JuliaHealth-Patient-level-prediction .ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "702f6894",
   "metadata": {},
   "outputs": [],
   "source": [
    "using SQLite\n",
    "using LibPQ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "171d3c73",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mGlobal database dialect set to: postgresql\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mGlobal schema set to: omop\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mmeasurement table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mpayer_plan_period table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mlocation table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39msource_to_concept_map table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mnote_nlp table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mvisit_detail_assign table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mvisit_occurrence table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mvocabulary table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mprocedure_occurrence table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mrelationship table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mdomain table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mdose_era table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mconcept table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mdeath table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mmetadata table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mconcept_class table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mdrug_era table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mnote table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mspecimen table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mcondition_occurrence table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mconcept_ancestor table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mcohort table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mfact_relationship table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mdrug_exposure table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mperson table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mobservation_period table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mcost table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mcohort_attribute table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mobservation table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mcondition_era table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mconcept_relationship table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mprovider table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mconcept_synonym table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mattribute_definition table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mcdm_source table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mcohort_definition table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mdrug_strength table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mvisit_detail table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mcare_site table generated internally\n",
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mdevice_exposure table generated internally\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "46520-element Vector{Int64}:\n",
       " 622701440\n",
       " 622684030\n",
       " 622692774\n",
       " 622709475\n",
       " 622705072\n",
       " 622691611\n",
       " 622703768\n",
       " 622697129\n",
       " 622701153\n",
       " 622682262\n",
       " 622705465\n",
       " 622711774\n",
       " 622693042\n",
       "         ⋮\n",
       " 622690452\n",
       " 622698813\n",
       " 622691630\n",
       " 622689444\n",
       " 622691888\n",
       " 622678894\n",
       " 622709120\n",
       " 622702234\n",
       " 622706201\n",
       " 622680998\n",
       " 622693599\n",
       " 622698890"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using DataFrames\n",
    "using DBInterface\n",
    "import OMOPCDMCohortCreator as occ\n",
    "\"\"\"\n",
    "using OMOPCDMDatabaseConnector\n",
    "This package will connect the database directly in the future but it is still under maintanence\n",
    "\"\"\"\n",
    "\n",
    "#connecting the basic way\n",
    "DBconn = DBInterface.connect(LibPQ.Connection,\"**********************************\")\n",
    "occ.GenerateDatabaseDetails(\n",
    "           :postgresql,\n",
    "           \"omop\"\n",
    "       )\n",
    "tables = occ.GenerateTables(DBconn)\n",
    "occ.GetDatabasePersonIDs(DBconn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6bc17658",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "93-element Vector{Int64}:\n",
       "  4164092\n",
       " 44784623\n",
       " 40480002\n",
       " 43530679\n",
       "   437544\n",
       " 43531622\n",
       "  4112018\n",
       "   374055\n",
       "   759831\n",
       "   442615\n",
       "   437540\n",
       "  4201094\n",
       "  4326561\n",
       "        ⋮\n",
       "  4318408\n",
       "   439040\n",
       "   433050\n",
       "   618759\n",
       "  4045745\n",
       "   373503\n",
       "  4154699\n",
       "  4136546\n",
       "  4017107\n",
       "   380423\n",
       "   434656\n",
       " 43531583"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### The concepts for AFib and Stroke from ATLAS OHDSI\n",
    "\n",
    "Afib = [4199501,313217]\n",
    "stroke = [4164092,\n",
    "44784623,\n",
    "40480002,\n",
    "43530679,\n",
    "437544,\n",
    "43531622,\n",
    "4112018,\n",
    "374055,\n",
    "759831,\n",
    "442615,\n",
    "437540,\n",
    "4201094,\n",
    "4326561,\n",
    "4029497,\n",
    "380747,\n",
    "372924,\n",
    "316437,\n",
    "375557,\n",
    "376713,\n",
    "374384,\n",
    "441874,\n",
    "381316,\n",
    "381591,\n",
    "44782819,\n",
    "36712779,\n",
    "438873,\n",
    "438881,\n",
    "438270,\n",
    "434166,\n",
    "440537,\n",
    "4014781,\n",
    "372721,\n",
    "4159164,\n",
    "4153380,\n",
    "37109512,\n",
    "432346,\n",
    "43530687,\n",
    "40479575,\n",
    "4306943,\n",
    "441246,\n",
    "40481762,\n",
    "40484522,\n",
    "40484513,\n",
    "436277,\n",
    "437427,\n",
    "439190,\n",
    "439847,\n",
    "42873157,\n",
    "444197,\n",
    "444198,\n",
    "444196,\n",
    "433624,\n",
    "436526,\n",
    "40492969,\n",
    "434155,\n",
    "4310996,\n",
    "434056,\n",
    "40480938,\n",
    "40481842,\n",
    "378774,\n",
    "377254,\n",
    "444091,\n",
    "443790,\n",
    "443864,\n",
    "314667,\n",
    "436430,\n",
    "4162038,\n",
    "435378,\n",
    "433037,\n",
    "372654,\n",
    "443599,\n",
    "436519,\n",
    "260841,\n",
    "313272,\n",
    "313833,\n",
    "40480449,\n",
    "432923,\n",
    "4134162,\n",
    "441709,\n",
    "440244,\n",
    "378544,\n",
    "4318408,\n",
    "439040,\n",
    "433050,\n",
    "618759,\n",
    "4045745,\n",
    "373503,\n",
    "4154699,\n",
    "4136546,\n",
    "4017107,\n",
    "380423,\n",
    "434656,\n",
    "43531583]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "57d48389",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>46476×3 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">46451 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">subject_id</th><th style = \"text-align: left;\">person_id</th><th style = \"text-align: left;\">age</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Union{Missing, Int32}\" style = \"text-align: left;\">Int32?</th><th title = \"Union{Missing, Int32}\" style = \"text-align: left;\">Int32?</th><th title = \"Union{Missing, Int32}\" style = \"text-align: left;\">Int32?</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">249</td><td style = \"text-align: right;\">622672103</td><td style = \"text-align: right;\">75</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">250</td><td style = \"text-align: right;\">622672104</td><td style = \"text-align: right;\">24</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">251</td><td style = \"text-align: right;\">622672105</td><td style = \"text-align: right;\">20</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">252</td><td style = \"text-align: right;\">622672106</td><td style = \"text-align: right;\">55</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: right;\">253</td><td style = \"text-align: right;\">622672107</td><td style = \"text-align: right;\">84</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: right;\">255</td><td style = \"text-align: right;\">622672108</td><td style = \"text-align: right;\">78</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: right;\">256</td><td style = \"text-align: right;\">622672109</td><td style = \"text-align: right;\">77</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"text-align: right;\">257</td><td style = \"text-align: right;\">622672110</td><td style = \"text-align: right;\">82</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: right;\">258</td><td style = \"text-align: right;\">622672111</td><td style = \"text-align: right;\">0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: right;\">260</td><td style = \"text-align: right;\">622672112</td><td style = \"text-align: right;\">0</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"text-align: right;\">261</td><td style = \"text-align: right;\">622672113</td><td style = \"text-align: right;\">76</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">12</td><td style = \"text-align: right;\">262</td><td style = \"text-align: right;\">622672114</td><td style = \"text-align: right;\">64</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">13</td><td style = \"text-align: right;\">263</td><td style = \"text-align: right;\">622672115</td><td style = \"text-align: right;\">56</td></tr><tr><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46465</td><td style = \"text-align: right;\">44065</td><td style = \"text-align: right;\">622718611</td><td style = \"text-align: right;\">66</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46466</td><td style = \"text-align: right;\">44069</td><td style = \"text-align: right;\">622718612</td><td style = \"text-align: right;\">67</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46467</td><td style = \"text-align: right;\">44071</td><td style = \"text-align: right;\">622718613</td><td style = \"text-align: right;\">60</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46468</td><td style = \"text-align: right;\">44073</td><td style = \"text-align: right;\">622718614</td><td style = \"text-align: right;\">88</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46469</td><td style = \"text-align: right;\">44082</td><td style = \"text-align: right;\">622718615</td><td style = \"text-align: right;\">66</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46470</td><td style = \"text-align: right;\">44083</td><td style = \"text-align: right;\">622718616</td><td style = \"text-align: right;\">54</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46471</td><td style = \"text-align: right;\">44084</td><td style = \"text-align: right;\">622718617</td><td style = \"text-align: right;\">58</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46472</td><td style = \"text-align: right;\">44089</td><td style = \"text-align: right;\">622718618</td><td style = \"text-align: right;\">85</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46473</td><td style = \"text-align: right;\">44115</td><td style = \"text-align: right;\">622718619</td><td style = \"text-align: right;\">37</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46474</td><td style = \"text-align: right;\">44123</td><td style = \"text-align: right;\">622718620</td><td style = \"text-align: right;\">85</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46475</td><td style = \"text-align: right;\">44126</td><td style = \"text-align: right;\">622718621</td><td style = \"text-align: right;\">52</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">46476</td><td style = \"text-align: right;\">44128</td><td style = \"text-align: right;\">622718622</td><td style = \"text-align: right;\">51</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccc}\n",
