init

data/走势.csv

@@ -0,0 +1,55 @@
+地区,时间,地区生产总值,第一产业增加值,第二产业增加值,工业,第二产业增加值,人均生产总值,地区生产总值增速,第一产业增加值增速,第二产业增加值增速,工业增速,第二产业增加值增速,人均生产总值增速
+   贵 阳 市,2015/12/31,2891.16,129.89,1108.52,714.15,1652.75,63003,12.5,6.4,14.6,10.2,11.1,11.3
+   六盘水市,2015/12/31,1201.08,114.51,614.14,528.27,472.43,41618,12.1,6.9,12.1,10.9,12.9,11.8
+   遵 义 市,2015/12/31,2168.34,349.27,970.75,799.82,848.32,35123,13.2,6.8,13.7,12.2,14.1,12.7
+   安 顺 市,2015/12/31,625.41,113.10,207.62,159.66,304.69,27065,13.6,6.5,13.8,11.8,15.2,13.3
+   毕 节 市,2015/12/31,1461.35,324.71,566.56,453.10,570.07,22230,12.9,6.9,12.6,11.7,15.5,12.3
+   铜 仁 市,2015/12/31,770.89,191.10,221.21,160.55,358.59,24712,12.7,6.7,13.8,12.2,14.9,12.4
+   黔西南州,2015/12/31,801.65,159.97,273.29,223.92,368.39,28464,13.6,6.5,13.3,11.8,15.6,13.6
+   黔东南州,2015/12/31,811.55,163.48,232.38,161.66,415.69,23311,13.1,6.4,10.5,11.4,17.0,13.0
+   黔 南 州,2015/12/31,902.91,158.31,327.87,247.16,416.73,27888,13.3,6.5,12.5,12.3,16.4,13.2
+   贵 阳 市,2016/12/31,3157.70,137.14,1218.79,771.33,1801.77,67772,11.7,5.9,12.1,9.9,11.9,10.1
+   六盘水市,2016/12/31,1313.70,125.49,660.00,563.42,528.21,45325,12.0,6.3,10.9,9.8,14.7,11.5
+   遵 义 市,2016/12/31,2403.94,370.48,1063.00,867.86,970.46,38709,12.4,5.7,12.8,11.7,14.5,11.7
+   安 顺 市,2016/12/31,701.35,124.07,227.12,172.24,350.16,30216,12.4,6.3,12.5,11.1,14.5,11.9
+   毕 节 市,2016/12/31,1625.79,344.43,617.87,488.60,663.49,24544,12.1,6.0,12.0,11.1,15.2,11.2
+   铜 仁 市,2016/12/31,856.97,202.70,243.41,174.04,410.86,27366,11.9,5.8,13.1,11.6,14.2,11.4
+   黔西南州,2016/12/31,929.14,188.84,298.31,241.68,441.99,32833,13.3,6.2,12.3,11.2,17.2,12.8
+   黔东南州,2016/12/31,939.05,184.11,261.36,180.74,493.58,26858,13.3,6.1,12.9,11.3,16.3,12.9
+   黔 南 州,2016/12/31,1023.39,183.36,359.47,267.31,480.56,31472,12.5,6.4,12.7,11.4,14.6,12.0
+   贵 阳 市,2017/12/31,3537.96,147.33,1375.18,872.57,2015.45,74493,11.3,6.3,10.0,9.5,12.6,9.2
+   六盘水市,2017/12/31,1461.71,134.82,729.38,617.86,597.51,50136,11.1,6.6,10.7,10.1,12.4,10.4
+   遵 义 市,2017/12/31,2748.59,402.34,1241.05,1016.14,1105.20,44060,12.1,6.8,11.9,11.5,14.3,11.6
+   安 顺 市,2017/12/31,802.46,135.70,267.82,203.75,398.94,34345,12.3,6.7,12.1,11.6,14.2,11.5
+   毕 节 市,2017/12/31,1841.61,378.61,692.19,545.95,770.81,27690,11.7,6.8,10.1,9.3,15.6,11.3
+   铜 仁 市,2017/12/31,969.86,219.73,277.53,196.01,472.60,30801,11.5,6.6,11.8,10.6,13.6,10.9
+   黔西南州,2017/12/31,1067.60,204.08,340.68,273.92,522.84,37471,12.5,6.6,10.7,9.7,16.2,11.8
