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Examples: Add get-trading-hours, get-chart-range-request and get-chart-last-request
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‎examples/get-chart-last-request.ipynb

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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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"source": [
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"import json\n",
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"with open(\"../credentials.json\", \"r\") as f:\n",
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" CREDENTIALS = json.load(f)"
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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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"from datetime import datetime as dt\n",
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"START = round(dt.today().replace(month=1, day=1).timestamp() * 1000) # 1st January of the current year\n",
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"END = round(dt.today().timestamp() * 1000) # Today (current date)"
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"import xapi\n",
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"x = await xapi.connect(**CREDENTIALS)\n",
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"result = await x.socket.getChartLastRequest(\"EURUSD\", START, xapi.PeriodCode.PERIOD_D1)\n",
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"if result[\"status\"] == True:\n",
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" rateInfos = result[\"returnData\"]['rateInfos']"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"df = pd.DataFrame(rateInfos)\n",
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"df['open'] /= 1000\n",
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"for column in ['close', 'high', 'low']:\n",
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" df[column] = df['open'] + df[column] / 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": 7,
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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>ctm</th>\n",
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" <th>ctmString</th>\n",
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" <th>open</th>\n",
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" <th>close</th>\n",
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" <th>high</th>\n",
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" <th>low</th>\n",
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" <th>vol</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>0</th>\n",
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" <td>1704150000000</td>\n",
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" <td>Jan 2, 2024, 12:00:00 AM</td>\n",
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" <td>110.443</td>\n",
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" <td>109.406</td>\n",
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" <td>110.443</td>\n",
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" <td>109.380</td>\n",
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" <td>607082.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>1704236400000</td>\n",
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" <td>Jan 3, 2024, 12:00:00 AM</td>\n",
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" <td>109.411</td>\n",
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" <td>109.209</td>\n",
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" <td>109.650</td>\n",
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" <td>108.926</td>\n",
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" <td>630593.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>1704322800000</td>\n",
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" <td>Jan 4, 2024, 12:00:00 AM</td>\n",
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" <td>109.209</td>\n",
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" <td>109.467</td>\n",
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" <td>109.717</td>\n",
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" <td>109.158</td>\n",
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" <td>564061.0</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>1704409200000</td>\n",
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" <td>Jan 5, 2024, 12:00:00 AM</td>\n",
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" <td>109.470</td>\n",
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" <td>109.387</td>\n",
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" <td>109.979</td>\n",
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" <td>108.763</td>\n",
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" <td>749938.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>1704582000000</td>\n",
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" <td>Jan 7, 2024, 12:00:00 AM</td>\n",
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" <td>109.345</td>\n",
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" <td>109.440</td>\n",
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" <td>109.447</td>\n",
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" <td>109.335</td>\n",
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" <td>0.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>208</th>\n",
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" <td>1725141600000</td>\n",
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" <td>Sep 1, 2024, 12:00:00 AM</td>\n",
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" <td>110.407</td>\n",
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" <td>110.478</td>\n",
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" <td>110.494</td>\n",
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" <td>110.402</td>\n",
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" <td>0.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>209</th>\n",
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" <td>1725228000000</td>\n",
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" <td>Sep 2, 2024, 12:00:00 AM</td>\n",
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" <td>110.477</td>\n",
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" <td>110.699</td>\n",
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" <td>110.771</td>\n",
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" <td>110.416</td>\n",
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" <td>220155.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>210</th>\n",
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" <td>1725314400000</td>\n",
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" <td>Sep 3, 2024, 12:00:00 AM</td>\n",
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" <td>110.699</td>\n",
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" <td>110.447</td>\n",
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" <td>110.724</td>\n",
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" <td>110.260</td>\n",
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" <td>484804.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>211</th>\n",
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" <td>1725400800000</td>\n",
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" <td>Sep 4, 2024, 12:00:00 AM</td>\n",
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" <td>110.450</td>\n",
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" <td>110.824</td>\n",
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" <td>110.949</td>\n",
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" <td>110.389</td>\n",
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" <td>472459.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>212</th>\n",
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" <td>1725487200000</td>\n",
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" <td>Sep 5, 2024, 12:00:00 AM</td>\n",
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" <td>110.833</td>\n",
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" <td>110.806</td>\n",
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" <td>111.194</td>\n",
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" <td>110.744</td>\n",
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" <td>362370.0</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>213 rows × 7 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" ctm ctmString open close high \\\n",
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"0 1704150000000 Jan 2, 2024, 12:00:00 AM 110.443 109.406 110.443 \n",
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"1 1704236400000 Jan 3, 2024, 12:00:00 AM 109.411 109.209 109.650 \n",
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"2 1704322800000 Jan 4, 2024, 12:00:00 AM 109.209 109.467 109.717 \n",
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"3 1704409200000 Jan 5, 2024, 12:00:00 AM 109.470 109.387 109.979 \n",
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"4 1704582000000 Jan 7, 2024, 12:00:00 AM 109.345 109.440 109.447 \n",
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".. ... ... ... ... ... \n",
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"208 1725141600000 Sep 1, 2024, 12:00:00 AM 110.407 110.478 110.494 \n",
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"209 1725228000000 Sep 2, 2024, 12:00:00 AM 110.477 110.699 110.771 \n",
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"210 1725314400000 Sep 3, 2024, 12:00:00 AM 110.699 110.447 110.724 \n",
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"211 1725400800000 Sep 4, 2024, 12:00:00 AM 110.450 110.824 110.949 \n",
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"212 1725487200000 Sep 5, 2024, 12:00:00 AM 110.833 110.806 111.194 \n",
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"\n",
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" low vol \n",
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"0 109.380 607082.0 \n",
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"1 108.926 630593.0 \n",
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"2 109.158 564061.0 \n",
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"3 108.763 749938.0 \n",
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"4 109.335 0.0 \n",
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".. ... ... \n",
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"208 110.402 0.0 \n",
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"209 110.416 220155.0 \n",
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"210 110.260 484804.0 \n",
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"211 110.389 472459.0 \n",
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"212 110.744 362370.0 \n",
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"\n",
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"[213 rows x 7 columns]"
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]
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},
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"execution_count": 7,
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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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"df"
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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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"metadata": {},
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"outputs": [],
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"source": []
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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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"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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"kernelspec": {
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.10"
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"nbformat": 4,
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"nbformat_minor": 2
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}

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