【乐学偶得出品】0.extra.【金融数据可视化】.ipynb

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   "metadata": {},
   "source": [
    "乐学偶得版权所有 lexueoude.com 公众号1：乐学Fintech 2: 乐学偶得"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import tushare as ts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
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       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
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       "      <th>0</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>20190628</td>\n",
       "      <td>13.73</td>\n",
       "      <td>13.79</td>\n",
       "      <td>13.58</td>\n",
       "      <td>13.78</td>\n",
       "      <td>13.71</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.5106</td>\n",
       "      <td>498093.69</td>\n",
       "      <td>682679.970</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>20190627</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.85</td>\n",
       "      <td>13.45</td>\n",
       "      <td>13.71</td>\n",
       "      <td>13.37</td>\n",
       "      <td>0.34</td>\n",
       "      <td>2.5430</td>\n",
       "      <td>925074.94</td>\n",
       "      <td>1270042.461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>20190626</td>\n",
       "      <td>13.27</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.19</td>\n",
       "      <td>13.37</td>\n",
       "      <td>13.29</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.6020</td>\n",
       "      <td>546504.76</td>\n",
       "      <td>731207.282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>20190625</td>\n",
       "      <td>13.72</td>\n",
       "      <td>13.72</td>\n",
       "      <td>13.07</td>\n",
       "      <td>13.43</td>\n",
       "      <td>13.69</td>\n",
       "      <td>-0.26</td>\n",
       "      <td>-1.8992</td>\n",
       "      <td>1469227.07</td>\n",
       "      <td>1954855.785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>20190624</td>\n",
       "      <td>13.69</td>\n",
       "      <td>13.83</td>\n",
       "      <td>13.61</td>\n",
       "      <td>13.69</td>\n",
       "      <td>13.64</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.3666</td>\n",
       "      <td>659572.85</td>\n",
       "      <td>904433.349</td>\n",
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      "text/plain": [
       "     ts_code trade_date   open   high    low  close  pre_close  change  \\\n",
       "0  000001.SZ   20190628  13.73  13.79  13.58  13.78      13.71    0.07   \n",
       "1  000001.SZ   20190627  13.50  13.85  13.45  13.71      13.37    0.34   \n",
       "2  000001.SZ   20190626  13.27  13.50  13.19  13.37      13.29    0.08   \n",
       "3  000001.SZ   20190625  13.72  13.72  13.07  13.43      13.69   -0.26   \n",
       "4  000001.SZ   20190624  13.69  13.83  13.61  13.69      13.64    0.05   \n",
       "\n",
       "   pct_chg         vol       amount  \n",
       "0   0.5106   498093.69   682679.970  \n",
       "1   2.5430   925074.94  1270042.461  \n",
       "2   0.6020   546504.76   731207.282  \n",
       "3  -1.8992  1469227.07  1954855.785  \n",
       "4   0.3666   659572.85   904433.349  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pro = ts.pro_api()\n",
    "df = pro.daily(ts_code='000001.SZ', start_date='20180101', end_date='20190630')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
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       "      <th>trade_date</th>\n",
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       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.73</td>\n",
       "      <td>13.79</td>\n",
       "      <td>13.58</td>\n",
       "      <td>13.78</td>\n",
       "      <td>13.71</td>\n",
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       "      <td>682679.970</td>\n",
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       "    <tr>\n",
       "      <th>2019-06-27</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.85</td>\n",
       "      <td>13.45</td>\n",
       "      <td>13.71</td>\n",
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       "    <tr>\n",
       "      <th>2019-06-26</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.27</td>\n",
       "      <td>13.50</td>\n",
       "      <td>13.19</td>\n",
       "      <td>13.37</td>\n",
       "      <td>13.29</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.6020</td>\n",
       "      <td>546504.76</td>\n",
       "      <td>731207.282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-25</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.72</td>\n",
       "      <td>13.72</td>\n",
       "      <td>13.07</td>\n",
       "      <td>13.43</td>\n",
       "      <td>13.69</td>\n",
       "      <td>-0.26</td>\n",
       "      <td>-1.8992</td>\n",
       "      <td>1469227.07</td>\n",
       "      <td>1954855.785</td>\n",
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       "    <tr>\n",
       "      <th>2019-06-24</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.69</td>\n",
       "      <td>13.83</td>\n",
       "      <td>13.61</td>\n",
       "      <td>13.69</td>\n",
       "      <td>13.64</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.3666</td>\n",
       "      <td>659572.85</td>\n",
       "      <td>904433.349</td>\n",
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      "text/plain": [
       "              ts_code   open   high    low  close  pre_close  change  pct_chg  \\\n",
       "trade_date                                                                      \n",
       "2019-06-28  000001.SZ  13.73  13.79  13.58  13.78      13.71    0.07   0.5106   \n",
       "2019-06-27  000001.SZ  13.50  13.85  13.45  13.71      13.37    0.34   2.5430   \n",
       "2019-06-26  000001.SZ  13.27  13.50  13.19  13.37      13.29    0.08   0.6020   \n",
       "2019-06-25  000001.SZ  13.72  13.72  13.07  13.43      13.69   -0.26  -1.8992   \n",
