[GitHub] [spark] xinrong-databricks commented on a diff in pull request #36870: [SPARK-39483][PYTHON] Construct the schema from `np.dtype` when `createDataFrame` from a NumPy array

[GitBox <gi...@apache.org>]

xinrong-databricks commented on code in PR #36870:
URL: https://github.com/apache/spark/pull/36870#discussion_r902961587


##########
python/pyspark/sql/session.py:
##########
@@ -975,6 +976,17 @@ def createDataFrame(  # type: ignore[misc]
             if data.ndim not in [1, 2]:
                 raise ValueError("NumPy array input should be of 1 or 2 dimensions.")
             column_names = ["value"] if data.ndim == 1 else ["_1", "_2"]
+            if schema is None and not self._jconf.arrowPySparkEnabled():
+                # Construct `schema` from `np.dtype` of the input NumPy array
+                # TODO: Apply the logic below when self._jconf.arrowPySparkEnabled() is True
+                spark_type = _from_numpy_type(data.dtype)
+                if spark_type is not None:
+

Review Comment:
   Good idea! Simplified.
   
   As for `nullable`, shall we follow how we infer schema, as [here](https://github.com/apache/spark/blob/b588d070ebc234280af730c8f9915e8859b1886e/python/pyspark/sql/types.py#L1348)?
   
   Let me know if you have other concerns.



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