power_generation_eda.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2fb0c3e2",
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   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>pumped storage net power generation(TPC)</th>\n",
       "      <th>pumped storage load auxiliaries(TPC)</th>\n",
       "      <th>heat power net power generation(TPC)</th>\n",
       "      <th>heat power load auxiliaries(TPC)</th>\n",
       "      <th>heat power net power generation(IPP)</th>\n",
       "      <th>heat power net power generation(self)</th>\n",
       "      <th>nuclear power net power generation(TPC)</th>\n",
       "      <th>nuclear power load auxiliaries(TPC)</th>\n",
       "      <th>renewable energy</th>\n",
       "      <th>...</th>\n",
       "      <th>renewable energy solar power(self)</th>\n",
       "      <th>renewable energy wind power(self)</th>\n",
       "      <th>renewable energy biomass(self)</th>\n",
       "      <th>renewable energy Waste-to-energy(self)</th>\n",
       "      <th>total power generation</th>\n",
       "      <th>total power generation(TPC)</th>\n",
       "      <th>total net power generation(TPC)</th>\n",
       "      <th>total load auxiliaries(TPC)</th>\n",
       "      <th>total power generation(IPP)</th>\n",
       "      <th>total power generation(self)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>94</td>\n",
       "      <td>3830.254000</td>\n",
       "      <td>8.26425</td>\n",
       "      <td>94828.53629</td>\n",
       "      <td>4722.994654</td>\n",
       "      <td>37520.59588</td>\n",
       "      <td>39088.66034</td>\n",
       "      <td>38403.88780</td>\n",
       "      <td>1568.12020</td>\n",
       "      <td>7540.953655</td>\n",
       "      <td>...</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>14.305665</td>\n",
       "      <td>323.479207</td>\n",
       "      <td>3053.840426</td>\n",
       "      <td>227512.2671</td>\n",
       "      <td>147466.5950</td>\n",
       "      <td>141150.4771</td>\n",
       "      <td>6316.117928</td>\n",
       "      <td>37564.42640</td>\n",
       "      <td>42481.24563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>95</td>\n",
       "      <td>3902.278001</td>\n",
       "      <td>8.38872</td>\n",
       "      <td>103094.70090</td>\n",
       "      <td>5094.444369</td>\n",
       "      <td>36875.63699</td>\n",
       "      <td>38940.33964</td>\n",
       "      <td>38316.60622</td>\n",
       "      <td>1553.89158</td>\n",
       "      <td>7743.855829</td>\n",
       "      <td>...</td>\n",
       "      <td>1.457000</td>\n",
       "      <td>11.731636</td>\n",
       "      <td>321.295341</td>\n",
       "      <td>3056.677989</td>\n",
       "      <td>235530.1423</td>\n",
       "      <td>156172.6496</td>\n",
       "      <td>149495.2453</td>\n",
       "      <td>6677.404275</td>\n",
       "      <td>37025.99107</td>\n",
       "      <td>42331.50160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>96</td>\n",
       "      <td>3924.461000</td>\n",
       "      <td>8.24026</td>\n",
       "      <td>106912.01940</td>\n",
       "      <td>5170.269862</td>\n",
       "      <td>37395.02604</td>\n",
       "      <td>40842.61070</td>\n",
       "      <td>38960.77298</td>\n",
       "      <td>1578.38702</td>\n",
       "      <td>8324.820677</td>\n",
       "      <td>...</td>\n",
       "      <td>2.180000</td>\n",
       "      <td>10.169579</td>\n",
       "      <td>302.267532</td>\n",
       "      <td>3163.288733</td>\n",
       "      <td>243116.6079</td>\n",
       "      <td>161152.6489</td>\n",
       "      <td>154376.6775</td>\n",
       "      <td>6775.971402</td>\n",
       "      <td>37643.44250</td>\n",
       "      <td>44320.51655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97</td>\n",
       "      <td>3458.878000</td>\n",
       "      <td>8.28650</td>\n",
       "      <td>108140.78450</td>\n",
       "      <td>5176.339498</td>\n",
       "      <td>36480.25678</td>\n",
       "      <td>35954.91204</td>\n",
       "      <td>39260.45902</td>\n",
       "      <td>1566.40058</td>\n",
       "      <td>8259.072411</td>\n",
       "      <td>...</td>\n",
       "      <td>4.376857</td>\n",
       "      <td>9.179507</td>\n",
       "      <td>272.488782</td>\n",
       "      <td>3088.740144</td>\n",
       "      <td>238305.3893</td>\n",
       "      <td>162044.7045</td>\n",
       "      <td>155271.9872</td>\n",
       "      <td>6772.717294</td>\n",
       "      <td>36930.98750</td>\n",
       "      <td>39329.69733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>98</td>\n",
       "      <td>3289.716523</td>\n",
       "      <td>15.38786</td>\n",
       "      <td>96761.75147</td>\n",
       "      <td>4518.353189</td>\n",
       "      <td>39618.93004</td>\n",
       "      <td>36452.37884</td>\n",
       "      <td>39981.03390</td>\n",
       "      <td>1590.09490</td>\n",
       "      <td>7809.531307</td>\n",
       "      <td>...</td>\n",
       "      <td>9.014407</td>\n",
       "      <td>8.277022</td>\n",
       "      <td>229.350506</td>\n",
       "      <td>3036.144627</td>\n",
       "      <td>230037.1780</td>\n",
       "      <td>150129.5847</td>\n",
       "      <td>143986.1861</td>\n",
       "      <td>6143.398562</td>\n",
       "      <td>40172.42793</td>\n",
       "      <td>39735.16540</td>\n",
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       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  pumped storage net power generation(TPC)  \\\n",
       "0    94                               3830.254000   \n",
       "1    95                               3902.278001   \n",
       "2    96                               3924.461000   \n",
       "3    97                               3458.878000   \n",
       "4    98                               3289.716523   \n",
       "\n",
       "   pumped storage load auxiliaries(TPC)  heat power net power generation(TPC)  \\\n",
       "0                               8.26425                           94828.53629   \n",
       "1                               8.38872                          103094.70090   \n",
       "2                               8.24026                          106912.01940   \n",
       "3                               8.28650                          108140.78450   \n",
       "4                              15.38786                           96761.75147   \n",