       "2019-06-24  000001.SZ  13.69  13.83  13.61  13.69      13.64    0.05   0.3666   \n",
       "\n",
       "                   vol       amount  \n",
       "trade_date                           \n",
       "2019-06-28   498093.69   682679.970  \n",
       "2019-06-27   925074.94  1270042.461  \n",
       "2019-06-26   546504.76   731207.282  \n",
       "2019-06-25  1469227.07  1954855.785  \n",
       "2019-06-24   659572.85   904433.349  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pandas有个专门把字符串转为时间格式的函数，to_datetime。第一个参数是原始数据，第二个参数是原始数据的格式\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'],format='%Y%m%d')\n",
    "# 把trade_date设置为索引\n",
    "df.set_index('trade_date',inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <th>ts_code</th>\n",
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       "      <th>high</th>\n",
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       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
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       "      <th>vol</th>\n",
       "      <th>amount</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",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.35</td>\n",
       "      <td>13.93</td>\n",
       "      <td>13.32</td>\n",
       "      <td>13.70</td>\n",
       "      <td>13.30</td>\n",
       "      <td>0.40</td>\n",
       "      <td>3.01</td>\n",
       "      <td>2081592.55</td>\n",
       "      <td>2856543.822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.73</td>\n",
       "      <td>13.86</td>\n",
       "      <td>13.20</td>\n",
       "      <td>13.33</td>\n",
       "      <td>13.70</td>\n",
       "      <td>-0.37</td>\n",
       "      <td>-2.70</td>\n",
       "      <td>2962498.38</td>\n",
       "      <td>4006220.766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.32</td>\n",
       "      <td>13.37</td>\n",
       "      <td>13.13</td>\n",
       "      <td>13.25</td>\n",
       "      <td>13.33</td>\n",
       "      <td>-0.08</td>\n",
       "      <td>-0.60</td>\n",
       "      <td>1854509.48</td>\n",
       "      <td>2454543.516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.21</td>\n",
       "      <td>13.35</td>\n",
       "      <td>13.15</td>\n",
       "      <td>13.30</td>\n",
       "      <td>13.25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.38</td>\n",
       "      <td>1210312.72</td>\n",
       "      <td>1603289.517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>000001.SZ</td>\n",
       "      <td>13.25</td>\n",
       "      <td>13.29</td>\n",
       "      <td>12.86</td>\n",
       "      <td>12.96</td>\n",
       "      <td>13.30</td>\n",
       "      <td>-0.34</td>\n",
       "      <td>-2.56</td>\n",
       "      <td>2158620.81</td>\n",
       "      <td>2806099.169</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "              ts_code   open   high    low  close  pre_close  change  pct_chg  \\\n",
       "trade_date                                                                      \n",
       "2018-01-02  000001.SZ  13.35  13.93  13.32  13.70      13.30    0.40     3.01   \n",
       "2018-01-03  000001.SZ  13.73  13.86  13.20  13.33      13.70   -0.37    -2.70   \n",
       "2018-01-04  000001.SZ  13.32  13.37  13.13  13.25      13.33   -0.08    -0.60   \n",
       "2018-01-05  000001.SZ  13.21  13.35  13.15  13.30      13.25    0.05     0.38   \n",
       "2018-01-08  000001.SZ  13.25  13.29  12.86  12.96      13.30   -0.34    -2.56   \n",
       "\n",
       "                   vol       amount  \n",
       "trade_date                           \n",
       "2018-01-02  2081592.55  2856543.822  \n",
       "2018-01-03  2962498.38  4006220.766  \n",
       "2018-01-04  1854509.48  2454543.516  \n",
       "2018-01-05  1210312.72  1603289.517  \n",
       "2018-01-08  2158620.81  2806099.169  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=df.sort_index(ascending=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "trade_date\n",
       "2018-01-02    3.01\n",
       "2018-01-03   -2.70\n",
       "2018-01-04   -0.60\n",
       "2018-01-05    0.38\n",
       "2018-01-08   -2.56\n",
       "Name: pct_chg, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "returns=df[\"pct_chg\"].dropna()\n",
    "\n",
    "sns.distplot(returns)\n",
    "returns.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>601111.SH</td>\n",
       "      <td>12.32</td>\n",
       "      <td>12.33</td>\n",
       "      <td>11.52</td>\n",
       "      <td>11.79</td>\n",
       "      <td>12.32</td>\n",
       "      <td>-0.53</td>\n",
       "      <td>-4.30</td>\n",
       "      <td>1084426.35</td>\n",
       "      <td>1276203.270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>601111.SH</td>\n",
       "      <td>11.70</td>\n",
       "      <td>12.92</td>\n",
       "      <td>11.58</td>\n",
       "      <td>12.83</td>\n",
       "      <td>11.79</td>\n",
       "      <td>1.04</td>\n",
       "      <td>8.82</td>\n",
       "      <td>1241841.00</td>\n",
       "      <td>1521291.842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>601111.SH</td>\n",
       "      <td>12.60</td>\n",
       "      <td>12.66</td>\n",
       "      <td>12.22</td>\n",
       "      <td>12.37</td>\n",
       "      <td>12.83</td>\n",
       "      <td>-0.46</td>\n",
       "      <td>-3.59</td>\n",
       "      <td>819331.41</td>\n",
       "      <td>1015749.123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>601111.SH</td>\n",
       "      <td>12.30</td>\n",
       "      <td>12.67</td>\n",
       "      <td>12.00</td>\n",
       "      <td>12.18</td>\n",
       "      <td>12.37</td>\n",
       "      <td>-0.19</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>801047.94</td>\n",
       "      <td>986105.421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>601111.SH</td>\n",
       "      <td>12.75</td>\n",
       "      <td>13.12</td>\n",
       "      <td>12.31</td>\n",
