emkornfield commented on a change in pull request #7816:
URL: https://github.com/apache/arrow/pull/7816#discussion_r463915789
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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++) {
PyObject* numpy_array;
- RETURN_NOT_OK(ConvertArrayToPandas(
- modified_options, arr->field(static_cast<int>(i)), nullptr,
&numpy_array));
+ std::shared_ptr<Array> field = arr->field(static_cast<int>(i));
+ // Seen notes above about timstamp conversion. Don't blindly convert
because
Review comment:
my code, I can fix. Typos: "timestamp" and "Seen"
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