第零集 漫谈Python与金融.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "---\n",
    "\n",
    "# Python 金融之旅 —— “超级Excel”\n",
    "\n",
    "##### \"编程是一门艺术\" - Donald Knuth\n",
    "\n",
    "#### 目录\n",
    "1. [你想转正吗？](#introduction)\n",
    "2. [Python Pandas 的基础操作](#python-refresher)\n",
    "3. [从Python到量化...](#advanced-topics)\n",
    "\n",
    "[@Zhongfang Yuan(Harold)](mailto:zhongfangyuan@link.cuhk.edu.cn)\n",
    "###### 金融工程专业大四学生\n",
    "###### [申请金融工程硕士学位并担任内容创作者](https://space.bilibili.com/629573485)\n",
    "\n",
    "---\n",
    "\n",
    "### 1. 你想转正吗？ <a name=\"Introduction\"></a>\n",
    "\n",
    "- 为什么不用Excel？\n",
    "- 我讨厌编程！\n",
    "- Python？我不喜欢这个名字，听起来像一条巨蟒。\n",
    "\n",
    "##### “Python是一条巨蟒，它会把你吞下去”\n",
    "\n",
    "让我给你讲一个关于Rivers和Jae的故事。\n",
    "\n",
    "<font color=\"red\"> 很久很久以前，在一个遥远的银河系里... </font>\n",
    "\n",
    "##### 毕业后，Rivers和Jae在香港摩根大通找到了实习机会，成为专门研究房地产行业的股票分析师。他们都有金融背景。Rivers不会编程，因为他害怕编程！而Jae在港中大（深圳）上的FIN3080课程中学习了Python。\n",
    "##### 他们在大学时是最好的朋友，所以他们选的课程都一样，除了FIN3080，一门港中深的量化分析课。\n",
    "##### 在他们实习结束时，只有一个人可以留下。\n",
    "\n",
    "---\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"hengda.png\" alt=\"Sample Image\" width=\"50%\">\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "一天，他们的领导，Harold，走向他们，给他们带来了一条消息，说：\n",
    "嘿，你们这两个聪明人！我的客户对恒大很生气，问我们为什么之前没有建议他买入……你们试着给我一些关于何时以及为什么会发生这种情况的分析。哦，也许还可以分析一下其他公司。我有个会议要去了，今天下午之前给我。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rivers 转向Excel来分析数据，但他只能做到中学生水平的Excel操作。\n",
    "同时，Jae 尝试用Python来解决问题。\n",
    "由于这是一台新电脑，Jae下载并安装了他所需的Python包。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ! pip install pandas\n",
    "# ! pip install matplotlib  # he wants to draw pictures\n",
    "# ! pip install numpy\n",
    "# ! pip install seaborn\n",
    "\n",
    "# for mac\n",
    "# ! pip3 install pandas\n",
    "# ! pip3 install matplotlib  # he wants to draw pictures\n",
    "# ! pip3 install numpy\n",
    "# ! pip3 install seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "#画图\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[ 2,  6],\n",
       "        [ 5, 12]])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.matrix([[1, 2], [3, 4]])\n",
    "# a = [[1, 2],\n",
    "#      [3, 4]]\n",
    "b = np.matrix([[1, 4], [2, 8]])\n",
    "# b = [[1, 4],\n",
    "#      [2, 8]]\n",
    "\n",
    "# a +b  = [[2, 6],\n",
    "#          [5, 12]]\n",
    "\n",
    "a + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df = pd.DataFrame(np.random.randn(100, 4), columns=list('ABCD'))\n",
    "df = pd.read_excel(\"3333.HK.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>代码</th>\n",
       "      <th>简称</th>\n",
       "      <th>日期</th>\n",
       "      <th>前收盘价(元)</th>\n",
       "      <th>开盘价(元)</th>\n",
       "      <th>最高价(元)</th>\n",
       "      <th>最低价(元)</th>\n",
       "      <th>收盘价(元)</th>\n",
       "      <th>成交量(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)</th>\n",
       "      <th>成交金额(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)</th>\n",
       "      <th>...</th>\n",
       "      <th>A股流通市值(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)</th>\n",
       "      <th>B股流通市值(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)</th>\n",
       "      <th>总市值(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)</th>\n",
       "      <th>A股流通股本(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)</th>\n",
       "      <th>B股流通股本(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)</th>\n",
       "      <th>总股本(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)</th>\n",
       "      <th>市盈率</th>\n",
       "      <th>市净率</th>\n",
       "      <th>市销率</th>\n",
       "      <th>市现率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-05</td>\n",
       "      <td>--</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.80</td>\n",
       "      <td>3.81</td>\n",
       "      <td>4.70</td>\n",
       "      <td>1205691000</td>\n",
       "      <td>4951375460</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>7.050000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>234.4769</td>\n",
       "      <td>7.0885</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-06</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.65</td>\n",
       "      <td>4.80</td>\n",
       "      <td>4.41</td>\n",
       "      <td>4.58</td>\n",
       "      <td>485523000</td>\n",
       "      <td>2211906560</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.870000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>228.4902</td>\n",
       "      <td>6.9074</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-09</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.69</td>\n",
       "      <td>167349730</td>\n",
       "      <td>789367832</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>7.035000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>233.9780</td>\n",
       "      <td>7.0730</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-10</td>\n",
       "      <td>4.69</td>\n",
       "      <td>4.73</td>\n",
       "      <td>4.77</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.58</td>\n",
       "      <td>108415000</td>\n",
       "      <td>497236920</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.870000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>228.4902</td>\n",
       "      <td>6.9066</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-11</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.59</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.36</td>\n",
       "      <td>4.41</td>\n",
       "      <td>68496000</td>\n",
       "      <td>305624310</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.615000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>220.0092</td>\n",
       "      <td>6.6502</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3407</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-04</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.58</td>\n",
       "      <td>179485417</td>\n",
       "      <td>52910752</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>3.895269e+09</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.0495</td>\n",
       "      <td>-0.0065</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3408</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-05</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.69</td>\n",
       "      <td>251503540</td>\n",
       "      <td>81113253</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>4.621505e+09</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.0587</td>\n",
       "      <td>-0.0077</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3409</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-06</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.71</td>\n",
       "      <td>1.26</td>\n",
       "      <td>0.70</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1271456257</td>\n",
       "      <td>633395325</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>8.450753e+09</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.1074</td>\n",
       "      <td>-0.0141</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3410</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-07</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.43</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1.14</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1003565956</td>\n",
       "      <td>691153067</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>8.450753e+09</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.1074</td>\n",
       "      <td>-0.0141</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3411</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-11</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.31</td>\n",
       "      <td>1.53</td>\n",
       "      <td>1.16</td>\n",
       "      <td>1.51</td>\n",
       "      <td>530679150</td>\n",
       "      <td>368973167</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>1.016731e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.1292</td>\n",
       "      <td>-0.0170</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3412 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           代码    简称          日期 前收盘价(元)  开盘价(元)  最高价(元)  最低价(元)  收盘价(元)  \\\n",
       "0     3333.HK  中国恒大  2009-11-05      --    4.00    4.80    3.81    4.70   \n",
       "1     3333.HK  中国恒大  2009-11-06     4.7    4.65    4.80    4.41    4.58   \n",
       "2     3333.HK  中国恒大  2009-11-09    4.58    4.60    4.85    4.58    4.69   \n",
       "3     3333.HK  中国恒大  2009-11-10    4.69    4.73    4.77    4.45    4.58   \n",
       "4     3333.HK  中国恒大  2009-11-11    4.58    4.59    4.60    4.36    4.41   \n",
       "...       ...   ...         ...     ...     ...     ...     ...     ...   \n",
       "3407  3333.HK  中国恒大  2023-09-04    0.54    0.56    0.61    0.55    0.58   \n",
       "3408  3333.HK  中国恒大  2023-09-05    0.58    0.60    0.69    0.58    0.69   \n",
       "3409  3333.HK  中国恒大  2023-09-06    0.69    0.71    1.26    0.70    1.26   \n",
       "3410  3333.HK  中国恒大  2023-09-07    1.26    1.43    1.63    1.14    1.26   \n",
       "3411  3333.HK  中国恒大  2023-09-11    1.26    1.31    1.53    1.16    1.51   \n",
