f925dff46b
- Added dingdanliu_nb_mflow for improved order processing - Updated related scripts and configurations to support new functionality
250 lines
11 KiB
Plaintext
250 lines
11 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "1a846b12",
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"metadata": {},
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"source": [
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"from ssquant.SQDATA import TakeData\n",
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"\n",
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"#注意首先需要pip install ssquant\n",
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"#否则链接不到数据库\n",
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"#输入俱乐部的账号密码即可调用，注意保密。\n",
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"#目前数据是2019年1月-至今\n",
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"#每日下午收盘后3点30分录入当天数据。\n",
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"#有任何疑问可以再群里提出，或者私信我(慕金龙)\n",
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"#官网: quant789.com\n",
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"#公众号：松鼠Quant\n",
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"#客服微信: viquant01\n",
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"\n",
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"#只能调取分钟及以上数据，tick数据每月底更新到百度网盘下载\n",
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"\n",
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"'''\n",
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"获取数据-\n",
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"品种:symbol,不区分大小写\n",
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"起始时间:start_date,\n",
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"结束时间:end_date(包含当天),\n",
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"周期kline_period:1M..5M..NM(分钟),1D(天),1W(周),1Y(月)\n",
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"复权adjust_type:0(不复权)1(后复权)\n",
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"注意：\n",
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"1.请正确输入账号密码\n",
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"2.不要挂代理访问数据库\n",
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"3.暂时没有股指数据，下个月补齐。\n",
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"'''\n",
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" \n",
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"# username='俱乐部账号' password='密码'\n",
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"client = TakeData(username='240884432@qq.com', password='7777')\n",
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"data = client.get_data(\n",
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" symbol='rb888',\n",
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" start_date='2023-01-02',\n",
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" end_date='2024-01-03',\n",
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" kline_period='60M',\n",
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" adjust_type=1\n",
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")\n",
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"print(data)\n",
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"\n",
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"\n",
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"\n",
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"'''\n",
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"datetime:时间,\n",
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"\n",
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"symbol:品种,\n",
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"\n",
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"open:开盘价,\n",
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"\n",
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"high:最高价,\n",
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"\n",
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"low:最低价,\n",
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"\n",
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"close:收盘价,\n",
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"\n",
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"volume:成交量(单bar),\n",
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"\n",
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"amount:成交金额(单bar),\n",
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"\n",
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"openint:持仓量(单bar),\n",
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"\n",
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"cumulative_openint:累计持仓量，\n",
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"\n",
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"open_bidp , open_askp: K线第一个价格的买一价格和卖一价格\n",
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"\n",
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"close_bidp , close_askp: K线最后一个价格的买一价格和卖一价格\n",
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"\n",
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"\n",
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" datetime symbol open high low close volume amount cumulative_openint openint open_bidp open_askp close_bidp close_askp\n",
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"0 2023-01-03 10:00:00 rb2305 4081.0 4081.0 4016.0 4037.0 737537 29782187220 1883481 -48415 4081.0 4084.0 4037.0 4038.0\n",
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"1 2023-01-03 11:00:00 rb2305 4038.0 4056.0 4037.0 4042.0 158548 6415696920 1887716 4235 4037.0 4038.0 4042.0 4044.0\n",
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"2 2023-01-03 12:00:00 rb2305 4044.0 4054.0 4037.0 4051.0 67448 2728130300 1890125 2409 4043.0 4044.0 4050.0 4051.0\n",
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"3 2023-01-03 14:00:00 rb2305 4055.0 4065.0 4045.0 4058.0 110181 4469698600 1895841 5723 4050.0 4051.0 4058.0 4059.0\n",
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"4 2023-01-03 15:00:00 rb2305 4059.0 4074.0 4056.0 4063.0 167932 6824213940 1882723 -13125 4058.0 4059.0 4062.0 4063.0\n",
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"... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n",
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"1689 2024-01-03 12:00:00 rb2405 4055.0 4057.0 4044.0 4049.0 79745 3229361570 1597387 -6515 4054.0 4055.0 4049.0 4050.0\n",
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"1690 2024-01-03 14:00:00 rb2405 4050.0 4056.0 4046.0 4049.0 55040 2229498750 1598566 1179 4050.0 4051.0 4049.0 4050.0\n",
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"1691 2024-01-03 15:00:00 rb2405 4050.0 4064.0 4048.0 4055.0 148845 6038835190 1583796 -14770 4049.0 4050.0 4055.0 4056.0\n",
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"1692 2024-01-03 22:00:00 rb2405 4054.0 4054.0 4040.0 4049.0 181753 7354584770 1582419 990 4053.0 4054.0 4048.0 4049.0\n",
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"1693 2024-01-03 23:00:00 rb2405 4049.0 4057.0 4042.0 4049.0 104712 4240341050 1574287 -8132 4048.0 4049.0 4049.0 4050.0\n",
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"'''"
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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": 9,
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"id": "65b4b7aa",
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"metadata": {},
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"outputs": [],
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"source": [
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"from ssquant.SQDATA import TakeData\n",
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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": 10,
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"id": "edd4f1e5",
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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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" datetime symbol open high low close volume \\\n",
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"0 2023-01-03 10:00:00 rb2305 4081 4081 4016 4037 737537 \n",
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"1 2023-01-03 11:00:00 rb2305 4038 4056 4037 4042 158548 \n",
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"2 2023-01-03 12:00:00 rb2305 4044 4054 4037 4051 67448 \n",
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"3 2023-01-03 14:00:00 rb2305 4055 4065 4045 4058 110181 \n",
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"4 2023-01-03 15:00:00 rb2305 4059 4074 4056 4063 167932 \n",
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".. ... ... ... ... ... ... ... \n",
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"112 2023-02-01 12:00:00 rb2305 4126 4129 4105 4107 193291 \n",
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"113 2023-02-01 14:00:00 rb2305 4108 4117 4100 4109 137182 \n",
