时间序列相关性.ipynb

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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-04T13:56:46.829591Z",
     "start_time": "2019-09-04T13:56:43.604952Z"
    }
   },
   "outputs": [],
   "source": [
    "#先引入后面可能用到的包（package）\n",
    "import pandas as pd  \n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "import tushare as ts \n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline   \n",
    "\n",
    "#正常显示画图时出现的中文和负号\n",
    "from pylab import mpl\n",
    "mpl.rcParams['font.sans-serif']=['SimHei']\n",
    "mpl.rcParams['axes.unicode_minus']=False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-04T13:56:47.460973Z",
     "start_time": "2019-09-04T13:56:47.397969Z"
    }
   },
   "outputs": [],
   "source": [
    "#使用之前先输入token，可以从个人主页上复制出来，每次调用数据需要先运行该命令\n",
    "token='e0eeb08befd1f07516df2cbf9cbd58663f77fd72f92a04f290291c9d'\n",
    "ts.set_token(token)\n",
    "pro=ts.pro_api()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-04T14:04:34.958737Z",
     "start_time": "2019-09-04T14:04:34.447011Z"
    }
   },
   "outputs": [],
   "source": [
    "from dateutil.parser import parse\n",
    "from datetime import datetime,timedelta\n",
    "#获取交易日历\n",
    "cals=pro.trade_cal(exchange='')\n",
    "cals=cals[cals.is_open==1].cal_date.values\n",
    "def trans_date(date):\n",
    "    while date not in cals:\n",
    "        t=parse(date)\n",
    "        date=(t-timedelta(1)).strftime('%Y%m%d')\n",
    "    return date\n",
    "def get_code():\n",
    "    df = pro.stock_basic(list_status='L')\n",
    "    codes=df.ts_code.values\n",
    "    names=df.name.values\n",
    "    stock=dict(zip(codes,names))\n",
    "    return stock\n",
    "def get_daily_data(n=300):\n",
    "    t=datetime.now()\n",
    "    if t.hour>18:\n",
    "        t0=t.strftime('%Y%m%d')\n",
    "    else:\n",
    "        t0=(t-timedelta(1)).strftime('%Y%m%d')\n",
    "    t1=trans_date(t0)\n",
    "    n0=np.argwhere(cals==t1)[0][0]+1\n",
    "    dates=cals[:n0][-n:]\n",
    "    df=pro.daily(trade_date=dates[0])\n",
    "    for d in dates[1:]:\n",
    "        df1=pro.daily(trade_date=d)\n",
    "        df=pd.concat([df,df1])\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-04T14:09:04.817722Z",
     "start_time": "2019-09-04T14:05:02.335630Z"
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>ts_code</th>\n",
       "      <th>平安银行</th>\n",
       "      <th>万科A</th>\n",
       "      <th>国农科技</th>\n",
       "      <th>世纪星源</th>\n",
       "      <th>深振业A</th>\n",
       "      <th>全新好</th>\n",
       "      <th>神州高铁</th>\n",
       "      <th>中国宝安</th>\n",
       "      <th>*ST美丽</th>\n",
       "      <th>深物业A</th>\n",
       "      <th>...</th>\n",
       "      <th>南微医学</th>\n",
       "      <th>天宜上佳</th>\n",
       "      <th>航天宏图</th>\n",
       "      <th>虹软科技</th>\n",
       "      <th>晶晨股份</th>\n",
       "      <th>西部超导</th>\n",
       "      <th>柏楚电子</th>\n",
       "      <th>微芯生物</th>\n",
       "      <th>铂力特</th>\n",
       "      <th>嘉元科技</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20180615</th>\n",
       "      <td>10.17</td>\n",
       "      <td>27.99</td>\n",
       "      <td>19.85</td>\n",
       "      <td>3.11</td>\n",
       "      <td>6.89</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.40</td>\n",
       "      <td>3.95</td>\n",
       "      <td>13.44</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180619</th>\n",
       "      <td>9.87</td>\n",
       "      <td>27.10</td>\n",
       "      <td>19.22</td>\n",
       "      <td>2.80</td>\n",
       "      <td>6.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.86</td>\n",
       "      <td>3.79</td>\n",
       "      <td>12.10</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180620</th>\n",
       "      <td>9.91</td>\n",
       "      <td>26.96</td>\n",
       "      <td>19.15</td>\n",
       "      <td>2.90</td>\n",
       "      <td>6.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.85</td>\n",
       "      <td>4.02</td>\n",
       "      <td>12.09</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180621</th>\n",
       "      <td>9.86</td>\n",
       "      <td>27.73</td>\n",
       "      <td>18.83</td>\n",
       "      <td>2.91</td>\n",
       "      <td>6.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.71</td>\n",
       "      <td>4.05</td>\n",
       "      <td>11.26</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180622</th>\n",
       "      <td>9.85</td>\n",
       "      <td>28.10</td>\n",
       "      <td>19.03</td>\n",
       "      <td>2.93</td>\n",
       "      <td>5.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.84</td>\n",
       "      <td>4.01</td>\n",
       "      <td>11.41</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 3688 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "ts_code      平安银行    万科A   国农科技  世纪星源  深振业A  全新好  神州高铁  中国宝安  *ST美丽   深物业A  \\\n",
       "trade_date                                                                   \n",
       "20180615    10.17  27.99  19.85  3.11  6.89  NaN   NaN  5.40   3.95  13.44   \n",
       "20180619     9.87  27.10  19.22  2.80  6.20  NaN   NaN  4.86   3.79  12.10   \n",
       "20180620     9.91  26.96  19.15  2.90  6.19  NaN   NaN  4.85   4.02  12.09   \n",
       "20180621     9.86  27.73  18.83  2.91  6.12  NaN   NaN  4.71   4.05  11.26   \n",
       "20180622     9.85  28.10  19.03  2.93  5.99  NaN   NaN  4.84   4.01  11.41   \n",
       "\n",
       "ts_code     ...   南微医学  天宜上佳  航天宏图  虹软科技  晶晨股份  西部超导  柏楚电子  微芯生物  铂力特  嘉元科技  \n",
       "trade_date  ...                                                              \n",
       "20180615    ...    NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  NaN   NaN  \n",
       "20180619    ...    NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  NaN   NaN  \n",
       "20180620    ...    NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  NaN   NaN  \n",
       "20180621    ...    NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  NaN   NaN  \n",
       "20180622    ...    NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN  NaN   NaN  \n",
       "\n",
       "[5 rows x 3688 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
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    }
   ],
   "source": [
    "df=get_daily_data(n=300)\n",
    "df_new=df.set_index(['trade_date','ts_code'])['close']\n",
    "df_new.head(10)\n",
    "#数据重排，列名为代码\n",
    "data=df_new.unstack()\n",
    "data.rename(columns=get_code(),inplace=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>ts_code</th>\n",
       "      <th>金浦钛业</th>\n",
       "      <th>慈星股份</th>\n",
       "      <th>三川智慧</th>\n",
       "      <th>邦宝益智</th>\n",
       "      <th>凯文教育</th>\n",
       "      <th>搜于特</th>\n",
       "      <th>奋达科技</th>\n",
       "      <th>华灿光电</th>\n",
       "      <th>新大陆</th>\n",
       "      <th>福成股份</th>\n",
       "      <th>...</th>\n",
       "      <th>美吉姆</th>\n",
       "      <th>华谊嘉信</th>\n",
       "      <th>广东鸿图</th>\n",
       "      <th>北玻股份</th>\n",
       "      <th>国金证券</th>\n",
       "      <th>杭齿前进</th>\n",
       "      <th>三丰智能</th>\n",
       "      <th>合肥城建</th>\n",
       "      <th>海汽集团</th>\n",
       "      <th>漫步者</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>20180615</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.37</td>\n",
       "      <td>3.79</td>\n",
       "      <td>16.53</td>\n",
       "      <td>13.57</td>\n",
       "      <td>3.59</td>\n",
       "      <td>9.85</td>\n",
       "      <td>14.67</td>\n",
       "      <td>16.24</td>\n",
       "      <td>10.70</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.57</td>\n",
       "      <td>9.01</td>\n",
       "      <td>3.26</td>\n",
       "      <td>7.70</td>\n",
       "      <td>6.67</td>\n",
       "      <td>12.26</td>\n",
       "      <td>11.92</td>\n",
       "      <td>9.63</td>\n",
       "      <td>7.13</td>\n",
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       "    <tr>\n",
       "      <th>20180619</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.79</td>\n",
       "      <td>3.44</td>\n",
       "      <td>14.88</td>\n",
       "      <td>13.10</td>\n",
       "      <td>3.45</td>\n",
       "      <td>8.87</td>\n",
       "      <td>13.60</td>\n",
       "      <td>14.73</td>\n",
       "      <td>10.60</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.21</td>\n",
       "      <td>8.48</td>\n",
       "      <td>2.97</td>\n",
       "      <td>6.99</td>\n",
       "      <td>6.19</td>\n",
       "      <td>11.42</td>\n",
       "      <td>10.73</td>\n",
       "      <td>8.67</td>\n",
       "      <td>6.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180620</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.93</td>\n",
       "      <td>3.50</td>\n",
       "      <td>14.71</td>\n",
       "      <td>13.15</td>\n",
       "      <td>3.49</td>\n",
       "      <td>8.85</td>\n",
       "      <td>13.52</td>\n",
       "      <td>15.17</td>\n",
       "      <td>10.42</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.53</td>\n",
       "      <td>8.55</td>\n",
       "      <td>3.10</td>\n",
       "      <td>7.03</td>\n",
       "      <td>6.19</td>\n",
       "      <td>11.65</td>\n",
       "      <td>10.73</td>\n",
       "      <td>9.40</td>\n",
       "      <td>6.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180621</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.77</td>\n",
       "      <td>3.42</td>\n",
       "      <td>15.30</td>\n",
       "      <td>13.00</td>\n",
       "      <td>3.45</td>\n",
       "      <td>8.40</td>\n",
       "      <td>12.85</td>\n",
       "      <td>14.91</td>\n",
       "      <td>10.22</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.52</td>\n",
       "      <td>8.60</td>\n",
       "      <td>3.06</td>\n",
       "      <td>6.69</td>\n",
       "      <td>6.07</td>\n",
       "      <td>11.31</td>\n",
       "      <td>10.10</td>\n",
       "      <td>9.02</td>\n",
       "      <td>6.28</td>\n",
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       "    <tr>\n",
       "      <th>20180622</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.85</td>\n",
       "      <td>3.47</td>\n",
       "      <td>15.37</td>\n",
       "      <td>13.35</td>\n",
       "      <td>3.47</td>\n",
       "      <td>8.63</td>\n",
       "      <td>12.81</td>\n",
       "      <td>15.13</td>\n",
       "      <td>10.19</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.48</td>\n",
       "      <td>8.62</td>\n",
       "      <td>3.10</td>\n",
       "      <td>6.82</td>\n",
       "      <td>6.18</td>\n",
       "      <td>11.64</td>\n",
       "      <td>10.42</td>\n",
       "      <td>9.11</td>\n",
       "      <td>6.43</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>5 rows × 2875 columns</p>\n",
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      ],
