{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 公司股价预测作业" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 作业要求：\n", "设计一个预测股票价格的方法，并用实例证明此方法的有效性。 \n", "所给的数据，要求全部都要使用，注意 \n", "1. 数据需清洗 \n", "2. 特征综合使用 \n", "\n", "可自己额外补充资源或数据" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 基础得分点\n", "1.\t程序可运行\n", "2.\t缺失数据处理\n", "3.\t正则提取\n", "4.\t时间信息转换\n", "5.\t数据拼接\n", "6.\t数据标准化\n", "7.\t数据可视化\n", "8.\t模型构建与应用\n", "9.\tMarkdown 排版\n", "10.\t分析逻辑" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 数据说明\n", "1.\t**全标题** \n", " 这是股票平台上发布的对各公司的分析文章\n", " 1. 标题：文章的标题\n", " 1. 字段1_链接_链接：原文章所在的URL\n", " 1. ABOUT：文章针对的公司，都为缩写形式，多个公司以逗号隔开\n", " 1. TIME：文章发布的时间\n", " 1. AUTHOR：作者\n", " 1. COMMENTS：采集时，文章的被评论次数\n", "2.\t**摘要** \n", " 这是股票平台上发布的对各公司的分析文章的摘要部分，**和“全标题”中的内容对应** \n", " 1. 标题：文章的标题 \n", " 1. 字段2：文章发布的时间 \n", " 1. 字段5：文章针对的公司及提及的公司； \n", " 1. About为针对公司，都提取缩写的大写模型，多个公司以逗号隔开 \n", " 1. include为提及的其它公司，都提取缩写的大写模型，多个公司以逗号隔开 \n", " 1. 字段1：摘要的全文字内容 \n", "3.\t**回帖** \n", " 这是网友在各文章下的回复内容 \n", " 1. Title：各文章的标题；空标题的，用最靠近的有内容的下方标题 \n", " 1. Content：回复的全文字内容 \n", "4.\t**论坛** \n", " 这是网友在各公司的论坛页面下，对之进行评论的发帖内容 \n", " 1. 字段1：作者 \n", " 1. 字段2：发帖日期 \n", " 1. 字段3：帖子内容 \n", " 1. 字段4_链接：具体的各公司的页面URL \n", "5.\t**股票价格**\n", " 为各公司工作日股票的价格 \n", " 1. PERMNO：公司编号 \n", " 1. Date：日期 \n", " 1. TICKER：公司简写 \n", " 1. COMNAM：公司全写 \n", " 1. BIDLO：最低价 \n", " 1. ASKHI：最高价 \n", " 1. PRC：收盘价 \n", " 1. VOL：成交量 \n", " 1. OPENPRC：开盘价 " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 一、文件格式统一\n", "显然，提供的文件中有`xlsx`格式的，也有`csv`格式的。 \n", "而`csv`格式的操作行为明显速度和效率上明显优于`xlsx`格式，因此在这里我们将所有格式统一为`csv`格式。" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:48.873911Z", "start_time": "2020-06-30T13:03:46.090417Z" } }, "outputs": [], "source": [ "import os\n", "import pandas as pd\n", "import numpy as np\n", "\n", "\n", "# 转化函数，其实没有必要转化为函数，毕竟只用一次\n", "def xlsx_to_csv_pd(path):\n", " for root, dirs, files in os.walk(path):\n", " for file in files:\n", " if(file.endswith('.xlsx')):\n", " # 获取文件路径\n", " data_xls = pd.read_excel(os.path.join(root, file), index_col=0)\n", " data_xls.to_csv(os.path.join(root, file).replace(\n", " '.xlsx', '.csv'), encoding='utf-8')\n", " print(os.path.join(root, file), \"转化成功\")\n", " os.remove(os.path.join(root, file))\n", "\n", "\n", "# 批量转化\n", "xlsx_to_csv_pd(os.getcwd())" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-06-20T07:01:50.232528Z", "start_time": "2020-06-20T07:01:50.228539Z" } }, "source": [ "# 二、数据清洗" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.1 全标题摘要聚合\n", "股票平台上发布的对各公司的分析文章的摘要部分，和“全标题”中的内容对应。 \n", "所以读取全部内容，根据标题和时间以及公司聚合，同时去除原文链接这种对于我来说没用的内容。" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.1.1 读取全标题信息\n", "这是股票平台上发布的对各公司的分析文章\n", "\n", "1. 标题：文章的标题\n", "1. 字段1_链接_链接：原文章所在的URL\n", "1. ABOUT：文章针对的公司，都为缩写形式，多个公司以逗号隔开\n", "1. TIME：文章发布的时间\n", "1. AUTHOR：作者\n", "1. COMMENTS：采集时，文章的被评论次数 \n", "\n", "在这个Section,我们会读取整个csv文件，并且舍弃【字段1_链接_链接】" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:49.222500Z", "start_time": "2020-06-30T13:03:48.877903Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
针对公司发布时间作者评论数
标题
Micron Technology: Insanely Cheap Stock Given Its High Earnings Quality[MU]Dec. 31, 2018, 7:57 PMRuerd Heeg75
Molson Coors Seems Attractive At These Valuations[TAP]Dec. 31, 2018, 7:44 PMSanjit Deepalam16
Gerdau: The Brazilian Play On U.S. Steel[GGB]Dec. 31, 2018, 7:10 PMShannon Bruce1
Will Apple Get Its Mojo Back?[AAPL]Dec. 31, 2018, 5:36 PMTipRanks68
Lululemon Stock Looks Compelling On This Dip[LULU]Dec. 31, 2018, 5:26 PML&F Capital Management4
...............
Overstock: The Perfect Stock Blockchain Play[OSTK]Jan. 1, 2018, 6:54 AMOpaque Investors47
2017: The Year The Unicorn Died[UBER, SFTBF, SFTBY]Jan. 1, 2018, 6:54 AMMark St. Cyr5
Big Changes For Centurylink, AT&T And Verizon In 2018[CTL, T, VZ]Jan. 1, 2018, 5:38 AMEconDad32
UPS: If The Founders Were Alive Today[UPS]Jan. 1, 2018, 5:11 AMRoger Gaebel15
U.S. Silica - Buying The Dip Of This Booming Company[SLCA]Jan. 1, 2018, 12:20 AMThe Value Investor27
\n", "

17928 rows × 4 columns

\n", "
" ], "text/plain": [ " 针对公司 \\\n", "标题 \n", "Micron Technology: Insanely Cheap Stock Given I... [MU] \n", "Molson Coors Seems Attractive At These Valuations [TAP] \n", "Gerdau: The Brazilian Play On U.S. Steel [GGB] \n", "Will Apple Get Its Mojo Back? [AAPL] \n", "Lululemon Stock Looks Compelling On This Dip [LULU] \n", "... ... \n", "Overstock: The Perfect Stock Blockchain Play [OSTK] \n", "2017: The Year The Unicorn Died [UBER, SFTBF, SFTBY] \n", "Big Changes For Centurylink, AT&T And Verizon I... [CTL, T, VZ] \n", "UPS: If The Founders Were Alive Today [UPS] \n", "U.S. Silica - Buying The Dip Of This Booming Co... [SLCA] \n", "\n", " 发布时间 \\\n", "标题 \n", "Micron Technology: Insanely Cheap Stock Given I... Dec. 31, 2018, 7:57 PM \n", "Molson Coors Seems Attractive At These Valuations Dec. 31, 2018, 7:44 PM \n", "Gerdau: The Brazilian Play On U.S. Steel Dec. 31, 2018, 7:10 PM \n", "Will Apple Get Its Mojo Back? Dec. 31, 2018, 5:36 PM \n", "Lululemon Stock Looks Compelling On This Dip Dec. 31, 2018, 5:26 PM \n", "... ... \n", "Overstock: The Perfect Stock Blockchain Play Jan. 1, 2018, 6:54 AM \n", "2017: The Year The Unicorn Died Jan. 1, 2018, 6:54 AM \n", "Big Changes For Centurylink, AT&T And Verizon I... Jan. 1, 2018, 5:38 AM \n", "UPS: If The Founders Were Alive Today Jan. 1, 2018, 5:11 AM \n", "U.S. Silica - Buying The Dip Of This Booming Co... Jan. 1, 2018, 12:20 AM \n", "\n", " 作者 \\\n", "标题 \n", "Micron Technology: Insanely Cheap Stock Given I... Ruerd Heeg \n", "Molson Coors Seems Attractive At These Valuations Sanjit Deepalam \n", "Gerdau: The Brazilian Play On U.S. Steel Shannon Bruce \n", "Will Apple Get Its Mojo Back? TipRanks \n", "Lululemon Stock Looks Compelling On This Dip L&F Capital Management \n", "... ... \n", "Overstock: The Perfect Stock Blockchain Play Opaque Investors \n", "2017: The Year The Unicorn Died Mark St. Cyr \n", "Big Changes For Centurylink, AT&T And Verizon I... EconDad \n", "UPS: If The Founders Were Alive Today Roger Gaebel \n", "U.S. Silica - Buying The Dip Of This Booming Co... The Value Investor \n", "\n", " 评论数 \n", "标题 \n", "Micron Technology: Insanely Cheap Stock Given I... 75 \n", "Molson Coors Seems Attractive At These Valuations 16 \n", "Gerdau: The Brazilian Play On U.S. Steel 1 \n", "Will Apple Get Its Mojo Back? 68 \n", "Lululemon Stock Looks Compelling On This Dip 4 \n", "... .. \n", "Overstock: The Perfect Stock Blockchain Play 47 \n", "2017: The Year The Unicorn Died 5 \n", "Big Changes For Centurylink, AT&T And Verizon I... 32 \n", "UPS: If The Founders Were Alive Today 15 \n", "U.S. Silica - Buying The Dip Of This Booming Co... 27 \n", "\n", "[17928 rows x 4 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 读取整个csv文件，并且舍弃【字段1_链接_链接】\n", "Title_data = pd.read_csv(\"./全标题.csv\", index_col=0, usecols=[0, 2, 3, 4, 5])\n", "\n", "# 更改列标\n", "Title_data.columns = ['针对公司', '发布时间', '作者', '评论数']\n", "\n", "# 评论数去除Comments无用字段\n", "Title_data[\"评论数\"] = Title_data[\"评论数\"].str.extract(\"([0-9]+)\")\n", "\n", "# 针对公司处理\n", "Title_data[\"针对公司\"] = Title_data[\"针对公司\"].str.replace(\" \", \"\")\n", "Title_data[\"针对公司\"] = Title_data[\"针对公司\"].str.split(\",\")\n", "\n", "# 显示内容\n", "Title_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.1.2 读取摘要信息\n", "\n", "这是股票平台上发布的对各公司的分析文章的摘要部分，**和“全标题”中的内容对应** \n", "1. 标题：文章的标题 \n", "1. 字段2：文章发布的时间 \n", "1. 字段5：文章针对的公司及提及的公司； \n", " 1. About为针对公司，都提取缩写的大写模型，多个公司以逗号隔开 \n", " 1. include为提及的其它公司，都提取缩写的大写模型，多个公司以逗号隔开 \n", "1. 字段1：摘要的全文字内容 " ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:49.594504Z", "start_time": "2020-06-30T13:03:49.226491Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
发布时间针对公司摘要
标题
HealthEquity: Strong Growth May Be Slowing Heading Into 2021Apr. 1, 2019 10:46 PM[HQY]SummaryHealthEquity’s revenue and earnings hav...
Valero May Rally Up To 40% Within The Next 12 MonthsApr. 1, 2019 10:38 PM[VLO]SummaryValero is ideally positioned to benefit...
Apple Makes A China MoveApr. 1, 2019 7:21 PM[AAPL]SummaryCompany cuts prices on many key product...
Polaris Industries: Ready To RallyApr. 1, 2019 7:14 PM[PII]SummaryPolaris is a well-respected brand name ...
How Apple Will Return A Minimum Of 8% By The End Of FY19Apr. 1, 2019 5:03 PM[AAPL]SummaryApple has exhibited strong segment grow...
............
Cushman & Wakefield Proposes Terms For $765 Million IPOJul. 24, 2018 2:18 PM[CWK]SummaryCushman & Wakefield has filed proposed ...
Quantamental Focus: Home Depot A Top Buy, With Improving Operating ProfitabilityJul. 24, 2018 2:16 PM[HD]SummaryHome Depot Inc. is a specialty retailer...
Rubicon Technology: A Promising Net-Net Cash-Box SituationJul. 24, 2018 2:16 PM[RBCN]SummaryRubicon is trading well below likely li...
Stamps.com: A Cash MachineJul. 24, 2018 1:57 PM[STMP]SummaryThe Momentum Growth Quotient for the co...
Can Heineken Turn The 'Mallya Drama' In Its Own Favor?Jul. 24, 2018 1:24 PM[HEINY]SummaryMallya, United Breweries' chairman, can...
\n", "

