Kaggle(ds2014)用ETL処理

KaggleApp.scala

import org.apache.spark._
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.rdd.RDD


object KaggleApp { 
	def main(args: Array[String]) { 

		val sc = new SparkContext("local", "Kaggle")
		
		println(" ************************* train ")
		impl(sc.textFile("mydata/train.csv"), "train")

		println(" ************************* test ")
		impl(sc.textFile("mydata/test_v2.csv"), "test")


		println("Grouped's params as CSV header")
		val g = new Grouped("","","","",0,"",0,"","",0,0,"","",0,false,false,false,false,false,false,false,false,false,false,false,false,0,0,0,0,"","","","","",0,0,0,0,"","","","","","","","","","","","","","",0,"","","","","","","",0,0,0,0,0,0,0,0,"",0)
		val tpe = ExtractTypeInfo.getType(g)
    	println(ExtractTypeInfo.getParamsAsCsvHeader(tpe))

	}

	def impl(tf:RDD[String], typ:String) {

		// 読み込んだCSVファイルの件数を確認
		println("train length : " + tf.count())
		// [info] train length : 665249

		// CSVを１行ずつHistoryオブジェクトに格納
		val histories:RDD[History] 
			= tf.map(line => line.split(",")).map(cols => 
				new History(
					cols(0), 			// customer_ID
					cols(1),			// shopping_pt
					cols(2),			// record_type
					cols(3),			// day
					cols(4),			// time
					cols(5),			// state
					cols(6),			// location
					cols(7).toInt,		// group_size
					cols(8),			// homeowner
					cols(9).toInt,		// car_age
					cols(10),			// car_value
					cols(11),			// risk_factor
					cols(12).toInt,		// age_oldest
					cols(13).toInt,		// age_youngest
					cols(14),			// married_couple
					cols(15),			// C_previous

					// NAだったら0を挿入する
					if(cols(16) == "NA") 0 else cols(16).toInt,		// duration_previous

					cols(17),			// A
					cols(18),			// B
					cols(19),			// C
					cols(20),			// D
					cols(21),			// E
					cols(22),			// F
					cols(23),			// G
					cols(24).toInt		// cost
				)
			)

		// customer_ID をキーにグルーピングした結果を、 Grouped オブジェクトに格納

		if(typ == "train"){
			val groupedTrain:RDD[Grouped]
				= histories
					.map(hist => (hist.customer_ID, hist))
					.groupByKey().mapValues { hists =>
						new Grouped(
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.customer_ID,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.day,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.state,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.location,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.group_size,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.homeowner,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.car_age,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.car_value,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.risk_factor,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.age_oldest,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.age_youngest,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.married_couple,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.c_previous,
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.duration_previous,

							// customer_ID キーでグルーピングされたリストに対して、
							// さらに 各プロパティ	 でグルーピングしてその件数を確認
							// １件だけならグルーピングの中で唯一と判断できる
							if(hists.groupBy(_.state).size == 1) true else false,
							if(hists.groupBy(_.location).size == 1) true else false,
							if(hists.groupBy(_.group_size).size == 1) true else false,
							if(hists.groupBy(_.homeowner).size == 1) true else false,
							if(hists.groupBy(_.car_age).size == 1) true else false,
							if(hists.groupBy(_.car_value).size == 1) true else false,
							if(hists.groupBy(_.risk_factor).size == 1) true else false,
							if(hists.groupBy(_.age_oldest).size == 1) true else false,
							if(hists.groupBy(_.age_youngest).size == 1) true else false,
							if(hists.groupBy(_.married_couple).size == 1) true else false,
							if(hists.groupBy(_.c_previous).size == 1) true else false,
							if(hists.groupBy(_.duration_previous).size == 1) true else false,

							hists.filter(_.record_type == "0").size,					// count

							hists.filter(_.record_type == "0").minBy(_.cost).cost,											// minCost
							hists.filter(_.record_type == "0").map(_.cost).sum / hists.filter(_.record_type == "0").size,	// meanCost
							hists.filter(_.record_type == "0").maxBy(_.cost).cost,											// maxCost