      "text/plain": [
       "ts_code     金浦钛业  慈星股份  三川智慧   邦宝益智   凯文教育   搜于特  奋达科技   华灿光电    新大陆   福成股份  \\\n",
       "trade_date                                                                    \n",
       "20180615     NaN  6.37  3.79  16.53  13.57  3.59  9.85  14.67  16.24  10.70   \n",
       "20180619     NaN  5.79  3.44  14.88  13.10  3.45  8.87  13.60  14.73  10.60   \n",
       "20180620     NaN  5.93  3.50  14.71  13.15  3.49  8.85  13.52  15.17  10.42   \n",
       "20180621     NaN  5.77  3.42  15.30  13.00  3.45  8.40  12.85  14.91  10.22   \n",
       "20180622     NaN  5.85  3.47  15.37  13.35  3.47  8.63  12.81  15.13  10.19   \n",
       "\n",
       "ts_code     ...   美吉姆  华谊嘉信  广东鸿图  北玻股份  国金证券  杭齿前进   三丰智能   合肥城建  海汽集团   漫步者  \n",
       "trade_date  ...                                                                \n",
       "20180615    ...   NaN  3.57  9.01  3.26  7.70  6.67  12.26  11.92  9.63  7.13  \n",
       "20180619    ...   NaN  3.21  8.48  2.97  6.99  6.19  11.42  10.73  8.67  6.47  \n",
       "20180620    ...   NaN  3.53  8.55  3.10  7.03  6.19  11.65  10.73  9.40  6.59  \n",
       "20180621    ...   NaN  3.52  8.60  3.06  6.69  6.07  11.31  10.10  9.02  6.28  \n",
       "20180622    ...   NaN  3.48  8.62  3.10  6.82  6.18  11.64  10.42  9.11  6.43  \n",
       "\n",
       "[5 rows x 2875 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#剔除次新股和st股票\n",
    "def get_new_code():\n",
    "    df = pro.stock_basic(exchange='', list_status='L')\n",
    "    #剔除2017年以后上市的新股次新股\n",
    "    df=df[df['list_date'].apply(int).values<20170101]\n",
    "    #剔除st股\n",
    "    df=df[-df['name'].apply(lambda x:x.startswith('*ST'))]\n",
    "    df=df[-df['name'].apply(lambda x:x.startswith('ST'))]\n",
    "    #将剩下的股票代码和名称映射为字典\n",
    "    codes=df.ts_code.values\n",
    "    names=df.name.values\n",
    "    stock=dict(zip(names,codes))\n",
    "    return stock\n",
    "new_codes=list(set(data.columns).intersection(set(get_new_code().keys())))\n",
    "data_new=data[new_codes]\n",
    "data_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-04T14:14:04.250483Z",
     "start_time": "2019-09-04T14:14:04.181666Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th>ts_code</th>\n",
       "      <th>慈星股份</th>\n",
       "      <th>三川智慧</th>\n",
       "      <th>邦宝益智</th>\n",
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       "      <th>中交地产</th>\n",
       "      <th>...</th>\n",
       "      <th>黑猫股份</th>\n",
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       "      <th>华谊嘉信</th>\n",
       "      <th>广东鸿图</th>\n",
       "      <th>北玻股份</th>\n",
       "      <th>国金证券</th>\n",
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       "      <th>海汽集团</th>\n",
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       "      <th>trade_date</th>\n",
       "      <th></th>\n",
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       "      <th>20190829</th>\n",
       "      <td>5.28</td>\n",
       "      <td>4.59</td>\n",
       "      <td>9.29</td>\n",
       "      <td>7.50</td>\n",
       "      <td>2.37</td>\n",
       "      <td>4.35</td>\n",
       "      <td>17.45</td>\n",
       "      <td>9.37</td>\n",
       "      <td>6.98</td>\n",
       "      <td>6.47</td>\n",
       "      <td>...</td>\n",
       "      <td>4.96</td>\n",
       "      <td>4.88</td>\n",
       "      <td>3.17</td>\n",
       "      <td>6.90</td>\n",
       "      <td>2.74</td>\n",
       "      <td>8.87</td>\n",
       "      <td>11.97</td>\n",
       "      <td>9.52</td>\n",
       "      <td>6.27</td>\n",
       "      <td>6.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20190830</th>\n",
       "      <td>5.14</td>\n",
       "      <td>4.52</td>\n",
       "      <td>9.06</td>\n",
       "      <td>7.30</td>\n",
       "      <td>2.31</td>\n",
       "      <td>4.21</td>\n",
       "      <td>17.16</td>\n",
       "      <td>9.17</td>\n",
       "      <td>6.97</td>\n",
       "      <td>6.25</td>\n",
       "      <td>...</td>\n",
       "      <td>4.92</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.06</td>\n",
       "      <td>6.66</td>\n",
       "      <td>2.68</td>\n",
       "      <td>8.78</td>\n",
       "      <td>11.34</td>\n",
       "      <td>9.32</td>\n",
       "      <td>6.19</td>\n",
       "      <td>5.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20190902</th>\n",
       "      <td>5.17</td>\n",
       "      <td>4.61</td>\n",
       "      <td>9.21</td>\n",
       "      <td>7.70</td>\n",
       "      <td>2.38</td>\n",
       "      <td>4.33</td>\n",
       "      <td>17.62</td>\n",
       "      <td>9.15</td>\n",
       "      <td>7.05</td>\n",
       "      <td>6.33</td>\n",
       "      <td>...</td>\n",
       "      <td>4.99</td>\n",
       "      <td>5.07</td>\n",
       "      <td>3.10</td>\n",
       "      <td>6.73</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8.94</td>\n",
       "      <td>11.54</td>\n",
       "      <td>9.66</td>\n",
       "      <td>6.24</td>\n",
       "      <td>6.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20190903</th>\n",
       "      <td>5.13</td>\n",
       "      <td>4.65</td>\n",
       "      <td>9.28</td>\n",
       "      <td>7.68</td>\n",
       "      <td>2.37</td>\n",
       "      <td>4.40</td>\n",
       "      <td>17.63</td>\n",
       "      <td>9.10</td>\n",
       "      <td>7.06</td>\n",
       "      <td>6.32</td>\n",
       "      <td>...</td>\n",
       "      <td>5.00</td>\n",
       "      <td>5.11</td>\n",
       "      <td>3.08</td>\n",
       "      <td>6.74</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8.90</td>\n",
       "      <td>11.41</td>\n",
       "      <td>9.69</td>\n",
       "      <td>6.22</td>\n",
       "      <td>6.47</td>\n",
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       "    <tr>\n",
       "      <th>20190904</th>\n",
       "      <td>5.12</td>\n",
       "      <td>4.69</td>\n",
       "      <td>9.29</td>\n",
       "      <td>7.60</td>\n",
       "      <td>2.39</td>\n",
       "      <td>4.48</td>\n",
       "      <td>17.58</td>\n",
       "      <td>9.09</td>\n",
       "      <td>7.11</td>\n",
       "      <td>6.59</td>\n",
       "      <td>...</td>\n",
       "      <td>5.01</td>\n",
       "      <td>5.10</td>\n",
       "      <td>3.08</td>\n",
       "      <td>6.78</td>\n",
       "      <td>2.78</td>\n",
       "      <td>9.00</td>\n",
       "      <td>11.17</td>\n",
       "      <td>9.85</td>\n",
       "      <td>6.31</td>\n",
       "      <td>6.48</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 2379 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "ts_code     慈星股份  三川智慧  邦宝益智  凯文教育   搜于特  奋达科技    新大陆  福成股份  万安科技  中交地产  ...   \\\n",
       "trade_date                                                               ...    \n",
       "20190829    5.28  4.59  9.29  7.50  2.37  4.35  17.45  9.37  6.98  6.47  ...    \n",
       "20190830    5.14  4.52  9.06  7.30  2.31  4.21  17.16  9.17  6.97  6.25  ...    \n",
       "20190902    5.17  4.61  9.21  7.70  2.38  4.33  17.62  9.15  7.05  6.33  ...    \n",
       "20190903    5.13  4.65  9.28  7.68  2.37  4.40  17.63  9.10  7.06  6.32  ...    \n",
       "20190904    5.12  4.69  9.29  7.60  2.39  4.48  17.58  9.09  7.11  6.59  ...    \n",
       "\n",
       "ts_code     黑猫股份  中航三鑫  华谊嘉信  广东鸿图  北玻股份  国金证券   杭齿前进  三丰智能  海汽集团   漫步者  \n",
       "trade_date                                                               \n",
       "20190829    4.96  4.88  3.17  6.90  2.74  8.87  11.97  9.52  6.27  6.24  \n",
       "20190830    4.92  5.00  3.06  6.66  2.68  8.78  11.34  9.32  6.19  5.99  \n",
       "20190902    4.99  5.07  3.10  6.73  2.75  8.94  11.54  9.66  6.24  6.40  \n",
       "20190903    5.00  5.11  3.08  6.74  2.75  8.90  11.41  9.69  6.22  6.47  \n",
       "20190904    5.01  5.10  3.08  6.78  2.78  9.00  11.17  9.85  6.31  6.48  \n",
       "\n",
       "[5 rows x 2379 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
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    }
   ],
   "source": [
    "final_data=data_new.dropna(axis=1)\n",
    "final_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-04T14:31:31.720590Z",
     "start_time": "2019-09-04T14:31:27.054072Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <th>慈星股份</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.756323</td>\n",
       "      <td>0.433446</td>\n",
       "      <td>-0.034682</td>\n",
       "      <td>0.345737</td>\n",
       "      <td>0.278549</td>\n",
       "      <td>0.679325</td>\n",
       "      <td>0.294054</td>\n",
       "      <td>0.646856</td>\n",
       "      <td>0.150996</td>\n",
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       "      <td>-0.238495</td>\n",
       "      <td>0.486394</td>\n",
       "      <td>0.027420</td>\n",
       "      <td>0.018429</td>\n",
       "      <td>0.400401</td>\n",
       "      <td>0.650403</td>\n",
       "      <td>0.460415</td>\n",
       "      <td>0.013551</td>\n",
       "      <td>0.175915</td>\n",
       "      <td>0.412670</td>\n",
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       "      <th>三川智慧</th>\n",
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       "      <td>-0.401434</td>\n",
       "      <td>0.037537</td>\n",
       "      <td>0.036726</td>\n",
       "      <td>0.823073</td>\n",
       "      <td>0.190707</td>\n",
       "      <td>0.496171</td>\n",
       "      <td>-0.077782</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.596240</td>\n",
       "      <td>0.489602</td>\n",
       "      <td>-0.013086</td>\n",
       "      <td>-0.012861</td>\n",
       "      <td>0.262497</td>\n",
       "      <td>0.832359</td>\n",
       "      <td>0.726243</td>\n",
       "      <td>0.009637</td>\n",
       "      <td>-0.126639</td>\n",
       "      <td>0.242778</td>\n",
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       "      <th>邦宝益智</th>\n",
       "      <td>0.433446</td>\n",
       "      <td>0.203454</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.579755</td>\n",
       "      <td>0.722670</td>\n",
       "      <td>0.577385</td>\n",
       "      <td>0.192028</td>\n",
       "      <td>0.482302</td>\n",
       "      <td>0.696565</td>\n",
       "      <td>0.680662</td>\n",
       "      <td>...</td>\n",
       "      <td>0.379865</td>\n",
       "      <td>0.547940</td>\n",
       "      <td>0.291968</td>\n",
       "      <td>0.331730</td>\n",
       "      <td>0.593811</td>\n",
       "      <td>0.072941</td>\n",
       "      <td>-0.199625</td>\n",
       "      <td>0.400099</td>\n",
       "      <td>0.657290</td>\n",
       "      <td>0.527877</td>\n",
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       "      <th>凯文教育</th>\n",
       "      <td>-0.034682</td>\n",
       "      <td>-0.401434</td>\n",
       "      <td>0.579755</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.743102</td>\n",
