Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/18378#discussion_r123325897
--- Diff: python/pyspark/sql/dataframe.py ---
@@ -1721,7 +1721,8 @@ def toPandas(self):
1 5 Bob
"""
import pandas as pd
- return pd.DataFrame.from_records(self.collect(),
columns=self.columns)
+ dtype = {field.name: _to_numpy_type(field.dataType) for field in
self.schema}
+ return pd.DataFrame.from_records(self.collect(),
columns=self.columns).astype(dtype)
--- End diff --
This is probably the easiest way to assign the types, but data is still
loaded and inferred then the `astype` will then cast the data and I'm not sure
if it will make a pass over the data or do it lazily. A more ideal way would
be to not use `from_records` but then I think the data would need to be broken
up into columns.
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