							hists.filter(_.record_type == "0").minBy(_.cost).policy,	// minCostPolicy
							hists.filter(_.record_type == "0").maxBy(_.cost).policy,	// maxCostPolicy
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.policy, 			// evePolicy
							hists.filter(_.shopping_pt == "1")(0).policy, 	// firstPolicy
//							hists(0).policy, 								// firstPolicy
							hists.filter(_.record_type == "0").sortBy(_.shopping_pt).last.policy,	// lastPolicy

							hists.filter(_.record_type == "0").groupBy(_.day).size,	// daysCount
							howLong(hists.filter(_.record_type == "0")),			// howLong

							howPrev(hists),											// howPrevPolicy
//							hists.filter(_.record_type == "1")(0).cost,				// finCost
							hists.sortBy(_.shopping_pt).last.cost,										// finCost

							hists.filter(_.record_type == "1")(0).A,
							hists.filter(_.record_type == "1")(0).B,
							hists.filter(_.record_type == "1")(0).C,
							hists.filter(_.record_type == "1")(0).D,
							hists.filter(_.record_type == "1")(0).E,
							hists.filter(_.record_type == "1")(0).F,
							hists.filter(_.record_type == "1")(0).G,

							/**
							if(hists.size > 0) hists.filter(_.shopping_pt == "1")(0).A else "",
							if(hists.size > 0) hists.filter(_.shopping_pt == "1")(0).B else "",
							if(hists.size > 0) hists.filter(_.shopping_pt == "1")(0).C else "",
							if(hists.size > 0) hists.filter(_.shopping_pt == "1")(0).D else "",
							if(hists.size > 0) hists.filter(_.shopping_pt == "1")(0).E else "",
							if(hists.size > 0) hists.filter(_.shopping_pt == "1")(0).F else "",
							if(hists.size > 0) hists.filter(_.shopping_pt == "1")(0).G else "",

							if(hists.size > 1) hists.filter(_.shopping_pt == "2")(0).A else "",
							if(hists.size > 1) hists.filter(_.shopping_pt == "2")(0).B else "",
							if(hists.size > 1) hists.filter(_.shopping_pt == "2")(0).C else "",
							if(hists.size > 1) hists.filter(_.shopping_pt == "2")(0).D else "",
							if(hists.size > 1) hists.filter(_.shopping_pt == "2")(0).E else "",
							if(hists.size > 1) hists.filter(_.shopping_pt == "2")(0).F else "",
							if(hists.size > 1) hists.filter(_.shopping_pt == "2")(0).G else "",
							**/

							hists.filter(_.shopping_pt == "1")(0).A,
							hists.filter(_.shopping_pt == "1")(0).B,
							hists.filter(_.shopping_pt == "1")(0).C,
							hists.filter(_.shopping_pt == "1")(0).D,
							hists.filter(_.shopping_pt == "1")(0).E,
							hists.filter(_.shopping_pt == "1")(0).F,
							hists.filter(_.shopping_pt == "1")(0).G,

							hists.filter(_.shopping_pt == "1")(0).cost,

							hists.filter(_.shopping_pt == "2")(0).A,
							hists.filter(_.shopping_pt == "2")(0).B,
							hists.filter(_.shopping_pt == "2")(0).C,
							hists.filter(_.shopping_pt == "2")(0).D,
							hists.filter(_.shopping_pt == "2")(0).E,
							hists.filter(_.shopping_pt == "2")(0).F,
							hists.filter(_.shopping_pt == "2")(0).G,

							hists.filter(_.shopping_pt == "2")(0).cost,

							howChg(hists, "A"),
							howChg(hists, "B"),
							howChg(hists, "C"),
							howChg(hists, "D"),
							howChg(hists, "E"),
							howChg(hists, "F"),
							howChg(hists, "G"),

							getChgOpt(	howChg(hists, "A"), 
										howChg(hists, "B"),
										howChg(hists, "C"),
										howChg(hists, "D"),
										howChg(hists, "E"),
										howChg(hists, "F"),
										howChg(hists, "G")),

							howOptChg(howChg(hists, "A"),howChg(hists, "B"),
								howChg(hists, "C"),howChg(hists, "D"),
								howChg(hists, "E"),howChg(hists, "F"),howChg(hists, "G"))
						)

					}.map(groupedHistory => groupedHistory._2)

