{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "描述性分析\n"
     ]
    },
    {
     "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>国内生产总值</th>\n",
       "      <th>电力消费</th>\n",
       "      <th>焦炭消费:总量</th>\n",
       "      <th>原油消费:总量</th>\n",
       "      <th>燃料油消费:总量</th>\n",
       "      <th>汽油消费:总量</th>\n",
       "      <th>煤油消费:总量</th>\n",
       "      <th>柴油消费:总量</th>\n",
       "      <th>天然气消费:总量</th>\n",
       "      <th>液化石油气消费:总量</th>\n",
       "      <th>油品消费</th>\n",
       "      <th>煤炭消费:总量</th>\n",
       "      <th>车辆拥有量:汽车</th>\n",
       "      <th>碳排放</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>32231.467278</td>\n",
       "      <td>3150.957377</td>\n",
       "      <td>259.616187</td>\n",
       "      <td>331.982977</td>\n",
       "      <td>39.840015</td>\n",
       "      <td>61.396661</td>\n",
       "      <td>14.633404</td>\n",
       "      <td>105.685627</td>\n",
       "      <td>91064.120862</td>\n",
       "      <td>22.589437</td>\n",
       "      <td>344.648993</td>\n",
       "      <td>2548.027914</td>\n",
       "      <td>69675.137241</td>\n",
       "      <td>463.346552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>29824.924128</td>\n",
       "      <td>2202.860645</td>\n",
       "      <td>154.347321</td>\n",
       "      <td>170.866131</td>\n",
       "      <td>5.052866</td>\n",
       "      <td>35.588773</td>\n",
       "      <td>10.229105</td>\n",
       "      <td>52.156736</td>\n",
       "      <td>88509.653809</td>\n",
       "      <td>16.021178</td>\n",
       "      <td>165.757111</td>\n",
       "      <td>1195.800138</td>\n",
       "      <td>75729.604936</td>\n",
       "      <td>199.010381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2200.562846</td>\n",
       "      <td>680.400000</td>\n",
       "      <td>71.180000</td>\n",
       "      <td>123.561000</td>\n",
       "      <td>28.287953</td>\n",
       "      <td>22.095000</td>\n",
       "      <td>3.848000</td>\n",
       "      <td>28.959000</td>\n",
       "      <td>15880.000000</td>\n",
       "      <td>3.015000</td>\n",
       "      <td>123.835000</td>\n",
       "      <td>1104.320000</td>\n",
       "      <td>6061.100000</td>\n",
       "      <td>218.470000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>8519.550709</td>\n",
       "      <td>1159.843000</td>\n",
       "      <td>108.706020</td>\n",
       "      <td>173.671900</td>\n",
       "      <td>36.832869</td>\n",
       "      <td>33.068320</td>\n",
       "      <td>7.064100</td>\n",
       "      <td>53.096930</td>\n",
       "      <td>20257.000000</td>\n",