       "      <td>0.637461</td>\n",
       "      <td>-0.280553</td>\n",
       "      <td>0.269075</td>\n",
       "      <td>0.383689</td>\n",
       "      <td>0.629695</td>\n",
       "      <td>...</td>\n",
       "      <td>0.849128</td>\n",
       "      <td>0.187422</td>\n",
       "      <td>0.226343</td>\n",
       "      <td>0.260683</td>\n",
       "      <td>0.446052</td>\n",
       "      <td>-0.468549</td>\n",
       "      <td>-0.589541</td>\n",
       "      <td>0.314814</td>\n",
       "      <td>0.782421</td>\n",
       "      <td>0.569440</td>\n",
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       "    <tr>\n",
       "      <th>搜于特</th>\n",
       "      <td>0.345737</td>\n",
       "      <td>0.037537</td>\n",
       "      <td>0.722670</td>\n",
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       "      <td>1.000000</td>\n",
       "      <td>0.637597</td>\n",
       "      <td>0.090617</td>\n",
       "      <td>0.624742</td>\n",
       "      <td>0.743998</td>\n",
       "      <td>0.750142</td>\n",
       "      <td>...</td>\n",
       "      <td>0.653571</td>\n",
       "      <td>0.532841</td>\n",
       "      <td>0.378806</td>\n",
       "      <td>0.423850</td>\n",
       "      <td>0.715777</td>\n",
       "      <td>0.000958</td>\n",
       "      <td>-0.270992</td>\n",
       "      <td>0.459930</td>\n",
       "      <td>0.766377</td>\n",
       "      <td>0.690990</td>\n",
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       "    <tr>\n",
       "      <th>奋达科技</th>\n",
       "      <td>0.278549</td>\n",
       "      <td>0.036726</td>\n",
       "      <td>0.577385</td>\n",
       "      <td>0.637461</td>\n",
       "      <td>0.637597</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.225153</td>\n",
       "      <td>0.243073</td>\n",
       "      <td>0.582748</td>\n",
       "      <td>0.685663</td>\n",
       "      <td>...</td>\n",
       "      <td>0.443930</td>\n",
       "      <td>0.509498</td>\n",
       "      <td>0.338467</td>\n",
       "      <td>0.453160</td>\n",
       "      <td>0.534477</td>\n",
       "      <td>0.053574</td>\n",
       "      <td>-0.080164</td>\n",
       "      <td>0.436698</td>\n",
       "      <td>0.812744</td>\n",
       "      <td>0.687040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新大陆</th>\n",
       "      <td>0.679325</td>\n",
       "      <td>0.823073</td>\n",
       "      <td>0.192028</td>\n",
       "      <td>-0.280553</td>\n",
       "      <td>0.090617</td>\n",
       "      <td>0.225153</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.264844</td>\n",
       "      <td>0.606550</td>\n",
       "      <td>0.039354</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.406281</td>\n",
       "      <td>0.669672</td>\n",
       "      <td>0.232992</td>\n",
       "      <td>0.326502</td>\n",
       "      <td>0.490043</td>\n",
       "      <td>0.915643</td>\n",
       "      <td>0.822527</td>\n",
       "      <td>0.307270</td>\n",
       "      <td>0.120478</td>\n",
       "      <td>0.468470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>福成股份</th>\n",
       "      <td>0.294054</td>\n",
       "      <td>0.190707</td>\n",
       "      <td>0.482302</td>\n",
       "      <td>0.269075</td>\n",
       "      <td>0.624742</td>\n",
       "      <td>0.243073</td>\n",
       "      <td>0.264844</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.689438</td>\n",
       "      <td>0.606063</td>\n",
       "      <td>...</td>\n",
       "      <td>0.405376</td>\n",
       "      <td>0.656787</td>\n",
       "      <td>0.530883</td>\n",
       "      <td>0.653076</td>\n",
       "      <td>0.765167</td>\n",
       "      <td>0.351374</td>\n",
       "      <td>0.012664</td>\n",
       "      <td>0.596653</td>\n",
       "      <td>0.466242</td>\n",
       "      <td>0.407059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>万安科技</th>\n",
       "      <td>0.646856</td>\n",
       "      <td>0.496171</td>\n",
       "      <td>0.696565</td>\n",
       "      <td>0.383689</td>\n",
       "      <td>0.743998</td>\n",
       "      <td>0.582748</td>\n",
       "      <td>0.606550</td>\n",
       "      <td>0.689438</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.581277</td>\n",
       "      <td>...</td>\n",
       "      <td>0.277477</td>\n",
       "      <td>0.818302</td>\n",
       "      <td>0.528957</td>\n",
       "      <td>0.581346</td>\n",
       "      <td>0.881065</td>\n",
       "      <td>0.527124</td>\n",
       "      <td>0.254875</td>\n",
       "      <td>0.517335</td>\n",
       "      <td>0.672594</td>\n",
       "      <td>0.794198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中交地产</th>\n",
       "      <td>0.150996</td>\n",
       "      <td>-0.077782</td>\n",
       "      <td>0.680662</td>\n",
       "      <td>0.629695</td>\n",
       "      <td>0.750142</td>\n",
       "      <td>0.685663</td>\n",
       "      <td>0.039354</td>\n",
       "      <td>0.606063</td>\n",
       "      <td>0.581277</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.564162</td>\n",
       "      <td>0.446497</td>\n",
       "      <td>0.317854</td>\n",
       "      <td>0.499472</td>\n",
       "      <td>0.578404</td>\n",
       "      <td>-0.041275</td>\n",
       "      <td>-0.332901</td>\n",
       "      <td>0.542976</td>\n",
       "      <td>0.723574</td>\n",
       "      <td>0.506656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>雷柏科技</th>\n",
       "      <td>0.260434</td>\n",
       "      <td>0.027788</td>\n",
       "      <td>0.689838</td>\n",
       "      <td>0.704966</td>\n",
       "      <td>0.809276</td>\n",
       "      <td>0.740550</td>\n",
       "      <td>0.250501</td>\n",
       "      <td>0.638777</td>\n",
       "      <td>0.807555</td>\n",
       "      <td>0.723213</td>\n",
       "      <td>...</td>\n",
       "      <td>0.689334</td>\n",
       "      <td>0.697288</td>\n",
       "      <td>0.607022</td>\n",
       "      <td>0.734101</td>\n",
       "      <td>0.883531</td>\n",
       "      <td>0.119576</td>\n",
       "      <td>-0.082832</td>\n",
       "      <td>0.693061</td>\n",
       "      <td>0.899288</td>\n",
       "      <td>0.817835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>圆通速递</th>\n",
       "      <td>0.601366</td>\n",
       "      <td>0.459576</td>\n",
       "      <td>0.544246</td>\n",
       "      <td>0.355147</td>\n",
       "      <td>0.638498</td>\n",
       "      <td>0.572750</td>\n",
       "      <td>0.554512</td>\n",
       "      <td>0.615826</td>\n",
       "      <td>0.771545</td>\n",
       "      <td>0.545989</td>\n",
       "      <td>...</td>\n",
       "      <td>0.212533</td>\n",
       "      <td>0.723429</td>\n",
       "      <td>0.284724</td>\n",
       "      <td>0.455001</td>\n",
       "      <td>0.714141</td>\n",
       "      <td>0.484067</td>\n",
       "      <td>0.279396</td>\n",
       "      <td>0.454189</td>\n",
       "      <td>0.534255</td>\n",
       "      <td>0.638658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>华润双鹤</th>\n",
       "      <td>-0.019849</td>\n",
       "      <td>-0.373908</td>\n",
       "      <td>0.572264</td>\n",
       "      <td>0.954226</td>\n",
       "      <td>0.689897</td>\n",
       "      <td>0.704271</td>\n",
       "      <td>-0.240119</td>\n",
       "      <td>0.177519</td>\n",
       "      <td>0.342642</td>\n",
       "      <td>0.656528</td>\n",
       "      <td>...</td>\n",
       "      <td>0.787830</td>\n",
       "      <td>0.149415</td>\n",
       "      <td>0.148993</td>\n",
       "      <td>0.217317</td>\n",
       "      <td>0.391303</td>\n",
       "      <td>-0.445977</td>\n",
       "      <td>-0.576048</td>\n",
       "      <td>0.283957</td>\n",
       "      <td>0.777748</td>\n",
       "      <td>0.564677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>亚太科技</th>\n",
       "      <td>0.374692</td>\n",
       "      <td>0.252504</td>\n",
       "      <td>0.631258</td>\n",
       "      <td>0.381674</td>\n",
       "      <td>0.691783</td>\n",
       "      <td>0.626098</td>\n",
       "      <td>0.462160</td>\n",
       "      <td>0.751244</td>\n",
       "      <td>0.842072</td>\n",
       "      <td>0.694792</td>\n",
       "      <td>...</td>\n",
       "      <td>0.432660</td>\n",
       "      <td>0.818475</td>\n",
       "      <td>0.678111</td>\n",
       "      <td>0.829496</td>\n",
       "      <td>0.890459</td>\n",
       "      <td>0.402070</td>\n",
       "      <td>0.180810</td>\n",
       "      <td>0.764941</td>\n",
       "      <td>0.747440</td>\n",
       "      <td>0.692990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>人民同泰</th>\n",
       "      <td>0.540342</td>\n",
       "      <td>0.428267</td>\n",
       "      <td>0.490142</td>\n",
       "      <td>0.317298</td>\n",
       "      <td>0.640748</td>\n",
       "      <td>0.510308</td>\n",
       "      <td>0.558442</td>\n",
       "      <td>0.619400</td>\n",
       "      <td>0.794948</td>\n",
       "      <td>0.511715</td>\n",
       "      <td>...</td>\n",
       "      <td>0.212889</td>\n",
       "      <td>0.744111</td>\n",
       "      <td>0.312276</td>\n",
       "      <td>0.402214</td>\n",
       "      <td>0.709062</td>\n",
       "      <td>0.502309</td>\n",
       "      <td>0.226203</td>\n",
       "      <td>0.414921</td>\n",
       "      <td>0.499636</td>\n",
       "      <td>0.805176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>海兴电力</th>\n",
       "      <td>0.361034</td>\n",
       "      <td>0.167884</td>\n",
       "      <td>0.602399</td>\n",
       "      <td>0.661396</td>\n",
       "      <td>0.638800</td>\n",
       "      <td>0.812182</td>\n",
       "      <td>0.379346</td>\n",
       "      <td>0.281263</td>\n",
       "      <td>0.699714</td>\n",
       "      <td>0.543328</td>\n",
       "      <td>...</td>\n",
       "      <td>0.454946</td>\n",
       "      <td>0.584944</td>\n",
       "      <td>0.333820</td>\n",
       "      <td>0.444175</td>\n",
       "      <td>0.676720</td>\n",
       "      <td>0.154960</td>\n",
       "      <td>0.073304</td>\n",
       "      <td>0.465613</td>\n",
       "      <td>0.778745</td>\n",
       "      <td>0.825208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>隧道股份</th>\n",
       "      <td>0.400729</td>\n",
       "      <td>0.551399</td>\n",
       "      <td>0.232368</td>\n",
       "      <td>-0.191934</td>\n",
       "      <td>0.180259</td>\n",
       "      <td>0.181453</td>\n",
       "      <td>0.727167</td>\n",
       "      <td>0.611321</td>\n",
       "      <td>0.625450</td>\n",
       "      <td>0.173654</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.101397</td>\n",
       "      <td>0.792019</td>\n",
       "      <td>0.560239</td>\n",
       "      <td>0.707180</td>\n",
       "      <td>0.696108</td>\n",
       "      <td>0.778177</td>\n",
       "      <td>0.687882</td>\n",