			// グループングされた件数を確認
			println("groupedTrain length :" + groupedTrain.count())
			groupedTrain.saveAsTextFile("mydata/groups.train")

		}else if(typ == "test"){
			val groupedTest:RDD[Grouped]
				= histories
					.map(hist => (hist.customer_ID, hist))
					.groupByKey().mapValues { hists =>
						new Grouped(
								hists.sortBy(_.shopping_pt).last.customer_ID,
								hists.sortBy(_.shopping_pt).last.day,
								hists.sortBy(_.shopping_pt).last.state,
								hists.sortBy(_.shopping_pt).last.location,
								hists.sortBy(_.shopping_pt).last.group_size,
								hists.sortBy(_.shopping_pt).last.homeowner,
								hists.sortBy(_.shopping_pt).last.car_age,
								hists.sortBy(_.shopping_pt).last.car_value,
								hists.sortBy(_.shopping_pt).last.risk_factor,
								hists.sortBy(_.shopping_pt).last.age_oldest,
								hists.sortBy(_.shopping_pt).last.age_youngest,
								hists.sortBy(_.shopping_pt).last.married_couple,
								hists.sortBy(_.shopping_pt).last.c_previous,
								hists.sortBy(_.shopping_pt).last.duration_previous,

								// customer_ID キーでグルーピングされたリストに対して、
								// さらに 各プロパティ	 でグルーピングしてその件数を確認
								// １件だけならグルーピングの中で唯一と判断できる
								if(hists.groupBy(_.state).size == 1) true else false,
								if(hists.groupBy(_.location).size == 1) true else false,
								if(hists.groupBy(_.group_size).size == 1) true else false,
								if(hists.groupBy(_.homeowner).size == 1) true else false,
								if(hists.groupBy(_.car_age).size == 1) true else false,
								if(hists.groupBy(_.car_value).size == 1) true else false,
								if(hists.groupBy(_.risk_factor).size == 1) true else false,
								if(hists.groupBy(_.age_oldest).size == 1) true else false,
								if(hists.groupBy(_.age_youngest).size == 1) true else false,
								if(hists.groupBy(_.married_couple).size == 1) true else false,
								if(hists.groupBy(_.c_previous).size == 1) true else false,
								if(hists.groupBy(_.duration_previous).size == 1) true else false,

								hists.size,		// count

								hists.minBy(_.cost).cost,			// minCost
								hists.map(_.cost).sum / hists.size,	// meanCost
								hists.maxBy(_.cost).cost,			// maxCost

								hists.minBy(_.cost).policy,						// minCostPolicy
								hists.maxBy(_.cost).policy,						// maxCostPolicy
								hists.sortBy(_.shopping_pt).last.policy, 								// evePolicy
								hists.filter(_.shopping_pt == "1")(0).policy, 	// firstPolicy
								"",	// lastPolicy

								hists.groupBy(_.day).size,	// daysCount
								howLong(hists),				// howLong

								0,	// howPrevPolicy
								0,	// finCost

								hists.sortBy(_.shopping_pt).last.A,
								hists.sortBy(_.shopping_pt).last.B,
								hists.sortBy(_.shopping_pt).last.C,
								hists.sortBy(_.shopping_pt).last.D,
								hists.sortBy(_.shopping_pt).last.E,
								hists.sortBy(_.shopping_pt).last.F,
								hists.sortBy(_.shopping_pt).last.G,

								hists.filter(_.shopping_pt == "1")(0).A,
								hists.filter(_.shopping_pt == "1")(0).B,
								hists.filter(_.shopping_pt == "1")(0).C,
								hists.filter(_.shopping_pt == "1")(0).D,
								hists.filter(_.shopping_pt == "1")(0).E,
								hists.filter(_.shopping_pt == "1")(0).F,
								hists.filter(_.shopping_pt == "1")(0).G,

								hists.filter(_.shopping_pt == "1")(0).cost,

								hists.filter(_.shopping_pt == "2")(0).A,
								hists.filter(_.shopping_pt == "2")(0).B,
								hists.filter(_.shopping_pt == "2")(0).C,
								hists.filter(_.shopping_pt == "2")(0).D,
								hists.filter(_.shopping_pt == "2")(0).E,
								hists.filter(_.shopping_pt == "2")(0).F,
								hists.filter(_.shopping_pt == "2")(0).G,