       "\n",
       "     成交量(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)  \\\n",
       "0                                            1205691000                         \n",
       "1                                             485523000                         \n",
       "2                                             167349730                         \n",
       "3                                             108415000                         \n",
       "4                                              68496000                         \n",
       "...                                                 ...                         \n",
       "3407                                          179485417                         \n",
       "3408                                          251503540                         \n",
       "3409                                         1271456257                         \n",
       "3410                                         1003565956                         \n",
       "3411                                          530679150                         \n",
       "\n",
       "     成交金额(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)  \\\n",
       "0                                            4951375460                          \n",
       "1                                            2211906560                          \n",
       "2                                             789367832                          \n",
       "3                                             497236920                          \n",
       "4                                             305624310                          \n",
       "...                                                 ...                          \n",
       "3407                                           52910752                          \n",
       "3408                                           81113253                          \n",
       "3409                                          633395325                          \n",
       "3410                                          691153067                          \n",
       "3411                                          368973167                          \n",
       "\n",
       "      ...  \\\n",
       "0     ...   \n",
       "1     ...   \n",
       "2     ...   \n",
       "3     ...   \n",
       "4     ...   \n",
       "...   ...   \n",
       "3407  ...   \n",
       "3408  ...   \n",
       "3409  ...   \n",
       "3410  ...   \n",
       "3411  ...   \n",
       "\n",
       "      A股流通市值(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)  \\\n",
       "0                                                    --                             \n",
       "1                                                    --                             \n",
       "2                                                    --                             \n",
       "3                                                    --                             \n",
       "4                                                    --                             \n",
       "...                                                 ...                             \n",
       "3407                                                 --                             \n",
       "3408                                                 --                             \n",
       "3409                                                 --                             \n",
       "3410                                                 --                             \n",
       "3411                                                 --                             \n",
       "\n",
       "      B股流通市值(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)  \\\n",
       "0                                                    --                             \n",
       "1                                                    --                             \n",
       "2                                                    --                             \n",
       "3                                                    --                             \n",
       "4                                                    --                             \n",
       "...                                                 ...                             \n",
       "3407                                                 --                             \n",
       "3408                                                 --                             \n",
       "3409                                                 --                             \n",
       "3410                                                 --                             \n",
       "3411                                                 --                             \n",
       "\n",
       "     总市值(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)(元)  \\\n",
       "0                                          7.050000e+10                         \n",
       "1                                          6.870000e+10                         \n",
       "2                                          7.035000e+10                         \n",
       "3                                          6.870000e+10                         \n",
       "4                                          6.615000e+10                         \n",
       "...                                                 ...                         \n",
       "3407                                       3.895269e+09                         \n",
       "3408                                       4.621505e+09                         \n",
       "3409                                       8.450753e+09                         \n",
       "3410                                       8.450753e+09                         \n",
       "3411                                       1.016731e+10                         \n",
       "\n",
       "     A股流通股本(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)  \\\n",
       "0                                                    --                            \n",
       "1                                                    --                            \n",
       "2                                                    --                            \n",
       "3                                                    --                            \n",
       "4                                                    --                            \n",
       "...                                                 ...                            \n",
       "3407                                                 --                            \n",
       "3408                                                 --                            \n",
       "3409                                                 --                            \n",
       "3410                                                 --                            \n",
       "3411                                                 --                            \n",
       "\n",
       "     B股流通股本(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)  \\\n",
       "0                                                    --                            \n",
       "1                                                    --                            \n",
       "2                                                    --                            \n",
       "3                                                    --                            \n",
       "4                                                    --                            \n",
       "...                                                 ...                            \n",
       "3407                                                 --                            \n",
       "3408                                                 --                            \n",
       "3409                                                 --                            \n",
       "3410                                                 --                            \n",
       "3411                                                 --                            \n",
       "\n",
       "     总股本(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)(股)  \\\n",
       "0                                           15000000000                         \n",
       "1                                           15000000000                         \n",
       "2                                           15000000000                         \n",
       "3                                           15000000000                         \n",
       "4                                           15000000000                         \n",
       "...                                                 ...                         \n",
       "3407                                        13204300900                         \n",
       "3408                                        13204300900                         \n",
       "3409                                        13204300900                         \n",
       "3410                                        13204300900                         \n",