       "\t& subject\\_id & person\\_id & age\\\\\n",
       "\t\\hline\n",
       "\t& Int32? & Int32? & Int32?\\\\\n",
       "\t\\hline\n",
       "\t1 & 249 & 622672103 & 75 \\\\\n",
       "\t2 & 250 & 622672104 & 24 \\\\\n",
       "\t3 & 251 & 622672105 & 20 \\\\\n",
       "\t4 & 252 & 622672106 & 55 \\\\\n",
       "\t5 & 253 & 622672107 & 84 \\\\\n",
       "\t6 & 255 & 622672108 & 78 \\\\\n",
       "\t7 & 256 & 622672109 & 77 \\\\\n",
       "\t8 & 257 & 622672110 & 82 \\\\\n",
       "\t9 & 258 & 622672111 & 0 \\\\\n",
       "\t10 & 260 & 622672112 & 0 \\\\\n",
       "\t11 & 261 & 622672113 & 76 \\\\\n",
       "\t12 & 262 & 622672114 & 64 \\\\\n",
       "\t13 & 263 & 622672115 & 56 \\\\\n",
       "\t14 & 264 & 622672116 & 0 \\\\\n",
       "\t15 & 265 & 622672117 & 56 \\\\\n",
       "\t16 & 266 & 622672118 & 78 \\\\\n",
       "\t17 & 267 & 622672119 & 25 \\\\\n",
       "\t18 & 268 & 622672120 & 66 \\\\\n",
       "\t19 & 269 & 622672121 & 40 \\\\\n",
       "\t20 & 270 & 622672122 & 80 \\\\\n",
       "\t21 & 663 & 622672123 & 58 \\\\\n",
       "\t22 & 664 & 622672124 & 82 \\\\\n",
       "\t23 & 665 & 622672125 & 62 \\\\\n",
       "\t24 & 666 & 622672126 & 60 \\\\\n",
       "\t25 & 667 & 622672127 & 70 \\\\\n",
       "\t26 & 668 & 622672128 & 87 \\\\\n",
       "\t27 & 669 & 622672129 & 61 \\\\\n",
       "\t28 & 670 & 622672130 & 80 \\\\\n",
       "\t29 & 671 & 622672131 & 48 \\\\\n",
       "\t30 & 672 & 622672132 & 47 \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m46476×3 DataFrame\u001b[0m\n",
       "\u001b[1m   Row \u001b[0m│\u001b[1m subject_id \u001b[0m\u001b[1m person_id \u001b[0m\u001b[1m age    \u001b[0m\n",
       "       │\u001b[90m Int32?     \u001b[0m\u001b[90m Int32?    \u001b[0m\u001b[90m Int32? \u001b[0m\n",
       "───────┼───────────────────────────────\n",
       "     1 │        249  622672103      75\n",
       "     2 │        250  622672104      24\n",
       "     3 │        251  622672105      20\n",
       "     4 │        252  622672106      55\n",
       "     5 │        253  622672107      84\n",
       "     6 │        255  622672108      78\n",
       "     7 │        256  622672109      77\n",
       "     8 │        257  622672110      82\n",
       "     9 │        258  622672111       0\n",
       "    10 │        260  622672112       0\n",
       "    11 │        261  622672113      76\n",
       "   ⋮   │     ⋮           ⋮        ⋮\n",
       " 46467 │      44071  622718613      60\n",
       " 46468 │      44073  622718614      88\n",
       " 46469 │      44082  622718615      66\n",
       " 46470 │      44083  622718616      54\n",
       " 46471 │      44084  622718617      58\n",
       " 46472 │      44089  622718618      85\n",
       " 46473 │      44115  622718619      37\n",
       " 46474 │      44123  622718620      85\n",
       " 46475 │      44126  622718621      52\n",
       " 46476 │      44128  622718622      51\n",
       "\u001b[36m                     46455 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### since mimic iii data manipulated date of birth for patients for privacy issues, it can be retrieved from mimic data using this query\n",
    "## IMPORTANT NOTE: Addition of 229896253 for each mimic_id is a special case for our database, Almost you don't have to add it\n",
    "\n",
    "Mconn = LibPQ.Connection(\"*******************************************\")\n",
    "LibPQ.execute(Mconn,\"set search_path to mimiciii\")\n",
    "\n",
    "### something happened in the database and each mimic_id is past its corresponding person_id by 229896253\n",
    "\n",
    "age_mimic = LibPQ.execute(Mconn,\"SELECT pat.subject_id, (pat.mimic_id) AS person_id,\n",
    " CAST(CAST(EXTRACT(epoch FROM adm.admittime - pat.dob)/(60*60*24*365.242) AS numeric) AS integer) AS age\n",
    "FROM icustays ie\n",
    "INNER JOIN admissions adm\n",
    "    ON ie.hadm_id = adm.hadm_id\n",
    "INNER JOIN patients pat\n",
    "    ON ie.subject_id = pat.subject_id\n",
    ";\") |> DataFrame\n",
    "age_mimic = unique(age_mimic, :person_id)\n",
    "sort(age_mimic, :person_id)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "af85c242",
   "metadata": {},
   "outputs": [],
   "source": [
    "### Getting list of person_ids who suffer from AFib and stroke using OMOPCDMCohortCreator###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e81683fc",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>15137×3 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">15112 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">person_id</th><th style = \"text-align: left;\">has_AFib</th><th style = \"text-align: left;\">has_stroke</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Int32\" style = \"text-align: left;\">Int32</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">622707430</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">622716907</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">622704382</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">622695167</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">5</td><td style = \"text-align: right;\">622679460</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">6</td><td style = \"text-align: right;\">622673865</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">7</td><td style = \"text-align: right;\">622690154</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">8</td><td style = \"text-align: right;\">622679180</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">9</td><td style = \"text-align: right;\">622678192</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">10</td><td style = \"text-align: right;\">622702721</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">11</td><td style = \"text-align: right;\">622693672</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">12</td><td style = \"text-align: right;\">622697655</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">13</td><td style = \"text-align: right;\">622713836</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15126</td><td style = \"text-align: right;\">622707415</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15127</td><td style = \"text-align: right;\">622700696</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15128</td><td style = \"text-align: right;\">622679790</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15129</td><td style = \"text-align: right;\">622687676</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15130</td><td style = \"text-align: right;\">622691527</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15131</td><td style = \"text-align: right;\">622717579</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15132</td><td style = \"text-align: right;\">622698960</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15133</td><td style = \"text-align: right;\">622702426</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15134</td><td style = \"text-align: right;\">622708972</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15135</td><td style = \"text-align: right;\">622701212</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15136</td><td style = \"text-align: right;\">622717243</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15137</td><td style = \"text-align: right;\">622690412</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccc}\n",
       "\t& person\\_id & has\\_AFib & has\\_stroke\\\\\n",
       "\t\\hline\n",
       "\t& Int32 & Int64 & Int64\\\\\n",
       "\t\\hline\n",
       "\t1 & 622707430 & 1 & 1 \\\\\n",
       "\t2 & 622716907 & 1 & 1 \\\\\n",
       "\t3 & 622704382 & 1 & 1 \\\\\n",
       "\t4 & 622695167 & 1 & 1 \\\\\n",
       "\t5 & 622679460 & 1 & 1 \\\\\n",
       "\t6 & 622673865 & 1 & 1 \\\\\n",
       "\t7 & 622690154 & 1 & 1 \\\\\n",
       "\t8 & 622679180 & 1 & 1 \\\\\n",
       "\t9 & 622678192 & 1 & 1 \\\\\n",
       "\t10 & 622702721 & 1 & 1 \\\\\n",
       "\t11 & 622693672 & 1 & 1 \\\\\n",
       "\t12 & 622697655 & 1 & 1 \\\\\n",
       "\t13 & 622713836 & 1 & 1 \\\\\n",
       "\t14 & 622698895 & 1 & 1 \\\\\n",
       "\t15 & 622705975 & 1 & 1 \\\\\n",
       "\t16 & 622712282 & 1 & 1 \\\\\n",
       "\t17 & 622706810 & 1 & 1 \\\\\n",
       "\t18 & 622698969 & 1 & 1 \\\\\n",
       "\t19 & 622704074 & 1 & 1 \\\\\n",
       "\t20 & 622685911 & 1 & 1 \\\\\n",
       "\t21 & 622714984 & 1 & 1 \\\\\n",
       "\t22 & 622689560 & 1 & 1 \\\\\n",
       "\t23 & 622708953 & 1 & 1 \\\\\n",
       "\t24 & 622714964 & 1 & 1 \\\\\n",
       "\t25 & 622696501 & 1 & 1 \\\\\n",
       "\t26 & 622673322 & 1 & 1 \\\\\n",
       "\t27 & 622691871 & 1 & 1 \\\\\n",
       "\t28 & 622711131 & 1 & 1 \\\\\n",
       "\t29 & 622673167 & 1 & 1 \\\\\n",
       "\t30 & 622698789 & 1 & 1 \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m15137×3 DataFrame\u001b[0m\n",
       "\u001b[1m   Row \u001b[0m│\u001b[1m person_id \u001b[0m\u001b[1m has_AFib \u001b[0m\u001b[1m has_stroke \u001b[0m\n",
       "       │\u001b[90m Int32     \u001b[0m\u001b[90m Int64    \u001b[0m\u001b[90m Int64      \u001b[0m\n",
       "───────┼─────────────────────────────────\n",
       "     1 │ 622707430         1           1\n",
       "     2 │ 622716907         1           1\n",