       "      <td>0.586370</td>\n",
       "      <td>0.259419</td>\n",
       "      <td>0.365507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>开尔新材</th>\n",
       "      <td>0.676485</td>\n",
       "      <td>0.800787</td>\n",
       "      <td>0.079480</td>\n",
       "      <td>-0.425236</td>\n",
       "      <td>-0.025262</td>\n",
       "      <td>-0.049543</td>\n",
       "      <td>0.688814</td>\n",
       "      <td>0.109089</td>\n",
       "      <td>0.325854</td>\n",
       "      <td>-0.072167</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.647625</td>\n",
       "      <td>0.337610</td>\n",
       "      <td>-0.230857</td>\n",
       "      <td>-0.227603</td>\n",
       "      <td>0.050139</td>\n",
       "      <td>0.733066</td>\n",
       "      <td>0.565379</td>\n",
       "      <td>-0.174959</td>\n",
       "      <td>-0.272221</td>\n",
       "      <td>0.177740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>硅宝科技</th>\n",
       "      <td>0.686322</td>\n",
       "      <td>0.734156</td>\n",
       "      <td>0.159758</td>\n",
       "      <td>-0.133436</td>\n",
       "      <td>0.152757</td>\n",
       "      <td>0.285378</td>\n",
       "      <td>0.863043</td>\n",
       "      <td>0.265131</td>\n",
       "      <td>0.589162</td>\n",
       "      <td>0.012755</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.303954</td>\n",
       "      <td>0.668467</td>\n",
       "      <td>0.174255</td>\n",
       "      <td>0.227573</td>\n",
       "      <td>0.472604</td>\n",
       "      <td>0.818610</td>\n",
       "      <td>0.731226</td>\n",
       "      <td>0.181066</td>\n",
       "      <td>0.149637</td>\n",
       "      <td>0.543501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>宁夏建材</th>\n",
       "      <td>0.521147</td>\n",
       "      <td>0.475162</td>\n",
       "      <td>0.209783</td>\n",
       "      <td>0.146585</td>\n",
       "      <td>0.487117</td>\n",
       "      <td>0.301311</td>\n",
       "      <td>0.606066</td>\n",
       "      <td>0.607317</td>\n",
       "      <td>0.718309</td>\n",
       "      <td>0.287078</td>\n",
       "      <td>...</td>\n",
       "      <td>0.157511</td>\n",
       "      <td>0.660409</td>\n",
       "      <td>0.304174</td>\n",
       "      <td>0.431814</td>\n",
       "      <td>0.725919</td>\n",
       "      <td>0.591842</td>\n",
       "      <td>0.441153</td>\n",
       "      <td>0.380319</td>\n",
       "      <td>0.358100</td>\n",
       "      <td>0.717479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>百润股份</th>\n",
       "      <td>0.728753</td>\n",
       "      <td>0.729346</td>\n",
       "      <td>0.109693</td>\n",
       "      <td>-0.146953</td>\n",
       "      <td>0.089763</td>\n",
       "      <td>0.184707</td>\n",
       "      <td>0.697042</td>\n",
       "      <td>0.007395</td>\n",
       "      <td>0.398250</td>\n",
       "      <td>-0.051659</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.458712</td>\n",
       "      <td>0.361836</td>\n",
       "      <td>-0.259349</td>\n",
       "      <td>-0.226108</td>\n",
       "      <td>0.138723</td>\n",
       "      <td>0.640891</td>\n",
       "      <td>0.555929</td>\n",
       "      <td>-0.175714</td>\n",
       "      <td>-0.074018</td>\n",
       "      <td>0.417954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>一心堂</th>\n",
       "      <td>0.562017</td>\n",
       "      <td>0.305876</td>\n",
       "      <td>0.767404</td>\n",
       "      <td>0.607120</td>\n",
       "      <td>0.700795</td>\n",
       "      <td>0.635371</td>\n",
       "      <td>0.323379</td>\n",
       "      <td>0.308728</td>\n",
       "      <td>0.675937</td>\n",
       "      <td>0.617241</td>\n",
       "      <td>...</td>\n",
       "      <td>0.288448</td>\n",
       "      <td>0.444985</td>\n",
       "      <td>0.063936</td>\n",
       "      <td>0.104847</td>\n",
       "      <td>0.499505</td>\n",
       "      <td>0.132169</td>\n",
       "      <td>-0.115902</td>\n",
       "      <td>0.254626</td>\n",
       "      <td>0.598855</td>\n",
       "      <td>0.690314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>东莞控股</th>\n",
       "      <td>0.740503</td>\n",
       "      <td>0.833269</td>\n",
       "      <td>0.335860</td>\n",
       "      <td>-0.206701</td>\n",
       "      <td>0.246950</td>\n",
       "      <td>0.267630</td>\n",
       "      <td>0.902994</td>\n",
       "      <td>0.476687</td>\n",
       "      <td>0.724820</td>\n",
       "      <td>0.175042</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.323565</td>\n",
       "      <td>0.788141</td>\n",
       "      <td>0.297609</td>\n",
       "      <td>0.406790</td>\n",
       "      <td>0.607037</td>\n",
       "      <td>0.926845</td>\n",
       "      <td>0.755474</td>\n",
       "      <td>0.313893</td>\n",
       "      <td>0.194084</td>\n",
       "      <td>0.473586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>东易日盛</th>\n",
       "      <td>-0.146982</td>\n",
       "      <td>-0.265372</td>\n",
       "      <td>0.579773</td>\n",
       "      <td>0.529537</td>\n",
       "      <td>0.634578</td>\n",
       "      <td>0.476704</td>\n",
       "      <td>-0.095413</td>\n",
       "      <td>0.602717</td>\n",
       "      <td>0.450072</td>\n",
       "      <td>0.732980</td>\n",
       "      <td>...</td>\n",
       "      <td>0.672984</td>\n",
       "      <td>0.443065</td>\n",
       "      <td>0.594715</td>\n",
       "      <td>0.730856</td>\n",
       "      <td>0.627841</td>\n",
       "      <td>-0.147202</td>\n",
       "      <td>-0.297952</td>\n",
       "      <td>0.755118</td>\n",
       "      <td>0.703802</td>\n",
       "      <td>0.358309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>九鼎新材</th>\n",
       "      <td>0.046246</td>\n",
       "      <td>0.258333</td>\n",
       "      <td>-0.429658</td>\n",
       "      <td>-0.223762</td>\n",
       "      <td>-0.308903</td>\n",
       "      <td>-0.070234</td>\n",
       "      <td>0.332768</td>\n",
       "      <td>-0.449471</td>\n",
       "      <td>-0.141472</td>\n",
       "      <td>-0.412829</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.398456</td>\n",
       "      <td>-0.066782</td>\n",
       "      <td>-0.335117</td>\n",
       "      <td>-0.350877</td>\n",
       "      <td>-0.236901</td>\n",
       "      <td>0.223784</td>\n",
       "      <td>0.404771</td>\n",
       "      <td>-0.263714</td>\n",
       "      <td>-0.302967</td>\n",
       "      <td>0.178768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中信重工</th>\n",
       "      <td>0.721708</td>\n",
       "      <td>0.842966</td>\n",
       "      <td>0.113637</td>\n",
       "      <td>-0.338907</td>\n",
       "      <td>0.145811</td>\n",
       "      <td>0.091539</td>\n",
       "      <td>0.871252</td>\n",
       "      <td>0.366408</td>\n",
       "      <td>0.605456</td>\n",
       "      <td>-0.000707</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.434574</td>\n",
       "      <td>0.625339</td>\n",
       "      <td>0.202988</td>\n",
       "      <td>0.240161</td>\n",
       "      <td>0.466044</td>\n",
       "      <td>0.920200</td>\n",
       "      <td>0.812362</td>\n",
       "      <td>0.207684</td>\n",
       "      <td>-0.001565</td>\n",
       "      <td>0.371633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>威海广泰</th>\n",
       "      <td>0.740558</td>\n",
       "      <td>0.857778</td>\n",
       "      <td>0.126471</td>\n",
       "      <td>-0.297546</td>\n",
       "      <td>0.106126</td>\n",
       "      <td>0.141421</td>\n",
       "      <td>0.905247</td>\n",
       "      <td>0.267018</td>\n",
       "      <td>0.579219</td>\n",
       "      <td>-0.024337</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.450276</td>\n",
       "      <td>0.633461</td>\n",
       "      <td>0.103232</td>\n",
       "      <td>0.163921</td>\n",
       "      <td>0.415017</td>\n",
       "      <td>0.892486</td>\n",
       "      <td>0.793691</td>\n",
       "      <td>0.148782</td>\n",
       "      <td>0.012597</td>\n",
       "      <td>0.457748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>经纬辉开</th>\n",
       "      <td>0.364127</td>\n",
       "      <td>0.377471</td>\n",
       "      <td>0.389133</td>\n",
       "      <td>0.162270</td>\n",
       "      <td>0.410883</td>\n",
       "      <td>0.479095</td>\n",
       "      <td>0.633511</td>\n",
       "      <td>0.574313</td>\n",
       "      <td>0.742560</td>\n",
       "      <td>0.381274</td>\n",
       "      <td>...</td>\n",
       "      <td>0.215632</td>\n",
       "      <td>0.796654</td>\n",
       "      <td>0.648202</td>\n",
       "      <td>0.802716</td>\n",
       "      <td>0.829780</td>\n",
       "      <td>0.597721</td>\n",
       "      <td>0.503116</td>\n",
       "      <td>0.707016</td>\n",
       "      <td>0.582966</td>\n",
       "      <td>0.631710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>闽发铝业</th>\n",
       "      <td>0.484453</td>\n",
       "      <td>0.331710</td>\n",
       "      <td>0.722680</td>\n",
       "      <td>0.499971</td>\n",
       "      <td>0.793687</td>\n",
       "      <td>0.609700</td>\n",
       "      <td>0.405357</td>\n",
       "      <td>0.640640</td>\n",
       "      <td>0.809767</td>\n",
       "      <td>0.692698</td>\n",
       "      <td>...</td>\n",
       "      <td>0.352625</td>\n",
       "      <td>0.681916</td>\n",
       "      <td>0.415673</td>\n",
       "      <td>0.507028</td>\n",
       "      <td>0.757899</td>\n",
       "      <td>0.340189</td>\n",
       "      <td>0.038194</td>\n",
       "      <td>0.467275</td>\n",
       "      <td>0.720197</td>\n",
       "      <td>0.643992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中洲控股</th>\n",
       "      <td>-0.298318</td>\n",
       "      <td>-0.590505</td>\n",
       "      <td>0.314969</td>\n",
       "      <td>0.766476</td>\n",
       "      <td>0.623393</td>\n",
       "      <td>0.302193</td>\n",
       "      <td>-0.512121</td>\n",
       "      <td>0.399560</td>\n",
       "      <td>0.206731</td>\n",
       "      <td>0.490061</td>\n",
       "      <td>...</td>\n",
       "      <td>0.908584</td>\n",
       "      <td>0.069513</td>\n",
       "      <td>0.347711</td>\n",
       "      <td>0.358526</td>\n",
       "      <td>0.387088</td>\n",
       "      <td>-0.560778</td>\n",
       "      <td>-0.644330</td>\n",
       "      <td>0.382425</td>\n",
       "      <td>0.583767</td>\n",
       "      <td>0.325184</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>羚锐制药</th>\n",
       "      <td>0.551324</td>\n",
       "      <td>0.337248</td>\n",
       "      <td>0.671932</td>\n",
       "      <td>0.563282</td>\n",
       "      <td>0.729313</td>\n",
       "      <td>0.548483</td>\n",
       "      <td>0.439336</td>\n",
       "      <td>0.588209</td>\n",
       "      <td>0.793593</td>\n",