10131 rows × 3 columns

\n", "
" ], "text/plain": [ " 发布时间 \\\n", "标题 \n", "HealthEquity: Strong Growth May Be Slowing Head... Apr. 1, 2019 10:46 PM \n", "Valero May Rally Up To 40% Within The Next 12 M... Apr. 1, 2019 10:38 PM \n", "Apple Makes A China Move Apr. 1, 2019 7:21 PM \n", "Polaris Industries: Ready To Rally Apr. 1, 2019 7:14 PM \n", "How Apple Will Return A Minimum Of 8% By The En... Apr. 1, 2019 5:03 PM \n", "... ... \n", "Cushman & Wakefield Proposes Terms For $765 Mil... Jul. 24, 2018 2:18 PM \n", "Quantamental Focus: Home Depot A Top Buy, With ... Jul. 24, 2018 2:16 PM \n", "Rubicon Technology: A Promising Net-Net Cash-Bo... Jul. 24, 2018 2:16 PM \n", "Stamps.com: A Cash Machine Jul. 24, 2018 1:57 PM \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... Jul. 24, 2018 1:24 PM \n", "\n", " 针对公司 \\\n", "标题 \n", "HealthEquity: Strong Growth May Be Slowing Head... [HQY] \n", "Valero May Rally Up To 40% Within The Next 12 M... [VLO] \n", "Apple Makes A China Move [AAPL] \n", "Polaris Industries: Ready To Rally [PII] \n", "How Apple Will Return A Minimum Of 8% By The En... [AAPL] \n", "... ... \n", "Cushman & Wakefield Proposes Terms For $765 Mil... [CWK] \n", "Quantamental Focus: Home Depot A Top Buy, With ... [HD] \n", "Rubicon Technology: A Promising Net-Net Cash-Bo... [RBCN] \n", "Stamps.com: A Cash Machine [STMP] \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... [HEINY] \n", "\n", " 摘要 \n", "标题 \n", "HealthEquity: Strong Growth May Be Slowing Head... SummaryHealthEquity’s revenue and earnings hav... \n", "Valero May Rally Up To 40% Within The Next 12 M... SummaryValero is ideally positioned to benefit... \n", "Apple Makes A China Move SummaryCompany cuts prices on many key product... \n", "Polaris Industries: Ready To Rally SummaryPolaris is a well-respected brand name ... \n", "How Apple Will Return A Minimum Of 8% By The En... SummaryApple has exhibited strong segment grow... \n", "... ... \n", "Cushman & Wakefield Proposes Terms For $765 Mil... SummaryCushman & Wakefield has filed proposed ... \n", "Quantamental Focus: Home Depot A Top Buy, With ... SummaryHome Depot Inc. is a specialty retailer... \n", "Rubicon Technology: A Promising Net-Net Cash-Bo... SummaryRubicon is trading well below likely li... \n", "Stamps.com: A Cash Machine SummaryThe Momentum Growth Quotient for the co... \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... SummaryMallya, United Breweries' chairman, can... \n", "\n", "[10131 rows x 3 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 读取整个csv文件，并且舍弃【字段1_链接_链接】\n", "import re\n", "Content_data = pd.read_csv(\"./摘要.csv\", index_col=0)\n", "\n", "# 更改列标\n", "Content_data.columns = ['发布时间', '针对公司', '摘要']\n", "\n", "# 处理【时间】\n", "Content_data[\"发布时间\"] = Content_data[\"发布时间\"].map(lambda x: x.replace(\" ET\", \"\"))\n", "\n", "\n", "# 处理【针对公司】\n", "Content_data[\"针对公司\"] = Content_data[\"针对公司\"].map(\n", " lambda x: x.split(\"Includes:\")[0].replace(\"| About: \", \"\").split(\",\"))\n", "# 提取【针对公司】中的简写\n", "Content_data[\"针对公司\"] = Content_data[\"针对公司\"].map(\n", " lambda x: [\"\".join(re.findall('[(](.*?)[)]', i, re.S)) for i in x if not i.find(\"(\") == -1])\n", "\n", "# 显示前五行内容\n", "Content_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.1.3 合并两表" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:54.208850Z", "start_time": "2020-06-30T13:03:49.598494Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
标题作者评论数摘要针对公司发布时间
Micron Technology: Insanely Cheap Stock Given Its High Earnings QualityMicron Technology: Insanely Cheap Stock Given ...Ruerd Heeg75SummaryLast year, a combination of relatively ...MUDec. 31, 2018 7:57 PM
Molson Coors Seems Attractive At These ValuationsMolson Coors Seems Attractive At These ValuationsSanjit Deepalam16SummaryMolson Coors's stock has fallen over 30...TAPDec. 31, 2018 7:44 PM
Gerdau: The Brazilian Play On U.S. SteelGerdau: The Brazilian Play On U.S. SteelShannon Bruce1SummaryGerdau is delivering good results, incl...GGBDec. 31, 2018 7:10 PM
Will Apple Get Its Mojo Back?Will Apple Get Its Mojo Back?TipRanks68SummaryApple has been resting on a reputation ...AAPLDec. 31, 2018 5:36 PM
Lululemon Stock Looks Compelling On This DipLululemon Stock Looks Compelling On This DipL&F Capital Management4SummaryLululemon stock had a strong 2018 but f...LULUDec. 31, 2018 5:26 PM
.....................
Stamps.com: A Cash MachineStamps.com: A Cash MachineChartMasterPro1SummaryThe Momentum Growth Quotient for the co...STMPJul. 24, 2018 1:57 PM
Can Heineken Turn The 'Mallya Drama' In Its Own Favor?Can Heineken Turn The 'Mallya Drama' In Its Ow...The Millennial Investor4SummaryMallya, United Breweries' chairman, can...HEINYJul. 24, 2018 1:24 PM
Thor Industries Is UndervaluedThor Industries Is UndervaluedQuinn Foley22SummaryThor and other RV makers became signifi...THOFeb. 4, 2019 8:19 AM
Xinyuan Real Estate: The Path Is Becoming ClearerXinyuan Real Estate: The Path Is Becoming ClearerWG Investment Research6SummaryXinyuan's stock has performed well so f...XINFeb. 19, 2019 12:00 PM
Lockheed Martin: The Sky Is The LimitLockheed Martin: The Sky Is The LimitMichael J. Bernard56SummaryLockheed Martin exhibits strong competi...LMTFeb. 13, 2019 3:22 PM
\n", "

5898 rows × 6 columns

\n", "
" ], "text/plain": [ " 标题 \\\n", "Micron Technology: Insanely Cheap Stock Given I... Micron Technology: Insanely Cheap Stock Given ... \n", "Molson Coors Seems Attractive At These Valuations Molson Coors Seems Attractive At These Valuations \n", "Gerdau: The Brazilian Play On U.S. Steel Gerdau: The Brazilian Play On U.S. Steel \n", "Will Apple Get Its Mojo Back? Will Apple Get Its Mojo Back? \n", "Lululemon Stock Looks Compelling On This Dip Lululemon Stock Looks Compelling On This Dip \n", "... ... \n", "Stamps.com: A Cash Machine Stamps.com: A Cash Machine \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... Can Heineken Turn The 'Mallya Drama' In Its Ow... \n", "Thor Industries Is Undervalued Thor Industries Is Undervalued \n", "Xinyuan Real Estate: The Path Is Becoming Clearer Xinyuan Real Estate: The Path Is Becoming Clearer \n", "Lockheed Martin: The Sky Is The Limit Lockheed Martin: The Sky Is The Limit \n", "\n", " 作者 \\\n", "Micron Technology: Insanely Cheap Stock Given I... Ruerd Heeg \n", "Molson Coors Seems Attractive At These Valuations Sanjit Deepalam \n", "Gerdau: The Brazilian Play On U.S. Steel Shannon Bruce \n", "Will Apple Get Its Mojo Back? TipRanks \n", "Lululemon Stock Looks Compelling On This Dip L&F Capital Management \n", "... ... \n", "Stamps.com: A Cash Machine ChartMasterPro \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... The Millennial Investor \n", "Thor Industries Is Undervalued Quinn Foley \n", "Xinyuan Real Estate: The Path Is Becoming Clearer WG Investment Research \n", "Lockheed Martin: The Sky Is The Limit Michael J. Bernard \n", "\n", " 评论数 \\\n", "Micron Technology: Insanely Cheap Stock Given I... 75 \n", "Molson Coors Seems Attractive At These Valuations 16 \n", "Gerdau: The Brazilian Play On U.S. Steel 1 \n", "Will Apple Get Its Mojo Back? 68 \n", "Lululemon Stock Looks Compelling On This Dip 4 \n", "... .. \n", "Stamps.com: A Cash Machine 1 \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... 4 \n", "Thor Industries Is Undervalued 22 \n", "Xinyuan Real Estate: The Path Is Becoming Clearer 6 \n", "Lockheed Martin: The Sky Is The Limit 56 \n", "\n", " 摘要 \\\n", "Micron Technology: Insanely Cheap Stock Given I... SummaryLast year, a combination of relatively ... \n", "Molson Coors Seems Attractive At These Valuations SummaryMolson Coors's stock has fallen over 30... \n", "Gerdau: The Brazilian Play On U.S. Steel SummaryGerdau is delivering good results, incl... \n", "Will Apple Get Its Mojo Back? SummaryApple has been resting on a reputation ... \n", "Lululemon Stock Looks Compelling On This Dip SummaryLululemon stock had a strong 2018 but f... \n", "... ... \n", "Stamps.com: A Cash Machine SummaryThe Momentum Growth Quotient for the co... \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... SummaryMallya, United Breweries' chairman, can... \n", "Thor Industries Is Undervalued SummaryThor and other RV makers became signifi... \n", "Xinyuan Real Estate: The Path Is Becoming Clearer SummaryXinyuan's stock has performed well so f... \n", "Lockheed Martin: The Sky Is The Limit SummaryLockheed Martin exhibits strong competi... \n", "\n", " 针对公司 \\\n", "Micron Technology: Insanely Cheap Stock Given I... MU \n", "Molson Coors Seems Attractive At These Valuations TAP \n", "Gerdau: The Brazilian Play On U.S. Steel GGB \n", "Will Apple Get Its Mojo Back? AAPL \n", "Lululemon Stock Looks Compelling On This Dip LULU \n", "... ... \n", "Stamps.com: A Cash Machine STMP \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... HEINY \n", "Thor Industries Is Undervalued THO \n", "Xinyuan Real Estate: The Path Is Becoming Clearer XIN \n", "Lockheed Martin: The Sky Is The Limit LMT \n", "\n", " 发布时间 \n", "Micron Technology: Insanely Cheap Stock Given I... Dec. 31, 2018 7:57 PM \n", "Molson Coors Seems Attractive At These Valuations Dec. 31, 2018 7:44 PM \n", "Gerdau: The Brazilian Play On U.S. Steel Dec. 31, 2018 7:10 PM \n", "Will Apple Get Its Mojo Back? Dec. 31, 2018 5:36 PM \n", "Lululemon Stock Looks Compelling On This Dip Dec. 31, 2018 5:26 PM \n", "... ... \n", "Stamps.com: A Cash Machine Jul. 24, 2018 1:57 PM \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... Jul. 24, 2018 1:24 PM \n", "Thor Industries Is Undervalued Feb. 4, 2019 8:19 AM \n", "Xinyuan Real Estate: The Path Is Becoming Clearer Feb. 19, 2019 12:00 PM \n", "Lockheed Martin: The Sky Is The Limit Feb. 13, 2019 3:22 PM \n", "\n", "[5898 rows x 6 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Title_Content_data = pd.merge(\n", " Title_data, Content_data, right_on='标题', left_index=True, how='outer')\n", "\n", "\n", "def UpdateCompany(x):\n", " try:\n", " x[\"针对公司_x\"].extend(x[\"针对公司_y\"])\n", " return \",\".join(np.unique(x[\"针对公司_x\"]))\n", " except:\n", " return np.NAN\n", "\n", "\n", "def UpdateTime(x):\n", " try:\n", " return np.unique([x[\"发布时间_x\"].strip(), x[\"发布时间_y\"].strip()])[0]\n", " except:\n", " return np.NAN\n", "\n", "\n", "Title_Content_data['针对公司'] = Title_Content_data[['针对公司_x', '针对公司_y']].apply(\n", " lambda x: UpdateCompany(x), axis=1)\n", "\n", "Title_Content_data['发布时间'] = Title_Content_data[[\"发布时间_x\", \"发布时间_y\"]].apply(\n", " lambda x: UpdateTime(x), axis=1)\n", "\n", "# pd.to_datetime(df)\n", "\n", "# 删除无用列\n", "Title_Content_data.drop([\"发布时间_x\", \"发布时间_y\"], axis=1, inplace=True)\n", "Title_Content_data.drop([\"针对公司_x\", \"针对公司_y\"], axis=1, inplace=True)\n", "\n", "# 删除无用行\n", "Title_Content_data.dropna(axis=0, how='any', subset=[\n", " \"发布时间\", \"针对公司\", \"评论数\"], inplace=True)\n", "\n", "Title_Content_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.1.4 处理发布时间为标准日期格式" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:54.376403Z", "start_time": "2020-06-30T13:03:54.213841Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
标题作者评论数摘要针对公司发布时间
Micron Technology: Insanely Cheap Stock Given Its High Earnings QualityMicron Technology: Insanely Cheap Stock Given ...Ruerd Heeg75SummaryLast year, a combination of relatively ...MU2018-12-31
Molson Coors Seems Attractive At These ValuationsMolson Coors Seems Attractive At These ValuationsSanjit Deepalam16SummaryMolson Coors's stock has fallen over 30...TAP2018-12-31
Gerdau: The Brazilian Play On U.S. SteelGerdau: The Brazilian Play On U.S. SteelShannon Bruce1SummaryGerdau is delivering good results, incl...GGB2018-12-31
Will Apple Get Its Mojo Back?Will Apple Get Its Mojo Back?TipRanks68SummaryApple has been resting on a reputation ...AAPL2018-12-31
Lululemon Stock Looks Compelling On This DipLululemon Stock Looks Compelling On This DipL&F Capital Management4SummaryLululemon stock had a strong 2018 but f...LULU2018-12-31
.....................
Stamps.com: A Cash MachineStamps.com: A Cash MachineChartMasterPro1SummaryThe Momentum Growth Quotient for the co...STMP2018-07-24
Can Heineken Turn The 'Mallya Drama' In Its Own Favor?Can Heineken Turn The 'Mallya Drama' In Its Ow...The Millennial Investor4SummaryMallya, United Breweries' chairman, can...HEINY2018-07-24
Thor Industries Is UndervaluedThor Industries Is UndervaluedQuinn Foley22SummaryThor and other RV makers became signifi...THO2019-02-04
Xinyuan Real Estate: The Path Is Becoming ClearerXinyuan Real Estate: The Path Is Becoming ClearerWG Investment Research6SummaryXinyuan's stock has performed well so f...XIN2019-02-19
Lockheed Martin: The Sky Is The LimitLockheed Martin: The Sky Is The LimitMichael J. Bernard56SummaryLockheed Martin exhibits strong competi...LMT2019-02-13
\n", "

