HyukjinKwon commented on code in PR #41514:
URL: https://github.com/apache/spark/pull/41514#discussion_r1227737630
##########
python/pyspark/pandas/data_type_ops/num_ops.py:
##########
@@ -213,37 +215,43 @@ def abs(self, operand: IndexOpsLike) -> IndexOpsLike:
F.abs(operand.spark.column), field=operand._internal.data_fields[0]
)
+ def eq(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
+ # We can directly use `super().eq` when given object is list, tuple,
dict or set.
+ if not isinstance(right, IndexOpsMixin) and is_list_like(right):
+ return super().eq(left, right)
+ if _is_extension_dtypes(left) or _is_extension_dtypes(right):
+ return pyspark_column_op("__eq__", left, right)
+ return pyspark_column_op("__eq__", left, right, fillna=False)
+
+ def ne(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
+ _sanitize_list_like(right)
+ if _is_extension_dtypes(left) or _is_extension_dtypes(right):
+ return pyspark_column_op("__ne__", left, right)
+ return pyspark_column_op("__ne__", left, right, fillna=True)
+
def lt(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
_sanitize_list_like(right)
- result = pyspark_column_op("__lt__")(left, right)
- if is_remote():
- # TODO(SPARK-43877): Fix behavior difference for compare binary
functions.
- result = result.fillna(False)
- return result
+ if _is_extension_dtypes(left) or _is_extension_dtypes(right):
+ return pyspark_column_op("__lt__", left, right)
+ return pyspark_column_op("__lt__", left, right, fillna=False)
Review Comment:
I think you can put `_is_extension_dtypes(left) or
_is_extension_dtypes(right)` condition to `fillna`?
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