{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import os\n",
    "from pandas.io.json import json_normalize\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Arc, Rectangle, ConnectionPatch\n",
    "from matplotlib.offsetbox import  OffsetImage\n",
    "#import squarify\n",
    "from functools import reduce\n",
    "path = \"/home/kirugulige/Documents/Football-Analytics/open-data-master/data/events/\"\n",
    "Xg_req = pd.DataFrame(data=None)\n",
    "filename = '69275.json'    \n",
    "with open(\"%s\" % path + filename,encoding=\"utf8\") as data_file:    \n",
    "    data = json.load(data_file)\n",
    "    df = pd.DataFrame(data=None)\n",
    "        \n",
    "    df = json_normalize(data, sep = \"_\")\n",
    "        \n",
    "        #df =  df[(df['type_name'] == \"Shot\")]\n",
    "        #df = df.loc[:,['location','shot_body_part_id','shot_end_location','shot_one_on_one','shot_technique_id','shot_type_id','under_pressure','shot_outcome_id']]\n",
    "        #print(df.shape)\n",
    "Xg_req = Xg_req.append(df,ignore_index=True,sort=False)\n",
    "        #df.drop(df.index, inplace=True)\n",
    "        \n",
    "print(\"done\")\n",
    "df = Xg_req"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "through_ball = df.query('pass_through_ball == True')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "assist = df.query('pass_goal_assist == True')\n",
    "print(len(assist.index))\n",
    "goal = assist.query('shot_outcome_id == 97')\n",
    "#assist = df.query('pass_goal_assist == True')\n",
    "print(len(goal.index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>period</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>location</th>\n",
       "      <th>pass_end_location</th>\n",
       "      <th>pass_recipient_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>1f6ef40d-cd32-4566-add6-f1558833d0c1</td>\n",
       "      <td>1</td>\n",
       "      <td>00:05:57.827</td>\n",
       "      <td>[81.5, 37.8]</td>\n",
       "      <td>[103.1, 33.4]</td>\n",
       "      <td>Pablo Daniel Osvaldo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>604</th>\n",
       "      <td>4040c0ab-d934-469b-84f5-c595213b851b</td>\n",
       "      <td>1</td>\n",
       "      <td>00:13:56.420</td>\n",
       "      <td>[48.2, 57.4]</td>\n",
       "      <td>[85.5, 38.3]</td>\n",
       "      <td>Pablo Daniel Osvaldo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>794</th>\n",
       "      <td>7dbe04a8-41c5-4ea8-bfa1-892fe23a72e6</td>\n",
       "      <td>1</td>\n",
       "      <td>00:18:30.829</td>\n",
       "      <td>[66.8, 46.7]</td>\n",
       "      <td>[93.5, 38.5]</td>\n",
       "      <td>Pedro Eliezer Rodríguez Ledesma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840</th>\n",
       "      <td>3a7da0a1-e9c4-40a1-9702-e99c5ace03c2</td>\n",
       "      <td>1</td>\n",
       "      <td>00:20:46.623</td>\n",
       "      <td>[66.0, 56.5]</td>\n",
       "      <td>[105.5, 34.7]</td>\n",
       "      <td>José María Callejón Bueno</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>962</th>\n",
       "      <td>2bc53e64-664a-4f83-9d0c-6b046d91a7d9</td>\n",
       "      <td>1</td>\n",
       "      <td>00:23:55.494</td>\n",
       "      <td>[81.5, 28.1]</td>\n",
       "      <td>[94.2, 31.7]</td>\n",
       "      <td>David Villa Sánchez</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       id  period     timestamp      location  \\\n",
       "280  1f6ef40d-cd32-4566-add6-f1558833d0c1       1  00:05:57.827  [81.5, 37.8]   \n",
       "604  4040c0ab-d934-469b-84f5-c595213b851b       1  00:13:56.420  [48.2, 57.4]   \n",
