333 lines
7.7 KiB
Plaintext
333 lines
7.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "4817ec9b-c8e3-45a4-97dc-acee536e4d77",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import requests\n",
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"import json"
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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": 4,
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"id": "a05a0d5e-012e-46b8-a52c-7f8a3a412e62",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"nac4_finals_draft_id='FMHZx'"
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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": 22,
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"id": "16438549-78b6-4865-ba7d-fb90486579e3",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"def download_draft_json(draft_id):\n",
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" url = \"https://aoe2cm.net/api/draft/{}\".format(draft_id)\n",
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"\n",
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" payload={}\n",
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" headers = {}\n",
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"\n",
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" response = requests.request(\"GET\", url, headers=headers, data=payload)\n",
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"\n",
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" # print(response.text)\n",
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" draft_json_string = response.text\n",
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" draft_dict = json.loads(draft_json_string)\n",
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" return draft_dict"
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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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"id": "527953cb-e30f-4599-a5e6-b5f8ce3b678d",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# draft_dict['events']"
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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": 23,
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"id": "4f068845-8292-4b38-bd2b-0d89a2eea434",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"marcel_vs_canuck= 'lipeX'"
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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": 25,
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"id": "8a375968-3d08-46e2-b7be-45a926de40f1",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"marcel_vs_canuck_json = download_draft_json(marcel_vs_canuck)"
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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": 44,
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"id": "69ecf8fd-b437-4632-9f6e-1172a34badf0",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# marcel_vs_canuck_json"
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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": 29,
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"id": "c45783ac-50c0-4cf2-b451-23d11b5f5079",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import pandas as pd"
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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": 36,
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"id": "a9f08fa9-4f90-4ba1-a639-78ec888ac86c",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"draft_events = marcel_vs_canuck_json['events']"
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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": 41,
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"id": "527935c9-1f49-4c7f-8b4a-b95475a66068",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"draft_events_df = pd.DataFrame.from_dict(draft_events)"
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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": 45,
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"id": "7e2bb0c3-ab79-4e95-94f7-52a590e8dfe6",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"draft_picks = draft_events_df[draft_events_df['actionType'] == 'pick']"
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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": 46,
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"id": "99dedcda-5664-492b-a076-7fe059948660",
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"metadata": {
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"tags": []
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},
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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>player</th>\n",
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" <th>executingPlayer</th>\n",
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" <th>actionType</th>\n",
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" <th>chosenOptionId</th>\n",
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" <th>isRandomlyChosen</th>\n",
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" <th>offset</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>2</th>\n",
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" <td>HOST</td>\n",
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" <td>HOST</td>\n",
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" <td>pick</td>\n",
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" <td>Koala</td>\n",
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" <td>False</td>\n",
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" <td>13973</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>GUEST</td>\n",
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" <td>GUEST</td>\n",
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" <td>pick</td>\n",
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" <td>Nordinseln</td>\n",
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" <td>False</td>\n",
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" <td>26925</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>8</th>\n",
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" <td>HOST</td>\n",
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" <td>HOST</td>\n",
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" <td>pick</td>\n",
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" <td>Vier Seen</td>\n",
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" <td>False</td>\n",
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" <td>54947</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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" player executingPlayer actionType chosenOptionId isRandomlyChosen offset\n",
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"2 HOST HOST pick Koala False 13973\n",
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"3 GUEST GUEST pick Nordinseln False 26925\n",
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"8 HOST HOST pick Vier Seen False 54947"
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]
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},
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"execution_count": 46,
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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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"draft_picks"
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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": null,
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"id": "17a9c895-c486-4b53-b34d-917e6e94d0fc",
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"metadata": {},
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"outputs": [],
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"source": [
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"# the last pick is the neutral map\n",
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"def mark_neutral_map(draft_picks):\n",
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" draft_picks.\n",
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" draft_picks['neutral_map'] = "
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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": 49,
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"id": "1a82cae5-dd3d-4799-baa1-be30f550d19b",
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"metadata": {
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"tags": []
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},
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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>player</th>\n",
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" <th>executingPlayer</th>\n",
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" <th>actionType</th>\n",
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" <th>chosenOptionId</th>\n",
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" <th>isRandomlyChosen</th>\n",
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" <th>offset</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>8</th>\n",
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" <td>HOST</td>\n",
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" <td>HOST</td>\n",
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" <td>pick</td>\n",
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" <td>Vier Seen</td>\n",
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" <td>False</td>\n",
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" <td>54947</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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" player executingPlayer actionType chosenOptionId isRandomlyChosen offset\n",
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"8 HOST HOST pick Vier Seen False 54947"
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]
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},
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"execution_count": 49,
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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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"draft_picks.tail(1)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"nbconvert_exporter": "python",
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