5898 rows × 6 columns

\n", "
" ], "text/plain": [ " 标题 \\\n", "Micron Technology: Insanely Cheap Stock Given I... Micron Technology: Insanely Cheap Stock Given ... \n", "Molson Coors Seems Attractive At These Valuations Molson Coors Seems Attractive At These Valuations \n", "Gerdau: The Brazilian Play On U.S. Steel Gerdau: The Brazilian Play On U.S. Steel \n", "Will Apple Get Its Mojo Back? Will Apple Get Its Mojo Back? \n", "Lululemon Stock Looks Compelling On This Dip Lululemon Stock Looks Compelling On This Dip \n", "... ... \n", "Stamps.com: A Cash Machine Stamps.com: A Cash Machine \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... Can Heineken Turn The 'Mallya Drama' In Its Ow... \n", "Thor Industries Is Undervalued Thor Industries Is Undervalued \n", "Xinyuan Real Estate: The Path Is Becoming Clearer Xinyuan Real Estate: The Path Is Becoming Clearer \n", "Lockheed Martin: The Sky Is The Limit Lockheed Martin: The Sky Is The Limit \n", "\n", " 作者 \\\n", "Micron Technology: Insanely Cheap Stock Given I... Ruerd Heeg \n", "Molson Coors Seems Attractive At These Valuations Sanjit Deepalam \n", "Gerdau: The Brazilian Play On U.S. Steel Shannon Bruce \n", "Will Apple Get Its Mojo Back? TipRanks \n", "Lululemon Stock Looks Compelling On This Dip L&F Capital Management \n", "... ... \n", "Stamps.com: A Cash Machine ChartMasterPro \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... The Millennial Investor \n", "Thor Industries Is Undervalued Quinn Foley \n", "Xinyuan Real Estate: The Path Is Becoming Clearer WG Investment Research \n", "Lockheed Martin: The Sky Is The Limit Michael J. Bernard \n", "\n", " 评论数 \\\n", "Micron Technology: Insanely Cheap Stock Given I... 75 \n", "Molson Coors Seems Attractive At These Valuations 16 \n", "Gerdau: The Brazilian Play On U.S. Steel 1 \n", "Will Apple Get Its Mojo Back? 68 \n", "Lululemon Stock Looks Compelling On This Dip 4 \n", "... .. \n", "Stamps.com: A Cash Machine 1 \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... 4 \n", "Thor Industries Is Undervalued 22 \n", "Xinyuan Real Estate: The Path Is Becoming Clearer 6 \n", "Lockheed Martin: The Sky Is The Limit 56 \n", "\n", " 摘要 \\\n", "Micron Technology: Insanely Cheap Stock Given I... SummaryLast year, a combination of relatively ... \n", "Molson Coors Seems Attractive At These Valuations SummaryMolson Coors's stock has fallen over 30... \n", "Gerdau: The Brazilian Play On U.S. Steel SummaryGerdau is delivering good results, incl... \n", "Will Apple Get Its Mojo Back? SummaryApple has been resting on a reputation ... \n", "Lululemon Stock Looks Compelling On This Dip SummaryLululemon stock had a strong 2018 but f... \n", "... ... \n", "Stamps.com: A Cash Machine SummaryThe Momentum Growth Quotient for the co... \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... SummaryMallya, United Breweries' chairman, can... \n", "Thor Industries Is Undervalued SummaryThor and other RV makers became signifi... \n", "Xinyuan Real Estate: The Path Is Becoming Clearer SummaryXinyuan's stock has performed well so f... \n", "Lockheed Martin: The Sky Is The Limit SummaryLockheed Martin exhibits strong competi... \n", "\n", " 针对公司 发布时间 \n", "Micron Technology: Insanely Cheap Stock Given I... MU 2018-12-31 \n", "Molson Coors Seems Attractive At These Valuations TAP 2018-12-31 \n", "Gerdau: The Brazilian Play On U.S. Steel GGB 2018-12-31 \n", "Will Apple Get Its Mojo Back? AAPL 2018-12-31 \n", "Lululemon Stock Looks Compelling On This Dip LULU 2018-12-31 \n", "... ... ... \n", "Stamps.com: A Cash Machine STMP 2018-07-24 \n", "Can Heineken Turn The 'Mallya Drama' In Its Own... HEINY 2018-07-24 \n", "Thor Industries Is Undervalued THO 2019-02-04 \n", "Xinyuan Real Estate: The Path Is Becoming Clearer XIN 2019-02-19 \n", "Lockheed Martin: The Sky Is The Limit LMT 2019-02-13 \n", "\n", "[5898 rows x 6 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 去除文本中空格\n", "Title_Content_data[\"发布时间\"] = Title_Content_data[\"发布时间\"].str.replace(\" \", \"\")\n", "\n", "# 去除具体时间，只保留日期\n", "Title_Content_data[\"发布时间\"] = Title_Content_data[\"发布时间\"].str.extract(\n", " \"([a-zA-Z]+\\.[0-9]+,[0-9]{4})\")\n", "\n", "# 序列转化\n", "Title_Content_data[\"发布时间\"] = pd.to_datetime(Title_Content_data[\"发布时间\"])\n", "\n", "Title_Content_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.2 回帖聚合\n", "这是网友在各文章下的回复内容 \n", "1. Title：各文章的标题；空标题的，用最靠近的有内容的下方标题 \n", "1. Content：回复的全文字内容 \n", "\n", "回帖都处于一个文件夹下，这时我们遍历文件夹。 \n", "然后统一操作，合并各个Dataframe就完事了。" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:55.651011Z", "start_time": "2020-06-30T13:03:54.381390Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
回复内容标题
0Bought GLW after the dot.com bust in early 200...Corning: A Unique Company Playing In Multiple ...
1Bill, a very fair assessment on BB going forwa...BlackBerry Takes A Step Forward
2Nice article. I'm sticking with SBLKZ. Nice yieldStar Bulk Poised To Rip Higher, Buyback Coming?
3Craig - Hallum was ranked on TipRanks as #1 in...DiaMedica Therapeutics Aims For $18 Million IPO
4Why your strong emphasis on free CF? Most d...Gulfport Energy: Higher Risk, Higher Reward
\n", "
" ], "text/plain": [ " 回复内容 \\\n", "0 Bought GLW after the dot.com bust in early 200... \n", "1 Bill, a very fair assessment on BB going forwa... \n", "2 Nice article. I'm sticking with SBLKZ. Nice yield \n", "3 Craig - Hallum was ranked on TipRanks as #1 in... \n", "4 Why your strong emphasis on free CF? Most d... \n", "\n", " 标题 \n", "0 Corning: A Unique Company Playing In Multiple ... \n", "1 BlackBerry Takes A Step Forward \n", "2 Star Bulk Poised To Rip Higher, Buyback Coming? \n", "3 DiaMedica Therapeutics Aims For $18 Million IPO \n", "4 Gulfport Energy: Higher Risk, Higher Reward " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 创建一个空的 DataFrame\n", "Reply_data = pd.DataFrame(columns=['字段', '标题1'])\n", "\n", "for root, dirs, files in os.walk(os.path.join(os.getcwd(), \"回帖\")):\n", " for file in files:\n", " if(file.endswith('.csv')):\n", " # 获取文件路径\n", " Reply_data_part = pd.read_csv(os.path.join(root, file))\n", " \n", " # 删除无用行\n", " Reply_data_part.dropna(axis=0, how='any', inplace=True)\n", " # display(Reply_data_part.head())\n", " Reply_data = pd.concat(\n", " [Reply_data, Reply_data_part], axis=0, ignore_index=True)\n", "\n", "# 更改列标\n", "Reply_data.columns = ['回复内容', '标题']\n", "\n", "Reply_data.head()" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-06-30T06:12:42.394844Z", "start_time": "2020-06-30T06:12:42.389832Z" } }, "source": [ "## 2.3 论坛聚合\n", "这是网友在各公司的论坛页面下，对之进行评论的发帖内容 \n", "1. 字段1：作者 \n", "1. 字段2：发帖日期 \n", "1. 字段3：帖子内容 \n", "1. 字段4_链接：具体的各公司的页面URL " ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:55.882390Z", "start_time": "2020-06-30T13:03:55.656996Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
作者发帖日期帖子内容公司
0ComputerBlue31-Dec-18Let's create a small spec POS portfolio $COTY ...https://seekingalpha.com/symbol/COTY
1Darren McCammon31-Dec-18$RICK \"Now that we've reported results, we'll ...https://seekingalpha.com/symbol/RICK
2Jonathan Cooper31-Dec-18Do any $APHA shareholders support the $GGB tak...https://seekingalpha.com/symbol/APHA
3lstasel31-Dec-18Long on $T . Even if it means smaller dividend...https://seekingalpha.com/symbol/T
4Nicholas Ward31-Dec-182018 was a down year for me, but I'm happy to ...https://seekingalpha.com/symbol/SPY
\n", "
" ], "text/plain": [ " 作者 发帖日期 \\\n", "0 ComputerBlue 31-Dec-18 \n", "1 Darren McCammon 31-Dec-18 \n", "2 Jonathan Cooper 31-Dec-18 \n", "3 lstasel 31-Dec-18 \n", "4 Nicholas Ward 31-Dec-18 \n", "\n", " 帖子内容 \\\n", "0 Let's create a small spec POS portfolio $COTY ... \n", "1 $RICK \"Now that we've reported results, we'll ... \n", "2 Do any $APHA shareholders support the $GGB tak... \n", "3 Long on $T . Even if it means smaller dividend... \n", "4 2018 was a down year for me, but I'm happy to ... \n", "\n", " 公司 \n", "0 https://seekingalpha.com/symbol/COTY \n", "1 https://seekingalpha.com/symbol/RICK \n", "2 https://seekingalpha.com/symbol/APHA \n", "3 https://seekingalpha.com/symbol/T \n", "4 https://seekingalpha.com/symbol/SPY " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 创建一个空的 DataFrame\n", "Forum_data = pd.read_csv(\"论坛.csv\")\n", "\n", "# 更改列标\n", "Forum_data.columns = ['作者', '发帖日期', '帖子内容', '公司']\n", "\n", "# 删除无用行\n", "Forum_data.dropna(axis=0, how='any', inplace=True)\n", "\n", "Forum_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.3.1 公司序列处理\n", "可以看到公司那一栏其实是URL，前面的 https://seekingalpha.com/symbol/ 可以直接去掉" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:55.976140Z", "start_time": "2020-06-30T13:03:55.887378Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
作者发帖日期帖子内容公司
0ComputerBlue31-Dec-18Let's create a small spec POS portfolio $COTY ...COTY
1Darren McCammon31-Dec-18$RICK \"Now that we've reported results, we'll ...RICK
2Jonathan Cooper31-Dec-18Do any $APHA shareholders support the $GGB tak...APHA
3lstasel31-Dec-18Long on $T . Even if it means smaller dividend...T
4Nicholas Ward31-Dec-182018 was a down year for me, but I'm happy to ...SPY
\n", "
" ], "text/plain": [ " 作者 发帖日期 \\\n", "0 ComputerBlue 31-Dec-18 \n", "1 Darren McCammon 31-Dec-18 \n", "2 Jonathan Cooper 31-Dec-18 \n", "3 lstasel 31-Dec-18 \n", "4 Nicholas Ward 31-Dec-18 \n", "\n", " 帖子内容 公司 \n", "0 Let's create a small spec POS portfolio $COTY ... COTY \n", "1 $RICK \"Now that we've reported results, we'll ... RICK \n", "2 Do any $APHA shareholders support the $GGB tak... APHA \n", "3 Long on $T . Even if it means smaller dividend... T \n", "4 2018 was a down year for me, but I'm happy to ... SPY " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Forum_data[\"公司\"] = Forum_data[\"公司\"].str.replace(\n", " r\"https://seekingalpha.com/symbol/\", \"\")\n", "\n", "Forum_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "然后时间那里一样需要格式化成一样的" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:56.100810Z", "start_time": "2020-06-30T13:03:55.980129Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
作者发帖日期帖子内容公司
0ComputerBlue2018-12-31Let's create a small spec POS portfolio $COTY ...COTY
1Darren McCammon2018-12-31$RICK \"Now that we've reported results, we'll ...RICK
2Jonathan Cooper2018-12-31Do any $APHA shareholders support the $GGB tak...APHA
3lstasel2018-12-31Long on $T . Even if it means smaller dividend...T
4Nicholas Ward2018-12-312018 was a down year for me, but I'm happy to ...SPY
\n", "
" ], "text/plain": [ " 作者 发帖日期 \\\n", "0 ComputerBlue 2018-12-31 \n", "1 Darren McCammon 2018-12-31 \n", "2 Jonathan Cooper 2018-12-31 \n", "3 lstasel 2018-12-31 \n", "4 Nicholas Ward 2018-12-31 \n", "\n", " 帖子内容 公司 \n", "0 Let's create a small spec POS portfolio $COTY ... COTY \n", "1 $RICK \"Now that we've reported results, we'll ... RICK \n", "2 Do any $APHA shareholders support the $GGB tak... APHA \n", "3 Long on $T . Even if it means smaller dividend... T \n", "4 2018 was a down year for me, but I'm happy to ... SPY " ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Forum_data[\"发帖日期\"] = pd.to_datetime(Forum_data[\"发帖日期\"])\n", "\n", "Forum_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2.4 股价处理\n", "为各公司工作日股票的价格 \n", "1. PERMNO：公司编号 \n", "1. Date：日期 \n", "1. TICKER：公司简写 \n", "1. COMNAM：公司全写 \n", "1. BIDLO：最低价 \n", "1. ASKHI：最高价 \n", "1. PRC：收盘价 \n", "1. VOL：成交量 \n", "1. OPENPRC：开盘价 " ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:58.142273Z", "start_time": "2020-06-30T13:03:56.106790Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
公司编号日期公司简写最低价最高价收盘价成交量开盘价
01002620180702JJSF150.70000153.27499152.92000100388.0152.17999
11002620180703JJSF151.35001153.73000153.3200155547.0153.67000
21002620180705JJSF152.46001156.00000155.81000199370.0153.95000
31002620180706JJSF154.80000158.44000158.42999127431.0156.00000
41002620180709JJSF154.44000159.05000154.5300097661.0158.60001
\n", "
" ], "text/plain": [ " 公司编号 日期 公司简写 最低价 最高价 收盘价 成交量 开盘价\n", "0 10026 20180702 JJSF 150.70000 153.27499 152.92000 100388.0 152.17999\n", "1 10026 20180703 JJSF 151.35001 153.73000 153.32001 55547.0 153.67000\n", "2 10026 20180705 JJSF 152.46001 156.00000 155.81000 199370.0 153.95000\n", "3 10026 20180706 JJSF 154.80000 158.44000 158.42999 127431.0 156.00000\n", "4 10026 20180709 JJSF 154.44000 159.05000 154.53000 97661.0 158.60001" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 创建一个空的 DataFrame\n", "Stock_data = pd.read_csv(\"股票价格.csv\", usecols=[0, 1, 2, 4, 5, 6, 7, 8])\n", "\n", "# 更改列标\n", "Stock_data.columns = ['公司编号', '日期', '公司简写', '最低价', '最高价', '收盘价', '成交量', '开盘价']\n", "\n", "\n", "# 删除无用行\n", "Stock_data.dropna(axis=0, how='any', inplace=True)\n", "\n", "Stock_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "时间序列处理一下" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:58.287884Z", "start_time": "2020-06-30T13:03:58.146264Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
公司编号日期公司简写最低价最高价收盘价成交量开盘价
0100262018-07-02JJSF150.70000153.27499152.92000100388.0152.17999
1100262018-07-03JJSF151.35001153.73000153.3200155547.0153.67000
2100262018-07-05JJSF152.46001156.00000155.81000199370.0153.95000
3100262018-07-06JJSF154.80000158.44000158.42999127431.0156.00000
4100262018-07-09JJSF154.44000159.05000154.5300097661.0158.60001
\n", "
" ], "text/plain": [ " 公司编号 日期 公司简写 最低价 最高价 收盘价 成交量 \\\n", "0 10026 2018-07-02 JJSF 150.70000 153.27499 152.92000 100388.0 \n", "1 10026 2018-07-03 JJSF 151.35001 153.73000 153.32001 55547.0 \n", "2 10026 2018-07-05 JJSF 152.46001 156.00000 155.81000 199370.0 \n", "3 10026 2018-07-06 JJSF 154.80000 158.44000 158.42999 127431.0 \n", "4 10026 2018-07-09 JJSF 154.44000 159.05000 154.53000 97661.0 \n", "\n", " 开盘价 \n", "0 152.17999 \n", "1 153.67000 \n", "2 153.95000 \n", "3 156.00000 \n", "4 158.60001 " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Stock_data[\"日期\"] = pd.to_datetime(Stock_data[\"日期\"], format=\"%Y%m%d\")\n", "Stock_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 三、图表绘制" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3.1 各公司股票分类\n", "按照各个公司将股票分开，这里利用groupby函数。 \n", "这里只展示分类后第一个股票的图表。" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:58.854875Z", "start_time": "2020-06-30T13:03:58.290875Z" } }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", "StockData = Stock_data.groupby(['公司编号'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "现在我们其中一个公司，因为其实对于不同公司来说，股价的预测可能是不一样的。 \n", "而且，数据量太大，运行起来太慢。" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:59.063322Z", "start_time": "2020-06-30T13:03:58.857868Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
公司编号日期公司简写最低价最高价收盘价成交量开盘价
500578536132018-07-02MU51.3254.530054.4838915998.051.52
500579536132018-07-03MU50.1054.790051.4852179035.054.55
500580536132018-07-05MU51.9453.310052.8451116248.052.85
500581536132018-07-06MU51.9853.410053.2331831420.052.54
500582536132018-07-09MU53.1154.500054.3132561338.053.80
...........................
500699536132018-12-24MU29.0030.350029.0223995373.029.86
500700536132018-12-26MU28.3930.910030.8945697474.029.34
500701536132018-12-27MU30.2332.010031.9339864916.030.41
500702536132018-12-28MU31.4032.278531.5729849028.032.00
500703536132018-12-31MU31.4632.400031.7321390910.031.99
\n", "