       "     3 │ 622704382         1           1\n",
       "     4 │ 622695167         1           1\n",
       "     5 │ 622679460         1           1\n",
       "     6 │ 622673865         1           1\n",
       "     7 │ 622690154         1           1\n",
       "     8 │ 622679180         1           1\n",
       "     9 │ 622678192         1           1\n",
       "    10 │ 622702721         1           1\n",
       "    11 │ 622693672         1           1\n",
       "   ⋮   │     ⋮         ⋮          ⋮\n",
       " 15128 │ 622679790         0           1\n",
       " 15129 │ 622687676         0           1\n",
       " 15130 │ 622691527         0           1\n",
       " 15131 │ 622717579         0           1\n",
       " 15132 │ 622698960         0           1\n",
       " 15133 │ 622702426         0           1\n",
       " 15134 │ 622708972         0           1\n",
       " 15135 │ 622701212         0           1\n",
       " 15136 │ 622717243         0           1\n",
       " 15137 │ 622690412         0           1\n",
       "\u001b[36m                       15116 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AFib_combined_df = DataFrame()\n",
    "stroke_combined_df = DataFrame()\n",
    "AFib_combined_df = occ.ConditionFilterPersonIDs(Afib,DBconn)\n",
    "AFib_combined_df[!, :has_AFib] .= 1\n",
    "stroke_combined_df = occ.ConditionFilterPersonIDs(stroke,DBconn)   \n",
    "stroke_combined_df[!, :has_stroke] .= 1\n",
    "df = outerjoin(AFib_combined_df, stroke_combined_df, on = [:person_id => :person_id], matchmissing = :equal)\n",
    "df = coalesce.(df, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fd9166ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>15137×5 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">15112 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">person_id</th><th style = \"text-align: left;\">race_concept_id</th><th style = \"text-align: left;\">gender_concept_id</th><th style = \"text-align: left;\">has_AFib</th><th style = \"text-align: left;\">has_stroke</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Union{Missing, Int32}\" style = \"text-align: left;\">Int32?</th><th title = \"Union{Missing, Int32}\" style = \"text-align: left;\">Int32?</th><th title = \"Union{Missing, Int32}\" style = \"text-align: left;\">Int32?</th><th title = \"Union{Missing, Int64}\" style = \"text-align: left;\">Int64?</th><th title = \"Union{Missing, Int64}\" style = \"text-align: left;\">Int64?</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">622707430</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">622716907</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">622704382</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">4</td><td style = \"text-align: right;\">622695167</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; 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text-align: right;\">13</td><td style = \"text-align: right;\">622713836</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td></tr><tr><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td><td style = \"text-align: right;\">&vellip;</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15126</td><td style = \"text-align: right;\">622707415</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15127</td><td style = \"text-align: right;\">622700696</td><td style = \"text-align: right;\">4087921</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15128</td><td style = \"text-align: right;\">622679790</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15129</td><td style = \"text-align: right;\">622687676</td><td style = \"text-align: right;\">4188159</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15130</td><td style = \"text-align: right;\">622691527</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15131</td><td style = \"text-align: right;\">622717579</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15132</td><td style = \"text-align: right;\">622698960</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15133</td><td style = \"text-align: right;\">622702426</td><td style = \"text-align: right;\">8515</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15134</td><td style = \"text-align: right;\">622708972</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15135</td><td style = \"text-align: right;\">622701212</td><td style = \"text-align: right;\">38003599</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15136</td><td style = \"text-align: right;\">622717243</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15137</td><td style = \"text-align: right;\">622690412</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccc}\n",
       "\t& person\\_id & race\\_concept\\_id & gender\\_concept\\_id & has\\_AFib & has\\_stroke\\\\\n",
       "\t\\hline\n",
       "\t& Int32? & Int32? & Int32? & Int64? & Int64?\\\\\n",
       "\t\\hline\n",
       "\t1 & 622707430 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t2 & 622716907 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t3 & 622704382 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t4 & 622695167 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t5 & 622679460 & 4087921 & 8532 & 1 & 1 \\\\\n",
       "\t6 & 622673865 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t7 & 622690154 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t8 & 622679180 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t9 & 622678192 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t10 & 622702721 & 4188159 & 8507 & 1 & 1 \\\\\n",
       "\t11 & 622693672 & 4218674 & 8532 & 1 & 1 \\\\\n",
       "\t12 & 622697655 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t13 & 622713836 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t14 & 622698895 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t15 & 622705975 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t16 & 622712282 & 4218674 & 8532 & 1 & 1 \\\\\n",
       "\t17 & 622706810 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t18 & 622698969 & 4087921 & 8532 & 1 & 1 \\\\\n",
       "\t19 & 622704074 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t20 & 622685911 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t21 & 622714984 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t22 & 622689560 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t23 & 622708953 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t24 & 622714964 & 4218674 & 8507 & 1 & 1 \\\\\n",
       "\t25 & 622696501 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t26 & 622673322 & 8527 & 8532 & 1 & 1 \\\\\n",
       "\t27 & 622691871 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t28 & 622711131 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t29 & 622673167 & 8527 & 8507 & 1 & 1 \\\\\n",
       "\t30 & 622698789 & 38003579 & 8532 & 1 & 1 \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m15137×5 DataFrame\u001b[0m\n",
       "\u001b[1m   Row \u001b[0m│\u001b[1m person_id \u001b[0m\u001b[1m race_concept_id \u001b[0m\u001b[1m gender_concept_id \u001b[0m\u001b[1m has_AFib \u001b[0m\u001b[1m has_stroke \u001b[0m\n",
       "       │\u001b[90m Int32?    \u001b[0m\u001b[90m Int32?          \u001b[0m\u001b[90m Int32?            \u001b[0m\u001b[90m Int64?   \u001b[0m\u001b[90m Int64?     \u001b[0m\n",
       "───────┼─────────────────────────────────────────────────────────────────────\n",
       "     1 │ 622707430             8527               8507         1           1\n",
       "     2 │ 622716907             8527               8507         1           1\n",
       "     3 │ 622704382             8527               8507         1           1\n",
       "     4 │ 622695167             8527               8532         1           1\n",
       "     5 │ 622679460          4087921               8532         1           1\n",
       "     6 │ 622673865             8527               8532         1           1\n",
       "     7 │ 622690154             8527               8507         1           1\n",
       "     8 │ 622679180             8527               8507         1           1\n",
       "     9 │ 622678192             8527               8507         1           1\n",
       "    10 │ 622702721          4188159               8507         1           1\n",
       "    11 │ 622693672          4218674               8532         1           1\n",
       "   ⋮   │     ⋮             ⋮                 ⋮             ⋮          ⋮\n",
       " 15128 │ 622679790             8527               8507         0           1\n",
       " 15129 │ 622687676          4188159               8532         0           1\n",
       " 15130 │ 622691527             8527               8532         0           1\n",
       " 15131 │ 622717579             8527               8532         0           1\n",
       " 15132 │ 622698960             8527               8507         0           1\n",
       " 15133 │ 622702426             8515               8507         0           1\n",
       " 15134 │ 622708972             8527               8507         0           1\n",
       " 15135 │ 622701212         38003599               8532         0           1\n",
       " 15136 │ 622717243             8527               8532         0           1\n",
       " 15137 │ 622690412             8527               8532         0           1\n",
       "\u001b[36m                                                           15116 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Getting each patiend gender and race\n",
    "df = occ.GetPatientGender(df, DBconn)\n",
    "df = occ.GetPatientRace(df, DBconn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4231b55f",
   "metadata": {},
   "outputs": [
    {
     "ename": "LoadError",
     "evalue": "ArgumentError: column :person_id not found in the left data frame",
     "output_type": "error",
     "traceback": [
      "ArgumentError: column :person_id not found in the left data frame",
      "",
      "Stacktrace:",
      " [1] DataFrames.DataFrameJoiner(dfl::DataFrame, dfr::DataFrame, on::Vector{Pair{Symbol, Symbol}}, matchmissing::Symbol, kind::Symbol)",
      "   @ DataFrames ~/.julia/packages/DataFrames/58MUJ/src/join/composer.jl:54",
      " [2] _join(df1::DataFrame, df2::DataFrame; on::Vector{Pair{Symbol, Symbol}}, kind::Symbol, makeunique::Bool, indicator::Nothing, validate::Tuple{Bool, Bool}, left_rename::typeof(identity), right_rename::typeof(identity), matchmissing::Symbol, order::Symbol)",
      "   @ DataFrames ~/.julia/packages/DataFrames/58MUJ/src/join/composer.jl:504",
      " [3] #leftjoin#673",
      "   @ ~/.julia/packages/DataFrames/58MUJ/src/join/composer.jl:940 [inlined]",
      " [4] top-level scope",
      "   @ In[9]:2"
     ]
    }
   ],
   "source": [
