Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/4528#discussion_r24481115
--- Diff: python/pyspark/sql/context.py ---
@@ -336,19 +353,28 @@ def createDataFrame(self, rdd, schema=None,
samplingRatio=None):
>>> df3.collect()
[Row(name=u'Alice', age=1)]
"""
- if isinstance(rdd, DataFrame):
+ if isinstance(data, DataFrame):
raise TypeError("rdd is already a DataFrame")
- if isinstance(schema, StructType):
- return self.applySchema(rdd, schema)
- else:
- if isinstance(schema, (list, tuple)):
- first = rdd.first()
- if not isinstance(first, (list, tuple)):
- raise ValueError("each row in `rdd` should be list or
tuple")
- row_cls = Row(*schema)
- rdd = rdd.map(lambda r: row_cls(*r))
- return self.inferSchema(rdd, samplingRatio)
+ if has_pandas and isinstance(data, pandas.DataFrame):
--- End diff --
No, user cannot create a pandas.DataFrame object if pandas is not available.
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