As mentioned in many other locations on the web, adding a new column to an existing DataFrame is not straightforward. Unfortunately it is important to have this functionalit
All you need here is a literal and cast:
from pyspark.sql.functions import lit
new_df = old_df.withColumn('new_column', lit(None).cast(StringType()))
A full example:
df = sc.parallelize([row(1, "2"), row(2, "3")]).toDF()
df.printSchema()
## root
## |-- foo: long (nullable = true)
## |-- bar: string (nullable = true)
new_df = df.withColumn('new_column', lit(None).cast(StringType()))
new_df.printSchema()
## root
## |-- foo: long (nullable = true)
## |-- bar: string (nullable = true)
## |-- new_column: string (nullable = true)
new_df.show()
## +---+---+----------+
## |foo|bar|new_column|
## +---+---+----------+
## | 1| 2| null|
## | 2| 3| null|
## +---+---+----------+
A Scala equivalent can be found here: Create new Dataframe with empty/null field values