[jira] [Commented] (SPARK-32098) Use iloc for positional slicing instead of direct slicing in createDataFrame with Arrow

["Dongjoon Hyun (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-32098?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17151773#comment-17151773 ] 

Dongjoon Hyun commented on SPARK-32098:
---------------------------------------

Hi, [~hyukjin.kwon] and [~bryanc]. I'm trying to verify this at 2.4.6 with the above example, but there was no luck until now. Did I miss something?
{code}
$ ./bin/pyspark --conf spark.sql.execution.arrow.pyspark.enabled=true
Python 3.7.7 (default, Mar 21 2020, 21:07:30)
[Clang 11.0.0 (clang-1100.0.33.16)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
20/07/05 23:13:03 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 2.4.6
      /_/

Using Python version 3.7.7 (default, Mar 21 2020 21:07:30)
SparkSession available as 'spark'.
>>> import pandas as pd
>>> spark.createDataFrame(pd.DataFrame({'a': [1,2,3]}, index=[2., 3., 4.])).show()
+---+
|  a|
+---+
|  1|
|  2|
|  3|
+---+
{code}

> Use iloc for positional slicing instead of direct slicing in createDataFrame with Arrow
> ---------------------------------------------------------------------------------------
>
>                 Key: SPARK-32098
>                 URL: https://issues.apache.org/jira/browse/SPARK-32098
>             Project: Spark
>          Issue Type: Improvement
>          Components: PySpark
>    Affects Versions: 2.4.6, 3.0.0
>            Reporter: Hyukjin Kwon
>            Assignee: Hyukjin Kwon
>            Priority: Critical
>              Labels: correctness
>             Fix For: 2.4.7, 3.0.1, 3.1.0
>
>
> When you use floats are index of pandas, it produces a wrong results:
> {code}
> >>> import pandas as pd
> >>> spark.createDataFrame(pd.DataFrame({'a': [1,2,3]}, index=[2., 3., 4.])).show()
> +---+
> |  a|
> +---+
> |  1|
> |  1|
> |  2|
> +---+
> {code}
> This is because direct slicing uses the value as index when the index contains floats:
> {code}
> >>> pd.DataFrame({'a': [1,2,3]}, index=[2., 3., 4.])[2:]
>      a
> 2.0  1
> 3.0  2
> 4.0  3
> >>> pd.DataFrame({'a': [1,2,3]}, index=[2., 3., 4.]).iloc[2:]
>      a
> 4.0  3
> >>> pd.DataFrame({'a': [1,2,3]}, index=[2, 3, 4])[2:]
>    a
> 4  3
> {code}



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