       "      <td>12.50</td>\n",
       "      <td>12.18</td>\n",
       "      <td>0.32</td>\n",
       "      <td>2.63</td>\n",
       "      <td>1506660.76</td>\n",
       "      <td>1915376.396</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ts_code   open   high    low  close  pre_close  change  pct_chg  \\\n",
       "trade_date                                                                      \n",
       "2018-01-02  601111.SH  12.32  12.33  11.52  11.79      12.32   -0.53    -4.30   \n",
       "2018-01-03  601111.SH  11.70  12.92  11.58  12.83      11.79    1.04     8.82   \n",
       "2018-01-04  601111.SH  12.60  12.66  12.22  12.37      12.83   -0.46    -3.59   \n",
       "2018-01-05  601111.SH  12.30  12.67  12.00  12.18      12.37   -0.19    -1.54   \n",
       "2018-01-08  601111.SH  12.75  13.12  12.31  12.50      12.18    0.32     2.63   \n",
       "\n",
       "                   vol       amount  \n",
       "trade_date                           \n",
       "2018-01-02  1084426.35  1276203.270  \n",
       "2018-01-03  1241841.00  1521291.842  \n",
       "2018-01-04   819331.41  1015749.123  \n",
       "2018-01-05   801047.94   986105.421  \n",
       "2018-01-08  1506660.76  1915376.396  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ZGGH= pro.daily(ts_code='601111.SH', start_date='20180101', end_date='20190630')\n",
    "# pandas有个专门把字符串转为时间格式的函数，to_datetime。第一个参数是原始数据，第二个参数是原始数据的格式\n",
    "df_ZGGH['trade_date'] = pd.to_datetime(df_ZGGH['trade_date'],format='%Y%m%d')\n",
    "# 把trade_date设置为索引\n",
    "df_ZGGH.set_index('trade_date',inplace=True)\n",
    "df_ZGGH=df_ZGGH.sort_index(ascending=True)\n",
    "df_ZGGH.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>601857.SH</td>\n",
       "      <td>8.09</td>\n",
       "      <td>8.33</td>\n",
       "      <td>8.08</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.09</td>\n",
       "      <td>0.16</td>\n",
       "      <td>1.98</td>\n",
       "      <td>613961.00</td>\n",
       "      <td>504750.225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>601857.SH</td>\n",
       "      <td>8.23</td>\n",
       "      <td>8.37</td>\n",
       "      <td>8.21</td>\n",
       "      <td>8.27</td>\n",
       "      <td>8.25</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.24</td>\n",
       "      <td>474138.35</td>\n",
       "      <td>392423.555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>601857.SH</td>\n",
       "      <td>8.34</td>\n",
       "      <td>8.79</td>\n",
       "      <td>8.32</td>\n",
       "      <td>8.55</td>\n",
       "      <td>8.27</td>\n",
       "      <td>0.28</td>\n",
       "      <td>3.39</td>\n",
       "      <td>1522772.62</td>\n",
       "      <td>1301096.070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>601857.SH</td>\n",
       "      <td>8.53</td>\n",
       "      <td>8.66</td>\n",
       "      <td>8.48</td>\n",
       "      <td>8.59</td>\n",
       "      <td>8.55</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.47</td>\n",
       "      <td>1022461.29</td>\n",
       "      <td>875275.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>601857.SH</td>\n",
       "      <td>8.56</td>\n",
       "      <td>8.62</td>\n",
       "      <td>8.47</td>\n",
       "      <td>8.53</td>\n",
       "      <td>8.59</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>-0.70</td>\n",
       "      <td>641963.46</td>\n",
       "      <td>547507.905</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ts_code  open  high   low  close  pre_close  change  pct_chg  \\\n",
       "trade_date                                                                   \n",
       "2018-01-02  601857.SH  8.09  8.33  8.08   8.25       8.09    0.16     1.98   \n",
       "2018-01-03  601857.SH  8.23  8.37  8.21   8.27       8.25    0.02     0.24   \n",
       "2018-01-04  601857.SH  8.34  8.79  8.32   8.55       8.27    0.28     3.39   \n",
       "2018-01-05  601857.SH  8.53  8.66  8.48   8.59       8.55    0.04     0.47   \n",
       "2018-01-08  601857.SH  8.56  8.62  8.47   8.53       8.59   -0.06    -0.70   \n",
       "\n",
       "                   vol       amount  \n",
       "trade_date                           \n",
       "2018-01-02   613961.00   504750.225  \n",
       "2018-01-03   474138.35   392423.555  \n",
       "2018-01-04  1522772.62  1301096.070  \n",
       "2018-01-05  1022461.29   875275.600  \n",
       "2018-01-08   641963.46   547507.905  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ZGSY= pro.daily(ts_code='601857.SH', start_date='20180101', end_date='20190630')\n",
    "# pandas有个专门把字符串转为时间格式的函数，to_datetime。第一个参数是原始数据，第二个参数是原始数据的格式\n",
    "df_ZGSY['trade_date'] = pd.to_datetime(df_ZGSY['trade_date'],format='%Y%m%d')\n",
    "# 把trade_date设置为索引\n",
    "df_ZGSY.set_index('trade_date',inplace=True)\n",
    "df_ZGSY=df_ZGSY.sort_index(ascending=True)\n",
    "df_ZGSY.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x1a220c9630>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(df_ZGGH['change'], df_ZGSY['change'], kind='reg', height=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_df(ticker,start,end):\n",
    "    df = pro.daily(ts_code=ticker, start_date=start, end_date=end)\n",
    "    df['trade_date'] = pd.to_datetime(df['trade_date'],format='%Y%m%d')\n",
    "    # 把trade_date设置为索引\n",
    "    df.set_index('trade_date',inplace=True)\n",
    "    df=df.sort_index(ascending=True)\n",
    "    returns=df[\"pct_chg\"].dropna()\n",
    "    returns.name=ticker\n",
    "    return returns\n",
    "\n",
    "series_600029=get_df(\"600029.SH\",\"20180101\",\"20190630\")\n",
    "series_600115=get_df(\"600115.SH\",\"20180101\",\"20190630\")\n",
    "series_600221=get_df(\"600221.SH\",\"20180101\",\"20190630\")\n",
    "series_601021=get_df(\"601021.SH\",\"20180101\",\"20190630\")\n",
    "series_601111=get_df(\"601111.SH\",\"20180101\",\"20190630\")\n",
