Pre_process_rosters.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "spark = org.apache.spark.sql.SparkSession@4fd07a98\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "org.apache.spark.sql.SparkSession@4fd07a98"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import org.apache.spark.sql.{DataFrame, Dataset, Row, SparkSession}\n",
    "import org.apache.spark.sql.functions._\n",
    "import org.apache.spark.sql.types._\n",
    "val spark = SparkSession.builder.master(\"local[*]\").appName(\"dataProcessing\").getOrCreate()\n",
    "import spark.implicits._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
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     "text": [
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     ]
    }
   ],
   "source": [
    "import java.io.File\n",
    "import scala.io.Source\n",
    "\n",
    "val path = System.getProperty(\"user.dir\")\n",
    "val seasons = 1990 to 2018\n",
    "val teams = 1 to 30\n",
    "\n",
    "for (i <- seasons){\n",
    "    for (j <- teams){\n",
    "        val file = path + \"/season_averages/\" + i + \"/rosters_old/\" + j + \".json\"\n",
    "        try{\n",
    "            var df_stats = spark.read.json(file)\n",
    "            var elem = df_stats.select(explode($\"data\").as(\"data\"))\n",
    "            var minutes = elem.select(\"data.min\")\n",
    "            val split_min = elem.withColumn(\"seconds\", split($\"data.min\", \":\")(0) * 60 + split($\"data.min\", \":\")(1))\n",
    "            val best_12 = split_min.orderBy(desc(\"seconds\")).limit(12)\n",
    "            \n",
    "            val best_12_struct = best_12.withColumn(\"row\", struct(col(\"data.ast\"), col(\"data.blk\"), col(\"data.dreb\"),\n",
    "                                                                  col(\"data.fg3_pct\"), col(\"data.fg3a\"), \n",
    "                                                                  col(\"data.fg3m\"), col(\"data.fg_pct\"), \n",
    "                                                                  col(\"data.fga\"), col(\"data.fgm\"), \n",
    "                                                                  col(\"data.ft_pct\"), col(\"data.fta\"),\n",
    "                                                                  col(\"data.ftm\"), col(\"data.games_played\"), \n",
    "                                                                  col(\"seconds\"), col(\"data.oreb\"), col(\"data.pf\"),\n",
    "                                                                  col(\"data.player_id\"), \n",
    "                                                                  col(\"data.pts\"), col(\"data.reb\"), \n",
    "                                                                  col(\"data.season\"), col(\"data.stl\"), \n",
    "                                                                  col(\"data.turnover\"))).agg(collect_list(col(\"row\")).as(\"data\"))\n",
    "            \n",
    "            val best_12_data = best_12_struct.select(\"data\")\n",
    "            best_12_data.write.mode(\"overwrite\").format(\"json\").save(path + \"/season_averages/\" + i + \"/\" + j)\n",
    "\n",
    "            \n",
    "            val best_12_36 = best_12.withColumn(\"ast\", (col(\"data.ast\") / col(\"seconds\") * 2160))\n",
    "                                    .withColumn(\"blk\", col(\"data.blk\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"dreb\", col(\"data.dreb\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"fg3a\", col(\"data.fg3a\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"fg3m\", col(\"data.fg3m\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"fga\", col(\"data.fga\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"fgm\", col(\"data.fgm\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"fta\", col(\"data.fta\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"ftm\", col(\"data.ftm\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"oreb\", col(\"data.oreb\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"pf\", col(\"data.pf\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"pts\", col(\"data.pts\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"reb\", col(\"data.reb\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"seconds\", col(\"seconds\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"stl\", col(\"data.stl\") / col(\"seconds\") * 2160)\n",
    "                                    .withColumn(\"turnover\", col(\"data.turnover\") / col(\"seconds\") * 2160)\n",
    "\n",
    "            val best_12_36_struct = best_12_36.withColumn(\"row\", struct(col(\"ast\"), col(\"blk\"), col(\"dreb\"), \n",
    "                                                                        col(\"data.fg3_pct\"), col(\"fg3a\"), \n",
    "                                                                        col(\"fg3m\"), col(\"data.fg_pct\"), col(\"fga\"),\n",
    "                                                                        col(\"fgm\"), col(\"data.ft_pct\"),\n",
    "                                                                        col(\"fta\"), col(\"ftm\"),\n",
    "                                                                        col(\"data.games_played\"), \n",
    "                                                                        col(\"seconds\"), col(\"oreb\"), \n",
    "                                                                        col(\"pf\"), col(\"data.player_id\"),\n",
    "                                                                        col(\"pts\"), col(\"reb\"), col(\"data.season\"),\n",
    "                                                                        col(\"stl\"), col(\"turnover\"))).agg(collect_list(col(\"row\")).as(\"data\"))\n",
    "            val best_12_36_data = best_12_36_struct.select(\"data\")\n",
    "            best_12_36_data.write.mode(\"overwrite\").format(\"json\").save(path + \"/season_averages/\" + i + \"/\" + j + \"-36\")\n",
    "            println(\"File \" + file + \" saved\")\n",
    "            \n",
    "        \n",
    "        }\n",
    "        catch{\n",
    "            case e: org.apache.spark.sql.AnalysisException => println(\"File \" + file + \" not found\")\n",
    "        }\n",
    "    } \n",
    "}"
   ]
  }
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