       "3411                                        13204300900                         \n",
       "\n",
       "           市盈率     市净率 市销率  市现率  \n",
       "0     234.4769  7.0885  --   --  \n",
       "1     228.4902  6.9074  --   --  \n",
       "2     233.9780  7.0730  --   --  \n",
       "3     228.4902  6.9066  --   --  \n",
       "4     220.0092  6.6502  --   --  \n",
       "...        ...     ...  ..  ...  \n",
       "3407   -0.0495 -0.0065  --   --  \n",
       "3408   -0.0587 -0.0077  --   --  \n",
       "3409   -0.1074 -0.0141  --   --  \n",
       "3410   -0.1074 -0.0141  --   --  \n",
       "3411   -0.1292 -0.0170  --   --  \n",
       "\n",
       "[3412 rows x 24 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "df.columns = ['代码', '简称', '日期', '前收盘价', '开盘价', '最高价',\n",
    "               '最低价', '收盘价', '成交量', '成交金额', '涨跌(元)',\t\n",
    "               '涨跌幅(%)', '均价(元)','换手率(%)',  'A股流通市值', 'B股流通市值', \n",
    "               '总市值', 'A股流通股本', 'B股流通股本', '总股本', '市盈率', '市净率', '市销率', '市现率']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>代码</th>\n",
       "      <th>简称</th>\n",
       "      <th>日期</th>\n",
       "      <th>前收盘价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>收盘价</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>...</th>\n",
       "      <th>A股流通市值</th>\n",
       "      <th>B股流通市值</th>\n",
       "      <th>总市值</th>\n",
       "      <th>A股流通股本</th>\n",
       "      <th>B股流通股本</th>\n",
       "      <th>总股本</th>\n",
       "      <th>市盈率</th>\n",
       "      <th>市净率</th>\n",
       "      <th>市销率</th>\n",
       "      <th>市现率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-05</td>\n",
       "      <td>--</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.80</td>\n",
       "      <td>3.81</td>\n",
       "      <td>4.70</td>\n",
       "      <td>1205691000</td>\n",
       "      <td>4951375460</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>7.050000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>234.4769</td>\n",
       "      <td>7.0885</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-06</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.65</td>\n",
       "      <td>4.80</td>\n",
       "      <td>4.41</td>\n",
       "      <td>4.58</td>\n",
       "      <td>485523000</td>\n",
       "      <td>2211906560</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.870000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>228.4902</td>\n",
       "      <td>6.9074</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-09</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.69</td>\n",
       "      <td>167349730</td>\n",
       "      <td>789367832</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>7.035000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>233.9780</td>\n",
       "      <td>7.0730</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-10</td>\n",
       "      <td>4.69</td>\n",
       "      <td>4.73</td>\n",
       "      <td>4.77</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.58</td>\n",
       "      <td>108415000</td>\n",
       "      <td>497236920</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.870000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>228.4902</td>\n",
       "      <td>6.9066</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-11</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.59</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.36</td>\n",
       "      <td>4.41</td>\n",
       "      <td>68496000</td>\n",
       "      <td>305624310</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.615000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>220.0092</td>\n",
       "      <td>6.6502</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3407</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-04</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.58</td>\n",
       "      <td>179485417</td>\n",
       "      <td>52910752</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>3.895269e+09</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.0495</td>\n",
       "      <td>-0.0065</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3408</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-05</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.69</td>\n",
       "      <td>251503540</td>\n",
       "      <td>81113253</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>4.621505e+09</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.0587</td>\n",
       "      <td>-0.0077</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3409</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-06</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.71</td>\n",
       "      <td>1.26</td>\n",
       "      <td>0.70</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1271456257</td>\n",
       "      <td>633395325</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>8.450753e+09</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.1074</td>\n",
       "      <td>-0.0141</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3410</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-07</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.43</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1.14</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1003565956</td>\n",
       "      <td>691153067</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>8.450753e+09</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.1074</td>\n",
       "      <td>-0.0141</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3411</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2023-09-11</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.31</td>\n",
       "      <td>1.53</td>\n",
       "      <td>1.16</td>\n",
       "      <td>1.51</td>\n",
       "      <td>530679150</td>\n",
       "      <td>368973167</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>1.016731e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>-0.1292</td>\n",
       "      <td>-0.0170</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3412 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           代码    简称          日期  前收盘价   开盘价   最高价   最低价   收盘价         成交量  \\\n",
       "0     3333.HK  中国恒大  2009-11-05    --  4.00  4.80  3.81  4.70  1205691000   \n",
       "1     3333.HK  中国恒大  2009-11-06   4.7  4.65  4.80  4.41  4.58   485523000   \n",
       "2     3333.HK  中国恒大  2009-11-09  4.58  4.60  4.85  4.58  4.69   167349730   \n",
       "3     3333.HK  中国恒大  2009-11-10  4.69  4.73  4.77  4.45  4.58   108415000   \n",
       "4     3333.HK  中国恒大  2009-11-11  4.58  4.59  4.60  4.36  4.41    68496000   \n",
       "...       ...   ...         ...   ...   ...   ...   ...   ...         ...   \n",
       "3407  3333.HK  中国恒大  2023-09-04  0.54  0.56  0.61  0.55  0.58   179485417   \n",
       "3408  3333.HK  中国恒大  2023-09-05  0.58  0.60  0.69  0.58  0.69   251503540   \n",
       "3409  3333.HK  中国恒大  2023-09-06  0.69  0.71  1.26  0.70  1.26  1271456257   \n",
       "3410  3333.HK  中国恒大  2023-09-07  1.26  1.43  1.63  1.14  1.26  1003565956   \n",
       "3411  3333.HK  中国恒大  2023-09-11  1.26  1.31  1.53  1.16  1.51   530679150   \n",
       "\n",
       "            成交金额  ...  A股流通市值  B股流通市值           总市值 A股流通股本 B股流通股本  \\\n",
       "0     4951375460  ...      --      --  7.050000e+10     --     --   \n",
       "1     2211906560  ...      --      --  6.870000e+10     --     --   \n",
       "2      789367832  ...      --      --  7.035000e+10     --     --   \n",
       "3      497236920  ...      --      --  6.870000e+10     --     --   \n",
       "4      305624310  ...      --      --  6.615000e+10     --     --   \n",
       "...          ...  ...     ...     ...           ...    ...    ...   \n",
       "3407    52910752  ...      --      --  3.895269e+09     --     --   \n",
       "3408    81113253  ...      --      --  4.621505e+09     --     --   \n",
       "3409   633395325  ...      --      --  8.450753e+09     --     --   \n",
       "3410   691153067  ...      --      --  8.450753e+09     --     --   \n",
       "3411   368973167  ...      --      --  1.016731e+10     --     --   \n",
       "\n",
       "              总股本       市盈率     市净率 市销率  市现率  \n",
       "0     15000000000  234.4769  7.0885  --   --  \n",
       "1     15000000000  228.4902  6.9074  --   --  \n",
       "2     15000000000  233.9780  7.0730  --   --  \n",
       "3     15000000000  228.4902  6.9066  --   --  \n",
       "4     15000000000  220.0092  6.6502  --   --  \n",
       "...           ...       ...     ...  ..  ...  \n",
       "3407  13204300900   -0.0495 -0.0065  --   --  \n",
       "3408  13204300900   -0.0587 -0.0077  --   --  \n",
       "3409  13204300900   -0.1074 -0.0141  --   --  \n",
       "3410  13204300900   -0.1074 -0.0141  --   --  \n",
       "3411  13204300900   -0.1292 -0.0170  --   --  \n",
       "\n",
       "[3412 rows x 24 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据看起来很混乱，但不用担心，Jae上过FIN3080，他见过更糟糕的情况。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>代码</th>\n",
       "      <th>简称</th>\n",
       "      <th>日期</th>\n",
       "      <th>前收盘价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>收盘价</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>...</th>\n",
