I have a use case where I want to replace nulls in struct type columns with empty values.
Below is sample which you can use to recreate the scenario:

from pyspark.sql.types import StructType,StructField, StringType, IntegerType

data = [(1, [1, 'Aman']), (2, [2, "Raman"]),(3, [3, "Baman"]),(4,None)]

schema = (StructType([ 
    StructField("ID",IntegerType(),True),   
    StructField("Name",StructType([
      StructField("NameID",IntegerType(),True),
      StructField("FirstName",StringType(),True),
    ]),True) 
  ]))

df = spark.createDataFrame(data, schema)

df.show()

I want to know how we can replace nulls in Name column.

>Solution :

Using when expression:

from pyspark.sql import functions as F

df1 = df.withColumn(
    "Name",
    F.when(
        F.col("Name").isNull(),
        F.struct(
            F.lit(None).alias("NameID"), #replace None by default ID value if needed
            F.lit("").alias("FirstName")
        )
    ).otherwise(F.col("Name"))
)

df1.show()
#+---+----------+
#| ID|      Name|
#+---+----------+
#|  1| {1, Aman}|
#|  2|{2, Raman}|
#|  3|{3, Baman}|
#|  4|  {null, }|
#+---+----------+