k-nearest-neighbour-o-ptimized-b-inary-e-stimator.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/input/nba-free-throws/free_throws.csv\n"
     ]
    }
   ],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load in \n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the \"../input/\" directory.\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# Any results you write to the current directory are saved as output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n",
      "1.0\n",
      "1.0\n",
      "1.221836035291544\n",
      "1.1462776372476002\n",
      "1.116600603841073\n",
      "1.0549725040039502\n",
      "1.04249439517558\n",
      "1.0400714280560561\n",
      "1.0300256701535584\n",
      "1.0389069978746095\n",
      "1.0317053122583848\n",
      "1.0242093710850997\n",
      "1.0438822665721947\n",
      "1.0414101490284606\n",
      "1.0318320054724055\n",
      "1.0579506596319928\n",
      "1.0425518862409817\n",
      "1.0419168961771836\n",
      "1.0450293435062783\n",
      "1.0446938987540142\n",
      "1.04012415176964\n",
      "1.0442518616156138\n",
      "1.0372967453002473\n",
      "1.0406374954152606\n",
      "1.0510597929003391\n",
      "1.051841420927914\n",
      "1.046570092860661\n",
      "1.0480646976015158\n",
      "1.0507137938776998\n",
      "1.0436085338858285\n",
      "1.040448179239802\n",
      "1.0431381087225386\n",
      "1.0637699516510728\n",
      "1.0629210136331684\n",
      "1.0617003356147325\n",
      "1.0527405754444388\n",
      "1.0555004367206584\n",
      "1.094965250368896\n",
      "1.088280055442117\n",
      "1.0737762454181778\n",
      "1.0920821314378382\n",
      "1.0904912681584786\n",
      "1.0911544544183787\n",
      "1.1126662593838468\n",
      "1.1078602130798647\n",
      "1.100079095334758\n",
      "1.0954034486174546\n",
      "1.0932771256881684\n",
      "1.0891044864694313\n",
      "1.0861067270062263\n",
      "1.0842937853497723\n",
      "1.0832570210856707\n",
      "1.085618869442829\n",
      "1.0806739479553158\n",
      "1.0788492992904921\n",
      "1.0773724890938123\n",
      "1.0707596969880362\n",
      "1.0731411499071022\n",
      "1.0723789760963374\n",
      "1.0702662793327127\n",
      "1.0675296064041195\n",
      "1.0667917183844164\n",
      "1.0837831278136842\n",
      "1.0947144573988563\n",
      "1.092485271298485\n",
      "1.0906102063163259\n",
      "1.0893895892929093\n",
      "1.0894363715003115\n",
      "1.0890007273340612\n",
      "1.0879098793337048\n",
      "1.087533166074971\n",
      "1.0893344002580654\n",
      "1.0933848923132303\n",
      "1.0937408683123488\n",
      "1.0933686720334113\n",
      "1.0952987498198656\n",
      "1.092839570254341\n",
      "1.091027670170932\n",
      "1.08855559066789\n",
      "1.083118487953881\n",
      "1.077093273933426\n",
      "1.0737765808976756\n",
      "1.0712042572980685\n",
      "1.0688078532839453\n",
      "1.066841381768412\n",
      "1.0649997392792185\n",
      "1.064664597099772\n",
      "1.0639271489438902\n",
      "1.0646973512987572\n",
      "1.0645056130316084\n",
      "1.0624856899665482\n",
      "1.0610918855753662\n",
      "1.0619003129603042\n",
      "1.0619101772763975\n",
      "1.062207668082941\n",
      "1.0604852709450732\n",
      "1.0593338998787274\n",
      "1.0669092367146027\n",
      "1.0647237469990747\n",
      "1.0645838331802466\n",
      "1.0614402238130736\n",
      "1.0600565856094915\n",
      "1.0590846002102248\n",
      "1.0574628934798298\n",
      "1.0559039418441052\n",
      "1.0551330355112885\n",
      "1.050519237273967\n",
      "1.0470929783880056\n",
      "1.0480746865146704\n",
      "1.0473588586859535\n",
      "1.0476367305141578\n",
      "1.0470833407559204\n",
      "1.0468360829297763\n",
      "1.0460981306995356\n",
      "1.0458602389980844\n",
      "1.0453636419911894\n",
      "1.0442389943532129\n",
      "1.0438180326391033\n",
      "1.0444957473665126\n",
      "1.0440684879346958\n",
      "1.0438902155247016\n",
      "1.0441820416127483\n",
      "1.0429093966709049\n",
      "1.041562345043058\n",
      "1.042496491055129\n",
      "1.0416385047125556\n",
      "1.0412215041130144\n",
      "1.0405228303587988\n",
      "1.0400228544342491\n",
      "1.0380053534107825\n",
      "1.0363498957119182\n",
      "1.0358579422282481\n",
      "1.0350955716983126\n",
      "1.0340694135848443\n",
      "1.0334726725832015\n",
      "1.0328297650029157\n",
      "1.0331815968669535\n",
      "1.0331938386805957\n",
      "1.0307046783662561\n",
      "1.0301427100784657\n",
      "1.030074360266178\n",
      "1.0303195962429321\n",
      "1.0274284325214431\n",
      "1.0272696628636733\n",
      "1.0278174950088081\n",
      "1.0276550757209262\n",
