testing_api.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ScoreBoardDate: 2022-10-24\n",
      "0022200044: Pacers vs. 76ers @ 2022-10-24 19:00:00-04:00\n",
      "0022200045: Raptors vs. Heat @ 2022-10-24 19:30:00-04:00\n",
      "0022200046: Magic vs. Knicks @ 2022-10-24 19:30:00-04:00\n",
      "0022200047: Celtics vs. Bulls @ 2022-10-24 20:00:00-04:00\n",
      "0022200048: Jazz vs. Rockets @ 2022-10-24 20:00:00-04:00\n",
      "0022200049: Nets vs. Grizzlies @ 2022-10-24 20:00:00-04:00\n",
      "0022200050: Spurs vs. Timberwolves @ 2022-10-24 20:00:00-04:00\n",
      "0022200051: Nuggets vs. Trail Blazers @ 2022-10-24 22:00:00-04:00\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime, timezone\n",
    "from dateutil import parser\n",
    "from nba_api.live.nba.endpoints import scoreboard\n",
    "\n",
    "f = \"{gameId}: {awayTeam} vs. {homeTeam} @ {gameTimeLTZ}\" \n",
    "\n",
    "board = scoreboard.ScoreBoard()\n",
    "print(\"ScoreBoardDate: \" + board.score_board_date)\n",
    "games = board.games.get_dict()\n",
    "for game in games:\n",
    "    gameTimeLTZ = parser.parse(game[\"gameTimeUTC\"]).replace(tzinfo=timezone.utc).astimezone(tz=None)\n",
    "    print(f.format(gameId=game['gameId'], awayTeam=game['awayTeam']['teamName'], homeTeam=game['homeTeam']['teamName'], gameTimeLTZ=gameTimeLTZ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'str' object has no attribute 'show'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[0;32mIn [14], line 22\u001b[0m\n\u001b[1;32m     19\u001b[0m values \u001b[39m=\u001b[39m [\u001b[39mround\u001b[39m(row, \u001b[39m2\u001b[39m) \u001b[39mfor\u001b[39;00m row \u001b[39min\u001b[39;00m career[\u001b[39m'\u001b[39m\u001b[39mPPG\u001b[39m\u001b[39m'\u001b[39m]]\n\u001b[1;32m     20\u001b[0m plot_div \u001b[39m=\u001b[39m plot([Scatter(x\u001b[39m=\u001b[39mseason, y\u001b[39m=\u001b[39mvalues,\n\u001b[1;32m     21\u001b[0m                 mode\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mlines\u001b[39m\u001b[39m'\u001b[39m, name\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mPPG by Season\u001b[39m\u001b[39m'\u001b[39m, opacity\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m, marker_color\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mred\u001b[39m\u001b[39m'\u001b[39m)], output_type\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mdiv\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m---> 22\u001b[0m plot_div\u001b[39m.\u001b[39;49mshow()\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'str' object has no attribute 'show'"
     ]
    }
   ],
   "source": [
    "from nba_api.stats.endpoints import playercareerstats\n",
    "import pandas\n",
    "import numpy\n",
    "from plotly.offline import plot\n",
    "from plotly.graph_objs import Scatter\n",
    "#for a player like nikola jokic\n",
    "career = playercareerstats.PlayerCareerStats(player_id='203999').get_data_frames()[0]\n",
    "career = pandas.DataFrame(career)\n",
    "career.pop(\"PLAYER_ID\")\n",
    "career.pop(\"TEAM_ID\")\n",
    "career.pop(\"LEAGUE_ID\")\n",
    "career.columns=['Season', 'Team', 'Age', 'GP', 'GS', 'Min', 'FGM', 'FGA', 'FG_PCT', 'FG3M', 'FG3A', 'FG3_PCT', 'FTM', 'FTA',\n",
    "       'FT_PCT', 'OREB', 'DREB', 'REB', 'AST', 'STL', 'BLK', 'TOV', 'PF','PTS']\n",
    "ppg = []\n",
    "for i in range(len(career['PTS'])):\n",
    "       ppg+=[career['PTS'][i]/career['GP'][i]]\n",
    "career['PPG']=ppg\n",
    "season = [row for row in career['Season']]\n",
    "values = [round(row, 2) for row in career['PPG']]\n",
    "plot_div = plot([Scatter(x=season, y=values,\n",
    "                mode='lines', name='PPG by Season', opacity=1, marker_color='red')], output_type='div')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'id': 1628369,\n",
       "  'full_name': 'Jayson Tatum',\n",
       "  'first_name': 'Jayson',\n",
       "  'last_name': 'Tatum',\n",
       "  'is_active': True}]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from nba_api.stats.static import players\n",
    "player_list = players.find_players_by_full_name('Jayson Tatum')\n",
    "player_list\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PLAYER_ID</th>\n",
       "      <th>SEASON_ID</th>\n",
       "      <th>LEAGUE_ID</th>\n",
       "      <th>TEAM_ID</th>\n",
       "      <th>TEAM_ABBREVIATION</th>\n",
       "      <th>PLAYER_AGE</th>\n",
       "      <th>GP</th>\n",
       "      <th>GS</th>\n",
       "      <th>MIN</th>\n",
       "      <th>FGM</th>\n",
       "      <th>...</th>\n",
       "      <th>FT_PCT</th>\n",