    "#joining the table with their ages\n",
    "df = leftjoin(df, age_mimic,  on = [:person_id => :person_id], matchmissing = :equal, makeunique=true)\n",
    "sort(df, :person_id)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "bf75dc4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>15127×7 DataFrame</span></div><div style = \"float: right;\"><span style = \"font-style: italic;\">15102 rows omitted</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">person_id</th><th style = \"text-align: left;\">race_concept_id</th><th style = \"text-align: left;\">gender_concept_id</th><th style = \"text-align: left;\">has_AFib</th><th style = \"text-align: left;\">has_stroke</th><th style = \"text-align: left;\">subject_id</th><th style = \"text-align: left;\">age</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Int32\" style = \"text-align: left;\">Int32</th><th title = \"Int32\" style = \"text-align: left;\">Int32</th><th title = \"Int32\" style = \"text-align: left;\">Int32</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int32\" style = \"text-align: left;\">Int32</th><th title = \"Int32\" style = \"text-align: left;\">Int32</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: right;\">622672122</td><td style = \"text-align: right;\">4218674</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">270</td><td style = \"text-align: right;\">80</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: right;\">622672559</td><td style = \"text-align: right;\">38003599</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">274</td><td style = \"text-align: right;\">66</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: right;\">622672560</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">275</td><td style = \"text-align: right;\">82</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; 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text-align: right;\">15120</td><td style = \"text-align: right;\">622713254</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">94916</td><td style = \"text-align: right;\">300</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15121</td><td style = \"text-align: right;\">622713255</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">94921</td><td style = \"text-align: right;\">69</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15122</td><td style = \"text-align: right;\">622713256</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">94924</td><td style = \"text-align: right;\">75</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15123</td><td style = \"text-align: right;\">622713257</td><td style = \"text-align: right;\">38003599</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">94926</td><td style = \"text-align: right;\">87</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15124</td><td style = \"text-align: right;\">622713258</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">94932</td><td style = \"text-align: right;\">47</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15125</td><td style = \"text-align: right;\">622713261</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8507</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">94942</td><td style = \"text-align: right;\">80</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15126</td><td style = \"text-align: right;\">622713264</td><td style = \"text-align: right;\">8527</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">94953</td><td style = \"text-align: right;\">53</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">15127</td><td style = \"text-align: right;\">622713265</td><td style = \"text-align: right;\">4218674</td><td style = \"text-align: right;\">8532</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">94954</td><td style = \"text-align: right;\">68</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccc}\n",
       "\t& person\\_id & race\\_concept\\_id & gender\\_concept\\_id & has\\_AFib & has\\_stroke & subject\\_id & \\\\\n",
       "\t\\hline\n",
       "\t& Int32 & Int32 & Int32 & Int64 & Int64 & Int32 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 622672122 & 4218674 & 8507 & 0 & 1 & 270 & $\\dots$ \\\\\n",
       "\t2 & 622672559 & 38003599 & 8507 & 0 & 1 & 274 & $\\dots$ \\\\\n",
       "\t3 & 622672560 & 8527 & 8507 & 0 & 1 & 275 & $\\dots$ \\\\\n",
       "\t4 & 622672566 & 8527 & 8532 & 0 & 1 & 282 & $\\dots$ \\\\\n",
       "\t5 & 622672568 & 8527 & 8532 & 1 & 0 & 284 & $\\dots$ \\\\\n",
       "\t6 & 622672570 & 8527 & 8532 & 1 & 0 & 286 & $\\dots$ \\\\\n",
       "\t7 & 622672573 & 4218674 & 8507 & 1 & 0 & 290 & $\\dots$ \\\\\n",
       "\t8 & 622672587 & 38003599 & 8532 & 1 & 1 & 304 & $\\dots$ \\\\\n",
       "\t9 & 622672588 & 8527 & 8532 & 1 & 1 & 305 & $\\dots$ \\\\\n",
       "\t10 & 622672589 & 8527 & 8532 & 0 & 1 & 306 & $\\dots$ \\\\\n",
       "\t11 & 622672590 & 8527 & 8532 & 0 & 1 & 307 & $\\dots$ \\\\\n",
       "\t12 & 622672595 & 4218674 & 8532 & 0 & 1 & 313 & $\\dots$ \\\\\n",
       "\t13 & 622672603 & 4218674 & 8532 & 1 & 0 & 321 & $\\dots$ \\\\\n",
       "\t14 & 622672606 & 8527 & 8507 & 0 & 1 & 324 & $\\dots$ \\\\\n",
       "\t15 & 622672612 & 8527 & 8507 & 0 & 1 & 330 & $\\dots$ \\\\\n",
       "\t16 & 622672620 & 8527 & 8507 & 1 & 0 & 338 & $\\dots$ \\\\\n",
       "\t17 & 622672621 & 38003599 & 8532 & 1 & 0 & 339 & $\\dots$ \\\\\n",
       "\t18 & 622672622 & 8527 & 8532 & 0 & 1 & 340 & $\\dots$ \\\\\n",
       "\t19 & 622672624 & 38003599 & 8532 & 0 & 1 & 342 & $\\dots$ \\\\\n",
       "\t20 & 622672626 & 4188159 & 8532 & 1 & 0 & 345 & $\\dots$ \\\\\n",
       "\t21 & 622672627 & 38003599 & 8532 & 1 & 0 & 346 & $\\dots$ \\\\\n",
       "\t22 & 622672633 & 8527 & 8507 & 0 & 1 & 352 & $\\dots$ \\\\\n",
       "\t23 & 622672634 & 8527 & 8507 & 1 & 0 & 353 & $\\dots$ \\\\\n",
       "\t24 & 622672384 & 8527 & 8507 & 0 & 1 & 67 & $\\dots$ \\\\\n",
       "\t25 & 622672397 & 8527 & 8507 & 0 & 1 & 81 & $\\dots$ \\\\\n",
       "\t26 & 622672399 & 4218674 & 8532 & 0 & 1 & 83 & $\\dots$ \\\\\n",
       "\t27 & 622672401 & 8527 & 8507 & 1 & 0 & 85 & $\\dots$ \\\\\n",
       "\t28 & 622672409 & 8515 & 8507 & 1 & 0 & 94 & $\\dots$ \\\\\n",
       "\t29 & 622672412 & 4218674 & 8507 & 1 & 0 & 97 & $\\dots$ \\\\\n",
       "\t30 & 622672415 & 4218674 & 8532 & 1 & 0 & 100 & $\\dots$ \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ &  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m15127×7 DataFrame\u001b[0m\n",
       "\u001b[1m   Row \u001b[0m│\u001b[1m person_id \u001b[0m\u001b[1m race_concept_id \u001b[0m\u001b[1m gender_concept_id \u001b[0m\u001b[1m has_AFib \u001b[0m\u001b[1m has_stroke \u001b[0m\u001b[1m \u001b[0m ⋯\n",
       "       │\u001b[90m Int32     \u001b[0m\u001b[90m Int32           \u001b[0m\u001b[90m Int32             \u001b[0m\u001b[90m Int64    \u001b[0m\u001b[90m Int64      \u001b[0m\u001b[90m \u001b[0m ⋯\n",
       "───────┼────────────────────────────────────────────────────────────────────────\n",
       "     1 │ 622672122          4218674               8507         0           1   ⋯\n",
       "     2 │ 622672559         38003599               8507         0           1\n",
       "     3 │ 622672560             8527               8507         0           1\n",
       "     4 │ 622672566             8527               8532         0           1\n",
       "     5 │ 622672568             8527               8532         1           0   ⋯\n",
       "     6 │ 622672570             8527               8532         1           0\n",
       "     7 │ 622672573          4218674               8507         1           0\n",
       "     8 │ 622672587         38003599               8532         1           1\n",
       "     9 │ 622672588             8527               8532         1           1   ⋯\n",
       "    10 │ 622672589             8527               8532         0           1\n",
       "    11 │ 622672590             8527               8532         0           1\n",
       "   ⋮   │     ⋮             ⋮                 ⋮             ⋮          ⋮        ⋱\n",
       " 15118 │ 622713246             8527               8507         1           1\n",
       " 15119 │ 622713249             8527               8507         1           0   ⋯\n",
       " 15120 │ 622713254             8527               8507         1           0\n",
       " 15121 │ 622713255             8527               8507         1           0\n",
       " 15122 │ 622713256             8527               8532         0           1\n",
       " 15123 │ 622713257         38003599               8532         1           1   ⋯\n",
       " 15124 │ 622713258             8527               8532         0           1\n",
       " 15125 │ 622713261             8527               8507         1           1\n",
       " 15126 │ 622713264             8527               8532         0           1\n",
       " 15127 │ 622713265          4218674               8532         1           0   ⋯\n",
       "\u001b[36m                                                2 columns and 15106 rows omitted\u001b[0m"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df.age .= ifelse.(df.age .> 89, 90, df.age)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5ed81244",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5-element Vector{Int64}:\n",
       " 0\n",
       " 0\n",
       " 0\n",
       " 0\n",
       " 0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "[count(ismissing,col) for col in eachcol(df)]\n",
    "dropmissing!(df)\n",
    "[count(ismissing,col) for col in eachcol(df)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "52c7f5e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7-element Vector{DataType}:\n",
       " Int32\n",
       " Int32\n",
       " Int32\n",
       " Int64\n",
       " Int64\n",
       " Int32\n",
       " Int32"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eltype.(eachcol(df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4f97e0cc",
   "metadata": {},
   "outputs": [
    {
     "ename": "LoadError",
     "evalue": "ArgumentError: column name :subject_id not found in the data frame",
     "output_type": "error",
     "traceback": [
      "ArgumentError: column name :subject_id not found in the data frame",
      "",
      "Stacktrace:",
      " [1] lookupname",
      "   @ ~/.julia/packages/DataFrames/58MUJ/src/other/index.jl:413 [inlined]",
      " [2] getindex",
      "   @ ~/.julia/packages/DataFrames/58MUJ/src/other/index.jl:422 [inlined]",
      " [3] getindex",
      "   @ ~/.julia/packages/DataFrames/58MUJ/src/other/index.jl:227 [inlined]",
      " [4] manipulate(df::DataFrame, c::InvertedIndex{Symbol}; copycols::Bool, keeprows::Bool, renamecols::Bool)",
      "   @ DataFrames ~/.julia/packages/DataFrames/58MUJ/src/abstractdataframe/selection.jl:1836",
