xinrong-databricks commented on a change in pull request #32611:
URL: https://github.com/apache/spark/pull/32611#discussion_r638140558
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File path: python/pyspark/pandas/data_type_ops/boolean_ops.py
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@@ -15,7 +15,27 @@
# limitations under the License.
#
-from pyspark.pandas.data_type_ops.base import DataTypeOps
+import numbers
+from typing import TYPE_CHECKING, Union
+
+import numpy as np
+from pandas.api.types import CategoricalDtype
+
+from pyspark.pandas.base import column_op, IndexOpsMixin, numpy_column_op
+from pyspark.pandas.data_type_ops.base import DataTypeOps,
transform_boolean_operand_to_numeric
+from pyspark.pandas.typedef.typehints import as_spark_type
+from pyspark.sql import Column, functions as F
+from pyspark.sql.types import NumericType
+
+if TYPE_CHECKING:
+ from pyspark.pandas.indexes import Index # noqa: F401 (SPARK-34943)
+ from pyspark.pandas.series import Series # noqa: F401 (SPARK-34943)
+
+
+def is_numeric_index_ops(index_ops: IndexOpsMixin) -> bool:
+ """Check if the given index_ops is numeric IndexOpsMixin."""
+ return isinstance(index_ops.spark.data_type, NumericType) and (
+ not isinstance(index_ops.dtype, CategoricalDtype))
Review comment:
`is_valid_operand_for_numeric_arithmetic` returns True for
`BooleanType`, whereas `is_numeric_index_ops ` returns False for `BooleanType`.
We may also pass in a boolean flag deciding how to deal with `BooleanType`.
How do you think about this?
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