PySpark - ValueError: Cannot convert column into bool - pyspark

Question

So I've seen this solution:
ValueError: Cannot convert column into bool
which has the solution I think. But I'm trying to make it work with my dataframe and can't figure out how to implement it.
My original code:
if df2['DayOfWeek']>=6 :
df2['WeekendOrHol'] = 1
this gives me the error:
Cannot convert column into bool: please use '&' for 'and', '|' for
'or', '~' for 'not' when building DataFrame boolean expressions.
So based on the above link I tried:
from pyspark.sql.functions import when
when((df2['DayOfWeek']>=6),df2['WeekendOrHol'] = 1)
when(df2['DayOfWeek']>=6,df2['WeekendOrHol'] = 1)
but this is incorrect as it gives me an error too.

Answer 1

To update a column based on a condition you need to use when like this:
from pyspark.sql import functions as F
# update `WeekendOrHol` column, when `DayOfWeek` >= 6,
# then set `WeekendOrHol` to 1 otherwise, set the value of `WeekendOrHol` to what it is now - or you could do something else.
# If no otherwise is provided then the column values will be set to None
df2 = df2.withColumn('WeekendOrHol',
F.when(
F.col('DayOfWeek') >= 6, F.lit(1)
).otherwise(F.col('WeekendOrHol')
)
Hope this helps, good luck!

Answer 2

Best answer as provided by pault:
df2=df2.withColumn("WeekendOrHol", (df2["DayOfWeek"]>=6).cast("int"))
This is a duplicate of:
this