       "      <td>11.784700</td>\n",
       "      <td>198.199350</td>\n",
       "      <td>1377.484040</td>\n",
       "      <td>13193.000000</td>\n",
       "      <td>270.560000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>18731.890312</td>\n",
       "      <td>2494.031938</td>\n",
       "      <td>251.058469</td>\n",
       "      <td>300.862400</td>\n",
       "      <td>38.502200</td>\n",
       "      <td>48.549090</td>\n",
       "      <td>10.768400</td>\n",
       "      <td>109.749322</td>\n",
       "      <td>46608.473200</td>\n",
       "      <td>20.464974</td>\n",
       "      <td>325.470227</td>\n",
       "      <td>2433.754433</td>\n",
       "      <td>31596.629000</td>\n",
       "      <td>441.590000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>53857.995347</td>\n",
       "      <td>4976.264000</td>\n",
       "      <td>437.166000</td>\n",
       "      <td>466.789200</td>\n",
       "      <td>44.004701</td>\n",
       "      <td>81.659040</td>\n",
       "      <td>19.566048</td>\n",
       "      <td>156.351061</td>\n",
       "      <td>149700.001024</td>\n",
       "      <td>24.822015</td>\n",
       "      <td>477.972623</td>\n",
       "      <td>3889.611071</td>\n",
       "      <td>109330.912000</td>\n",
       "      <td>692.230000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>98651.520229</td>\n",
       "      <td>7486.610000</td>\n",
       "      <td>468.849443</td>\n",
       "      <td>672.683000</td>\n",
       "      <td>48.872984</td>\n",
       "      <td>136.280000</td>\n",
       "      <td>39.502000</td>\n",
       "      <td>173.603111</td>\n",
       "      <td>305970.000000</td>\n",
       "      <td>60.664000</td>\n",
       "      <td>645.065400</td>\n",
       "      <td>4244.259405</td>\n",
       "      <td>253763.816000</td>\n",
       "      <td>731.630000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             国内生产总值         电力消费     焦炭消费:总量     原油消费:总量   燃料油消费:总量  \\\n",
       "count     29.000000    29.000000   29.000000   29.000000  29.000000   \n",
       "mean   32231.467278  3150.957377  259.616187  331.982977  39.840015   \n",
       "std    29824.924128  2202.860645  154.347321  170.866131   5.052866   \n",
       "min     2200.562846   680.400000   71.180000  123.561000  28.287953   \n",
       "25%     8519.550709  1159.843000  108.706020  173.671900  36.832869   \n",
       "50%    18731.890312  2494.031938  251.058469  300.862400  38.502200   \n",
       "75%    53857.995347  4976.264000  437.166000  466.789200  44.004701   \n",
       "max    98651.520229  7486.610000  468.849443  672.683000  48.872984   \n",
       "\n",
