data_generation-2022.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3120e701-883f-4f64-8d41-f958fdb91a52",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mDEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\u001b[0m\n",
      "Collecting BeautifulSoup\n",
      "  Downloading BeautifulSoup-3.2.2.tar.gz (32 kB)\n",
      "  Preparing metadata (setup.py) ... \u001b[?25lerror\n",
      "\u001b[31m  ERROR: Command errored out with exit status 1:\n",
      "   command: /usr/local/opt/python@3.9/bin/python3.9 -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '\"'\"'/private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_c65708ed3fa541539235e94ca6d6041b/setup.py'\"'\"'; __file__='\"'\"'/private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_c65708ed3fa541539235e94ca6d6041b/setup.py'\"'\"';f = getattr(tokenize, '\"'\"'open'\"'\"', open)(__file__) if os.path.exists(__file__) else io.StringIO('\"'\"'from setuptools import setup; setup()'\"'\"');code = f.read().replace('\"'\"'\\r\\n'\"'\"', '\"'\"'\\n'\"'\"');f.close();exec(compile(code, __file__, '\"'\"'exec'\"'\"'))' egg_info --egg-base /private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-pip-egg-info-66qw_qum\n",
      "       cwd: /private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_c65708ed3fa541539235e94ca6d6041b/\n",
      "  Complete output (6 lines):\n",
      "  Traceback (most recent call last):\n",
      "    File \"<string>\", line 1, in <module>\n",
      "    File \"/private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_c65708ed3fa541539235e94ca6d6041b/setup.py\", line 3\n",
      "      \"You're trying to run a very old release of Beautiful Soup under Python 3. This will not work.\"<>\"Please use Beautiful Soup 4, available through the pip package 'beautifulsoup4'.\"\n",
      "                                                                                                     ^\n",
      "  SyntaxError: invalid syntax\n",
      "  ----------------------------------------\u001b[0m\n",
      "\u001b[33mWARNING: Discarding https://files.pythonhosted.org/packages/40/f2/6c9f2f3e696ee6a1fb0e4d7850617e224ed2b0b1e872110abffeca2a09d4/BeautifulSoup-3.2.2.tar.gz#sha256=a04169602bff6e3138b1259dbbf491f5a27f9499dea9a8fbafd48843f9d89970 (from https://pypi.org/simple/beautifulsoup/). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.\u001b[0m\n",
      "\u001b[?25h  Downloading BeautifulSoup-3.2.1.tar.gz (31 kB)\n",
      "  Preparing metadata (setup.py) ... \u001b[?25lerror\n",
      "\u001b[31m  ERROR: Command errored out with exit status 1:\n",
      "   command: /usr/local/opt/python@3.9/bin/python3.9 -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '\"'\"'/private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_9ad747411cfc445a8a8fe95646c4a584/setup.py'\"'\"'; __file__='\"'\"'/private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_9ad747411cfc445a8a8fe95646c4a584/setup.py'\"'\"';f = getattr(tokenize, '\"'\"'open'\"'\"', open)(__file__) if os.path.exists(__file__) else io.StringIO('\"'\"'from setuptools import setup; setup()'\"'\"');code = f.read().replace('\"'\"'\\r\\n'\"'\"', '\"'\"'\\n'\"'\"');f.close();exec(compile(code, __file__, '\"'\"'exec'\"'\"'))' egg_info --egg-base /private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-pip-egg-info-jaz6n7vz\n",
      "       cwd: /private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_9ad747411cfc445a8a8fe95646c4a584/\n",
      "  Complete output (6 lines):\n",
      "  Traceback (most recent call last):\n",
      "    File \"<string>\", line 1, in <module>\n",
      "    File \"/private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_9ad747411cfc445a8a8fe95646c4a584/setup.py\", line 22\n",
      "      print \"Unit tests have failed!\"\n",
      "            ^\n",
      "  SyntaxError: Missing parentheses in call to 'print'. Did you mean print(\"Unit tests have failed!\")?\n",