								hists.filter(_.shopping_pt == "2")(0).cost,

								howChg(hists, "A"),
								howChg(hists, "B"),
								howChg(hists, "C"),
								howChg(hists, "D"),
								howChg(hists, "E"),
								howChg(hists, "F"),
								howChg(hists, "G"),

								getChgOpt(	howChg(hists, "A"), 
											howChg(hists, "B"),
											howChg(hists, "C"),
											howChg(hists, "D"),
											howChg(hists, "E"),
											howChg(hists, "F"),
											howChg(hists, "G")),

								howOptChg(	howChg(hists, "A"), 
											howChg(hists, "B"),
											howChg(hists, "C"),
											howChg(hists, "D"),
											howChg(hists, "E"),
											howChg(hists, "F"),
											howChg(hists, "G"))

						)
					}.map(groupedHistory => groupedHistory._2)

			println("groupedTrain length :" + groupedTest.count())
			groupedTest.saveAsTextFile("mydata/groups.test")
		}

		/**
		この結果、mydata/groups/part-0000* というファイルが複数作成されるので、それを以下のようにひとつのファイルに結合
		touch groups.csv
		cat groups/part-00000 >> groups.csv 
		cat groups/part-00001 >> groups.csv
		cat groups.csv | wc -l
		**/

	}//*
  
  def howPrev(hists:Seq[History]):Int = {
  	val sorted = hists.sortBy(_.shopping_pt).reverse //降順ソート
	val fin = sorted(0)
	val prevs = sorted.tail
	var cnt = 0

	prevs.foreach(prev =>
		if(prev.policy == fin.policy){
			cnt = cnt + 1
			return cnt
		}else{
			cnt = cnt + 1
		}
	)
	return cnt
  }

  def howLong(hists:Seq[History]):Int = {
  	val sorted = hists.sortBy(_.shopping_pt).reverse //降順ソート

  	if(sorted.size == 1){
  		return 0
  	}else{
		// tpl : (preDay, preTime, hl)
	  	sorted.foldLeft((0, 0, 0)){ (tpl, hist) => 
	  		val nowTime =  toMin(hist.time)
	  		if(tpl._1 == hist.day.toInt){
	  			(hist.day.toInt, nowTime, nowTime - tpl._2 + tpl._3)
			}else{
				(hist.day.toInt, nowTime, nowTime + tpl._3)
			}
	  	}._3
	}
  }

  def toMin(hhmm:String):Int = {
  	val h = hhmm.substring(0,2).toInt
  	val m = hhmm.substring(3,5).toInt
  	return h * 60 + m
  }

  def howChg(hists:Seq[History], a2g:String):Int = {
  	val sorted = hists.sortBy(_.shopping_pt)

	if(sorted.size == 1){
  		return 0
  	}else{
  		// tpl : (pre, count)
  		sorted.foldLeft(("",0)){ (tpl, hist) =>
			a2g match {
				case "A" => howChangedImpl(tpl._1, hist.A, tpl._2)
				case "B" => howChangedImpl(tpl._1, hist.B, tpl._2)
				case "C" => howChangedImpl(tpl._1, hist.C, tpl._2)
				case "D" => howChangedImpl(tpl._1, hist.D, tpl._2)
				case "E" => howChangedImpl(tpl._1, hist.E, tpl._2)
				case "F" => howChangedImpl(tpl._1, hist.F, tpl._2)
				case "G" => howChangedImpl(tpl._1, hist.G, tpl._2)
				case _ => throw new Exception("Unknown a2g :" + a2g)
			}
  		}._2
  	}
  }

  def howOptChg(a:Int, b:Int, c:Int, d:Int, e:Int, f:Int, g:Int) : Int = {
  	val ca = if(a > 0) 1 else 0
  	val cb = if(b > 0) 1 else 0
  	val cc = if(c > 0) 1 else 0
  	val cd = if(d > 0) 1 else 0
  	val ce = if(e > 0) 1 else 0
  	val cf = if(f > 0) 1 else 0
  	val cg = if(g > 0) 1 else 0
  	return ca + cb + cc + cd + ce + cf + cg
  }