       "          汽油消费:总量    煤油消费:总量     柴油消费:总量       天然气消费:总量  液化石油气消费:总量  \\\n",
       "count   29.000000  29.000000   29.000000      29.000000   29.000000   \n",
       "mean    61.396661  14.633404  105.685627   91064.120862   22.589437   \n",
       "std     35.588773  10.229105   52.156736   88509.653809   16.021178   \n",
       "min     22.095000   3.848000   28.959000   15880.000000    3.015000   \n",
       "25%     33.068320   7.064100   53.096930   20257.000000   11.784700   \n",
       "50%     48.549090  10.768400  109.749322   46608.473200   20.464974   \n",
       "75%     81.659040  19.566048  156.351061  149700.001024   24.822015   \n",
       "max    136.280000  39.502000  173.603111  305970.000000   60.664000   \n",
       "\n",
       "             油品消费      煤炭消费:总量       车辆拥有量:汽车         碳排放  \n",
       "count   29.000000    29.000000      29.000000   29.000000  \n",
       "mean   344.648993  2548.027914   69675.137241  463.346552  \n",
       "std    165.757111  1195.800138   75729.604936  199.010381  \n",
       "min    123.835000  1104.320000    6061.100000  218.470000  \n",
       "25%    198.199350  1377.484040   13193.000000  270.560000  \n",
       "50%    325.470227  2433.754433   31596.629000  441.590000  \n",
       "75%    477.972623  3889.611071  109330.912000  692.230000  \n",
       "max    645.065400  4244.259405  253763.816000  731.630000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AeUC2SNtdVZ7mwu0kJfWiyvsEImIzxY39RcATZfKTwAnA8hZpza/fFBFDETE0MjJSdXZbGttOcnj0AMnz20lu2zW8IPmRpPlSaRDIzJ9l5lbgMPAUsLg8tRh4tHw0pzW/x02ZOZiZgwMDA1Vmd0JuJympV1UWBCLinIi4tDx8mKLp56zyeD2wE9jRIq3juJ2kpF5VZU3g+8DKiLgQeCXwWWBfRFwO7M/MvZm5tzmtwvzMmttJSupVVXYM7wM+UR5+ofx7Q4vrjkjrNJs3ruWqO+4b1yTkdpKSekFtdxabyWgft5OU1KsiMxc6D9M2ODiYQ0NDc36fsdE+zZ29y17YxzVvfoU3d0k9JSLuyczBVudquWxEq9E+AI/99JBDPyXVSi2DwGSjehz6KalOatknsHJpP8OTBIKxIOEsYUm9rpZB4A3rBvizbzww4fkl/X2c8bE7GT1w6Lm0sVnCgIFAUs+oZXPQjt2TLz/xk4PPjgsAY2wqktRrahkEpprpe/hnE4+YcpawpF5SyyAwl5m+zhKW1EtqGQQ2b1xLf9+iGb/OWcKSek0tO4YbZwBPNkqokRPJJPWi2gWB5mGfl56zms/fM9xy8hjAogiuf8d6b/6SelKtmoNabQ7z+XuGeeuZq1ja33fE9f19iwwAknparYLARJvD7Ng9wv+95o38wTvPYNXSfgJYtbSf6y4+3QAgqafVqjloqs1hLtqwypu+pFqpVU1g6QuPbPIBh31Kqq/aBIFtu4Z58ulnj0jvWxQO+5RUW7UJAlu37+FQi5nAxx19lE1AkmqrNkFgov6Ax1usESRJdVGbIOBm8ZJ0pNoEgVZLRbgMhKS6q8UQ0bFZwgcOHWZRBIczWeUmMZLU+0GgeVP5w5nP1QAMAJLqruebgyaaJezmMJJUgyAw0Sqhbg4jST0eBLbtGiYmOOeoIEnq8SCwdfseWm0UGeCoIEmix4PARE0+CXYKSxI9HgQmavJZZVOQJAE9HgScICZJk+vpeQKNewmPbSfp/ABJel5lQSAijgUuAUaAVwEfBT4AjAJLMvPG8rormtPmkxvFSNLEqmwOugA4nJl/A/wYGARWZOYtwLKIWBcRpzanVZgfSVKTKpuDdgIvKp+vAF4P3F0e3wucRzFQpzltd4V5kiQ1qKwmkJmjmfmv5a/9f6EIOE+Up58ETgCWt0gbJyI2RcRQRAyNjIxUlV1JqqVKRwdFxInAhsy8GXgUWFyeWlwet0obJzNvyszBzBwcGBioMruSVDuVBYGIOBp4U2beHhF9wDeAs8rT6ymai3a0SJMktUlktlpYYR7eOOJ9FG38h4CfA34L+GXmMDooIkaAH05yyXLgkbnmvcvUscxQz3LXscxQz3LPd5l/LjNbNqVUFgQWQkQMZebgQuejnepYZqhnuetYZqhnudtZ5p6eMSxJmpxBQJJqrNeCwE0LnYEFUMcyQz3LXccyQz3L3bYy91SfgCRpZnqtJiBJmgGDgCTVWM8sJV31aqTtFBFfB75fHn4UeDPTmF8x3bROEhGvAf5bZr6tPJ51ubql/C3KPO77zszv9WCZZ72qcA+W+2t00PfdEzWBHlyN9NOZeWlmXkrxHU25+up00xasRBPIzP9DsW5Uy+9xvtMWpJBNGstceu77Lm8IPVdmZrmqcA+W+ww67PvulZrA+fTWaqTnRMQy4GXAfUxv9dXppnXyv0ur73EuZe2W8jd+31cw//8OnVDmncxuVeFeK/cPgHd30vfdEzUBprEaaZf5o8z8FPBtWpdtLmmdbL7L2i3lb/y+X0cPlnkOqwr3VLkzcz8d9n33Sk1gytVIu0XZhri/PHwQWM2RZYs5pHWyVt/jXMra8eVv8X2fyPz/O3SExlWFI+I3qcl33VTujvu+e6Um0EurkV4AvLN8fhLwZaa3+up00zrZXMrVreVv/r730oNlnsOqwr1W7v9Oh33fPVETyMy9EbEvIi4H9mfm3oXO0xzcCfx6RFwIHJ+Zd0fEq5vL1qq8003rJBHxOuC1EfErwBeAWZerW8rfVOavAJc0fN/fLq/pqTID/xE4LyLO5/lVhXv+u6Z1uV/TSd+3M4YlqcZ6pTlIkjQLBgFJqjGDgCTVmEFAXS0KLXdgioijo9jmtNW5FzYdv6/8+4Km9JaDJyJifTnyY6J8HdMibelE1zdc09/w/NURccYU109Yfmk6DALqducDvzp2EBHHRMSq8nADMFzeTHc2PoB/joh/3/A+p5Z/P9fiuuUtPvc6YEnD557TdP4TEfGLjQ9gyzTK85aIuKh8/mbg8YhYXj4um2H5pSn1xBBR1U9EbAXOBk4BflTesAGOA3ZFxHXArwG3A8uAfwd8KDO3RMSHM3NL+T4BLCqf/wLwg8x8R0Rcm5nXRsT1mflIRLyTYor/M8DRFJP4bi9eDsDPR8RFY0P+KMaA/15TtvdMo2i3AS8vayCPA8eUj37gWxHRl5mHpio/sGkanyUZBNSdMnNzFOuv/D5wA3BSZv5d4zURsR+4CLiaYnLSsoi4AFgdEW8HfhP4IUUt4MUUN9CfNX9U+Xm3UdygiYgPAbdn5gPl8cmZ+f2m1/09xZyPRusj4iRgX2Y+01ymiPi3wEPAPwMfpJgN+pny9CnAazPz0HTLL02HQUBdqWy7/x2KpXlPBl5Spg9m5lBEvBR4mKLJ8yXAX1H84v994P3luUczcwQYiYi3Av8EXF3+ql4TEa+nWJvlyobPPZtiqv/xEXFamfwh4DfK85cA7wUOAxe2yPp/Aj4JfDEijgP+d2aeWZ67H/ivwF0UM0G/C1xPEZyezcznVh6dqvwz+KdUzRkE1K1WUTTxvJJizZTjIuJdABHxXyhuim8ATqdYVOthilUc11DcxB+m/JUfxfr+qymajfZk5ocbmoM+OfaBEbGWoqbwVp6fqg/FzRuAzLwVuLVsjvpzipUioVge4F2ZeWXDtU+VNZOx4wPAx8vZpGeV+X+Wou/hj3m+VjBl+TPzO9P8d1TNOWNYXa8cHXNaZt5cHq/IzB+Xz38XuAW4DDhI0azyIMXyvtcDv0Txa38gM6+MiB0UzTBrKJb9XZ6Zp5WdrYcoAsd7xvoUys/4ZOPNvUz7e4ob+NIyaRR4IjNb1Q4aX7caWJuZX2lIO7vM35dmWn5pKtYE1HUiYiNwDUUnLTT9EgZeFBFbKDpnXwx8j+Lm/16KPoLPAe8ur70VeBrYWh4Ple3tH8vMa8ZqApk5XH72vwE2Nf6Cp6Em0OAWih2kzi6P7wYuiIjIhl9eEbE8Mx8pn68D/gfw9qb3+h7wqrIJqI9iLf6pyv/BzPxqi3xJ4xgE1HUyczuwfey4/KV8emb+aUPaMZl5MCI+kpkZEbspbpq3UbTXHyzeKg+U1xMRLwfuKd9i0QQfH8BNzTWBcRdEvAO4HPh1xtcEAIYoOo0p+wS+QjGUlczcHREHmzuNy9FJx1A0/fxoOuWXpst5AuoFfeXjOZl5sHw6tuHGTzLzmXJ0zWuA/wA8GBH9EfFuiv8XzgDuKK8/tuwYPqXpsxbxfF/C0rL/YeyziIhXA++jaApq5eaIOLPM41OZuaHp/OEJXncr8BFabxpyRPml6bJPQF0vIpZQ/Lc8OsvXr6CoJRyVmfvKtOPKjtvjMvOphmv7gaMz8/HyeDlFW/8z5fEi4JjM/OmcCjWz/M+p/Ko3g4Ak1ZjNQZJUYwYBSaoxg4Ak1ZhBQJJqzCAgSTVmEJCkGvv/5RzIKxmiPksAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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mZgXmIGBmVmAOAmZmBeYgYGZWYLmljZA0A1gNPAT0RcSnJZ0PDAGzIuLydNx+ZWZm1hh5tgSOA+ZExHXAQkkvBeZFxNXAbElLJB1TWZZjfcyAbOWr5es2sujCb7J83UYGtg02u0pmTZNbSyAitku6JW12AcuAzWl7O7ACiCplt5afR9IaYA1AX19fXtW1gvDSh2Yj5T4mIGkt2Y39MGB3Kn4UmAPMrVI2QkSsj4j+iOjv7e3Nu7rW4bz0odlIuQaBiHgmIi4B9gKPATPTrpnAg+mrsswsN1760Gyk3IKApFMknZM27yXr+jkpbS8FNgE3VSkzy42XPjQbKc+WwB3AfElnACcAVwL3SToX2BUROyNiZ2VZjvUx89KHZhUUEc2uQ936+/tjy5Ytza6GtYiBbYMTWsJwoj9n1q4kbY2I/mr7vLyktaV6Z/mMdsP3Td8s4yeGrS3VM8unFCgGh4YJ9gUKPxdgto+DgLWlemb5eDqo2djcHWRtaX5PN4NVAkH5LJ+8p4N6bME6gVsC1pbqmeXTc3BX1Z8drXw8qnU1rf3adl7ykRudjsLailsC1pZKn7hrfRIfbeLbZCbElT79V2uF7NkbDA3vAZyOwtqHg4C1rbFm+Tycbsj1lo+lckbSWErjD/XMVjJrFncHWcea6qeDqw00j6V8/MGzlawVOQhYx5rqp4MnMqBcHnA8W8lakYOAdawzly3g4lXHs6CnGwELerq5eNXxE+5+qdWCmH1wF13TNKKsMuA4eZ21Io8JWFuYaF/6VD4dvHbl4v3GBLq7pj8bWMaqYz3TWs0azUHAWl6rLAQz1oyksQLOaEHEyeusmRwErOXV6ktv9MyaybQs6pnWatZoDgLW8jqpL93J66zVeGDYWp4XgjHLj4OAtbxmLgQzsG2Q5es2OhWEdSx3B1nLa1ZfeqsMSJvlyUHA2kIz+tJbaUDaLC/uDjIbRScNSJuNxkHAbBQekLYicBCwSenkgdNmDkibNYrHBGzCOn3g1A93WRE4CNiEFWHg1A93WadzELAJm+jAqRdWMWsdHhOwCZvIwKkXVjFrLQ4CNmETGTj1wipmrcXdQTZhExk49dx7s9biIGCTMt6BUy+sYtZa3B1kDeW592atxS0BayjPvTdrLQ4C1nCee2/WOnILApIOAs4G7gdOBj4IvAsYAmZFxOXpuPMry8zMrDHyHBN4LbA3Ir4B3AP0A/Mi4mpgtqQlko6pLMuxPmZmViHP7qBNwGHp9TzgVGBz2t4OrACiStmt5SeRtAZYA9DX15djdc3Miie3lkBEDEXE7enT/s/JAs7utPtRYA4wt0pZ5XnWR0R/RPT39vbmVV0zs0LKdYqopMOBZRFxFfAgMDPtmpm2q5WZmVmD5DkwPAN4fURcKakL+D7wBuDfgKXANenQN1Upq2rr1q0PSPpVXnWeInOBB5pdiTbg6zQ2X6P6+DqN7cjRduQ5JvDnwApJp6UKvB24T9K5wK6I2Akgab+y0UREy/cHSdoSEf3Nrker83Uam69RfXydJie3IBARnwc+X1H80yrHXZZXHczMrDanjTAzKzAHgam3vtkVaBO+TmPzNaqPr9MkKCKaXQczM2sStwTMzArMQcDMrMAcBMzMCsyppCchPRC3GngI6IuITzsr6v5GuU7fBe5Ih3wwIn7RtAq2GEmLgAsi4h1+P42u4jr5/TRBbglMznHAnIi4Dlgo6aU4K2o1lddpDnBFRJyTvvwfdqSTgUOcZXdMJwOHpNd+P02QWwKTEBHbJd2SNruAZYyRFbWIqlynR4BTJM0GjgXOj4hnmlbBFiJpJXADWSr20/D7qaqK6wR+P02YWwJTQNJasv+chzFGVtQiK12niNgDfC4iPgP8EHhlc2vWGlLCxcci4uFUNGaW3SKqcp3A76cJcxCYpIh4JiIuAfYCj+GsqFWVXydJrwN2pV13AYc3r2YtZSlwgKRTya6J30/VjbhOkl6E308T5iAwCZJOkXRO2ryXbJGck9L2UrKFdQqvynU6kSyjLMBCoGbiwKKIiA0RsSkiNpFdpxvw+2k/Va7TMfj9NGEOApNzBzBf0hnACcCVVMmUavtdp8uB4bR9aET8sKm1ayHKnAW8kOxDhd9PVVRcpzvw+2nCnDbCzKzA3BIwMyswBwEzswJzEDAzKzAHAWtLkvolvTy9Xi3pwPT6jyqOO1rSARVlL5LUXePc0yQdV6V8dml/Wdmfpu8zqxw/o/z7eJTXT9LRoxxzYJWynvH+Lis2BwFrV3OBGemGfArZE6OLgBMl/bWk6ZIOBd5GloLh8LIb69sAlU4kaamk3604/9uq/M6DJH0x+xGtkzQXeImkI4BPVDn+JElvBP5A0kslza4VfCpclOp8CHChpOlVjvmkpN8u/wLW1Xl+M8BpI6x9zQKOIEvV8X/AK4BryR6oKqVauAh4GngB8FzgaUmHAXsj4vHSiVJai2WSuoCZEbFL0qMAko6IiLvScfdI+jvgt9Lvmse+Z0PeXTqfpPOAPwEOJkuTMQ14PL3+NHBVrT9M0nOArwPd6dzvAfrYlyCtZCHwsYqyHbXObVbJU0St7Ug6Fngr2c3422Q3yiPJbpS9wHSyrKWQ5Zb5KnBPRDwgaSlwbkS8J53rOcBQRDyVupeuAX4JLCK76UZEvErSkUB/RFwr6WXA36Tf/zzgF8DtEfFn6ZyvJXuC/EjgGbKAdQdZMNiVHnKq9fd9hSxolZsZESdWHPce4MaK45YC3wHui4inav0eM3BLwNrToWQJ1X4DnA58A3gN2VqzyyLiU5IWkt3QjwZeDeyQ9M70qb/8XI8AV0r6S+AJ4KqI+LCkj0XERZI+BhARv5L0Vkn/Tnbz31kWSA4CPlB2zuOA3yMLELeTBabH09cRkk6PiNtTV893Km/uwF0R8YbyAkmXlr0+GziPLNCcUeX6vBW4FLh+jOto5iBg7ScitkiaR/Yp+1KyLpEPAG8Gvirp5Ii4WdKryD7Vr42I/5X0RkmPkXXhlM41LOlCsoyd11L9plo69qI0dvA/wFmSXpJ2zSidU1mE+RZZmuOFaf/TZDfsncBZEXF/Ot9jqdVQaYGkTRVlD5TV4xrgGkkXA18my5xJOv+bIuKC0f4Gs0oOAtaungvcQjbA+y9kCdZui4jbJH1C0k/IWgk/ILs3nxcRV0h6HnCqpFVkn7g3A4PA4RERkt6UEpMtSgOtP6/4vSdExDfSeT6dyqaRdcEQWf/qTyTdFRFvTEFjZ0TskHRZKQCUVG4n/wDcBPwBWUvhHkknVDnuFcDLgJ60PcS+rKNmdfHsIGtXc4BXkXX33AwsiIivpn1fJhswnkkWKL4H/Cq1DBakr40RsTnNIPoU+272V0XEqcA/pu/3AkiaJekj7GtFbI+IU9Mxp1epX+kD1suBO9NrVR6UZhiVb59ONrC9jqy/f7Wkg8laB2+q+PGrgben+n8qvd6oiv4us1rcErB29STwJbJZOFuBQ9NN/m6yG+93IuJ/Ut/+M8B/lH4wtQJ2A0TEbkmPA3ekm2fVlkBEPCzperIMqDDyhj6Nsi6m5AplK4ENA0dLOg347/ID0pjAt8gCVmm5xD8F/pcsX/5DZNNAjycbfF4hqSsi9ih7HuLc9Pf3pFMOpe9byLqszMbkloC1HUkvJhv0fRp4RUQ8QdYt8n3gd8imjB6VDp+epn6OOAXZdM2SGWSLthwIXJo+4R+ZPuX/rOy4vWSDx6TfTeoWWk8WiErZLZeStVCOjYiPRsRPgc8DJ0taUTpZRDwWEcvKzv9r4C1kgeNMSZvS2MBXgCURcUEKAC8D/qJUhyquklQ52GxWlaeIWtuRpKjzjStpZkQ8UlH2WxHx6CTrMD0i9qbXXWm1tNLA8LTSvjykB8cOLH/WwWyiHATMzArM3UFmZgXmIGBmVmAOAmZmBeYgYGZWYA4CZmYF9v8HB4oTi6NGtgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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yua3CeHrK8LYR1m3cxKrLv8y6jZsY3jYy3yFJ6kOV9QQy866IuLs8XACsBe4sj+8CTgWyRds9VcXUK9xeUlKnVD4mEBEbKC7shwJPlc1PA4cAS1u0Nf/8JRGxJSK27Nixo+pwu4LbS0rqlEqTQGa+lJlXAruBZ4CF5VMLgcfLr+a25ve4NjOHMnNocHCwynC7httLSuqUypJARJwSEReUh49QlH5OKo/XAJuBO1q01Z7bS0rqlCp7AvcDyyPibOAE4Drg0Yi4CNiZmdszc3tzW4Xx9Ay3l5TUKZGZ8x3DjA0NDeWWLVs69nnD20bmbYvH+fxsSf0lIrZm5lCr59xechKznaHT7ou220tK6gTvGJ7EbGboNBLGyOgukj0Jw7n9krqdSWASs5mh45ROSb3KctAYY0s6+0Swu8V4SasZOu2a0uk4gKROMwmUmscAWiWAyWboLF88wEiLC/5spnR+cPhuvvCtB2h8qncJS+oEy0GlViUdgH0jCGDF4gGuOPf4lhfkVlM6AZ59/sUZjQsMbxsZlwAaLClJqpo9gdJkpZuXMrl/47+d8mcbieGjX/o+o7te+EX7E8++MKMZRa16EdPFJUntYE+gtLd36Z6zdgUHHzAxp85kRtFc4pKkdjAJlNpxl+7ezihqFmVcklQVk0DpnLUruOLc41mxeGDaMYDJzKY3MV2ZJ4DfOWWlg8KSKlXbMYHJpmPuzUV3w/pjxs0wgtnPKIIiATk9VFIn1DIJVLVpS+NnZzLXf7KEMdvehyTtjVomganu8N3bC/BMexOzSRiSVJVaJoFu2bTFReIkzbdaDgy7aYskFWqXBIa3jfDMcy9OaHfTFkl1VKtyUPOAcMOSgxbwkTcfZ2lGUu3Uqicw2Q1aB+2/nwlAUi3VKgl0y4CwJHWLWiUBB4QlabxaJYE3rh4kmtocEJZUZ7VJAsPbRrh568i4NfsDeMuJztWXVF+1SQKtBoUTuOOeHfMTkCR1gb6fIjrdxi0OCkuqs75OApPdFzCWg8KS6qyvy0HTbdzioLCkuuvrnsBUpR7X7JekPk8Ck23csmLxAN+4/PR5iEiSuktfl4PasW+wJPWzvu4JuHGLJE2tr5MAuHGLJE2lsiQQEQcC5wM7gNcCHwbeA4wCizLz6vJ1lza3SZI6o8oxgTOB3Zn598DDwBCwLDNvAJZExOqIOLK5rcJ4JElNqiwHbQYOLR8vA04D7iyP7wJOpVi5obntnrFvEhGXAJcArFy5ssJwJal+KusJZOZoZv6o/Gv/hxQJ56ny6aeBQ4ClLdqa3+fazBzKzKHBwcGqwpWkWqp0imhEHAaszczrgceBheVTC8vjVm2SpA6pcmB4f+CszLwuIhYA3wLeCvwdsAa4sXzpxS3aWtq6detjEfHTqmIuLQUeq/gz2qVXYu2VOMFYq9IrsfZKnDC7WF852RNVjgn8AXBqRJxeBvAO4NGIuAjYmZnbASJiQttkMrPyelBEbMnMoao/px16JdZeiROMtSq9EmuvxAnti7WyJJCZnwU+29T8/Ravu6qqGCRJU+vrZSMkSVMzCUx07XwHMAu9EmuvxAnGWpVeibVX4oQ2xRqZOf2rJEl9yZ6AJNWYSUCSaswkIEk11vdLSc9GRHwDuL88/HBm/ng+42kWEb8CvC8zzyuPu3YF1haxduW5nelqt/Ntkji/Tnee0/2BC4EngJWZ+alu/V2dJNau/F0FiIhVwGWZ+a52nVN7AuNdk5kXlF9d8x++ITO/SbHGEt2+AuvYWEvdem6nXe12XqPboznO19C95/RY4JDMvAU4PCJOpjvPKUyM9RC697xC8QfAwe38/9+ewHinRMQS4Gjg0sx8ab4DmsLpTLMCa5fp1nO7melXu+2G87qZ8XH+BPj9bjynmXlXRNxdHi4A1tKd57RVrD+jS39XI2I9cBvFHwRt+//fnsB4f5mZnwa+C7xhvoOZxrQrsHaZrjy3M1ztdt41x5mZO+nSc9oQERsoLkyH0oXndKxGrJn5Al14XsvFOJ/JzCfLprb9/28SKJU1153l4YPAYfMYzkz0zAqs3X5uZ7DabVcYG2e3n9PMfCkzrwR2A8/QpecUxscaEW+iO8/rGmC/iDiNIqa2nVOTwB5nUqxyCnA4MOVidl3gDuCk8vEainJBt+racztmtdv/OWa12647ry3i/E907zk9JSIuKA8fodg8quvOKbSM9US68Lxm5u2ZuTkzN1PEeRttOqcmgT2+AuyKiLOBl2Xmd+c7oGYR8Qbg9RHxG8B9tFiVtVs0xfpVuvfc/gGwPiI+D2wCXqQ7z2tznF+ke8/p/cDyMrYTgOvoznMKE2O9mi49r1E4DziOIrG25Zy6bIQk1Zg9AUmqMZOAJNWYSUCSaswkIEk1ZhJQ34iIgyLileXjFRGxrHz86ohYNMnP7BMRx7ZoX9J4fkzb75bfF7Z4/f5jv88y7oExj181yWsOaNG2eLafJTUzCaifHAq8u3x8DMWUPyhuqT85Ig6OiDUR8eamn/v3Ld7rwIj4HMXMvI0RsRR4TUS8AvjTFq8/KSLeBrwlIk6OiCVjL+7T+GBEHBYRBwOXR8S+LV7zZxHxq2O/gI0zfH9pUq4dpH7yAvB4RPw28CHg+XI5gMMobq2/MjNvioi15Q1XCzNzZ0Q0FuV7RWY+CJCZD0fEfwH+FXAzxXo9jZue3tv4wIh4J/A7wEEUa8/sAzxbPv4UcP1UAUfEvwa+BAyU7/0+YCV7VrFsOBz4RFPbvTM6K9IUvE9AfSEiAlgHXExxM9XDFBfOO4HfBP6G4uI8mpnPl0td30ixENsqiotuZuYby5LSUGbeHBGvA/4zRTJ4NfBj4EeZ+fvl555JsTTCK4GXgEXle+1DcRPP5mnivgl4eVPzwsw8sel176O4oXGsNcDXgEcz8/lpTpHUkj0B9YuTgKMoFgG7MSJOp/irepSiJ/C3FCtEXhcRfwT8HLg+Mz8aEZ/IzA9GxCcAMvOnEfGHEfG/KC7+2zPzffCLdZA+NOZzjwV+gyJB/AgYpEg2zwKviIgzyoXfDga+1nxxBx7MzLeObYiIT455fD7wTopEc3aLf/cfAp8Ebp3NyZIaTALqFzsp/io+qzx+iOKieR7wdxSbhjwHXE6xDO/NtL6oAlAmhTcD/xc4LyJeUz61P0VZqNH7+CrFGu+Hl8+/SHHB3g6cl5k7yvd7puw1NFsREZub2h4bE8eNwI0RcQXwBYrljSnf/+LMvGyyf4M0EyYB9YXM/GFE/BLFRfVC4O3lU6soLvaHUQyk3gAclpkZEReXqzKuKgdaf9j0tidk5t9HxKsp6vtQlHm+Vn5mAt+LiAcz821l0tiemfdGxFWNBDAmxnHHpf9OsRjgWyh6Cg9HxAktXvd64HXA4vJ4lD1LCUtz5uwg9ZOjKAaHB4EzgO8A/wS8JzNXA7cAf8Gei/31mXka8Nfl90cAImJRRHyM8i9+4K7MPK18zRktPrfxx9SvAA+Uj6P5ReUMo7HHZ1CMWWykqPdfGBEHUSSyi5t+/AbgHWX8f1E+3lT2RqQ5syegfnIi8HHgTcBvAZ+nWBb4tIh4eWb+Q0Q8C9xfXjxb9gQy88mIuLV8Pxh/Qd+HPcmh4ZootvfbBbyqHI/4+tgXlGMCX6XYZauxV+zvAt+k2CzkCYppoMdTDD6fGhELMvOFiPgt4CKKWUiLy7ccLb9voShZSXNiT0B9ISKOppgV9BLFoO83M/Muiqman6FIBL9GUdN/GjgA+GT5F/4ry7/yfzDmLXeX7wNFnZ+yLHQtsLU8johYA7wKODozP56Z3wc+C7w2Ik5tvFlmPpOZa8e8/79QlKx2AedExOZybOAmYHVmXlYmgNcB/6ERQwvXR0TzYLM0Y04RVV+IiIMy89mIiBzzSx0Rh2bmXu1kFRH7Zubu8vGCcgvCxsDwPo3nqlDeOHZAZj5b1Weo3kwCklRjloMkqcZMApJUYyYBSaoxk4Ak1dj/B9Mj1oHjn6EpAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "import pandas as pd\n",