      " [5] select(df::DataFrame, args::Any; copycols::Bool, renamecols::Bool, threads::Bool)",
      "   @ DataFrames ~/.julia/packages/DataFrames/58MUJ/src/abstractdataframe/selection.jl:1299",
      " [6] select(df::DataFrame, args::Any)",
      "   @ DataFrames ~/.julia/packages/DataFrames/58MUJ/src/abstractdataframe/selection.jl:1299",
      " [7] top-level scope",
      "   @ In[8]:3"
     ]
    }
   ],
   "source": [
    "# dropping person_id and subject_id columns because they won't be needed\n",
    "df = select(df, Not(:person_id))\n",
    "df = select(df, Not(:subject_id))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6d69b6cb",
   "metadata": {},
   "outputs": [
    {
     "ename": "LoadError",
     "evalue": "ArgumentError: column name :age not found in the data frame",
     "output_type": "error",
     "traceback": [
      "ArgumentError: column name :age not found in the data frame",
      "",
      "Stacktrace:",
      " [1] lookupname",
      "   @ ~/.julia/packages/DataFrames/58MUJ/src/other/index.jl:413 [inlined]",
      " [2] getindex",
      "   @ ~/.julia/packages/DataFrames/58MUJ/src/other/index.jl:422 [inlined]",
      " [3] getindex(df::DataFrame, #unused#::typeof(!), col_ind::Symbol)",
      "   @ DataFrames ~/.julia/packages/DataFrames/58MUJ/src/dataframe/dataframe.jl:557",
      " [4] getproperty(df::DataFrame, col_ind::Symbol)",
      "   @ DataFrames ~/.julia/packages/DataFrames/58MUJ/src/abstractdataframe/abstractdataframe.jl:431",
      " [5] top-level scope",
      "   @ In[10]:2"
     ]
    }
   ],
   "source": [
    "eltype.(eachcol(df))\n",
    "df.age = convert.(Int64, df.age)\n",
    "df.race_concept_id = convert.(Int64, df.race_concept_id)\n",
    "df.gender_concept_id = convert.(Int64, df.gender_concept_id)\n",
    "df.has_AFib = convert.(Int64, df.has_AFib)\n",
    "df.has_stroke = convert.(Int64, df.has_stroke)\n",
    "df = select(df, Not(:gender_concept_id))\n",
    "df = select(df, Not(:race_concept_id))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "c928bd2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div style = \"float: left;\"><span>3×7 DataFrame</span></div><div style = \"clear: both;\"></div></div><div class = \"data-frame\" style = \"overflow-x: scroll;\"><table class = \"data-frame\" style = \"margin-bottom: 6px;\"><thead><tr class = \"header\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">Row</th><th style = \"text-align: left;\">variable</th><th style = \"text-align: left;\">mean</th><th style = \"text-align: left;\">min</th><th style = \"text-align: left;\">median</th><th style = \"text-align: left;\">max</th><th style = \"text-align: left;\">nmissing</th><th style = \"text-align: left;\">eltype</th></tr><tr class = \"subheader headerLastRow\"><th class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\"></th><th title = \"Symbol\" style = \"text-align: left;\">Symbol</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Float64\" style = \"text-align: left;\">Float64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"Int64\" style = \"text-align: left;\">Int64</th><th title = \"DataType\" style = \"text-align: left;\">DataType</th></tr></thead><tbody><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">1</td><td style = \"text-align: left;\">has_AFib</td><td style = \"text-align: right;\">0.681766</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">1.0</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0</td><td style = \"text-align: left;\">Int64</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">2</td><td style = \"text-align: left;\">has_stroke</td><td style = \"text-align: right;\">0.44256</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">0.0</td><td style = \"text-align: right;\">1</td><td style = \"text-align: right;\">0</td><td style = \"text-align: left;\">Int64</td></tr><tr><td class = \"rowNumber\" style = \"font-weight: bold; text-align: right;\">3</td><td style = \"text-align: left;\">age</td><td style = \"text-align: right;\">87.8847</td><td style = \"text-align: right;\">0</td><td style = \"text-align: right;\">74.0</td><td style = \"text-align: right;\">307</td><td style = \"text-align: right;\">0</td><td style = \"text-align: left;\">Int64</td></tr></tbody></table></div>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccccccc}\n",
       "\t& variable & mean & min & median & max & nmissing & eltype\\\\\n",
       "\t\\hline\n",
       "\t& Symbol & Float64 & Int64 & Float64 & Int64 & Int64 & DataType\\\\\n",
       "\t\\hline\n",
       "\t1 & has\\_AFib & 0.681766 & 0 & 1.0 & 1 & 0 & Int64 \\\\\n",
       "\t2 & has\\_stroke & 0.44256 & 0 & 0.0 & 1 & 0 & Int64 \\\\\n",
       "\t3 & age & 87.8847 & 0 & 74.0 & 307 & 0 & Int64 \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m3×7 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m variable   \u001b[0m\u001b[1m mean      \u001b[0m\u001b[1m min   \u001b[0m\u001b[1m median  \u001b[0m\u001b[1m max   \u001b[0m\u001b[1m nmissing \u001b[0m\u001b[1m eltype   \u001b[0m\n",
       "     │\u001b[90m Symbol     \u001b[0m\u001b[90m Float64   \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Int64 \u001b[0m\u001b[90m Int64    \u001b[0m\u001b[90m DataType \u001b[0m\n",
       "─────┼──────────────────────────────────────────────────────────────────\n",
       "   1 │ has_AFib     0.681766      0      1.0      1         0  Int64\n",
       "   2 │ has_stroke   0.44256       0      0.0      1         0  Int64\n",
       "   3 │ age         87.8847        0     74.0    307         0  Int64"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "describe(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "d831184f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dict{Int64, Int64} with 2 entries:\n",
       "  0 => 2892\n",
       "  1 => 2296"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using Pkg\n",
    "using StatsBase\n",
    "countmap(df.has_stroke)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "d098630c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(\u001b[1m3632×3 DataFrame\u001b[0m\n",
       "\u001b[1m  Row \u001b[0m│\u001b[1m has_AFib \u001b[0m\u001b[1m has_stroke \u001b[0m\u001b[1m age   \u001b[0m\n",
       "      │\u001b[90m Int64    \u001b[0m\u001b[90m Int64      \u001b[0m\u001b[90m Int64 \u001b[0m\n",
       "──────┼─────────────────────────────\n",
       "    1 │        1           0     69\n",
       "    2 │        1           0     67\n",
       "    3 │        1           0     62\n",
       "    4 │        0           1     49\n",
       "    5 │        0           1     63\n",
       "    6 │        1           0     44\n",
       "    7 │        1           0     88\n",
       "    8 │        1           0     83\n",
       "    9 │        1           0     85\n",
       "   10 │        1           0     79\n",
       "   11 │        1           0     67\n",
       "  ⋮   │    ⋮          ⋮         ⋮\n",
       " 3623 │        1           0     80\n",
       " 3624 │        0           1     81\n",
       " 3625 │        1           1     77\n",
       " 3626 │        0           1     79\n",
       " 3627 │        1           0     73\n",
       " 3628 │        1           0     76\n",
       " 3629 │        1           0     71\n",
       " 3630 │        1           0     88\n",
       " 3631 │        1           0     80\n",
       " 3632 │        1           0     84\n",
       "\u001b[36m                   3611 rows omitted\u001b[0m, \u001b[1m1556×3 DataFrame\u001b[0m\n",
       "\u001b[1m  Row \u001b[0m│\u001b[1m has_AFib \u001b[0m\u001b[1m has_stroke \u001b[0m\u001b[1m age   \u001b[0m\n",
       "      │\u001b[90m Int64    \u001b[0m\u001b[90m Int64      \u001b[0m\u001b[90m Int64 \u001b[0m\n",
       "──────┼─────────────────────────────\n",
       "    1 │        1           0     77\n",
       "    2 │        1           1    300\n",
       "    3 │        1           0     80\n",
       "    4 │        1           0     84\n",
       "    5 │        1           0     84\n",
       "    6 │        1           0     89\n",
       "    7 │        1           0     86\n",
       "    8 │        0           1     60\n",
       "    9 │        1           1     67\n",
       "   10 │        1           0     83\n",
       "   11 │        1           0     85\n",
       "  ⋮   │    ⋮          ⋮         ⋮\n",
       " 1547 │        1           0     59\n",
       " 1548 │        1           1     71\n",
       " 1549 │        1           0     73\n",
       " 1550 │        1           0     59\n",
       " 1551 │        1           0    300\n",
       " 1552 │        1           1     53\n",
       " 1553 │        1           1     58\n",
       " 1554 │        0           1     74\n",
       " 1555 │        1           0     59\n",
       " 1556 │        1           0     85\n",
       "\u001b[36m                   1535 rows omitted\u001b[0m)"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#using MLJ\n",
    "#df, df_test = partition(df, 0.7, rng=123, shuffle= true)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "bf8fbebe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3-element Vector{NamedTuple{(:name, :package_name, :is_supervised, :abstract_type, :deep_properties, :docstring, :fit_data_scitype, :human_name, :hyperparameter_ranges, :hyperparameter_types, :hyperparameters, :implemented_methods, :inverse_transform_scitype, :is_pure_julia, :is_wrapper, :iteration_parameter, :load_path, :package_license, :package_url, :package_uuid, :predict_scitype, :prediction_type, :reporting_operations, :reports_feature_importances, :supports_class_weights, :supports_online, :supports_training_losses, :supports_weights, :transform_scitype, :input_scitype, :target_scitype, :output_scitype)}}:\n",
       " (name = EvoTreeCount, package_name = EvoTrees, ... )\n",
       " (name = NeuralNetworkClassifier, package_name = BetaML, ... )\n",
       " (name = NeuralNetworkRegressor, package_name = BetaML, ... )"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using MLJ\n",
    "using BetaML\n",
    "\n",
    "# Split the data into training and test sets\n",
    "#selected_features = [:gender_concept_id, :age, :race_concept_id, :has_AFib]\n",
    "selected_features = [ :age, :has_AFib]\n",
    "\n",
    "X = select(df, selected_features)\n",
    "y = df.has_stroke\n",
    "train, test = partition(df, 0.7, rng=123, shuffle=true)\n",
    "train_X = select(train, selected_features)\n",
    "train_y = train.has_stroke\n",
    "test_X = select(test, selected_features)\n",
    "test_y = test.has_stroke\n",
    "\n",
    "models(matching(X, y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "1b908b51",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "import EvoTrees ✔\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mFor silent loading, specify `verbosity=0`. \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "EvoTreeClassifier(\n",
