pralabhkumar commented on a change in pull request #34401:
URL: https://github.com/apache/spark/pull/34401#discussion_r738109398
##########
File path: python/pyspark/sql/pandas/conversion.py
##########
@@ -151,7 +151,17 @@ def toPandas(self) -> "PandasDataFrameLike":
_convert_map_items_to_dict(pdf[field.name])
return pdf
else:
- return pd.DataFrame.from_records([],
columns=self.columns)
+ pdf = pd.DataFrame.from_records([],
columns=self.columns)
+ df = pd.DataFrame()
+ for fieldIdx, field in enumerate(self.schema):
+ pandas_type = \
+
PandasConversionMixin._to_corrected_pandas_type(field.dataType)
+ column_name = self.schema[fieldIdx].name
+ series = pdf.iloc[:, fieldIdx]
+ if pandas_type is not None:
+ series = series.astype(pandas_type, copy=False)
+ df.insert(fieldIdx, column_name, series,
allow_duplicates=True)
Review comment:
@HyukjinKwon Thx for the comment . There is simple way to assign types
to an empty DF . but the problem is when DF contain duplicate columns. We can
check if there are duplicate columns in DF then use the above approach else use
the simple approach .
Please let me know if its ok .
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