      "1.0274941211406803\n",
      "1.027613485577193\n",
      "1.0280737529330406\n",
      "1.028079505378285\n",
      "1.028174802247606\n",
      "1.0284834264460305\n",
      "1.0284273413738825\n",
      "1.0369244941370266\n",
      "1.0369980717719693\n",
      "1.036738508393702\n",
      "1.0367715571463922\n",
      "1.0368233844000811\n",
      "1.0369218524093873\n",
      "1.03695840198561\n",
      "1.0371964414337875\n",
      "1.036201791097942\n",
      "1.0406463488749589\n",
      "1.040525092405718\n",
      "1.0404263508255471\n",
      "1.0429913696273552\n",
      "1.041539808849619\n",
      "1.0412419197488723\n",
      "1.0412988184740135\n",
      "1.0461421098077641\n",
      "1.046910526308383\n",
      "1.048221119567757\n",
      "1.0486180362060051\n",
      "1.0504762978866384\n",
      "1.0501118027472167\n",
      "1.0482984334466383\n",
      "1.0529903631995787\n",
      "1.0528162756759745\n",
      "1.0522411398756877\n",
      "1.0544915589809172\n",
      "1.055352087969199\n",
      "1.0546884963622838\n",
      "1.0538979221337057\n",
      "1.0535147364518103\n",
      "1.053295749263311\n",
      "1.0550338443037237\n",
      "1.0547209730704221\n",
      "1.054649821344276\n",
      "1.0547625041790396\n",
      "1.0546063252706446\n",
      "1.0543245594959318\n",
      "1.0544669039678924\n",
      "1.054081260737395\n",
      "1.0538423337322635\n",
      "1.053191794160888\n",
      "1.051264796329962\n",
      "1.0522379768770993\n",
      "1.0520573600901213\n",
      "1.0520778501159331\n",
      "1.0518621180120387\n",
      "1.0519061007000463\n",
      "1.0517203520296605\n",
      "1.0517549921423153\n",
      "1.0513293604871627\n",
      "1.0510091533642296\n",
      "1.0508690847557796\n",
      "1.0504521023896352\n",
      "1.048758539387987\n",
      "1.0485141851001236\n",
      "1.0477810060046162\n",
      "1.0483555112190912\n",
      "1.046758775374596\n",
      "1.0495403066416198\n",
      "1.0490566792792402\n",
      "1.0491779816732905\n",
      "1.049886623228922\n",
      "1.0500202820344389\n",
      "1.0483685715781363\n",
      "1.048966036954512\n",
      "1.0485744532143941\n",
      "1.0483314930474832\n",
      "1.0480425321070854\n",
      "1.047408247853366\n",
      "1.047249926063441\n",
      "1.0467964638654172\n",
      "1.046944519005599\n",
      "1.0467883702262208\n",
      "1.0458632052490173\n",
      "1.0452729673645036\n",
      "1.0450488562512177\n",
      "1.0448765090011043\n",
      "1.0442038562594245\n",
      "1.0467113367816254\n",
      "1.0464083467415302\n",
      "1.0451508520943862\n",
      "1.044289197152074\n",
      "1.0433871150374887\n",
      "1.0479876570309417\n",
      "1.0485587448784974\n",
      "1.0479362767862241\n",
      "1.0477891044319216\n",
      "1.0472843274218233\n",
      "1.0464878390072667\n",
      "1.0494971069906853\n",
      "1.051768614373157\n",
      "1.05213396479411\n",
      "1.051987438045025\n",
      "1.0519704153900915\n",
      "1.0519503443181246\n",
      "1.0508385626767347\n",
      "1.0496938237848297\n",
      "1.0539945933917465\n",
      "1.0542339821073603\n",
      "1.0544639456459945\n",
      "1.053891694797776\n",
      "1.052729109269965\n",
      "1.0535159726381331\n",
      "1.0523703256426795\n",
      "1.051700225792954\n",
      "1.0509348311919622\n",
      "1.050021064090564\n",
      "1.0499873735525236\n",
      "1.049915619001617\n",
      "1.049842600203569\n",
      "1.049709134765901\n",
      "1.0496929821146417\n",
      "1.0492760776278536\n",
      "1.0487300521528518\n",
      "1.0483356761229718\n",
      "1.0501578097732616\n",
      "1.0495184239579083\n",
      "1.049224038561551\n",
      "1.0488461046410393\n",
      "1.048201947614598\n",
      "1.0478301807799992\n",
      "1.0469464929044001\n",
      "1.047038627229648\n",
      "1.046287217310646\n",
      "1.0465401439667512\n",
      "1.0463533702982397\n",
      "1.0464042228576205\n",
      "1.0461654118942165\n",
      "1.0462052105188588\n",
      "1.0451135234305353\n",
      "1.044425885110978\n",
      "1.044203202412882\n",
      "1.0442693213180338\n",
      "1.0457005598343556\n",
      "1.0452059545914425\n",
      "1.0450772155314343\n",
      "1.0449861381088872\n",
      "1.0448671211037213\n",
      "1.0448042544340725\n",
      "1.0448597699622562\n",
      "1.0441492597950393\n",
      "1.0445841879943738\n",
      "1.0450080709023943\n",
      "1.044364433550596\n",
      "1.0445692435743097\n",
      "1.0444569604390928\n",
      "1.0443963399533849\n",
      "1.0440246739030001\n",
      "1.0451838005109728\n",
      "1.0440640808565531\n",
      "1.0447163764051781\n",
      "1.0445468614892912\n",
      "1.0448138802879523\n",
      "1.0448865791962236\n",