126 rows × 8 columns

\n", "
" ], "text/plain": [ " 公司编号 日期 公司简写 最低价 最高价 收盘价 成交量 开盘价\n", "500578 53613 2018-07-02 MU 51.32 54.5300 54.48 38915998.0 51.52\n", "500579 53613 2018-07-03 MU 50.10 54.7900 51.48 52179035.0 54.55\n", "500580 53613 2018-07-05 MU 51.94 53.3100 52.84 51116248.0 52.85\n", "500581 53613 2018-07-06 MU 51.98 53.4100 53.23 31831420.0 52.54\n", "500582 53613 2018-07-09 MU 53.11 54.5000 54.31 32561338.0 53.80\n", "... ... ... ... ... ... ... ... ...\n", "500699 53613 2018-12-24 MU 29.00 30.3500 29.02 23995373.0 29.86\n", "500700 53613 2018-12-26 MU 28.39 30.9100 30.89 45697474.0 29.34\n", "500701 53613 2018-12-27 MU 30.23 32.0100 31.93 39864916.0 30.41\n", "500702 53613 2018-12-28 MU 31.40 32.2785 31.57 29849028.0 32.00\n", "500703 53613 2018-12-31 MU 31.46 32.4000 31.73 21390910.0 31.99\n", "\n", "[126 rows x 8 columns]" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Company_test = Stock_data[Stock_data[\"公司简写\"] == \"MU\"]\n", "\n", "Company_test" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.1.1 成交量绘图\n", "这里我们绘制MU公司的成交量折线图。" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:59.555005Z", "start_time": "2020-06-30T13:03:59.068307Z" }, "scrolled": true }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "plt.plot(Company_test[\"日期\"], Company_test[\"成交量\"])\n", "plt.title(\"成交量绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"成交量\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.1.2 收盘价绘图\n", "这里我们绘制MU公司的收盘价折线图。" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:59.902075Z", "start_time": "2020-06-30T13:03:59.558994Z" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "plt.plot(Company_test[\"日期\"], Company_test[\"收盘价\"])\n", "plt.title(\"成交量绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"收盘价\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.1.3 收盘价*成交量绘图" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 四、有效数据整合" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "在最终的的数据里，已经最后用于分析的模型中，我们将会用到`帖子评论数`和`论坛评论数`来进行最终结果的预测。 \n", "所以在这里，我们新增两行来存贮这些数据。" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:03:59.946954Z", "start_time": "2020-06-30T13:03:59.905068Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
公司编号日期公司简写最低价最高价收盘价成交量开盘价帖子评论数论坛评论数
0100262018-07-02JJSF150.70000153.27499152.92000100388.0152.1799900
1100262018-07-03JJSF151.35001153.73000153.3200155547.0153.6700000
2100262018-07-05JJSF152.46001156.00000155.81000199370.0153.9500000
3100262018-07-06JJSF154.80000158.44000158.42999127431.0156.0000000
4100262018-07-09JJSF154.44000159.05000154.5300097661.0158.6000100
\n", "
" ], "text/plain": [ " 公司编号 日期 公司简写 最低价 最高价 收盘价 成交量 \\\n", "0 10026 2018-07-02 JJSF 150.70000 153.27499 152.92000 100388.0 \n", "1 10026 2018-07-03 JJSF 151.35001 153.73000 153.32001 55547.0 \n", "2 10026 2018-07-05 JJSF 152.46001 156.00000 155.81000 199370.0 \n", "3 10026 2018-07-06 JJSF 154.80000 158.44000 158.42999 127431.0 \n", "4 10026 2018-07-09 JJSF 154.44000 159.05000 154.53000 97661.0 \n", "\n", " 开盘价 帖子评论数 论坛评论数 \n", "0 152.17999 0 0 \n", "1 153.67000 0 0 \n", "2 153.95000 0 0 \n", "3 156.00000 0 0 \n", "4 158.60001 0 0 " ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Stock_data['帖子评论数'] = 0\n", "Stock_data['论坛评论数'] = 0\n", "Stock_data.head()" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-06-30T07:38:46.466173Z", "start_time": "2020-06-30T07:38:46.460189Z" } }, "source": [ "每个公司对应帖子的评论数和论坛的评论数整合。 \n", "这里只对一家公司做测试，因为数据集太大了。" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:00.173385Z", "start_time": "2020-06-30T13:03:59.948949Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
公司编号日期公司简写最低价最高价收盘价成交量开盘价帖子评论数论坛评论数
500578536132018-07-02MU51.3254.530054.4838915998.051.5200
500579536132018-07-03MU50.1054.790051.4852179035.054.5500
500580536132018-07-05MU51.9453.310052.8451116248.052.8500
500581536132018-07-06MU51.9853.410053.2331831420.052.5400
500582536132018-07-09MU53.1154.500054.3132561338.053.8000
.................................
500699536132018-12-24MU29.0030.350029.0223995373.029.8600
500700536132018-12-26MU28.3930.910030.8945697474.029.3400
500701536132018-12-27MU30.2332.010031.9339864916.030.4100
500702536132018-12-28MU31.4032.278531.5729849028.032.0000
500703536132018-12-31MU31.4632.400031.7321390910.031.9900
\n", "

126 rows × 10 columns

\n", "
" ], "text/plain": [ " 公司编号 日期 公司简写 最低价 最高价 收盘价 成交量 开盘价 \\\n", "500578 53613 2018-07-02 MU 51.32 54.5300 54.48 38915998.0 51.52 \n", "500579 53613 2018-07-03 MU 50.10 54.7900 51.48 52179035.0 54.55 \n", "500580 53613 2018-07-05 MU 51.94 53.3100 52.84 51116248.0 52.85 \n", "500581 53613 2018-07-06 MU 51.98 53.4100 53.23 31831420.0 52.54 \n", "500582 53613 2018-07-09 MU 53.11 54.5000 54.31 32561338.0 53.80 \n", "... ... ... ... ... ... ... ... ... \n", "500699 53613 2018-12-24 MU 29.00 30.3500 29.02 23995373.0 29.86 \n", "500700 53613 2018-12-26 MU 28.39 30.9100 30.89 45697474.0 29.34 \n", "500701 53613 2018-12-27 MU 30.23 32.0100 31.93 39864916.0 30.41 \n", "500702 53613 2018-12-28 MU 31.40 32.2785 31.57 29849028.0 32.00 \n", "500703 53613 2018-12-31 MU 31.46 32.4000 31.73 21390910.0 31.99 \n", "\n", " 帖子评论数 论坛评论数 \n", "500578 0 0 \n", "500579 0 0 \n", "500580 0 0 \n", "500581 0 0 \n", "500582 0 0 \n", "... ... ... \n", "500699 0 0 \n", "500700 0 0 \n", "500701 0 0 \n", "500702 0 0 \n", "500703 0 0 \n", "\n", "[126 rows x 10 columns]" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Company_test = Stock_data[Stock_data[\"公司简写\"] == \"MU\"]\n", "\n", "# 按照时间排序\n", "Company_test = Company_test.sort_values(by='日期')\n", "\n", "Company_test" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "现在找出所有对应的帖子。 \n", "此处的对应指的是公司和发布时间相对应。" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:00.226243Z", "start_time": "2020-06-30T13:04:00.177376Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
标题作者评论数摘要针对公司发布时间
Micron Technology: Insanely Cheap Stock Given Its High Earnings QualityMicron Technology: Insanely Cheap Stock Given ...Ruerd Heeg75SummaryLast year, a combination of relatively ...MU2018-12-31
Micron Earnings Review: Free Cash Flow Yield Is 24%, Capital Discipline Is At HandMicron Earnings Review: Free Cash Flow Yield I...Brian Gilmartin, CFA72SummaryEPS estimates have fallen sharply after...MU2018-12-30
Micron's Trajectory After The Q1 2019 Earnings ReleaseMicron's Trajectory After The Q1 2019 Earnings...Jeffery Margolf27SummaryMicron collapsed in the second half of ...MU2018-12-27
Micron: A Major Opportunity Trading At Book ValueMicron: A Major Opportunity Trading At Book ValueLyn Alden Schwartzer205SummaryMicron Technology is now trading just a...MU2018-12-27
Micron: This Ain't 2016Micron: This Ain't 2016Billy Duberstein118SummaryIt looks as if Micron is undergoing its...MU2018-12-26
.....................
Murphy Oil Falls Despite Strong Q2 ResultsMurphy Oil Falls Despite Strong Q2 ResultsLeo Nelissen8SummaryMurphy Oil beat both sales and EPS esti...MUR2018-08-10
Micron: Sky-High Price Targets Justified?Micron: Sky-High Price Targets Justified?Khaveen Jeyaratnam267SummaryMicron’s price targets have been held a...MU2018-08-09
Micron: A Bad Beat PerspectiveMicron: A Bad Beat PerspectiveQuad 7 Capital364SummaryWe recently made a short-term trade in ...MU2018-08-02
Micron: Among The Best Bargains In MemoryMicron: Among The Best Bargains In MemoryRussell Naisbitt311SummaryCurrently mired in the low $50’s, Micro...MU2018-07-31
Micron's Multiple Expansion Should Drive Stock Much HigherMicron's Multiple Expansion Should Drive Stock...Victor Dergunov131SummaryDespite the nearly 100% run-up over the...MU2018-07-29
\n", "

85 rows × 6 columns

\n", "
" ], "text/plain": [ " 标题 \\\n", "Micron Technology: Insanely Cheap Stock Given I... Micron Technology: Insanely Cheap Stock Given ... \n", "Micron Earnings Review: Free Cash Flow Yield Is... Micron Earnings Review: Free Cash Flow Yield I... \n", "Micron's Trajectory After The Q1 2019 Earnings ... Micron's Trajectory After The Q1 2019 Earnings... \n", "Micron: A Major Opportunity Trading At Book Value Micron: A Major Opportunity Trading At Book Value \n", "Micron: This Ain't 2016 Micron: This Ain't 2016 \n", "... ... \n", "Murphy Oil Falls Despite Strong Q2 Results Murphy Oil Falls Despite Strong Q2 Results \n", "Micron: Sky-High Price Targets Justified? Micron: Sky-High Price Targets Justified? \n", "Micron: A Bad Beat Perspective Micron: A Bad Beat Perspective \n", "Micron: Among The Best Bargains In Memory Micron: Among The Best Bargains In Memory \n", "Micron's Multiple Expansion Should Drive Stock ... Micron's Multiple Expansion Should Drive Stock... \n", "\n", " 作者 \\\n", "Micron Technology: Insanely Cheap Stock Given I... Ruerd Heeg \n", "Micron Earnings Review: Free Cash Flow Yield Is... Brian Gilmartin, CFA \n", "Micron's Trajectory After The Q1 2019 Earnings ... Jeffery Margolf \n", "Micron: A Major Opportunity Trading At Book Value Lyn Alden Schwartzer \n", "Micron: This Ain't 2016 Billy Duberstein \n", "... ... \n", "Murphy Oil Falls Despite Strong Q2 Results Leo Nelissen \n", "Micron: Sky-High Price Targets Justified? Khaveen Jeyaratnam \n", "Micron: A Bad Beat Perspective Quad 7 Capital \n", "Micron: Among The Best Bargains In Memory Russell Naisbitt \n", "Micron's Multiple Expansion Should Drive Stock ... Victor Dergunov \n", "\n", " 评论数 \\\n", "Micron Technology: Insanely Cheap Stock Given I... 75 \n", "Micron Earnings Review: Free Cash Flow Yield Is... 72 \n", "Micron's Trajectory After The Q1 2019 Earnings ... 27 \n", "Micron: A Major Opportunity Trading At Book Value 205 \n", "Micron: This Ain't 2016 118 \n", "... ... \n", "Murphy Oil Falls Despite Strong Q2 Results 8 \n", "Micron: Sky-High Price Targets Justified? 267 \n", "Micron: A Bad Beat Perspective 364 \n", "Micron: Among The Best Bargains In Memory 311 \n", "Micron's Multiple Expansion Should Drive Stock ... 131 \n", "\n", " 摘要 \\\n", "Micron Technology: Insanely Cheap Stock Given I... SummaryLast year, a combination of relatively ... \n", "Micron Earnings Review: Free Cash Flow Yield Is... SummaryEPS estimates have fallen sharply after... \n", "Micron's Trajectory After The Q1 2019 Earnings ... SummaryMicron collapsed in the second half of ... \n", "Micron: A Major Opportunity Trading At Book Value SummaryMicron Technology is now trading just a... \n", "Micron: This Ain't 2016 SummaryIt looks as if Micron is undergoing its... \n", "... ... \n", "Murphy Oil Falls Despite Strong Q2 Results SummaryMurphy Oil beat both sales and EPS esti... \n", "Micron: Sky-High Price Targets Justified? SummaryMicron’s price targets have been held a... \n", "Micron: A Bad Beat Perspective SummaryWe recently made a short-term trade in ... \n", "Micron: Among The Best Bargains In Memory SummaryCurrently mired in the low $50’s, Micro... \n", "Micron's Multiple Expansion Should Drive Stock ... SummaryDespite the nearly 100% run-up over the... \n", "\n", " 针对公司 发布时间 \n", "Micron Technology: Insanely Cheap Stock Given I... MU 2018-12-31 \n", "Micron Earnings Review: Free Cash Flow Yield Is... MU 2018-12-30 \n", "Micron's Trajectory After The Q1 2019 Earnings ... MU 2018-12-27 \n", "Micron: A Major Opportunity Trading At Book Value MU 2018-12-27 \n", "Micron: This Ain't 2016 MU 2018-12-26 \n", "... ... ... \n", "Murphy Oil Falls Despite Strong Q2 Results MUR 2018-08-10 \n", "Micron: Sky-High Price Targets Justified? MU 2018-08-09 \n", "Micron: A Bad Beat Perspective MU 2018-08-02 \n", "Micron: Among The Best Bargains In Memory MU 2018-07-31 \n", "Micron's Multiple Expansion Should Drive Stock ... MU 2018-07-29 \n", "\n", "[85 rows x 6 columns]" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MU_Passage = Title_Content_data[Title_Content_data[\"针对公司\"].str.contains(\"MU\")]\n", "\n", "MU_Passage" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-06-30T12:12:45.686910Z", "start_time": "2020-06-30T12:12:45.680961Z" } }, "source": [ "找出所有对应帖子后，我们增加相应的评论数。 \n", "下面是我们操作完毕的结果。" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:00.764803Z", "start_time": "2020-06-30T13:04:00.230235Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
公司编号日期公司简写最低价最高价收盘价成交量开盘价帖子评论数论坛评论数
500578536132018-07-02MU51.3254.530054.4838915998.051.5200
500579536132018-07-03MU50.1054.790051.4852179035.054.5500
500580536132018-07-05MU51.9453.310052.8451116248.052.8500
500581536132018-07-06MU51.9853.410053.2331831420.052.5400
500582536132018-07-09MU53.1154.500054.3132561338.053.8000
.................................
500699536132018-12-24MU29.0030.350029.0223995373.029.8600
500700536132018-12-26MU28.3930.910030.8945697474.029.341180
500701536132018-12-27MU30.2332.010031.9339864916.030.412320
500702536132018-12-28MU31.4032.278531.5729849028.032.0000
500703536132018-12-31MU31.4632.400031.7321390910.031.99750
\n", "