+   黔东南州,2017/12/31,972.18,195.87,224.11,141.88,552.20,27654,5.2,6.4,-0.8,1.7,8.1,4.7
+   黔 南 州,2017/12/31,1160.59,202.30,412.91,306.47,545.38,35481,12.1,6.6,11.5,10.7,14.5,11.4
+   贵 阳 市,2018/12/31,3798.45,153.10,1413.67,874.96,2231.68,78449,9.9,6.6,7.9,7.5,11.3,7.8
+   六盘水市,2018/12/31,1525.69,147.95,741.97,621.09,635.77,52059,8.8,6.9,8.1,7.6,10.0,8.2
+   遵 义 市,2018/12/31,3000.23,411.36,1374.16,1110.82,1214.71,47931,10.4,6.7,11.9,12.0,10.1,10.1
+   安 顺 市,2018/12/31,849.40,149.16,272.83,204.42,427.41,36164,10.3,6.9,10.4,11.1,11.4,9.8
+   毕 节 市,2018/12/31,1921.43,414.76,697.03,547.84,809.64,28794,10.2,6.9,9.3,10.3,12.5,9.9
+   铜 仁 市,2018/12/31,1066.52,242.51,301.55,204.81,522.46,33720,9.6,6.9,7.1,5.2,12.3,9.1
+   黔西南州,2018/12/31,1163.77,212.92,375.80,295.83,575.05,40608,12.0,6.9,11.5,11.1,14.3,11.4
+   黔东南州,2018/12/31,1036.62,211.31,231.59,142.48,593.72,29358,7.9,6.8,7.0,9.0,8.7,7.4
+   黔 南 州,2018/12/31,1313.46,216.56,468.25,343.71,628.65,39965,10.8,6.9,10.2,10.2,12.6,10.3
+   贵 阳 市,2019/12/31,4039.60 ,161.34 ,1495.41 ,869.00 ,2382.85 ,81995 ,7.4,5.6,8.2,6.5,7.0,5.6
+   六盘水市,2019/12/31,1265.97 ,154.76 ,582.43 ,512.24 ,528.78 ,43003 ,7.5,5.7,8.7,9.0,6.6,7.0
+   遵 义 市,2019/12/31,3483.32 ,431.87 ,1592.79 ,1417.48 ,1458.66 ,55411 ,9.7,5.5,12.3,12.4,8.0,9.2
+   安 顺 市,2019/12/31,923.94 ,157.19 ,292.14 ,232.12 ,474.61 ,39177 ,8.1,5.7,9.6,10.9,7.8,7.6
+   毕 节 市,2019/12/31,1901.36 ,439.36 ,520.67 ,403.55 ,941.33 ,28378 ,8.0,5.7,6.8,5.9,9.9,7.5
+   铜 仁 市,2019/12/31,1249.16 ,254.89 ,325.87 ,216.23 ,668.40 ,39298 ,8.0,5.9,7.0,5.2,9.6,7.5
+   黔西南州,2019/12/31,1272.80 ,226.88 ,444.58 ,330.12 ,601.34 ,44212 ,9.8,6.0,12.1,11.7,9.5,9.3
+   黔东南州,2019/12/31,1123.04 ,223.73 ,253.74 ,139.69 ,645.57 ,31678 ,8.4,5.7,8.1,6.2,9.5,7.9
+   黔 南 州,2019/12/31,1518.04 ,230.54 ,554.38 ,429.08 ,733.12 ,46048 ,7.9,5.5,10.4,10.8,6.7,7.6
+   贵 阳 市,2020/12/31,4311.65 ,178.31 ,1552.59 ,883.68 ,2580.75 ,72246 ,5.0 ,6.4 ,5.5 ,4.5 ,4.4 ,3.6 
+   六盘水市,2020/12/31,1339.62 ,170.79 ,599.99 ,522.47 ,568.84 ,44224 ,4.5 ,5.9 ,4.4 ,3.6 ,4.3 ,4.2 
+   遵 义 市,2020/12/31,3720.05 ,489.62 ,1615.60 ,1441.43 ,1614.83 ,56334 ,4.6 ,6.2 ,4.2 ,4.8 ,4.7 ,4.3 
+   安 顺 市,2020/12/31,966.74 ,176.33 ,292.60 ,227.41 ,497.81 ,39160 ,3.1 ,6.4 ,2.8 ,1.4 ,2.1 ,2.7 
+   毕 节 市,2020/12/31,2020.39 ,486.55 ,533.45 ,404.96 ,1000.39 ,29295 ,4.4 ,6.3 ,3.8 ,2.2 ,3.9 ,4.2 
+   铜 仁 市,2020/12/31,1327.79 ,289.39 ,332.58 ,215.72 ,705.82 ,40269 ,4.4 ,6.7 ,3.2 ,1.5 ,4.0 ,4.0 