       "  nrounds = 100, \n",
       "  lambda = 0.0, \n",
       "  gamma = 0.0, \n",
       "  eta = 0.1, \n",
       "  max_depth = 6, \n",
       "  min_weight = 1.0, \n",
       "  rowsample = 1.0, \n",
       "  colsample = 1.0, \n",
       "  nbins = 32, \n",
       "  alpha = 0.5, \n",
       "  tree_type = \"binary\", \n",
       "  rng = Random.MersenneTwister(123))"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tree = @load EvoTreeClassifier pkg = EvoTrees\n",
    "using EvoTrees\n",
    "config = EvoTreeClassifier(\n",
    "    loss=:mse, \n",
    "    nrounds=100, \n",
    "    max_depth=6,\n",
    "    nbins=32,\n",
    "    eta=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "f95136b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[36m\u001b[1m┌ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mEvoTreeClassifier{EvoTrees.MLogLoss}\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - nrounds: 100\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - lambda: 0.0\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - gamma: 0.0\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - eta: 0.1\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - max_depth: 6\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - min_weight: 1.0\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - rowsample: 1.0\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - colsample: 1.0\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - nbins: 32\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - alpha: 0.5\n",
      "\u001b[36m\u001b[1m│ \u001b[22m\u001b[39m - tree_type: binary\n",
      "\u001b[36m\u001b[1m└ \u001b[22m\u001b[39m - rng: Random.MersenneTwister(123, (0, 4008, 3006, 626))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "EvoTree{EvoTrees.MLogLoss, 2}\n",
       " - Contains 101 trees in field `trees` (incl. 1 bias tree).\n",
       " - Data input has 2 features.\n",
       " - [:target_levels, :fnames, :feattypes, :edges, :featbins] info accessible in field `info`\n"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_X =Matrix(train_X)\n",
    "m = fit_evotree(config; x_train  = train_X, y_train=train_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "471eefcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1090×2 Matrix{Float32}:\n",
       " 0.800264    0.199736\n",
       " 0.814238    0.185762\n",
       " 1.36711f-5  0.999986\n",
       " 0.847743    0.152257\n",
       " 0.827981    0.172019\n",
       " 1.36711f-5  0.999986\n",
       " 0.741776    0.258224\n",
       " 0.822133    0.177867\n",
       " 1.36711f-5  0.999986\n",
       " 0.847743    0.152257\n",
       " 1.36711f-5  0.999986\n",
       " 0.800264    0.199736\n",
       " 1.36711f-5  0.999986\n",
       " ⋮           \n",
       " 1.36711f-5  0.999986\n",
       " 0.797935    0.202065\n",
       " 0.735359    0.264641\n",
       " 0.735655    0.264345\n",
       " 0.741776    0.258224\n",
       " 0.860911    0.139089\n",
       " 0.908374    0.0916265\n",
       " 1.36711f-5  0.999986\n",
       " 0.908374    0.0916265\n",
       " 0.826605    0.173395\n",
       " 1.36711f-5  0.999986\n",
       " 1.36711f-5  0.999986"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_X = Matrix(test_X)\n",
    "preds = MLJ.predict( m,test_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "a7e25da6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2-element Vector{Pair{String, Float64}}:\n",
       " \"feat_2\" => 0.9758581174651332\n",
       " \"feat_1\" => 0.024141882534866845"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_gain = EvoTrees.importance(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "ba6a8406",
   "metadata": {},
   "outputs": [
    {
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       "  341.43,415.368 343.307,338.288 345.184,340.182 347.061,225.604 348.938,362.317 350.814,321.521 352.691,1445.72 354.568,447.28 356.445,438.569 358.322,1445.72 \n",
       "  360.198,321.521 362.075,329.461 363.952,1445.72 365.829,1445.72 367.706,340.182 369.582,236.83 371.459,384.924 373.336,338.288 375.213,225.604 377.09,362.317 \n",
       "  378.967,362.317 380.843,225.604 382.72,1445.72 384.597,1445.72 386.474,1445.72 388.351,1445.72 390.227,201.67 392.104,362.317 393.981,1445.72 395.858,277.024 \n",
       "  397.735,308.8 399.611,1445.72 401.488,201.67 403.365,338.288 405.242,1445.72 407.119,340.182 408.996,218.486 410.872,1445.72 412.749,225.604 414.626,362.317 \n",
       "  416.503,212.366 418.38,218.486 420.256,325.516 422.133,294.689 424.01,378.48 425.887,294.689 427.764,447.28 429.641,1445.72 431.517,1445.72 433.394,310.962 \n",
       "  435.271,447.28 437.148,363.074 439.025,325.516 440.901,362.317 442.778,1445.72 444.655,198.096 446.532,1445.72 448.409,362.317 450.285,1445.72 452.162,325.516 \n",
       "  454.039,378.48 455.916,87.9941 457.793,1445.72 459.67,1445.72 461.546,415.368 463.423,1445.72 465.3,362.317 467.177,359.154 469.054,1445.72 470.93,277.024 \n",
       "  472.807,201.67 474.684,1445.72 476.561,308.8 478.438,325.516 480.315,362.317 482.191,362.317 484.068,415.368 485.945,225.604 487.822,1445.72 489.699,340.182 \n",
       "  491.575,359.154 493.452,212.366 495.329,378.48 497.206,323.389 499.083,1445.72 500.959,294.689 502.836,362.317 504.713,362.317 506.59,202.112 508.467,325.516 \n",
       "  510.344,362.317 512.22,310.962 514.097,236.83 515.974,1445.72 517.851,225.604 519.728,212.366 521.604,1445.72 523.481,225.604 525.358,1445.72 527.235,294.689 \n",
       "  529.112,329.461 530.988,1445.72 532.865,340.182 534.742,378.48 536.619,1445.72 538.496,447.28 540.373,1445.72 542.249,438.569 544.126,1445.72 546.003,438.569 \n",
       "  547.88,1445.72 549.757,277.024 551.633,1445.72 553.51,308.8 555.387,415.368 557.264,236.83 559.141,1445.72 561.018,308.8 562.894,1445.72 564.771,362.317 \n",
       "  566.648,1445.72 568.525,1445.72 570.402,378.48 572.278,1445.72 574.155,325.516 576.032,202.112 577.909,277.024 579.786,362.317 581.662,1445.72 583.539,378.48 \n",
       "  585.416,202.112 587.293,212.366 589.17,378.48 591.047,325.516 592.923,338.288 594.8,338.288 596.677,329.461 598.554,338.288 600.431,225.604 602.307,438.569 \n",
       "  604.184,225.604 606.061,1445.72 607.938,1445.72 609.815,447.28 611.692,1445.72 613.568,236.83 615.445,321.521 617.322,446.879 619.199,1445.72 621.076,362.317 \n",
       "  622.952,446.879 624.829,1445.72 626.706,276.81 628.583,338.288 630.46,415.368 632.336,359.154 634.213,201.67 636.09,212.366 637.967,1445.72 639.844,218.486 \n",
       "  641.721,384.924 643.597,276.81 645.474,362.317 647.351,329.461 649.228,212.366 651.105,438.569 652.981,359.154 654.858,415.368 656.735,1445.72 658.612,225.604 \n",
       "  660.489,415.368 662.366,325.516 664.242,1445.72 666.119,1445.72 667.996,323.389 669.873,1445.72 671.75,277.024 673.626,362.317 675.503,1445.72 677.38,362.317 \n",
       "  679.257,276.81 681.134,87.9941 683.01,276.81 684.887,294.689 686.764,1445.72 688.641,340.182 690.518,1445.72 692.395,1445.72 694.271,277.024 696.148,1445.72 \n",
       "  698.025,362.317 699.902,1445.72 701.779,359.154 703.655,1445.72 705.532,276.81 707.409,363.074 709.286,1445.72 711.163,1445.72 713.039,362.317 714.916,1445.72 \n",
       "  716.793,87.9941 718.67,212.366 720.547,1445.72 722.424,236.83 724.3,225.604 726.177,294.689 728.054,1445.72 729.931,1445.72 731.808,1445.72 733.684,1445.72 \n",
       "  735.561,1445.72 737.438,359.154 739.315,201.67 741.192,446.879 743.069,1445.72 744.945,1445.72 746.822,310.962 748.699,415.368 750.576,1445.72 752.453,329.461 \n",
       "  754.329,438.569 756.206,446.879 758.083,323.389 759.96,1445.72 761.837,362.317 763.713,88.5629 765.59,378.48 767.467,308.8 769.344,363.074 771.221,438.569 \n",
       "  773.098,201.67 774.974,325.516 776.851,1445.72 778.728,310.962 780.605,1445.72 782.482,276.81 784.358,378.48 786.235,212.366 788.112,338.288 789.989,225.604 \n",
       "  791.866,1445.72 793.743,338.288 795.619,294.689 797.496,236.83 799.373,202.112 801.25,1445.72 803.127,201.67 805.003,362.317 806.88,323.389 808.757,359.154 \n",
       "  810.634,362.317 812.511,1445.72 814.387,1445.72 816.264,363.074 818.141,294.689 820.018,379.274 821.895,1445.72 823.772,323.389 825.648,323.389 827.525,1445.72 \n",
       "  829.402,329.461 831.279,201.67 833.156,1445.72 835.032,1445.72 836.909,310.962 838.786,338.288 840.663,212.366 842.54,1445.72 844.416,276.81 846.293,340.182 \n",
       "  848.17,447.28 850.047,1445.72 851.924,277.024 853.801,1445.72 855.677,1445.72 857.554,362.317 859.431,378.48 861.308,329.461 863.185,359.154 865.061,362.317 \n",
       "  866.938,294.689 868.815,338.288 870.692,87.9941 872.569,1445.72 874.446,1445.72 876.322,201.67 878.199,1445.72 880.076,1445.72 881.953,1445.72 883.83,379.274 \n",
       "  885.706,1445.72 887.583,201.67 889.46,276.81 891.337,1445.72 893.214,202.112 895.09,1445.72 896.967,1445.72 898.844,1445.72 900.721,1445.72 902.598,1445.72 \n",
       "  904.475,236.83 906.351,362.317 908.228,1445.72 910.105,1445.72 911.982,384.924 913.859,447.28 915.735,225.604 917.612,308.8 919.489,338.288 921.366,359.154 \n",
       "  923.243,277.024 925.12,1445.72 926.996,276.81 928.873,294.689 930.75,236.83 932.627,1445.72 934.504,212.366 936.38,201.67 938.257,1445.72 940.134,359.154 \n",
       "  942.011,1445.72 943.888,1445.72 945.764,87.9941 947.641,340.182 949.518,308.8 951.395,236.83 953.272,363.074 955.149,1445.72 957.025,225.604 958.902,1445.72 \n",
       "  960.779,1445.72 962.656,1445.72 964.533,236.83 966.409,379.274 968.286,201.67 970.163,362.317 972.04,338.288 973.917,362.317 975.794,1445.72 977.67,1445.72 \n",
       "  979.547,201.67 981.424,1445.72 983.301,277.024 985.178,384.924 987.054,378.48 988.931,1445.72 990.808,1445.72 992.685,359.154 994.562,338.288 996.438,359.154 \n",
       "  998.315,438.569 1000.19,294.689 1002.07,236.83 1003.95,362.317 1005.82,1445.72 1007.7,1445.72 1009.58,225.604 1011.45,438.569 1013.33,277.024 1015.21,379.274 \n",
       "  1017.08,1445.72 1018.96,1445.72 1020.84,378.48 1022.71,384.924 1024.59,1445.72 1026.47,1445.72 1028.34,379.274 1030.22,212.366 1032.1,1445.72 1033.97,384.924 \n",
       "  1035.85,1445.72 1037.73,1445.72 1039.61,225.604 1041.48,276.81 1043.36,321.521 1045.24,1445.72 1047.11,1445.72 1048.99,415.368 1050.87,1445.72 1052.74,321.521 \n",
       "  1054.62,1445.72 1056.5,359.154 1058.37,379.274 1060.25,1445.72 1062.13,1445.72 1064,415.368 1065.88,1445.72 1067.76,363.074 1069.63,1445.72 1071.51,1445.72 \n",
       "  1073.39,201.67 1075.26,447.28 1077.14,363.074 1079.02,1445.72 1080.9,321.521 1082.77,276.81 1084.65,379.274 1086.53,236.83 1088.4,1445.72 1090.28,236.83 \n",