      "  ----------------------------------------\u001b[0m\n",
      "\u001b[33mWARNING: Discarding https://files.pythonhosted.org/packages/1e/ee/295988deca1a5a7accd783d0dfe14524867e31abb05b6c0eeceee49c759d/BeautifulSoup-3.2.1.tar.gz#sha256=6a8cb4401111e011b579c8c52a51cdab970041cc543814bbd9577a4529fe1cdb (from https://pypi.org/simple/beautifulsoup/). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.\u001b[0m\n",
      "\u001b[?25h  Downloading BeautifulSoup-3.2.0.tar.gz (31 kB)\n",
      "  Preparing metadata (setup.py) ... \u001b[?25lerror\n",
      "\u001b[31m  ERROR: Command errored out with exit status 1:\n",
      "   command: /usr/local/opt/python@3.9/bin/python3.9 -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '\"'\"'/private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_203c60400526459d953263f56cfc8bb3/setup.py'\"'\"'; __file__='\"'\"'/private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_203c60400526459d953263f56cfc8bb3/setup.py'\"'\"';f = getattr(tokenize, '\"'\"'open'\"'\"', open)(__file__) if os.path.exists(__file__) else io.StringIO('\"'\"'from setuptools import setup; setup()'\"'\"');code = f.read().replace('\"'\"'\\r\\n'\"'\"', '\"'\"'\\n'\"'\"');f.close();exec(compile(code, __file__, '\"'\"'exec'\"'\"'))' egg_info --egg-base /private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-pip-egg-info-1rvs39xe\n",
      "       cwd: /private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_203c60400526459d953263f56cfc8bb3/\n",
      "  Complete output (6 lines):\n",
      "  Traceback (most recent call last):\n",
      "    File \"<string>\", line 1, in <module>\n",
      "    File \"/private/var/folders/2q/sh3vf_jn6px9pnsjd6jm0gmw0000gt/T/pip-install-z9ntbs9s/beautifulsoup_203c60400526459d953263f56cfc8bb3/setup.py\", line 22\n",
      "      print \"Unit tests have failed!\"\n",
      "            ^\n",
      "  SyntaxError: Missing parentheses in call to 'print'. Did you mean print(\"Unit tests have failed!\")?\n",
      "  ----------------------------------------\u001b[0m\n",
      "\u001b[33mWARNING: Discarding https://files.pythonhosted.org/packages/33/fe/15326560884f20d792d3ffc7fe8f639aab88647c9d46509a240d9bfbb6b1/BeautifulSoup-3.2.0.tar.gz#sha256=0dc52d07516c1665c9dd9f0a390a7a054bfb7b147a50b2866fb116b8909dfd37 (from https://pypi.org/simple/beautifulsoup/). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.\u001b[0m\n",
      "\u001b[31mERROR: Could not find a version that satisfies the requirement BeautifulSoup (from versions: 3.2.0, 3.2.1, 3.2.2)\u001b[0m\n",
      "\u001b[31mERROR: No matching distribution found for BeautifulSoup\u001b[0m\n",
      "\u001b[?25hNote: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install bs4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "307210a2-9180-40ac-bfa7-6c8a465bd3cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mDEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\u001b[0m\n",
      "Collecting datetime\n",
      "  Downloading DateTime-4.3-py2.py3-none-any.whl (60 kB)\n",
      "     |████████████████████████████████| 60 kB 4.0 MB/s            \n",
      "\u001b[?25hCollecting zope.interface\n",
      "  Downloading zope.interface-5.4.0-cp39-cp39-macosx_10_14_x86_64.whl (208 kB)\n",
      "     |████████████████████████████████| 208 kB 1.4 MB/s            \n",
      "\u001b[?25hRequirement already satisfied: pytz in /usr/local/lib/python3.9/site-packages (from datetime) (2021.3)\n",
      "Requirement already satisfied: setuptools in /usr/local/lib/python3.9/site-packages (from zope.interface->datetime) (59.0.1)\n",
      "Installing collected packages: zope.interface, datetime\n",
      "\u001b[33m  DEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\u001b[0m\n",
