403 lines
43 KiB
Plaintext
403 lines
43 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"done\n"
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]
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}
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],
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"source": [
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"import json\n",
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"import os\n",
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"from pandas.io.json import json_normalize\n",
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"import numpy as np\n",
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"import seaborn as sns\n",
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"from matplotlib.patches import Arc, Rectangle, ConnectionPatch\n",
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"from matplotlib.offsetbox import OffsetImage\n",
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"#import squarify\n",
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"from functools import reduce\n",
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"path = \"\"\"C:\\\\Users\\\\Koushik\\\\Downloads\\\\open-data-master\\\\open-data-master\\\\data\\\\my_events\\\\\"\"\"\n",
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"Xg_req = pd.DataFrame(data=None)\n",
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"for filename in (os.listdir(path)):\n",
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" #print(filename)\n",
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" \n",
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" with open(\"%s\" % path + filename,encoding=\"utf8\") as data_file: \n",
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" data = json.load(data_file)\n",
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" df = pd.DataFrame(data=None)\n",
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" \n",
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" df = json_normalize(data, sep = \"_\")\n",
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" \n",
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" #df = df[(df['type_name'] == \"Shot\")]\n",
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" #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",
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" #print(df.shape)\n",
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" Xg_req = Xg_req.append(df,ignore_index=True,sort=False)\n",
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" #df.drop(df.index, inplace=True)\n",
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" \n",
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"print(\"done\")\n",
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"df = Xg_req"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"through_ball = df.query('pass_through_ball == True')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 26,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"118\n",
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"12\n"
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]
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}
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],
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"source": [
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"assist = df.query('shot_follows_dribble == True')\n",
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"print(len(assist.index))\n",
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"goal = assist.query('shot_outcome_id == 97')\n",
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"#assist = df.query('pass_goal_assist == True')\n",
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"print(len(goal.index))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>id</th>\n",
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" <th>period</th>\n",
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" <th>timestamp</th>\n",
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" <th>location</th>\n",
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" <th>pass_end_location</th>\n",
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" <th>pass_recipient_name</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>27</th>\n",
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" <td>95ffe924-77f3-40e2-afc6-23e5fed8865f</td>\n",
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" <td>1</td>\n",
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" <td>00:00:38.660</td>\n",
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" <td>[44.0, 17.0]</td>\n",
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" <td>[95.0, 23.0]</td>\n",
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" <td>Francesca Kirby</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>257</th>\n",
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" <td>ce817472-51c1-4b9a-89d5-2b929f422b2e</td>\n",
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" <td>1</td>\n",
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" <td>00:08:03.753</td>\n",
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" <td>[89.0, 65.0]</td>\n",
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" <td>[116.0, 55.0]</td>\n",
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" <td>Nikita Parris</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>623</th>\n",
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" <td>cf2ed5ec-1d2f-4746-a482-4ff7a1823adf</td>\n",
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" <td>1</td>\n",
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" <td>00:19:30.020</td>\n",
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" <td>[39.0, 38.0]</td>\n",
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" <td>[96.0, 42.0]</td>\n",
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" <td>Ramona Bachmann</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1574</th>\n",
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" <td>898b1dba-d2e6-431c-b830-4d897c946ad2</td>\n",
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" <td>2</td>\n",
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" <td>00:01:56.558</td>\n",
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" <td>[41.0, 79.0]</td>\n",
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" <td>[101.0, 47.0]</td>\n",
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" <td>Ramona Bachmann</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3292</th>\n",
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" <td>7799fb29-209f-4b3a-a73e-2c35f9d83c51</td>\n",
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" <td>1</td>\n",
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" <td>00:09:35.360</td>\n",
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" <td>[74.0, 48.0]</td>\n",
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" <td>[98.0, 32.0]</td>\n",
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" <td>Mallory Weber</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" id period timestamp \\\n",
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"27 95ffe924-77f3-40e2-afc6-23e5fed8865f 1 00:00:38.660 \n",
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"257 ce817472-51c1-4b9a-89d5-2b929f422b2e 1 00:08:03.753 \n",
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"623 cf2ed5ec-1d2f-4746-a482-4ff7a1823adf 1 00:19:30.020 \n",
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"1574 898b1dba-d2e6-431c-b830-4d897c946ad2 2 00:01:56.558 \n",
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"3292 7799fb29-209f-4b3a-a73e-2c35f9d83c51 1 00:09:35.360 \n",
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"\n",
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" location pass_end_location pass_recipient_name \n",
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"27 [44.0, 17.0] [95.0, 23.0] Francesca Kirby \n",
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"257 [89.0, 65.0] [116.0, 55.0] Nikita Parris \n",