       "794  7dbe04a8-41c5-4ea8-bfa1-892fe23a72e6       1  00:18:30.829  [66.8, 46.7]   \n",
       "840  3a7da0a1-e9c4-40a1-9702-e99c5ace03c2       1  00:20:46.623  [66.0, 56.5]   \n",
       "962  2bc53e64-664a-4f83-9d0c-6b046d91a7d9       1  00:23:55.494  [81.5, 28.1]   \n",
       "\n",
       "    pass_end_location              pass_recipient_name  \n",
       "280     [103.1, 33.4]             Pablo Daniel Osvaldo  \n",
       "604      [85.5, 38.3]             Pablo Daniel Osvaldo  \n",
       "794      [93.5, 38.5]  Pedro Eliezer Rodríguez Ledesma  \n",
       "840     [105.5, 34.7]        José María Callejón Bueno  \n",
       "962      [94.2, 31.7]              David Villa Sánchez  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "through_ball= through_ball[[\"id\", \"period\", \"timestamp\", \"location\", \"pass_end_location\", \"pass_recipient_name\"]]\n",
    "through_ball.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>period</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>location</th>\n",
       "      <th>pass_end_location</th>\n",
       "      <th>pass_recipient_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>794</th>\n",
       "      <td>7dbe04a8-41c5-4ea8-bfa1-892fe23a72e6</td>\n",
       "      <td>1</td>\n",
       "      <td>00:18:30.829</td>\n",
       "      <td>[66.8, 46.7]</td>\n",
       "      <td>[93.5, 38.5]</td>\n",
       "      <td>Pedro Eliezer Rodríguez Ledesma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2436</th>\n",
       "      <td>9810ac65-15b8-4736-a09e-08f7faaff01d</td>\n",
       "      <td>2</td>\n",
       "      <td>00:17:04.830</td>\n",
       "      <td>[52.7, 63.4]</td>\n",
       "      <td>[84.2, 57.1]</td>\n",
       "      <td>Pablo Daniel Osvaldo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2935</th>\n",
       "      <td>7269b3a6-43d7-45bc-8823-bcfd1542ad45</td>\n",
       "      <td>2</td>\n",
       "      <td>00:30:03.492</td>\n",
       "      <td>[64.4, 33.8]</td>\n",
       "      <td>[79.4, 25.5]</td>\n",
       "      <td>David Villa Sánchez</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3344</th>\n",
       "      <td>dc1b453d-6e7e-49b1-ad88-79525e8223f9</td>\n",
       "      <td>2</td>\n",
       "      <td>00:38:47.689</td>\n",
       "      <td>[70.1, 30.6]</td>\n",
       "      <td>[98.0, 23.3]</td>\n",
       "      <td>David Villa Sánchez</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        id  period     timestamp  \\\n",
       "794   7dbe04a8-41c5-4ea8-bfa1-892fe23a72e6       1  00:18:30.829   \n",
       "2436  9810ac65-15b8-4736-a09e-08f7faaff01d       2  00:17:04.830   \n",
       "2935  7269b3a6-43d7-45bc-8823-bcfd1542ad45       2  00:30:03.492   \n",
       "3344  dc1b453d-6e7e-49b1-ad88-79525e8223f9       2  00:38:47.689   \n",
       "\n",
       "          location pass_end_location              pass_recipient_name  \n",
       "794   [66.8, 46.7]      [93.5, 38.5]  Pedro Eliezer Rodríguez Ledesma  \n",
       "2436  [52.7, 63.4]      [84.2, 57.1]             Pablo Daniel Osvaldo  \n",
       "2935  [64.4, 33.8]      [79.4, 25.5]              David Villa Sánchez  \n",
       "3344  [70.1, 30.6]      [98.0, 23.3]              David Villa Sánchez  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "assist= assist[[\"id\", \"period\", \"timestamp\", \"location\", \"pass_end_location\", \"pass_recipient_name\"]]\n",
    "assist.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_pitch(ax):\n",
    "    # focus on only half of the pitch\n",
    "    #Pitch Outline & Centre Line\n",
    "    Pitch = Rectangle([0,0], width = 120, height = 80, fill = False)\n",
    "    #Left, Right Penalty Area and midline\n",