       "      <td>0.589346</td>\n",
       "      <td>...</td>\n",
       "      <td>0.411199</td>\n",
       "      <td>0.641167</td>\n",
       "      <td>0.297052</td>\n",
       "      <td>0.376734</td>\n",
       "      <td>0.750707</td>\n",
       "      <td>0.310306</td>\n",
       "      <td>0.035535</td>\n",
       "      <td>0.471619</td>\n",
       "      <td>0.647938</td>\n",
       "      <td>0.810850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>王府井</th>\n",
       "      <td>0.392415</td>\n",
       "      <td>0.090883</td>\n",
       "      <td>0.751748</td>\n",
       "      <td>0.707116</td>\n",
       "      <td>0.770509</td>\n",
       "      <td>0.838450</td>\n",
       "      <td>0.305225</td>\n",
       "      <td>0.493473</td>\n",
       "      <td>0.732703</td>\n",
       "      <td>0.766776</td>\n",
       "      <td>...</td>\n",
       "      <td>0.536990</td>\n",
       "      <td>0.688530</td>\n",
       "      <td>0.394738</td>\n",
       "      <td>0.545454</td>\n",
       "      <td>0.718222</td>\n",
       "      <td>0.159496</td>\n",
       "      <td>-0.078007</td>\n",
       "      <td>0.570705</td>\n",
       "      <td>0.869367</td>\n",
       "      <td>0.765445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>河钢股份</th>\n",
       "      <td>0.110952</td>\n",
       "      <td>0.183570</td>\n",
       "      <td>0.174731</td>\n",
       "      <td>-0.055747</td>\n",
       "      <td>0.305985</td>\n",
       "      <td>0.193013</td>\n",
       "      <td>0.342883</td>\n",
       "      <td>0.708752</td>\n",
       "      <td>0.472774</td>\n",
       "      <td>0.376748</td>\n",
       "      <td>...</td>\n",
       "      <td>0.172970</td>\n",
       "      <td>0.575305</td>\n",
       "      <td>0.685401</td>\n",
       "      <td>0.798289</td>\n",
       "      <td>0.619874</td>\n",
       "      <td>0.467725</td>\n",
       "      <td>0.296652</td>\n",
       "      <td>0.651015</td>\n",
       "      <td>0.337914</td>\n",
       "      <td>0.159003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>华泰股份</th>\n",
       "      <td>0.352450</td>\n",
       "      <td>0.222074</td>\n",
       "      <td>0.457464</td>\n",
       "      <td>0.272335</td>\n",
       "      <td>0.629858</td>\n",
       "      <td>0.554568</td>\n",
       "      <td>0.478573</td>\n",
       "      <td>0.774706</td>\n",
       "      <td>0.763268</td>\n",
       "      <td>0.616314</td>\n",
       "      <td>...</td>\n",
       "      <td>0.395561</td>\n",
       "      <td>0.811210</td>\n",
       "      <td>0.695672</td>\n",
       "      <td>0.850290</td>\n",
       "      <td>0.856701</td>\n",
       "      <td>0.495426</td>\n",
       "      <td>0.243572</td>\n",
       "      <td>0.738341</td>\n",
       "      <td>0.683052</td>\n",
       "      <td>0.622529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>国美通讯</th>\n",
       "      <td>0.261459</td>\n",
       "      <td>-0.026466</td>\n",
       "      <td>0.688195</td>\n",
       "      <td>0.713981</td>\n",
       "      <td>0.761043</td>\n",
       "      <td>0.654798</td>\n",
       "      <td>0.173044</td>\n",
       "      <td>0.556360</td>\n",
       "      <td>0.724512</td>\n",
       "      <td>0.644069</td>\n",
       "      <td>...</td>\n",
       "      <td>0.714986</td>\n",
       "      <td>0.585645</td>\n",
       "      <td>0.521554</td>\n",
       "      <td>0.625734</td>\n",
       "      <td>0.813504</td>\n",
       "      <td>0.022535</td>\n",
       "      <td>-0.159511</td>\n",
       "      <td>0.620663</td>\n",
       "      <td>0.877529</td>\n",
       "      <td>0.776344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>吉峰科技</th>\n",
       "      <td>0.668981</td>\n",
       "      <td>0.629276</td>\n",
       "      <td>0.449655</td>\n",
       "      <td>-0.126170</td>\n",
       "      <td>0.265741</td>\n",
       "      <td>0.115581</td>\n",
       "      <td>0.689114</td>\n",
       "      <td>0.510462</td>\n",
       "      <td>0.619213</td>\n",
       "      <td>0.268939</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.204040</td>\n",
       "      <td>0.575756</td>\n",
       "      <td>0.191763</td>\n",
       "      <td>0.246187</td>\n",
       "      <td>0.502207</td>\n",
       "      <td>0.669128</td>\n",
       "      <td>0.414524</td>\n",
       "      <td>0.315336</td>\n",
       "      <td>0.123481</td>\n",
       "      <td>0.382628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>深科技</th>\n",
       "      <td>0.529473</td>\n",
       "      <td>0.770142</td>\n",
       "      <td>0.067068</td>\n",
       "      <td>-0.242234</td>\n",
       "      <td>0.061867</td>\n",
       "      <td>0.152503</td>\n",
       "      <td>0.794583</td>\n",
       "      <td>0.044889</td>\n",
       "      <td>0.430603</td>\n",
       "      <td>-0.078641</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.475872</td>\n",
       "      <td>0.507937</td>\n",
       "      <td>-0.031985</td>\n",
       "      <td>-0.003834</td>\n",
       "      <td>0.252768</td>\n",
       "      <td>0.730319</td>\n",
       "      <td>0.700432</td>\n",
       "      <td>0.059207</td>\n",
       "      <td>-0.039428</td>\n",
       "      <td>0.472494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>上海凯宝</th>\n",
       "      <td>0.238083</td>\n",
       "      <td>-0.106340</td>\n",
       "      <td>0.668814</td>\n",
       "      <td>0.867643</td>\n",
       "      <td>0.857183</td>\n",
       "      <td>0.763036</td>\n",
       "      <td>0.096572</td>\n",
       "      <td>0.491244</td>\n",
       "      <td>0.702104</td>\n",
       "      <td>0.721062</td>\n",
       "      <td>...</td>\n",
       "      <td>0.778441</td>\n",
       "      <td>0.532056</td>\n",
       "      <td>0.432406</td>\n",
       "      <td>0.515304</td>\n",
       "      <td>0.742388</td>\n",
       "      <td>-0.075180</td>\n",
       "      <td>-0.290038</td>\n",
       "      <td>0.529285</td>\n",
       "      <td>0.908305</td>\n",
       "      <td>0.824209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>招商轮船</th>\n",
       "      <td>0.356789</td>\n",
       "      <td>0.639861</td>\n",
       "      <td>-0.181563</td>\n",
       "      <td>-0.543551</td>\n",
       "      <td>-0.179912</td>\n",
       "      <td>-0.063249</td>\n",
       "      <td>0.795300</td>\n",
       "      <td>0.245807</td>\n",
       "      <td>0.311361</td>\n",
       "      <td>-0.163403</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.517070</td>\n",
       "      <td>0.518953</td>\n",
       "      <td>0.265244</td>\n",
       "      <td>0.337378</td>\n",
       "      <td>0.288104</td>\n",
       "      <td>0.894638</td>\n",
       "      <td>0.842173</td>\n",
       "      <td>0.237744</td>\n",
       "      <td>-0.139678</td>\n",
       "      <td>0.151903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>北京利尔</th>\n",
       "      <td>0.519113</td>\n",
       "      <td>0.522470</td>\n",
       "      <td>0.260431</td>\n",
       "      <td>0.016872</td>\n",
       "      <td>0.432419</td>\n",
       "      <td>0.293770</td>\n",
       "      <td>0.735550</td>\n",
       "      <td>0.631882</td>\n",
       "      <td>0.770094</td>\n",
       "      <td>0.252097</td>\n",
       "      <td>...</td>\n",
       "      <td>0.101065</td>\n",
       "      <td>0.800766</td>\n",
       "      <td>0.541208</td>\n",
       "      <td>0.643402</td>\n",
       "      <td>0.812743</td>\n",
       "      <td>0.733494</td>\n",
       "      <td>0.582584</td>\n",
       "      <td>0.618513</td>\n",
       "      <td>0.394377</td>\n",
       "      <td>0.662053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>锦泓集团</th>\n",
       "      <td>-0.220054</td>\n",
       "      <td>-0.431831</td>\n",
       "      <td>0.490292</td>\n",
       "      <td>0.669624</td>\n",
       "      <td>0.565285</td>\n",
       "      <td>0.550005</td>\n",
       "      <td>-0.151435</td>\n",
       "      <td>0.514437</td>\n",
       "      <td>0.390180</td>\n",
       "      <td>0.658196</td>\n",
       "      <td>...</td>\n",
       "      <td>0.827554</td>\n",
       "      <td>0.411827</td>\n",
       "      <td>0.650017</td>\n",
       "      <td>0.774566</td>\n",
       "      <td>0.634665</td>\n",
       "      <td>-0.240310</td>\n",
       "      <td>-0.349112</td>\n",
       "      <td>0.764305</td>\n",
       "      <td>0.817010</td>\n",
       "      <td>0.438019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>大连圣亚</th>\n",
       "      <td>0.613110</td>\n",
       "      <td>0.706895</td>\n",
       "      <td>-0.179497</td>\n",
       "      <td>-0.505913</td>\n",
       "      <td>-0.161537</td>\n",
       "      <td>-0.101849</td>\n",
       "      <td>0.746218</td>\n",
       "      <td>0.071846</td>\n",
       "      <td>0.271632</td>\n",
       "      <td>-0.279952</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.598563</td>\n",
       "      <td>0.372877</td>\n",
       "      <td>-0.018049</td>\n",
       "      <td>-0.048079</td>\n",
       "      <td>0.111123</td>\n",
       "      <td>0.825872</td>\n",
       "      <td>0.751806</td>\n",
       "      <td>-0.118462</td>\n",
       "      <td>-0.238661</td>\n",
       "      <td>0.176338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>云南锗业</th>\n",
       "      <td>0.594264</td>\n",
       "      <td>0.602974</td>\n",
       "      <td>0.462922</td>\n",
       "      <td>0.281320</td>\n",
       "      <td>0.558396</td>\n",
       "      <td>0.505214</td>\n",
       "      <td>0.628330</td>\n",
       "      <td>0.271806</td>\n",
       "      <td>0.743988</td>\n",
       "      <td>0.298084</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.023137</td>\n",
       "      <td>0.614442</td>\n",
       "      <td>0.117431</td>\n",
       "      <td>0.141621</td>\n",
       "      <td>0.546312</td>\n",
       "      <td>0.496688</td>\n",
       "      <td>0.350595</td>\n",
       "      <td>0.138256</td>\n",
       "      <td>0.375598</td>\n",
       "      <td>0.731994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>永高股份</th>\n",
       "      <td>0.730511</td>\n",
       "      <td>0.758181</td>\n",
       "      <td>-0.065760</td>\n",
       "      <td>-0.358757</td>\n",
       "      <td>-0.069902</td>\n",
       "      <td>0.041416</td>\n",
       "      <td>0.769081</td>\n",
       "      <td>0.011053</td>\n",
       "      <td>0.344981</td>\n",
       "      <td>-0.203862</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.558012</td>\n",
       "      <td>0.355795</td>\n",
       "      <td>-0.157234</td>\n",
       "      <td>-0.155463</td>\n",
       "      <td>0.130907</td>\n",
       "      <td>0.763736</td>\n",
       "      <td>0.695546</td>\n",
       "      <td>-0.190959</td>\n",
       "      <td>-0.175192</td>\n",
       "      <td>0.301142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>西部牧业</th>\n",
