diff -r fd03a2f06286 -r 1b0f1573c27c templates/alcohol.scala
--- a/templates/alcohol.scala	Tue Nov 07 14:17:21 2017 +0000
+++ b/templates/alcohol.scala	Wed Nov 08 02:06:54 2017 +0000
@@ -6,64 +6,60 @@
 import io.Source
 import scala.util._
 
-def get_csv_page(url: String) : List[String] = 
-  Source.fromURL(url)("ISO-8859-1").getLines.toList
-
-def get_csv_file(file: String) : List[String] = 
-  Source.fromFile(file)("ISO-8859-1").getLines.toList
-
-
 val url_alcohol = 
   "https://raw.githubusercontent.com/fivethirtyeight/data/master/alcohol-consumption/drinks.csv"
 
 val file_population = 
   "population.csv"
 
-get_csv_page(url_alcohol)
-get_csv_file(file_population)
 
-get_csv_page(url_alcohol).size
-get_csv_file(file_population).size
+//(1) Complete the get_csv_page function below. It takes the URL-string
+//    as argument and generates a list of strings corresponing to each
+//    line in the csv list. The URL url_alcohol is one possible argument.
 
-val alcs = get_csv_page(url_alcohol)
-val pops = get_csv_file(file_population)
+//def get_csv_page(url: String) : List[String] = ...
 
 
-def process_alcs(lines: List[String]) : List[(String, Double)] =
-  for (l <- lines) yield {
-    val entries = l.split(",").toList 
-    (entries(0), entries(4).toDouble) 
-  }
+//    Complete the get_csv_file function below. It takes a file-string
+//    as argument and reads the content of the given file. Like above
+//    it should generates a list of strings corresponing to each
+//    line in the csv-list. The filename file_population is one possible
+//    argument.
 
-def process_pops(lines: List[String]) : Map[String, Long] =
-  (for (l <- lines) yield {
-    val entries = l.split(",").toList 
-    (entries(0), entries(1).toLong)
-  }).toMap
+//def get_csv_file(file: String) : List[String] = ...
+
 
 
-def sorted_country_consumption() : List[(String, Long)] = {
-  val alcs2 = process_alcs(alcs.drop(1))
-  val pops2 = process_pops(pops.drop(1))
-  val cons_list = 
-    for ((cname, cons) <- alcs2; 
-	 if pops2.isDefinedAt(cname)) yield (cname, (cons * pops2(cname)).toLong)
-  cons_list.sortBy(_._2).reverse
-}
+//(2) Complete the functions that process the csv-lists. For
+//    process_alcs extract the country name (as String) and the 
+//    pure alcohol consumption (as Double). For process_pops
+//    generate a Map of Strings (country names) to Long numbers 
+//    (population size). 
 
-sorted_country_consumption().take(10)
-sorted_country_consumption().size
+//def process_alcs(lines: List[String]) : List[(String, Double)] = ...
 
-def percentage(n: Int) : (Long, Long, Double) = {
-  val cons_list = sorted_country_consumption()
-  val sum_n = cons_list.take(n).map(_._2).sum
-  val sum_all = cons_list.map(_._2).sum
-  val perc = (sum_n.toDouble / sum_all.toDouble) * 100.0
-  (sum_all, sum_n, perc)
-}
+//def process_pops(lines: List[String]) : Map[String, Long] = ...
+
 
 
-percentage(10)
-percentage(164)
+//(3) Calculate for each country the overall alcohol_consumption using
+//    the data from the alcohol list and the population sizes list. You
+//    should only include countries on the alcohol list that are also
+//    (with the exact name) on the population sizes list. Note that
+//    the spelling of some names in the alcohol list differs from the
+//    population sizes list. Sort the resulting list according to the 
+//    country with the highest alcohol consumption to the country 
+//    with the lowest alcohol consumption.
+
+//def sorted_country_consumption() : List[(String, Long)] = ...
+
+
+//   Calculate the world consumption of pure alcohol of all countries, which 
+//   should be the first element in the tuple below. The second element is
+//   the overall consumption of the first n countries in the sorted list
+//   from above; and finally the double should be the percentage of the 
+//   first n countries of the the world consumption of alcohol.          
+
+//def percentage(n: Int) : (Long, Long, Double) = ...
 
 }