+   黔西南州,2020/12/31,1353.40 ,249.35 ,462.99 ,337.70 ,641.06 ,44881 ,4.7 ,6.5 ,5.3 ,4.1 ,3.5 ,4.5 
+   黔东南州,2020/12/31,1191.52 ,244.81 ,258.53 ,140.07 ,688.18 ,31719 ,4.5 ,6.3 ,3.3 ,2.8 ,4.4 ,4.2 
+   黔 南 州,2020/12/31,1595.40 ,254.73 ,563.29 ,429.24 ,777.38 ,45654 ,4.0 ,6.5 ,4.3 ,3.5 ,2.9 ,3.7 

gdp2.ipynb

@@ -0,0 +1,243 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "218af1ec",
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\")\n",
+    "import pandas  as  pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import  json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "33e62663",
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签SimHei\n",
+    "plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "df=pd.read_excel('./input/gdphb.xlsx')\n",
+    "\n",
+    "display(df)\n",
+    "# df=df[df[\"地区\"].str.strip()==\"安顺市\"]\n",
+    "def minmax_norm(df_input):\n",
+    "    return (df_input - df_input.min()) / (df_input.max() - df_input.min()) * 40 + 60\n",
+    "global_df_arr=[]; #用来装需要预测的df数组\n",
+    "global_corr_obj= {};#地区各指标相关数组\n",
+    "for  s  in   df[\"地区\"].unique():\n",
+    "    #print(s)\n",
+    "    new_df=df[df[\"地区\"].str.strip()==s ]\n",
+    "    # print(new_df.columns)\n",
+    "    norm_df_input=new_df.drop(columns=['地区', 'ds']);\n",
+    "    # print(norm_df_input.dtypes)\n",
+    "    norm_df=  minmax_norm(norm_df_input);\n",
+    "\n",
+    "    corr= norm_df.corr()\n",
+    "    # print(s+\"地区指标相关性\")\n",
+    "    # display(corr)\n",
+    "    result = corr.to_json(orient=\"index\")\n",
+    "        # print(result)\n",
+    "    parsed_corr = json.loads(result.replace(\":null\",\":\\\"NaN\\\"\"))\n",
+    "    global_corr_obj[s]=parsed_corr;\n",
+    "\n",
+    "    # continue\n",
+    "    for s_index  in  new_df.columns:\n",
+    "        if s_index not in ['地区', 'ds', 'y'] :\n",
+    "        #if sindex not in ['地区', 'ds', 'y'] and  \"增速\" not  in  sindex:\n",
+    "            sdf=new_df.loc[:,['地区', 'ds']]\n",
+    "            sdf['y']=df[s_index]\n",
+    "            sdf['title-text']=s_index\n",
+    "            sdf= sdf.reset_index(drop=True)\n",
+    "            sdf=sdf.dropna()\n",
+    "           #print(sdf)\n",
+    "            global_df_arr.append(sdf)\n",
+    "# print(df_arr)\n",
+    "#global_df_arr\n",
+    "\n",
+    "# display(global_corr_obj)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "# global_df_arr"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "# print(\"各指标的相关性\")\n",