       "      <th>A股流通市值</th>\n",
       "      <th>B股流通市值</th>\n",
       "      <th>总市值</th>\n",
       "      <th>A股流通股本</th>\n",
       "      <th>B股流通股本</th>\n",
       "      <th>总股本</th>\n",
       "      <th>市盈率</th>\n",
       "      <th>市净率</th>\n",
       "      <th>市销率</th>\n",
       "      <th>市现率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.80</td>\n",
       "      <td>3.81</td>\n",
       "      <td>4.70</td>\n",
       "      <td>1.205691e+09</td>\n",
       "      <td>4.951375e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>7.050000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>234.4769</td>\n",
       "      <td>7.0885</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-06</td>\n",
       "      <td>4.70</td>\n",
       "      <td>4.65</td>\n",
       "      <td>4.80</td>\n",
       "      <td>4.41</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.855230e+08</td>\n",
       "      <td>2.211907e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.870000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>228.4902</td>\n",
       "      <td>6.9074</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-09</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.69</td>\n",
       "      <td>1.673497e+08</td>\n",
       "      <td>7.893678e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>7.035000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>233.9780</td>\n",
       "      <td>7.0730</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-10</td>\n",
       "      <td>4.69</td>\n",
       "      <td>4.73</td>\n",
       "      <td>4.77</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.58</td>\n",
       "      <td>1.084150e+08</td>\n",
       "      <td>4.972369e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.870000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>228.4902</td>\n",
       "      <td>6.9066</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-11</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.59</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.36</td>\n",
       "      <td>4.41</td>\n",
       "      <td>6.849600e+07</td>\n",
       "      <td>3.056243e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.615000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>220.0092</td>\n",
       "      <td>6.6502</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        代码    简称         日期  前收盘价   开盘价   最高价   最低价   收盘价           成交量  \\\n",
       "0  3333.HK  中国恒大 2009-11-05   NaN  4.00  4.80  3.81  4.70  1.205691e+09   \n",
       "1  3333.HK  中国恒大 2009-11-06  4.70  4.65  4.80  4.41  4.58  4.855230e+08   \n",
       "2  3333.HK  中国恒大 2009-11-09  4.58  4.60  4.85  4.58  4.69  1.673497e+08   \n",
       "3  3333.HK  中国恒大 2009-11-10  4.69  4.73  4.77  4.45  4.58  1.084150e+08   \n",
       "4  3333.HK  中国恒大 2009-11-11  4.58  4.59  4.60  4.36  4.41  6.849600e+07   \n",
       "\n",
       "           成交金额  ...  A股流通市值  B股流通市值           总市值 A股流通股本 B股流通股本          总股本  \\\n",
       "0  4.951375e+09  ...      --      --  7.050000e+10     --     --  15000000000   \n",
       "1  2.211907e+09  ...      --      --  6.870000e+10     --     --  15000000000   \n",
       "2  7.893678e+08  ...      --      --  7.035000e+10     --     --  15000000000   \n",
       "3  4.972369e+08  ...      --      --  6.870000e+10     --     --  15000000000   \n",
       "4  3.056243e+08  ...      --      --  6.615000e+10     --     --  15000000000   \n",
       "\n",
       "        市盈率     市净率 市销率  市现率  \n",
       "0  234.4769  7.0885  --   --  \n",
       "1  228.4902  6.9074  --   --  \n",
       "2  233.9780  7.0730  --   --  \n",
       "3  228.4902  6.9066  --   --  \n",
       "4  220.0092  6.6502  --   --  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "df['代码'] = df['代码'].astype(str)\n",
    "df['简称'] = df['简称'].astype(str)\n",
    "\n",
    "df['日期'] = pd.to_datetime(df['日期'])\n",
    "\n",
    "df['成交量'] = df['成交量'].replace('--', None)\n",
    "df['成交金额'] = df['成交金额'].replace('--', None)\n",
    "df['前收盘价'] = df['前收盘价'].replace('--', None)\n",
    "\n",
    "df['成交量'] = df['成交量'].astype(float)\n",
    "df['成交金额'] = df['成交金额'].astype(float)\n",
    "df['前收盘价'] = df['前收盘价'].astype(float)\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3412 entries, 0 to 3411\n",
      "Data columns (total 24 columns):\n",
      " #   Column  Non-Null Count  Dtype         \n",
      "---  ------  --------------  -----         \n",
      " 0   代码      3412 non-null   object        \n",
      " 1   简称      3412 non-null   object        \n",
      " 2   日期      3412 non-null   datetime64[ns]\n",
      " 3   前收盘价    3411 non-null   float64       \n",
      " 4   开盘价     3412 non-null   float64       \n",
      " 5   最高价     3412 non-null   float64       \n",
      " 6   最低价     3412 non-null   float64       \n",
      " 7   收盘价     3412 non-null   float64       \n",
      " 8   成交量     3046 non-null   float64       \n",
      " 9   成交金额    3046 non-null   float64       \n",
      " 10  涨跌(元)   3412 non-null   float64       \n",
      " 11  涨跌幅(%)  3412 non-null   float64       \n",
      " 12  均价(元)   3412 non-null   object        \n",
      " 13  换手率(%)  3412 non-null   object        \n",
      " 14  A股流通市值  3412 non-null   object        \n",
      " 15  B股流通市值  3412 non-null   object        \n",
      " 16  总市值     3412 non-null   float64       \n",
      " 17  A股流通股本  3412 non-null   object        \n",
      " 18  B股流通股本  3412 non-null   object        \n",
      " 19  总股本     3412 non-null   int64         \n",
      " 20  市盈率     3412 non-null   float64       \n",
      " 21  市净率     3412 non-null   float64       \n",
      " 22  市销率     3412 non-null   object        \n",
      " 23  市现率     3412 non-null   object        \n",
      "dtypes: datetime64[ns](1), float64(12), int64(1), object(10)\n",
      "memory usage: 639.9+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>日期</th>\n",
       "      <th>前收盘价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>收盘价</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>涨跌(元)</th>\n",
       "      <th>涨跌幅(%)</th>\n",
       "      <th>总市值</th>\n",
       "      <th>总股本</th>\n",
       "      <th>市盈率</th>\n",
       "      <th>市净率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3412</td>\n",
       "      <td>3411.000000</td>\n",
       "      <td>3412.000000</td>\n",
       "      <td>3412.000000</td>\n",
       "      <td>3412.000000</td>\n",
       "      <td>3412.000000</td>\n",
       "      <td>3.046000e+03</td>\n",
       "      <td>3.046000e+03</td>\n",
       "      <td>3412.000000</td>\n",
       "      <td>3412.000000</td>\n",
       "      <td>3.412000e+03</td>\n",
       "      <td>3.412000e+03</td>\n",
       "      <td>3412.000000</td>\n",
       "      <td>3412.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2016-10-05 00:08:26.447831296</td>\n",
       "      <td>14.170833</td>\n",
       "      <td>14.194997</td>\n",
       "      <td>14.463860</td>\n",
       "      <td>13.876339</td>\n",
       "      <td>14.167122</td>\n",
       "      <td>5.405282e+07</td>\n",
       "      <td>3.518338e+08</td>\n",
       "      <td>-0.000586</td>\n",
       "      <td>0.060415</td>\n",
       "      <td>1.172663e+11</td>\n",
       "      <td>1.407033e+10</td>\n",
       "      <td>14.678715</td>\n",
       "      <td>1.580284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2009-11-05 00:00:00</td>\n",
       "      <td>0.530000</td>\n",
       "      <td>0.430000</td>\n",
       "      <td>0.590000</td>\n",
       "      <td>0.430000</td>\n",
       "      <td>0.530000</td>\n",
       "      <td>2.594010e+06</td>\n",
       "      <td>1.405174e+07</td>\n",
       "      <td>-6.330000</td>\n",
       "      <td>-78.787900</td>\n",
       "      <td>3.565161e+09</td>\n",
       "      <td>1.303703e+10</td>\n",
       "      <td>-0.183800</td>\n",
       "      <td>-0.040100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2013-04-18 18:00:00</td>\n",
       "      <td>3.540000</td>\n",
       "      <td>3.550000</td>\n",
       "      <td>3.630000</td>\n",
       "      <td>3.470000</td>\n",
       "      <td>3.540000</td>\n",
       "      <td>1.770011e+07</td>\n",
       "      <td>1.184267e+08</td>\n",
       "      <td>-0.100000</td>\n",
       "      <td>-1.376100</td>\n",
       "      <td>4.753303e+10</td>\n",
       "      <td>1.320430e+10</td>\n",
       "      <td>3.573000</td>\n",
       "      <td>0.861650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2016-10-04 12:00:00</td>\n",
       "      <td>5.040000</td>\n",
       "      <td>5.045000</td>\n",
       "      <td>5.170000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>5.040000</td>\n",
       "      <td>3.206565e+07</td>\n",
       "      <td>2.251348e+08</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.621640e+10</td>\n",
       "      <td>1.368107e+10</td>\n",
       "      <td>6.010350</td>\n",
       "      <td>1.345150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2020-03-23 06:00:00</td>\n",
       "      <td>28.465000</td>\n",
       "      <td>28.520000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>27.730000</td>\n",
       "      <td>28.457500</td>\n",
