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https://issues.apache.org/jira/browse/SPARK-34544?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17293013#comment-17293013
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Rafal Wojdyla commented on SPARK-34544:
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[~zero323] I appreciate your prompt answers.
Re:
{quote}
For in-house deployments the easiest way is to actually patch Spark to mark
return type as pandas.core.frame.DataFrame and either patch Pandas
(https://github.com/pandas-dev/pandas/pull/28831) or put extracted stubs in
MYPYPATH.
{quote}
so that would require that we build our own pyspark? That is certainly
"doable", but I hope you see that's it's not very user friendly. Are there any
other options?
Re:
{quote}
If there are popular methods which didn't get into protocol I'd probably add
these as a temporary fix.
{quote}
Some examples we have hit (this list is not complete): {{head}},
{{convert_dtypes}}. wdyt?
Re:
{quote}
Looking forward to Spark 3.2 we can closely monitor Pandas progress ‒ if they
become PEP 561 we simply drop the protocol. Otherwise we can give Microsoft
stubs a shot.
{quote}
What would be the timeline for that (roughly)?
> pyspark toPandas() should return pd.DataFrame
> ---------------------------------------------
>
> Key: SPARK-34544
> URL: https://issues.apache.org/jira/browse/SPARK-34544
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 3.1.1
> Reporter: Rafal Wojdyla
> Assignee: Maciej Szymkiewicz
> Priority: Major
>
> Right now {{toPandas()}} returns {{DataFrameLike}}, which is an incomplete
> "view" of pandas {{DataFrame}}. Which leads to cases like mypy reporting that
> certain pandas methods are not present in {{DataFrameLike}}, even tho those
> methods are valid methods on pandas {{DataFrame}}, which is the actual type
> of the object. This requires type ignore comments or asserts.
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