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https://issues.apache.org/jira/browse/SPARK-49383?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wenchen Fan resolved SPARK-49383.
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Fix Version/s: 4.0.0
Resolution: Fixed
Issue resolved by pull request 47884
[https://github.com/apache/spark/pull/47884]
> Support Transpose DataFrame API
> -------------------------------
>
> Key: SPARK-49383
> URL: https://issues.apache.org/jira/browse/SPARK-49383
> Project: Spark
> Issue Type: New Feature
> Components: Connect, PySpark, SQL
> Affects Versions: 4.0.0
> Reporter: Xinrong Meng
> Assignee: Xinrong Meng
> Priority: Major
> Labels: pull-request-available
> Fix For: 4.0.0
>
>
> Support Transpose as Scala/Python DataFrame API in both Spark Connect and
> Classic Spark.
> Transposing data is a crucial operation in data analysis, enabling the
> transformation of rows into columns. This operation is widely used in tools
> like pandas and numpy, allowing for more flexible data manipulation and
> visualization.
> While Apache Spark supports unpivot and pivot operations, it currently lacks
> a built-in transpose function. Implementing a transpose operation in Spark
> would enhance its data processing capabilities, aligning it with the
> functionalities available in pandas and numpy, and further empowering users
> in their data analysis workflows.
> Please see
> [https://docs.google.com/document/d/1QSmG81qQ-muab0UOeqgDAELqF7fJTH8GnxCJF4Ir-kA/edit]
> for a detailed design.
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