// Part 2 about Alcohol-Consumption Worldwide
//============================================
object CW6b {
import io.Source
import scala.util._
val url_alcohol =
"https://raw.githubusercontent.com/fivethirtyeight/data/master/alcohol-consumption/drinks.csv"
val file_population =
"population.csv"
//(1) Complete the get_csv_page function below. It takes a URL-string
// as argument and generates a list of strings corresponding to each
// line in the downloaded csv-list. The URL url_alcohol above is one
// possible argument.
//def get_csv_page(url: String) : List[String] = ...
def get_csv_page(url: String) : List[String] = {
val csv = Source.fromURL(url)
val contents = csv.mkString.split("\n")
contents.toList
}
// Complete the get_csv_file function below. It takes a file name
// as argument and reads the content of the given file. Like above,
// it should generate a list of strings corresponding to each
// line in the csv-list. The filename file_population is one possible
// argument.
//def get_csv_file(file: String) : List[String] = ...
def get_csv_file(file: String) : List[String] = {
val csv = Source.fromFile(file)
val contents = csv.mkString.split("\n")
contents.toList
}
//(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 sizes).
//def process_alcs(lines: List[String]) : List[(String, Double)] = ...
def process_alcs(lines: List[String]) : List[(String, Double)] = {
val beheaded = lines.drop(1)
val splitEntries = for (n <- beheaded) yield n.split(",").toList
for (n <- splitEntries) yield (n.take(1).mkString, n.drop(4).mkString.toDouble)
}
//def process_pops(lines: List[String]) : Map[String, Long] = ...
def process_pops(lines: List[String]) : Map[String, Long] = {
val beheaded = lines.drop(1);
def toOnePair(line: String) : (String, Long) = {
val splitAsList = line.split(",").toList
(splitAsList.take(1).mkString, splitAsList.drop(1).mkString.toLong)
}
val splitEntries = for (n <- beheaded) yield toOnePair(n)
splitEntries.toMap
}
//(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
// on the population sizes list with the exact same name. Note that
// the spelling of some names in the alcohol list differs from the
// population sizes list. You can ignore entries where the names differ.
// 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)] = ...
def sorted_country_consumption() : List[(String, Long)] = {
val countryToPop = process_pops(get_csv_file(file_population))
val countryAndAlc = process_alcs(get_csv_page(url_alcohol))
val countryAndConsumption = countryAndAlc.collect {
case oneCountryAndAlc
if countryToPop.isDefinedAt(oneCountryAndAlc._1) =>
(oneCountryAndAlc._1, (oneCountryAndAlc._2*countryToPop.get(oneCountryAndAlc._1).get).toLong)
}
countryAndConsumption.sortWith(_._2 > _._2)
}
// 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 drinking from the the world consumption of alcohol.
//def percentage(n: Int) : (Long, Long, Double) = ...
def percentage(n: Int) : (Long, Long, Double) = {
val ctryConsump = sorted_country_consumption()
val totalAlc = ctryConsump.map(_._2).sum
val firstNAlc = ctryConsump.take(n).map(_._2).sum
val pcntage = (firstNAlc*1.0/totalAlc)*100;
(ctryConsump.map(_._2).sum, ctryConsump.take(n).map(_._2).sum, pcntage)
}
}