    "series_603885=get_df(\"603885.SH\",\"20180101\",\"20190630\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>trade_date</th>\n",
       "      <th>2018-01-02 00:00:00</th>\n",
       "      <th>2018-01-03 00:00:00</th>\n",
       "      <th>2018-01-04 00:00:00</th>\n",
       "      <th>2018-01-05 00:00:00</th>\n",
       "      <th>2018-01-08 00:00:00</th>\n",
       "      <th>2018-01-09 00:00:00</th>\n",
       "      <th>2018-01-10 00:00:00</th>\n",
       "      <th>2018-01-11 00:00:00</th>\n",
       "      <th>2018-01-12 00:00:00</th>\n",
       "      <th>2018-01-15 00:00:00</th>\n",
       "      <th>...</th>\n",
       "      <th>2019-06-17 00:00:00</th>\n",
       "      <th>2019-06-18 00:00:00</th>\n",
       "      <th>2019-06-19 00:00:00</th>\n",
       "      <th>2019-06-20 00:00:00</th>\n",
       "      <th>2019-06-21 00:00:00</th>\n",
       "      <th>2019-06-24 00:00:00</th>\n",
       "      <th>2019-06-25 00:00:00</th>\n",
       "      <th>2019-06-26 00:00:00</th>\n",
       "      <th>2019-06-27 00:00:00</th>\n",
       "      <th>2019-06-28 00:00:00</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>600029.SH</th>\n",
       "      <td>-4.36</td>\n",
       "      <td>4.74</td>\n",
       "      <td>-4.44</td>\n",
       "      <td>-2.10</td>\n",
       "      <td>3.85</td>\n",
       "      <td>1.98</td>\n",
       "      <td>-2.96</td>\n",
       "      <td>-1.66</td>\n",
       "      <td>-0.44</td>\n",
       "      <td>0.71</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4231</td>\n",
       "      <td>0.1404</td>\n",
       "      <td>3.0856</td>\n",
       "      <td>3.2653</td>\n",
       "      <td>-0.1318</td>\n",
       "      <td>-0.5277</td>\n",
       "      <td>-1.3263</td>\n",
       "      <td>1.4785</td>\n",
       "      <td>2.5166</td>\n",
       "      <td>-0.2584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600115.SH</th>\n",
       "      <td>-2.07</td>\n",
       "      <td>5.60</td>\n",
       "      <td>-1.88</td>\n",
       "      <td>-0.96</td>\n",
       "      <td>2.06</td>\n",
       "      <td>1.07</td>\n",
       "      <td>-3.76</td>\n",
       "      <td>0.85</td>\n",
       "      <td>-0.97</td>\n",
       "      <td>0.86</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1709</td>\n",
       "      <td>-0.3425</td>\n",
       "      <td>5.1546</td>\n",
       "      <td>3.4314</td>\n",
       "      <td>-0.6319</td>\n",
       "      <td>-0.9539</td>\n",
       "      <td>-1.2841</td>\n",
       "      <td>0.3252</td>\n",
       "      <td>1.9449</td>\n",
       "      <td>-0.3180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600221.SH</th>\n",
       "      <td>0.00</td>\n",
       "      <td>1.57</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.9901</td>\n",
       "      <td>0.4902</td>\n",
       "      <td>-0.4878</td>\n",
       "      <td>-0.4902</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601021.SH</th>\n",
       "      <td>2.47</td>\n",
       "      <td>2.72</td>\n",
       "      <td>-0.33</td>\n",
       "      <td>-0.79</td>\n",
       "      <td>0.72</td>\n",
       "      <td>-3.56</td>\n",
       "      <td>-3.42</td>\n",
       "      <td>-1.02</td>\n",
       "      <td>0.83</td>\n",
       "      <td>-1.60</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.5074</td>\n",
       "      <td>0.1109</td>\n",
       "      <td>0.3765</td>\n",
       "      <td>1.4122</td>\n",
       "      <td>-0.1088</td>\n",
       "      <td>-2.0257</td>\n",
       "      <td>0.0445</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601111.SH</th>\n",
       "      <td>-4.30</td>\n",
       "      <td>8.82</td>\n",
       "      <td>-3.59</td>\n",
       "      <td>-1.54</td>\n",
       "      <td>2.63</td>\n",
       "      <td>-0.40</td>\n",
       "      <td>-2.97</td>\n",
       "      <td>-1.32</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.67</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2291</td>\n",
       "      <td>0.8000</td>\n",
       "      <td>4.5351</td>\n",
       "      <td>3.1453</td>\n",
       "      <td>-0.1052</td>\n",
       "      <td>-0.4211</td>\n",
       "      <td>-0.6342</td>\n",
       "      <td>-0.5319</td>\n",
       "      <td>1.8182</td>\n",
       "      <td>0.5252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603885.SH</th>\n",
       "      <td>0.92</td>\n",
       "      <td>4.99</td>\n",
       "      <td>-1.30</td>\n",
       "      <td>1.13</td>\n",
       "      <td>-2.91</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-3.30</td>\n",
       "      <td>0.26</td>\n",
       "      <td>1.05</td>\n",
       "      <td>-1.62</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4184</td>\n",
       "      <td>2.6667</td>\n",
       "      <td>1.7045</td>\n",
       "      <td>2.5539</td>\n",
       "      <td>1.1673</td>\n",
       "      <td>-0.3077</td>\n",
       "      <td>1.3117</td>\n",
       "      <td>-0.7616</td>\n",
       "      <td>1.5349</td>\n",
       "      <td>-0.9826</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 361 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "trade_date  2018-01-02  2018-01-03  2018-01-04  2018-01-05  2018-01-08  \\\n",
       "600029.SH        -4.36        4.74       -4.44       -2.10        3.85   \n",
       "600115.SH        -2.07        5.60       -1.88       -0.96        2.06   \n",
       "600221.SH         0.00        1.57       -0.93        0.00        1.25   \n",
       "601021.SH         2.47        2.72       -0.33       -0.79        0.72   \n",
       "601111.SH        -4.30        8.82       -3.59       -1.54        2.63   \n",
       "603885.SH         0.92        4.99       -1.30        1.13       -2.91   \n",
       "\n",
       "trade_date  2018-01-09  2018-01-10  2018-01-11  2018-01-12  2018-01-15  \\\n",
       "600029.SH         1.98       -2.96       -1.66       -0.44        0.71   \n",
       "600115.SH         1.07       -3.76        0.85       -0.97        0.86   \n",
