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PySpark DataFrame | intersect method

schedule Aug 12, 2023
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PySpark DataFrame's `intersect(~)` method returns a new PySpark DataFrame with rows that exist in another PySpark DataFrame. Note that unlike `intersectAll(~)`, `intersect(~)` only includes duplicate rows once.

NOTE

The `intersect(~)` method is equivalent to the `INTERSECT` statement in SQL.

Parameters

1. `other` | PySpark DataFrame

The other PySpark DataFrame with which to perform intersection.

Return Value

A new PySpark DataFrame.

Examples

Consider the following PySpark DataFrame:

``` df = spark.createDataFrame([("Alex", 20), ("Bob", 30), ("Cathy", 40)], ["name", "age"])df.show() +-----+---+| name|age|+-----+---+| Alex| 20|| Bob| 30||Cathy| 40|+-----+---+ ```

Consider the other PySpark DataFrame:

``` df_other = spark.createDataFrame([("Alex", 20), ("Doge", 30), ("eric", 40)], ["name", "age"])df_other.show() +----+---+|name|age|+----+---+|Alex| 20||Doge| 30||eric| 40|+----+---+ ```

Getting rows of PySpark DataFrame that exist in another PySpark DataFrame

To get rows of a PySpark DataFrame that exist in another PySpark DataFrame, use the `intersect(~)` method like so:

``` df_intersect = df.intersect(df_other)df_intersect.show() +----+---+|name|age|+----+---+|Alex| 20|+----+---+ ```

Here, we get this row because both PySpark DataFrames contained this row.

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