    "from pandas import DataFrame\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['Simsun'] \n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "target_url = (\"final(1).xlsx\")\n",
    "#读取数据\n",
    "data = pd.read_excel(target_url,index_col='年份')\n",
    "y=data['碳排放']\n",
    "#描述性分析\n",
    "print('描述性分析')\n",
    "display(data.describe())\n",
    "#绘制交会图-GDP和碳排放\n",
    "x1=data['国内生产总值']\n",
    "plt.scatter(x1,y)\n",
    "plt.xlabel(\"GDP\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "#绘制交会图-GDP和车辆拥有量:汽车\n",
    "x2= data['车辆拥有量:汽车']\n",
    "plt.scatter(x2,y)\n",
    "plt.xlabel(\"车辆拥有量:汽车\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "#绘制交会图-GDP和电力消费\n",
    "x3= data['电力消费']\n",
    "plt.scatter(x3, y)\n",
    "plt.xlabel(\"电力消费\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "#绘制交会图-GDP和焦炭消费:总量\n",
    "x4= data['焦炭消费:总量']\n",
    "plt.scatter(x4, y)\n",
    "plt.xlabel(\"焦炭消费:总量\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "#绘制交会图-GDP和原油消费:总量\n",
    "x5= data['原油消费:总量']\n",
    "plt.scatter(x5, y)\n",
    "plt.xlabel(\"原油消费:总量\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "#绘制交会图-GDP和燃料油消费:总量\n",
    "x6= data['燃料油消费:总量']\n",
    "plt.scatter(x6, y)\n",
    "plt.xlabel(\"燃料油消费:总量\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "#绘制交会图-GDP和汽油消费:总量\n",
    "x7= data['汽油消费:总量']\n",
    "plt.scatter(x7, y)\n",
    "plt.xlabel(\"汽油消费:总量\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "\n",
    "#绘制交会图-GDP和煤油消费:总量\n",
    "x8= data['煤油消费:总量']\n",
    "plt.scatter(x8, y)\n",
    "plt.xlabel(\"煤油消费:总量\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "\n",
    "#绘制交会图-GDP和柴油消费:总量\n",
    "x9= data['柴油消费:总量']\n",
    "plt.scatter(x9, y)\n",
    "plt.xlabel(\"柴油消费:总量\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "\n",
    "#绘制交会图-GDP和天然气消费:总量\n",
    "x10= data['天然气消费:总量']\n",
    "plt.scatter(x10, y)\n",
    "plt.xlabel(\"天然气消费:总量\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "\n",
    "#绘制交会图-GDP和液化石油气消费:总量\n",
    "x11= data['液化石油气消费:总量']\n",
    "plt.scatter(x11, y)\n",
    "plt.xlabel(\"液化石油气消费:总量\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "\n",
    "#绘制交会图-GDP和油品消费\n",
    "x12= data['油品消费']\n",
    "plt.scatter(x12, y)\n",
    "plt.xlabel(\"油品消费\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n",
    "\n",
    "#绘制交会图-GDP和煤炭消费:总量\n",
    "x13= data['煤炭消费:总量']\n",
    "plt.scatter(x13, y)\n",
    "plt.xlabel(\"煤炭消费:总量\")\n",
    "plt.ylabel(\"碳排放量\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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