    "    LeftPenalty = Rectangle([0,22.3], width = 14.6, height = 35.3, fill = False)\n",
    "    RightPenalty = Rectangle([105.4,22.3], width = 14.6, height = 35.3, fill = False)\n",
    "    midline = ConnectionPatch([60,0], [60,80], \"data\", \"data\")\n",
    "\n",
    "    #Left, Right 6-yard Box\n",
    "    LeftSixYard = Rectangle([0,32], width = 4.9, height = 16, fill = False)\n",
    "    RightSixYard = Rectangle([115.1,32], width = 4.9, height = 16, fill = False)\n",
    "\n",
    "\n",
    "    #Prepare Circles\n",
    "    centreCircle = plt.Circle((60,40),8.1,color=\"black\", fill = False)\n",
    "    centreSpot = plt.Circle((60,40),0.71,color=\"black\")\n",
    "    #Penalty spots and Arcs around penalty boxes\n",
    "    leftPenSpot = plt.Circle((9.7,40),0.71,color=\"black\")\n",
    "    rightPenSpot = plt.Circle((110.3,40),0.71,color=\"black\")\n",
    "    leftArc = Arc((9.7,40),height=16.2,width=16.2,angle=0,theta1=310,theta2=50,color=\"black\")\n",
    "    rightArc = Arc((110.3,40),height=16.2,width=16.2,angle=0,theta1=130,theta2=230,color=\"black\")\n",
    "    \n",
    "    element = [Pitch, LeftPenalty, RightPenalty, midline, LeftSixYard, RightSixYard, centreCircle, \n",
    "               centreSpot, rightPenSpot, leftPenSpot, leftArc, rightArc]\n",
    "    for i in element:\n",
    "        ax.add_patch(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure() #set up the figures\n",
    "fig.set_size_inches(12, 8)\n",
    "ax=fig.add_subplot(1,1,1)\n",
    "ax.set_facecolor('grey')\n",
    "draw_pitch(ax) #overlay our different objects on the pitch\n",
    "plt.ylim(-2, 82)\n",
    "plt.xlim(-2, 122)\n",
    "#plt.plot(x_axis,y_axis,'ro')\n",
    "#plt.plot(x,y,'bo')\n",
    "#plt.axis('off')\n",
    "\n",
    "for i in range(len(through_ball)):\n",
    "    x = through_ball.iloc[i]['pass_end_location'][0]\n",
    "    y = through_ball.iloc[i]['pass_end_location'][1]\n",
    "    xe = through_ball.iloc[i]['location'][0]\n",
    "    ye = through_ball.iloc[i]['location'][0]\n",
    "    ax.scatter(x,y,color=\"red\",edgecolors=\"black\",zorder=10,alpha=1)\n",
    "    ax.plot([x,xe],[y,ye],zorder=11,alpha=1,color=\"black\")\n",
    "\n",
    "\"\"\"\n",
    "for i in range(len(assist)):\n",
    "    # annotate draw an arrow from a current position to pass_end_location\n",
    "    ax.annotate(\"\", xy = (assist.iloc[i]['pass_end_location'][0], assist.iloc[i]['pass_end_location'][1]), xycoords = 'data',\n",
    "               xytext = (assist.iloc[i]['location'][0], assist.iloc[i]['location'][1]), textcoords = 'data',\n",
    "               arrowprops=dict(arrowstyle=\"->\",connectionstyle=\"arc3\", color = \"red\"),)\n",
    "\"\"\"\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure() #set up the figures\n",
    "fig.set_size_inches(12, 8)\n",
    "ax=fig.add_subplot(1,1,1)\n",
    "ax.set_facecolor('grey')\n",
    "draw_pitch(ax) #overlay our different objects on the pitch\n",
    "plt.ylim(-2, 82)\n",
    "plt.xlim(-2, 122)\n",
    "#plt.plot(x_axis,y_axis,'ro')\n",
    "#plt.plot(x,y,'bo')\n",
    "#plt.axis('off')\n",
    "\n",
    "for i in range(len(assist)):\n",
    "    x = assist.iloc[i]['pass_end_location'][0]\n",
    "    y = assist.iloc[i]['pass_end_location'][1]\n",
    "    xe = assist.iloc[i]['location'][0]\n",
    "    ye = assist.iloc[i]['location'][0]\n",
    "    ax.scatter(x,y,color=\"red\",edgecolors=\"black\",zorder=10,alpha=1)\n",
    "    ax.plot([x,xe],[y,ye],zorder=11,alpha=1,color=\"black\")\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "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",
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