PySpark: modify column values when another column value satisfies a condition

Question

I have a PySpark Dataframe that has two columns Id and rank,

+---+----+
| Id|Rank|
+---+----+
|  a|   5|
|  b|   7|
|  c|   8|
|  d|   1|
+---+----+
<         


        

Answer 1

You can use when and otherwise like -

from pyspark.sql.functions import *

df\
.withColumn('Id_New',when(df.Rank <= 5,df.Id).otherwise('other'))\
.drop(df.Id)\
.select(col('Id_New').alias('Id'),col('Rank'))\
.show()

this gives output as -

+-----+----+
|   Id|Rank|
+-----+----+
|    a|   5|
|other|   7|
|other|   8|
|    d|   1|
+-----+----+

Answer 2

Starting with @Pushkr solution couldn't you just use the following ?

from pyspark.sql.functions import *

df.withColumn('Id',when(df.Rank <= 5,df.Id).otherwise('other')).show()