      "\u001b[33mDEPRECATION: Configuring installation scheme with distutils config files is deprecated and will no longer work in the near future. If you are using a Homebrew or Linuxbrew Python, please see discussion at https://github.com/Homebrew/homebrew-core/issues/76621\u001b[0m\n",
      "Successfully installed datetime-4.3 zope.interface-5.4.0\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "75c7a169-2b2d-460e-8f6d-2b26f33b49c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "import requests\n",
    "import pprint\n",
    "from datetime import datetime\n",
    "\n",
    "import json\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "import datetime\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "59b6e6a1-24fc-4530-afd2-a4a02fb33459",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "team_abbreviations = {'Atlanta Hawks':'ATL', \n",
    "                      'Brooklyn Nets':'BKN',\n",
    "                      'Boston Celtics':'BOS',\n",
    "                      'Charlotte Hornets': 'CHA',\n",
    "                      'Chicago Bulls': 'CHI',\n",
    "                      'Cleveland Cavaliers': 'CLE',\n",
    "                      'Dallas Mavericks': 'DAL',\n",
    "                      'Denver Nuggets': 'DEN',\n",
    "                      'Detroit Pistons': 'DET',\n",
    "                      'Golden State Warriors': 'GSW',\n",
    "                      'Houston Rockets':'HOU',\n",
    "                      'Indiana Pacers': 'IND',\n",
    "                      'Los Angeles Clippers':'LAC',\n",
    "                      'Los Angeles Lakers': 'LAL',\n",
    "                      'Memphis Grizzlies': 'MEM',\n",
    "                      'Miami Heat': 'MIA',\n",
    "                      'Milwaukee Bucks':'MIL',\n",
    "                      'Minnesota Timberwolves':'MIN',\n",
    "                      'New Orleans Pelicans': 'NOP',\n",
    "                      'New York Knicks': 'NYK',\n",
    "                      'Oklahoma City Thunder': 'OKC',\n",
    "                      'Orlando Magic': 'ORL',\n",
    "                      'Philadelphia 76ers': 'PHI',\n",
    "                      'Phoenix Suns': 'PHX',\n",
    "                      'Portland Trail Blazers': 'POR',\n",
    "                      'Sacramento Kings': 'SAC',\n",
    "                      'San Antonio Spurs': 'SAS',\n",
    "                      'Toronto Raptors': 'TOR',\n",
    "                      'Utah Jazz' : 'UTA',\n",
    "                      'Washington Wizards':'WAS'}\n",
    "\n",
    "city_abbreviations = {'Atlanta':'Atlanta Hawks', \n",
    "                      'Brooklyn':'Brooklyn Nets',\n",
    "                      'Boston':'Boston Celtics',\n",
    "                      'Charlotte':'Charlotte Hornets',\n",
    "                      'Chicago':'Chicago Bulls',\n",
    "                      'Cleveland':'Cleveland Cavaliers',\n",
    "                      'Dallas':'Dallas Mavericks',\n",
    "                      'Denver':'Denver Nuggets',\n",
    "                      'Detroit':'Detroit Pistons',\n",
    "                      'Golden State':'Golden State Warriors',\n",
    "                      'Houston':'Houston Rockets',\n",
    "                      'Indiana':'Indiana Pacers',\n",
    "                      'LA Clippers':'Los Angeles Clippers',\n",
    "                      'LA Lakers':'Los Angeles Lakers',\n",
    "                      'Memphis':'Memphis Grizzlies',\n",
    "                      'Miami':'Miami Heat',\n",
    "                      'Milwaukee':'Milwaukee Bucks',\n",
    "                      'Minnesota':'Minnesota Timberwolves',\n",
    "                      'New Orleans':'New Orleans Pelicans',\n",
    "                      'New York':'New York Knicks',\n",
    "                      'Oklahoma City':'Oklahoma City Thunder',\n",
    "                      'Orlando': 'Orlando Magic',\n",
    "                      'Philadelphia':'Philadelphia 76ers',\n",