+    "# df.corr()"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "# m = Prophet(changepoints=['2020-12-01'])  #2020是个例外\n",
+    "from prophet import Prophet\n",
+    "from prophet.plot import plot_plotly, plot_components_plotly\n",
+    "def show_prophet(dfs):\n",
+    "    json_arr=[];\n",
+    "    for mdf in  dfs:\n",
+    "        # m = Prophet(changepoints=['2020-12-01'])\n",
+    "        m = Prophet(changepoints=['2020-12-01'])\n",
+    "        m.fit(mdf)\n",
+    "        future = m.make_future_dataframe(periods=2,freq=\"Y\")\n",
+    "        # print(future,m)\n",
+    "        forecast = m.predict(future)\n",
+    "        # forecast['y']=mdf.loc[:,['y']]\n",
+    "        forecast= pd.concat([forecast,mdf.loc[:,'y']],axis=1)\n",
+    "        # print(forecast.to_json(orient ='index'))\n",
+    "        title= mdf[\"title-text\"][mdf.index[0]]\n",
+    "        地区=mdf[\"地区\"][mdf.index[0]]\n",
+    "        print(地区+title+\"回归分析\")\n",
+    "        fig=plot_plotly(m, forecast,xlabel=\"时间\",ylabel=title,)\n",
+    "        fig.show()\n",
+    "        result = forecast.to_json(orient=\"index\")\n",
+    "        # print(result)\n",
+    "        parsed = json.loads(result.replace(\":null\",\":\\\"NaN\\\"\"))\n",
+    "        #data_obj=json.load(forecast.to_json(orient ='index'))\n",
+    "\n",
+    "        json_obj={\"axis\":地区,\"info\":title,\"data\": parsed }\n",
+    "        json_arr.append(json_obj)\n",
+    "        # print(json_obj )\n",
+    "        # print(title+\"趋势分析图\")\n",
+    "        # fig.show()\n",
+    "\n",
+    "    return  json_arr\n",
+    "res=show_prophet(global_df_arr[:])\n",
+    "# print(res)\n"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "print(res)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ca17354e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fdf21f14-a2e5-4ee6-94fd-10dda9900f42",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "c09ee517baf2ef8cdccf4daa50b9eecbe95ad60e1eec620e80956ae2b91f8870"
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

input/gdp.csv

@@ -0,0 +1,55 @@
+地区,时间,地区生产总值,第一产业增加值,第二产业增加值,工业,第二产业增加值,人均生产总值,地区生产总值增速,第一产业增加值增速,第二产业增加值增速,工业增速,第二产业增加值增速,人均生产总值增速
+   贵 阳 市,2015/12/31,2891.16,129.89,1108.52,714.15,1652.75,63003,12.5,6.4,14.6,10.2,11.1,11.3
+   六盘水市,2015/12/31,1201.08,114.51,614.14,528.27,472.43,41618,12.1,6.9,12.1,10.9,12.9,11.8