       "\n",
       "   heat power load auxiliaries(TPC)  heat power net power generation(IPP)  \\\n",
       "0                       4722.994654                           37520.59588   \n",
       "1                       5094.444369                           36875.63699   \n",
       "2                       5170.269862                           37395.02604   \n",
       "3                       5176.339498                           36480.25678   \n",
       "4                       4518.353189                           39618.93004   \n",
       "\n",
       "   heat power net power generation(self)  \\\n",
       "0                            39088.66034   \n",
       "1                            38940.33964   \n",
       "2                            40842.61070   \n",
       "3                            35954.91204   \n",
       "4                            36452.37884   \n",
       "\n",
       "   nuclear power net power generation(TPC)  \\\n",
       "0                              38403.88780   \n",
       "1                              38316.60622   \n",
       "2                              38960.77298   \n",
       "3                              39260.45902   \n",
       "4                              39981.03390   \n",
       "\n",
       "   nuclear power load auxiliaries(TPC)  renewable energy  ...  \\\n",
       "0                           1568.12020       7540.953655  ...   \n",
       "1                           1553.89158       7743.855829  ...   \n",
       "2                           1578.38702       8324.820677  ...   \n",
       "3                           1566.40058       8259.072411  ...   \n",
       "4                           1590.09490       7809.531307  ...   \n",
       "\n",
       "   renewable energy solar power(self)  renewable energy wind power(self)  \\\n",
       "0                            0.960000                          14.305665   \n",
       "1                            1.457000                          11.731636   \n",
       "2                            2.180000                          10.169579   \n",
       "3                            4.376857                           9.179507   \n",
       "4                            9.014407                           8.277022   \n",
       "\n",
       "   renewable energy biomass(self)  renewable energy Waste-to-energy(self)  \\\n",
       "0                      323.479207                             3053.840426   \n",
       "1                      321.295341                             3056.677989   \n",
       "2                      302.267532                             3163.288733   \n",
       "3                      272.488782                             3088.740144   \n",
       "4                      229.350506                             3036.144627   \n",
       "\n",
       "   total power generation  total power generation(TPC)  \\\n",
       "0             227512.2671                  147466.5950   \n",
       "1             235530.1423                  156172.6496   \n",
       "2             243116.6079                  161152.6489   \n",
       "3             238305.3893                  162044.7045   \n",
       "4             230037.1780                  150129.5847   \n",
       "\n",
       "   total net power generation(TPC)  total load auxiliaries(TPC)  \\\n",
       "0                      141150.4771                  6316.117928   \n",
       "1                      149495.2453                  6677.404275   \n",
       "2                      154376.6775                  6775.971402   \n",
       "3                      155271.9872                  6772.717294   \n",
       "4                      143986.1861                  6143.398562   \n",
       "\n",
       "   total power generation(IPP)  total power generation(self)  \n",
       "0                  37564.42640                   42481.24563  \n",
       "1                  37025.99107                   42331.50160  \n",
       "2                  37643.44250                   44320.51655  \n",
       "3                  36930.98750                   39329.69733  \n",
       "4                  40172.42793                   39735.16540  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv('power_generation.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d5a4b765",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['year', 'pumped storage net power generation(TPC)',\n",
       "       'pumped storage load auxiliaries(TPC)',\n",
       "       'heat power net power generation(TPC)',\n",
       "       'heat power load auxiliaries(TPC)',\n",
       "       'heat power net power generation(IPP)',\n",
       "       'heat power net power generation(self)',\n",
       "       'nuclear power net power generation(TPC)',\n",
       "       'nuclear power load auxiliaries(TPC)', 'renewable energy',\n",
       "       'renewable energy hydroelectric power net power generation(TPC)',\n",
       "       'renewable energy hydroelectric power load auxiliaries(TPC)',\n",
       "       'renewable energy geothermal power(TPC)',\n",
       "       'renewable energy solar power(TPC)', 'renewable energy wind power(TPC)',\n",
       "       'renewable energy hydroelectric power(IPP)',\n",
       "       'renewable energy solar power(IPP)', 'renewable energy wind power(IPP)',\n",
       "       'renewable energy hydroelectric power(self)',\n",
       "       'renewable energy geothermal power(self)',\n",
       "       'renewable energy solar power(self)',\n",
       "       'renewable energy wind power(self)', 'renewable energy biomass(self)',\n",
       "       'renewable energy Waste-to-energy(self)', 'total power generation',\n",
       "       'total power generation(TPC)', 'total net power generation(TPC)',\n",
       "       'total load auxiliaries(TPC)', 'total power generation(IPP)',\n",
       "       'total power generation(self)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fde3cf26",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total power generation(TPC)</th>\n",
       "      <th>total net power generation(TPC)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>147466.5950</td>\n",
       "      <td>141150.4771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>156172.6496</td>\n",
       "      <td>149495.2453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>161152.6489</td>\n",
       "      <td>154376.6775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>162044.7045</td>\n",