    "                      'Phoenix':'Phoenix Suns',\n",
    "                      'Portland':'Portland Trail Blazers',\n",
    "                      'Sacramento':'Sacramento Kings',\n",
    "                      'San Antonio':'San Antonio Spurs',\n",
    "                      'Toronto':'Toronto Raptors',\n",
    "                      'Utah':'Utah Jazz',\n",
    "                      'Washington':'Washington Wizards'}\n",
    "def get_team_name(bad_str, full_team):\n",
    "    if full_team:\n",
    "        return team_abbreviations[bad_str]\n",
    "    else:\n",
    "        full_team_name = city_abbreviations[bad_str]\n",
    "        return get_team_name(full_team_name, True)\n",
    "print('done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "f893a15a-6320-4a3a-b291-890d85f620cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\n",
      "2022\n",
      "0\n",
      "BOS\n",
      "1\n",
      "DEN\n",
      "2\n",
      "SAS\n",
      "3\n",
      "MIL\n",
      "4\n",
      "MIA\n",
      "5\n",
      "DAL\n",
      "6\n",
      "OKC\n",
      "7\n",
      "MEM\n",
      "8\n",
      "PHX\n",
      "9\n",
      "PHI\n",
      "10\n",
      "CHI\n",
      "11\n",
      "NOP\n",
      "12\n",
      "ATL\n",
      "13\n",
      "CLE\n",
      "14\n",
      "LAC\n",
      "15\n",
      "IND\n",
      "16\n",
      "UTA\n",
      "17\n",
      "LAL\n",
      "18\n",
      "HOU\n",
      "19\n",
      "GSW\n",
      "20\n",
      "TOR\n",
      "21\n",
      "DET\n",
      "22\n",
      "MIN\n",
      "23\n",
      "SAC\n",
      "24\n",
      "WAS\n",
      "25\n",
      "NYK\n",
      "26\n",
      "POR\n",
      "27\n",
      "BKN\n",
      "28\n",
      "ORL\n",
      "29\n",
      "CHA\n"
     ]
    }
   ],
   "source": [
    "'''\n",
    "Scrapes data from oddshark and adds it csv\n",
    "'''\n",
    "\n",
    "\n",
    "columns = ['Win %','avg margin of victory','home or away']\n",
    "\n",
    "all_data = {}\n",
    "\n",
    "\n",
    "for year in [2022]:\n",
    "    print('\\n'*2)\n",
    "    print(year)\n",
    "    for j in range(30):\n",
    "        print(j)\n",
    "        URL = 'https://www.oddsshark.com/stats/gamelog/basketball/nba/207'+str(22+j)+'/'+str(year)\n",
    "        page = requests.get(URL)\n",
    "\n",
    "        soup = BeautifulSoup(page.content,'html.parser')\n",
    "\n",
    "        #pprint.pprint(soup)\n",
    "        title_text = soup.find(id = 'page-title').text.split()\n",
    "        dash_index = title_text.index('-')\n",
    "        team = get_team_name(\" \".join(title_text[:dash_index]), True)\n",
    "\n",
    "        print(team)\n",
    "\n",
    "        results = soup.find(id='content')\n",
    "        \n",
    "        if results is None:\n",
    "            continue\n",
    "        games = results.find_all('tr')\n",
    "\n",
    "\n",
    "        \n",
    "        total_data = {'team':[], 'date':[],'wins':[],'losses':[], 'won by':[],'home or away':[],'spread':[],'won against spread':[],'opponent':[]}\n",
    "        for game in games:\n",
    "            data = game.find_all('td')\n",
    "            new_data = ['Date','Opponent','Game','Result','Score','ATS','Spread']\n",
    "            storage = {}\n",
    "            if data:\n",
    "                for i in range(len(new_data)):\n",
    "                    storage[new_data[i]] = data[i].text\n",
    "                \n",
    "                \n",
    "                if len(storage['Result']):\n",
    "                    \n",
    "                    date_str = storage['Date']\n",
    "                    split = date_str.split(' ')\n",
    "                    month_map = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']\n",
    "                    month_num = month_map.index(split[0])+1\n",
    "                    date_num = int(split[1][:-1])\n",
    "                    year_num = int(split[2])\n",