       "      <td>0.763218</td>\n",
       "      <td>0.820417</td>\n",
       "      <td>0.053791</td>\n",
       "      <td>-0.442957</td>\n",
       "      <td>0.018875</td>\n",
       "      <td>-0.131160</td>\n",
       "      <td>0.638839</td>\n",
       "      <td>0.122919</td>\n",
       "      <td>0.361127</td>\n",
       "      <td>-0.166254</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.598129</td>\n",
       "      <td>0.273533</td>\n",
       "      <td>-0.205533</td>\n",
       "      <td>-0.244296</td>\n",
       "      <td>0.081373</td>\n",
       "      <td>0.693134</td>\n",
       "      <td>0.555445</td>\n",
       "      <td>-0.248900</td>\n",
       "      <td>-0.291857</td>\n",
       "      <td>0.158375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>锦龙股份</th>\n",
       "      <td>0.698215</td>\n",
       "      <td>0.843238</td>\n",
       "      <td>0.090754</td>\n",
       "      <td>-0.431029</td>\n",
       "      <td>0.017468</td>\n",
       "      <td>0.105070</td>\n",
       "      <td>0.908566</td>\n",
       "      <td>0.297028</td>\n",
       "      <td>0.523130</td>\n",
       "      <td>-0.021221</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.522005</td>\n",
       "      <td>0.604722</td>\n",
       "      <td>0.203144</td>\n",
       "      <td>0.240434</td>\n",
       "      <td>0.381742</td>\n",
       "      <td>0.971792</td>\n",
       "      <td>0.820138</td>\n",
       "      <td>0.179373</td>\n",
       "      <td>-0.024162</td>\n",
       "      <td>0.276496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>特一药业</th>\n",
       "      <td>0.837665</td>\n",
       "      <td>0.654837</td>\n",
       "      <td>0.562612</td>\n",
       "      <td>0.230404</td>\n",
       "      <td>0.572866</td>\n",
       "      <td>0.505141</td>\n",
       "      <td>0.707158</td>\n",
       "      <td>0.457510</td>\n",
       "      <td>0.843180</td>\n",
       "      <td>0.372480</td>\n",
       "      <td>...</td>\n",
       "      <td>0.026952</td>\n",
       "      <td>0.718129</td>\n",
       "      <td>0.196419</td>\n",
       "      <td>0.264123</td>\n",
       "      <td>0.674247</td>\n",
       "      <td>0.630240</td>\n",
       "      <td>0.394900</td>\n",
       "      <td>0.251583</td>\n",
       "      <td>0.460290</td>\n",
       "      <td>0.750077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>正海磁材</th>\n",
       "      <td>0.596432</td>\n",
       "      <td>0.652305</td>\n",
       "      <td>0.359004</td>\n",
       "      <td>0.108669</td>\n",
       "      <td>0.294067</td>\n",
       "      <td>0.322709</td>\n",
       "      <td>0.495506</td>\n",
       "      <td>-0.041892</td>\n",
       "      <td>0.479311</td>\n",
       "      <td>0.111797</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.263330</td>\n",
       "      <td>0.272034</td>\n",
       "      <td>-0.161082</td>\n",
       "      <td>-0.198415</td>\n",
       "      <td>0.192214</td>\n",
       "      <td>0.372520</td>\n",
       "      <td>0.268311</td>\n",
       "      <td>-0.251309</td>\n",
       "      <td>0.132403</td>\n",
       "      <td>0.413851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>信捷电气</th>\n",
       "      <td>0.630906</td>\n",
       "      <td>0.662524</td>\n",
       "      <td>0.349320</td>\n",
       "      <td>0.035363</td>\n",
       "      <td>0.322972</td>\n",
       "      <td>0.479128</td>\n",
       "      <td>0.828228</td>\n",
       "      <td>0.336499</td>\n",
       "      <td>0.705531</td>\n",
       "      <td>0.234278</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.101292</td>\n",
       "      <td>0.769163</td>\n",
       "      <td>0.299103</td>\n",
       "      <td>0.439997</td>\n",
       "      <td>0.639963</td>\n",
       "      <td>0.755791</td>\n",
       "      <td>0.678502</td>\n",
       "      <td>0.457830</td>\n",
       "      <td>0.391577</td>\n",
       "      <td>0.681543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱尔眼科</th>\n",
       "      <td>0.523785</td>\n",
       "      <td>0.520665</td>\n",
       "      <td>0.491370</td>\n",
       "      <td>0.202690</td>\n",
       "      <td>0.437723</td>\n",
       "      <td>0.386100</td>\n",
       "      <td>0.567747</td>\n",
       "      <td>0.335063</td>\n",
       "      <td>0.576721</td>\n",
       "      <td>0.376379</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.001707</td>\n",
       "      <td>0.551003</td>\n",
       "      <td>0.079462</td>\n",
       "      <td>0.183581</td>\n",
       "      <td>0.465783</td>\n",
       "      <td>0.438669</td>\n",
       "      <td>0.279629</td>\n",
       "      <td>0.429892</td>\n",
       "      <td>0.331116</td>\n",
       "      <td>0.598737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>黑猫股份</th>\n",
       "      <td>-0.238495</td>\n",
       "      <td>-0.596240</td>\n",
       "      <td>0.379865</td>\n",
       "      <td>0.849128</td>\n",
       "      <td>0.653571</td>\n",
       "      <td>0.443930</td>\n",
       "      <td>-0.406281</td>\n",
       "      <td>0.405376</td>\n",
       "      <td>0.277477</td>\n",
       "      <td>0.564162</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.122047</td>\n",
       "      <td>0.392315</td>\n",
       "      <td>0.453044</td>\n",
       "      <td>0.494541</td>\n",
       "      <td>-0.511753</td>\n",
       "      <td>-0.613279</td>\n",
       "      <td>0.470226</td>\n",
       "      <td>0.730655</td>\n",
       "      <td>0.442275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中航三鑫</th>\n",
       "      <td>0.486394</td>\n",
       "      <td>0.489602</td>\n",
       "      <td>0.547940</td>\n",
       "      <td>0.187422</td>\n",
       "      <td>0.532841</td>\n",
       "      <td>0.509498</td>\n",
       "      <td>0.669672</td>\n",
       "      <td>0.656787</td>\n",
       "      <td>0.818302</td>\n",
       "      <td>0.446497</td>\n",
       "      <td>...</td>\n",
       "      <td>0.122047</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.595129</td>\n",
       "      <td>0.704621</td>\n",
       "      <td>0.800572</td>\n",
       "      <td>0.657375</td>\n",
       "      <td>0.438286</td>\n",
       "      <td>0.624396</td>\n",
       "      <td>0.572942</td>\n",
       "      <td>0.660638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>华谊嘉信</th>\n",
       "      <td>0.027420</td>\n",
       "      <td>-0.013086</td>\n",
       "      <td>0.291968</td>\n",
       "      <td>0.226343</td>\n",
       "      <td>0.378806</td>\n",
       "      <td>0.338467</td>\n",
       "      <td>0.232992</td>\n",
       "      <td>0.530883</td>\n",
       "      <td>0.528957</td>\n",
       "      <td>0.317854</td>\n",
       "      <td>...</td>\n",
       "      <td>0.392315</td>\n",
       "      <td>0.595129</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.821834</td>\n",
       "      <td>0.671229</td>\n",
       "      <td>0.238679</td>\n",
       "      <td>0.130161</td>\n",
       "      <td>0.650340</td>\n",
       "      <td>0.584489</td>\n",
       "      <td>0.401624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>广东鸿图</th>\n",
       "      <td>0.018429</td>\n",
       "      <td>-0.012861</td>\n",
       "      <td>0.331730</td>\n",
       "      <td>0.260683</td>\n",
       "      <td>0.423850</td>\n",
       "      <td>0.453160</td>\n",
       "      <td>0.326502</td>\n",
       "      <td>0.653076</td>\n",
       "      <td>0.581346</td>\n",
       "      <td>0.499472</td>\n",
       "      <td>...</td>\n",
       "      <td>0.453044</td>\n",
       "      <td>0.704621</td>\n",
       "      <td>0.821834</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.790965</td>\n",
       "      <td>0.318687</td>\n",
       "      <td>0.201688</td>\n",
       "      <td>0.824347</td>\n",
       "      <td>0.675912</td>\n",
       "      <td>0.486274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>北玻股份</th>\n",
       "      <td>0.400401</td>\n",
       "      <td>0.262497</td>\n",
       "      <td>0.593811</td>\n",
       "      <td>0.446052</td>\n",
       "      <td>0.715777</td>\n",
       "      <td>0.534477</td>\n",
       "      <td>0.490043</td>\n",
       "      <td>0.765167</td>\n",
       "      <td>0.881065</td>\n",
       "      <td>0.578404</td>\n",
       "      <td>...</td>\n",
       "      <td>0.494541</td>\n",
       "      <td>0.800572</td>\n",
       "      <td>0.671229</td>\n",
       "      <td>0.790965</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.426725</td>\n",
       "      <td>0.219322</td>\n",
       "      <td>0.715877</td>\n",
       "      <td>0.754327</td>\n",
       "      <td>0.781490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>国金证券</th>\n",
       "      <td>0.650403</td>\n",
       "      <td>0.832359</td>\n",
       "      <td>0.072941</td>\n",
       "      <td>-0.468549</td>\n",
       "      <td>0.000958</td>\n",
       "      <td>0.053574</td>\n",
       "      <td>0.915643</td>\n",
       "      <td>0.351374</td>\n",
       "      <td>0.527124</td>\n",
       "      <td>-0.041275</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.511753</td>\n",
       "      <td>0.657375</td>\n",
       "      <td>0.238679</td>\n",
       "      <td>0.318687</td>\n",
       "      <td>0.426725</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.864075</td>\n",
       "      <td>0.236083</td>\n",
       "      <td>-0.034326</td>\n",
       "      <td>0.286110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>杭齿前进</th>\n",
       "      <td>0.460415</td>\n",
       "      <td>0.726243</td>\n",
       "      <td>-0.199625</td>\n",
       "      <td>-0.589541</td>\n",
       "      <td>-0.270992</td>\n",
       "      <td>-0.080164</td>\n",
       "      <td>0.822527</td>\n",
       "      <td>0.012664</td>\n",
       "      <td>0.254875</td>\n",
       "      <td>-0.332901</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.613279</td>\n",
       "      <td>0.438286</td>\n",
       "      <td>0.130161</td>\n",
       "      <td>0.201688</td>\n",
       "      <td>0.219322</td>\n",
       "      <td>0.864075</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.136822</td>\n",
       "      <td>-0.191193</td>\n",
       "      <td>0.150011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>三丰智能</th>\n",
       "      <td>0.013551</td>\n",
       "      <td>0.009637</td>\n",
       "      <td>0.400099</td>\n",
       "      <td>0.314814</td>\n",
       "      <td>0.459930</td>\n",
       "      <td>0.436698</td>\n",
       "      <td>0.307270</td>\n",
       "      <td>0.596653</td>\n",
       "      <td>0.517335</td>\n",
       "      <td>0.542976</td>\n",
       "      <td>...</td>\n",
       "      <td>0.470226</td>\n",
       "      <td>0.624396</td>\n",
       "      <td>0.650340</td>\n",
       "      <td>0.824347</td>\n",
       "      <td>0.715877</td>\n",
       "      <td>0.236083</td>\n",