+   遵 义 市,2015/12/31,2168.34,349.27,970.75,799.82,848.32,35123,13.2,6.8,13.7,12.2,14.1,12.7
+   安 顺 市,2015/12/31,625.41,113.10,207.62,159.66,304.69,27065,13.6,6.5,13.8,11.8,15.2,13.3
+   毕 节 市,2015/12/31,1461.35,324.71,566.56,453.10,570.07,22230,12.9,6.9,12.6,11.7,15.5,12.3
+   铜 仁 市,2015/12/31,770.89,191.10,221.21,160.55,358.59,24712,12.7,6.7,13.8,12.2,14.9,12.4
+   黔西南州,2015/12/31,801.65,159.97,273.29,223.92,368.39,28464,13.6,6.5,13.3,11.8,15.6,13.6
+   黔东南州,2015/12/31,811.55,163.48,232.38,161.66,415.69,23311,13.1,6.4,10.5,11.4,17.0,13.0
+   黔 南 州,2015/12/31,902.91,158.31,327.87,247.16,416.73,27888,13.3,6.5,12.5,12.3,16.4,13.2
+   贵 阳 市,2016/12/31,3157.70,137.14,1218.79,771.33,1801.77,67772,11.7,5.9,12.1,9.9,11.9,10.1
+   六盘水市,2016/12/31,1313.70,125.49,660.00,563.42,528.21,45325,12.0,6.3,10.9,9.8,14.7,11.5
+   遵 义 市,2016/12/31,2403.94,370.48,1063.00,867.86,970.46,38709,12.4,5.7,12.8,11.7,14.5,11.7
+   安 顺 市,2016/12/31,701.35,124.07,227.12,172.24,350.16,30216,12.4,6.3,12.5,11.1,14.5,11.9
+   毕 节 市,2016/12/31,1625.79,344.43,617.87,488.60,663.49,24544,12.1,6.0,12.0,11.1,15.2,11.2
+   铜 仁 市,2016/12/31,856.97,202.70,243.41,174.04,410.86,27366,11.9,5.8,13.1,11.6,14.2,11.4
+   黔西南州,2016/12/31,929.14,188.84,298.31,241.68,441.99,32833,13.3,6.2,12.3,11.2,17.2,12.8
+   黔东南州,2016/12/31,939.05,184.11,261.36,180.74,493.58,26858,13.3,6.1,12.9,11.3,16.3,12.9
+   黔 南 州,2016/12/31,1023.39,183.36,359.47,267.31,480.56,31472,12.5,6.4,12.7,11.4,14.6,12.0
+   贵 阳 市,2017/12/31,3537.96,147.33,1375.18,872.57,2015.45,74493,11.3,6.3,10.0,9.5,12.6,9.2
+   六盘水市,2017/12/31,1461.71,134.82,729.38,617.86,597.51,50136,11.1,6.6,10.7,10.1,12.4,10.4
+   遵 义 市,2017/12/31,2748.59,402.34,1241.05,1016.14,1105.20,44060,12.1,6.8,11.9,11.5,14.3,11.6
+   安 顺 市,2017/12/31,802.46,135.70,267.82,203.75,398.94,34345,12.3,6.7,12.1,11.6,14.2,11.5
+   毕 节 市,2017/12/31,1841.61,378.61,692.19,545.95,770.81,27690,11.7,6.8,10.1,9.3,15.6,11.3
+   铜 仁 市,2017/12/31,969.86,219.73,277.53,196.01,472.60,30801,11.5,6.6,11.8,10.6,13.6,10.9
+   黔西南州,2017/12/31,1067.60,204.08,340.68,273.92,522.84,37471,12.5,6.6,10.7,9.7,16.2,11.8
+   黔东南州,2017/12/31,972.18,195.87,224.11,141.88,552.20,27654,5.2,6.4,-0.8,1.7,8.1,4.7
+   黔 南 州,2017/12/31,1160.59,202.30,412.91,306.47,545.38,35481,12.1,6.6,11.5,10.7,14.5,11.4
+   贵 阳 市,2018/12/31,3798.45,153.10,1413.67,874.96,2231.68,78449,9.9,6.6,7.9,7.5,11.3,7.8