       "      <td>155271.9872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>150129.5847</td>\n",
       "      <td>143986.1861</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   total power generation(TPC)  total net power generation(TPC)\n",
       "0                  147466.5950                      141150.4771\n",
       "1                  156172.6496                      149495.2453\n",
       "2                  161152.6489                      154376.6775\n",
       "3                  162044.7045                      155271.9872\n",
       "4                  150129.5847                      143986.1861"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['total power generation(TPC)', 'total net power generation(TPC)']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "31e46e0b",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>pumped storage net power generation(TPC)</th>\n",
       "      <th>heat power net power generation(TPC)</th>\n",
       "      <th>nuclear power net power generation(TPC)</th>\n",
       "      <th>renewable energy hydroelectric power net power generation(TPC)</th>\n",
       "      <th>renewable energy geothermal power(TPC)</th>\n",
       "      <th>renewable energy solar power(TPC)</th>\n",
       "      <th>renewable energy wind power(TPC)</th>\n",
       "      <th>total power generation(TPC)</th>\n",
       "      <th>pumped storage rate</th>\n",
       "      <th>...</th>\n",
       "      <th>heat power rate(in total)</th>\n",
       "      <th>nuclear power rate(in total)</th>\n",
       "      <th>renewable energy power generation(TPC)</th>\n",
       "      <th>non-renewable energy power generation(TPC)</th>\n",
       "      <th>renewable energy rate</th>\n",
       "      <th>non-renewable energy rate</th>\n",
       "      <th>hydroelectric power rate(in renewable)</th>\n",
       "      <th>geothermal power rate(in renewable)</th>\n",
       "      <th>solar power rate(in renewable)</th>\n",
       "      <th>wind power rate(in renewable)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>94</td>\n",
       "      <td>3830.254000</td>\n",
       "      <td>94828.53629</td>\n",
       "      <td>38403.88780</td>\n",
       "      <td>4010.866060</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>76.994761</td>\n",
       "      <td>141150.538911</td>\n",
       "      <td>0.025974</td>\n",
       "      <td>...</td>\n",
       "      <td>0.671826</td>\n",
       "      <td>0.272078</td>\n",
       "      <td>4087.860821</td>\n",
       "      <td>137062.678090</td>\n",
       "      <td>0.028961</td>\n",
       "      <td>0.971039</td>\n",
       "      <td>0.981165</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.018835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>95</td>\n",
       "      <td>3902.278001</td>\n",
       "      <td>103094.70090</td>\n",
       "      <td>38316.60622</td>\n",
       "      <td>4007.618177</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>174.191349</td>\n",
       "      <td>149495.394647</td>\n",
       "      <td>0.024987</td>\n",
       "      <td>...</td>\n",
       "      <td>0.689618</td>\n",
       "      <td>0.256306</td>\n",
       "      <td>4181.809526</td>\n",
       "      <td>145313.585121</td>\n",
       "      <td>0.027973</td>\n",
       "      <td>0.972027</td>\n",
       "      <td>0.958345</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.041655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>96</td>\n",
       "      <td>3924.461000</td>\n",
       "      <td>106912.01940</td>\n",
       "      <td>38960.77298</td>\n",
       "      <td>4302.961153</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>276.462957</td>\n",
       "      <td>154376.677490</td>\n",
       "      <td>0.024352</td>\n",
       "      <td>...</td>\n",
       "      <td>0.692540</td>\n",
       "      <td>0.252375</td>\n",
       "      <td>4579.424110</td>\n",
       "      <td>149797.253380</td>\n",
       "      <td>0.029664</td>\n",
       "      <td>0.970336</td>\n",
       "      <td>0.939629</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.060371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97</td>\n",
       "      <td>3458.878000</td>\n",
       "      <td>108140.78450</td>\n",
       "      <td>39260.45902</td>\n",
       "      <td>4139.079649</td>\n",
       "      <td>0</td>\n",
       "      <td>0.096286</td>\n",
       "      <td>272.689757</td>\n",
       "      <td>155271.987212</td>\n",
       "      <td>0.021345</td>\n",
       "      <td>...</td>\n",
       "      <td>0.696460</td>\n",
       "      <td>0.252850</td>\n",
       "      <td>4411.865692</td>\n",
       "      <td>150860.121520</td>\n",
       "      <td>0.028414</td>\n",
       "      <td>0.971586</td>\n",
       "      <td>0.938170</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>0.061808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>98</td>\n",
       "      <td>3289.716523</td>\n",
       "      <td>96761.75147</td>\n",
       "      <td>39981.03390</td>\n",
       "      <td>3581.906588</td>\n",
       "      <td>0</td>\n",
       "      <td>0.098128</td>\n",
       "      <td>371.679524</td>\n",
       "      <td>143986.186133</td>\n",
       "      <td>0.021913</td>\n",
       "      <td>...</td>\n",
       "      <td>0.672021</td>\n",
       "      <td>0.277673</td>\n",
       "      <td>3953.684240</td>\n",
       "      <td>140032.501893</td>\n",
       "      <td>0.027459</td>\n",
       "      <td>0.972541</td>\n",
       "      <td>0.905967</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>0.094008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  pumped storage net power generation(TPC)  \\\n",
       "0    94                               3830.254000   \n",
       "1    95                               3902.278001   \n",
       "2    96                               3924.461000   \n",
       "3    97                               3458.878000   \n",
       "4    98                               3289.716523   \n",
       "\n",
       "   heat power net power generation(TPC)  \\\n",
       "0                           94828.53629   \n",
       "1                          103094.70090   \n",
       "2                          106912.01940   \n",
       "3                          108140.78450   \n",
       "4                           96761.75147   \n",
       "\n",