       "600221.SH         0.00         NaN         NaN         NaN         NaN   \n",
       "601021.SH        -3.56       -3.42       -1.02        0.83       -1.60   \n",
       "601111.SH        -0.40       -2.97       -1.32        0.42        0.67   \n",
       "603885.SH         0.45       -3.30        0.26        1.05       -1.62   \n",
       "\n",
       "trade_date     ...      2019-06-17  2019-06-18  2019-06-19  2019-06-20  \\\n",
       "600029.SH      ...          0.4231      0.1404      3.0856      3.2653   \n",
       "600115.SH      ...         -0.1709     -0.3425      5.1546      3.4314   \n",
       "600221.SH      ...          0.0000      0.0000      1.0000      0.9901   \n",
       "601021.SH      ...         -0.5074      0.1109      0.3765      1.4122   \n",
       "601111.SH      ...          0.2291      0.8000      4.5351      3.1453   \n",
       "603885.SH      ...          0.4184      2.6667      1.7045      2.5539   \n",
       "\n",
       "trade_date  2019-06-21  2019-06-24  2019-06-25  2019-06-26  2019-06-27  \\\n",
       "600029.SH      -0.1318     -0.5277     -1.3263      1.4785      2.5166   \n",
       "600115.SH      -0.6319     -0.9539     -1.2841      0.3252      1.9449   \n",
       "600221.SH       0.4902     -0.4878     -0.4902      0.0000      0.0000   \n",
       "601021.SH      -0.1088     -2.0257      0.0445      0.0000      0.0000   \n",
       "601111.SH      -0.1052     -0.4211     -0.6342     -0.5319      1.8182   \n",
       "603885.SH       1.1673     -0.3077      1.3117     -0.7616      1.5349   \n",
       "\n",
       "trade_date  2019-06-28  \n",
       "600029.SH      -0.2584  \n",
       "600115.SH      -0.3180  \n",
       "600221.SH       0.0000  \n",
       "601021.SH       0.0000  \n",
       "601111.SH       0.5252  \n",
       "603885.SH      -0.9826  \n",
       "\n",
       "[6 rows x 361 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sector=pd.DataFrame([series_600029,series_600115,series_600221,series_601021,series_601111,series_603885])\n",
    "df_sector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>600029.SH</th>\n",
       "      <th>600115.SH</th>\n",
       "      <th>600221.SH</th>\n",
       "      <th>601021.SH</th>\n",
       "      <th>601111.SH</th>\n",
       "      <th>603885.SH</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>-4.3600</td>\n",
       "      <td>-2.0700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2.4700</td>\n",
       "      <td>-4.3000</td>\n",
       "      <td>0.9200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>4.7400</td>\n",
       "      <td>5.6000</td>\n",
       "      <td>1.5700</td>\n",
       "      <td>2.7200</td>\n",
       "      <td>8.8200</td>\n",
       "      <td>4.9900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>-4.4400</td>\n",
       "      <td>-1.8800</td>\n",
       "      <td>-0.9300</td>\n",
       "      <td>-0.3300</td>\n",
       "      <td>-3.5900</td>\n",
       "      <td>-1.3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>-2.1000</td>\n",
       "      <td>-0.9600</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.7900</td>\n",
       "      <td>-1.5400</td>\n",
       "      <td>1.1300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>3.8500</td>\n",
       "      <td>2.0600</td>\n",
       "      <td>1.2500</td>\n",
       "      <td>0.7200</td>\n",
       "      <td>2.6300</td>\n",
       "      <td>-2.9100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-09</th>\n",
       "      <td>1.9800</td>\n",
       "      <td>1.0700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-3.5600</td>\n",
       "      <td>-0.4000</td>\n",
       "      <td>0.4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-10</th>\n",
       "      <td>-2.9600</td>\n",
       "      <td>-3.7600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-3.4200</td>\n",
       "      <td>-2.9700</td>\n",
       "      <td>-3.3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-11</th>\n",
       "      <td>-1.6600</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.3200</td>\n",
       "      <td>0.2600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-12</th>\n",
       "      <td>-0.4400</td>\n",
       "      <td>-0.9700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.8300</td>\n",
       "      <td>0.4200</td>\n",
       "      <td>1.0500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-15</th>\n",
       "      <td>0.7100</td>\n",
       "      <td>0.8600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.6000</td>\n",
       "      <td>0.6700</td>\n",
       "      <td>-1.6200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-16</th>\n",
       "      <td>-3.6200</td>\n",
       "      <td>-2.4200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-5.0600</td>\n",
       "      <td>-3.9000</td>\n",
       "      <td>-1.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-17</th>\n",
       "      <td>-4.3100</td>\n",
       "      <td>-2.6100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5300</td>\n",
       "      <td>-4.2300</td>\n",
       "      <td>-0.3300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-18</th>\n",
       "      <td>1.1500</td>\n",
       "      <td>-0.5100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.4700</td>\n",
       "      <td>-0.4500</td>\n",
       "      <td>-0.8000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-19</th>\n",
       "      <td>0.1900</td>\n",
       "      <td>0.7700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.3500</td>\n",
       "      <td>2.0800</td>\n",
       "      <td>1.1500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-22</th>\n",
       "      <td>0.7600</td>\n",
       "      <td>2.0400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.1200</td>\n",
       "      <td>2.7500</td>\n",
       "      <td>3.2600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-23</th>\n",
