pyspark.sql.functions.transform_values

pyspark.sql.functions.transform_values(col: ColumnOrName, f: Callable[[pyspark.sql.column.Column, pyspark.sql.column.Column], pyspark.sql.column.Column]) → pyspark.sql.column.Column

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.

Parameters

colColumn or str

name of column or expression

ffunction

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).

Returns

Column

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}|
+---------------------------------------+

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