generated from dhairya/scenario_template
System save at 13/10/2024 23:59 by user_client2024
This commit is contained in:
user_client2024
parent
9a36694f7f
commit
c1627a1c91
@ -2,72 +2,12 @@
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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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"execution_count": 4,
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"id": "90c70e46-71a0-44a6-8090-f53aad3193c3",
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Query start time: 2024-10-13 18:13:45.509982\n",
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"Query end time: 2024-10-13 18:13:45.944136\n"
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]
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},
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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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" .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>START_DATE_TIME</th>\n",
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" <th>END_DATE_TIME</th>\n",
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" <th>FOCAL_ID</th>\n",
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" <th>MIN_PRICE</th>\n",
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" <th>MAX_PRICE</th>\n",
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" <th>PRICE_CHANGE (%)</th>\n",
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" <th>PARTICIPANT_VOLUME</th>\n",
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" <th>TOTAL_VOLUME</th>\n",
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" <th>VOLUME (%)</th>\n",
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" <th>PARTICIPANT_VOLUME_PCT</th>\n",
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" <th>Segment</th>\n",
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" <th>SAR_FLAG</th>\n",
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" <th>Risk</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\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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"Empty DataFrame\n",
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"Columns: [START_DATE_TIME, END_DATE_TIME, FOCAL_ID, MIN_PRICE, MAX_PRICE, PRICE_CHANGE (%), PARTICIPANT_VOLUME, TOTAL_VOLUME, VOLUME (%), PARTICIPANT_VOLUME_PCT, Segment, SAR_FLAG, Risk]\n",
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"Index: []"
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]
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},
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"execution_count": 1,
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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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"outputs": [],
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"source": [
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"from datetime import datetime\n",
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"import pandas as pd\n",
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@ -171,35 +111,28 @@
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" return final_scenario_df\n",
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"\n",
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"\n",
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"# Instantiate and execute logic\n",
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"scenario = Scenario()\n",
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"scenario.logic(validation_window=1000)\n"
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"\n"
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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": 6,
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"execution_count": 5,
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"id": "caee5554-5254-4388-bf24-029281d77890",
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"metadata": {},
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"outputs": [
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{
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"ename": "TypeError",
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"evalue": "unsupported operand type(s) for /: 'NoneType' and 'int'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[6], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m scenario \u001b[38;5;241m=\u001b[39m Scenario()\n\u001b[0;32m----> 2\u001b[0m \u001b[43mscenario\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlogic\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
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"Cell \u001b[0;32mIn[4], line 60\u001b[0m, in \u001b[0;36mScenario.logic\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 58\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlogic\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 59\u001b[0m validation_window \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mvalidation_window\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 60\u001b[0m time_window_s \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(\u001b[43mvalidation_window\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1000\u001b[39;49m)\n\u001b[1;32m 62\u001b[0m query_start_time \u001b[38;5;241m=\u001b[39m datetime\u001b[38;5;241m.\u001b[39mnow()\n\u001b[1;32m 63\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mQuery start time:\u001b[39m\u001b[38;5;124m\"\u001b[39m, query_start_time)\n",
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"\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'NoneType' and 'int'"
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]
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}
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],
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"outputs": [],
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"source": [
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"# Instantiate and execute logic\n",
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"scenario = Scenario()\n",
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"scenario.logic(validation_window=1000)"
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"#scenario = Scenario()\n",
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"#scenario.logic(validation_window=1000)"
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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": "1feaf267-88d1-41b8-a8b9-f150b7ff16cd",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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70
main.ipynb
70
main.ipynb
@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 4,
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"id": "90c70e46-71a0-44a6-8090-f53aad3193c3",
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"metadata": {
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"tags": []
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@ -116,74 +116,14 @@
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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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"execution_count": 5,
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"id": "caee5554-5254-4388-bf24-029281d77890",
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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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"Query start time: 2024-10-13 18:14:29.793521\n",
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"Query end time: 2024-10-13 18:14:29.933772\n"
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]
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},
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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>START_DATE_TIME</th>\n",
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" <th>END_DATE_TIME</th>\n",
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" <th>FOCAL_ID</th>\n",
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" <th>MIN_PRICE</th>\n",
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" <th>MAX_PRICE</th>\n",
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" <th>PRICE_CHANGE (%)</th>\n",
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" <th>PARTICIPANT_VOLUME</th>\n",
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" <th>TOTAL_VOLUME</th>\n",
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" <th>VOLUME (%)</th>\n",
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" <th>PARTICIPANT_VOLUME_PCT</th>\n",
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" <th>Segment</th>\n",
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" <th>SAR_FLAG</th>\n",
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" <th>Risk</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\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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"Empty DataFrame\n",
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"Columns: [START_DATE_TIME, END_DATE_TIME, FOCAL_ID, MIN_PRICE, MAX_PRICE, PRICE_CHANGE (%), PARTICIPANT_VOLUME, TOTAL_VOLUME, VOLUME (%), PARTICIPANT_VOLUME_PCT, Segment, SAR_FLAG, Risk]\n",
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"Index: []"
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]
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},
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"execution_count": 2,
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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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"outputs": [],
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"source": [
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"# Instantiate and execute logic\n",
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"scenario = Scenario()\n",
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"scenario.logic(validation_window=1000)"
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"#scenario = Scenario()\n",
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"#scenario.logic(validation_window=1000)"
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]
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},
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{
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8
main.py
8
main.py
@ -1,7 +1,7 @@
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#!/usr/bin/env python
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# coding: utf-8
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# In[3]:
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# In[4]:
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from datetime import datetime
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@ -109,12 +109,12 @@ class Scenario:
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# In[2]:
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# In[5]:
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# Instantiate and execute logic
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scenario = Scenario()
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scenario.logic(validation_window=1000)
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#scenario = Scenario()
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#scenario.logic(validation_window=1000)
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# In[ ]:
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