       "      <td>-0.9400</td>\n",
       "      <td>-0.6200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.2600</td>\n",
       "      <td>-0.6000</td>\n",
       "      <td>-0.4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-24</th>\n",
       "      <td>0.1900</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0900</td>\n",
       "      <td>1.8200</td>\n",
       "      <td>1.1700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-25</th>\n",
       "      <td>3.3100</td>\n",
       "      <td>3.5000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.9200</td>\n",
       "      <td>5.7200</td>\n",
       "      <td>2.7500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-26</th>\n",
       "      <td>4.3900</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.6900</td>\n",
       "      <td>6.0500</td>\n",
       "      <td>-0.0600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-29</th>\n",
       "      <td>0.3500</td>\n",
       "      <td>0.8400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.7500</td>\n",
       "      <td>0.6100</td>\n",
       "      <td>-0.3100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-30</th>\n",
       "      <td>2.7900</td>\n",
       "      <td>1.1900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.6800</td>\n",
       "      <td>-1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-31</th>\n",
       "      <td>0.0000</td>\n",
       "      <td>-1.4200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.5200</td>\n",
       "      <td>-0.8300</td>\n",
       "      <td>0.3800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-01</th>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.8000</td>\n",
       "      <td>3.6400</td>\n",
       "      <td>-0.1900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-02</th>\n",
       "      <td>-1.0900</td>\n",
       "      <td>-3.0700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.1600</td>\n",
       "      <td>-0.5100</td>\n",
       "      <td>0.1900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-05</th>\n",
       "      <td>8.2100</td>\n",
       "      <td>4.5000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.1100</td>\n",
       "      <td>3.5300</td>\n",
       "      <td>2.2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-06</th>\n",
       "      <td>-2.5800</td>\n",
       "      <td>-0.3500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-4.6500</td>\n",
       "      <td>-3.1900</td>\n",
       "      <td>-1.1100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-07</th>\n",
       "      <td>-5.1400</td>\n",
       "      <td>-3.6200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.1200</td>\n",
       "      <td>-6.6700</td>\n",
       "      <td>-1.7400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-08</th>\n",
       "      <td>-2.8800</td>\n",
       "      <td>-2.6700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-2.3600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>-1.4600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-09</th>\n",
       "      <td>-5.7500</td>\n",
       "      <td>-7.7200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-5.3700</td>\n",
       "      <td>-5.2500</td>\n",
       "      <td>-9.4600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-12</th>\n",
       "      <td>3.2300</td>\n",
       "      <td>1.7500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.5900</td>\n",
       "      <td>3.8900</td>\n",
       "      <td>4.6900</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-17</th>\n",
       "      <td>-3.6437</td>\n",
       "      <td>-4.4944</td>\n",
       "      <td>-1.9324</td>\n",
       "      <td>-3.1308</td>\n",
       "      <td>-4.6016</td>\n",
       "      <td>-3.3038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-20</th>\n",
       "      <td>-0.9804</td>\n",
       "      <td>-1.1765</td>\n",
       "      <td>-0.9852</td>\n",
       "      <td>-0.6030</td>\n",
       "      <td>-1.8824</td>\n",
       "      <td>-2.2500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-21</th>\n",
       "      <td>1.5559</td>\n",
       "      <td>0.6803</td>\n",
       "      <td>0.9950</td>\n",
       "      <td>1.9655</td>\n",
       "      <td>1.1990</td>\n",
       "      <td>1.1935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-22</th>\n",
       "      <td>0.1393</td>\n",
       "      <td>1.5203</td>\n",
       "      <td>2.4631</td>\n",
       "      <td>1.8087</td>\n",
       "      <td>0.7109</td>\n",
       "      <td>1.4322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-23</th>\n",
       "      <td>-2.2253</td>\n",
       "      <td>-1.4975</td>\n",
       "      <td>-3.3654</td>\n",
       "      <td>-2.7115</td>\n",
       "      <td>-2.8235</td>\n",
       "      <td>-0.6645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-24</th>\n",
       "      <td>1.7070</td>\n",
       "      <td>1.3514</td>\n",
       "      <td>0.4975</td>\n",
       "      <td>1.4486</td>\n",
       "      <td>1.2107</td>\n",
       "      <td>1.3378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-27</th>\n",
       "      <td>1.9580</td>\n",
       "      <td>1.6667</td>\n",
       "      <td>1.4851</td>\n",
       "      <td>1.4993</td>\n",
       "      <td>2.1531</td>\n",
       "      <td>2.9703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-28</th>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.6557</td>\n",
       "      <td>-0.9756</td>\n",
       "      <td>2.5088</td>\n",
       "      <td>-0.2342</td>\n",
       "      <td>0.1603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-29</th>\n",
       "      <td>-1.0974</td>\n",
       "      <td>-0.9772</td>\n",
       "      <td>-0.4926</td>\n",
       "      <td>-0.9607</td>\n",
       "      <td>-0.2347</td>\n",
       "      <td>-0.3200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-30</th>\n",
       "      <td>-0.8322</td>\n",