  def getChgOpt(a:Int, b:Int, c:Int, d:Int, e:Int, f:Int, g:Int) : String = {
  	val ca = if(a > 0) 1 else 0
  	val cb = if(b > 0) 1 else 0
  	val cc = if(c > 0) 1 else 0
  	val cd = if(d > 0) 1 else 0
  	val ce = if(e > 0) 1 else 0
  	val cf = if(f > 0) 1 else 0
  	val cg = if(g > 0) 1 else 0
  	return "c" + ca.toString + cb.toString + cc.toString + cd.toString + ce.toString + cf.toString + cg.toString
  }

  def howChangedImpl(pre:String, opt:String, count:Int):(String, Int) = {
  	if(pre == ""){
  		(opt, 0)
	}else{
		if(pre == opt){
			(opt, count)
		}else{
			(opt, count + 1)
		}
	}
  }

}

Models.scala

import scala.reflect.runtime.{universe => ru}
import ru._

class History(
	val customer_ID:String,
	val shopping_pt:String,
	val record_type:String,
	val day:String,
	val time:String,
	val state:String,
	val location:String,
	val group_size:Int,
	val homeowner:String,
	val car_age:Int,
	val car_value:String,
	val risk_factor:String,
	val age_oldest:Int,
	val age_youngest:Int,
	val married_couple:String,
	val c_previous:String,
	val duration_previous:Int,
	val A:String,
	val B:String,
	val C:String,
	val D:String,
	val E:String,
	val F:String,
	val G:String,
	val cost:Int
	) extends Serializable {

	def policy:String = A + B + C + D + E + F + G

	override def toString = {
		customer_ID + "," +
		shopping_pt + "," +
		record_type + "," +
		day + "," +
		time + "," +
		state + "," +
		location + "," +
		group_size + "," +
		homeowner + "," +
		car_age + "," +
		car_value + "," +
		risk_factor + "," +
		age_oldest + "," +
		age_youngest + "," +
		married_couple + "," +
		c_previous + "," +
		duration_previous + "," +
		A + "," +
		B + "," +
		C + "," +
		D + "," +
		E + "," +
		F + "," +
		G + "," +
		cost
  	}

}

class Grouped(
	val customer_ID:String,
	val day:String,
	val state:String,
	val location:String,
	val group_size:Int,
	val homeowner:String,
	val car_age:Int,
	val car_value:String,
	val risk_factor:String,
	val age_oldest:Int,
	val age_youngest:Int,
	val married_couple:String,
	val c_previous:String,
	val duration_previous:Int,

	val isSingle_state:Boolean,
	val isSingle_location:Boolean,
	val isSingle_group_size:Boolean,
	val isSingle_homeowner:Boolean,
	val isSingle_car_age:Boolean,
	val isSingle_car_value:Boolean,
	val isSingle_risk_factor:Boolean,
	val isSingle_age_oldest:Boolean,
	val isSingle_age_youngest:Boolean,
	val isSingle_married_couple:Boolean,
	val isSingle_c_previous:Boolean,
	val isSingle_duration_previous:Boolean,

	val count:Int,			// 全部で何回見積もりしたか

	val minCost:Int,
	val meanCost:Int,
	val maxCost:Int,

	val minCostPolicy:String,
	val maxCostPolicy:String,
	val evePolicy:String,
	val firstPolicy:String,
	val lastPolicy:String,

	val daysCount:Int,
	val howLong:Int,

	val howPrevPolicy:Int,
	val finCost:Int,

	val vA:String,
	val vB:String,
	val vC:String,
	val vD:String,
	val vE:String,
	val vF:String,
	val vG:String,

	val vA1:String,
	val vB1:String,
	val vC1:String,
	val vD1:String,
	val vE1:String,
	val vF1:String,
	val vG1:String,

	val cost1:Int,

	val vA2:String,
	val vB2:String,
	val vC2:String,
	val vD2:String,
	val vE2:String,
	val vF2:String,
	val vG2:String,

	val cost2:Int,

	val cA:Int, //How many times Changed A
	val cB:Int,
	val cC:Int,
	val cD:Int,
	val cE:Int,
	val cF:Int,
	val cG:Int,
	val chgOpt:String,
	val howChanged:Int

