Error in creating dataframe: java.lang.RuntimeException: scala.Tuple2 is not a valid external type for schema of string

You don't need a schema to create a Row, you need the schema when you create the DataFrame. You also need to introduce some logic how to convert your splitted line (which produces 3 strings) into integers:

here a minimal solution without exception-handling:

val data = sc.parallelize(Seq("Bern;10;12")) // mock for real data

val schema = new StructType().add("city", StringType, true).add("female", IntegerType, true).add("male", IntegerType, true)

val cities = data.map(line => {
val Array(city,female,male) = line.split(";")
  Row(
    city,
    female.toInt,
    male.toInt
  )
 }
)

val citiesDF = sqlContext.createDataFrame(cities, schema)

I normally use case-classes to create a dataframe, because spark can infer the schema from the case class:

// "schema" for dataframe, define outside of main method
case class MyRow(city:Option[String],female:Option[Int],male:Option[Int]) 

val data = sc.parallelize(Seq("Bern;10;12")) // mock for real data

import sqlContext.implicits._

val citiesDF = data.map(line => {
val Array(city,female,male) = line.split(";")
  MyRow(
    Some(city),
    Some(female.toInt),
    Some(male.toInt)
  )
}
).toDF()