       "      <td>-1.4803</td>\n",
       "      <td>-0.4950</td>\n",
       "      <td>1.3395</td>\n",
       "      <td>-0.9412</td>\n",
       "      <td>-1.4446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-31</th>\n",
       "      <td>0.5594</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.4102</td>\n",
       "      <td>0.4751</td>\n",
       "      <td>1.5472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-03</th>\n",
       "      <td>1.6690</td>\n",
       "      <td>1.6694</td>\n",
       "      <td>0.4975</td>\n",
       "      <td>0.5492</td>\n",
       "      <td>4.1371</td>\n",
       "      <td>0.3208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-04</th>\n",
       "      <td>-1.6416</td>\n",
       "      <td>-1.6420</td>\n",
       "      <td>-0.9901</td>\n",
       "      <td>-0.6600</td>\n",
       "      <td>-0.1135</td>\n",
       "      <td>-1.5987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-05</th>\n",
       "      <td>0.1391</td>\n",
       "      <td>-0.1669</td>\n",
       "      <td>-0.5000</td>\n",
       "      <td>-0.5727</td>\n",
       "      <td>0.6818</td>\n",
       "      <td>-1.7059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-06</th>\n",
       "      <td>-1.9444</td>\n",
       "      <td>-2.0067</td>\n",
       "      <td>-0.5025</td>\n",
       "      <td>-0.9217</td>\n",
       "      <td>-1.8059</td>\n",
       "      <td>-1.0744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-10</th>\n",
       "      <td>-1.1331</td>\n",
       "      <td>-1.5358</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.8372</td>\n",
       "      <td>-1.1494</td>\n",
       "      <td>-0.9190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-11</th>\n",
       "      <td>3.8682</td>\n",
       "      <td>3.9861</td>\n",
       "      <td>2.5253</td>\n",
       "      <td>4.6670</td>\n",
       "      <td>4.5349</td>\n",
       "      <td>3.2040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-12</th>\n",
       "      <td>-0.2759</td>\n",
       "      <td>-0.5000</td>\n",
       "      <td>-0.9852</td>\n",
       "      <td>-0.4705</td>\n",
       "      <td>0.3337</td>\n",
       "      <td>-0.8170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-13</th>\n",
       "      <td>-0.6916</td>\n",
       "      <td>-0.3350</td>\n",
       "      <td>1.4925</td>\n",
       "      <td>-0.7429</td>\n",
       "      <td>-1.7738</td>\n",
       "      <td>0.1647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-14</th>\n",
       "      <td>-1.2535</td>\n",
       "      <td>-1.6807</td>\n",
       "      <td>-1.9608</td>\n",
       "      <td>2.8124</td>\n",
       "      <td>-1.4673</td>\n",
       "      <td>-1.7270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-17</th>\n",
       "      <td>0.4231</td>\n",
       "      <td>-0.1709</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.5074</td>\n",
       "      <td>0.2291</td>\n",
       "      <td>0.4184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-18</th>\n",
       "      <td>0.1404</td>\n",
       "      <td>-0.3425</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.1109</td>\n",
       "      <td>0.8000</td>\n",
       "      <td>2.6667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-19</th>\n",
       "      <td>3.0856</td>\n",
       "      <td>5.1546</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.3765</td>\n",
       "      <td>4.5351</td>\n",
       "      <td>1.7045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-20</th>\n",
       "      <td>3.2653</td>\n",
       "      <td>3.4314</td>\n",
       "      <td>0.9901</td>\n",
       "      <td>1.4122</td>\n",
       "      <td>3.1453</td>\n",
       "      <td>2.5539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-21</th>\n",
       "      <td>-0.1318</td>\n",
       "      <td>-0.6319</td>\n",
       "      <td>0.4902</td>\n",
       "      <td>-0.1088</td>\n",
       "      <td>-0.1052</td>\n",
       "      <td>1.1673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-24</th>\n",
       "      <td>-0.5277</td>\n",
       "      <td>-0.9539</td>\n",
       "      <td>-0.4878</td>\n",
       "      <td>-2.0257</td>\n",
       "      <td>-0.4211</td>\n",
       "      <td>-0.3077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-25</th>\n",
       "      <td>-1.3263</td>\n",
       "      <td>-1.2841</td>\n",
       "      <td>-0.4902</td>\n",
       "      <td>0.0445</td>\n",
       "      <td>-0.6342</td>\n",
       "      <td>1.3117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-26</th>\n",
       "      <td>1.4785</td>\n",
       "      <td>0.3252</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.5319</td>\n",
       "      <td>-0.7616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-27</th>\n",
       "      <td>2.5166</td>\n",
       "      <td>1.9449</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.8182</td>\n",
       "      <td>1.5349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-28</th>\n",
       "      <td>-0.2584</td>\n",
       "      <td>-0.3180</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.5252</td>\n",
       "      <td>-0.9826</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>361 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            600029.SH  600115.SH  600221.SH  601021.SH  601111.SH  603885.SH\n",
       "trade_date                                                                  \n",
       "2018-01-02    -4.3600    -2.0700     0.0000     2.4700    -4.3000     0.9200\n",
       "2018-01-03     4.7400     5.6000     1.5700     2.7200     8.8200     4.9900\n",
       "2018-01-04    -4.4400    -1.8800    -0.9300    -0.3300    -3.5900    -1.3000\n",
       "2018-01-05    -2.1000    -0.9600     0.0000    -0.7900    -1.5400     1.1300\n",
       "2018-01-08     3.8500     2.0600     1.2500     0.7200     2.6300    -2.9100\n",
