sportowe_wizualizacja/PassMap.ipynb
Mikołaj Pokrywka a3632acda9 wip
2022-11-15 18:27:23 +01:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_16887/3839686170.py:21: FutureWarning: pandas.io.json.json_normalize is deprecated, use pandas.json_normalize instead\n",
" df = json_normalize(data, sep = \"_\")\n"
]
},
{
"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 = \"\"\"my_events/\"\"\"\n",
"Xg_req = pd.DataFrame(data=None)\n",
"for filename in (os.listdir(path)):\n",
" #print(filename)\n",
" \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": 79,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/home/mikolaj/2ait_tech/sportowe/Football-Analytics\n"
]
}
],
"source": [
"!pwd"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" 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>index</th>\n",
" <th>period</th>\n",
" <th>timestamp</th>\n",
" <th>minute</th>\n",
" <th>second</th>\n",
" <th>possession</th>\n",
" <th>duration</th>\n",
" <th>type_id</th>\n",
" <th>type_name</th>\n",
" <th>...</th>\n",
" <th>substitution_replacement_name</th>\n",
" <th>50_50_outcome_id</th>\n",
" <th>50_50_outcome_name</th>\n",
" <th>foul_committed_offensive</th>\n",
" <th>foul_committed_card_id</th>\n",
" <th>foul_committed_card_name</th>\n",
" <th>pass_inswinging</th>\n",
" <th>shot_redirect</th>\n",
" <th>block_save_block</th>\n",
" <th>pass_goal_assist</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>907</th>\n",
" <td>27622bee-3beb-45b5-a8e9-4353a3c48cf4</td>\n",
" <td>908</td>\n",
" <td>1</td>\n",
" <td>00:29:57.022</td>\n",
" <td>29</td>\n",
" <td>57</td>\n",
" <td>63</td>\n",
" <td>0.602922</td>\n",
" <td>16</td>\n",
" <td>Shot</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2589</th>\n",
" <td>7ec34223-fb09-47a9-998f-568ba958ef0d</td>\n",
" <td>2590</td>\n",
" <td>2</td>\n",
" <td>00:44:46.358</td>\n",
" <td>89</td>\n",
" <td>46</td>\n",
" <td>194</td>\n",
" <td>1.080860</td>\n",
" <td>16</td>\n",
" <td>Shot</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2764</th>\n",
" <td>f66400ca-02a4-4121-92d4-991cb225d885</td>\n",
" <td>2765</td>\n",
" <td>2</td>\n",
" <td>00:49:59.483</td>\n",
" <td>94</td>\n",
" <td>59</td>\n",
" <td>209</td>\n",
" <td>0.663063</td>\n",
