Concatenate all pyspark dataframe columns into one string column

Question

I have the following pyspark dataframe

identification	p1	p2	p3	p4
1	1	0	0	1
2	0	1	1	0
3	0	0	0	1

I want to concatenate all columns from p1 to p4 in a way to gather the values of 1 and 0 in this way

identification	p1	p2	p3	p4	joined_column
1	1	0	0	1	1001
2	0	1	1	0	0110
3	0	0	0	1	0001

All columns from p1 to p4 are Integer, so I tried to cast them into string before concatenate all columns ( except the 'identification' column ) in this way:

from pyspark.sql.types import StringType 
from pyspark.sql import functions as F

df_concat=df.withColumn('joined_column', F.concat([F.col(c).cast(StringType()) for c in df.columns if  c!='identification']))

I get the following error :

TypeError: Invalid argument, not a string or column: 

Is there any solution or other way to concatenate all columns of a pyspark dataframe into one string ?

Answer 1

I will answer the question based on @samkart comment. We don't need to convert each column into a string, it will be converted automatically while concatenating.

from pyspark.sql import functions as F

df_concat=df.withColumn('joined_column', F.concat(*[F.col(c) for c in df.columns if  c!='identification']))

This will be true independent of columns number and names