xinrong-databricks commented on a change in pull request #33911:
URL: https://github.com/apache/spark/pull/33911#discussion_r704796337
##########
File path: python/pyspark/pandas/data_type_ops/boolean_ops.py
##########
@@ -248,6 +249,30 @@ def and_func(left: Column, right: Any) -> Column:
return column_op(and_func)(left, right)
+ def __xor__(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
+ _sanitize_list_like(right)
+ if isinstance(right, IndexOpsMixin) and isinstance(right.dtype,
extension_dtypes):
+ return right.__xor__(left)
+ elif (
+ isinstance(right, int)
+ or (hasattr(right, "dtype") and np.issubdtype(right.dtype, int))
+ or isinstance(right, bool)
+ or (hasattr(right, "dtype") and right.dtype == "bool")
Review comment:
How do you think about the code block below?
```py
def _is_valid_for_logical_operator(right: Any) -> bool:
from pyspark.pandas.base import IndexOpsMixin
return (
isinstance(right, IndexOpsMixin)
and (
isinstance(right.spark.data_type, BooleanType)
or isinstance(right.spark.data_type, IntegralType)
)
or isinstance(right, (int, bool))
)
```
IndexOpsMixin provides a unified interface for Series and Index.
DataTypeOps aims to make operations of Series and Index data-type-based.
We may access the DataTypeOps from the property `_dtype_op` of IndexOpsMixin.
Hope that makes sense to you. Let me know if you have any other questions :).
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