modify column inside a structfield for pyspark

Question

I have a df with schema :

root
 |-- AddressBook: struct (nullable = true)
 |    |-- ContactInformationsList: array (nullable = true)
 |    |    |-- element: struct (containsNull = true)
 |    |    |    |-- ContactId: string (nullable = true)
 |    |    |    |-- ContactMeansDesc: string (nullable = true)
 |    |    |    |-- IsPrimaryMeans: boolean (nullable = true)
 |    |    |    |-- TypeMeansContactId: string (nullable = true)
 |    |    |    |-- Value: string (nullable = true)
 |    |-- PersonData: struct (nullable = true)
 |    |    |-- BirthDate: string (nullable = true)
 |    |    |-- CSP: string (nullable = true)
 |    |    |-- Civility: string (nullable = true)
 |    |    |-- FirstName: string (nullable = true)
 |    |    |-- Gender: string (nullable = true)
 |    |    |-- LastName: string (nullable = true)
 |    |    |-- MaritalStatus: string (nullable = true)
 |    |    |-- SBirthDate: string (nullable = true)
 |    |    |-- Title: string (nullable = true)
 |-- PublicId: string (nullable = true)
 |-- Version: long (nullable = true)

This dataframe constains prod data, therefore I would like to change some of the personal information. Basically, replace the columns AddressBook.Persondata.Lastname with a hash of the value.

I tried :

df.withColumn(
    'AddressBook.Persondata.Lastname', 
    F.hash(F.col('AddressBook.Persondata.Lastname'))
)

but it just added another column:

|-- AddressBook.Persondata.Lastname: int (nullable = true)

Is there a simple way to modify my data ?