Spark Dataframe Group by having New Indicator Column

I need to group by "KEY" Column and need to check whether "TYPE_CODE" column has both "PL" and "JL" values , if so then i need to add a Indicator Column as "Y" else "N"

Example :

    //Input Values
    val values = List(List("66","PL") ,
    List("67","JL") , List("67","PL"),List("67","PO"),
    List("68","JL"),List("68","PO")).map(x =>(x(0), x(1)))

    import spark.implicits._
    //created a dataframe
    val cmc = values.toDF("KEY","TYPE_CODE")

    cmc.show(false)
    ------------------------
    KEY |TYPE_CODE  |
    ------------------------
    66  |PL |
    67  |JL |
    67  |PL |
    67  |PO |
    68  |JL |
    68  |PO |
    -------------------------

Expected Output :

For each "KEY", If it has "TYPE_CODE" has both PL & JL then Y else N

    -----------------------------------------------------
    KEY |TYPE_CODE  | Indicator
    -----------------------------------------------------
    66  |PL         | N
    67  |JL         | Y
    67  |PL         | Y
    67  |PO         | Y
    68  |JL         | N
    68  |PO         | N
    ---------------------------------------------------

For example, 67 has both PL & JL - So "Y" 66 has only PL - So "N" 68 has only JL - So "N"