126 rows × 10 columns

\n", "
" ], "text/plain": [ " 公司编号 日期 公司简写 最低价 最高价 收盘价 成交量 开盘价 \\\n", "500578 53613 2018-07-02 MU 51.32 54.5300 54.48 38915998.0 51.52 \n", "500579 53613 2018-07-03 MU 50.10 54.7900 51.48 52179035.0 54.55 \n", "500580 53613 2018-07-05 MU 51.94 53.3100 52.84 51116248.0 52.85 \n", "500581 53613 2018-07-06 MU 51.98 53.4100 53.23 31831420.0 52.54 \n", "500582 53613 2018-07-09 MU 53.11 54.5000 54.31 32561338.0 53.80 \n", "... ... ... ... ... ... ... ... ... \n", "500699 53613 2018-12-24 MU 29.00 30.3500 29.02 23995373.0 29.86 \n", "500700 53613 2018-12-26 MU 28.39 30.9100 30.89 45697474.0 29.34 \n", "500701 53613 2018-12-27 MU 30.23 32.0100 31.93 39864916.0 30.41 \n", "500702 53613 2018-12-28 MU 31.40 32.2785 31.57 29849028.0 32.00 \n", "500703 53613 2018-12-31 MU 31.46 32.4000 31.73 21390910.0 31.99 \n", "\n", " 帖子评论数 论坛评论数 \n", "500578 0 0 \n", "500579 0 0 \n", "500580 0 0 \n", "500581 0 0 \n", "500582 0 0 \n", "... ... ... \n", "500699 0 0 \n", "500700 118 0 \n", "500701 232 0 \n", "500702 0 0 \n", "500703 75 0 \n", "\n", "[126 rows x 10 columns]" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def AddCount(r):\n", " row = MU_Passage.loc[(MU_Passage[\"针对公司\"] == r[\"公司简写\"])\n", " & (MU_Passage[\"发布时间\"] == r[\"日期\"])]\n", " count = int(r[\"帖子评论数\"])\n", " for rr in row.itertuples():\n", " count += int(getattr(rr, '评论数'))\n", " return count\n", "\n", "\n", "Company_test[\"帖子评论数\"] = Company_test[['帖子评论数', '公司简写', '日期']].apply(\n", " lambda x: AddCount(x), axis=1)\n", "\n", "Company_test" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "接下来处理论坛评论，操作方法和上面一致。" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:00.808688Z", "start_time": "2020-06-30T13:04:00.768793Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
作者发帖日期帖子内容公司
53Sunil Shah2018-12-30$MU The latter proposals include cracking down...MU
117Sunil Shah2018-12-28$MUCheck the OBV min by min for last 3 days.Th...MU
124Sunil Shah2018-12-28$MU last chance to get on board before MASSIVE...MU
225Sunil Shah2018-12-26$MU Did I say 24 dec was the low.WELL it's tod...MU
330Sunil Shah2018-12-24$MU @RogerSach @floridahockey @Natecrk6 @Ian C...MU
...............
24323Vertical Spread2018-01-09Back into 2018 Long term Call Spreads, $MU, $N...MU
24391GarethSoloway2018-01-09Sold $MU scalp at $43.88 from entry of $43.57 ...MU
24394GarethSoloway2018-01-09$MU hitting major support here at $43.50. Gap ...MU
24533Ryan Mallory2018-01-08Stocks to Trade: $MU $PAH-OLD $MAR http://bit....MU
24971Focus Equity2018-01-03$MU Micron: The Market's Search for Cyclicalit...MU
\n", "

217 rows × 4 columns

\n", "
" ], "text/plain": [ " 作者 发帖日期 \\\n", "53 Sunil Shah 2018-12-30 \n", "117 Sunil Shah 2018-12-28 \n", "124 Sunil Shah 2018-12-28 \n", "225 Sunil Shah 2018-12-26 \n", "330 Sunil Shah 2018-12-24 \n", "... ... ... \n", "24323 Vertical Spread 2018-01-09 \n", "24391 GarethSoloway 2018-01-09 \n", "24394 GarethSoloway 2018-01-09 \n", "24533 Ryan Mallory 2018-01-08 \n", "24971 Focus Equity 2018-01-03 \n", "\n", " 帖子内容 公司 \n", "53 $MU The latter proposals include cracking down... MU \n", "117 $MUCheck the OBV min by min for last 3 days.Th... MU \n", "124 $MU last chance to get on board before MASSIVE... MU \n", "225 $MU Did I say 24 dec was the low.WELL it's tod... MU \n", "330 $MU @RogerSach @floridahockey @Natecrk6 @Ian C... MU \n", "... ... .. \n", "24323 Back into 2018 Long term Call Spreads, $MU, $N... MU \n", "24391 Sold $MU scalp at $43.88 from entry of $43.57 ... MU \n", "24394 $MU hitting major support here at $43.50. Gap ... MU \n", "24533 Stocks to Trade: $MU $PAH-OLD $MAR http://bit.... MU \n", "24971 $MU Micron: The Market's Search for Cyclicalit... MU \n", "\n", "[217 rows x 4 columns]" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MU_Forum = Forum_data[Forum_data[\"公司\"] == \"MU\"]\n", "\n", "MU_Forum" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:01.276560Z", "start_time": "2020-06-30T13:04:00.811677Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
公司编号日期公司简写最低价最高价收盘价成交量开盘价帖子评论数论坛评论数
500578536132018-07-02MU51.3254.530054.4838915998.051.5201
500579536132018-07-03MU50.1054.790051.4852179035.054.5502
500580536132018-07-05MU51.9453.310052.8451116248.052.8502
500581536132018-07-06MU51.9853.410053.2331831420.052.5401
500582536132018-07-09MU53.1154.500054.3132561338.053.8000
.................................
500699536132018-12-24MU29.0030.350029.0223995373.029.8601
500700536132018-12-26MU28.3930.910030.8945697474.029.341181
500701536132018-12-27MU30.2332.010031.9339864916.030.412320
500702536132018-12-28MU31.4032.278531.5729849028.032.0002
500703536132018-12-31MU31.4632.400031.7321390910.031.99750
\n", "

