PySpark Pivot and Unpivot DataFrame

PySpark pivot() function is used to rotate/transpose the data from one column into multiple Dataframe columns and back using unpivot(). Pivot() It is an aggregation where one of the grouping columns values transposed into individual columns with distinct data. This tutorial describes and provides a PySpark example on how to…

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PySpark Groupby Explained with Example

Similar to SQL GROUP BY clause, PySpark groupBy() function is used to collect the identical data into groups on DataFrame and perform aggregate functions on the grouped data. In this article, I will explain several groupBy() examples using PySpark (Spark with Python). Related: How to group and aggregate data using…

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Spark Groupby Example with DataFrame

Similar to SQL "GROUP BY" clause, Spark groupBy() function is used to collect the identical data into groups on DataFrame/Dataset and perform aggregate functions on the grouped data. In this article, I will explain several groupBy() examples with the Scala language. The same approach can be used with the Pyspark…

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How to Pivot and Unpivot a Spark DataFrame

This article describes and provides scala example on how to Pivot Spark DataFrame ( creating Pivot tables ) and Unpivot back. Pivoting is used to rotate the data from one column into multiple columns. It is an aggregation where one of the grouping columns values transposed into individual columns with distinct data.

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