       "      <td>6.429147e+07</td>\n",
       "      <td>4.117172e+08</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>1.289100</td>\n",
       "      <td>2.002347e+11</td>\n",
       "      <td>1.496999e+10</td>\n",
       "      <td>14.339900</td>\n",
       "      <td>2.017650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2023-09-11 00:00:00</td>\n",
       "      <td>52.550000</td>\n",
       "      <td>53.030000</td>\n",
       "      <td>53.770000</td>\n",
       "      <td>51.620000</td>\n",
       "      <td>52.550000</td>\n",
       "      <td>1.925707e+09</td>\n",
       "      <td>1.051735e+10</td>\n",
       "      <td>7.280000</td>\n",
       "      <td>82.857100</td>\n",
       "      <td>4.144097e+11</td>\n",
       "      <td>1.604961e+10</td>\n",
       "      <td>234.476900</td>\n",
       "      <td>7.088500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>14.739339</td>\n",
       "      <td>14.770053</td>\n",
       "      <td>15.057941</td>\n",
       "      <td>14.415812</td>\n",
       "      <td>14.738772</td>\n",
       "      <td>8.690731e+07</td>\n",
       "      <td>4.760714e+08</td>\n",
       "      <td>0.694791</td>\n",
       "      <td>3.897873</td>\n",
       "      <td>1.053160e+11</td>\n",
       "      <td>9.663417e+08</td>\n",
       "      <td>32.189503</td>\n",
       "      <td>1.205894</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  日期         前收盘价          开盘价          最高价  \\\n",
       "count                           3412  3411.000000  3412.000000  3412.000000   \n",
       "mean   2016-10-05 00:08:26.447831296    14.170833    14.194997    14.463860   \n",
       "min              2009-11-05 00:00:00     0.530000     0.430000     0.590000   \n",
       "25%              2013-04-18 18:00:00     3.540000     3.550000     3.630000   \n",
       "50%              2016-10-04 12:00:00     5.040000     5.045000     5.170000   \n",
       "75%              2020-03-23 06:00:00    28.465000    28.520000    29.000000   \n",
       "max              2023-09-11 00:00:00    52.550000    53.030000    53.770000   \n",
       "std                              NaN    14.739339    14.770053    15.057941   \n",
       "\n",
       "               最低价          收盘价           成交量          成交金额        涨跌(元)  \\\n",
       "count  3412.000000  3412.000000  3.046000e+03  3.046000e+03  3412.000000   \n",
       "mean     13.876339    14.167122  5.405282e+07  3.518338e+08    -0.000586   \n",
       "min       0.430000     0.530000  2.594010e+06  1.405174e+07    -6.330000   \n",
       "25%       3.470000     3.540000  1.770011e+07  1.184267e+08    -0.100000   \n",
       "50%       4.920000     5.040000  3.206565e+07  2.251348e+08     0.000000   \n",
       "75%      27.730000    28.457500  6.429147e+07  4.117172e+08     0.090000   \n",
       "max      51.620000    52.550000  1.925707e+09  1.051735e+10     7.280000   \n",
       "std      14.415812    14.738772  8.690731e+07  4.760714e+08     0.694791   \n",
       "\n",
       "            涨跌幅(%)           总市值           总股本          市盈率          市净率  \n",
       "count  3412.000000  3.412000e+03  3.412000e+03  3412.000000  3412.000000  \n",
       "mean      0.060415  1.172663e+11  1.407033e+10    14.678715     1.580284  \n",
       "min     -78.787900  3.565161e+09  1.303703e+10    -0.183800    -0.040100  \n",
       "25%      -1.376100  4.753303e+10  1.320430e+10     3.573000     0.861650  \n",
       "50%       0.000000  6.621640e+10  1.368107e+10     6.010350     1.345150  \n",
       "75%       1.289100  2.002347e+11  1.496999e+10    14.339900     2.017650  \n",
       "max      82.857100  4.144097e+11  1.604961e+10   234.476900     7.088500  \n",
       "std       3.897873  1.053160e+11  9.663417e+08    32.189503     1.205894  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>代码</th>\n",
       "      <th>简称</th>\n",
       "      <th>日期</th>\n",
       "      <th>前收盘价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>收盘价</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>...</th>\n",
       "      <th>A股流通市值</th>\n",
       "      <th>B股流通市值</th>\n",
       "      <th>总市值</th>\n",
       "      <th>A股流通股本</th>\n",
       "      <th>B股流通股本</th>\n",
       "      <th>总股本</th>\n",
       "      <th>市盈率</th>\n",
       "      <th>市净率</th>\n",
       "      <th>市销率</th>\n",
       "      <th>市现率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.80</td>\n",
       "      <td>3.81</td>\n",
       "      <td>4.70</td>\n",
       "      <td>1.205691e+09</td>\n",
       "      <td>4.951375e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>7.050000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>234.4769</td>\n",
       "      <td>7.0885</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-06</td>\n",
       "      <td>4.70</td>\n",
       "      <td>4.65</td>\n",
       "      <td>4.80</td>\n",
       "      <td>4.41</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.855230e+08</td>\n",
       "      <td>2.211907e+09</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.870000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>228.4902</td>\n",
       "      <td>6.9074</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-09</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.69</td>\n",
       "      <td>1.673497e+08</td>\n",
       "      <td>7.893678e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>7.035000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>233.9780</td>\n",
       "      <td>7.0730</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-10</td>\n",
       "      <td>4.69</td>\n",
       "      <td>4.73</td>\n",
       "      <td>4.77</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.58</td>\n",
       "      <td>1.084150e+08</td>\n",
       "      <td>4.972369e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.870000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>228.4902</td>\n",
       "      <td>6.9066</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>2009-11-11</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.59</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.36</td>\n",
       "      <td>4.41</td>\n",
       "      <td>6.849600e+07</td>\n",
       "      <td>3.056243e+08</td>\n",
       "      <td>...</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6.615000e+10</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>15000000000</td>\n",
       "      <td>220.0092</td>\n",
       "      <td>6.6502</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        代码    简称         日期  前收盘价   开盘价   最高价   最低价   收盘价           成交量  \\\n",
       "0  3333.HK  中国恒大 2009-11-05   NaN  4.00  4.80  3.81  4.70  1.205691e+09   \n",
       "1  3333.HK  中国恒大 2009-11-06  4.70  4.65  4.80  4.41  4.58  4.855230e+08   \n",
       "2  3333.HK  中国恒大 2009-11-09  4.58  4.60  4.85  4.58  4.69  1.673497e+08   \n",
       "3  3333.HK  中国恒大 2009-11-10  4.69  4.73  4.77  4.45  4.58  1.084150e+08   \n",
       "4  3333.HK  中国恒大 2009-11-11  4.58  4.59  4.60  4.36  4.41  6.849600e+07   \n",
       "\n",
       "           成交金额  ...  A股流通市值  B股流通市值           总市值 A股流通股本 B股流通股本          总股本  \\\n",
       "0  4.951375e+09  ...      --      --  7.050000e+10     --     --  15000000000   \n",
       "1  2.211907e+09  ...      --      --  6.870000e+10     --     --  15000000000   \n",
       "2  7.893678e+08  ...      --      --  7.035000e+10     --     --  15000000000   \n",
       "3  4.972369e+08  ...      --      --  6.870000e+10     --     --  15000000000   \n",
       "4  3.056243e+08  ...      --      --  6.615000e+10     --     --  15000000000   \n",
       "\n",
       "        市盈率     市净率 市销率  市现率  \n",
       "0  234.4769  7.0885  --   --  \n",
       "1  228.4902  6.9074  --   --  \n",
       "2  233.9780  7.0730  --   --  \n",
       "3  228.4902  6.9066  --   --  \n",
       "4  220.0092  6.6502  --   --  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.sort_values(['代码',\"日期\"],inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 我想要通过各种方式，得到我想要的涨跌幅\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['收盘价'] = df['收盘价'].fillna(method='ffill')\n",
    "\n",
    "df['日频收益'] = df['收盘价'].pct_change()\n",
    "df['日频收益_log'] = np.log(df['收盘价']/df['收盘价'].shift(1))\n",
    "\n",
    "df['累计收益'] = df['日频收益'].cumsum()\n",
    "df['累计收益_log'] = df['日频收益_log'].cumsum()\n",
    "df['累计收益_2'] = df['日频收益'].apply(lambda x: (1+x)).cumprod()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# In Windows:\n",
    "# plt.rcParams['font.family'] = 'SimHei'\n",
    "\n",
    "plt.rcParams['font.family'] = ['Arial Unicode MS']\n",
    "plt.rcParams['figure.figsize'] = [5, 3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"close_ma_5\"] = df[\"收盘价\"].rolling(5).mean()\n",
    "df[\"close_ma_20\"] = df[\"收盘价\"].rolling(20).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x13a585af0>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['收盘价','close_ma_5','close_ma_20']].plot()\n",
    "\n",
    "plt.xlabel('日期')\n",
    "plt.ylabel('收盘价')\n",
    "plt.title('收盘价走势图')\n",
    "plt.legend(['收盘价','close_ma_5','close_ma_20'])\n",
    "plt.legend(loc='upper left')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>代码</th>\n",
       "      <th>简称</th>\n",