" <td>16</td>\n",
" <td>Shot</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>3 rows × 117 columns</p>\n",
"</div>"
],
"text/plain": [
" id index period timestamp \\\n",
"907 27622bee-3beb-45b5-a8e9-4353a3c48cf4 908 1 00:29:57.022 \n",
"2589 7ec34223-fb09-47a9-998f-568ba958ef0d 2590 2 00:44:46.358 \n",
"2764 f66400ca-02a4-4121-92d4-991cb225d885 2765 2 00:49:59.483 \n",
"\n",
" minute second possession duration type_id type_name ... \\\n",
"907 29 57 63 0.602922 16 Shot ... \n",
"2589 89 46 194 1.080860 16 Shot ... \n",
"2764 94 59 209 0.663063 16 Shot ... \n",
"\n",
" substitution_replacement_name 50_50_outcome_id 50_50_outcome_name \\\n",
"907 NaN NaN NaN \n",
"2589 NaN NaN NaN \n",
"2764 NaN NaN NaN \n",
"\n",
" foul_committed_offensive foul_committed_card_id \\\n",
"907 NaN NaN \n",
"2589 NaN NaN \n",
"2764 NaN NaN \n",
"\n",
" foul_committed_card_name pass_inswinging shot_redirect block_save_block \\\n",
"907 NaN NaN NaN NaN \n",
"2589 NaN NaN NaN NaN \n",
"2764 NaN NaN NaN NaN \n",
"\n",
" pass_goal_assist \n",
"907 NaN \n",
"2589 NaN \n",
"2764 NaN \n",
"\n",
"[3 rows x 117 columns]"
]
},
"execution_count": 80,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"d = df.query('shot_outcome_id == 97')\n",
"d"
]
},
{
"cell_type": "code",
"execution_count": 81,
"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": 82,
"metadata": {},
"outputs": [],
"source": [
"player_name = 'Kit Graham'"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {},
"outputs": [],
"source": [
"def draw_passes(p_name, position, team, type_name, period):\n",
" ozil_pass = df[(df.type_name == type_name) & (df.player_name == p_name) & (df.period == period) ]\n",
" pass_column = [i for i in df.columns if i.startswith(\"pass\")]\n",
" ozil_pass = ozil_pass[[\"id\", \"period\", \"timestamp\", \"location\", f'{type_name.lower()}_end_location', \"pass_recipient_name\"]]\n",
" ozil_pass.head()\n",
" 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(ozil_pass)):\n",
" # annotate draw an arrow from a current position to pass_end_location\n",
" ax.annotate(\"\", xy = (ozil_pass.iloc[i][f'{type_name.lower()}_end_location'][0], ozil_pass.iloc[i][f'{type_name.lower()}_end_location'][1]), xycoords = 'data',\n",
