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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2021/10/28 00:50:13 UTC
[GitHub] [spark] HyukjinKwon commented on a change in pull request #34401: [SPARK-30537][PYTHON], Fix toPandas wrong dtypes when applied on empty DF when Arrow enabled
HyukjinKwon commented on a change in pull request #34401:
URL: https://github.com/apache/spark/pull/34401#discussion_r737943724
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File path: python/pyspark/sql/pandas/conversion.py
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@@ -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:
Is there simpler and easier way to assign types to an empty pandas DataFrame? The current way looks too messy.
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