126 rows × 10 columns

\n", "
" ], "text/plain": [ " 公司编号 日期 公司简写 最低价 最高价 收盘价 成交量 开盘价 \\\n", "500578 53613 2018-07-02 MU 51.32 54.5300 54.48 38915998.0 51.52 \n", "500579 53613 2018-07-03 MU 50.10 54.7900 51.48 52179035.0 54.55 \n", "500580 53613 2018-07-05 MU 51.94 53.3100 52.84 51116248.0 52.85 \n", "500581 53613 2018-07-06 MU 51.98 53.4100 53.23 31831420.0 52.54 \n", "500582 53613 2018-07-09 MU 53.11 54.5000 54.31 32561338.0 53.80 \n", "... ... ... ... ... ... ... ... ... \n", "500699 53613 2018-12-24 MU 29.00 30.3500 29.02 23995373.0 29.86 \n", "500700 53613 2018-12-26 MU 28.39 30.9100 30.89 45697474.0 29.34 \n", "500701 53613 2018-12-27 MU 30.23 32.0100 31.93 39864916.0 30.41 \n", "500702 53613 2018-12-28 MU 31.40 32.2785 31.57 29849028.0 32.00 \n", "500703 53613 2018-12-31 MU 31.46 32.4000 31.73 21390910.0 31.99 \n", "\n", " 帖子评论数 论坛评论数 \n", "500578 0 1 \n", "500579 0 2 \n", "500580 0 2 \n", "500581 0 1 \n", "500582 0 0 \n", "... ... ... \n", "500699 0 1 \n", "500700 118 1 \n", "500701 232 0 \n", "500702 0 2 \n", "500703 75 0 \n", "\n", "[126 rows x 10 columns]" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def AddCount_n(r):\n", " row = MU_Forum.loc[(MU_Forum[\"公司\"] == r[\"公司简写\"]) &\n", " (MU_Forum[\"发帖日期\"] == r[\"日期\"])]\n", " count = int(r[\"论坛评论数\"])\n", " for rr in row.itertuples():\n", " count += 1\n", " return count\n", "\n", "\n", "Company_test[\"论坛评论数\"] = Company_test[['论坛评论数', '公司简写', '日期']].apply(\n", " lambda x: AddCount_n(x), axis=1)\n", "\n", "Company_test" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 五、线性回归" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.1 导入模块" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:02.713985Z", "start_time": "2020-06-30T13:04:01.285534Z" } }, "outputs": [], "source": [ "from sklearn import datasets\n", "from sklearn.linear_model import ElasticNet" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5.2 弹性网络回归模型" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.2.1 训练集处理" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:02.742907Z", "start_time": "2020-06-30T13:04:02.717975Z" } }, "outputs": [], "source": [ "# 测试集采样率\n", "RATING = 0.3\n", "\n", "# 集合创建\n", "test = pd.DataFrame() # 划分出的test集合\n", "train = pd.DataFrame() # 剩余的train集合\n", "\n", "# 训练样本\n", "sample = Company_test.sample(int(RATING*len(Company_test)))\n", "sample_index = sample.index\n", "\n", "# 剩余数据\n", "all_index = Company_test.index\n", "residue_index = all_index.difference(sample_index) # 去除sample之后剩余的数据\n", "residue = Company_test.loc[residue_index] # 这里要使用.loc而非.iloc\n", "\n", "# 保存\n", "test = pd.concat([test, sample], ignore_index=True)\n", "train = pd.concat([train, residue], ignore_index=True)\n", "\n", "\n", "# 只保留训练数据\n", "test = pd.DataFrame(\n", " test, columns=['最低价', '最高价', '收盘价', '成交量', '开盘价', \"帖子评论数\", \"论坛评论数\"])\n", "train = pd.DataFrame(\n", " train, columns=['最低价', '最高价', '收盘价', '成交量', '开盘价', \"帖子评论数\", \"论坛评论数\"])" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-06-30T12:15:55.452302Z", "start_time": "2020-06-30T12:15:55.446315Z" } }, "source": [ "在这里我们还需要将所有的数据上下两行相减。 \n", "在我看来，下一天的股价必然和前一天的股价有关，同%gui又与人们的评论数目有关。 \n", "至于为什么不做情感分析？ \n", "因为有评论总比没评论要好，评论有就说明人们持续关注，而一个股票最重要的就是热度" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:02.784796Z", "start_time": "2020-06-30T13:04:02.745899Z" } }, "outputs": [], "source": [ "test_n=pd.DataFrame()\n", "test_n[['最低价', '最高价', '收盘价', '成交量', '开盘价']] = test[[\n", " '最低价', '最高价', '收盘价', '成交量', '开盘价']].shift(1)\n", "test[['最低价', '最高价', '收盘价', '成交量', '开盘价']\n", " ] -= test_n[['最低价', '最高价', '收盘价', '成交量', '开盘价']]\n", "\n", "# 删除无用行\n", "test.dropna(axis=0, how='any', inplace=True)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:02.818705Z", "start_time": "2020-06-30T13:04:02.786789Z" } }, "outputs": [], "source": [ "train_n=pd.DataFrame()\n", "train_n[['最低价', '最高价', '收盘价', '成交量', '开盘价']] = train[[\n", " '最低价', '最高价', '收盘价', '成交量', '开盘价']].shift(1)\n", "train[['最低价', '最高价', '收盘价', '成交量', '开盘价']\n", " ] -= train_n[['最低价', '最高价', '收盘价', '成交量', '开盘价']]\n", "\n", "# 删除无用行\n", "train.dropna(axis=0, how='any', inplace=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "后期进行模型的拟合，需要用到Numpy中的矩阵。 \n", "所以在这里提前转化为矩阵。" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:02.830673Z", "start_time": "2020-06-30T13:04:02.822695Z" } }, "outputs": [], "source": [ "# 转化为numpy中的矩阵\n", "test = np.array(test)\n", "train = np.array(train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.2.2 模型创建\n", "这里采用的是弹性网络模型。 \n", "然后训练的数据其实是用前一天的数据去预测后一天的数据。" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:02.853612Z", "start_time": "2020-06-30T13:04:02.835661Z" } }, "outputs": [ { "data": { "text/plain": [ "ElasticNet()" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 建立模型\n", "model = ElasticNet()\n", "# 开始训练\n", "model.fit(train[:-2], train[1:-1, :5])" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:02.960326Z", "start_time": "2020-06-30T13:04:02.857602Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "predict:\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
01234
0-0.324136-0.5513940.094431-1.418783e+06-2.995172
1-0.370969-0.638064-0.208426-6.679494e+06-1.835660
20.5896490.8958760.0153397.016144e+064.607448
3-1.037168-0.928800-1.104351-4.080368e+06-1.081436
4-0.467017-0.783392-0.0331961.685619e+06-3.477304
5-0.191386-0.347014-0.0612886.104036e+05-1.162693
60.6203090.942816-0.0270946.986268e+065.063323
7-0.590589-0.9769510.030440-8.633691e+05-4.772629
8-0.205835-0.199933-0.556878-6.374661e+061.576247
9-0.377176-0.255359-0.4099953.085284e+05-0.126906
10-2.178385-2.375328-2.525755-2.511252e+07-2.121967
11-0.266343-0.0492810.1220038.577828e+06-1.922851
12-1.652772-1.128968-2.457531-8.046615e+062.433010
13-0.593373-0.805486-0.446146-9.454369e+06-2.028250
140.3722580.5504940.0077741.044474e+072.931931
15-1.337074-1.439859-1.171693-1.202798e+07-3.165275
16-0.124904-0.2381940.0195493.130554e+06-1.046651
17-0.164501-0.305589-0.092000-4.059373e+05-0.795737
18-0.112114-0.2165450.052627-2.383018e+06-1.112792
19-0.1210510.147603-0.7069093.962971e+063.406527
20-0.637786-1.057425-0.106033-7.467887e+06-4.455825
210.1575140.2141400.1187606.575364e+060.678880
22-0.791883-1.154095-0.601752-1.263435e+07-2.857859
230.8450221.300603-0.0003311.393748e+076.699657
24-0.580345-0.9562020.140733-2.758550e+06-5.248601
250.0109270.152307-0.1895043.341489e+061.418086
26-0.092902-0.192686-0.110433-3.379900e+06-0.138274
27-1.222715-1.001787-1.585746-6.308594e+060.331185
28-0.207593-0.372200-0.048033-9.184583e+05-1.357360
29-0.629426-0.706327-0.650828-3.184062e+06-0.975053
300.6417240.9820640.1019941.098066e+074.580549
31-0.351676-0.600111-0.028407-4.567701e+06-2.592237
32-0.156952-0.2891980.016283-2.077626e+06-1.282802
33-0.019955-0.075885-0.0856591.279864e+060.311722
34-0.685080-0.616434-0.861162-3.289734e+06-0.007059
35-0.565724-0.699722-0.386200-5.142649e+06-2.003095
\n", "