      "1.0448606193346843\n",
      "1.0449264982926731\n",
      "1.0446984437475584\n",
      "1.044755602981418\n",
      "1.0444647499481097\n",
      "1.0441107187767649\n",
      "1.0442212658570935\n",
      "1.0444661354627967\n",
      "1.044527679854305\n",
      "1.0441963734280288\n",
      "1.0439119797429246\n",
      "1.0436044120354695\n",
      "1.0429761703809892\n",
      "1.0426107778760723\n",
      "1.042395078996897\n",
      "1.0420788792778635\n",
      "1.0418276815291982\n",
      "1.0415727020179975\n",
      "1.0413253450183886\n",
      "1.0401330307436267\n",
      "1.0399586398188738\n",
      "1.039506666613106\n",
      "1.0396305454192427\n",
      "1.0397568962122623\n",
      "1.0396345759200551\n",
      "1.040145632086482\n",
      "1.0401225880950702\n",
      "1.0400714647510807\n",
      "1.039941087083004\n",
      "1.0396682851198713\n",
      "1.0389075804442596\n",
      "1.0390148106919612\n",
      "1.0390787380693052\n",
      "1.0382433841474947\n",
      "1.0382002777179737\n",
      "1.0381051107794288\n",
      "1.0393776978996927\n",
      "1.0390691416658615\n",
      "1.0386903851324127\n",
      "1.0388718822150191\n",
      "1.0389120365814493\n",
      "1.0390703312117888\n",
      "1.0384486591773752\n",
      "1.038137526970978\n",
      "1.0411551878085696\n",
      "1.0441928477724078\n",
      "1.0432378165284704\n",
      "1.0438137773556984\n",
      "1.0435663682508374\n",
      "1.0424606758201511\n",
      "1.0427388613704247\n",
      "1.0423557879566832\n",
      "1.042234549661642\n",
      "1.042062984430781\n",
      "1.0417450827662629\n",
      "1.041303939512054\n",
      "1.0410740069935762\n",
      "1.0403013907946297\n",
      "1.0402840707651764\n",
      "1.0404025757172743\n",
      "1.0410568882787115\n",
      "1.0408017143596153\n",
      "1.0407846855351215\n",
      "1.040735761371866\n",
      "1.040429512012211\n",
      "1.0425533315777424\n",
      "1.0425298143590482\n",
      "1.0425054896646357\n",
      "1.0444027058072751\n",
      "1.0441125204343398\n",
      "1.0436967534530743\n",
      "1.0432032252587493\n",
      "1.0464363449246148\n",
      "1.0489414801876211\n",
      "1.0486132130016785\n",
      "1.0484690133206553\n",
      "1.0481092328202708\n",
      "1.0476051091766032\n",
      "1.0476646341314577\n",
      "1.0476233139810682\n",
      "1.0478147335208685\n",
      "1.0516156907522938\n",
      "1.055298496360362\n",
      "1.0547931350936632\n",
      "1.0540870016902135\n",
      "1.0536913818295273\n",
      "1.0536654060893953\n",
      "1.053355318280386\n",
      "1.0539472952241467\n",
      "1.053865868577972\n",
      "1.0537573933724826\n",
      "1.0533949877989\n",
      "1.053201731115879\n",
      "1.0528660267925343\n",
      "1.0537258082384717\n",
      "1.0562851921493974\n",
      "1.055512105831045\n",
      "1.0567262945754823\n",
      "1.0575001305429679\n",
      "1.0570067061940656\n",
      "1.0570064845353997\n",
      "1.05698585444326\n",
      "1.0573219266700669\n",
      "1.0576512315445865\n",
      "1.0579738954016027\n",
      "1.0573297517090288\n",
      "1.0591455461988448\n",
      "1.0582726185673925\n",
      "1.0577308666765832\n",
      "1.056952602488162\n",
      "1.058774034201704\n",
      "1.0585535360218785\n",
      "1.0581680870840988\n",
      "1.05980460663826\n",
      "1.059202581899917\n",
      "1.059062669301036\n",
      "1.0583896485986597\n",
      "1.057853897484429\n",
      "1.057541648492387\n",
      "1.0599077427534966\n",
      "1.0591162219434553\n",
      "1.0585751918749817\n",
      "1.0581777144291087\n",
      "1.0581946231526105\n",
      "1.0583321063274633\n",
      "1.060677468110746\n",
      "1.0602192597583306\n",
      "1.0603023964804938\n",
      "1.0603195627468118\n",
      "1.0602474292930497\n",
      "1.0602695701351843\n",
      "1.0625548069933937\n",
      "1.0660173268067974\n",
      "1.0695019883348282\n",
      "1.0678252639760706\n",
      "1.0674649871721114\n",
      "1.0673306442980646\n",
      "1.0671914747257494\n",
      "1.0674813717801068\n",
      "1.0660819568379656\n",
      "1.0658685758324746\n",
      "1.0654340351935674\n",
      "1.064837810964412\n",
      "1.0648260286903595\n",
      "1.0669124983077185\n",
      "1.0688746626738899\n",
      "1.0715743321315143\n",
      "1.0723585044385797\n",
      "1.0720141953508662\n",
      "1.072198678497219\n",
      "1.0719629289329506\n",
      "1.0721421384811072\n",
      "1.0719070282805212\n",
      "1.071771468106502\n",
      "1.0716432739644903\n",
      "1.0714085580922015\n",
      "1.0731077470190376\n",
      "1.0727316622309915\n",
      "1.072437437960237\n",
      "1.0723051834548627\n",
      "1.0719293425725096\n",
      "1.0717486328432608\n",