       "   nuclear power net power generation(TPC)  \\\n",
       "0                              38403.88780   \n",
       "1                              38316.60622   \n",
       "2                              38960.77298   \n",
       "3                              39260.45902   \n",
       "4                              39981.03390   \n",
       "\n",
       "   renewable energy hydroelectric power net power generation(TPC)  \\\n",
       "0                                        4010.866060                \n",
       "1                                        4007.618177                \n",
       "2                                        4302.961153                \n",
       "3                                        4139.079649                \n",
       "4                                        3581.906588                \n",
       "\n",
       "   renewable energy geothermal power(TPC)  renewable energy solar power(TPC)  \\\n",
       "0                                       0                           0.000000   \n",
       "1                                       0                           0.000000   \n",
       "2                                       0                           0.000000   \n",
       "3                                       0                           0.096286   \n",
       "4                                       0                           0.098128   \n",
       "\n",
       "   renewable energy wind power(TPC)  total power generation(TPC)  \\\n",
       "0                         76.994761                141150.538911   \n",
       "1                        174.191349                149495.394647   \n",
       "2                        276.462957                154376.677490   \n",
       "3                        272.689757                155271.987212   \n",
       "4                        371.679524                143986.186133   \n",
       "\n",
       "   pumped storage rate  ...  heat power rate(in total)  \\\n",
       "0             0.025974  ...                   0.671826   \n",
       "1             0.024987  ...                   0.689618   \n",
       "2             0.024352  ...                   0.692540   \n",
       "3             0.021345  ...                   0.696460   \n",
       "4             0.021913  ...                   0.672021   \n",
       "\n",
       "   nuclear power rate(in total)  renewable energy power generation(TPC)  \\\n",
       "0                      0.272078                             4087.860821   \n",
       "1                      0.256306                             4181.809526   \n",
       "2                      0.252375                             4579.424110   \n",
       "3                      0.252850                             4411.865692   \n",
       "4                      0.277673                             3953.684240   \n",
       "\n",
       "   non-renewable energy power generation(TPC)  renewable energy rate  \\\n",
       "0                               137062.678090               0.028961   \n",
       "1                               145313.585121               0.027973   \n",
       "2                               149797.253380               0.029664   \n",
       "3                               150860.121520               0.028414   \n",
       "4                               140032.501893               0.027459   \n",
       "\n",
       "   non-renewable energy rate  hydroelectric power rate(in renewable)  \\\n",
       "0                   0.971039                                0.981165   \n",
       "1                   0.972027                                0.958345   \n",
       "2                   0.970336                                0.939629   \n",
       "3                   0.971586                                0.938170   \n",
       "4                   0.972541                                0.905967   \n",
       "\n",
       "   geothermal power rate(in renewable)  solar power rate(in renewable)  \\\n",
       "0                                  0.0                        0.000000   \n",
       "1                                  0.0                        0.000000   \n",
       "2                                  0.0                        0.000000   \n",
       "3                                  0.0                        0.000022   \n",
       "4                                  0.0                        0.000025   \n",
       "\n",
       "   wind power rate(in renewable)  \n",
       "0                       0.018835  \n",
       "1                       0.041655  \n",
       "2                       0.060371  \n",
       "3                       0.061808  \n",
       "4                       0.094008  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df[[\n",
    "       'year', \n",
    "       'pumped storage net power generation(TPC)',\n",
    "       'heat power net power generation(TPC)',\n",
    "       'heat power net power generation(IPP)',\n",
    "       'heat power net power generation(self)',\n",
    "       'nuclear power net power generation(TPC)', \n",
    "       'renewable energy',\n",
    "       'renewable energy hydroelectric power net power generation(TPC)',\n",
    "       'renewable energy geothermal power(TPC)',\n",
    "       'renewable energy solar power(TPC)', \n",
    "       'renewable energy wind power(TPC)',\n",
    "       'renewable energy hydroelectric power(IPP)',\n",
    "       'renewable energy solar power(IPP)', \n",
    "       'renewable energy wind power(IPP)',\n",
    "       'renewable energy hydroelectric power(self)',\n",
    "       'renewable energy geothermal power(self)',\n",
    "       'renewable energy solar power(self)',\n",
    "       'renewable energy wind power(self)',\n",
    "       'renewable energy biomass(self)',\n",
    "       'renewable energy Waste-to-energy(self)', \n",
    "       'total power generation',\n",
    "       'total power generation(TPC)', \n",
    "       'total net power generation(TPC)',\n",
    "       'total power generation(IPP)',\n",
    "       'total power generation(self)']].copy()\n",
    "\n",
    "tpc_df = df[[\n",
    "    'year',\n",
    "    'pumped storage net power generation(TPC)',\n",
    "    'heat power net power generation(TPC)',\n",
    "    'nuclear power net power generation(TPC)',\n",
    "    'renewable energy hydroelectric power net power generation(TPC)',\n",
    "    'renewable energy geothermal power(TPC)',\n",