" ], "text/plain": [ " 0 1 2 3 4\n", "0 -0.324136 -0.551394 0.094431 -1.418783e+06 -2.995172\n", "1 -0.370969 -0.638064 -0.208426 -6.679494e+06 -1.835660\n", "2 0.589649 0.895876 0.015339 7.016144e+06 4.607448\n", "3 -1.037168 -0.928800 -1.104351 -4.080368e+06 -1.081436\n", "4 -0.467017 -0.783392 -0.033196 1.685619e+06 -3.477304\n", "5 -0.191386 -0.347014 -0.061288 6.104036e+05 -1.162693\n", "6 0.620309 0.942816 -0.027094 6.986268e+06 5.063323\n", "7 -0.590589 -0.976951 0.030440 -8.633691e+05 -4.772629\n", "8 -0.205835 -0.199933 -0.556878 -6.374661e+06 1.576247\n", "9 -0.377176 -0.255359 -0.409995 3.085284e+05 -0.126906\n", "10 -2.178385 -2.375328 -2.525755 -2.511252e+07 -2.121967\n", "11 -0.266343 -0.049281 0.122003 8.577828e+06 -1.922851\n", "12 -1.652772 -1.128968 -2.457531 -8.046615e+06 2.433010\n", "13 -0.593373 -0.805486 -0.446146 -9.454369e+06 -2.028250\n", "14 0.372258 0.550494 0.007774 1.044474e+07 2.931931\n", "15 -1.337074 -1.439859 -1.171693 -1.202798e+07 -3.165275\n", "16 -0.124904 -0.238194 0.019549 3.130554e+06 -1.046651\n", "17 -0.164501 -0.305589 -0.092000 -4.059373e+05 -0.795737\n", "18 -0.112114 -0.216545 0.052627 -2.383018e+06 -1.112792\n", "19 -0.121051 0.147603 -0.706909 3.962971e+06 3.406527\n", "20 -0.637786 -1.057425 -0.106033 -7.467887e+06 -4.455825\n", "21 0.157514 0.214140 0.118760 6.575364e+06 0.678880\n", "22 -0.791883 -1.154095 -0.601752 -1.263435e+07 -2.857859\n", "23 0.845022 1.300603 -0.000331 1.393748e+07 6.699657\n", "24 -0.580345 -0.956202 0.140733 -2.758550e+06 -5.248601\n", "25 0.010927 0.152307 -0.189504 3.341489e+06 1.418086\n", "26 -0.092902 -0.192686 -0.110433 -3.379900e+06 -0.138274\n", "27 -1.222715 -1.001787 -1.585746 -6.308594e+06 0.331185\n", "28 -0.207593 -0.372200 -0.048033 -9.184583e+05 -1.357360\n", "29 -0.629426 -0.706327 -0.650828 -3.184062e+06 -0.975053\n", "30 0.641724 0.982064 0.101994 1.098066e+07 4.580549\n", "31 -0.351676 -0.600111 -0.028407 -4.567701e+06 -2.592237\n", "32 -0.156952 -0.289198 0.016283 -2.077626e+06 -1.282802\n", "33 -0.019955 -0.075885 -0.085659 1.279864e+06 0.311722\n", "34 -0.685080 -0.616434 -0.861162 -3.289734e+06 -0.007059\n", "35 -0.565724 -0.699722 -0.386200 -5.142649e+06 -2.003095" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "test:\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
0123456
0-9.6900-10.3700-10.32-12666639.0-9.3500.00.0
1-6.8100-5.8100-5.3516607118.0-6.7000.01.0
217.140017.360015.45-5021706.018.4200.00.0
3-2.2254-3.1000-1.24-10037380.0-2.865473.01.0
4-10.4446-10.3150-11.48-330409.0-10.4650.03.0
5-3.6000-2.6650-3.622384959.0-2.4700.02.0
616.440015.310017.13-920211.015.2600.00.0
7-15.3800-15.9200-16.05-6481339.0-16.1600.02.0
86.92007.75006.9523473524.06.840112.00.0
90.3600-0.38000.29-20411504.00.300236.00.0
10-0.95002.3700-0.5067739350.02.760722.02.0
11-8.0400-11.0000-7.65-73030926.0-12.110241.00.0
1213.900013.370013.703445797.013.830963.01.0
13-6.0600-5.1700-5.5412052055.0-5.720115.00.0
1410.970010.49009.86-4290504.011.8800.02.0
15-7.8659-7.8300-7.921020768.0-7.880454.00.0
16-3.7141-3.9900-3.52-5428688.0-4.6100.02.0
17-2.1100-2.1075-2.285353566.0-1.5500.01.0
18-4.3050-3.6825-3.86-8625966.0-3.8000.00.0
1913.176013.240013.187090753.013.490241.02.0
20-15.9610-14.7800-14.506709930.0-17.6300.02.0
213.56001.98001.91-15018298.04.5200.00.0
22-7.5000-6.9200-7.7130923367.0-6.94099.00.0
2321.830021.260022.52-3507060.021.1700.02.0
24-17.4100-17.5900-18.04-17142196.0-18.0200.01.0
254.24004.52005.12-11078680.05.270108.01.0
26-1.1500-0.0650-0.017135225.0-2.1500.01.0
276.40005.28564.732496653.07.150615.00.0
28-4.3800-4.5206-4.321103691.0-4.9100.01.0
29-3.6450-1.9400-1.618613067.0-2.900212.03.0
3017.455015.740015.05-13397740.016.3100.00.0
31-8.9600-9.1300-8.53-793257.0-8.9500.00.0
32-4.5300-4.5600-4.30-5112990.0-4.3300.00.0
331.67001.50001.414740616.01.7100.01.0
342.33002.21002.012607984.02.260322.01.0
35-7.0200-6.1300-5.79-2121778.0-6.540150.01.0
\n", "
" ], "text/plain": [ " 0 1 2 3 4 5 6\n", "0 -9.6900 -10.3700 -10.32 -12666639.0 -9.350 0.0 0.0\n", "1 -6.8100 -5.8100 -5.35 16607118.0 -6.700 0.0 1.0\n", "2 17.1400 17.3600 15.45 -5021706.0 18.420 0.0 0.0\n", "3 -2.2254 -3.1000 -1.24 -10037380.0 -2.865 473.0 1.0\n", "4 -10.4446 -10.3150 -11.48 -330409.0 -10.465 0.0 3.0\n", "5 -3.6000 -2.6650 -3.62 2384959.0 -2.470 0.0 2.0\n", "6 16.4400 15.3100 17.13 -920211.0 15.260 0.0 0.0\n", "7 -15.3800 -15.9200 -16.05 -6481339.0 -16.160 0.0 2.0\n", "8 6.9200 7.7500 6.95 23473524.0 6.840 112.0 0.0\n", "9 0.3600 -0.3800 0.29 -20411504.0 0.300 236.0 0.0\n", "10 -0.9500 2.3700 -0.50 67739350.0 2.760 722.0 2.0\n", "11 -8.0400 -11.0000 -7.65 -73030926.0 -12.110 241.0 0.0\n", "12 13.9000 13.3700 13.70 3445797.0 13.830 963.0 1.0\n", "13 -6.0600 -5.1700 -5.54 12052055.0 -5.720 115.0 0.0\n", "14 10.9700 10.4900 9.86 -4290504.0 11.880 0.0 2.0\n", "15 -7.8659 -7.8300 -7.92 1020768.0 -7.880 454.0 0.0\n", "16 -3.7141 -3.9900 -3.52 -5428688.0 -4.610 0.0 2.0\n", "17 -2.1100 -2.1075 -2.28 5353566.0 -1.550 0.0 1.0\n", "18 -4.3050 -3.6825 -3.86 -8625966.0 -3.800 0.0 0.0\n", "19 13.1760 13.2400 13.18 7090753.0 13.490 241.0 2.0\n", "20 -15.9610 -14.7800 -14.50 6709930.0 -17.630 0.0 2.0\n", "21 3.5600 1.9800 1.91 -15018298.0 4.520 0.0 0.0\n", "22 -7.5000 -6.9200 -7.71 30923367.0 -6.940 99.0 0.0\n", "23 21.8300 21.2600 22.52 -3507060.0 21.170 0.0 2.0\n", "24 -17.4100 -17.5900 -18.04 -17142196.0 -18.020 0.0 1.0\n", "25 4.2400 4.5200 5.12 -11078680.0 5.270 108.0 1.0\n", "26 -1.1500 -0.0650 -0.01 7135225.0 -2.150 0.0 1.0\n", "27 6.4000 5.2856 4.73 2496653.0 7.150 615.0 0.0\n", "28 -4.3800 -4.5206 -4.32 1103691.0 -4.910 0.0 1.0\n", "29 -3.6450 -1.9400 -1.61 8613067.0 -2.900 212.0 3.0\n", "30 17.4550 15.7400 15.05 -13397740.0 16.310 0.0 0.0\n", "31 -8.9600 -9.1300 -8.53 -793257.0 -8.950 0.0 0.0\n", "32 -4.5300 -4.5600 -4.30 -5112990.0 -4.330 0.0 0.0\n", "33 1.6700 1.5000 1.41 4740616.0 1.710 0.0 1.0\n", "34 2.3300 2.2100 2.01 2607984.0 2.260 322.0 1.0\n", "35 -7.0200 -6.1300 -5.79 -2121778.0 -6.540 150.0 1.0" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 测试\n", "#result = np.vstack((test,train))\n", "predict = model.predict(test)\n", "print('predict:')\n", "display(pd.DataFrame(predict))\n", "print('test:')\n", "display(pd.DataFrame(test))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "下面这个是余弦相似度函数，用来判断两个预测结果的相似度的。" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:02.977282Z", "start_time": "2020-06-30T13:04:02.964316Z" } }, "outputs": [], "source": [ "def cos_sim(vector_a, vector_b):\n", " \"\"\"\n", " 计算两个向量之间的余弦相似度\n", " :param vector_a: 向量 a \n", " :param vector_b: 向量 b\n", " :return: sim\n", " \"\"\"\n", " vector_a = np.mat(vector_a)\n", " vector_b = np.mat(vector_b)[:, :5]\n", " num = float(vector_a * vector_b.T)\n", " denom = np.linalg.norm(vector_a) * np.linalg.norm(vector_b)\n", " cos = num / denom\n", " sim = 0.5 + 0.5 * cos\n", " return sim" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "这里是预测率" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:03.004210Z", "start_time": "2020-06-30T13:04:02.983266Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "预测率：0.6111111111111112\n" ] } ], "source": [ "num = 0\n", "for i in range(len(test)-1):\n", " # print(cos_sim(predict[i],test[i]))\n", " if cos_sim(predict[i], test[i+1]) > 0.99:\n", " num += 1\n", "\n", "print(\"预测率：%s\" % (num/len(test)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 六、绘图" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:03.041112Z", "start_time": "2020-06-30T13:04:03.009196Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
01234
0-0.324136-0.5513940.094431-1.418783e+06-2.995172
1-0.370969-0.638064-0.208426-6.679494e+06-1.835660
20.5896490.8958760.0153397.016144e+064.607448
3-1.037168-0.928800-1.104351-4.080368e+06-1.081436
4-0.467017-0.783392-0.0331961.685619e+06-3.477304
..................
1190.1731220.2480160.3423278.724753e+06-0.326562
120-0.396982-0.493019-0.553413-7.326299e+060.070758
121-0.457023-0.394633-0.550916-2.196870e+06-0.057571
1220.0314780.0119700.0670078.028502e+06-0.053436
123-0.125540-0.118128-0.134878-1.076952e+06-0.036930
\n", "

