Pyspark how to create a customized csv from data frame

Question

i have below data frame which i need to load in to csv with customized row and values

common_df.show()
+--------+----------+-----+----+-----+-----------+-------+---+
|name    |department|state|id  |name | department| state | id|
+--------+----------+-----+----+-----+-----------+-------+---+
|James   |Sales     |NY   |101 |James|  Sales1   |null   |101|  
|Maria   |Finance   |CA   |102 |Maria|  Finance  |       |102|
|Jen     |Marketing |NY   |103 |Jen  |           |NY2    |103|

i am following below approach currently to convert df to csv

pandasdf=common_df.toPandas()
pandasdf.to_csv("s3://mylocation/result.csv")

The above going to convert with same structure in csv. however i need to structure from above format to something below, I think the solution would be to split each row to two allocating the id on left within data frame. but i don't see any example or solution directly from spark

    |name   |dept      |state|id  | 
------------------------------------    
101 |James  |Sales     |NY   |101 |     
    |James  |null      |NY   |101 |
------------------------------------    
102 |Maria  |Finance   |     |102 |     
    |Maria  |Finance   |CA   |102 | 
-------------------------------------   
103 |Jen    |Marketing |NY   |103 |     
    |Jen    |          |NY2  |103 |
------------------------------------    

Any solution to this?