       "      <td>0.136822</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.620209</td>\n",
       "      <td>0.492563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>海汽集团</th>\n",
       "      <td>0.175915</td>\n",
       "      <td>-0.126639</td>\n",
       "      <td>0.657290</td>\n",
       "      <td>0.782421</td>\n",
       "      <td>0.766377</td>\n",
       "      <td>0.812744</td>\n",
       "      <td>0.120478</td>\n",
       "      <td>0.466242</td>\n",
       "      <td>0.672594</td>\n",
       "      <td>0.723574</td>\n",
       "      <td>...</td>\n",
       "      <td>0.730655</td>\n",
       "      <td>0.572942</td>\n",
       "      <td>0.584489</td>\n",
       "      <td>0.675912</td>\n",
       "      <td>0.754327</td>\n",
       "      <td>-0.034326</td>\n",
       "      <td>-0.191193</td>\n",
       "      <td>0.620209</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.750991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>漫步者</th>\n",
       "      <td>0.412670</td>\n",
       "      <td>0.242778</td>\n",
       "      <td>0.527877</td>\n",
       "      <td>0.569440</td>\n",
       "      <td>0.690990</td>\n",
       "      <td>0.687040</td>\n",
       "      <td>0.468470</td>\n",
       "      <td>0.407059</td>\n",
       "      <td>0.794198</td>\n",
       "      <td>0.506656</td>\n",
       "      <td>...</td>\n",
       "      <td>0.442275</td>\n",
       "      <td>0.660638</td>\n",
       "      <td>0.401624</td>\n",
       "      <td>0.486274</td>\n",
       "      <td>0.781490</td>\n",
       "      <td>0.286110</td>\n",
       "      <td>0.150011</td>\n",
       "      <td>0.492563</td>\n",
       "      <td>0.750991</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2379 rows × 2379 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "ts_code      慈星股份      三川智慧      邦宝益智      凯文教育       搜于特      奋达科技       新大陆  \\\n",
       "ts_code                                                                         \n",
       "慈星股份     1.000000  0.756323  0.433446 -0.034682  0.345737  0.278549  0.679325   \n",
       "三川智慧     0.756323  1.000000  0.203454 -0.401434  0.037537  0.036726  0.823073   \n",
       "邦宝益智     0.433446  0.203454  1.000000  0.579755  0.722670  0.577385  0.192028   \n",
       "凯文教育    -0.034682 -0.401434  0.579755  1.000000  0.743102  0.637461 -0.280553   \n",
       "搜于特      0.345737  0.037537  0.722670  0.743102  1.000000  0.637597  0.090617   \n",
       "奋达科技     0.278549  0.036726  0.577385  0.637461  0.637597  1.000000  0.225153   \n",
       "新大陆      0.679325  0.823073  0.192028 -0.280553  0.090617  0.225153  1.000000   \n",
       "福成股份     0.294054  0.190707  0.482302  0.269075  0.624742  0.243073  0.264844   \n",
       "万安科技     0.646856  0.496171  0.696565  0.383689  0.743998  0.582748  0.606550   \n",
       "中交地产     0.150996 -0.077782  0.680662  0.629695  0.750142  0.685663  0.039354   \n",
       "雷柏科技     0.260434  0.027788  0.689838  0.704966  0.809276  0.740550  0.250501   \n",
       "圆通速递     0.601366  0.459576  0.544246  0.355147  0.638498  0.572750  0.554512   \n",
       "华润双鹤    -0.019849 -0.373908  0.572264  0.954226  0.689897  0.704271 -0.240119   \n",
       "亚太科技     0.374692  0.252504  0.631258  0.381674  0.691783  0.626098  0.462160   \n",
       "人民同泰     0.540342  0.428267  0.490142  0.317298  0.640748  0.510308  0.558442   \n",
       "海兴电力     0.361034  0.167884  0.602399  0.661396  0.638800  0.812182  0.379346   \n",
       "隧道股份     0.400729  0.551399  0.232368 -0.191934  0.180259  0.181453  0.727167   \n",
       "开尔新材     0.676485  0.800787  0.079480 -0.425236 -0.025262 -0.049543  0.688814   \n",
       "硅宝科技     0.686322  0.734156  0.159758 -0.133436  0.152757  0.285378  0.863043   \n",
       "宁夏建材     0.521147  0.475162  0.209783  0.146585  0.487117  0.301311  0.606066   \n",
       "百润股份     0.728753  0.729346  0.109693 -0.146953  0.089763  0.184707  0.697042   \n",
       "一心堂      0.562017  0.305876  0.767404  0.607120  0.700795  0.635371  0.323379   \n",
       "东莞控股     0.740503  0.833269  0.335860 -0.206701  0.246950  0.267630  0.902994   \n",
       "东易日盛    -0.146982 -0.265372  0.579773  0.529537  0.634578  0.476704 -0.095413   \n",
       "九鼎新材     0.046246  0.258333 -0.429658 -0.223762 -0.308903 -0.070234  0.332768   \n",
       "中信重工     0.721708  0.842966  0.113637 -0.338907  0.145811  0.091539  0.871252   \n",
       "威海广泰     0.740558  0.857778  0.126471 -0.297546  0.106126  0.141421  0.905247   \n",
       "经纬辉开     0.364127  0.377471  0.389133  0.162270  0.410883  0.479095  0.633511   \n",
       "闽发铝业     0.484453  0.331710  0.722680  0.499971  0.793687  0.609700  0.405357   \n",
       "中洲控股    -0.298318 -0.590505  0.314969  0.766476  0.623393  0.302193 -0.512121   \n",
       "...           ...       ...       ...       ...       ...       ...       ...   \n",
       "羚锐制药     0.551324  0.337248  0.671932  0.563282  0.729313  0.548483  0.439336   \n",
       "王府井      0.392415  0.090883  0.751748  0.707116  0.770509  0.838450  0.305225   \n",
       "河钢股份     0.110952  0.183570  0.174731 -0.055747  0.305985  0.193013  0.342883   \n",
       "华泰股份     0.352450  0.222074  0.457464  0.272335  0.629858  0.554568  0.478573   \n",
       "国美通讯     0.261459 -0.026466  0.688195  0.713981  0.761043  0.654798  0.173044   \n",
       "吉峰科技     0.668981  0.629276  0.449655 -0.126170  0.265741  0.115581  0.689114   \n",
       "深科技      0.529473  0.770142  0.067068 -0.242234  0.061867  0.152503  0.794583   \n",
       "上海凯宝     0.238083 -0.106340  0.668814  0.867643  0.857183  0.763036  0.096572   \n",
       "招商轮船     0.356789  0.639861 -0.181563 -0.543551 -0.179912 -0.063249  0.795300   \n",
       "北京利尔     0.519113  0.522470  0.260431  0.016872  0.432419  0.293770  0.735550   \n",
       "锦泓集团    -0.220054 -0.431831  0.490292  0.669624  0.565285  0.550005 -0.151435   \n",
       "大连圣亚     0.613110  0.706895 -0.179497 -0.505913 -0.161537 -0.101849  0.746218   \n",
       "云南锗业     0.594264  0.602974  0.462922  0.281320  0.558396  0.505214  0.628330   \n",
       "永高股份     0.730511  0.758181 -0.065760 -0.358757 -0.069902  0.041416  0.769081   \n",
       "西部牧业     0.763218  0.820417  0.053791 -0.442957  0.018875 -0.131160  0.638839   \n",
       "锦龙股份     0.698215  0.843238  0.090754 -0.431029  0.017468  0.105070  0.908566   \n",
       "特一药业     0.837665  0.654837  0.562612  0.230404  0.572866  0.505141  0.707158   \n",
       "正海磁材     0.596432  0.652305  0.359004  0.108669  0.294067  0.322709  0.495506   \n",
       "信捷电气     0.630906  0.662524  0.349320  0.035363  0.322972  0.479128  0.828228   \n",
       "爱尔眼科     0.523785  0.520665  0.491370  0.202690  0.437723  0.386100  0.567747   \n",
       "黑猫股份    -0.238495 -0.596240  0.379865  0.849128  0.653571  0.443930 -0.406281   \n",
       "中航三鑫     0.486394  0.489602  0.547940  0.187422  0.532841  0.509498  0.669672   \n",
       "华谊嘉信     0.027420 -0.013086  0.291968  0.226343  0.378806  0.338467  0.232992   \n",
       "广东鸿图     0.018429 -0.012861  0.331730  0.260683  0.423850  0.453160  0.326502   \n",
       "北玻股份     0.400401  0.262497  0.593811  0.446052  0.715777  0.534477  0.490043   \n",
       "国金证券     0.650403  0.832359  0.072941 -0.468549  0.000958  0.053574  0.915643   \n",
       "杭齿前进     0.460415  0.726243 -0.199625 -0.589541 -0.270992 -0.080164  0.822527   \n",
       "三丰智能     0.013551  0.009637  0.400099  0.314814  0.459930  0.436698  0.307270   \n",
       "海汽集团     0.175915 -0.126639  0.657290  0.782421  0.766377  0.812744  0.120478   \n",
       "漫步者      0.412670  0.242778  0.527877  0.569440  0.690990  0.687040  0.468470   \n",
       "\n",
       "ts_code      福成股份      万安科技      中交地产    ...         黑猫股份      中航三鑫      华谊嘉信  \\\n",
       "ts_code                                  ...                                    \n",
       "慈星股份     0.294054  0.646856  0.150996    ...    -0.238495  0.486394  0.027420   \n",
       "三川智慧     0.190707  0.496171 -0.077782    ...    -0.596240  0.489602 -0.013086   \n",
       "邦宝益智     0.482302  0.696565  0.680662    ...     0.379865  0.547940  0.291968   \n",
       "凯文教育     0.269075  0.383689  0.629695    ...     0.849128  0.187422  0.226343   \n",
       "搜于特      0.624742  0.743998  0.750142    ...     0.653571  0.532841  0.378806   \n",
       "奋达科技     0.243073  0.582748  0.685663    ...     0.443930  0.509498  0.338467   \n",
       "新大陆      0.264844  0.606550  0.039354    ...    -0.406281  0.669672  0.232992   \n",
       "福成股份     1.000000  0.689438  0.606063    ...     0.405376  0.656787  0.530883   \n",
       "万安科技     0.689438  1.000000  0.581277    ...     0.277477  0.818302  0.528957   \n",
       "中交地产     0.606063  0.581277  1.000000    ...     0.564162  0.446497  0.317854   \n",
       "雷柏科技     0.638777  0.807555  0.723213    ...     0.689334  0.697288  0.607022   \n",
       "圆通速递     0.615826  0.771545  0.545989    ...     0.212533  0.723429  0.284724   \n",
       "华润双鹤     0.177519  0.342642  0.656528    ...     0.787830  0.149415  0.148993   \n",
       "亚太科技     0.751244  0.842072  0.694792    ...     0.432660  0.818475  0.678111   \n",
       "人民同泰     0.619400  0.794948  0.511715    ...     0.212889  0.744111  0.312276   \n",
       "海兴电力     0.281263  0.699714  0.543328    ...     0.454946  0.584944  0.333820   \n",
       "隧道股份     0.611321  0.625450  0.173654    ...    -0.101397  0.792019  0.560239   \n",
       "开尔新材     0.109089  0.325854 -0.072167    ...    -0.647625  0.337610 -0.230857   \n",
       "硅宝科技     0.265131  0.589162  0.012755    ...    -0.303954  0.668467  0.174255   \n",
       "宁夏建材     0.607317  0.718309  0.287078    ...     0.157511  0.660409  0.304174   \n",
       "百润股份     0.007395  0.398250 -0.051659    ...    -0.458712  0.361836 -0.259349   \n",
       "一心堂      0.308728  0.675937  0.617241    ...     0.288448  0.444985  0.063936   \n",
       "东莞控股     0.476687  0.724820  0.175042    ...    -0.323565  0.788141  0.297609   \n",
       "东易日盛     0.602717  0.450072  0.732980    ...     0.672984  0.443065  0.594715   \n",
       "九鼎新材    -0.449471 -0.141472 -0.412829    ...    -0.398456 -0.066782 -0.335117   \n",
       "中信重工     0.366408  0.605456 -0.000707    ...    -0.434574  0.625339  0.202988   \n",
       "威海广泰     0.267018  0.579219 -0.024337    ...    -0.450276  0.633461  0.103232   \n",
       "经纬辉开     0.574313  0.742560  0.381274    ...     0.215632  0.796654  0.648202   \n",
       "闽发铝业     0.640640  0.809767  0.692698    ...     0.352625  0.681916  0.415673   \n",
       "中洲控股     0.399560  0.206731  0.490061    ...     0.908584  0.069513  0.347711   \n",
       "...           ...       ...       ...    ...          ...       ...       ...   \n",
       "羚锐制药     0.588209  0.793593  0.589346    ...     0.411199  0.641167  0.297052   \n",
       "王府井      0.493473  0.732703  0.766776    ...     0.536990  0.688530  0.394738   \n",
       "河钢股份     0.708752  0.472774  0.376748    ...     0.172970  0.575305  0.685401   \n",