      "1.0711685509609232\n",
      "1.070888805102759\n",
      "1.0707268279463982\n",
      "1.070539841592552\n",
      "1.0702111829668919\n",
      "1.069882528868663\n",
      "1.0693676674330708\n",
      "1.0693741543719306\n",
      "1.0694170435103583\n",
      "1.071353162841296\n",
      "1.0718754688455412\n",
      "1.071811811660876\n",
      "1.0718839731449932\n",
      "1.0714032894100083\n",
      "1.0714978446691747\n",
      "1.0716086371612512\n",
      "1.0703218370316565\n",
      "1.0727429719041126\n",
      "1.0726252403283196\n",
      "1.0720929767149643\n",
      "1.0719223680018952\n",
      "1.071891398051686\n",
      "1.0714396928500294\n",
      "1.0711005653041699\n",
      "1.0708815987638525\n",
      "1.0703058684977873\n",
      "1.0694421813468296\n",
      "1.0699337015249692\n",
      "1.0698424488577063\n",
      "1.068689854676239\n",
      "1.0679366110822963\n",
      "1.0679923540622713\n",
      "1.0681362412872115\n",
      "1.0681934948416654\n",
      "1.0683493579343548\n",
      "1.0683846061876032\n",
      "1.0685233046262348\n",
      "1.0698505242047645\n",
      "1.0707183504877942\n",
      "1.070405773537383\n",
      "1.070717242131626\n",
      "1.0722409188413884\n",
      "1.0714025539841834\n",
      "1.0712063081813603\n",
      "1.0709441338857877\n",
      "1.0705441245698177\n",
      "1.0702702415991414\n",
      "1.0702645198457545\n",
      "1.069890545592083\n",
      "1.0701710635389183\n",
      "1.0699334774789857\n",
      "1.0697496632132333\n",
      "1.06964883521834\n",
      "1.069532508381884\n",
      "1.0694864056595577\n",
      "1.0692141217351878\n",
      "1.0692284869336954\n",
      "1.0711225432692908\n",
      "1.0711276165744013\n",
      "1.0708544153402528\n",
      "1.0705832861609392\n",
      "1.0704464719564135\n",
      "1.0704310208253789\n",
      "1.070336160591511\n",
      "1.0700629720513553\n",
      "1.0695413296367025\n",
      "1.0702419702856358\n",
      "1.0699176448718262\n",
      "1.0695959353911266\n",
      "1.0693686389857504\n",
      "1.0689724239678144\n",
      "1.0686852593076968\n",
      "1.0691147750835406\n",
      "1.069887270989391\n",
      "1.0697833502908536\n",
      "1.0704556752632959\n",
      "1.0703193776016453\n",
      "1.0703206079243752\n",
      "1.0707427638455373\n",
      "1.070512181851242\n",
      "1.070270650301838\n",
      "1.0702043150595368\n",
      "1.0695039006739233\n",
      "1.0697827848920638\n",
      "1.0700636543226765\n",
      "1.0698861935999706\n",
      "1.0692720376588087\n",
      "1.0686075186813515\n",
      "1.0685494730442786\n",
      "1.0681022663289998\n",
      "1.068672131173752\n",
      "1.0685343860712542\n",
      "1.068331398219551\n",
      "1.0681125990055766\n",
      "1.068041305862002\n",
      "1.0669726927924763\n",
      "1.0670252201825703\n",
      "1.0665591876985678\n",
      "1.0656671338483246\n",
      "1.0669545383848278\n",
      "1.0667211901376539\n",
      "1.0661540216939718\n",
      "1.0682794835821492\n",
      "1.0677934897847485\n",
      "1.0675045783508494\n",
      "1.0675923998077261\n",
      "1.067508347013989\n",
      "1.067616474353093\n",
      "1.0677131033178064\n",
      "1.0672954048539385\n",
      "1.067060612967974\n",
      "1.0671262700553772\n",
      "1.0669091774987154\n",
      "1.0669671641146878\n",
      "1.0666591209379885\n",
      "1.0656077382364184\n",
      "1.0654060506703276\n",
      "1.0653437741671135\n",
      "1.0669536552520107\n",
      "1.0663675348014792\n",
      "1.066282458234069\n",
      "1.0663797745402774\n",
      "1.0663423015753866\n",
      "1.0664059076563646\n",
      "1.066163657470409\n",
      "1.0660705731514386\n",
      "1.0659387073003892\n",
      "1.0657376965185976\n",
      "1.0656290059994915\n",
      "1.0653529283025218\n",
      "1.0649674128065278\n",
      "1.0654194750824022\n",
      "1.0653342434064952\n",
      "1.066327919219319\n",
      "1.0663698336755756\n",
      "1.066404574278612\n",
      "1.0660286555762364\n",
      "1.06587174658503\n",
      "1.0658200755886447\n",
      "1.066392702151529\n",
      "1.0666738559706461\n",
      "1.0666819655180075\n",
      "1.0667226004420547\n",
      "1.0685091007471925\n",
      "1.0683858049998018\n",
      "1.0679751042317498\n",
      "1.0677997823159966\n",
      "1.0674625292039743\n",
      "1.0675052855228901\n",
      "1.067676726651068\n",
      "1.0674141274275206\n",
      "1.0671265206533918\n",
      "1.0669479975100873\n",
      "1.067642762472247\n",
      "1.0674730273085975\n",
      "1.068755444076182\n",
      "1.0684201650129233\n",
      "1.0693314497294462\n",
      "1.070824585619999\n",
      "1.070661566239875\n",
      "1.0705175716349034\n",
      "1.0702511728990527\n",