" xytext = (ozil_pass.iloc[i]['location'][0], ozil_pass.iloc[i]['location'][1]), textcoords = 'data',\n",
" arrowprops=dict(arrowstyle=\"->\",connectionstyle=\"arc3\", color = \"blue\"),)\n",
" plt.title(f\"{player_name} Position: {position}, Team: {team}, Type: {type_name}\")\n",
" plt.show()\n",
"\n",
"\n",
" fig, ax = plt.subplots()\n",
" fig.set_size_inches(7, 5)\n",
"\n",
" x_coord = [i[0] for i in ozil_pass[\"location\"]]\n",
" y_coord = [i[1] for i in ozil_pass[\"location\"]]\n",
"\n",
" #shades: give us the heat map we desire\n",
" # n_levels: draw more lines, the larger n, the more blurry it looks\n",
" sns.kdeplot(x_coord, y_coord, shade = \"True\", color = \"black\", n_levels = 30)\n",
" plt.show()\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 504x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mikolaj/.local/lib/python3.8/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"data": {
"image/png": 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5tZBSS5FYqLyWPr8twDGuFRBSQWhaHjNeEVs9OG6/hLRM0zxNee2114pIa9zempieM9/r3GPNJZBxEU4L0poS06el06e9QHF1QqkKwuk2IRWEsdLyVQ+Ol9uWxaQGQ4RlmjUjpJhibfJKxXRBDbnI1hBJSVG57usqec9XaanGtLXG6sLtjjc7Ya5iDF+q0NX+HNKyRVk2YuYqLJXS6zk9OGWcLgTiU4YDOWM/JS/2pW8yHlOyuILjXX4orsaZsxjD1a4t2hqvGx/bVT043S9FWjZhpZaklxLOuI2U9paWXsr4SWzl4RzMnXKLqQ7kGFU+TBV2Suq4FlC2GGMqLZM4XSXvLUhrzeSKYvq4k9DP2BK0cF9X6PF9f5cWzmfLUPsNU2tca0pOMca43WmKcIrpPq3puunvIdIqOZHunBGP61v3XKmikt/+505xlbi4h7YR+77mOBfbHLllRVwicpWIPCIifyIiT4vID4nINSLyuIh8ffPv1aU6u020MK5Vo4LQFH21IC0SjutiXztSSI2qcossUvbzbddiBWQv5KYKPw7gd1T1BwG8HcDTAO4D8ISq3gLgic1rUog5x7Vcx08txhiIfQTJWqQVG9GV/tYe8neebmN7OrKN0um6uUST0qeQ7XKOQcwki0tEvhfADwN4EABU9TVVfRXAnQAe2mz2EIC78rq4feSkCGNISRGO15mOnVOMYetby9IKEZEvnROS7jFts8SsGQOhF+2Uz2eJqGguQo7nWs+oK42cBOnNAM4D+HUReTuAswA+DOA6VX1xs81LAK7L6+J20UOK0NR+6LhWbDFGy9Ka0ntFYSyh4zg1RZLbti2aHN8GENoPlrDPR06qcBfAOwE8oKrvAPAXmKQFVVUBqGlnETklImdE5Mz58+czurEdtJYiHLcfM641EHOvlm2/0pjEMZ32qdRgeG+D6rHpwtrERlaXLl0y/oRuH9onMg854joH4JyqPrl5/QgORPayiFwPAJt/XzHtrKqnVXVPVfeOHz+e0Y31sNYU4UCsdFqftcIWYY1/HwvKJEZjCtDxzX0u4YV+oVkiLRd6zFjxhLSVypJSW+Ps8MniUtWXADwvIj+wWXQbgK8BeAzA3ZtldwN4NKuHW0IvKcLpcWqVvreQIqwVbYVSIvVUss+2C/dclYQhlJSVrX0Xcwqqt6i9JLnv/J8C+LSIHAPwLIB7cCDDz4rIvQCeA/D+zGNsNaVvNHa1G9KPkNkxXBWDqSnC2sSOL8UWZdiisJD2vMUdO8tfwEqP8cQKYM5U5nQqLDI/WZ94Vf0jAHuGVbfltLtt5EyCueSNxqF9K5EibHlsK7UoIzZNeGi7xIrCmt/SS8grdtxqKSivZeGZb5ieCzJMtBptxZITnYVGWyYBpJbNz0lqqiyl2GLtlIhg1zi+BXDKp8VpvSAj9dip0ZaJHqOtlHu3UmXVGjXL5HOE5fuC1OO53lb4l2qUkgUZpv1C2y8VbY2JnSGjFinSyqkkDL0w+i764zTh3ONboSky22zpqV++UoUVE80P2/YgsB76WJPtfvcLs2S0NV1XI9oaEzJDxpzkSisHX4m8abuUC1ULF7cSVXYp0mot/Wz7MlLzb7TWNCHAMa4mWUu01cMMF6n7lIi2xuuHC1vOuEYLoipNrLT29/OfNNyC9Fq4l69lKK6F2NZoa2mZ2aRVc1zLFzn5ZDXeJydN2NsFL0VaS9PKtE9rjrYApgqbo3a0ldOPkKcaT7ctwdGjR7PbCxUWED6ulXI81/rxRS9WMtPtQ/cPke0SLCmtkPceUwofmyZsRX4tw4hrAVquJIy5L2wgVSpzfUOuJa3YFGFKJWGpaKsUc9y7tA2l7qmESHXt0RZAcTVFSrQ1UHuWjJj9apA6LlVKWq7+xEor9L6tUEKiraUjqJrMnSK0ydv0NywZba35bxgLz8TMlI62cmbJuNyGI9oaiEkTmvYrQUjKMERwKdJKvV9ruo2pIMO2be1oq9U04ZKkvveYLx6sJMxnez+hjRHzrTFGVs5jXrRvHzq909zVhDkl6SZhAeWkFSO08YXOJzDX9E5zRltrTxPONbaVsv02f5kwwbMxI7XmJHT9Zy9RlLEGQqIsIFxarv1SU4RB0VuhSsLY5S3Py7e7u5v1uQ2VwlIpwlC2JdoCOMbVLLWLMi4fJyFNWArTf2JbVJTKsWPHqkgrZ1zLdM9WSoqwdCVhC8wtyBrSyj1Wyn7bJC2AEddslH7e1kBqUYYrTWg7lqvdklI7duxY9tRPLgGGFGHUlpatvSVThD1GWwND30M+h7HnJVZaTBHWh2elU2o+sK6FR5CnyitGWIA7yjK9LiWt2Al1mSIMo/SFvpS0alYRblu0BVBci5Ny31Rse7GPMZkT1/jEICGfwELSi61Ky3pBmzFFWEpapSbUPXLkyOL3crne+xzSCmUbpQVQXLNQqigjJk3oaivkpuMQ5pq+KWfcy3bRaE1aJce1YtKGudJyXXyHdSkCW1JeLUiL41puKK7GyLl3a0yp6Km0nEz3YuVWhZkIFZZpWamSd2Cd0kodw4kV2NzyKiksoK60th2eoQUpfbEuWTRRapwrdJ7BUvJy/af3RVXTZTHSMkVbOdKaUroYYy5pmfaN+WwN/aklsJDIskVpbXO0BVBc1amVJqxFqZubXdhkFlMZZtrPdTzfMldqcLreJp7xdrnSGkdbsbNz+JanSKvkxK87OztJ0RdQRmAl06BTXH8rSqscFFdnhMwEbyKm5D6X3Nncx/+Bp/2KiSpsNwz3Lq3Q4oxQac0lLFO7qQIb45NZbpFJ6DpKaz4oroYoFVWF3L+VW5gRg0lkMSnElOOFLi8hrVKFGIC/7H0uac31aI2cAo6BUiX7vvdMabUDxVWRnJuOY1milH0sn5QxqhLP2Zq2F7rOtK1NRtN1c0nLJ6ncQoylpWU75pz3EYa815x7rSitOlBcjbLE+FZNbJIaLvypAkt5YGNMlDVdv2ZptfIAw9oSC32fOdIJOQallQ7F1RGx41tLTpgbmx4cS8AlsZwnEPuiLNM2c0srdUwrVFq5UVas3HLFk3tTc4qMc6MkSqs+FFcjtB5VhaQCQ7Yp9Uyt2H17lFbOfVolo6wSJfADpUVWkhLCKXmPFqVlh+KqxJzjW63iSg/WuLE5dHmMsKav1yKtnEKEHJYay7IR+j7njLIASssHxbUyas/cDhyOrHwSqimvlPGtbZNWbJQ15zhX6Wgs5Zg+QmRDac0PxdUgPRdmmNKFvsIMILw4IySNGCIs03Yh92gB7U7j5JNWK8KK6cMSqcVQyVBYy0FxrYCaqcdSab2QyKzEMUz4oqzpNtskrRaE5WLO/pUUVkx7AKUVC8U1M6UfY9ICUynZijRqjG0N7ZqIjbJMr1uSVunUYI202UAv47gx76mGsABKKwWKqwI58xPaSJ3qKRXTfHJjIfkqCF3yAvJnnXdFaLYLR+p4FjCvtFqJsmIvwCH7tiC02PcVI3hGWfNAcZFDpEyACsQ/riRWYCGpxFBhmbbNKcKYvm5VWqXHZFIwtV9TZjnvp5awAEorF4qLAPBLxjab+3iflGdtlRjbGo4T0n7p1OD09dzSKhVl1RZWqWOPI/4a1EyfDlBa+WT/9UVkB8AZAC+o6h0icjOAhwG8CcBZAB9SVfez10k3hNxkXGKf0HZtxEZZ031iU4NAm9JqWVgp1OhvzcrDMRRWOUpMq/xhAE+PXn8UwMdU9S0AvgXg3gLH2BrmHgNw/QdMSS25CiVKXXRcbR09enSV0pq+51xplfx79MjOzs7lnxhSztvJkycprcJkiUtEbgTw4wA+sXktAN4D4JHNJg8BuCvnGKQ9fP9xfYUTsf/5x/ukRFlrkNaYsbRMF1/XBTlHWOOLve+nNXL7l3reKKw65H7l+lUAvwDgr25evwnAq6o6hA3nANyQeYyuiK0odBVClCqTN6XqdnZ3Lj+Ta4qpQMNVym5qP6T0vdQ3/tByeF902KO0priEFUOufHz717wFpKQ4Uz+jFFZdkq8cInIHgFdU9ayIvDth/1MATgHAiRMnUrvRFS2UAruIGYuabmuTF5Bf+m4j5v6t1qWVO56V88yokDZK02JUNpDzhYrCmoecr7wnAbxXRH4MwHcD+GsAPg7gKhHZ3URdNwJ4wbSzqp4GcBoA9vb2NKMfpCLj6MsXRdnEV/LGY18VIqXlbtdEyxKZi9zon8Kal+S/lqreD+B+ANhEXD+vqh8Ukf8A4H04qCy8G8Cj+d0kpdjd2cX+xcNyMaYSA+7nMu3nktdArMRy7uGitMxQVmVS1RTWMtQoK/rnAB4WkV8C8BSAByscg8yIK+qKkddAqXu3xscLWZYirSlLSSt0PIvCslOyipLCWpYif0lV/T0Av7f5/VkA7yrRLpmfUvdp1bp3a3qM0OWp0hq/bkVajLLCqFHuT2G1wfbeyEGclYXA4UgrZqxrYLhw1HgeWOg6U3SXKy3fMeeW1hzCypVArS8xc92LRmG1BcW1MsaRTk6VoI/QGeGHdUDexct3gYqNsqavY6QV8xDIkAtrLWmlCquGDOYSTEkoq3bp79NEkkiVmC3qSjnG+OIV0pfQi12utFztuaTl60fsfVpLSqtHsdSCwmofflpXQGy0ZKosTME2qS7gF1OJC6WtjVhpuSoID23nGNeKjaymr0tJi8JKg7LqC35qC1LjOVw2ShU/jMe5bG26oq7QmeNL4rrYlpRWTDGGr48tSYuyoqh6h59gYiRGPHPJK0ZYwHzSynlNac0DRbUutvNTTLKImctwjsKMXGldsW/FCsKlpLVtwqKo1s12fZq3nEMVh6NxLlu60FakYXoN+CfiHShZmFFCWjWLMULW15TW2oVFQW0n6/5Uk6LpupBpoJaeFT72Qp5ajBGCa/vpVE4DodJqJcqiOMgSUFydceTIEVy6dMm5TUlZudqyiazkpLombFNGpTxM8dC2C49rtSgtiom0CMXVMCERTg1iZDW3vHKk1fK4Vilp5QqLoiI9QHFtMbZxrljmkJdrYt4UaS0xruWbNNfXbk1pUVikJyiuLSMljTjdJyYSzH2YpG8m+VxpTak5rjWQUvFYQ1qUFekViosYiRWcT2YxAgt97EkJaS2RIozpr2kbXz99UFikdyiumZjjER+uSW5zjx8SdYVWHZYgthDD2EbBFGGJca2UqInSItsIxUUukzPOdbmNGQpKUh+qWDNFaCOmGMNETFWkCwqLrAlz/oJsDa4ow4ftolrrgYU7OzvFpDVXitDVx5x9KC2yzTDiIlam6cGaE+f6iJFkrLTmSBEeOn7muFaotCgsslYYcZEsXEIpEXm52kl5GvAV2xdMEZYa16K0CHFDcRVizkea9ESOvFz7ps6GXjNFaILSIqQ8FFfD1CpySJ1BwravTyLR1X6eaM22rvUUYQ6UFiGvwzEu4qTUuNZYNqYy+pR2xuRKq+UUIaVFyGEorgVZYh7CWsSUwaemD1OldcX2hSfQHaC0CJkHpgpJNEs84ynnwu5Lf7rayy19p7QIKQ/FRYpR8/4tE6YLe8kU4RzjWrnnjNIi2wjF1RAhY0m+Z3GlkHMT8pSS8nIVadSQVkwkWXtKp5BtKS2yrVBcM7DUTbulCJHEmFL3b+X0J1darY9rUVpkm6G4CtDCPVwl5RgzJmRtI6