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"623 [39.0, 38.0] [96.0, 42.0] Ramona Bachmann \n",
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"1574 [41.0, 79.0] [101.0, 47.0] Ramona Bachmann \n",
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"3292 [74.0, 48.0] [98.0, 32.0] Mallory Weber "
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"through_ball= through_ball[[\"id\", \"period\", \"timestamp\", \"location\", \"pass_end_location\", \"pass_recipient_name\"]]\n",
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"through_ball.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>id</th>\n",
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" <th>period</th>\n",
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" <th>timestamp</th>\n",
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" <th>location</th>\n",
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" <th>pass_end_location</th>\n",
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" <th>pass_recipient_name</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>199</th>\n",
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" <td>c547c736-4bf5-484f-9360-463abb19e465</td>\n",
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" <td>1</td>\n",
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" <td>00:05:45.020</td>\n",
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" <td>[104.0, 36.0]</td>\n",
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" <td>[109.0, 29.0]</td>\n",
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" <td>Millie Bright</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>746</th>\n",
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" <td>e3eca08d-7c54-4c65-a19a-faa9708225b5</td>\n",
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" <td>1</td>\n",
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" <td>00:23:20.340</td>\n",
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" <td>[111.0, 24.0]</td>\n",
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" <td>[111.0, 35.0]</td>\n",
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" <td>So-yun Ji</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1649</th>\n",
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" <td>d48d70cf-3464-40c9-80c0-f81d7ce46b25</td>\n",
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" <td>2</td>\n",
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" <td>00:03:39.570</td>\n",
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" <td>[108.0, 5.0]</td>\n",
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" <td>[115.0, 43.0]</td>\n",
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" <td>Nikita Parris</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2739</th>\n",
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" <td>7f1fe749-1914-4f5d-8f0b-62c7c9f79196</td>\n",
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" <td>2</td>\n",
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" <td>00:40:33.251</td>\n",
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" <td>[109.0, 48.0]</td>\n",
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" <td>[97.0, 46.0]</td>\n",
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" <td>Georgia Stanway</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>63663</th>\n",
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" <td>59c55828-1423-4cf5-aef4-58f0cab1d9fe</td>\n",
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" <td>2</td>\n",
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" <td>00:06:57.202</td>\n",
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" <td>[81.0, 28.0]</td>\n",
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" <td>[87.0, 36.0]</td>\n",
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" <td>Hayley Raso</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" id period timestamp \\\n",
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"199 c547c736-4bf5-484f-9360-463abb19e465 1 00:05:45.020 \n",
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"746 e3eca08d-7c54-4c65-a19a-faa9708225b5 1 00:23:20.340 \n",
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"1649 d48d70cf-3464-40c9-80c0-f81d7ce46b25 2 00:03:39.570 \n",
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"2739 7f1fe749-1914-4f5d-8f0b-62c7c9f79196 2 00:40:33.251 \n",
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"63663 59c55828-1423-4cf5-aef4-58f0cab1d9fe 2 00:06:57.202 \n",
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"\n",
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" location pass_end_location pass_recipient_name \n",
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"199 [104.0, 36.0] [109.0, 29.0] Millie Bright \n",
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"746 [111.0, 24.0] [111.0, 35.0] So-yun Ji \n",
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"1649 [108.0, 5.0] [115.0, 43.0] Nikita Parris \n",
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"2739 [109.0, 48.0] [97.0, 46.0] Georgia Stanway \n",
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"63663 [81.0, 28.0] [87.0, 36.0] Hayley Raso "
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]
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},
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"execution_count": 20,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"assist= assist[[\"id\", \"period\", \"timestamp\", \"location\", \"pass_end_location\", \"pass_recipient_name\"]]\n",
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"assist.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"def draw_pitch(ax):\n",
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" # focus on only half of the pitch\n",
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" #Pitch Outline & Centre Line\n",
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" Pitch = Rectangle([0,0], width = 120, height = 80, fill = False)\n",
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" #Left, Right Penalty Area and midline\n",
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" LeftPenalty = Rectangle([0,22.3], width = 14.6, height = 35.3, fill = False)\n",
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" RightPenalty = Rectangle([105.4,22.3], width = 14.6, height = 35.3, fill = False)\n",
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" midline = ConnectionPatch([60,0], [60,80], \"data\", \"data\")\n",
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"\n",
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" #Left, Right 6-yard Box\n",
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" LeftSixYard = Rectangle([0,32], width = 4.9, height = 16, fill = False)\n",
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" RightSixYard = Rectangle([115.1,32], width = 4.9, height = 16, fill = False)\n",
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"\n",
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"\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": 22,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 504x360 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"fig=plt.figure() #set up the figures\n",
|
||
|
|
"fig.set_size_inches(7, 5)\n",
|
||
|
|
"ax=fig.add_subplot(1,1,1)\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",
|
||
|
|
" # annotate draw an arrow from a current position to pass_end_location\n",
|
||
|
|
" ax.annotate(\"\", xy = (through_ball.iloc[i]['pass_end_location'][0], through_ball.iloc[i]['pass_end_location'][1]), xycoords = 'data',\n",
|
||
|
|
" xytext = (through_ball.iloc[i]['location'][0], through_ball.iloc[i]['location'][1]), textcoords = 'data',\n",
|
||
|
|
" arrowprops=dict(arrowstyle=\"->\",connectionstyle=\"arc3\", color = \"blue\"),)\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()"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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": "3.6.8"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
|
||
|
|
}
|