      "1.0699758753621051\n",
      "1.0697971450345862\n",
      "1.069815075246917\n",
      "1.0698081654834193\n",
      "1.069887054068513\n",
      "1.0696817520474708\n",
      "1.0694356223256787\n",
      "1.069316821734661\n",
      "1.0691150803669238\n",
      "1.0693025850209175\n",
      "1.0694796290440711\n",
      "1.0692188414094745\n",
      "1.0691383199343387\n",
      "1.0689376706667573\n",
      "1.068592819857486\n",
      "1.0684780073194917\n",
      "1.0681228285774511\n",
      "1.0679040798956778\n",
      "1.06788710349269\n",
      "1.068078855981385\n",
      "1.0680929073456893\n",
      "1.0680463361575063\n",
      "1.0679710752009706\n",
      "1.0678735178409506\n",
      "1.0677943906359804\n",
      "1.0689848770272607\n",
      "1.0692693803502238\n",
      "1.06957048609385\n",
      "1.0693804792337411\n",
      "1.0691274181079862\n",
      "1.0690792639431979\n",
      "1.0688046816084662\n",
      "1.0685347456904384\n",
      "1.068389105858214\n",
      "1.068369486988311\n",
      "1.0681241564661241\n",
      "1.0688442146019086\n",
      "1.068950745617414\n",
      "1.068964835102107\n",
      "1.0682722902514252\n",
      "1.0677010332023444\n",
      "1.067586357783658\n",
      "1.0674600121543665\n",
      "1.0674288651336095\n",
      "1.0670338200471141\n",
      "1.067446944647537\n",
      "1.0673857667149738\n",
      "1.0673107713923977\n",
      "1.0672531236466798\n",
      "1.0669547720679575\n",
      "1.0671232680320408\n",
      "1.066732300067657\n",
      "1.0666284931428032\n",
      "1.0669301223366745\n",
      "1.0671678805475315\n",
      "1.0669347879130753\n",
      "1.066744046995754\n",
      "1.066652058754422\n",
      "1.0663893191217175\n",
      "1.0662714041260473\n",
      "1.0661575459102468\n",
      "1.0661512807812459\n",
      "1.0658801036047807\n",
      "1.065902978404672\n",
      "1.0656302937384392\n",
      "1.0662616745515152\n",
      "1.0662062723291712\n",
      "1.0664330208124413\n",
      "1.0666425024894686\n",
      "1.0667012263185538\n",
      "1.0664748301805003\n",
      "1.0667009183317386\n",
      "1.0667198353449576\n",
      "1.066539715202107\n",
      "1.0664638418419854\n",
      "1.0664141938824672\n",
      "1.0664747458539647\n",
      "1.0667754133704606\n",
      "1.06666248849351\n",
      "1.0665499781251264\n",
      "1.0664272559766161\n",
      "1.0663156141866688\n",
      "1.0662304380683543\n",
      "1.0661970141889066\n",
      "1.0660929121112144\n",
      "1.0660927717027275\n",
      "1.066625077570366\n",
      "1.0665165946643982\n",
      "1.066125883371752\n",
      "1.0657871123116478\n",
      "1.0656842474366053\n",
      "1.0657427650056632\n",
      "1.0655275560444968\n",
      "1.065490147017434\n",
      "1.0651297762387697\n",
      "1.0650809762661622\n",
      "1.064945019580093\n",
      "1.064863807630923\n",
      "1.0653723804061295\n",
      "1.0652273138767916\n",
      "1.0650170723768224\n",
      "1.0649466890687658\n",
      "1.0652320960296071\n",
      "1.0682611987965733\n",
      "1.0681125070794093\n",
      "1.0680463878743172\n",
      "1.0676862019952515\n",
      "1.067506830177721\n",
      "1.0670259704134675\n",
      "1.0680310952406737\n",
      "1.0680390762815504\n",
      "1.0680377917361925\n",
      "1.0680249756724078\n",
      "1.068012954013408\n",
      "1.0680052960419566\n",
      "1.0688061436923255\n",
      "1.0683477876094687\n",
      "1.06813742809334\n",
      "1.0680146876841305\n",
      "1.0678018268562834\n",
      "1.0674156553769334\n",
      "1.0671946627799787\n",
      "1.0670188360530695\n",
      "1.0668924714695218\n",
      "1.0669451892856152\n",
      "1.0667246940800215\n",
      "1.0665177145591265\n",
      "1.0664124829255077\n",
      "1.0662575301698998\n",
      "1.0660077487025343\n",
      "1.0657898151388723\n",
      "1.0669943959883441\n",
      "1.0669602264326314\n",
      "1.0666038678129084\n",
      "1.0661325406222626\n",
      "1.067329769530638\n",
      "1.0670692046596242\n",
      "1.0666958872959105\n",
      "1.06622766737245\n",
      "1.0658400065567213\n",
      "1.0654161542119296\n",
      "1.0662950151062984\n",
      "1.0658504595530656\n",
      "1.0667282044692794\n",
      "1.0663017844559743\n",
      "1.0662084159953937\n",
      "1.066145089403141\n",
      "1.0666057221286969\n",
      "1.0664062054543348\n",
      "1.0668215203119753\n",
      "1.0669171845723517\n",
      "1.0668904445978733\n",
      "1.0668386381478352\n",
      "1.0667733245557431\n",
      "1.066691783371928\n",
      "1.0675616670010495\n",
      "1.0685607399818435\n",
      "1.0687531789715576\n",
      "1.0728481780235348\n",
      "1.0730304268201472\n",
      "1.07296591510933\n",
      "1.072858337071899\n",