       "      <th>前收盘价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>收盘价</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>涨跌(元)</th>\n",
       "      <th>...</th>\n",
       "      <th>市净率</th>\n",
       "      <th>市销率</th>\n",
       "      <th>市现率</th>\n",
       "      <th>日频收益</th>\n",
       "      <th>日频收益_log</th>\n",
       "      <th>累计收益</th>\n",
       "      <th>累计收益_log</th>\n",
       "      <th>累计收益_2</th>\n",
       "      <th>close_ma_5</th>\n",
       "      <th>close_ma_20</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>日期</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009-11-05</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.80</td>\n",
       "      <td>3.81</td>\n",
       "      <td>4.70</td>\n",
       "      <td>1.205691e+09</td>\n",
       "      <td>4.951375e+09</td>\n",
       "      <td>1.20</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0885</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-11-06</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>4.70</td>\n",
       "      <td>4.65</td>\n",
       "      <td>4.80</td>\n",
       "      <td>4.41</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.855230e+08</td>\n",
       "      <td>2.211907e+09</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>...</td>\n",
       "      <td>6.9074</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>-0.025532</td>\n",
       "      <td>-0.025864</td>\n",
       "      <td>-0.025532</td>\n",
       "      <td>-0.025864</td>\n",
       "      <td>0.974468</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-11-09</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.69</td>\n",
       "      <td>1.673497e+08</td>\n",
       "      <td>7.893678e+08</td>\n",
       "      <td>0.11</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0730</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>0.024017</td>\n",
       "      <td>0.023734</td>\n",
       "      <td>-0.001514</td>\n",
       "      <td>-0.002130</td>\n",
       "      <td>0.997872</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-11-10</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>4.69</td>\n",
       "      <td>4.73</td>\n",
       "      <td>4.77</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.58</td>\n",
       "      <td>1.084150e+08</td>\n",
       "      <td>4.972369e+08</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>...</td>\n",
       "      <td>6.9066</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>-0.023454</td>\n",
       "      <td>-0.023734</td>\n",
       "      <td>-0.024969</td>\n",
       "      <td>-0.025864</td>\n",
       "      <td>0.974468</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-11-11</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.59</td>\n",
       "      <td>4.60</td>\n",
       "      <td>4.36</td>\n",
       "      <td>4.41</td>\n",
       "      <td>6.849600e+07</td>\n",
       "      <td>3.056243e+08</td>\n",
       "      <td>-0.17</td>\n",
       "      <td>...</td>\n",
       "      <td>6.6502</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>-0.037118</td>\n",
       "      <td>-0.037824</td>\n",
       "      <td>-0.062087</td>\n",
       "      <td>-0.063688</td>\n",
       "      <td>0.938298</td>\n",
       "      <td>4.592</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-04</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>0.54</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.58</td>\n",
       "      <td>1.794854e+08</td>\n",
       "      <td>5.291075e+07</td>\n",
       "      <td>0.04</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0065</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>0.074074</td>\n",
       "      <td>0.071459</td>\n",
       "      <td>0.500390</td>\n",
       "      <td>-2.092290</td>\n",
       "      <td>0.123404</td>\n",
       "      <td>0.586</td>\n",
       "      <td>2.5765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-05</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.69</td>\n",
       "      <td>2.515035e+08</td>\n",
       "      <td>8.111325e+07</td>\n",
       "      <td>0.11</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0077</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>0.189655</td>\n",
       "      <td>0.173663</td>\n",
       "      <td>0.690045</td>\n",
       "      <td>-1.918626</td>\n",
       "      <td>0.146809</td>\n",
       "      <td>0.586</td>\n",
       "      <td>2.4490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-06</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.71</td>\n",
       "      <td>1.26</td>\n",
       "      <td>0.70</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.271456e+09</td>\n",
       "      <td>6.333953e+08</td>\n",
       "      <td>0.57</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0141</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>0.826087</td>\n",
       "      <td>0.602175</td>\n",
       "      <td>1.516132</td>\n",
       "      <td>-1.316451</td>\n",
       "      <td>0.268085</td>\n",
       "      <td>0.720</td>\n",
       "      <td>2.3500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-07</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.43</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1.14</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.003566e+09</td>\n",
       "      <td>6.911531e+08</td>\n",
       "      <td>0.00</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0141</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.516132</td>\n",
       "      <td>-1.316451</td>\n",
       "      <td>0.268085</td>\n",
       "      <td>0.866</td>\n",
       "      <td>2.2510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-11</th>\n",
       "      <td>3333.HK</td>\n",
       "      <td>中国恒大</td>\n",
       "      <td>1.26</td>\n",
       "      <td>1.31</td>\n",
       "      <td>1.53</td>\n",
       "      <td>1.16</td>\n",
       "      <td>1.51</td>\n",
       "      <td>5.306792e+08</td>\n",
       "      <td>3.689732e+08</td>\n",
       "      <td>0.26</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.0170</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>0.198413</td>\n",
       "      <td>0.180998</td>\n",
       "      <td>1.714545</td>\n",
       "      <td>-1.135453</td>\n",
       "      <td>0.321277</td>\n",
       "      <td>1.060</td>\n",
       "      <td>2.1645</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3412 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 代码    简称  前收盘价   开盘价   最高价   最低价   收盘价           成交量  \\\n",
       "日期                                                                      \n",
       "2009-11-05  3333.HK  中国恒大   NaN  4.00  4.80  3.81  4.70  1.205691e+09   \n",
       "2009-11-06  3333.HK  中国恒大  4.70  4.65  4.80  4.41  4.58  4.855230e+08   \n",
       "2009-11-09  3333.HK  中国恒大  4.58  4.60  4.85  4.58  4.69  1.673497e+08   \n",
       "2009-11-10  3333.HK  中国恒大  4.69  4.73  4.77  4.45  4.58  1.084150e+08   \n",
       "2009-11-11  3333.HK  中国恒大  4.58  4.59  4.60  4.36  4.41  6.849600e+07   \n",
       "...             ...   ...   ...   ...   ...   ...   ...           ...   \n",
       "2023-09-04  3333.HK  中国恒大  0.54  0.56  0.61  0.55  0.58  1.794854e+08   \n",
       "2023-09-05  3333.HK  中国恒大  0.58  0.60  0.69  0.58  0.69  2.515035e+08   \n",
       "2023-09-06  3333.HK  中国恒大  0.69  0.71  1.26  0.70  1.26  1.271456e+09   \n",
       "2023-09-07  3333.HK  中国恒大  1.26  1.43  1.63  1.14  1.26  1.003566e+09   \n",
       "2023-09-11  3333.HK  中国恒大  1.26  1.31  1.53  1.16  1.51  5.306792e+08   \n",
       "\n",
       "                    成交金额  涨跌(元)  ...     市净率 市销率 市现率      日频收益  日频收益_log  \\\n",
       "日期                               ...                                       \n",
       "2009-11-05  4.951375e+09   1.20  ...  7.0885  --  --       NaN       NaN   \n",
       "2009-11-06  2.211907e+09  -0.12  ...  6.9074  --  -- -0.025532 -0.025864   \n",
       "2009-11-09  7.893678e+08   0.11  ...  7.0730  --  --  0.024017  0.023734   \n",
       "2009-11-10  4.972369e+08  -0.11  ...  6.9066  --  -- -0.023454 -0.023734   \n",
       "2009-11-11  3.056243e+08  -0.17  ...  6.6502  --  -- -0.037118 -0.037824   \n",
       "...                  ...    ...  ...     ...  ..  ..       ...       ...   \n",
       "2023-09-04  5.291075e+07   0.04  ... -0.0065  --  --  0.074074  0.071459   \n",
       "2023-09-05  8.111325e+07   0.11  ... -0.0077  --  --  0.189655  0.173663   \n",
       "2023-09-06  6.333953e+08   0.57  ... -0.0141  --  --  0.826087  0.602175   \n",
       "2023-09-07  6.911531e+08   0.00  ... -0.0141  --  --  0.000000  0.000000   \n",
       "2023-09-11  3.689732e+08   0.26  ... -0.0170  --  --  0.198413  0.180998   \n",
       "\n",
       "                累计收益  累计收益_log    累计收益_2  close_ma_5  close_ma_20  \n",
       "日期                                                                 \n",
       "2009-11-05       NaN       NaN       NaN         NaN          NaN  \n",
       "2009-11-06 -0.025532 -0.025864  0.974468         NaN          NaN  \n",
       "2009-11-09 -0.001514 -0.002130  0.997872         NaN          NaN  \n",
       "2009-11-10 -0.024969 -0.025864  0.974468         NaN          NaN  \n",
       "2009-11-11 -0.062087 -0.063688  0.938298       4.592          NaN  \n",
