrow/pull/7604#discussion_r449130523
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File path: cpp/src/arrow/python/arrow_to_pandas.cc
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@@ -642,24 +641,27 @@ inline Status ConvertStruct(const PandasOptions& options,
const ChunkedArray& da
std::vector<OwnedRef> fields_data(num_fields);
OwnedRef dict_item;
- // XXX(wesm): In ARROW-7723, we found as a result of ARROW-3789 that second
+ // In ARROW-7723, we found as a result of ARROW-3789 that second
// through microsecond resolution tz-aware timestamps were being promoted to
// use the DATETIME_NANO_TZ conversion path, yielding a datetime64[ns] NumPy
// array in this function. PyArray_GETITEM returns datetime.datetime for
// units second through microsecond but PyLong for nanosecond (because
- // datetime.datetime does not support nanoseconds). We inserted this hack to
- // preserve the <= 0.15.1 behavior until a better solution can be devised
+ // datetime.datetime does not support nanoseconds).
+ // We force the object conversion to preserve the value of the timezone.
PandasOptions modified_options = options;
- modified_options.ignore_timezone = true;
modified_options.coerce_temporal_nanoseconds = false;
for (int c = 0; c < data.num_chunks(); c++) {
auto arr = checked_cast<const StructArray*>(data.chunk(c).get());
// Convert the struct arrays first
for (int32_t i = 0; i < num_fields; i++) {
+ // Se notes above about conversion.
+ std::shared_ptr<Array> field = arr->field(static_cast<int>(i));
+ modified_options.timestamp_as_object =
+ field->type()->id() == Type::TIMESTAMP &&
+ !checked_cast<const
TimestampType&>(*field->type()).timezone().empty();
Review comment:
> Who does this? Does arrow do this in conversion? Or do you mean that
PyArray_GETITEM does this? (AFAIK numpy used to do things with system time
zone, but that should be solved nowadays)
@jorisvandenbossche
Python's [datetime.astimezone assumes
this](https://docs.python.org/3/library/datetime.html#datetime.datetime.astimezone)
as of 3.6. Since datetime essentially becomes the "display" I would think
most people would assume system timezone values.
> > Our timestamp -> datetime conversion assumes UTC as far as I can tell
(like I said not sure what pandas does here).
> Where do we assume this? (and this is about naive or aware timestamps?)
Core [timestamp conversion doesn't handle
timezones](https://github.com/apache/arrow/blob/edd88d7d222598550e4812c94194cbf973b20456/cpp/src/arrow/python/datetime.cc#L246).
for non-naive we use
[fromutc](https://github.com/apache/arrow/blob/89cf7bdd6fc0d34c96f1a0e1df0a3505b308188d/python/pyarrow/scalar.pxi#L310)
after the fact.
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