    "\n",
    "                    date = datetime(year_num, month_num, date_num)\n",
    "                    \n",
    "                    total_data['date'].append(date)\n",
    "\n",
    "                    game_opp = storage['Opponent'].split()\n",
    "                    if '@' in game_opp[0]:\n",
    "                        home = 0\n",
    "                    else: home = 1\n",
    "\n",
    "                    opp_city = \" \".join(game_opp[1:])\n",
    "                    opponent = get_team_name(opp_city, False)\n",
    "\n",
    "                    spread = eval(storage['Spread'])\n",
    "                    \n",
    "                    \n",
    "                    total_data['team'].append(team)\n",
    "\n",
    "                    if str(storage['ATS'])== 'W':\n",
    "                        ATS = 1\n",
    "                    else: ATS = 0\n",
    "                    total_data['won against spread'].append(ATS)\n",
    "\n",
    "                   \n",
    "                    total_data['home or away'].append(home)\n",
    "                    \n",
    "                    total_data['opponent'].append(opponent)\n",
    "                        \n",
    "                    won_by = eval(storage['Score'])\n",
    "                    total_data['won by'].append(won_by)\n",
    "\n",
    "                    result = storage['Result']\n",
    "                    try:\n",
    "                        num_wins = total_data['wins'][-1]\n",
    "                        num_loss = total_data['losses'][-1]\n",
    "                    except:\n",
    "                        num_wins = 0\n",
    "                        num_loss = 0\n",
    "\n",
    "                    if result == 'W':\n",
    "                        total_data['wins'].append(num_wins+1)\n",
    "                        total_data['losses'].append(num_loss)\n",
    "                    else:\n",
    "                        total_data['wins'].append(num_wins)\n",
    "                        total_data['losses'].append(num_loss+1)\n",
    "\n",
    "                    \n",
    "                    total_data['spread'].append(spread)\n",
    "                \n",
    "                else:\n",
    "                    break\n",
    "\n",
    "            \n",
    "\n",
    "\n",
    "        formatted_data = {}    \n",
    "        win_percentage = []\n",
    "        win_percentage_5 = []\n",
    "        avg_margin = []\n",
    "        avg_margin_5 = []\n",
    "        num_games = len(total_data['wins'])\n",
    "        for i in range(num_games):\n",
    "            wins = total_data['wins'][i]\n",
    "            losses = total_data['losses'][i]\n",
    "\n",
    "            win_percentage.append(float(wins)/(wins+losses))\n",
    "\n",
    "            if i<5:\n",
    "                wins_5 = 0\n",
    "                losses_5 = 0\n",
    "                avg_margin_5games = 0\n",
    "            else:\n",
    "                wins_5 = total_data['wins'][i-5]\n",
    "                loss_5 = total_data['losses'][i-5]\n",
    "                avg_margin_5games = avg_margin[i-5]\n",
    "            \n",
    "            last_5_games_wins =  wins-wins_5\n",
    "            last_5_games_losses = losses-losses_5\n",
    "            last_5_games_win_percent =float(last_5_games_wins)/(last_5_games_wins+last_5_games_losses)\n",
    "            win_percentage_5.append(last_5_games_win_percent)\n",
    "\n",
    "            margin = sum(total_data['won by'][:i+1])/float(i+1)\n",
    "            avg_margin.append(margin)\n",
    "\n",
    "            avg_margin_5.append(margin-avg_margin_5games)\n",
    "\n",
    "\n",
    "        formatted_data['win_percentage_5'] = win_percentage_5\n",
    "        formatted_data['win_percentage'] = win_percentage\n",
    "        formatted_data['avg_margin_5'] = avg_margin_5\n",