       "...              ...       ...       ...         ...          ...  \n",
       "2023-09-04  0.500390 -2.092290  0.123404       0.586       2.5765  \n",
       "2023-09-05  0.690045 -1.918626  0.146809       0.586       2.4490  \n",
       "2023-09-06  1.516132 -1.316451  0.268085       0.720       2.3500  \n",
       "2023-09-07  1.516132 -1.316451  0.268085       0.866       2.2510  \n",
       "2023-09-11  1.714545 -1.135453  0.321277       1.060       2.1645  \n",
       "\n",
       "[3412 rows x 30 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_recent = df[df.index>'2023-08-01']\n",
    "df_recent[['收盘价','close_ma_5','close_ma_20']].plot()\n",
    "plt.grid()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>收盘价</th>\n",
       "      <th>涨跌幅(%)</th>\n",
       "      <th>换手率(%)</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>市盈率</th>\n",
       "      <th>市净率</th>\n",
       "      <th>总股本</th>\n",
       "      <th>close_ma_5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>日期</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-08-24</th>\n",
       "      <td>3.24</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>--</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.1838</td>\n",
       "      <td>-0.0400</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>3.240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-25</th>\n",
       "      <td>3.24</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>--</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.1838</td>\n",
       "      <td>-0.0400</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>3.240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-28</th>\n",
       "      <td>0.69</td>\n",
       "      <td>-78.7879</td>\n",
       "      <td>13.9933</td>\n",
       "      <td>582346873.0</td>\n",
       "      <td>-0.0587</td>\n",
       "      <td>-0.0077</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>2.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-29</th>\n",
       "      <td>0.59</td>\n",
       "      <td>-14.2857</td>\n",
       "      <td>3.9602</td>\n",
       "      <td>165698771.0</td>\n",
       "      <td>-0.0503</td>\n",
       "      <td>-0.0066</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>2.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-30</th>\n",
       "      <td>0.53</td>\n",
       "      <td>-10.0000</td>\n",
       "      <td>1.9645</td>\n",
       "      <td>71924595.0</td>\n",
       "      <td>-0.0453</td>\n",
       "      <td>-0.0059</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>1.658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>0.54</td>\n",
       "      <td>1.8519</td>\n",
       "      <td>1.6063</td>\n",
       "      <td>60117438.0</td>\n",
       "      <td>-0.0461</td>\n",
       "      <td>-0.0060</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>1.118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-04</th>\n",
       "      <td>0.58</td>\n",
       "      <td>7.2727</td>\n",
       "      <td>1.3593</td>\n",
       "      <td>52910752.0</td>\n",
       "      <td>-0.0495</td>\n",
       "      <td>-0.0065</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>0.586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-05</th>\n",
       "      <td>0.69</td>\n",
       "      <td>18.6441</td>\n",
       "      <td>1.9047</td>\n",
       "      <td>81113253.0</td>\n",
       "      <td>-0.0587</td>\n",
       "      <td>-0.0077</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>0.586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-06</th>\n",
       "      <td>1.26</td>\n",
       "      <td>82.8571</td>\n",
       "      <td>9.6291</td>\n",
       "      <td>633395325.0</td>\n",
       "      <td>-0.1074</td>\n",
       "      <td>-0.0141</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>0.720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-07</th>\n",
       "      <td>1.26</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>7.6003</td>\n",
       "      <td>691153067.0</td>\n",
       "      <td>-0.1074</td>\n",
       "      <td>-0.0141</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>0.866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-11</th>\n",
       "      <td>1.51</td>\n",
       "      <td>20.3125</td>\n",
       "      <td>4.019</td>\n",
       "      <td>368973167.0</td>\n",
       "      <td>-0.1292</td>\n",
       "      <td>-0.0170</td>\n",
       "      <td>13204300900</td>\n",
       "      <td>1.060</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             收盘价   涨跌幅(%)   换手率(%)         成交金额     市盈率     市净率          总股本  \\\n",
       "日期                                                                             \n",
       "2023-08-24  3.24   0.0000       --          NaN -0.1838 -0.0400  13204300900   \n",
       "2023-08-25  3.24   0.0000       --          NaN -0.1838 -0.0400  13204300900   \n",
       "2023-08-28  0.69 -78.7879  13.9933  582346873.0 -0.0587 -0.0077  13204300900   \n",
       "2023-08-29  0.59 -14.2857   3.9602  165698771.0 -0.0503 -0.0066  13204300900   \n",
       "2023-08-30  0.53 -10.0000   1.9645   71924595.0 -0.0453 -0.0059  13204300900   \n",
       "2023-08-31  0.54   1.8519   1.6063   60117438.0 -0.0461 -0.0060  13204300900   \n",
       "2023-09-04  0.58   7.2727   1.3593   52910752.0 -0.0495 -0.0065  13204300900   \n",
       "2023-09-05  0.69  18.6441   1.9047   81113253.0 -0.0587 -0.0077  13204300900   \n",
       "2023-09-06  1.26  82.8571   9.6291  633395325.0 -0.1074 -0.0141  13204300900   \n",
       "2023-09-07  1.26   0.0000   7.6003  691153067.0 -0.1074 -0.0141  13204300900   \n",
       "2023-09-11  1.51  20.3125    4.019  368973167.0 -0.1292 -0.0170  13204300900   \n",
       "\n",
       "            close_ma_5  \n",
       "日期                      \n",
       "2023-08-24       3.240  \n",
       "2023-08-25       3.240  \n",
       "2023-08-28       2.730  \n",
       "2023-08-29       2.200  \n",
       "2023-08-30       1.658  \n",
       "2023-08-31       1.118  \n",
       "2023-09-04       0.586  \n",
       "2023-09-05       0.586  \n",
       "2023-09-06       0.720  \n",
       "2023-09-07       0.866  \n",
       "2023-09-11       1.060  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_recent[df_recent.index >= '2023-08-24'][[\"收盘价\", '涨跌幅(%)','换手率(%)','成交金额','市盈率','市净率','总股本',\"close_ma_5\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>收盘价</th>\n",
       "      <th>涨跌幅(%)</th>\n",
       "      <th>换手率(%)</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>市盈率</th>\n",
       "      <th>市净率</th>\n",
       "      <th>总股本</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>日期</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-08-29</th>\n",
       "      <td>1.86</td>\n",
       "      <td>12.3457</td>\n",
       "      <td>2.9593</td>\n",
       "      <td>7.145545e+08</td>\n",
       "      <td>-3.7122</td>\n",
       "      <td>0.1131</td>\n",
       "      <td>27637858596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-30</th>\n",
       "      <td>1.80</td>\n",
       "      <td>-3.2967</td>\n",
       "      <td>2.2952</td>\n",
       "      <td>5.652364e+08</td>\n",
       "      <td>-0.4033</td>\n",
       "      <td>0.1436</td>\n",
       "      <td>27637858596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>1.82</td>\n",
       "      <td>1.1364</td>\n",
       "      <td>2.0757</td>\n",
       "      <td>5.179268e+08</td>\n",
       "      <td>-0.4079</td>\n",
       "      <td>0.1452</td>\n",
       "      <td>27637858596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-04</th>\n",
       "      <td>2.08</td>\n",
       "      <td>14.6067</td>\n",
       "      <td>6.174</td>\n",
       "      <td>1.741268e+09</td>\n",
       "      <td>-0.4675</td>\n",
       "      <td>0.1663</td>\n",
       "      <td>27988507946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-05</th>\n",
       "      <td>2.06</td>\n",
       "      <td>-0.9804</td>\n",
       "      <td>2.9799</td>\n",
       "      <td>8.378436e+08</td>\n",
       "      <td>-0.4688</td>\n",
       "      <td>0.1670</td>\n",
       "      <td>27988507946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-06</th>\n",
       "      <td>2.49</td>\n",
       "      <td>20.7921</td>\n",
       "      <td>8.5585</td>\n",
       "      <td>2.809730e+09</td>\n",
       "      <td>-0.5663</td>\n",
       "      <td>0.2021</td>\n",
       "      <td>27988507946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-07</th>\n",
       "      <td>2.19</td>\n",
       "      <td>-12.2951</td>\n",
       "      <td>6.9157</td>\n",
       "      <td>2.292240e+09</td>\n",
       "      <td>-0.4966</td>\n",
       "      <td>0.1773</td>\n",
       "      <td>27988507946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-11</th>\n",
       "      <td>2.11</td>\n",
       "      <td>-3.7383</td>\n",
       "      <td>4.7779</td>\n",
       "      <td>1.386162e+09</td>\n",
       "      <td>-0.4781</td>\n",
       "      <td>0.1711</td>\n",
       "      <td>27988507946</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             收盘价   涨跌幅(%)  换手率(%)          成交金额     市盈率     市净率          总股本\n",