       "华泰股份     0.774706  0.763268  0.616314    ...     0.395561  0.811210  0.695672   \n",
       "国美通讯     0.556360  0.724512  0.644069    ...     0.714986  0.585645  0.521554   \n",
       "吉峰科技     0.510462  0.619213  0.268939    ...    -0.204040  0.575756  0.191763   \n",
       "深科技      0.044889  0.430603 -0.078641    ...    -0.475872  0.507937 -0.031985   \n",
       "上海凯宝     0.491244  0.702104  0.721062    ...     0.778441  0.532056  0.432406   \n",
       "招商轮船     0.245807  0.311361 -0.163403    ...    -0.517070  0.518953  0.265244   \n",
       "北京利尔     0.631882  0.770094  0.252097    ...     0.101065  0.800766  0.541208   \n",
       "锦泓集团     0.514437  0.390180  0.658196    ...     0.827554  0.411827  0.650017   \n",
       "大连圣亚     0.071846  0.271632 -0.279952    ...    -0.598563  0.372877 -0.018049   \n",
       "云南锗业     0.271806  0.743988  0.298084    ...    -0.023137  0.614442  0.117431   \n",
       "永高股份     0.011053  0.344981 -0.203862    ...    -0.558012  0.355795 -0.157234   \n",
       "西部牧业     0.122919  0.361127 -0.166254    ...    -0.598129  0.273533 -0.205533   \n",
       "锦龙股份     0.297028  0.523130 -0.021221    ...    -0.522005  0.604722  0.203144   \n",
       "特一药业     0.457510  0.843180  0.372480    ...     0.026952  0.718129  0.196419   \n",
       "正海磁材    -0.041892  0.479311  0.111797    ...    -0.263330  0.272034 -0.161082   \n",
       "信捷电气     0.336499  0.705531  0.234278    ...    -0.101292  0.769163  0.299103   \n",
       "爱尔眼科     0.335063  0.576721  0.376379    ...    -0.001707  0.551003  0.079462   \n",
       "黑猫股份     0.405376  0.277477  0.564162    ...     1.000000  0.122047  0.392315   \n",
       "中航三鑫     0.656787  0.818302  0.446497    ...     0.122047  1.000000  0.595129   \n",
       "华谊嘉信     0.530883  0.528957  0.317854    ...     0.392315  0.595129  1.000000   \n",
       "广东鸿图     0.653076  0.581346  0.499472    ...     0.453044  0.704621  0.821834   \n",
       "北玻股份     0.765167  0.881065  0.578404    ...     0.494541  0.800572  0.671229   \n",
       "国金证券     0.351374  0.527124 -0.041275    ...    -0.511753  0.657375  0.238679   \n",
       "杭齿前进     0.012664  0.254875 -0.332901    ...    -0.613279  0.438286  0.130161   \n",
       "三丰智能     0.596653  0.517335  0.542976    ...     0.470226  0.624396  0.650340   \n",
       "海汽集团     0.466242  0.672594  0.723574    ...     0.730655  0.572942  0.584489   \n",
       "漫步者      0.407059  0.794198  0.506656    ...     0.442275  0.660638  0.401624   \n",
       "\n",
       "ts_code      广东鸿图      北玻股份      国金证券      杭齿前进      三丰智能      海汽集团       漫步者  \n",
       "ts_code                                                                        \n",
       "慈星股份     0.018429  0.400401  0.650403  0.460415  0.013551  0.175915  0.412670  \n",
       "三川智慧    -0.012861  0.262497  0.832359  0.726243  0.009637 -0.126639  0.242778  \n",
       "邦宝益智     0.331730  0.593811  0.072941 -0.199625  0.400099  0.657290  0.527877  \n",
       "凯文教育     0.260683  0.446052 -0.468549 -0.589541  0.314814  0.782421  0.569440  \n",
       "搜于特      0.423850  0.715777  0.000958 -0.270992  0.459930  0.766377  0.690990  \n",
       "奋达科技     0.453160  0.534477  0.053574 -0.080164  0.436698  0.812744  0.687040  \n",
       "新大陆      0.326502  0.490043  0.915643  0.822527  0.307270  0.120478  0.468470  \n",
       "福成股份     0.653076  0.765167  0.351374  0.012664  0.596653  0.466242  0.407059  \n",
       "万安科技     0.581346  0.881065  0.527124  0.254875  0.517335  0.672594  0.794198  \n",
       "中交地产     0.499472  0.578404 -0.041275 -0.332901  0.542976  0.723574  0.506656  \n",
       "雷柏科技     0.734101  0.883531  0.119576 -0.082832  0.693061  0.899288  0.817835  \n",
       "圆通速递     0.455001  0.714141  0.484067  0.279396  0.454189  0.534255  0.638658  \n",
       "华润双鹤     0.217317  0.391303 -0.445977 -0.576048  0.283957  0.777748  0.564677  \n",
       "亚太科技     0.829496  0.890459  0.402070  0.180810  0.764941  0.747440  0.692990  \n",
       "人民同泰     0.402214  0.709062  0.502309  0.226203  0.414921  0.499636  0.805176  \n",
       "海兴电力     0.444175  0.676720  0.154960  0.073304  0.465613  0.778745  0.825208  \n",
       "隧道股份     0.707180  0.696108  0.778177  0.687882  0.586370  0.259419  0.365507  \n",
       "开尔新材    -0.227603  0.050139  0.733066  0.565379 -0.174959 -0.272221  0.177740  \n",
       "硅宝科技     0.227573  0.472604  0.818610  0.731226  0.181066  0.149637  0.543501  \n",
       "宁夏建材     0.431814  0.725919  0.591842  0.441153  0.380319  0.358100  0.717479  \n",
       "百润股份    -0.226108  0.138723  0.640891  0.555929 -0.175714 -0.074018  0.417954  \n",
       "一心堂      0.104847  0.499505  0.132169 -0.115902  0.254626  0.598855  0.690314  \n",
       "东莞控股     0.406790  0.607037  0.926845  0.755474  0.313893  0.194084  0.473586  \n",
       "东易日盛     0.730856  0.627841 -0.147202 -0.297952  0.755118  0.703802  0.358309  \n",
       "九鼎新材    -0.350877 -0.236901  0.223784  0.404771 -0.263714 -0.302967  0.178768  \n",
       "中信重工     0.240161  0.466044  0.920200  0.812362  0.207684 -0.001565  0.371633  \n",
       "威海广泰     0.163921  0.415017  0.892486  0.793691  0.148782  0.012597  0.457748  \n",
       "经纬辉开     0.802716  0.829780  0.597721  0.503116  0.707016  0.582966  0.631710  \n",
       "闽发铝业     0.507028  0.757899  0.340189  0.038194  0.467275  0.720197  0.643992  \n",
       "中洲控股     0.358526  0.387088 -0.560778 -0.644330  0.382425  0.583767  0.325184  \n",
       "...           ...       ...       ...       ...       ...       ...       ...  \n",
       "羚锐制药     0.376734  0.750707  0.310306  0.035535  0.471619  0.647938  0.810850  \n",
       "王府井      0.545454  0.718222  0.159496 -0.078007  0.570705  0.869367  0.765445  \n",
       "河钢股份     0.798289  0.619874  0.467725  0.296652  0.651015  0.337914  0.159003  \n",
       "华泰股份     0.850290  0.856701  0.495426  0.243572  0.738341  0.683052  0.622529  \n",
       "国美通讯     0.625734  0.813504  0.022535 -0.159511  0.620663  0.877529  0.776344  \n",
       "吉峰科技     0.246187  0.502207  0.669128  0.414524  0.315336  0.123481  0.382628  \n",
       "深科技     -0.003834  0.252768  0.730319  0.700432  0.059207 -0.039428  0.472494  \n",
       "上海凯宝     0.515304  0.742388 -0.075180 -0.290038  0.529285  0.908305  0.824209  \n",
       "招商轮船     0.337378  0.288104  0.894638  0.842173  0.237744 -0.139678  0.151903  \n",
       "北京利尔     0.643402  0.812743  0.733494  0.582584  0.618513  0.394377  0.662053  \n",
       "锦泓集团     0.774566  0.634665 -0.240310 -0.349112  0.764305  0.817010  0.438019  \n",
       "大连圣亚    -0.048079  0.111123  0.825872  0.751806 -0.118462 -0.238661  0.176338  \n",
       "云南锗业     0.141621  0.546312  0.496688  0.350595  0.138256  0.375598  0.731994  \n",
       "永高股份    -0.155463  0.130907  0.763736  0.695546 -0.190959 -0.175192  0.301142  \n",
       "西部牧业    -0.244296  0.081373  0.693134  0.555445 -0.248900 -0.291857  0.158375  \n",
       "锦龙股份     0.240434  0.381742  0.971792  0.820138  0.179373 -0.024162  0.276496  \n",
       "特一药业     0.264123  0.674247  0.630240  0.394900  0.251583  0.460290  0.750077  \n",
       "正海磁材    -0.198415  0.192214  0.372520  0.268311 -0.251309  0.132403  0.413851  \n",
       "信捷电气     0.439997  0.639963  0.755791  0.678502  0.457830  0.391577  0.681543  \n",
       "爱尔眼科     0.183581  0.465783  0.438669  0.279629  0.429892  0.331116  0.598737  \n",
       "黑猫股份     0.453044  0.494541 -0.511753 -0.613279  0.470226  0.730655  0.442275  \n",
       "中航三鑫     0.704621  0.800572  0.657375  0.438286  0.624396  0.572942  0.660638  \n",
       "华谊嘉信     0.821834  0.671229  0.238679  0.130161  0.650340  0.584489  0.401624  \n",
       "广东鸿图     1.000000  0.790965  0.318687  0.201688  0.824347  0.675912  0.486274  \n",
       "北玻股份     0.790965  1.000000  0.426725  0.219322  0.715877  0.754327  0.781490  \n",
       "国金证券     0.318687  0.426725  1.000000  0.864075  0.236083 -0.034326  0.286110  \n",
       "杭齿前进     0.201688  0.219322  0.864075  1.000000  0.136822 -0.191193  0.150011  \n",
       "三丰智能     0.824347  0.715877  0.236083  0.136822  1.000000  0.620209  0.492563  \n",
       "海汽集团     0.675912  0.754327 -0.034326 -0.191193  0.620209  1.000000  0.750991  \n",
       "漫步者      0.486274  0.781490  0.286110  0.150011  0.492563  0.750991  1.000000  \n",
       "\n",
       "[2379 rows x 2379 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-04T14:24:26.006419Z",
     "start_time": "2019-09-04T14:24:25.988464Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>ts_code</th>\n",
       "      <th>慈星股份</th>\n",
       "      <th>三川智慧</th>\n",
       "      <th>邦宝益智</th>\n",
       "      <th>凯文教育</th>\n",
       "      <th>搜于特</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</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>20180615</th>\n",
       "      <td>6.37</td>\n",
       "      <td>3.79</td>\n",
       "      <td>16.53</td>\n",
       "      <td>13.57</td>\n",
       "      <td>3.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180619</th>\n",
       "      <td>5.79</td>\n",
       "      <td>3.44</td>\n",
       "      <td>14.88</td>\n",
       "      <td>13.10</td>\n",
       "      <td>3.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180620</th>\n",
       "      <td>5.93</td>\n",
       "      <td>3.50</td>\n",
       "      <td>14.71</td>\n",
       "      <td>13.15</td>\n",
       "      <td>3.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180621</th>\n",
       "      <td>5.77</td>\n",
       "      <td>3.42</td>\n",
       "      <td>15.30</td>\n",
       "      <td>13.00</td>\n",
       "      <td>3.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20180622</th>\n",
       "      <td>5.85</td>\n",
       "      <td>3.47</td>\n",
       "      <td>15.37</td>\n",
       "      <td>13.35</td>\n",
       "      <td>3.47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "ts_code     慈星股份  三川智慧   邦宝益智   凯文教育   搜于特\n",
       "trade_date                                \n",
       "20180615    6.37  3.79  16.53  13.57  3.59\n",
       "20180619    5.79  3.44  14.88  13.10  3.45\n",
       "20180620    5.93  3.50  14.71  13.15  3.49\n",
       "20180621    5.77  3.42  15.30  13.00  3.45\n",
       "20180622    5.85  3.47  15.37  13.35  3.47"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd=final_data.iloc[:,:5]\n",
    "dd.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-04T14:25:22.423517Z",
     "start_time": "2019-09-04T14:25:22.099385Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#皮尔逊相关系数\n",
    "import seaborn as sns\n",
    "d1=dd.corr()\n",
    "plt.subplots(figsize=(9, 9)) # 设置画面大小\n",
    "sns.heatmap(d1, annot=True, vmax=1, square=True, cmap=\"Reds\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-04T14:26:21.554005Z",
     "start_time": "2019-09-04T14:26:21.271733Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(dd/dd.iloc[0]).plot(figsize=(16,5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}