    "    'renewable energy solar power(TPC)', \n",
    "    'renewable energy wind power(TPC)',\n",
    "    'total power generation(TPC)'\n",
    "]].copy()\n",
    "\n",
    "tpc_df['pumped storage rate'] = tpc_df.apply(lambda row: row['pumped storage net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['heat power rate'] = tpc_df.apply(lambda row: row['heat power net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['nuclear power rate'] = tpc_df.apply(lambda row: row['nuclear power net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['hydroelectric power rate(renewable energy)'] = tpc_df.apply(lambda row: row['renewable energy hydroelectric power net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['geothermal power rate(renewable energy)'] = tpc_df.apply(lambda row: row['renewable energy geothermal power(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['solar power rate(renewable energy)'] = tpc_df.apply(lambda row: row['renewable energy solar power(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['wind power rate(renewable energy)'] = tpc_df.apply(lambda row: row['renewable energy wind power(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "\n",
    "\n",
    "def get_total(row):\n",
    "    sum = 0 \n",
    "    sum += row['renewable energy hydroelectric power net power generation(TPC)']\n",
    "    sum += row['renewable energy geothermal power(TPC)']\n",
    "    sum += row['renewable energy solar power(TPC)']\n",
    "    sum += row['renewable energy wind power(TPC)']\n",
    "    sum += row['pumped storage net power generation(TPC)']\n",
    "    sum += row['heat power net power generation(TPC)']\n",
    "    sum += row['nuclear power net power generation(TPC)']\n",
    "    return sum\n",
    "\n",
    "tpc_df['total power generation(TPC)'] = tpc_df.apply(get_total, axis = 1)\n",
    "tpc_df['hydroelectric power rate(in total)'] = tpc_df.apply(lambda row: row['renewable energy hydroelectric power net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['geothermal power rate(in total)'] = tpc_df.apply(lambda row: row['renewable energy geothermal power(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['solar power rate(in total)'] = tpc_df.apply(lambda row: row['renewable energy solar power(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['wind power rate(in total)'] = tpc_df.apply(lambda row: row['renewable energy wind power(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['pumped storage rate(in total)'] = tpc_df.apply(lambda row: row['pumped storage net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['heat power rate(in total)'] = tpc_df.apply(lambda row: row['heat power net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "tpc_df['nuclear power rate(in total)'] = tpc_df.apply(lambda row: row['nuclear power net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "\n",
    "\n",
    "def get_renewable_energy_sum(row):\n",
    "    sum = 0\n",
    "    sum += row['renewable energy hydroelectric power net power generation(TPC)']\n",
    "    sum += row['renewable energy geothermal power(TPC)']\n",
    "    sum += row['renewable energy solar power(TPC)']\n",
    "    sum += row['renewable energy wind power(TPC)']\n",
    "    return sum\n",
    "\n",
    "def get_non_renewable_energy_sum(row):\n",
    "    sum = 0\n",
    "    sum += row['pumped storage net power generation(TPC)']\n",
    "    sum += row['heat power net power generation(TPC)']\n",
    "    sum += row['nuclear power net power generation(TPC)']\n",
    "    return sum\n",
    "\n",
    "tpc_df['renewable energy power generation(TPC)'] = tpc_df.apply(get_renewable_energy_sum, axis = 1)\n",
    "tpc_df['non-renewable energy power generation(TPC)'] = tpc_df.apply(get_non_renewable_energy_sum, axis = 1)\n",
    "tpc_df['renewable energy rate'] = tpc_df.apply(lambda row: row['renewable energy power generation(TPC)'] / row['total power generation(TPC)'], axis = 1)\n",
    "tpc_df['non-renewable energy rate'] = tpc_df.apply(lambda row: row['non-renewable energy power generation(TPC)'] / row['total power generation(TPC)'], axis = 1)\n",
    "\n",
    "tpc_df['hydroelectric power rate(in renewable)'] = tpc_df.apply(lambda row: row['renewable energy hydroelectric power net power generation(TPC)'] / row['renewable energy power generation(TPC)'], axis=1)\n",
    "tpc_df['geothermal power rate(in renewable)'] = tpc_df.apply(lambda row: row['renewable energy geothermal power(TPC)'] / row['renewable energy power generation(TPC)'], axis=1)\n",
    "tpc_df['solar power rate(in renewable)'] = tpc_df.apply(lambda row: row['renewable energy solar power(TPC)'] / row['renewable energy power generation(TPC)'], axis=1)\n",
    "tpc_df['wind power rate(in renewable)'] = tpc_df.apply(lambda row: row['renewable energy wind power(TPC)'] / row['renewable energy power generation(TPC)'], axis=1)\n",
    "\n",
    "\n",
    "tpc_df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "16cfe2ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(10,5))\n",
    "\n",
    "ax0 = sns.lineplot(ax=axes[0], x='year', y='pumped storage rate', data=tpc_df)\n",
    "ax0.set_title('pumped storage rate')\n",
    "\n",
    "ax1 = sns.lineplot(ax=axes[1], x='year', y='pumped storage net power generation(TPC)', data=tpc_df)\n",
    "ax1.set_title('pumped storage power')\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3733e6e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(10,5))\n",
    "\n",
    "ax0 = sns.lineplot(ax=axes[0], x='year', y='heat power rate', data=tpc_df)\n",
    "ax0.set_title('heat power rate')\n",
    "\n",
    "ax1 = sns.lineplot(ax=axes[1], x='year', y='heat power net power generation(TPC)', data=tpc_df)\n",
    "ax1.set_title('heat power')\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d854bd22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(10,5))\n",
    "\n",
    "ax0 = sns.lineplot(ax=axes[0], x='year', y='nuclear power rate', data=tpc_df)\n",
    "ax0.set_title('nuclear power rate')\n",
    "\n",
    "ax1 = sns.lineplot(ax=axes[1], x='year', y='nuclear power net power generation(TPC)', data=tpc_df)\n",