       "日期                                                                          \n",
       "2023-08-29  1.86  12.3457  2.9593  7.145545e+08 -3.7122  0.1131  27637858596\n",
       "2023-08-30  1.80  -3.2967  2.2952  5.652364e+08 -0.4033  0.1436  27637858596\n",
       "2023-08-31  1.82   1.1364  2.0757  5.179268e+08 -0.4079  0.1452  27637858596\n",
       "2023-09-04  2.08  14.6067   6.174  1.741268e+09 -0.4675  0.1663  27988507946\n",
       "2023-09-05  2.06  -0.9804  2.9799  8.378436e+08 -0.4688  0.1670  27988507946\n",
       "2023-09-06  2.49  20.7921  8.5585  2.809730e+09 -0.5663  0.2021  27988507946\n",
       "2023-09-07  2.19 -12.2951  6.9157  2.292240e+09 -0.4966  0.1773  27988507946\n",
       "2023-09-11  2.11  -3.7383  4.7779  1.386162e+09 -0.4781  0.1711  27988507946"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2007 = pd.read_excel('2007.HK.xlsx')\n",
    "df_2007.columns = ['代码', '简称', '日期', '前收盘价', '开盘价', '最高价',\n",
    "               '最低价', '收盘价', '成交量', '成交金额', '涨跌(元)',\t\n",
    "               '涨跌幅(%)', '均价(元)','换手率(%)',  'A股流通市值', 'B股流通市值', \n",
    "               '总市值', 'A股流通股本', 'B股流通股本', '总股本', '市盈率', '市净率', '市销率', '市现率']\n",
    "\n",
    "df_2007['代码'] = df_2007['代码'].astype(str)\n",
    "df_2007['简称'] = df_2007['简称'].astype(str)\n",
    "df_2007['日期'] = pd.to_datetime(df_2007['日期'])\n",
    "df_2007['成交量'] = df_2007['成交量'].replace('--', None)\n",
    "df_2007['成交金额'] = df_2007['成交金额'].replace('--', None)\n",
    "df_2007['前收盘价'] = df_2007['前收盘价'].replace('--', None)\n",
    "df_2007['成交量'] = df_2007['成交量'].astype(float)\n",
    "df_2007['成交金额'] = df_2007['成交金额'].astype(float)\n",
    "df_2007['前收盘价'] = df_2007['前收盘价'].astype(float)\n",
    "\n",
    "df_2007.set_index(\"日期\", inplace=True)\n",
    "df_2007_select = df_2007[df_2007.index >= '2023-08-29'][[\"收盘价\", '涨跌幅(%)','换手率(%)','成交金额','市盈率','市净率','总股本']]\n",
    "df_2007_select"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "df_recent = df_recent[df_recent.index >= '2023-08-29'][[\"收盘价\", '涨跌幅(%)','换手率(%)','成交金额','市盈率','市净率','总股本',\"close_ma_5\"]]\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(df_2007_select.index, df_2007_select['收盘价'], label='碧桂园')\n",
    "plt.plot(df_recent.index, df_recent['收盘价'], label='恒大')\n",
    "plt.xlabel('日期')\n",
    "plt.ylabel('收盘价')\n",
    "plt.legend()\n",
    "plt.title('Comparison of Close Prices')\n",
    "\n",
    "# Add a vertical line at August 31st\n",
    "plt.axvline(x=pd.to_datetime('2023-09-04'), color='red', linestyle='--', label='August 31st')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"discovery.png\" alt=\"Sample Image\" width=\"50%\">\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "最终，Jae给老板留下了深刻印象，留在了公司，而Rivers离开了公司。\n",
    "这个故事告诉我们，学习Python是非常重要的。\n",
    "\n",
    "2. Python Pandas 的基础操作 <a name=\"python-refresher\"></a>\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "#### 1. 版本控制\n",
    "\n",
    "使用 `requirements.txt` 文件来维护依赖和版本。这确保了在不同环境下工作或与他人共享代码时的一致性。\n",
    "\n",
    "```plaintext\n",
    "pandas==1.5.3\n",
    "matplotlib==3.7.1\n",
    "numpy==1.24.3\n",
    "scikit-learn==1.3.0\n",
    "statsmodels==0.14.0\n",
    "requests==2.31.0\n",
    "seaborn==0.11.2\n",
    "```\n",
    "```python\n",
    "! pip install -r requirements.txt\n",
    "# 或者\n",
    "! pip install pandas matplotlib numpy\n",
    "```\n",
    "例如，用 `pd.concat` 替换 `pd.append`：\n",
    "\n",
    "###### 之前\n",
    "df = df.append(new_data)\n",
    "###### 之后\n",
    "df = pd.concat([df, new_data], axis=0)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "#### 2. 本地路径\n",
    "\n",
    "```plaintext\n",
    "不良实践（绝对路径）\n",
    "使用绝对路径会给我们亲爱的助教带来非常非常难受的生活\n",
    "```\n",
    "\n",
    "```python\n",
    "file_path = \"C:/Users/ILOVECODING/MYCAT/username/Documents/data.csv\"\n",
    "```\n",
    "\n",
    "更好的实践（相对路径）\n",
    "\n",
    "```python\n",
    "file_path = \"./data/data.csv\"\n",
    "df = pd.read_csv(file_path)\n",
    "df = pd.read_csv('data.csv')\n",
    "```\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "#### 3. 变量命名\n",
    "\n",
    "```plaintext\n",
    "不良实践\n",
    "使用绝对路径会给我们亲爱的助教带来非常非常难受的生活\n",
    "```\n",
    "\n",
    "```python\n",
    "a = pd.read_csv('data1.csv')\n",
    "b = pd.read_csv('data2.csv')\n",
    "df = pd.read_csv('data3.csv')\n",
    "i_do_not_know_what_should_i_name_this_variable = pd.concat([df, a], axis=0) # axis = 0 表示垂直追加数据，这是我们在大多数情况下想要的\n",
    "```\n",
    "\n",
    "或许相对较好的实践（我的方法）\n",
    "\n",
    "```python\n",
    "df_stock_prices = pd.read_csv('data1.csv')\n",
    "df_daily_returns = pd.read_csv('data2.csv')\n",
    "df_combine_price_and_return =  pd.concat([df_stock_prices, df_daily_returns], axis=0)\n",
    "```\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "#### 4. 为你的代码添加注释，为你的代码添加注释，为你的代码添加注释\n",
    "\n",
    "```python\n",
    "def win_rate_test(sig_df, rets_df, win, negative=False):\n",
    "    \"\"\"\n",
    "    函数: 指标胜率测试 (Function: Indicator Win Rate Test)\n",
    "    :param sig_df: 单因子序列 (Parameter: Single-factor Time Series)\n",
    "    :param rets_df: 单标的收益率序列 (Parameter: Returns Time Series for a Single Asset)\n",
    "    :param negative: 多空头信号，默认为空头 (Parameter: Long/Short Signal, Default is Short)\n",
    "    \n",
    "    返回: DProfVol_window_size的DataFrame (Return: DataFrame of Win Rates for Different Window Sizes)\n",
    "    \"\"\"\n",
    "    \n",
    "    # 反转收益率数据框\n",
    "    rev_rets_df = rets_df[::-1]\n",
    "    # 计算总信号数\n",
    "    total = sig_df.sum().values[0]\n",
    "    # 初始化一个空列表以记录胜率\n",
    "    record = []\n",
    "    # 计算滚动收益并反转它们\n",
    "    rolling_rets = rev_rets_df.rolling(win).apply(lambda x: x.add(1).prod() - 1) \n",
    "    rolling_rets = rolling_rets[::-1]\n",
    "    # 初始化一个变量来计算赢得的次数\n",
    "    win_num = 0\n",
    "    # 遍历信号数据框中的每个日期\n",
    "    for date in sig_df.index:\n",
    "        if (sig_df.loc[date].values[0] == 1):\n",
    "            # 检查信号是多头（正）还是空头（负）\n",
    "            if (negative == False) and (rolling_rets.loc[date] <= 0):\n",
    "                win_num += 1\n",
    "            elif (negative == True) and (rolling_rets.loc[date] >= 0):\n",
    "                win_num += 1\n",
    "    # 计算当前窗口大小的胜率\n",
    "    win_ratio = win_num / total\n",
    "    # 将胜率添加到记录列表中\n",
    "    record.append(win_ratio)\n",
    "    # 将触发总次数添加到记录列表中\n",
    "    record.append(total)\n",
    "    \n",
    "    return record\n",
    "```\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### 5. 把Pandas想象成一个带有个性化功能的Excel；先熟悉它，然后深入思考。\n",
    "```python\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# 创建一个示例股票价格数据框\n",
    "data = {'Date': pd.date_range(start='2022-01-01', periods=10, freq='D'),\n",
    "        'AAPL': [150, 151, 150, 153, 150, 155, 150, 157, 153, 150],\n",
    "        'GOOG': [2800, 2810, 2820, 2830, 2840, 2850, 2860, 2870, 2880, 2890]}\n",
    "\n",
    "stock_prices_df = pd.DataFrame(data)\n",
    "\n",
    "# 创建一个示例交易量数据框\n",
    "data = {'Date': pd.date_range(start='2022-01-01', periods=10, freq='D'),\n",
    "        'AAPL_volume': [1000, 1200, 1000, 1000, 1900, 1600, 1800, 1600, 1200, 1900],\n",
    "        'GOOG_volume': [1000, 1100, 1200, 1050, 1150, 1250, 1300, 1400, 1500, 1450]}\n",
    "\n",
    "volume_df = pd.DataFrame(data)\n",
    "\n",
    "# 按'Date'列对数据框进行升序排序\n",
    "stock_prices_df.sort_values(by='Date', inplace=True)\n",
    "\n",
    "# 将stock_prices_df和volume_df根据'Date'列合并\n",
    "merged_df = pd.merge(stock_prices_df, volume_df, on='Date')\n",
    "print(\"\\n合并后的数据框：\")\n",
    "print(merged_df)\n",
    "groupby是一个很好用的函数。\n",
    "\n",
    "```python\n",
    "df_grouped = df.groupby('stock_code') # df_grouped 是一个groupby对象\n",
    "for stock_code, df_stock in df_grouped:\n",
    "    print(stock_code)\n",
    "    print(df_stock)\n",
    "    break\n",
    "```\n",
    "\n",
    "# 按'AAPL'分组并计算'GOOG'的平均值\n",
    "grouped_df = merged_df.groupby('AAPL')['GOOG'].mean()\n",
    "print(\"\\n分组后的数字是所有Google价格的平均值：\")\n",
    "print(grouped_df)\n",
    "\n",
    "# 使用apply()应用自定义聚合函数\n",
    "def custom_agg(x):\n",
    "    return x.sum() / len(x)\n",
    "\n",
    "# def custom_agg(x):\n",
    "#     return np.square(x.sum()) / len(x)\n",
    "\n",
    "agg_result = merged_df.groupby('AAPL')['GOOG'].apply(custom_agg)\n",
    "print(\"\\n使用apply()的自定义聚合：\")\n",
    "print(agg_result)\n",
    "\n",
    "# 将'AAPL'列向后移动1个周期\n",
    "merged_df['AAPL_shifted'] = merged_df['AAPL'].shift(periods=1)\n",
    "print(\"\\n移动后的'AAPL'列：\")\n",
    "print(merged_df)\n",
    "# 计算'AAPL'的滚动平均值，窗口大小为3\n",
    "merged_df['AAPL_rolling_mean'] = merged_df['AAPL'].rolling(window=3).mean()\n",
    "# 删除移动的'AAPL'列\n",
    "merged_df.drop(columns=['AAPL_shifted'], inplace=True)\n",
    "print(merged_df)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "小贴士：Google、Stack Overflow、复制粘贴，不要用chatgpt，尤其是开始的阶段）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### 3. Python与量化金融 <a name=\"Advanced-Topics\"></a>\n",
    "\n",
    "- 我们在这里做的除了Excel功能还有什么？\n",
    "- 这里的理念是什么？\n",
    "- 因子？\n",
    "- 市场时机？\n",
    "\n",
    "让我给你讲一个故事。\n",
    "\n",
    "<font color=\"red\"> 很久很久以前，在一个遥远的银河系里... </font> \n",
    "---"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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