       "  1092.16,212.366 1094.03,362.317 1095.91,310.962 1097.79,1445.72 1099.66,379.274 1101.54,1445.72 1103.42,438.569 1105.29,447.28 1107.17,1445.72 1109.05,202.112 \n",
       "  1110.92,276.81 1112.8,308.8 1114.68,446.879 1116.55,323.389 1118.43,201.67 1120.31,1445.72 1122.19,1445.72 1124.06,329.461 1125.94,1445.72 1127.82,1445.72 \n",
       "  1129.69,415.368 1131.57,1445.72 1133.45,415.368 1135.32,379.274 1137.2,212.366 1139.08,1445.72 1140.95,362.317 1142.83,1445.72 1144.71,379.274 1146.58,1445.72 \n",
       "  1148.46,338.288 1150.34,321.521 1152.21,225.604 1154.09,363.074 1155.97,415.368 1157.84,415.368 1159.72,1445.72 1161.6,329.461 1163.47,325.516 1165.35,1445.72 \n",
       "  1167.23,1445.72 1169.11,446.879 1170.98,1445.72 1172.86,447.28 1174.74,1445.72 1176.61,359.154 1178.49,1445.72 1180.37,310.962 1182.24,1445.72 1184.12,308.8 \n",
       "  1186,384.924 1187.87,236.83 1189.75,1445.72 1191.63,1445.72 1193.5,201.67 1195.38,1445.72 1197.26,1445.72 1199.13,277.024 1201.01,1445.72 1202.89,384.924 \n",
       "  1204.76,277.024 1206.64,1445.72 1208.52,225.604 1210.4,1445.72 1212.27,308.8 1214.15,1445.72 1216.03,325.516 1217.9,276.81 1219.78,1445.72 1221.66,1445.72 \n",
       "  1223.53,201.67 1225.41,276.81 1227.29,323.389 1229.16,362.317 1231.04,340.182 1232.92,447.28 1234.79,1445.72 1236.67,325.516 1238.55,363.074 1240.42,1445.72 \n",
       "  1242.3,1445.72 1244.18,218.486 1246.05,379.274 1247.93,363.074 1249.81,362.317 1251.69,1445.72 1253.56,415.368 1255.44,212.366 1257.32,202.112 1259.19,415.368 \n",
       "  1261.07,1445.72 1262.95,379.274 1264.82,198.096 1266.7,308.8 1268.58,212.366 1270.45,294.689 1272.33,438.569 1274.21,225.604 1276.08,1445.72 1277.96,1445.72 \n",
       "  1279.84,329.461 1281.71,1445.72 1283.59,1445.72 1285.47,276.81 1287.34,363.074 1289.22,325.516 1291.1,325.516 1292.98,378.48 1294.85,1445.72 1296.73,1445.72 \n",
       "  1298.61,321.521 1300.48,225.604 1302.36,359.154 1304.24,359.154 1306.11,446.879 1307.99,325.516 1309.87,338.288 1311.74,212.366 1313.62,1445.72 1315.5,1445.72 \n",
       "  1317.37,1445.72 1319.25,362.317 1321.13,1445.72 1323,1445.72 1324.88,202.112 1326.76,225.604 1328.63,338.288 1330.51,378.48 1332.39,379.274 1334.27,363.074 \n",
       "  1336.14,212.366 1338.02,340.182 1339.9,340.182 1341.77,446.879 1343.65,359.154 1345.53,1445.72 1347.4,1445.72 1349.28,362.317 1351.16,236.83 1353.03,1445.72 \n",
       "  1354.91,321.521 1356.79,363.074 1358.66,236.83 1360.54,1445.72 1362.42,384.924 1364.29,447.28 1366.17,1445.72 1368.05,225.604 1369.92,1445.72 1371.8,1445.72 \n",
       "  1373.68,1445.72 1375.55,321.521 1377.43,438.569 1379.31,329.461 1381.19,1445.72 1383.06,323.389 1384.94,1445.72 1386.82,1445.72 1388.69,1445.72 1390.57,277.024 \n",
       "  1392.45,340.182 1394.32,1445.72 1396.2,359.154 1398.08,362.317 1399.95,1445.72 1401.83,362.317 1403.71,1445.72 1405.58,446.879 1407.46,340.182 1409.34,446.879 \n",
       "  1411.21,1445.72 1413.09,438.569 1414.97,415.368 1416.84,1445.72 1418.72,1445.72 1420.6,359.154 1422.48,88.5629 1424.35,1445.72 1426.23,277.024 1428.11,1445.72 \n",
       "  1429.98,308.8 1431.86,325.516 1433.74,218.486 1435.61,310.962 1437.49,277.024 1439.37,276.81 1441.24,415.368 1443.12,201.67 1445,225.604 1446.87,1445.72 \n",
       "  1448.75,310.962 1450.63,1445.72 1452.5,446.879 1454.38,447.28 1456.26,310.962 1458.13,379.274 1460.01,446.879 1461.89,325.516 1463.77,218.486 1465.64,198.096 \n",
       "  1467.52,225.604 1469.4,323.389 1471.27,1445.72 1473.15,310.962 1475.03,338.288 1476.9,202.112 1478.78,1445.72 1480.66,1445.72 1482.53,1445.72 1484.41,359.154 \n",
       "  1486.29,362.317 1488.16,277.024 1490.04,88.5629 1491.92,362.317 1493.79,212.366 1495.67,1445.72 1497.55,212.366 1499.42,1445.72 1501.3,359.154 1503.18,201.67 \n",
       "  1505.06,1445.72 1506.93,329.461 1508.81,1445.72 1510.69,212.366 1512.56,362.317 1514.44,438.569 1516.32,1445.72 1518.19,1445.72 1520.07,379.274 1521.95,446.879 \n",
       "  1523.82,1445.72 1525.7,201.67 1527.58,379.274 1529.45,378.48 1531.33,225.604 1533.21,198.096 1535.08,1445.72 1536.96,321.521 1538.84,1445.72 1540.71,212.366 \n",
       "  1542.59,1445.72 1544.47,415.368 1546.35,1445.72 1548.22,1445.72 1550.1,236.83 1551.98,362.317 1553.85,384.924 1555.73,1445.72 1557.61,446.879 1559.48,212.366 \n",
       "  1561.36,1445.72 1563.24,225.604 1565.11,308.8 1566.99,325.516 1568.87,1445.72 1570.74,325.516 1572.62,236.83 1574.5,236.83 1576.37,323.389 1578.25,379.274 \n",
       "  1580.13,277.024 1582,1445.72 1583.88,1445.72 1585.76,198.096 1587.63,438.569 1589.51,415.368 1591.39,225.604 1593.27,202.112 1595.14,415.368 1597.02,212.366 \n",
       "  1598.9,1445.72 1600.77,1445.72 1602.65,1445.72 1604.53,363.074 1606.4,308.8 1608.28,447.28 1610.16,1445.72 1612.03,1445.72 1613.91,362.317 1615.79,363.074 \n",
       "  1617.66,338.288 1619.54,201.67 1621.42,325.516 1623.29,1445.72 1625.17,1445.72 1627.05,1445.72 1628.92,225.604 1630.8,225.604 1632.68,338.288 1634.56,323.389 \n",
       "  1636.43,308.8 1638.31,1445.72 1640.19,323.389 1642.06,212.366 1643.94,1445.72 1645.82,1445.72 1647.69,323.389 1649.57,277.024 1651.45,338.288 1653.32,325.516 \n",
       "  1655.2,340.182 1657.08,1445.72 1658.95,447.28 1660.83,362.317 1662.71,438.569 1664.58,362.317 1666.46,1445.72 1668.34,294.689 1670.21,1445.72 1672.09,1445.72 \n",
       "  1673.97,1445.72 1675.85,378.48 1677.72,362.317 1679.6,236.83 1681.48,277.024 1683.35,325.516 1685.23,1445.72 1687.11,362.317 1688.98,447.28 1690.86,1445.72 \n",
       "  1692.74,321.521 1694.61,1445.72 1696.49,212.366 1698.37,1445.72 1700.24,236.83 1702.12,362.317 1704,384.924 1705.87,379.274 1707.75,438.569 1709.63,359.154 \n",
       "  1711.5,1445.72 1713.38,1445.72 1715.26,1445.72 1717.14,338.288 1719.01,1445.72 1720.89,415.368 1722.77,1445.72 1724.64,277.024 1726.52,212.366 1728.4,1445.72 \n",
       "  1730.27,415.368 1732.15,1445.72 1734.03,1445.72 1735.9,363.074 1737.78,325.516 1739.66,1445.72 1741.53,202.112 1743.41,1445.72 1745.29,362.317 1747.16,294.689 \n",
       "  1749.04,1445.72 1750.92,1445.72 1752.79,1445.72 1754.67,1445.72 1756.55,1445.72 1758.43,1445.72 1760.3,276.81 1762.18,384.924 1764.06,379.274 1765.93,308.8 \n",
       "  1767.81,362.317 1769.69,1445.72 1771.56,447.28 1773.44,323.389 1775.32,446.879 1777.19,384.924 1779.07,447.28 1780.95,1445.72 1782.82,87.9941 1784.7,1445.72 \n",
       "  1786.58,325.516 1788.45,446.879 1790.33,325.516 1792.21,212.366 1794.08,1445.72 1795.96,329.461 1797.84,415.368 1799.72,384.924 1801.59,218.486 1803.47,379.274 \n",
       "  1805.35,1445.72 1807.22,325.516 1809.1,1445.72 1810.98,225.604 1812.85,446.879 1814.73,294.689 1816.61,321.521 1818.48,1445.72 1820.36,198.096 1822.24,294.689 \n",
       "  1824.11,225.604 1825.99,338.288 1827.87,1445.72 1829.74,310.962 1831.62,1445.72 1833.5,447.28 1835.37,447.28 1837.25,1445.72 1839.13,1445.72 1841,212.366 \n",
       "  1842.88,362.317 1844.76,310.962 1846.64,236.83 1848.51,308.8 1850.39,325.516 1852.27,236.83 1854.14,1445.72 1856.02,447.28 1857.9,1445.72 1859.77,202.112 \n",
       "  1861.65,1445.72 1863.53,198.096 1865.4,1445.72 1867.28,359.154 1869.16,321.521 1871.03,225.604 1872.91,277.024 1874.79,87.9941 1876.66,363.074 1878.54,338.288 \n",
       "  1880.42,1445.72 1882.29,236.83 1884.17,1445.72 1886.05,294.689 1887.93,294.689 1889.8,1445.72 1891.68,362.317 1893.56,362.317 1895.43,362.317 1897.31,308.8 \n",
       "  1899.19,1445.72 1901.06,277.024 1902.94,340.182 1904.82,415.368 1906.69,1445.72 1908.57,340.182 1910.45,1445.72 1912.32,363.074 1914.2,277.024 1916.08,1445.72 \n",
       "  1917.95,276.81 1919.83,447.28 1921.71,362.317 1923.58,321.521 1925.46,323.389 1927.34,438.569 1929.22,198.096 1931.09,415.368 1932.97,212.366 1934.85,1445.72 \n",
       "  1936.72,384.924 1938.6,1445.72 1940.48,1445.72 1942.35,201.67 1944.23,310.962 1946.11,340.182 1947.98,308.8 1949.86,1445.72 1951.74,276.81 1953.61,329.461 \n",
       "  1955.49,329.461 1957.37,1445.72 1959.24,379.274 1961.12,1445.72 1963,415.368 1964.87,1445.72 1966.75,1445.72 1968.63,294.689 1970.51,378.48 1972.38,338.288 \n",
       "  1974.26,1445.72 1976.14,415.368 1978.01,340.182 1979.89,1445.72 1981.77,338.288 1983.64,1445.72 1985.52,363.074 1987.4,225.604 1989.27,438.569 1991.15,225.604 \n",
       "  1993.03,1445.72 1994.9,362.317 1996.78,340.182 1998.66,378.48 2000.53,218.486 2002.41,415.368 2004.29,198.096 2006.16,198.096 2008.04,202.112 2009.92,1445.72 \n",
       "  2011.8,276.81 2013.67,1445.72 2015.55,225.604 2017.43,447.28 2019.3,447.28 2021.18,1445.72 2023.06,1445.72 2024.93,363.074 2026.81,276.81 2028.69,378.48 \n",
       "  2030.56,1445.72 2032.44,379.274 2034.32,1445.72 2036.19,1445.72 2038.07,323.389 2039.95,310.962 2041.82,362.317 2043.7,201.67 2045.58,1445.72 2047.45,325.516 \n",
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       "  2068.1,446.879 2069.98,323.389 2071.85,1445.72 2073.73,1445.72 2075.61,1445.72 2077.48,363.074 2079.36,363.074 2081.24,415.368 2083.11,87.9941 2084.99,1445.72 \n",
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       "  2143.17,447.28 2145.05,236.83 2146.93,212.366 2148.8,378.48 2150.68,1445.72 2152.56,225.604 2154.43,338.288 2156.31,338.288 2158.19,1445.72 2160.06,276.81 \n",
       "  2161.94,378.48 2163.82,384.924 2165.69,1445.72 2167.57,1445.72 2169.45,325.516 2171.32,415.368 2173.2,212.366 2175.08,276.81 2176.95,1445.72 2178.83,277.024 \n",
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       "  1542.59,87.9763 1544.47,1118.32 1546.35,87.9763 1548.22,87.9763 1550.1,1296.86 1551.98,1171.38 1553.85,1148.77 1555.73,87.9763 1557.61,1086.81 1559.48,1321.33 \n",
       "  1561.36,87.9763 1563.24,1308.09 1565.11,1224.89 1566.99,1208.18 1568.87,87.9763 1570.74,1208.18 1572.62,1296.86 1574.5,1296.86 1576.37,1210.3 1578.25,1154.42 \n",
       "  1580.13,1256.67 1582,87.9763 1583.88,87.9763 1585.76,1335.6 1587.63,1095.12 1589.51,1118.32 1591.39,1308.09 1593.27,1331.58 1595.14,1118.32 1597.02,1321.33 \n",
       "  1598.9,87.9763 1600.77,87.9763 1602.65,87.9763 1604.53,1170.62 1606.4,1224.89 1608.28,1086.41 1610.16,87.9763 1612.03,87.9763 1613.91,1171.38 1615.79,1170.62 \n",
       "  1617.66,1195.4 1619.54,1332.02 1621.42,1208.18 1623.29,87.9763 1625.17,87.9763 1627.05,87.9763 1628.92,1308.09 1630.8,1308.09 1632.68,1195.4 1634.56,1210.3 \n",
       "  1636.43,1224.89 1638.31,87.9763 1640.19,1210.3 1642.06,1321.33 1643.94,87.9763 1645.82,87.9763 1647.69,1210.3 1649.57,1256.67 1651.45,1195.4 1653.32,1208.18 \n",
       "  1655.2,1193.51 1657.08,87.9763 1658.95,1086.41 1660.83,1171.38 1662.71,1095.12 1664.58,1171.38 1666.46,87.9763 1668.34,1239 1670.21,87.9763 1672.09,87.9763 \n",
       "  1673.97,87.9763 1675.85,1155.21 1677.72,1171.38 1679.6,1296.86 1681.48,1256.67 1683.35,1208.18 1685.23,87.9763 1687.11,1171.38 1688.98,1086.41 1690.86,87.9763 \n",