    "ax1.set_title('nuclear')\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "20868fce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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j03pqYZYYyB7RGN7i8VgWMuwCuh7rQzw6F0EQXGBT9n4jQc+EiXoL4aQoKDok199BxEAWBCEiBwuL1bac/FIPMmEcsiTqeUahXm5BqMWZUF+sp3t3OoIguJGk1xLxxyb92zQ0jOMlm8VREVgDGYP36dAKaDX0QJjnydP6+YVQP729FjQLWgAtgf5iOeYRaBM0X2ukk59BECoz1goWJoxDZm3kzXsli9oD/oYxj4Hg90K/h16F7vbiRARBcJ7iQ4eNMm9WD3I/GMhE6iEHNEkPgzhrcz4HnQplQbOx7VNMCS617HYG1FFrMPSCXuZDJ2HffTimBtZ/wfILPP5VH/cE1h9z6twFQTiygkWrEA8yYUc966AtOIseUzti7PsMS7qOTpRrLgiJDcu5FcFItnqQGY/MsXee1EMOrAd5ELQag/laqADr70DnhuzDx5Pw/GFt/KbgR6C5frxP70MDmTrs4LkKghAh/pi0sRjIXSVRzxMwJhZjcY437y4Igpcl3kKdEQyzmLNht9SkD6iB3BLKtDzO0tui2ofeEoZQYHU79A1+HGZa9hurQzImQCVzDYIgOGIg102qphrVZZ8KVZqox456TBIRXGc6xrxnoWMZkmZK/g6CkNhNQlgD2Uq/1ilGfoiEugXTQC6pZn0koV7giPvQWwL10Qkog/Aj0EM/zzCMDhCf2wI9HvbNq1QZDc2hduzYUZHzF4RKT0kFi7r8/3TEtejZMlkS9bxhmK6B/H967KMk3EwQKkEXPSv92zQylnM37HH9nCoLThrI9Aa3sjymobs51n1gJLPp+I/Q6frxNm08s77JKzqU4yjw/MvQACo1NTWuDyIIlZUNu1gD+eg4Y8Yh784rKB28BXfAeHZiGEmTEEFI4BCLhnVqqDpJR6aMdWleH7N5VSVRL6AGMovXd4TnqR3E+dnLoE9D9uHja3Q1C9by3IvBnuWLUqEU7oAlf51P0cXx+bi55fjzocUOfgZBqLQcOnRYZWJwbgMPcig9043/ntIwxGUw/qVB45m0rB93g25w+zwEQfCmxJsJm4b0xjg8d6N4kANnIMPQLcJiLPQVtAyajG0s2XYLpXebAq2FVmtv8G16O43gHxhnrA3tb3TmNnkU2xfp55jFLSWOBMEBtuUeNGptWitYmHRpVl9Vr1rFaDktuMrrekxtoR+vhO6Sv4EgJK4HOVK1ICbqLd2cow4UMH9XCEyZNwKjlgbwlJBtL1rWGW88JsxxNH77RnjNq20+TUEQwrBx19EVLEyMjnpM1JOOem7TBGPgZDgIHjQdEViXX0dBSEBoItGDfGzH8GGi/Vo3NErALczKVoPbN3b57BIf6aQnCEJYNoRpEmKll3TU84I8GMSNzWRmMzTNkzMRBMFRsvcXqv3wDocLsbA2DJkr9ZAdQQxkQRAidtGrhjCK0Oxpkx7pDdQeDOCSqOcq9+jcjQ4wjqdhOQm6PZoDmdcBvQ8th5ZBQ6FG0DfQKr0sLZtJL7XucspuqKdZtvfXYW6rdSfUcNWIBEGIE3NsjRRiwfKb7ZvUlUQ9hxADWRCEiF30WqTUMpJBInmQzY56gmtTrnOxOF6Xe7sZ6q5D0qLhKehL7N8Fy946N+QB6DtsYzfT7/RjI/lPJ1Z31xWEnted/MxSm6MtXVCNCkOCINhL1p7wNZCt9EWYBRP1SiJWBTsRA1kQhMg1kMPEH5t0lkQ9rxikDVw2CLkchus15R2AfZKxOA4az8fsbqpLaLKb6US9G5fn6XVufwf75EPrdCI169EzgToZ22boHJJJlmMEQXDRg2wm6rHkJh0agr2IgSwIQhkG8tEl3kI76kklC/eAgfpf3RhkBDRQa0AUh7aH2DHpNbzGPOhViH/cNJbW5A562bScLqct9Xro9nDnKs2aBCHOChZ1kqqplDo1yjSQSYY0DAlWFQtBEIJJ7sFCwytRlgeZ9EIc8pdLthrTexKK6go0hrtp722sYz09zrfj0Jn4Wz1lhlNEIFKX02g6pJY2a8KCUgMGDJD5X0GIkc3wIDMHpKyxtWPTeqp+zepGmMWF/dlrTbAL8SALghDWe1xWBQuTHohDZqa1GSsnOA4bIzWrwHH09GbRONaP39cG8zaz+ZJebi+nyym3p5fTIVUQBLuahJQRXkGqVq2i+rROEQ+yA4iBLAhC2AoWJBoPMpEwC9doAi2FMfsV9Kmp8g6CYbwVi0zs21lvOpmvA/HYUXobl5/odW6/DPvXZDdUnYw3S4dh5LK8nK5ecY3lGEEQXOiiF64e8optucbMn2AfEmIhCMJRmAkfrcvxIDNRr0a1ko56I3tau8ALDvFIHMeyHNybsGuTdAfT67STZLJuV70Rupg76q6nk7URza6oY7DNbEhyq+7ox19utrw22l4LgmAf+wuKjDC38jzIZhwyg64WZO5VIzryHlqwAzGQBUEIG2LBxJDkWpGTQ0jN6iWJeoul5bQrwEidCsO1DVY7Yv1brPMOplqUx86PkNB3coT9x2ExLsz2OVj0iP6sBUGoSPxxeSXeTBhiwfkcJuqJgWwfEmIhCEJYAzlci+lIYRZsOS11OJ0HBvFNOn74Jb2JFSQ+duGtBUFwETOvIxoPMh0ZnZrWVxkb9zh9WpUKMZAFQQhrILeK0kBmot7eA5Ko5xJjoOFQDh/gpmSVpTSbIAiJVgM5Cg+y2XZ6HgzkQ4ekYIxdiIEsCMIRFBUfMupvllfBwqSn7qhHL7LgOGzcUWDxKDNMTn4RBSHB4BhcvWoV1bR+raj2Zxxy7sEitXrHPofPrPIgBrIgCEewZe9BVQQvRHkVLMIl6gmOwxjkh7CsjeWpWL4H/U+uuyAknge5eUotVQ1GcjT0QxwymSsNQ2xDDGRBEMJXsCiji15ooh6NZEnUc4UHdEe8RdDN0BToYXfeWhAENz3I0cQfm7RrUlc1rFND6iHbiFSxEAQhbJOQ8kq8WenZMkVNWbRFOuo5DMIrDmHxipYgCAnsQR7WIfqSbSxLzjALSdSzD/EgC4JwBBt256mkalVVs+ToYt/MOGQm6mXulo56ToIfwUXQwhD9DD0BNXb0zQVBcIXC4kNqW85BeJCjH4NJ39YN1dodeWpPXmmaghAHYiALgqag6JCUKtNd9Fh7M9rYtyMS9TZly/fJWdiU43PoSi3GH/8EbdXNOwRBCDhb9x5ULEYRbQULE3qQybxMKfdmB2IgC4LmzKd/Vhe9OENtzz2oKnsMcizhFaRTs3qG11kS9RxnOMIsHoQWaf0B207A8l9YtnX+7QVBcK3EW0ps43Dv9BTDscGGIUL8iIEsCIBTUqu27zMGlvOenVZpE87Y7GMjDeQoK1iYSKKea9RDKMVg8wHWB3GbfsiW0IIgJECCHonVg1w7qZrq1jxZzd0gM3l2IAayIIC1O0tqR957aidjeTE8yV8s2lLprk32/kKVm18Us4FMeqY3UIuko57T3Ai9CsN4HcV1bsM6S478w/F3FwTBNQ9y8waxxSCbYRbzM7ONevZCfIiBLAhgzfY84zqc06eF+njscNW1eX1165tz1VPfrqpUccmlFSwqYiAjDjnnYFHpawj2g+/ibKgnVvtAfbHeS2/LgybLNReExPAgp9avqWrVqBbzsX1bp6gDhcVq+dZcB86sciEGsiCANTv2GTG06Q3rGJ2L3h49RF3Qr6V64tuVauxb89SBguJKcZ02aOO2TePoaiCHS9STOGTngTG8F5J5VEFIUA9yLDWQwyXqzd0occiOGsiYthsKPadLCe2ANkJToDFQya+hICSIgcxC62blBsbUPn5xb/XQyC5qyuIt6uKXpqstew9UigoWpFWj2AfnTmn1SxL1pOW0IAhCfAZyjPHHJjSs05JrSqKekwYyDOAvdLzbV9DpUHOom+7axMCYT7DPOTacgyB4zpodeap9at2jCq+PPq6DGj9qgFq/c78659lpCX9XvmFXnjG1Vycp9h5CSdWrqi4ITREPsjPg+1gVGubQywuC4AMOHTpsGMjpFfQg83erX+uGCf9b5bUH+WpM4d0AfQpthoqgfdBc6HHoBOwz3Y2TFASn6x8zbrZDqlkM4EhO6pKmPrxtmKqNeLDLXv5VfTg3K7FLvFUg/tgaZkEDuTLFbbvcRe9xr89DEATn2JmXb/wmVdSDbIZZsGnT9pzKXbLUMQMZg/HO8g6OZh9B8Dsbd+epYty1d2hat8zwgU/GDMedeYq6Z/IC9c8vlhvHJGKIRZs4DeTcg0WGoS04wtfwEF0IRd/FRRCEwJV4a9Gg4gZyP4lDdjzEIhfKCSNjuy3vLgg+YLWuYBHJg2zSsG6S+u8Ng9WVg1urF6euUaMnzYExWOjGKbpCflGx2gKPQ6s4DOQekqjnNPdA70EFMh4LQuKxObvE6xuPB7l7i2QjH2TuRsnjdcqDXB9KDiNjezxvKgh+S9Aj7csxkEkNDDrjzu+p/npud/Xjyh3qwhemG401EoEseC4YGdEmxi56RyXqIRZZ4pCdQY+/VaEaMh4LQuKxKXt/3AYyk8xZl1466rlU5g3eiqZQa1Pxva0g+MtAbpZcS9WrGX1i2tVD26pJ1w9S23Ly1bnP/aJmrNnl4Bm6g2noxxODTOO4a7P6UsnCIRhaAa6C/qgft9Ld9ARBSJAQi/q1qqvkWjXieh3GIdNRwZlBwSEDmZUqoFVYZdemqdB6iBUuBCFhKliUFX8cieHHNFEfIy6ZoRdXj5+p3pq50YGz86BJSBweZDPMYvHmvUY2tmA7z0NDoSv0Y05/PCfXWRASg3hqIFthvgyT/ZZslohYJz3If4WGQCsxpdcOy5OhaRV9Q0HwE6y2sHb7vnLjjyPB2skf3TbcMJYf+miR+vMniwPb4pOJdazUkVqvZlyv0ytdJ+pJRz0nGIzv7BgsjUBFrLOWU5Ij7yQIgiehbulxhFeYsNQbmbtByr05aSAXYhDm/DFrcDL27Qfd5lQQAs+O3HyVm19UYQOZNKhdQ024dqC6cUQ7NXHGBnXta7PV3gOFgfQgM7wi3gIJkqjnKIX4+7D/rOGex3oqFsG8IxMEwTEPclOEDdLQlnrIzhrI2RiEaT38BL2J9aewLKr4WwqCv8IrSGiTkFhhB76Hz+qmHr2wl5q+Zqd69ee1dpye6+Xu4g2vOCJRL0syqB3gaegjiDkh47D8Bfq7E28kCIK75BwsNGbf4knQC41DZqKe1KV3zkA+F2Jw4t3Ql9Aa6KyKvZ0g+LOCRTweZCuXDGylujRLVvMzg2UccgA1PcjxwkofXZsnSyULZ/5Ob2JxH/QPaAt0Hrax7JsgCAlSA7llSvzjsGkgM5GcXmnBGQP5T+zgpDvpTYTowbg/9rcSBH8ayHWSqhlVLOwiiN3kGGpysPBQXCXerPRsmayWbMqRRD2bgdf4/7BoBb2O79ez0DKb30IQBK8NZJs8yKVxyFIP2TED+dQw286o0LsJgg9DLBheURUhEnbRI72Byt5faCRbBK2CRTxNQqz0aplixHav31USwiLYBqsIXQ7NgbE8C3oc4iyfIAgBx/T0tkixx2HTpVl9I/FaEvXs76R3K7QIq52xXGgRy70trNjbCYK/WBNHBYtI9ApgNzmzNXQ8baatSKKeM8BjPAG6HqsnQm9AF+ulIAgJYCAzf6NJ3fgqCZlUR7hbn1YpkqjngAf5Lehs6FO9NNUfA/RVFXw/QfANBwqKjQHJbgO5M+7aq8MjHSQDmR5kFq+wa2qvY1o9VdNI1AvONQgCcFC8Ck3H6gsQO9tcBDWM8tj1dHpA86E5etsj0Ca9jRpp2f9BaDW0AjrNsr2/fh0+9zQ7l9j7KQWhclewsHNGs1+bFKMW8v4Cqa1gZ6vpvdB6iNN5KRYDmfFvghB41u60N0HPpBamtFjJIUjGIQ3kFg1qGy1K7UAS9RyjMcQ/ErNAd0M7mR8Sw/EnYv8+0ADLtif0NmoKN8Dm7YbFZVB36HToeV1eTmnjfDTUUYvPC4JgQwyyHSXeQhP1ig8dVgsD9HsUpE56d2DBzOmmWm9g2+1On5gguFXirSJd9KJplhGkRD0ayK0a2TswM1mRngvpqGcf+D6dDw3G6qPacfEDxuMsG9/ChHHN7+C98iGG1a2GBuG9mmOZjG0zDpd8uSdB5znw/i+B9ZQAACAASURBVEIlZHvuQaP7W2XFrhrIVvq2MhP1pGGIE0l6N+ruTaxm8SfdVe+mWN9IEPzG2h37jLCCto3tN5AZg8tmIUFJ1GMMcptG9l6HnrhJ2JdfpNZJop5twEA9C/oXVidAt0DfQxyXo4EG7dc4PgOiB9hkrM4vmQCZ4RotoUzLPll6G5UVZnu4cx3NUA5qx44dUZ6iUFnh/dYZT/6sLnlpRiAbLcXLwcJio5qQXWFuJg3rJhmJ6JKo54yBzGCYYstjrkvMmZAQHmR2GmJIhN3Qe0qCEIfM2LSd+/JtaRIS7hosDsA1CBCsIDQXuhAGRRfoOibuRXnscOzbT7/GGBiux+lwiQ66OyrrKj+u960SwcCOtP3ojYcPv8xQDio1lQ3/BCEy22Ec7sorMGrIXz1+psreX1CpLteWvUb3eNs9yKR/64ZGqbegzGgGyUB+DZqpkzkewfqvULQDsiBUqgoWJl2a10ccbpVAxH2ZJd7saBJipWNTSdSzG/zAjcHiR6if9iY3jeHYzXq5XXfjG4T1bVAxa93j8SvcZvEMW/NN0qHNent6mO2CYEvTphtGtFPLt+SqK16ZqXbDYK4s2F0DOTQOmddyva5WJNhkIGPg/A8W1+mEEAax0GPxRHQvLwj+hHGxTNJzykBmshsT9YLgPd24yxkDmSWGurVIVgsDcA2CAgxilnWbBXF5iXZeXBTFcXWh+uY6Fr+DFuuYYpPzuU2vs3rRZXi+JtROJ+PNwthPL3Mutg3R1SuugT6x6eMJlZi1OieEBvIrowYYBvPlL/9qzG5VBjZl73fMg9wPBjJh22nB3iS9/2JQnMsOetBT0Dxui/4tBMF/bN57wOgc55SBHKSOeqYH2a4uekcl6uEaSKKebTwMDcR3ahR0jfb4/jGK49KgXzB2L9AG9uc4/kssH9Ul2xbq2sp3c2c8twSLydBSiPuNoadZv9at0Ks6cW8N9IVtn06otKzbmWc0tWBX0+M7paoJ1w5UG3bnqctgJG/PKQk/SHQPMqu7NWtgX1dXk2PwO1e/VnVJ1HMgxIJlfkrRpX76x/g+guDPChap9ifoWZPUmGySufuA7w1kDp4NatdwxEDOKyiGt1466tlEVR0iYbKL28o7CMeshXprdYfG6e1XQz2hXtA52kNsHjMO6gB1hkqNYKzPgXro58bqahaCEHfSdLsmv3U1HX5ME/X6dYPU5uwDhpG8VcfoJipZ+JxpuDlgiUy74TXtyzhk8SDHdt0iPaGLxOditReWOVp8zMFZptSEwMcfkw6Ik3WKoCTqGRUs4D12ot8DbxJIEEJNAsKX+Dt9BV1L4fHnkFG7WBCC7kFuF+KwGNK+sZp0/SAjge/Sl2eUtmJORJyogRyaqLdiW67KOVj5KoQ40SjkHxBj1v6NJeteUvWhxtCDFX1DQfADjG+jx7Rx3STH3oMd9Zio53cDORMeZLvjj61Te7VqVPX9NQgKGHv/HxYvQb2g3hArRdzv7VkJQnyw9nEmDMQO8CCHMqBtIzXphkFGktmlL80wxquErYHsQIKeNVGPcz0LMtljyD9Mnp2pTnviJ1+GIkYzNSfGsJCQCSGsDelkl9wgJOqxw1LmHhrIzoSaGIl6zZMD1VUwALDV9FRdA3mGx+ciCHGzEbHGHItCPcgm/eD9fPPGwSr3YJFhJK9PsJAtfnaGkDjpQe7dqoFR999viXpfLN5ieLb9WPva/mAXQQiIB9nJBL2gdNTbmnNQFRYfdsyD/FtHPUnUswPc0N2ok+xYcYLVK37FtutteXFB8LiCRfsmkcfkXukp6q2bBqsDhcVGuIVZFi5ROggWwUh20oNcv1YN1RkOGz8ZyIfwmc3z2Zbjv2olYiALlQ7GYDGmzQ0D2eyo59dEvQ26y50TFSxMeuKHTRL1bIMhFn1xw3UtK1nohGkJsRACjZnEG8mDbNK9RQP1zuihhsf10pd+VavgeUyoGsgOepDNMIv5G7N9U1VoDW5ycjArYN4kBNJAZuUKqAXU2pTTJyYITnsrnKxgEZREPTOez2kPMlm0yV+xbwGFjTqsVkFuSEtoQQhkBYsm9WqqZHg5o8nteGf0ECNcgNUtlm3JceEMncVMPmRnVydhqEpufpFapZPUvSbD4s3eHkQPMozh27HYBn2jM6apz6J5cRx7OrQCWg09EOZ58rR+fiHUT2+vBc1izU5oCfQXyzGNoG+gVXpZUgFbEHxUwSI0UW+hT41DVrCoXrWKau5A7U0T3ogYiXpZwf8h8wGbLJ1N/6w7m3L8vIfy+NwEocIVLJgTEi3HNK2v3oWRzJJoV7zyq6/zPKIhS3uQW7jgQSZzN+7xjYFcv2Z1Y52zukH0IN8Jdda1M3uaNTPLO0jXS34OOgPqBl2ObVxaOUN3aKJGQy/o7bxSJ7FmJ5Z9IBraQ/RzNLS/w3M85jv9WBBimtahUeik19SaqEcj2a8DOGsgM+6NyXROwdfm1Kh4kG2BjTk+hsw5UpbcZO1iVhwyOuUJQhBn9WKd0WuPELl3bx6i6iRVN4xkv1VniNWD3KhukvFZnIShdKzcZPXcekkGDPXB7RupejCSt/mwGUw0fw1O31Xk150dnlazQD0fwMB9B4tzdWcmEz6epAvNM9kkha1PdbF6cw6Acy41LD8IPOYEvT4R+hGSGDwhJgOZA4UTBdkjhRh8vnCLkajnZNWMihrIbtwo8BpMnpNpxA5W040AhNjBd6h0Nk0QEoG9+wvVrrwCo0lIrLRpXNcIt7gcBvJVr85Ur18/qNRLGiScroFswt8fvzQM2Y2/OW+MLuqfbix3BNSDTAP3R9045J4YpvJahsTGZeltUe2j457n68Yk3+CHYabeJ83s9qSXTcO9OY4dDc2hduzYEcXpCpXLW+F8eIVJz5YpRiKC2dK5MhrITFbcX1CMqVR/xL4JguAP1uoxoawKFmXRCuPX5JuHqkb1ktQ142eq2et323l67tVAdsFAJryBYFIkDVQvmauNdDYwaZpcM7BJeht1/HGSZRovmqm8cG6i0NTJiPvA+C2GGF6RDg2Codsjivf87UUOH2YB/QFUampqLIcKCUxR8SG1fleeK/HHfk/UY3WNbHhvnKxgYS13RxZKPWRBEMIkTZdXwaIsGLv77uihKq1BLRjJs9SMNezAHgw4s0gPstPxxyYD25Z42Get2+V5eEV1zCayfF/T+rWCWeaNU3rhFMVr0xvcyvKYhu7mWPfBe2XrMIrT9aZtDMPgil7SwywIUcFuTaz7274C03kVpVOzer7sqOdGBQsTeuxr16jmu2swG96m+99f6Ns61aFgzBsezTZBCFKCHg2leMehZjCOGW7BShDXvT5LzQ9ITPIeOClY29nJGshWaJByLPb6JiIDHuTucB7VTqoGA7nEg+y3cTiigYxB90m9/B/0aaiieO3ZUEfs2w6i9/kyKPQ4Pr5GV7NgEt5ehk1gPZXxyPr9+a05BVpuOYb1P8konaQiCL6rYGFN1OvSLNl3iXqsYEGc6qJnhXHH3Vv4r6PeWzM3qncRG80fqYDwTJTbBCEwIRY0ju3ICaEnkkZy9apV1Xv4fx0ENusSb26FWCRVr6oGwIs8Y+0uT1uLL8ANDMMrSFpyLXWw8JBRgi4oSXr/1cvHKvLCMHSLYNyOxepXECtaTMA2lmy7RT//IhZToJHQaoi/1tfpw+kZnqgrYfB/zWTsb5aW+ycf47kbdPjHxRU5P6HyJuiRDhWMd4snBvfzhZt9lahnxkS3diHEwrwG7872V6IePciEGdTMIvcr+M4MxWIYlBqSA5IMcZwUhMCGWFQkQS8SjevVVH1bp6i5G7MDVeLN6RrIVoZ2aKwe/XKF2rkv36g/7TZLt+SofBjJZkIlY5DNWsjR1ML23EDGD3mGXk6t6IvjWBrAU0K20TA21+lPHxPmuIVY9I3wmrztObmi5yRUbmggc0BoUMfd/4SMQ3571kbDKGXmtR/YuDvPKPnDEjtuXYPXp683mgJ0TPO+ItmWvQdKf5zYcrtrc9qavoXWO+/q+MeyXrwc3XJaEAIHO7oxxOLYjk1sb4jxzPerVO7BQqPFchCahLjlQSZD2zc2lr/Ci3xWrxauva81vIKYBnIqQizIdozDx7g4u1seEX8ZGVqBxcvQlzBKC0Oea4/FtdB6PDfB2VMUBPtYU4F6m3Yn6vnHQN5vZIC7hTVRzw8G8pz1v5U62rbXfxnUVrSjYirG3texvgHLuliWZDcJQkDZjJtUehLb2TyjR8OL3ZQXZO5VI2w2vu2GCXp1EIeb4qLThr9HdIwwDtkLA3kuDGTeEDBu3AyN8WOzkLKCfm6CjoWWYzCeDU2BvofWYdtLUIYYx0IQPchuxh9bE/WSEGPnpxhcxiC7UcHCWtifPwR+SdSbg/AKJquYHuSA0AJjMGvJL+MDrPeGnvf4nAShQtB7TGLpohcNfRBiwUg201PpZzZl7zeMRTdD79i8aaBHcciHETgwZ8PuI+pVp5khFj4r9VZWiMVWLO6j8Idrq+OCORewEs/5r6CrIJQD6z6yrJmbNZBDO+r5xTgsLD5kJIdc0De0NLnziXp+SVacDQ8yB+lliIfzYxenCDB5+jQz4Rlj8QKMz8d5e0qCEF+JN7sNZMaxdmpa3zctlcutgexi/LE1DvmHFTuMsY9Jcm5+3m2INbYayPRm01nB7X4i2rRRxgpzSo+NOw5jQPZ+flQQKpqg50GIhZmkRuOQd9B+mNbjFKSbIRbmNViyOcdI1POSHMQmLt+aY2Rz88fBbwNzWeD7E5qeX+zJiQhCnDAfgcZRqgOJYv1ggNFAZpyzn3Gri14oQ9s3KY1D9jL+mNB7XtIsJGAGMk6coRbv67AKs1bxx06elCA4WuLNAw+yGYPrl4565jm4HQ/Na8Canyu35br6vqHM25ht3CAMbNvIiIPb6vMYZAuZGJOHaUdFEvR7M9xCEIIGO7rRe+xEeAENsFyMt6u1Y8SP7C8oMkpMeuFB7obZvORaJXHIbscf10GoXRfMqFoxaiH7bCYvGg8yq0wM19nS9F6sitTeWRD87kGuWb2qax2LIiXq+aGb3AYXm4RYGdSuJHva6yL1jD9myEefVinag+yvgbkMbtFjckvdaKlPuEpAghCUEAunmjb1QxyyaZD52XtMvPAgc/zjeOx2HHIGvPocdxkHbaUpxuEdQfMgg3wYxaVNu3Gnx7hlf89ZCEKEChast+lVDd5OafWNRD0/xOCyix5vFnjX7ib8IWjbuI6avmanq+8brv4x46HrYnq3GQbmXYhPzy/yf6QCxuKd0JVQGtQUugoKTl9dQdAcxEwSq1jYXcHChGN9wzo1fJ2ol+VBibfQOGQma5vNSpwmL79ILduSe0R4hQl/i/zmqIjGQGZpoYewrI3lqVi+B7EEnCAECq8qWFg7GHVp7o9EvQ278oz446oe3CwM7dBEzVy7WxUVH3L9vc0uTmxDO6BNoyMyqP3mvQiH7jL6EPQyNMGU1+clCLGyHmMQ0zHsTtAzYdgGDTF6LH3vQfYgxMJaD9mtGb0FGHeZf8L48FBY6i2voNgwooNkID8A7YAWQTdDU+Cx+IOjZyUIDngr6DX1Kv7YmqS2yAeJeht3H1BtXA6vMBl+TGOjpehCj24UFm/ea7Q1ZZkjkqZrcfrNexGBTyDG6nwLfW6RIASygoWdXfRC6du6ofE+ezBD5Efoua0OJ4VZB9htGAdML7tbYRYZ2pvfr9XRBvJvpd7yA2Ug344f81egi6GLuI47szsdPzNBsBFOIzEpy6sKFtY4ZCaO8Hy8gsb5Ru1Brgxei3Dxx2RA2xIPMkMsyNa9/hmYy6AO/n73Q5OhD0x5fVKC4JcayFbMqfx5mf70IrPkWfOUWp6F/XEGcTDjkF0aizPgze+UVi9sJ1vzJsFPjopoDORRYbaxi54gBKqcEPHag2ztqOdlPWhOZbnZJMRK43o1jbbO01bv9Kz+Mb1WZnvTUgPZRwNzGXwGB8VIr09CEOwIeWuO2Zs6Sc61uu+dnmIYn6bn0m94VeItNA6ZhjpnWJ3kEDxUTJgMF39MWOYtMB5kDMKX63bT7bD81KIfsE2SQoRA1kB20lsRlEQ9rypYWBmOQXkOBkuGvrjexQke5AGWQZotXhkf7ifPRRncqY3kA1AOlMul1yclCLHC0AcnwytI7aRqqhtuxuduyHb0feJqEpLi3ThsGsjEaS/yavwGs8xpP4S9hMNMGN8eEA/ydOhxaLlemroXOt35U/OOvfsL1TPfrfJ9gXEhtgoWLRz2VsSSqOdlqTfTU+CVB5kMQxwyk+Xc9uzwe8C6o6x/bE3mYfxbEAxkGPj1oapQbShZP06O5lh8zvXQImg+NEdvawR9A63Sy9JfL6w/CK2GVkCnWbb316/D556GvJkfFgILb1Q5q+eGw4IeSyblepUUXFY3U445XiXomXRsWk81qZfkeBxyRpgGIVYa1C5xVPgpWbpqGV/gDdCP0FBoqkVzIf+kGTrAl0u2qMe/Wan+77OlnidTCYlRweKojnqbvUvUM+Of0xt6ZyCz/iaTU9wOs/gt/vjIQZphFgFqFhIPJ+J71wcaYEnC/g6PO3KpH9MI7obFZVB37RB5Htuq6WNegEZDPKZjojtMBGfCvOhNbO9QiTcrrJjA5kTLt3rbnCgUjjf0waV7HGLB+9vB7UvikJ38TcqAgdyoblLEWQOjm57PSr1F00lvCDQb2gcVQMWJPqV3yYBW6sYR7dTr09er535Y7fXpCHHC//Tsoud1/LFJL48T9dhFjwZhrRqmveM+bC/bu1WKmu5yoh7jjxuHGaQD1izETs6FJup1Ls+zbH8H/3dYB38d1jkQDsLY3xxLeq5nHC75NZ1kOUYQou6gR9q55EEmbDvtJ7I8LvEWmjjNHIz1Dv4mzYWBzPCKsiacjG56QfAgW3gWuhxiBz3+JW+EnnHypLyGf8CHRnZVF/RtqR77eqV6e9ZGr09JiINtOflGUprXFSysHmTiVZmzjRgEvYw/tsYhL8zKhiep0LX