) extends Serializable
{
	override def toString = {
		customer_ID + "," +
		day + "," +
		state + "," +
		location + "," +
		group_size + "," +
		homeowner + "," +
		car_age + "," +
		car_value + "," +
		risk_factor + "," +
		age_oldest + "," +
		age_youngest + "," +
		married_couple + "," +
		c_previous + "," +
		duration_previous + "," +
		isSingle_state + "," + 
		isSingle_location + "," + 
		isSingle_group_size + "," + 
		isSingle_homeowner + "," + 
		isSingle_car_age + "," + 
		isSingle_car_value + "," + 
		isSingle_risk_factor + "," + 
		isSingle_age_oldest + "," + 
		isSingle_age_youngest + "," + 
		isSingle_married_couple + "," + 
		isSingle_c_previous + "," + 
		isSingle_duration_previous + "," + 
		count + "," + 
		minCost + "," + 
		meanCost + "," + 
		maxCost + "," + 
		"p" + minCostPolicy + "," + 
		"p" + maxCostPolicy + "," + 
		"p" + evePolicy + "," + 
		"p" + firstPolicy + "," + 
		"p" + lastPolicy + "," +
		daysCount + "," + 
		howLong + "," + 
		howPrevPolicy + "," + 
		finCost + "," + 
		vA + "," +
		vB + "," +
		vC + "," +
		vD + "," +
		vE + "," +
		vF + "," +
		vG + "," +
		vA1 + "," +
		vB1 + "," +
		vC1 + "," +
		vD1 + "," +
		vE1 + "," +
		vF1 + "," +
		vG1 + "," +
		cost1 + "," +
		vA2 + "," +
		vB2 + "," +
		vC2 + "," +
		vD2 + "," +
		vE2 + "," +
		vF2 + "," +
		vG2 + "," +
		cost2 + "," +
		cA + "," + 
		cB + "," + 
		cC + "," + 
		cD + "," + 
		cE + "," + 
		cF + "," + 
		cG + "," + 
		chgOpt + "," +
		howChanged
  	}
}

class States(
	val state:String, //州略称
	val state_e:String, //州名称（英語）
	val state_j:String, //州名称（日本語）
	val kokusei1:String, //国勢調査１コード
	val kokusei1_ryk:String, //国勢調査１略号
	val kokusei2:String, //国勢調査２コード
	val kokusei2_ryk:String, //国勢調査２略号
	val gyosei:String, //行政管理予算局コード
	val gyosei_ryk:String, //行政管理予算局略号
	val keizai:String, //経済分析局
	val keizai_ryk:String, //経済分析局略号
	val hanzai:Int, //暴力犯罪発生率
	val hanzai_hyoka:String, //暴力犯罪評価
	val jinko:Int, //人口
	val jinko_mitsudo:Int, //人口密度
	val jinko_mitsudo_hyoka:String, //人口密度の評価
	val shotoku_jumin:Int, //住民１人あたり所得
	val shotoku_kojin:Int, //個人所得
	val shotoku_hensa:Int, //偏差値
	val shotoku_hyoka:Int, //所得評価
	val menkyo_seigen_ari:Int, //制限付き免許年齢
	val menkyo:Int, //免許年齢
	val menkyo_joken:String //免許条件有無

) extends Serializable
{
	override def toString = {
		state + "," + 
		state_e + "," + 
		state_j + "," + 
		kokusei1 + "," + 
		kokusei1_ryk + "," + 
		kokusei2 + "," + 
		kokusei2_ryk + "," + 
		gyosei + "," + 
		gyosei_ryk + "," + 
		keizai + "," + 
		keizai_ryk + "," + 
		hanzai + "," + 
		hanzai_hyoka + "," + 
		jinko + "," + 
		jinko_mitsudo + "," + 
		jinko_mitsudo_hyoka + "," + 
		shotoku_jumin + "," + 
		shotoku_kojin + "," + 
		shotoku_hensa + "," + 
		shotoku_hyoka + "," + 
		menkyo_seigen_ari + "," + 
		menkyo + "," + 
		menkyo_joken
	}
}