MAo3VpLT2uRWmRbYdVhaQaw8XZV22Y8yj6mBuMQ/YvPa5FaRFSHoprIdZQCh96j1du6jBHWkvfrzWF0iIkH6YKG2UsthYkt0QJvOu4JaQV83qu52vZoLQIeR1GXJWpVZjRSsFHrRnjQ4UF1JfWmCWKMSgtQg7DiCuTUoUZrYgohZKRxe7ubnPSWrIYg9Ii5EooLhJMzM26KW3Htj+3tIZoa+6ZMQghh0kWl4i8WUS+ICJfE5GvisiHN8uvEZHHReTrm3+vLtfd7abGzcc2UkriffKxbe8TVoi0dnd2Z5eWqa9X9JPFGIQUJyfi2gfwz1T1rQBuBfDTIvJWAPcBeEJVbwHwxOY1GdFCsUUqIRfcsZBcPyFtTNnZ3Ql6PEkNaV3RF1YQErIIyeJS1RdV9Q83v/9fAE8DuAHAnQAe2mz2EIC7MvvYLL7xrdRxq9bFVjvFZWs/NDVYS1oxKUJKi5B6FBnjEpGbALwDwJMArlPVFzerXgJwnWWfUyJyRkTOnD9/vkQ3VslcEjNFLTFPC84+viMSM0VZQNg9WpQWIesjW1wi8lcA/EcAP6uq/2e8TlUVgJr2U9XTqrqnqnvHjx/P7UbX9FpRWEJevrShTVgh41mUFiHrJOvKIyJHcSCtT6vq5zaLXxaR61X1RRG5HsAruZ0kbmqKb2d3Bxf37VHf+IIc0o9Q2dmivZTxrJBtakorBEqLkHByqgoFwIMAnlbVfzNa9RiAuze/3w3g0fTurY9Wxq+MF3fL401CKwxzCzKGY8VEWSFCSq0eLCUt3qtFSFlyIq6TAD4E4I9F5I82y/4FgF8G8FkRuRfAcwDen9XDRqlVmNEqvsirRPsmbDJNibJ8+9lK3iktQtoiWVyq+t8BiGX1bantEj81pbi7s4v9i+b2S8vLWfwRKKzQZSmpQdNrSouQ5eGt+ytgd9c/X6BpG9t+PnkNxEosJOUYIyzT8tQoC/DP8k5pEdIGFNfCTMXRzBiYQ14DJR44OT6edV1ilGVaVqIIw7SNa9splBYheVBcCSz9xOOQCKtEWyHyyjq2Q1ZAWWFNl1FahPQLxbVSolKDHnkBKCYwn6yG/oQuLxVlmV5TWoS0CcVVAZsEWkkDmvBFcWPhxEgsRFTD8WPWlYyyTK8pLULaheLaMpzRVWAKMlRGof2JXZdSRZhThGHbztXHMZQWIWWhuFZCsdTg5kJcteTec7EvmSqsFWW5+jmG0iKkPBTXluJNDRYUWMgFvkaqcElpUViE1IPiimTpisJYclODpgu0LYpL7V/supJRlq09pgYJaReKqzF2dnaCijiWTA2mSipk/9zIi6lBQtYPxdURR44cwaVLl5L2nTM1aGs7dZvSwrK1SWkR0gcUV+O4IrCYqMu3brzNmFiRxURjKUUaLmEBaVGWabvQPg5QWoTMB8W1MCVnwQhpMzayyk0LxrYXOq4VKyxb24yyCOkPiqszpunClHGtYT0wz+NXclKFtYRl29a3zxhKi5BloLhmJLTwYrrd9HUpeQ3bDMxV+h6ybcvCAigtQpaE4loJLnkBYVIqnRZMOUassGzLGGURsl4orgYwSSc26rK1M14HLPNk5pRxrdaEBVBahLQCxdURufIa1g/UkljOmNacwnLtN4bCIqQtKK6ZsY1zhURdpmU2eQF+MeWUvqekFUNlBbQhLIDSIqRFKK4KlCxxT5XX0A9gudJ3V5uhsrItd/WVaUFC1g3F1RAxwjPJC0ARgeXgEoNJVkB4dOVrn1EWIdsBxRXJyZMnsyfaDS2L921vWh4isDGpMguVQIysXMspLELIAMVVidR0oW0/l7yAK5+uPBaGa37D0ulBm6iAeFkB8wgLoLQI6QmKayFi5yAc9gGulJRv3VQmqRP1uto04RJLjnQoLEK2G4qrIr6oK0Vevv1cAhsIkU4KPqH4tvEJh8IihABAnSvYyil50ctJk/kimvFPaabtu9KArm12d3cv//j2t+Ha3wSlRUjfMOKqTG5pvK8iMCTCGm9Xm9Dj5EZXIW1MobAIWQcUVwOEVBmGpB3HxFQt5lBKVDHtUViEbDcUVyIxZfEhUVdI5BRzP5ZJAKkyS43WSsoqpr0BCouQdUJxzURoyjA0+hqISUPWThfGiCWmLxQWIWQMxZVB7M3IJeU1bnNgzpnfU+7/qikrgMIiZFuguGYmRl5AXHqv5MwYrjZjiI3yKCxCiA+KK5OUKaBi5yQcSBmjmuPhkGNS0pGpfaSwCNlOqtzHJSK3i8ifisgzInJfjWO0RMoFNDXVNldZeyip94v57t9ycfLkSUqLkC2m+NdxEdkB8O8A/B0A5wD8gYg8pqpfK32slkiNvID4dF7rpe82cqI/iooQMlAjj/QuAM+o6rMAICIPA7gTwKrFBaTPHJ/72BGXUEKlViuSy01VUliEkCk1xHUDgOdHr88B+NsVjtMkOY89qfHcrCVSiyXG1SgsQoiNxYozROQUgFMAcOLEiaW6UYXcZ3bN+eDHEpQqAKGsCCEh1BDXCwDePHp942bZIVT1NIDTALC3t6cV+rEoJR44udQ9Wi5KVylSVoSQWGqI6w8A3CIiN+NAWB8A8BMVjtM8JeQ1UOMerdjjlYTCIoSkUvzqpKr7IvJPAPxXADsAPqmqXy19nF4YLtClBDZm7nu0cqCoCCGlqHLlU9XPA/h8jbZ7pabAWoWyIoTUoJ+v7Cth7QKjrAghtaG4FmItAqOoCCFzQ3EtzPjC37rEKClCSAtQXA0xFcOSIqOkCCGtQnE1jEseuVKjmAghvUJxdQrFQwjZVqo81oQQQgipBcVFCCGkKyguQgghXUFxEUII6QqKixBCSFdQXIQQQrqC4iKEENIVFBchhJCuoLgIIYR0BcVFCCGkKyguQgghXUFxEUII6QqKixBCSFdQXIQQQrqC4iKEENIVFBchhJCuoLgIIYR0BcVFCCGkKyguQgghXUFxEUII6QqKixBCSFdQXIQQQrqC4iKEENIVFBchhJCuoLgIIYR0BcVFCCGkKyguQgghXUFxEUII6QqKixBCSFdQXIQQQrpCVHXpPkBEzgN4bul+WLgWwJ8t3YkVwfNZDp7LsvB8lqXE+fzrqnp8urAJcbWMiJxR1b2l+7EWeD7LwXNZFp7PstQ8n0wVEkII6QqKixBCSFdQXH5OL92BlcHzWQ6ey7LwfJal2vnkGBchhJCuYMRFCCGkKyiuCSKyIyJPichvbV7fLCJPisgzIvKbInJs6T72gohcJSKPiMifiMjTIvJDInKNiDwuIl/f/Hv10v3sBRH5ORH5qoh8RUQ+IyLfzc9nOCLySRF5RUS+Mlpm/DzKAb+2Oa9fFpF3LtfzNrGcz3+9+f/+ZRH5TyJy1Wjd/Zvz+aci8ndzjk1xXcmHATw9ev1RAB9T1bcA+BaAexfpVZ98HMDvqOoPAng7Ds7rfQCeUNVbADyxeU08iMgNAH4GwJ6qvg3ADoAPgJ/PGD4F4PbJMtvn8UcB3LL5OQXggZn62BOfwpXn83EAb1PVvwngfwK4HwBE5K04+Lz+jc0+/15EdlIPTHGNEJEbAfw4gE9sXguA9wB4ZLPJQwDuWqRznSEi3wvghwE8CACq+pqqvgrgThycR4DnM5ZdAN8jIrsA3gDgRfDzGYyq/j6AP58stn0e7wTwG3rAlwBcJSLXz9LRTjCdT1X9XVXd37z8EoAbN7/fCeBhVf1LVf0GgGcAvCv12BTXYX4VwC8AuLR5/SYAr47+EOcA3LBAv3rkZgDnAfz6JvX6CRF5I4DrVPXFzTYvAbhusR52hKq+AOBXAHwTB8L6NoCz4OczF9vn8QYAz4+247mN5x8B+O3N70XPJ8W1QUTuAPCKqp5dui8rYRfAOwE8oKrvAPAXmKQF9aCklWWtAWzGXu7EwReC7wPwRlyZpiEZ8PNYDhH5RQD7AD5do32K63VOAniviPwvAA/jIAXzcRykCHY329wI4IVlutcd5wCcU9UnN68fwYHIXh5SLpt/X1mof73xIwC+oarnVfUCgM/h4DPLz2cets/jCwDePNqO5zYQEfmHAO4A8EF9/X6roueT4tqgqver6o2qehMOBhH/m6p+EMAXALxvs9ndAB5dqItdoaovAXheRH5gs+g2AF8D8BgOziPA8xnDNwHcKiJv2Iy9DueTn888bJ/HxwD85Ka68FYA3x6lFIkFEbkdB8Mt71XV74xWPQbgAyLyXSJyMw6KXv5H8nF4A/KViMi7Afy8qt4hIt+PgwjsGgBPAfgHqvqXC3avG0Tkb+Gg0OUYgGcB3IODL0ufBXACB08EeL+qTgfMiQER+VcA/h4OUjBPAfgpHIwT8PMZgIh8BsC7cTBr+csAPgLgP8Pwedx8Ofi3OEjHfgfAPap6ZoFuN4vlfN4P4LsA/O/NZl9S1X+82f4XcTDutQ/gZ1X1t6dtBh+b4iKEENITTBUSQgjpCoqLEEJIV1BchBBCuoLiIoQQ0hUUFyGEkK6guAghhHQFxUUIIaQrKC5CCCFd8f8BY6WLDFNiwTYAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 504x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"draw_passes(\"Martha Thomas\", 'Center Forward', 'West Ham United LFC', type_name=\"Pass\", period=1)\n"