       "2018-01-09     1.9800     1.0700     0.0000    -3.5600    -0.4000     0.4500\n",
       "2018-01-10    -2.9600    -3.7600        NaN    -3.4200    -2.9700    -3.3000\n",
       "2018-01-11    -1.6600     0.8500        NaN    -1.0200    -1.3200     0.2600\n",
       "2018-01-12    -0.4400    -0.9700        NaN     0.8300     0.4200     1.0500\n",
       "2018-01-15     0.7100     0.8600        NaN    -1.6000     0.6700    -1.6200\n",
       "2018-01-16    -3.6200    -2.4200        NaN    -5.0600    -3.9000    -1.2500\n",
       "2018-01-17    -4.3100    -2.6100        NaN     0.5300    -4.2300    -0.3300\n",
       "2018-01-18     1.1500    -0.5100        NaN     1.4700    -0.4500    -0.8000\n",
       "2018-01-19     0.1900     0.7700        NaN    -0.3500     2.0800     1.1500\n",
       "2018-01-22     0.7600     2.0400        NaN     2.1200     2.7500     3.2600\n",
       "2018-01-23    -0.9400    -0.6200        NaN     0.2600    -0.6000    -0.4500\n",
       "2018-01-24     0.1900     0.5000        NaN    -0.0900     1.8200     1.1700\n",
       "2018-01-25     3.3100     3.5000        NaN     2.9200     5.7200     2.7500\n",
       "2018-01-26     4.3900     0.1200        NaN    -0.6900     6.0500    -0.0600\n",
       "2018-01-29     0.3500     0.8400        NaN    -1.7500     0.6100    -0.3100\n",
       "2018-01-30     2.7900     1.1900        NaN     0.1400     0.6800    -1.0000\n",
       "2018-01-31     0.0000    -1.4200        NaN    -1.5200    -0.8300     0.3800\n",
       "2018-02-01     1.5300     1.5600        NaN     0.8000     3.6400    -0.1900\n",
       "2018-02-02    -1.0900    -3.0700        NaN     1.1600    -0.5100     0.1900\n",
       "2018-02-05     8.2100     4.5000        NaN     2.1100     3.5300     2.2000\n",
       "2018-02-06    -2.5800    -0.3500        NaN    -4.6500    -3.1900    -1.1100\n",
       "2018-02-07    -5.1400    -3.6200        NaN    -1.1200    -6.6700    -1.7400\n",
       "2018-02-08    -2.8800    -2.6700        NaN    -2.3600     0.1600    -1.4600\n",
       "2018-02-09    -5.7500    -7.7200        NaN    -5.3700    -5.2500    -9.4600\n",
       "2018-02-12     3.2300     1.7500        NaN     2.5900     3.8900     4.6900\n",
       "...               ...        ...        ...        ...        ...        ...\n",
       "2019-05-17    -3.6437    -4.4944    -1.9324    -3.1308    -4.6016    -3.3038\n",
       "2019-05-20    -0.9804    -1.1765    -0.9852    -0.6030    -1.8824    -2.2500\n",
       "2019-05-21     1.5559     0.6803     0.9950     1.9655     1.1990     1.1935\n",
       "2019-05-22     0.1393     1.5203     2.4631     1.8087     0.7109     1.4322\n",
       "2019-05-23    -2.2253    -1.4975    -3.3654    -2.7115    -2.8235    -0.6645\n",
       "2019-05-24     1.7070     1.3514     0.4975     1.4486     1.2107     1.3378\n",
       "2019-05-27     1.9580     1.6667     1.4851     1.4993     2.1531     2.9703\n",
       "2019-05-28     0.0000     0.6557    -0.9756     2.5088    -0.2342     0.1603\n",
       "2019-05-29    -1.0974    -0.9772    -0.4926    -0.9607    -0.2347    -0.3200\n",
       "2019-05-30    -0.8322    -1.4803    -0.4950     1.3395    -0.9412    -1.4446\n",
       "2019-05-31     0.5594     0.0000     0.0000    -0.4102     0.4751     1.5472\n",
       "2019-06-03     1.6690     1.6694     0.4975     0.5492     4.1371     0.3208\n",
       "2019-06-04    -1.6416    -1.6420    -0.9901    -0.6600    -0.1135    -1.5987\n",
       "2019-06-05     0.1391    -0.1669    -0.5000    -0.5727     0.6818    -1.7059\n",
       "2019-06-06    -1.9444    -2.0067    -0.5025    -0.9217    -1.8059    -1.0744\n",
       "2019-06-10    -1.1331    -1.5358     0.0000    -0.8372    -1.1494    -0.9190\n",
       "2019-06-11     3.8682     3.9861     2.5253     4.6670     4.5349     3.2040\n",
       "2019-06-12    -0.2759    -0.5000    -0.9852    -0.4705     0.3337    -0.8170\n",
       "2019-06-13    -0.6916    -0.3350     1.4925    -0.7429    -1.7738     0.1647\n",
       "2019-06-14    -1.2535    -1.6807    -1.9608     2.8124    -1.4673    -1.7270\n",
       "2019-06-17     0.4231    -0.1709     0.0000    -0.5074     0.2291     0.4184\n",
       "2019-06-18     0.1404    -0.3425     0.0000     0.1109     0.8000     2.6667\n",
       "2019-06-19     3.0856     5.1546     1.0000     0.3765     4.5351     1.7045\n",
       "2019-06-20     3.2653     3.4314     0.9901     1.4122     3.1453     2.5539\n",
       "2019-06-21    -0.1318    -0.6319     0.4902    -0.1088    -0.1052     1.1673\n",
       "2019-06-24    -0.5277    -0.9539    -0.4878    -2.0257    -0.4211    -0.3077\n",
       "2019-06-25    -1.3263    -1.2841    -0.4902     0.0445    -0.6342     1.3117\n",
       "2019-06-26     1.4785     0.3252     0.0000     0.0000    -0.5319    -0.7616\n",
       "2019-06-27     2.5166     1.9449     0.0000     0.0000     1.8182     1.5349\n",
       "2019-06-28    -0.2584    -0.3180     0.0000     0.0000     0.5252    -0.9826\n",
       "\n",
       "[361 rows x 6 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sector=df_sector.T\n",
    "\n",
    "df_sector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yons/anaconda3/lib/python3.7/site-packages/statsmodels/nonparametric/kde.py:448: RuntimeWarning: invalid value encountered in greater\n",
      "  X = X[np.logical_and(X > clip[0], X < clip[1])] # won't work for two columns.\n",
      "/Users/yons/anaconda3/lib/python3.7/site-packages/statsmodels/nonparametric/kde.py:448: RuntimeWarning: invalid value encountered in less\n",
      "  X = X[np.logical_and(X > clip[0], X < clip[1])] # won't work for two columns.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1a24e031d0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 42 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df_sector, diag_kind='kde', height=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a22746048>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(df_sector,size=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}