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"114 2023-02-01 15:00:00 rb2305 4109 4114 4075 4084 378930 \n",
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"115 2023-02-01 22:00:00 rb2305 4092 4104 4087 4103 207519 \n",
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"116 2023-02-01 23:00:00 rb2305 4102 4109 4075 4098 189724 \n",
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"\n",
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" amount cumulative_openint openint open_bidp open_askp \\\n",
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"0 29782187220 1883481 -48415 4081 4084 \n",
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"1 6415696920 1887716 4235 4037 4038 \n",
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"2 2728130300 1890125 2409 4043 4044 \n",
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"3 4469698600 1895841 5723 4050 4051 \n",
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"4 6824213940 1882723 -13125 4058 4059 \n",
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".. ... ... ... ... ... \n",
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"112 7954826320 1984919 3490 4125 4126 \n",
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"113 5634834380 1998312 13394 4108 4109 \n",
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"114 15503896450 1994915 -3398 4109 4110 \n",
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"115 8500232870 1988628 -5587 4091 4092 \n",
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"116 7757206650 1973544 -15099 4101 4102 \n",
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"\n",
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" close_bidp close_askp \n",
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"0 4037 4038 \n",
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"1 4042 4044 \n",
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"2 4050 4051 \n",
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"3 4058 4059 \n",
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"4 4062 4063 \n",
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".. ... ... \n",
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"112 4106 4107 \n",
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"113 4108 4109 \n",
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"114 4084 4085 \n",
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"115 4102 4103 \n",
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"116 4098 4099 \n",
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"\n",
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"[117 rows x 14 columns]\n"
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]
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}
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],
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"source": [
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"client = TakeData(username='240884432@qq.com', password='Zj123!@#')\n",
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"data = client.get_data(\n",
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" symbol='rb888',\n",
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" start_date='2023-01-01',\n",
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" end_date='2023-02-01',\n",
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" kline_period='60M',\n",
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" adjust_type=1\n",
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")\n",
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"print(data)\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": 11,
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"id": "25c70609",
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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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" symbol open high low close volume amount \\\n",
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"datetime \n",
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"2023-01-03 10:00:00 rb2305 4081 4081 4016 4037 737537 29782187220 \n",
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"2023-01-03 11:00:00 rb2305 4038 4056 4037 4042 158548 6415696920 \n",
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"2023-01-03 12:00:00 rb2305 4044 4054 4037 4051 67448 2728130300 \n",
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"2023-01-03 14:00:00 rb2305 4055 4065 4045 4058 110181 4469698600 \n",
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"2023-01-03 15:00:00 rb2305 4059 4074 4056 4063 167932 6824213940 \n",
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"... ... ... ... ... ... ... ... \n",
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"2023-02-01 12:00:00 rb2305 4126 4129 4105 4107 193291 7954826320 \n",
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"2023-02-01 14:00:00 rb2305 4108 4117 4100 4109 137182 5634834380 \n",
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"2023-02-01 15:00:00 rb2305 4109 4114 4075 4084 378930 15503896450 \n",
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"2023-02-01 22:00:00 rb2305 4092 4104 4087 4103 207519 8500232870 \n",
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"2023-02-01 23:00:00 rb2305 4102 4109 4075 4098 189724 7757206650 \n",
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"\n",
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" cumulative_openint openint open_bidp open_askp \\\n",
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"datetime \n",
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"2023-01-03 10:00:00 1883481 -48415 4081 4084 \n",
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"2023-01-03 11:00:00 1887716 4235 4037 4038 \n",
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"2023-01-03 12:00:00 1890125 2409 4043 4044 \n",
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"2023-01-03 14:00:00 1895841 5723 4050 4051 \n",
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"2023-01-03 15:00:00 1882723 -13125 4058 4059 \n",
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"... ... ... ... ... \n",
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"2023-02-01 12:00:00 1984919 3490 4125 4126 \n",
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"2023-02-01 14:00:00 1998312 13394 4108 4109 \n",
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"2023-02-01 15:00:00 1994915 -3398 4109 4110 \n",
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"2023-02-01 22:00:00 1988628 -5587 4091 4092 \n",
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"2023-02-01 23:00:00 1973544 -15099 4101 4102 \n",
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"\n",
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" close_bidp close_askp \n",
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"datetime \n",
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"2023-01-03 10:00:00 4037 4038 \n",
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"2023-01-03 11:00:00 4042 4044 \n",
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"2023-01-03 12:00:00 4050 4051 \n",
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"2023-01-03 14:00:00 4058 4059 \n",
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"2023-01-03 15:00:00 4062 4063 \n",
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"... ... ... \n",
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"2023-02-01 12:00:00 4106 4107 \n",
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"2023-02-01 14:00:00 4108 4109 \n",
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"2023-02-01 15:00:00 4084 4085 \n",
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"2023-02-01 22:00:00 4102 4103 \n",
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"2023-02-01 23:00:00 4098 4099 \n",
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"\n",
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"[117 rows x 13 columns]\n"
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]
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}
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],
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"source": [
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"data.set_index(\"datetime\", inplace=True)\n",
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"data.index = pd.to_datetime(data.index)\n",
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"print(data)"
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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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"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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"version": 3
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},
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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": "3.10.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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