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. Supports Spark Connect.

For the corresponding Databricks SQL function, see transform_values function.

Syntax

from pyspark.databricks.sql import functions as dbf

dbf.transform_values(col=<col>, f=<f>)

Parameters

Parameter	Type	Description
col	pyspark.sql.Column or str	Name of column or expression.
f	function	A binary function.

Returns

pyspark.sql.Column: a new map of entries where new values were calculated by applying given function to each key value argument.

Examples

from pyspark.databricks.sql import functions as dbf
df = spark.createDataFrame([(1, {"IT": 10.0, "SALES": 2.0, "OPS": 24.0})], ("id", "data"))
row = df.select(dbf.transform_values(
    "data", lambda k, v: dbf.when(k.isin("IT", "OPS"), v + 10.0).otherwise(v)
).alias("new_data")).head()
sorted(row["new_data"].items())

[('IT', 20.0), ('OPS', 34.0), ('SALES', 2.0)]