       "  1692.74,1212.17 1694.61,87.9763 1696.49,1321.33 1698.37,87.9763 1700.24,1296.86 1702.12,1171.38 1704,1148.77 1705.87,1154.42 1707.75,1095.12 1709.63,1174.54 \n",
       "  1711.5,87.9763 1713.38,87.9763 1715.26,87.9763 1717.14,1195.4 1719.01,87.9763 1720.89,1118.32 1722.77,87.9763 1724.64,1256.67 1726.52,1321.33 1728.4,87.9763 \n",
       "  1730.27,1118.32 1732.15,87.9763 1734.03,87.9763 1735.9,1170.62 1737.78,1208.18 1739.66,87.9763 1741.53,1331.58 1743.41,87.9763 1745.29,1171.38 1747.16,1239 \n",
       "  1749.04,87.9763 1750.92,87.9763 1752.79,87.9763 1754.67,87.9763 1756.55,87.9763 1758.43,87.9763 1760.3,1256.88 1762.18,1148.77 1764.06,1154.42 1765.93,1224.89 \n",
       "  1767.81,1171.38 1769.69,87.9763 1771.56,1086.41 1773.44,1210.3 1775.32,1086.81 1777.19,1148.77 1779.07,1086.41 1780.95,87.9763 1782.82,1445.7 1784.7,87.9763 \n",
       "  1786.58,1208.18 1788.45,1086.81 1790.33,1208.18 1792.21,1321.33 1794.08,87.9763 1795.96,1204.23 1797.84,1118.32 1799.72,1148.77 1801.59,1315.21 1803.47,1154.42 \n",
       "  1805.35,87.9763 1807.22,1208.18 1809.1,87.9763 1810.98,1308.09 1812.85,1086.81 1814.73,1239 1816.61,1212.17 1818.48,87.9763 1820.36,1335.6 1822.24,1239 \n",
       "  1824.11,1308.09 1825.99,1195.4 1827.87,87.9763 1829.74,1222.73 1831.62,87.9763 1833.5,1086.41 1835.37,1086.41 1837.25,87.9763 1839.13,87.9763 1841,1321.33 \n",
       "  1842.88,1171.38 1844.76,1222.73 1846.64,1296.86 1848.51,1224.89 1850.39,1208.18 1852.27,1296.86 1854.14,87.9763 1856.02,1086.41 1857.9,87.9763 1859.77,1331.58 \n",
       "  1861.65,87.9763 1863.53,1335.6 1865.4,87.9763 1867.28,1174.54 1869.16,1212.17 1871.03,1308.09 1872.91,1256.67 1874.79,1445.7 1876.66,1170.62 1878.54,1195.4 \n",
       "  1880.42,87.9763 1882.29,1296.86 1884.17,87.9763 1886.05,1239 1887.93,1239 1889.8,87.9763 1891.68,1171.38 1893.56,1171.38 1895.43,1171.38 1897.31,1224.89 \n",
       "  1899.19,87.9763 1901.06,1256.67 1902.94,1193.51 1904.82,1118.32 1906.69,87.9763 1908.57,1193.51 1910.45,87.9763 1912.32,1170.62 1914.2,1256.67 1916.08,87.9763 \n",
       "  1917.95,1256.88 1919.83,1086.41 1921.71,1171.38 1923.58,1212.17 1925.46,1210.3 1927.34,1095.12 1929.22,1335.6 1931.09,1118.32 1932.97,1321.33 1934.85,87.9763 \n",
       "  1936.72,1148.77 1938.6,87.9763 1940.48,87.9763 1942.35,1332.02 1944.23,1222.73 1946.11,1193.51 1947.98,1224.89 1949.86,87.9763 1951.74,1256.88 1953.61,1204.23 \n",
       "  1955.49,1204.23 1957.37,87.9763 1959.24,1154.42 1961.12,87.9763 1963,1118.32 1964.87,87.9763 1966.75,87.9763 1968.63,1239 1970.51,1155.21 1972.38,1195.4 \n",
       "  1974.26,87.9763 1976.14,1118.32 1978.01,1193.51 1979.89,87.9763 1981.77,1195.4 1983.64,87.9763 1985.52,1170.62 1987.4,1308.09 1989.27,1095.12 1991.15,1308.09 \n",
       "  1993.03,87.9763 1994.9,1171.38 1996.78,1193.51 1998.66,1155.21 2000.53,1315.21 2002.41,1118.32 2004.29,1335.6 2006.16,1335.6 2008.04,1331.58 2009.92,87.9763 \n",
       "  2011.8,1256.88 2013.67,87.9763 2015.55,1308.09 2017.43,1086.41 2019.3,1086.41 2021.18,87.9763 2023.06,87.9763 2024.93,1170.62 2026.81,1256.88 2028.69,1155.21 \n",
       "  2030.56,87.9763 2032.44,1154.42 2034.32,87.9763 2036.19,87.9763 2038.07,1210.3 2039.95,1222.73 2041.82,1171.38 2043.7,1332.02 2045.58,87.9763 2047.45,1208.18 \n",
       "  2049.33,1210.3 2051.21,1170.62 2053.08,1256.88 2054.96,87.9763 2056.84,1086.81 2058.72,1118.32 2060.59,1095.12 2062.47,87.9763 2064.35,1335.6 2066.22,1445.7 \n",
       "  2068.1,1086.81 2069.98,1210.3 2071.85,87.9763 2073.73,87.9763 2075.61,87.9763 2077.48,1170.62 2079.36,1170.62 2081.24,1118.32 2083.11,1445.7 2084.99,87.9763 \n",
       "  2086.87,87.9763 2088.74,1171.38 2090.62,1308.09 2092.5,87.9763 2094.37,1256.67 2096.25,1170.62 2098.13,87.9763 2100.01,1170.62 2101.88,1321.33 2103.76,87.9763 \n",
       "  2105.64,1148.77 2107.51,1086.81 2109.39,1332.02 2111.27,1256.88 2113.14,1296.86 2115.02,1154.42 2116.9,1148.77 2118.77,1445.7 2120.65,1208.18 2122.53,87.9763 \n",
       "  2124.4,1171.38 2126.28,1296.86 2128.16,87.9763 2130.03,87.9763 2131.91,1155.21 2133.79,1296.86 2135.66,1174.54 2137.54,1086.41 2139.42,1256.88 2141.3,1239 \n",
       "  2143.17,1086.41 2145.05,1296.86 2146.93,1321.33 2148.8,1155.21 2150.68,87.9763 2152.56,1308.09 2154.43,1195.4 2156.31,1195.4 2158.19,87.9763 2160.06,1256.88 \n",
       "  2161.94,1155.21 2163.82,1148.77 2165.69,87.9763 2167.57,87.9763 2169.45,1208.18 2171.32,1118.32 2173.2,1321.33 2175.08,1256.88 2176.95,87.9763 2178.83,1256.67 \n",
       "  2180.71,1086.41 2182.59,87.9763 2184.46,87.9763 2186.34,1118.32 2188.22,1256.88 2190.09,87.9763 2191.97,1086.41 2193.85,1086.41 2195.72,1212.17 2197.6,1086.41 \n",
       "  2199.48,1321.33 2201.35,1296.86 2203.23,1171.38 2205.11,1445.7 2206.98,1335.6 2208.86,1239 2210.74,1331.58 2212.61,1308.09 2214.49,1208.18 2216.37,1086.81 \n",
       "  2218.24,1095.12 2220.12,87.9763 2222,87.9763 2223.88,1224.89 2225.75,87.9763 2227.63,87.9763 2229.51,87.9763 2231.38,1118.32 2233.26,1315.21 2235.14,1315.21 \n",
       "  2237.01,1308.09 2238.89,1331.58 2240.77,1174.54 2242.64,1171.38 2244.52,87.9763 2246.4,87.9763 2248.27,87.9763 2250.15,1224.89 2252.03,87.9763 2253.9,1171.38 \n",
       "  2255.78,1208.18 2257.66,1296.86 2259.53,1204.23 2261.41,1086.81 2263.29,1224.89 2265.16,1174.54 2267.04,1193.51 2268.92,1331.58 2270.8,87.9763 2272.67,1171.38 \n",
       "  2274.55,1086.41 2276.43,1086.81 2278.3,1095.12 2280.18,1256.88 2282.06,1321.33 2283.93,87.9763 2285.81,1321.33 2287.69,1210.3 2289.56,87.9763 2291.44,87.9763 \n",
       "  \n",
       "  \"/>\n",
       "<path clip-path=\"url(#clip210)\" d=\"\n",
       "M2011.46 1438.47 L2280.54 1438.47 L2280.54 1282.95 L2011.46 1282.95  Z\n",
       "  \" fill=\"#ffffff\" fill-rule=\"evenodd\" fill-opacity=\"1\"/>\n",
       "<polyline clip-path=\"url(#clip210)\" style=\"stroke:#000000; stroke-linecap:round; stroke-linejoin:round; stroke-width:4; stroke-opacity:1; fill:none\" points=\"\n",
       "  2011.46,1438.47 2280.54,1438.47 2280.54,1282.95 2011.46,1282.95 2011.46,1438.47 \n",
       "  \"/>\n",
       "<polyline clip-path=\"url(#clip210)\" style=\"stroke:#009af9; stroke-linecap:round; stroke-linejoin:round; stroke-width:4; stroke-opacity:1; fill:none\" points=\"\n",
       "  2035.53,1334.79 2179.97,1334.79 \n",
       "  \"/>\n",
       "<path clip-path=\"url(#clip210)\" d=\"M2217.88 1354.48 Q2216.07 1359.11 2214.36 1360.52 Q2212.65 1361.94 2209.78 1361.94 L2206.38 1361.94 L2206.38 1358.37 L2208.88 1358.37 Q2210.63 1358.37 2211.61 1357.54 Q2212.58 1356.7 2213.76 1353.6 L2214.52 1351.66 L2204.04 1326.15 L2208.55 1326.15 L2216.65 1346.43 L2224.76 1326.15 L2229.27 1326.15 L2217.88 1354.48 Z\" fill=\"#000000\" fill-rule=\"evenodd\" fill-opacity=\"1\" /><path clip-path=\"url(#clip210)\" d=\"M2236.56 1348.14 L2244.2 1348.14 L2244.2 1321.77 L2235.89 1323.44 L2235.89 1319.18 L2244.15 1317.51 L2248.83 1317.51 L2248.83 1348.14 L2256.47 1348.14 L2256.47 1352.07 L2236.56 1352.07 L2236.56 1348.14 Z\" fill=\"#000000\" fill-rule=\"evenodd\" fill-opacity=\"1\" /><polyline clip-path=\"url(#clip210)\" style=\"stroke:#e26f46; stroke-linecap:round; stroke-linejoin:round; stroke-width:4; stroke-opacity:1; fill:none\" points=\"\n",
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       "  \"/>\n",
       "<path clip-path=\"url(#clip210)\" d=\"M2217.88 1406.32 Q2216.07 1410.95 2214.36 1412.36 Q2212.65 1413.78 2209.78 1413.78 L2206.38 1413.78 L2206.38 1410.21 L2208.88 1410.21 Q2210.63 1410.21 2211.61 1409.38 Q2212.58 1408.54 2213.76 1405.44 L2214.52 1403.5 L2204.04 1377.99 L2208.55 1377.99 L2216.65 1398.27 L2224.76 1377.99 L2229.27 1377.99 L2217.88 1406.32 Z\" fill=\"#000000\" fill-rule=\"evenodd\" fill-opacity=\"1\" /><path clip-path=\"url(#clip210)\" d=\"M2239.78 1399.98 L2256.1 1399.98 L2256.1 1403.91 L2234.15 1403.91 L2234.15 1399.98 Q2236.82 1397.22 2241.4 1392.6 Q2246 1387.94 2247.19 1386.6 Q2249.43 1384.08 2250.31 1382.34 Q2251.21 1380.58 2251.21 1378.89 Q2251.21 1376.14 2249.27 1374.4 Q2247.35 1372.66 2244.25 1372.66 Q2242.05 1372.66 2239.59 1373.43 Q2237.16 1374.19 2234.38 1375.74 L2234.38 1371.02 Q2237.21 1369.89 2239.66 1369.31 Q2242.12 1368.73 2244.15 1368.73 Q2249.52 1368.73 2252.72 1371.41 Q2255.91 1374.1 2255.91 1378.59 Q2255.91 1380.72 2255.1 1382.64 Q2254.32 1384.54 2252.21 1387.13 Q2251.63 1387.8 2248.53 1391.02 Q2245.43 1394.22 2239.78 1399.98 Z\" fill=\"#000000\" fill-rule=\"evenodd\" fill-opacity=\"1\" /></svg>\n"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using Plots\n",
    "plot(preds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "a4d849ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "preds[:,2]= [if x < 0.5 0 else 1 end for x in preds[:,2]];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "728b66d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1090×2 Matrix{Float32}:\n",
       " 0.800264    0.0\n",
       " 0.814238    0.0\n",
       " 1.36711f-5  1.0\n",
       " 0.847743    0.0\n",
       " 0.827981    0.0\n",
       " 1.36711f-5  1.0\n",
       " 0.741776    0.0\n",
       " 0.822133    0.0\n",
       " 1.36711f-5  1.0\n",
       " 0.847743    0.0\n",
       " 1.36711f-5  1.0\n",
       " 0.800264    0.0\n",
       " 1.36711f-5  1.0\n",
       " ⋮           \n",
       " 1.36711f-5  1.0\n",
       " 0.797935    0.0\n",
       " 0.735359    0.0\n",
       " 0.735655    0.0\n",
       " 0.741776    0.0\n",
       " 0.860911    0.0\n",
       " 0.908374    0.0\n",
       " 1.36711f-5  1.0\n",
       " 0.908374    0.0\n",
       " 0.826605    0.0\n",
       " 1.36711f-5  1.0\n",
       " 1.36711f-5  1.0"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "13f380f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1090-element BitVector:\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 0\n",
       " 1\n",
       " 0\n",
       " 0\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " ⋮\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1\n",
       " 1"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred = convert.(Int64, preds[:,2])\n",
    "prediction_df = DataFrame(y_actual = test_y, y_predicted = pred, prob_predicted = preds[:,1]);\n",
    "prediction_df.correctly_classified = prediction_df.y_actual .== prediction_df.y_predicted\n",
    "     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "095b788d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of the model is : 0.865137614678899"
     ]
    }
   ],
   "source": [
    "accuracy = mean(prediction_df.correctly_classified)\n",
    "print(\"Accuracy of the model is : \",accuracy)"
   ]
  },
  {
   "cell_type": "raw",
   "id": "cbd9880e",
   "metadata": {},
   "source": [
    "test_y"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Julia 1.8.3",
   "language": "julia",
   "name": "julia-1.8"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}