HyukjinKwon commented on a change in pull request #34631:
URL: https://github.com/apache/spark/pull/34631#discussion_r751947212
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File path: python/pyspark/sql/pandas/conversion.py
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@@ -225,7 +227,10 @@ def toPandas(self) -> "PandasDataFrameLike":
else:
series = pdf[column_name]
- if t is not None:
+ # No need to cast for empty series for timedelta.
+ should_check_timedelta = is_timedelta64_dtype(t) and len(pdf) == 0
Review comment:
This is, BTW, to work around a bug from Arrow <> pandas.
For some reasons, `pd.Series(pd.Timedelta(...), dtype="object")` created
from Arrow becomes `float64` when you cast with
`series.astype("timedelta64[us]")` when the data is non-empty - this cannot be
reproduced with plain pandas `Series`.
So, here I avoided it by just skipping the casting because the type becomes
correct when it is not empty. When data is empty, the type becomes `object`,
and it has to be casted.
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