Filter

Filters DataFrame based on the provided filter condition

Parameters

Parameter	Description	Required
DataFrame	Input DataFrame on which the filter condition will be applied.	True
Filter Condition	BooleanType column or boolean expression. Supports SQL, Python and Scala expressions.	True

Example

Spark Code

Python

def Filter_Orders(spark: SparkSession, in0: DataFrame) -> DataFrame:
    return in0.filter(
        (
          ((col("order_category") == lit("Marketing"))
          & ((col("order_status") == lit("Finished")) | (col("order_status") == lit("Approved"))))
          & ~ col("is_discounted")
        )
    )

Scala

object Filter_Orders {

  def apply(spark: SparkSession, in: DataFrame): DataFrame =
    in.filter(
      (
        col("order_category") === lit("Marketing"))
        .and(
          (col("order_status") === lit("Finished"))
            .or(col("order_status") === lit("Approved"))
        )
        .and(!col("is_discounted"))
    )
}