       "      <th>OREB</th>\n",
       "      <th>DREB</th>\n",
       "      <th>REB</th>\n",
       "      <th>AST</th>\n",
       "      <th>STL</th>\n",
       "      <th>BLK</th>\n",
       "      <th>TOV</th>\n",
       "      <th>PF</th>\n",
       "      <th>PTS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>203999</td>\n",
       "      <td>2015-16</td>\n",
       "      <td>00</td>\n",
       "      <td>1610612743</td>\n",
       "      <td>DEN</td>\n",
       "      <td>21.0</td>\n",
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       "      <td>55</td>\n",
       "      <td>1733.0</td>\n",
       "      <td>307</td>\n",
       "      <td>...</td>\n",
       "      <td>0.811</td>\n",
       "      <td>181</td>\n",
       "      <td>379</td>\n",
       "      <td>560</td>\n",
       "      <td>189</td>\n",
       "      <td>79</td>\n",
       "      <td>50</td>\n",
       "      <td>104</td>\n",
       "      <td>208</td>\n",
       "      <td>796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>203999</td>\n",
       "      <td>2016-17</td>\n",
       "      <td>00</td>\n",
       "      <td>1610612743</td>\n",
       "      <td>DEN</td>\n",
       "      <td>22.0</td>\n",
       "      <td>73</td>\n",
       "      <td>59</td>\n",
       "      <td>2038.0</td>\n",
       "      <td>494</td>\n",
       "      <td>...</td>\n",
       "      <td>0.825</td>\n",
       "      <td>212</td>\n",
       "      <td>506</td>\n",
       "      <td>718</td>\n",
       "      <td>359</td>\n",
       "      <td>61</td>\n",
       "      <td>55</td>\n",
       "      <td>171</td>\n",
       "      <td>214</td>\n",
       "      <td>1221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>203999</td>\n",
       "      <td>2017-18</td>\n",
       "      <td>00</td>\n",
       "      <td>1610612743</td>\n",
       "      <td>DEN</td>\n",
       "      <td>23.0</td>\n",
       "      <td>75</td>\n",
       "      <td>73</td>\n",
       "      <td>2443.0</td>\n",
       "      <td>504</td>\n",
       "      <td>...</td>\n",
       "      <td>0.850</td>\n",
       "      <td>195</td>\n",
       "      <td>608</td>\n",
       "      <td>803</td>\n",
       "      <td>458</td>\n",
       "      <td>90</td>\n",
       "      <td>61</td>\n",
       "      <td>210</td>\n",
       "      <td>212</td>\n",
       "      <td>1385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>203999</td>\n",
       "      <td>2018-19</td>\n",
       "      <td>00</td>\n",
       "      <td>1610612743</td>\n",
       "      <td>DEN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>2504.0</td>\n",
       "      <td>616</td>\n",
       "      <td>...</td>\n",
       "      <td>0.821</td>\n",
       "      <td>228</td>\n",
       "      <td>637</td>\n",
       "      <td>865</td>\n",
       "      <td>580</td>\n",
       "      <td>108</td>\n",
       "      <td>55</td>\n",
       "      <td>248</td>\n",
       "      <td>228</td>\n",
       "      <td>1604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>203999</td>\n",
       "      <td>2019-20</td>\n",
       "      <td>00</td>\n",
       "      <td>1610612743</td>\n",
       "      <td>DEN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>73</td>\n",
       "      <td>73</td>\n",
       "      <td>2335.0</td>\n",
       "      <td>565</td>\n",
       "      <td>...</td>\n",
       "      <td>0.817</td>\n",
       "      <td>166</td>\n",
       "      <td>545</td>\n",
       "      <td>711</td>\n",
       "      <td>512</td>\n",
       "      <td>85</td>\n",
       "      <td>44</td>\n",
       "      <td>226</td>\n",
       "      <td>222</td>\n",
       "      <td>1456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>203999</td>\n",
       "      <td>2020-21</td>\n",
       "      <td>00</td>\n",
       "      <td>1610612743</td>\n",
       "      <td>DEN</td>\n",
       "      <td>26.0</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>2488.0</td>\n",
       "      <td>732</td>\n",
       "      <td>...</td>\n",
       "      <td>0.868</td>\n",
       "      <td>205</td>\n",
       "      <td>575</td>\n",
       "      <td>780</td>\n",
       "      <td>599</td>\n",
       "      <td>95</td>\n",
       "      <td>48</td>\n",
       "      <td>222</td>\n",
       "      <td>192</td>\n",
       "      <td>1898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>203999</td>\n",
       "      <td>2021-22</td>\n",
       "      <td>00</td>\n",
       "      <td>1610612743</td>\n",
       "      <td>DEN</td>\n",
