How To Apply Multiple Conditions on Case-Otherwise Statement Using Spark Dataframe API

I am trying to add a new column to an existing data frame using the withColumn statement in Spark Dataframe API. The below code works but I was wondering if there's a way that I can select more than one group. Let's say Group 1, 2, 3, 4 instead of only Group 1. I think I may be able to write when statement four times. I have seen people do that in some posts. However, in R, there is a %in% operator that can specify if a variable contains values in a vector, but I don't know if there's such thing in Spark. I checked on the Spark API documentation but most of the functions don't contain any examples.

# R Sample Code:
 library(dplyr)
 df1 <- df %>% mutate( Selected_Group = (Group %in% 1:4))

Spark Dataframe Sample Code That Selects Group 1:

 val df1 = df.withColumn("Selected_Group", when($"Group" === 1, 1).otherwise(0))

Data

ID, Group
1, 0
2, 1
3, 2
. .
. .
100, 99