      "1.0727650301864087\n",
      "1.0731003996214015\n",
      "1.073340070409901\n",
      "1.0731112910139435\n",
      "1.073156060293863\n",
      "1.0729315594055342\n",
      "1.0728337019418221\n",
      "1.0726016792743114\n",
      "1.0725271079099474\n",
      "1.072318802634131\n",
      "1.0726392378248872\n",
      "1.0730401916953942\n",
      "1.0730786394826881\n",
      "1.073009097523817\n",
      "1.0726114450380126\n",
      "1.0739749993387853\n",
      "1.0736274652833036\n",
      "1.0736015817997508\n",
      "1.0730947099745864\n",
      "1.0727069731085077\n",
      "1.0723570616803335\n",
      "1.0728304163429945\n",
      "1.0726685998270953\n",
      "1.0725678398470464\n",
      "1.07234821372929\n",
      "1.0722290089979265\n",
      "1.0720778680435494\n",
      "1.0719942887166658\n",
      "1.0719402418959871\n",
      "1.071906324211482\n",
      "1.0719474913347253\n",
      "1.0715198759635287\n",
      "1.07096645270526\n",
      "1.0706872335424285\n",
      "1.0706656254054818\n",
      "1.0718403729176404\n",
      "1.071424402537116\n",
      "1.0713798742700051\n",
      "1.0713352127237643\n",
      "1.0708093474140268\n",
      "1.0704345847241408\n",
      "1.070343722530251\n",
      "1.0703042013893063\n",
      "1.0700301378053971\n",
      "1.0698720867885234\n",
      "1.0697226201650427\n",
      "1.0701473330846922\n",
      "1.0701437292134448\n",
      "1.0699603383358156\n",
      "1.069798520697514\n",
      "1.0694050663466141\n",
      "1.068860060307841\n",
      "1.0687163942239661\n",
      "1.0687894636935273\n",
      "1.0686045020719632\n",
      "1.0684818546561248\n",
      "1.068262308074254\n",
      "1.0679841282965696\n",
      "1.0676701257141605\n",
      "1.067443825336177\n",
      "1.068524903612135\n",
      "1.0684487776621199\n",
      "1.0684507273043111\n",
      "1.0682882225151447\n",
      "1.0682202496622355\n",
      "1.067843503240239\n",
      "1.0684856567479337\n",
      "1.069305771957442\n",
      "1.0699214982366487\n",
      "1.0710740211725118\n",
      "1.0706034442481063\n",
      "1.0704947871883246\n",
      "1.0713159043909108\n",
      "1.0710742478719755\n",
      "1.071044067204568\n",
      "1.0712316633881496\n",
      "1.0712002231423299\n",
      "1.071177298849206\n",
      "1.0708734809296858\n",
      "1.0707860705672507\n",
      "1.0707731137687682\n",
      "1.070574577242982\n",
      "1.070496216161705\n",
      "1.0714987632676949\n",
      "1.0710794894147895\n",
      "1.070362487368128\n",
      "1.0731785881287697\n",
      "1.0731442495117718\n",
      "1.0729434613127513\n",
      "1.0728858957049867\n",
      "1.072857381076928\n",
      "1.0726890730285736\n",
      "1.0725096769718694\n",
      "1.0722735115658397\n",
      "1.072099317414054\n",
      "1.0728438318157971\n",
      "1.0727217051560929\n",
      "1.0726706281184204\n",
      "1.0725669109683482\n",
      "1.0725589588088973\n",
      "1.0723180946608633\n",
      "1.0721700726498467\n",
      "1.0719314219341403\n",
      "1.0717167590147139\n",
      "1.0717153976101825\n",
      "1.0714796172346055\n",
      "1.0712675701658547\n",
      "1.0711902727851121\n",
      "1.0711203832861078\n",
      "1.0711543445321199\n",
      "1.071202237318711\n",
      "1.0710748880433696\n",
      "1.0710011704989792\n",
      "1.0710091484514983\n",
      "1.0710754291779991\n",
      "1.0714311623222281\n",
      "1.0711069877256203\n",
      "1.0717877784965266\n",
      "1.0718946181284328\n",
      "1.0716990936831714\n",
      "1.0726207947188917\n",
      "1.07252501013244\n",
      "1.072496470434429\n",
      "1.072593622629244\n",
      "1.072361222245134\n",
      "1.072390664668247\n",
      "1.0724468346846472\n",
      "1.0726061432708216\n",
      "1.072529668042746\n",
      "1.072572547305584\n",
      "1.071854101690665\n",
      "1.073537191337827\n",
      "1.0735443879199744\n",
      "1.0735940499170507\n",
      "1.073749833177517\n",
      "1.073394404990751\n",
      "1.0732187938300437\n",
      "1.0729627842592047\n",
      "1.0727062172106672\n",
      "1.0723878350441707\n",
      "1.0728338351832483\n",
      "1.0733464995157727\n",
      "1.0730269055472932\n",
      "1.0727896705735591\n",
      "1.073495368212571\n",
      "1.0739748178433688\n",
      "1.073693249721892\n",
      "1.0736390072160904\n",
      "1.0738152006340598\n",
      "1.0736495508969548\n",
      "1.0743530733325588\n",
      "1.0740434495386604\n",
      "1.0740244597283433\n",
      "1.0757732963511695\n",
      "1.0774627711825049\n",
      "1.0768341958495373\n",
      "1.0783931369962743\n",
      "1.078407637246294\n",
      "1.0784584921729548\n",
      "1.0776817458199597\n",
      "1.0792394311406188\n",
      "1.078969056319589\n",