124 rows × 5 columns

\n", "
" ], "text/plain": [ " 0 1 2 3 4\n", "0 -0.324136 -0.551394 0.094431 -1.418783e+06 -2.995172\n", "1 -0.370969 -0.638064 -0.208426 -6.679494e+06 -1.835660\n", "2 0.589649 0.895876 0.015339 7.016144e+06 4.607448\n", "3 -1.037168 -0.928800 -1.104351 -4.080368e+06 -1.081436\n", "4 -0.467017 -0.783392 -0.033196 1.685619e+06 -3.477304\n", ".. ... ... ... ... ...\n", "119 0.173122 0.248016 0.342327 8.724753e+06 -0.326562\n", "120 -0.396982 -0.493019 -0.553413 -7.326299e+06 0.070758\n", "121 -0.457023 -0.394633 -0.550916 -2.196870e+06 -0.057571\n", "122 0.031478 0.011970 0.067007 8.028502e+06 -0.053436\n", "123 -0.125540 -0.118128 -0.134878 -1.076952e+06 -0.036930\n", "\n", "[124 rows x 5 columns]" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "result = np.mat(model.predict(np.vstack((test, train))))\n", "\n", "# 将结果转化为DataFrame\n", "pd.DataFrame(result)" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:03.107931Z", "start_time": "2020-06-30T13:04:03.047098Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
最低价最高价收盘价成交量开盘价
5005791.22-0.26003.00-13263037.0-3.03
500580-1.841.4800-1.361062787.01.70
500581-0.04-0.1000-0.3919284828.00.31
500582-1.13-1.0900-1.08-729918.0-1.26
500583-1.24-1.4000-1.43-2273157.0-0.86
..................
5006991.111.70001.3030627935.01.82
5007000.61-0.5600-1.87-21702101.00.52
500701-1.84-1.1000-1.045832558.0-1.07
500702-1.17-0.26850.3610015888.0-1.59
500703-0.06-0.1215-0.168458118.00.01
\n", "

125 rows × 5 columns

\n", "
" ], "text/plain": [ " 最低价 最高价 收盘价 成交量 开盘价\n", "500579 1.22 -0.2600 3.00 -13263037.0 -3.03\n", "500580 -1.84 1.4800 -1.36 1062787.0 1.70\n", "500581 -0.04 -0.1000 -0.39 19284828.0 0.31\n", "500582 -1.13 -1.0900 -1.08 -729918.0 -1.26\n", "500583 -1.24 -1.4000 -1.43 -2273157.0 -0.86\n", "... ... ... ... ... ...\n", "500699 1.11 1.7000 1.30 30627935.0 1.82\n", "500700 0.61 -0.5600 -1.87 -21702101.0 0.52\n", "500701 -1.84 -1.1000 -1.04 5832558.0 -1.07\n", "500702 -1.17 -0.2685 0.36 10015888.0 -1.59\n", "500703 -0.06 -0.1215 -0.16 8458118.0 0.01\n", "\n", "[125 rows x 5 columns]" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Company_test_temp = pd.DataFrame()\n", "Company_test_temp[['最低价', '最高价', '收盘价', '成交量', '开盘价']\n", " ] = Company_test[['最低价', '最高价', '收盘价', '成交量', '开盘价']].shift(1)\n", "Company_test_temp[['最低价', '最高价', '收盘价', '成交量', '开盘价']\n", " ] -= Company_test[['最低价', '最高价', '收盘价', '成交量', '开盘价']]\n", "\n", "Company_test_temp.dropna(axis=0, how='any', inplace=True)\n", "\n", "Company_test_temp" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-06-30T11:35:54.782905Z", "start_time": "2020-06-30T11:35:54.778915Z" } }, "source": [ "## 6.1最低价走势比较" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.1.1 原始数据" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:03.551348Z", "start_time": "2020-06-30T13:04:03.111924Z" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "plt.plot(Company_test[\"日期\"].iloc[1:26], Company_test_temp[\"最低价\"].iloc[1:26])\n", "plt.title(\"最低价绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"最低价\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.1.2 预测数据" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:03.956807Z", "start_time": "2020-06-30T13:04:03.555336Z" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "# print(np.array(s[0]))\n", "plt.plot(Company_test[\"日期\"][1:26], result[:25, 0])\n", "plt.title(\"最低价绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"最低价\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 6.2最高价走势比较" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.2.1 原始数据" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:04.376684Z", "start_time": "2020-06-30T13:04:03.964789Z" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "plt.plot(Company_test[\"日期\"].iloc[1:26], Company_test_temp[\"最高价\"].iloc[1:26])\n", "plt.title(\"最高价绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"最高价\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.2.2 预测数据" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:04.773627Z", "start_time": "2020-06-30T13:04:04.381672Z" }, "scrolled": true }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "# print(np.array(s[0]))\n", "plt.plot(Company_test[\"日期\"][1:26], result[:25, 1])\n", "plt.title(\"最高价绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"最高价\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 6.3收盘价走势比较" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.3.1 原始数据" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:05.164108Z", "start_time": "2020-06-30T13:04:04.776621Z" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "plt.plot(Company_test[\"日期\"].iloc[1:26], Company_test_temp[\"收盘价\"].iloc[1:26])\n", "plt.title(\"收盘价\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"收盘价\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.3.2 预测数据" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:05.521069Z", "start_time": "2020-06-30T13:04:05.167099Z" }, "scrolled": true }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "# print(np.array(s[0]))\n", "plt.plot(Company_test[\"日期\"][1:26], result[:25, 2])\n", "plt.title(\"收盘价绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"收盘价\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 6.4成交量走势预测" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.4.1 原始数据" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:05.914555Z", "start_time": "2020-06-30T13:04:05.524061Z" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "plt.plot(Company_test[\"日期\"].iloc[1:26], Company_test_temp[\"成交量\"].iloc[1:26])\n", "plt.title(\"成交量绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"成交量\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.4.2 预测数据" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:06.304512Z", "start_time": "2020-06-30T13:04:05.918545Z" }, "scrolled": true }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "# print(np.array(s[0]))\n", "plt.plot(Company_test[\"日期\"][1:26], result[:25, 3])\n", "plt.title(\"成交量绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"成交量\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 6.5 开盘价走势预测" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.3.1 原始数据" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:06.713931Z", "start_time": "2020-06-30T13:04:06.308501Z" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "plt.plot(Company_test[\"日期\"].iloc[1:26], Company_test_temp[\"开盘价\"].iloc[1:26])\n", "plt.title(\"开盘价绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"开盘价\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6.5.2 预测数据" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "ExecuteTime": { "end_time": "2020-06-30T13:04:07.093034Z", "start_time": "2020-06-30T13:04:06.718918Z" }, "scrolled": true }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"] # 用来正常显示中文标签\n", "plt.rcParams[\"axes.unicode_minus\"] = False # 用来正常显示负号\n", "\n", "plt.figure(figsize=(15, 3))\n", "\n", "# print(np.array(s[0]))\n", "plt.plot(Company_test[\"日期\"][1:26], result[:25, 4])\n", "plt.title(\"开盘价绘图\") # 图名\n", "plt.xlabel(\"日期\") # x轴标签\n", "plt.ylabel(\"开盘价\") # y轴标签\n", "plt.tick_params(axis='both') # x,y轴都有刻度\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.2" } }, "nbformat": 4, "nbformat_minor": 4 }