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From "Hyukjin Kwon (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-24946) PySpark - Allow np.Arrays and pd.Series in df.approxQuantile
Date Tue, 31 Jul 2018 02:36:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-24946?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16563052#comment-16563052
] 

Hyukjin Kwon commented on SPARK-24946:
--------------------------------------

Hmmm. mind if I ask a discussion in dev mailing list after Spark 2.4.0 is released (since
committers and guys are busy on this currently)? This one specific case can be trivial but
I am worried if we should consider allowing all other cases.

> PySpark - Allow np.Arrays and pd.Series in df.approxQuantile
> ------------------------------------------------------------
>
>                 Key: SPARK-24946
>                 URL: https://issues.apache.org/jira/browse/SPARK-24946
>             Project: Spark
>          Issue Type: Improvement
>          Components: PySpark
>    Affects Versions: 2.3.1
>            Reporter: Paul Westenthanner
>            Priority: Minor
>              Labels: DataFrame, beginner, pyspark
>
> As Python user it is convenient to pass a numpy array or pandas series `{{approxQuantile}}(_col_,
_probabilities_, _relativeError_)` for the probabilities parameter. 
>  
> Especially for creating cumulative plots (say in 1% steps) it is handy to use `approxQuantile(col,
np.arange(0, 1.0, 0.01), relativeError)`.
>  
>  



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