      "1.079031938225233\n",
      "1.0789919181677212\n",
      "1.0788988609340118\n",
      "1.0810402742985399\n",
      "1.0803621322371664\n",
      "1.080123847291758\n",
      "1.0799191353342696\n",
      "1.0796712315634434\n",
      "1.0790551945173965\n",
      "1.081080791997525\n",
      "1.0809863435785463\n",
      "1.080687804344221\n",
      "1.0800890999587756\n",
      "1.0820814733306787\n",
      "1.083626962093947\n",
      "1.0855997729927624\n",
      "1.087221368493325\n",
      "1.0890767132506893\n",
      "1.0890304964633333\n",
      "1.0893497339837386\n",
      "1.0892915771019889\n",
      "1.0892775027912234\n",
      "1.089416988141609\n",
      "1.0892694166426158\n",
      "1.089276580671041\n",
      "1.090914568839383\n",
      "1.0906318802147432\n",
      "1.0910237038518271\n",
      "1.091025421096025\n",
      "1.0910266555002661\n",
      "1.0909188128799583\n",
      "1.0908274267701283\n",
      "1.0906909082689882\n",
      "1.0903489195923415\n",
      "1.090204637768646\n",
      "1.089916767485584\n",
      "1.0902430250275719\n",
      "1.0906892385652327\n",
      "1.09051863413153\n",
      "1.0904682248615274\n",
      "1.090039535607159\n",
      "1.0899546815522352\n",
      "1.0898966761283173\n",
      "1.089590288450317\n",
      "1.0894130807114217\n",
      "1.08944531421015\n",
      "1.0895957962853977\n",
      "1.0895245522064\n",
      "1.089452463282003\n",
      "1.0895079026615713\n",
      "1.089444708035625\n",
      "1.0894254701579764\n",
      "1.0900696239615184\n",
      "1.0907157520147974\n",
      "1.090600998177479\n",
      "1.0903474593611655\n",
      "1.0901985422644989\n",
      "1.0899921735886255\n",
      "1.0898718228146074\n"
     ]
    },
    {
     "ename": "ZeroDivisionError",
     "evalue": "division by zero",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-5e97609cae64>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     82\u001b[0m         \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mabs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'score'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'score'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'-'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'score'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'score'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'-'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     83\u001b[0m         \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'previous_shots'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 84\u001b[0;31m         \u001b[0mprediction\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mestimate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'player'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mshot_type\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mPoint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     85\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'shot_made'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     86\u001b[0m             \u001b[0mpredicted_points\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mprediction\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-2-5e97609cae64>\u001b[0m in \u001b[0;36mestimate\u001b[0;34m(player_name, shottype, test)\u001b[0m\n\u001b[1;32m     67\u001b[0m     \u001b[0mx_max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mx\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmade_points\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mmissed_points\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     68\u001b[0m     \u001b[0my_max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0my\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmade_points\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mmissed_points\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 69\u001b[0;31m     \u001b[0mscale\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0my_max\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mx_max\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     70\u001b[0m     \u001b[0msample_size\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0.20\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmade\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmissed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     71\u001b[0m     \u001b[0mneighbours\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnearest_neighbours\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmade_points\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mmissed_points\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0msample_size\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mscale\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mZeroDivisionError\u001b[0m: division by zero"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "df = pd.read_csv('/kaggle/input/nba-free-throws/free_throws.csv')\n",