+   六盘水市,2018/12/31,1525.69,147.95,741.97,621.09,635.77,52059,8.8,6.9,8.1,7.6,10.0,8.2
+   遵 义 市,2018/12/31,3000.23,411.36,1374.16,1110.82,1214.71,47931,10.4,6.7,11.9,12.0,10.1,10.1
+   安 顺 市,2018/12/31,849.40,149.16,272.83,204.42,427.41,36164,10.3,6.9,10.4,11.1,11.4,9.8
+   毕 节 市,2018/12/31,1921.43,414.76,697.03,547.84,809.64,28794,10.2,6.9,9.3,10.3,12.5,9.9
+   铜 仁 市,2018/12/31,1066.52,242.51,301.55,204.81,522.46,33720,9.6,6.9,7.1,5.2,12.3,9.1
+   黔西南州,2018/12/31,1163.77,212.92,375.80,295.83,575.05,40608,12.0,6.9,11.5,11.1,14.3,11.4
+   黔东南州,2018/12/31,1036.62,211.31,231.59,142.48,593.72,29358,7.9,6.8,7.0,9.0,8.7,7.4
+   黔 南 州,2018/12/31,1313.46,216.56,468.25,343.71,628.65,39965,10.8,6.9,10.2,10.2,12.6,10.3
+   贵 阳 市,2019/12/31,4039.60 ,161.34 ,1495.41 ,869.00 ,2382.85 ,81995 ,7.4,5.6,8.2,6.5,7.0,5.6
+   六盘水市,2019/12/31,1265.97 ,154.76 ,582.43 ,512.24 ,528.78 ,43003 ,7.5,5.7,8.7,9.0,6.6,7.0
+   遵 义 市,2019/12/31,3483.32 ,431.87 ,1592.79 ,1417.48 ,1458.66 ,55411 ,9.7,5.5,12.3,12.4,8.0,9.2
+   安 顺 市,2019/12/31,923.94 ,157.19 ,292.14 ,232.12 ,474.61 ,39177 ,8.1,5.7,9.6,10.9,7.8,7.6
+   毕 节 市,2019/12/31,1901.36 ,439.36 ,520.67 ,403.55 ,941.33 ,28378 ,8.0,5.7,6.8,5.9,9.9,7.5
+   铜 仁 市,2019/12/31,1249.16 ,254.89 ,325.87 ,216.23 ,668.40 ,39298 ,8.0,5.9,7.0,5.2,9.6,7.5
+   黔西南州,2019/12/31,1272.80 ,226.88 ,444.58 ,330.12 ,601.34 ,44212 ,9.8,6.0,12.1,11.7,9.5,9.3
+   黔东南州,2019/12/31,1123.04 ,223.73 ,253.74 ,139.69 ,645.57 ,31678 ,8.4,5.7,8.1,6.2,9.5,7.9
+   黔 南 州,2019/12/31,1518.04 ,230.54 ,554.38 ,429.08 ,733.12 ,46048 ,7.9,5.5,10.4,10.8,6.7,7.6
+   贵 阳 市,2020/12/31,4311.65 ,178.31 ,1552.59 ,883.68 ,2580.75 ,72246 ,5.0 ,6.4 ,5.5 ,4.5 ,4.4 ,3.6 
+   六盘水市,2020/12/31,1339.62 ,170.79 ,599.99 ,522.47 ,568.84 ,44224 ,4.5 ,5.9 ,4.4 ,3.6 ,4.3 ,4.2 
+   遵 义 市,2020/12/31,3720.05 ,489.62 ,1615.60 ,1441.43 ,1614.83 ,56334 ,4.6 ,6.2 ,4.2 ,4.8 ,4.7 ,4.3 
+   安 顺 市,2020/12/31,966.74 ,176.33 ,292.60 ,227.41 ,497.81 ,39160 ,3.1 ,6.4 ,2.8 ,1.4 ,2.1 ,2.7 
+   毕 节 市,2020/12/31,2020.39 ,486.55 ,533.45 ,404.96 ,1000.39 ,29295 ,4.4 ,6.3 ,3.8 ,2.2 ,3.9 ,4.2 
+   铜 仁 市,2020/12/31,1327.79 ,289.39 ,332.58 ,215.72 ,705.82 ,40269 ,4.4 ,6.7 ,3.2 ,1.5 ,4.0 ,4.0 
+   黔西南州,2020/12/31,1353.40 ,249.35 ,462.99 ,337.70 ,641.06 ,44881 ,4.7 ,6.5 ,5.3 ,4.1 ,3.5 ,4.5 
+   黔东南州,2020/12/31,1191.52 ,244.81 ,258.53 ,140.07 ,688.18 ,31719 ,4.5 ,6.3 ,3.3 ,2.8 ,4.4 ,4.2 
+   黔 南 州,2020/12/31,1595.40 ,254.73 ,563.29 ,429.24 ,777.38 ,45654 ,4.0 ,6.5 ,4.3 ,3.5 ,2.9 ,3.7