    "        formatted_data['avg_margin'] = avg_margin\n",
    "        formatted_data['home_or_away'] = total_data['home or away']\n",
    "        formatted_data['spread'] = total_data['spread']\n",
    "        formatted_data['beat_spread'] = total_data['won against spread']\n",
    "        formatted_data['opponent'] = total_data['opponent']\n",
    "        formatted_data['date'] = total_data['date']\n",
    "        all_data[team] = formatted_data\n",
    "\n",
    "    def myconverter(o):\n",
    "        if isinstance(o, datetime):\n",
    "            return o.__str__()\n",
    "    with open(\"scraped-team-data/nba_team_\"+str(year)+\".json\", \"w\") as outfile:  \n",
    "        json.dump(all_data, outfile,default = my_converter, indent=4) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "9a10c82e-169d-4d5d-bf51-46dfb020df1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def my_converter(o):\n",
    "    if isinstance(o, datetime):\n",
    "        return o.__str__()\n",
    "with open(\"scraped-team-data/nba_team_\"+str(year)+\".json\", \"w\") as outfile:  \n",
    "    json.dump(all_data, outfile,default = my_converter, indent=4) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "0e758f15-fdcc-4d61-8d49-5c266a5fb82f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2022\n"
     ]
    }
   ],
   "source": [
    "\n",
    "import pandas as pd\n",
    "\n",
    "\n",
    "data_frames = []\n",
    "\n",
    "for year in [2022]: \n",
    "    print(year)\n",
    "    data = None\n",
    "    with open(\"scraped-team-data/nba_team_\"+str(year)+\".json\", \"r\") as f:  \n",
    "        data = json.load(f)\n",
    "\n",
    "    new_data = {}\n",
    "\n",
    "    mini_data_frames = []\n",
    "\n",
    "    for team, values in data.items():\n",
    "        \n",
    "        mini_data = values.copy()\n",
    "        \n",
    "        num_games = len(values['win_percentage'])\n",
    "\n",
    "        opp_win_percentage_5  = []\n",
    "        opp_win_percentage = []\n",
    "        opp_avg_margin_5 = []\n",
    "        opp_avg_margin = []\n",
    "        \n",
    "\n",
    "        for i in range(num_games):\n",
    "            \n",
    "            date = mini_data['date'][i]\n",
    "            opponent = values['opponent'][i]\n",
    "            opp_values = data[opponent]\n",
    "            opp_index = opp_values['date'].index(date)\n",
    "            opp_win_percentage_5.append(opp_values['win_percentage_5'][opp_index])\n",
    "            opp_win_percentage.append(opp_values['win_percentage'][opp_index])\n",
    "            opp_avg_margin_5.append(opp_values['avg_margin_5'][opp_index])\n",
    "            opp_avg_margin.append(opp_values['avg_margin'][opp_index])\n",
    "\n",
    "        mini_data['opp_win_percentage_5'] = opp_win_percentage_5\n",
    "        mini_data['opp_win_percentage'] = opp_win_percentage\n",
    "        mini_data['opp_avg_margin_5'] = opp_avg_margin_5\n",
    "        mini_data['opp_avg_margin'] = opp_avg_margin\n",
    "        \n",
    "\n",
    "        mini_data.pop('opponent')\n",
    "\n",
    "        mini_data_frames.append(pd.DataFrame.from_dict(mini_data))\n",
    "    \n",
    "    \n",
    "    data_frames.append(pd.concat(mini_data_frames))\n",
    "\n",
    "\n",
    "all_data = pd.concat(data_frames)\n",
    "\n",
    "with open('2022_data.csv', 'w') as train:\n",
    "    all_data.to_csv(train)\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "e5f971db-e4f1-405b-9956-2521a9294d71",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1108\n"
     ]
    }
   ],
   "source": [
    "\n",
    "training_data = pd.read_csv('2022_data.csv')\n",
    "print(training_data.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7993de4f-b8db-4b53-9503-034a8d11b461",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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