    "\n",
    "pm_counter = 0\n",
    "pm = {}\n",
    "pm_list = []\n",
    "new_df = df[df['play'].str.contains('1 of 1|1 of 2|1 of 3|2 of 2|2 of 3|3 of 3')]\n",
    "\n",
    "for s in new_df.itertuples():\n",
    "    unique_id = str(getattr(s, 'game_id'))+getattr(s, 'player')\n",
    "    pm_list.append(pm.get(unique_id, 0))\n",
    "    pm[unique_id] = pm.get(unique_id, 0) + 1\n",
    "\n",
    "new_df.insert(len(new_df.columns), \"previous_shots\", pm_list)\n",
    "\n",
    "class Point:\n",
    "    def __init__(self,x,y):\n",
    "        self.x = x\n",
    "        self.y = y\n",
    "    \n",
    "def estimate(player_name, shottype, test):      \n",
    "    made = []\n",
    "    missed = []\n",
    "    made_counter = 0\n",
    "    for row in new_df.itertuples():\n",
    "        if shottype in getattr(row, 'play') and getattr(row, 'player')==player_name:\n",
    "            if getattr(row, 'shot_made')==1:\n",
    "                made.append(row)\n",
    "                made_counter += 1\n",
    "            else:\n",
    "                missed.append(row)\n",
    "        \n",
    "    ratio = made_counter / (len(made)+len(missed))\n",
    "\n",
    "    x_made = [getattr(s, 'previous_shots') for s in made]\n",
    "    y_made = [abs(int(getattr(rows, 'score')[:getattr(rows, 'score').find('-')]) - int(getattr(rows, 'score')[getattr(rows, 'score').find('-')+1:])) for rows in made]\n",
    "    made_points = [Point(x,y) for x,y in zip(x_made,y_made)]\n",
    "    x_missed = [getattr(s, 'previous_shots') for s in missed]\n",
    "    y_missed = [abs(int(getattr(rows, 'score')[:getattr(rows, 'score').find('-')]) - int(getattr(rows, 'score')[getattr(rows, 'score').find('-')+1:])) for rows in missed]\n",
    "    missed_points = [Point(x,y) for x,y in zip(x_missed,y_missed)]\n",
    "\n",
    "    \"\"\"\n",
    "    fig = mpl.pyplot.figure()\n",
    "    ax = fig.add_subplot(1,1,1)\n",
    "    ax.scatter([p.x for p in made_points], [p.y for p in made_points], c=\"green\", alpha=\"0.5\", label=\"made\", edgecolors=\"none\", s=20)\n",
    "    ax.scatter([p.x for p in missed_points], [p.y for p in missed_points], c=\"red\", alpha=\"0.5\", label=\"missed\", edgecolors = \"none\", s=20)\n",
    "    mpl.pyplot.xlabel(\"Number of Free Throws Previously Shot\")\n",
    "    mpl.pyplot.ylabel(\"Point Differential\")\n",
    "    mpl.pyplot.title(player_name + \"Free Throws\")\n",
    "    mpl.pyplot.legend(loc=2)\n",
    "    mpl.pyplot.show()\"\"\"\n",
    "    \n",
    "    def distance(p1,p2,scale):\n",
    "        return pow(((p1.x-p2.x)*scale)**2+(p1.y-p2.y)**2,0.5)\n",
    "    \n",
    "    def nearest_neighbours(p,shots,num,scale):\n",
    "        return sorted(shots,key=lambda q: distance(p,q,scale))[:num]\n",
    "\n",
    "    def percentage(neighbours):\n",
    "        counter = 0\n",
    "        for n in neighbours:\n",
    "            if n in made_points:\n",
    "                counter += 1\n",
    "        return counter/len(neighbours)\n",
    "    \n",
    "    x_max = max([p.x for p in made_points+missed_points])\n",
    "    y_max = max([p.y for p in made_points+missed_points])\n",
    "    scale = y_max/x_max\n",
    "    sample_size = int(0.20*(len(made)+len(missed)))\n",
    "    neighbours = nearest_neighbours(test,made_points+missed_points,sample_size,scale)\n",
    "    return percentage(neighbours)\n",
    "\n",
    "testing_set = new_df.iloc[501000:]\n",
    "predicted_points = 0\n",
    "predicted_average = 0\n",
    "actual_points = 0\n",
    "ds_size = 0\n",
    "for row in testing_set.itertuples():\n",
    "    if \" of \" in getattr(row, 'play'):\n",
    "        shot_type = getattr(row, 'play')[getattr(row, 'play').find(\" of \")-1:getattr(row, 'play').find(\" of \")+5]\n",
    "        y = abs(int(getattr(row, 'score')[:getattr(row, 'score').find('-')]) - int(getattr(row, 'score')[getattr(row, 'score').find('-')+1:]))\n",
    "        x = getattr(row, 'previous_shots')\n",
    "        prediction = estimate(getattr(row, 'player'),shot_type,Point(x,y))\n",
    "        if getattr(row, 'shot_made')==1:\n",
    "            predicted_points += prediction\n",
    "            actual_points += 1\n",
    "        else:\n",
    "            predicted_points -= prediction\n",
    "            actual_points -= 1\n",
    "        ds_size += 1\n",
    "        predicted_average += prediction\n",
    "        print(predicted_points/(predicted_average/ds_size)/actual_points)\n",
    "\n",
    "\n",
    "        \n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "        \n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}