]
},
{
"cell_type": "code",
"execution_count": 85,
"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"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mikolaj/.local/lib/python3.8/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 504x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"draw_passes(\"Martha Thomas\", 'Center Forward', 'West Ham United LFC', type_name=\"Pass\", period=2)"
]
},
{
"cell_type": "code",
"execution_count": 86,
"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"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mikolaj/.local/lib/python3.8/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 504x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"draw_passes(\"Rianna Dean\", 'Center Forward', 'Tottenham Hotspur Women', type_name=\"Pass\", period=1)\n"
]
},
{
"cell_type": "code",
"execution_count": 87,
"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"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mikolaj/.local/lib/python3.8/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
" warnings.warn(\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 504x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"draw_passes(\"Rianna Dean\", 'Center Forward', 'Tottenham Hotspur Women', type_name=\"Pass\", period=2)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Wnioski:\n",
"Obie zawodniczki poruszały się dosyć defensywnie jak na napastniczki, szczególnie Martha Thomas zachowywała defensywę w pierwszej połowie. Jednakże w drugie połowie widać bardziej ofensywną gre u obu zawodniczek\n",
"\n",
"Martha Thomas, więcej podań wykonywała na lewą stronę boiska, a Rianna Dean w pierwszej połowie na prawą, a w drugiej połowie na lewą\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.10.6 64-bit",
"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": "3.8.12"
},
"vscode": {
"interpreter": {
"hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}