       "      <td>27.0</td>\n",
       "      <td>74</td>\n",
       "      <td>74</td>\n",
       "      <td>2476.0</td>\n",
       "      <td>764</td>\n",
       "      <td>...</td>\n",
       "      <td>0.810</td>\n",
       "      <td>206</td>\n",
       "      <td>813</td>\n",
       "      <td>1019</td>\n",
       "      <td>584</td>\n",
       "      <td>109</td>\n",
       "      <td>63</td>\n",
       "      <td>281</td>\n",
       "      <td>191</td>\n",
       "      <td>2004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>203999</td>\n",
       "      <td>2022-23</td>\n",
       "      <td>00</td>\n",
       "      <td>1610612743</td>\n",
       "      <td>DEN</td>\n",
       "      <td>27.0</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>376.0</td>\n",
       "      <td>99</td>\n",
       "      <td>...</td>\n",
       "      <td>0.875</td>\n",
       "      <td>20</td>\n",
       "      <td>97</td>\n",
       "      <td>117</td>\n",
       "      <td>102</td>\n",
       "      <td>16</td>\n",
       "      <td>8</td>\n",
       "      <td>39</td>\n",
       "      <td>35</td>\n",
       "      <td>262</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   PLAYER_ID SEASON_ID LEAGUE_ID     TEAM_ID TEAM_ABBREVIATION  PLAYER_AGE  \\\n",
       "0     203999   2015-16        00  1610612743               DEN        21.0   \n",
       "1     203999   2016-17        00  1610612743               DEN        22.0   \n",
       "2     203999   2017-18        00  1610612743               DEN        23.0   \n",
       "3     203999   2018-19        00  1610612743               DEN        24.0   \n",
       "4     203999   2019-20        00  1610612743               DEN        25.0   \n",
       "5     203999   2020-21        00  1610612743               DEN        26.0   \n",
       "6     203999   2021-22        00  1610612743               DEN        27.0   \n",
       "7     203999   2022-23        00  1610612743               DEN        27.0   \n",
       "\n",
       "   GP  GS     MIN  FGM  ...  FT_PCT  OREB  DREB   REB  AST  STL  BLK  TOV  \\\n",
       "0  80  55  1733.0  307  ...   0.811   181   379   560  189   79   50  104   \n",
       "1  73  59  2038.0  494  ...   0.825   212   506   718  359   61   55  171   \n",
       "2  75  73  2443.0  504  ...   0.850   195   608   803  458   90   61  210   \n",
       "3  80  80  2504.0  616  ...   0.821   228   637   865  580  108   55  248   \n",
       "4  73  73  2335.0  565  ...   0.817   166   545   711  512   85   44  226   \n",
       "5  72  72  2488.0  732  ...   0.868   205   575   780  599   95   48  222   \n",
       "6  74  74  2476.0  764  ...   0.810   206   813  1019  584  109   63  281   \n",
       "7  12  12   376.0   99  ...   0.875    20    97   117  102   16    8   39   \n",
       "\n",
       "    PF   PTS  \n",
       "0  208   796  \n",
       "1  214  1221  \n",
       "2  212  1385  \n",
       "3  228  1604  \n",
       "4  222  1456  \n",
       "5  192  1898  \n",
       "6  191  2004  \n",
       "7   35   262  \n",
       "\n",
       "[8 rows x 27 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from nba_api.stats.endpoints import playercareerstats\n",
    "import pandas\n",
    "import numpy\n",
    "from plotly.offline import plot\n",
    "from plotly.graph_objs import Scatter\n",
    "#for a player like nikola jokic\n",
    "career = playercareerstats.PlayerCareerStats(player_id='203999').get_data_frames()[0]\n",
    "career = pandas.DataFrame(career)\n",
    "career\n",
    "# career.pop(\"PLAYER_ID\")\n",
    "# career.pop(\"TEAM_ID\")\n",
    "# career.pop(\"LEAGUE_ID\")\n",
    "# career.columns=['Season', 'Team', 'Age', 'GP', 'GS', 'Min', 'FGM', 'FGA', 'FG_PCT', 'FG3M', 'FG3A', 'FG3_PCT', 'FTM', 'FTA',\n",
    "#        'FT_PCT', 'OREB', 'DREB', 'REB', 'AST', 'STL', 'BLK', 'TOV', 'PF','PTS']\n",
    "# ppg = []\n",
    "# tov = []\n",
    "# for i in range(len(career['PTS'])):\n",
    "#        ppg+=[career['PTS'][i]/career['GP'][i]]\n",
    "#        tov += [round(career['TOV'][i]/career['GP'][i], 2)]\n",
    "\n",
    "# career['TOV'] = tov\n",
    "# career['TOV']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://nba-players.herokuapp.com/players/Tatum/Jayson'"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = \"Jayson Tatum\"\n",
    "first_name = res.split(\" \")[:1][0]\n",
    "last_name = res.split(\" \")[1:][0]\n",
    "string = f\"https://nba-players.herokuapp.com/players/{last_name}/{first_name}\"\n",
    "string"
   ]
  }
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