pyspark.sql.functions.
transform_values
Applies a function to every key-value pair in a map and returns a map with the results of those applications as the new values for the pairs.
New in version 3.1.0.
Column
name of column or expression
a binary function (k: Column, v: Column) -> Column... Can use methods of Column, functions defined in pyspark.sql.functions and Scala UserDefinedFunctions. Python UserDefinedFunctions are not supported (SPARK-27052).
(k: Column, v: Column) -> Column...
pyspark.sql.functions
UserDefinedFunctions
Examples
>>> df = spark.createDataFrame([(1, {"IT": 10.0, "SALES": 2.0, "OPS": 24.0})], ("id", "data")) >>> df.select(transform_values( ... "data", lambda k, v: when(k.isin("IT", "OPS"), v + 10.0).otherwise(v) ... ).alias("new_data")).show(truncate=False) +---------------------------------------+ |new_data | +---------------------------------------+ |{OPS -> 34.0, IT -> 20.0, SALES -> 2.0}| +---------------------------------------+