3nLNht+E9Dh2kDQ8yfiASfMaIH+5rfPYMiB5gwoYjW4wnS5Zml1R26su0HJult5kd/EK3HwXfg6Ec1I4drBQqCCWs0yXeOrjgQWZoHUOo6MH0W/wx8aqzq5txyLsxY8CbokjhFVZHRdAMZA6c9B5Uw7IYeg3rJzp7Wt7D8if/uqiXOrFzqvrDR4vUl4uN3xAhwAl6fvEge52ot2F3nmrtYfyxybBjmhhTjGwa4gZM/qDX3hp/bB2YWRs554B/o8dgaFaFFsfxEsMxfvfD8gxoDF7ruLLeLoKBHWn70RsPH36ZoRxUampq7GcrJCxrdu4zxkA3vKelDUP8ZiBrDzIreXgN233Te+tUHHJGOfHHR3iQfTSTF42BvB9fsCQsmdjxKHQ31v3hinOYGvgP/NyV/Yyp4Dvema9+dblnuWBziTefxCAzEaErO+p5kKjHqhH0qPvBg9y3dQrCPKq6FofMqhnW+sdWSpuF5PpncA4FhiazjBZgDG5dweM36+V2LD6CBkHbdNgEDQku+ZzpGW5lOTwd2qy3p4fZLggxVbBgkrBb9X85tc+QBj8ZX5uy9xulJr0MdbPeRNCL7FQccgbG3hrVqqhe6SWzp5FoCkcFY9Pdrm4Uj4F8td5vLJSnB80LnTwpP8GqBxNGDTQMipsmzlFLNnvfJliIvXIBY17NMjJ+StRzu1KKHypYmNSsXs3w5k5f446BPGvdblUbP0bdWxxd9OG3ZiH++QGNAI3YJfhB+85afrO8g7BPXai+uY7F7yB6oz+11LofpTv1Kb39MuxbE2qnk/Fm6TCMXJ2bQuvmGssxghB1kxA3S27282EcckmJN+/DK6xxyDv35ZfOuNodf9y9RYNybwbM2vTb4cTxvYGss5bHYVA8COVAf4Hu0SEXlYaGdZPUpOsHqfq1qqtRE2ZjmrYkfsoNaEC9+vNaddubGYjN8f2Pt38rWGAw9lM1qtKOeg4XZw+XoEe86qIXyrAOTdTKbftcKe0zB/HH9FpzZiiUADUL+Qt0FvR/IeU3yyMN+gX/BxZgOQv6HOP4l1j+EzqVZd641I/pRVqCxWRoKcT9xjDETr/WrdCrEH8H1kBf2PPRhMoAy63xN7SdC/HHJrwp5swdPZl+YXO29yXe3IhDLig6pBZkZZcbXmGGuhG/2DplGsh6QEzVIRaVGgbST7phkCo6dEhdM2GWKz/ofI9rX5+t/vb5MsRAb1XnPTtNPNgVwE8VLEx6pnvTUc+snNHGJwby8GNKBmWnvcj78ovU0s05YcMrrF2ctvncg8xSm1ish2ro9dnQ3CiOWwv11uoOjdPbd0Ens8ybXpYGhHMfqAPUGSo1grE+B+qhnxurq1kIQtSe08Liw656kDlbxepBczf6o2EIHV+8Dl6XeLPCWXImNNodh7wEM6X5MJKjMZDNWV6GAQYlxIKD8TQYyX+E7jHl9In5kWOa1levXTvQcP+PgpHsZPb91JU71BlP/aRm4sv6t/N6qE/HjjAyYS56YYYkDMZAHgyjzTB6vO6gFzZRr7r7iXr0INdNqmbUo/QDnHZLxszM9NXOxvfPw9Qqo1kGhtQ/NuHUHzvq+d2DjLH3Jizeh17Sm1hB4mPvzkgQYo8/Jm5XFWKYBfM+8ou8j2/dmZdveFb95EHmDOsQeJF/Xbvb1tC/jCgT9I7ophcED7KGCRif6X0Zw2aqUtK3dUP1wlX9MC2cq0ZPmmN7MDn/0/x9yjLDAKcRQ8P4qiFtjJjVT8YMV52b1Ve3vDHX6PQnjpvoYt2I3zzInObvir8ly5y5bSC3buyfcBMm6QxB7Ns0hz3IrH/MfCD+/40Ewyz84rkogzHQcMioRY8xYJWlNJsg+B4zxtXNEAszUa8A4R2LN+X4poKFn2KQzThklmRbud2+piqM+07HjYAZPlEWDeskGcl8fin1Vq6BrOOOj5IbJ+dXTujcVD12cW/jTuuud+arYpvuttbDmLvoxenq5Z/WwihubRjHNIitGZ7vjB6izuvTwuj0x8oafsn29H2JN59UsAgNs1iCwdrNRD3DQG7kr0F5+DFNjAxz1md2soNeN8QhMlkzEgFpFsLGHQXmA9zo8ANJiIMQKKcFZ2vcnsXq1yaldDbJLzWQ/eRBdiIO+TCir+hBjsZ7bJbXTa3HUm8BMZCF8JzXt6X641nd1JdLtqo/frI4bm/uh3Oz1JlP/2zEiL54VX+EVfQMm/HJbU9c2kfdd3pn9dnCzerSl2YE4Ufd0/hjeg79ULUhbKJevnuJejTEaSC3gQfZTzgdh1wIr9E8xB4OaBM+/ji0WYjPmQqj+CEsa2PJpLr3oP95fE6CEFOIRaR2w07StH4t1QrOAXPK30v86kFOb1jHuEZ2lbTdhBsBzspFayCTVKNZiD/GYTGQ4+CGEe3UrSd0UG/N3KiegEe3oslDd787X90zeYERj/nFnceq03s0K/MYTo/fdsIx6iUY0qtgAJ7z7C+uT9UHhTXwVjD5gEkafsPsqOdWoh6nrRjC45cKFiYMf2Hs2TSHujgxOe8AZlrCNQgJrYXMMkc0qH3MAxDb0i2CboamQA97ekaCEANrd+5T7V0OrzDpjzAL1kOP16Flh+HI3Iv6tWp4eh6RwixmrrMnDtm8GWF4S7SUNAsJSJk33RhEiMB9p3VWlwxIV09/v1pNnM58xuihUUuv8SfzN6m7T+mk3kb4RCxtJ3/XvZn64NZhqnrVquriF2eo/y2Qev1BqGARmqi3yKWbG7M8oV8qWFhv+BhmMQMeZCd+uGYjvIKwxXRZsB0t396NCjVxcAL0Jq7TxdBF0CuQhFgIgUmapkfRq6RpejL5/5shXV57kP3QYjpSmEX2/kK1bGuOLQYyk8K7WEJFy4PjcCA8yBh3GeB6rkvnEkj44/7383uqU7ulqUf+tyQqI5V3Zi//tEZd8Px0VQiP3rs3D1V3ntKxQl2FujZPVp+MHW5M19/+9jz1H3iy3W4+4VcYG854Nz/GH5cm6uHv55YH2ayB7IcueuEG5Z37CtSKbfYlh5jMWb/H+MzlJYmYtZB9HrJ0re5qOkN3Nj0bit49Iwg+SJpma2MvMJN0vW4YQg8yE9f8yND2TWyLQ86AgdyndYqqHqb2fFmhMHtgoPuh2kg0Z80Sb89Cx0L9TDl+ZgGCf/xnLu+rBiLG8Z7J89XPqzgDGh7eGY16bZb6+5Tl6pSuaWoKQirKm/otjyYIan/zpsHqov7wZH+3So15a67aX1AU12smApsxCLH+otvlhGKhZ8tk1xL1aCDzHsxviSGEHmQyzeZyb3SuskFIed5jkhYAAxmf5xqok+5myrbPz0GRBxxB8BFrTQPZo1k9ejLrwKPJzm5ee5D9Fn9s0gyhZowR/zXOOGTOFizbkmOEtcSCWerNDzN50RjIw6DuIZ2bHnPypIIIk+deGTXAmM6/+b8ZYWOCWdt45FM/Gy1vx53fwygXl1LHnkxextj++6Je6g8juxqJgwy5oIFYmVmtK1h4NRjHkqi33oXujDSQOa0XrpOc1/DHom3jOkaYhd0eK3qmB0VxE8ofBr+3m4Zz4iroJV0L+RToWehYb89KEKJjLcbkKh4mTdOZ1adVisrw0IO890ChMeb70VFhMkTHIRfH4bhZkJlt1J4323xHy2/d9AJgIMNbcWIYneTGyQWNBrVrGC2pWb7m2tdmG4MBYWLUuM+XGrWNG9etqf53+wh15eA2ttei5evddFx7NWHUQKMaxjnPTvNFSRsv44+JX2OQSc+WJaWH3Aiz4HfCj9U8TIbBizxz7W6jFa2d4RUkUgc9K410Dc6tPkkQicCTUB/oFegOjMWPQjM8PidBiLqCBW+Gw1VocgsmjC3bkuvZLKvpuGqZ4t+xeEj7Rir3YFFcnXvnwEtfpZza8+FINZuF5ATAQIbRlQaNh4xWo1h2g25w1vm8RQAAIABJREFU/tSCCWsV//eGwYqm79XjZxnTFBe+MF298vM6dfWQNka8MJOznOTELk3Vh7cNM6aSLn35V/XRPM7EVj7WYDBu6EG9zVjomFbPtY56mUYNZP8OysMQh0zPykIbrwUT9PgdiCbMhjU4Gf+23d8hFoxFuR6im2UcxuJZ0H89Pi1BiHpGx+sZPSbq0TO6INPdLqZHlXjzsQeZlSzijUNm/HGnpvUNx2EsNE32Tze9aOZaX4e+glrox6xndpdjZ5QAMH7n9esGqez9BeoyGKic2mZt47+e18O1O2ca4R+PGa76Yjrp7ncXqH99ubzSJe+xSYifvcduJuqxnOCuvAIYyHV9PyhPX21fmAW9GPQeRztbwwxqP9dCxudIxqI11AZqC7FWoK/r0gmCmQ/AWVWvEvRM+rZO8TRRjwl6xK8xyKajrwOcCjMqGIdMW4PXN9bwCsJZdubKBMKDDJrgiz3ZHISxznkJ79MLfQ67pE24dqC6uH96VLWNnYCeU3qzLx/USr3w4xp18xsZhqFUmabz/G4gk16IQ2b7UydvYMwudX72IDeuV9O4WbArUY9JHvRYDYwiQc8ah+xnAxn8Ap0NLYQuxXjcGRrl8TkJQrkwpjSvoNizEm8mzPuh8edVoh4N5JqYNWxSz78zm2ZlodmIQ65IXXjm/zBEI5YGISas5sUwi6B4kPPgtaBrx/j1xvoQLLyZmwgYg+ER+/fFvT2td8jpe5ah+/PZ3dR3y7apy+HRZnZporN3f6HR9KFDU/96TK2JevscTtTbuFvXQPZxDDIZjkGZCTR2tFDP2GDWP46+SozRbtrHSXowhntBt+nuedIdSAiUw4J41STECg03jjNelBA3K1jYnYPkRLm3PNzQVGR2szT3owIGMmGoG+tlB8FAvhf6FOqAP+g0LCdBtzt6VoKt8D/idcPbqZeuHmAE3d87eUHCh1us2en/BD03O+qV1kD2u4F8TBMjqZXxa/EyG4M0PTU9WpRc32hgLWT+KOQeLIz7/R36v9wDmofVxdBSrGdwm9fnJQjRdNAj7XxQdpMGMpthmGXn3CQLHmQ/xx9bE/UqGofM8bsxZrAr6pAxuukFpIpFBhbH63JvbG3aHds4vScEDDYzeUiXgXvqu1Ven46q7BUsrIl6NOQWZe11tIJFSp0aKtmHrU2tDGzXSFXHFNs0G+KQ56zfbZR04ixKtPxWC9n7wTkCL0P3YAxuA7XWDgxuEwRfsw4e5Fo1qqrm5TTscQOz9bEXYRZGF70G/jeQGyPkrXNa/QrVQzbjjyvqJWcM9I4ghFjgA/6MxV+gVtAGDMr+dK0IUXHDiHZGQxEayJ8v3JLQFSxYssuv3YrcTtSjB9lvLabDUa9mddUbRu20OLs4sYTT4s05MTfhCUCzkLoYg38wH2D9R27z8HwEISrorW3buK5RLcZr6DhJrlXd9UQ9ho4x9C8IHmQzDpnhEpzVi5Zd+0pyPyoSf2z1IDOpvCLxz3YSjWuFCSArdOem6TCY50BPOHtaglPwjo5NSvq1TlH3vjfflfJiXlWw4GAcS4tLr+OQl8Cgcyr0hQZyqwAYyGYc8qKsbKOgfkWZvzHbKOUUTQe9gDULWYv/w3+E2mo9jG3rvD4pQSgPVrDwy4wejXR6OO0I5apYDeRgGMhD2jdWB2DULwjT+CwSczH2krgM5OSauPlXxs2E30Ms1mLxDfQd9BPEX9muDp+X4CDsuvfi1f1VwzpJavSkOb5o6VgZS7y5lajHxhuc1vN7gp61YQjvE9hxsqLMQngFHVWxDtKMQSY+rmTBGsip0IfQR3r9Ok/PSBDKgR7ITIxBXlewsMIWyKsQihfPjXiFS7wFxIM8BHHIjJKIJQ55zobdxuwtf9MqCpP0iNel3qIJsViDxcdQGjQe6gGj+XSnT0xwFn4BX7lmgNq9v0Dd8kaGyi9KnMp9nJZhWbMgVLCwlgUkToRZbIE3tAgWp59LvIXWKWWsYjxxyJwW7NIsWdWPMea6dlI1Y+rVryEWGHv3QHdg9UToOKzfyW1en5cglDeDxRkd9gjwC/Qg00s5PzPb/SYhAfEgp8CJ1hXjaCwGMuO6mXgeT88H1qMnXifqRTP//DS0Eboc4sA8CkZzB0fPSnAFfokfv7iPMc308EeLPSl549RgTIMwSB7kjk2dS9QrrWDh4yYhoTMcjB2evmZnhT3mjC2Mpf7xUaXefGogY+wdCC3C6gJoEdYXQP29Pi9BKC+8gnjdRc8Kcx04y+RmmAVDLPieZihXUOKQM6IsvcmZggX4DaN3Ph5MD7LX43A0IRZPQRdj9RSIFS0e0d30hATgzF7N1R0nd1TvZWSp8b8kRihjkCpYmFR3MFGPFSyCUOLNyrAOTdTKbfsqVCx+2ZZctb+gOKb6x0c3C/Ft2BFn8W7DmNyWwvoY6DWPz0kQyoRJW8RPHmQmBHOWaZ6LiXos8cYwLiZmB4WhiEOm4TtPxxaXBcvIct944o8Jm6gwtMP3HmR4Jx6HZmKV6gP9Cero9IkJ7nEXDOTTuqepv09Zpqau3JEQFSyIn+LdoqFXujOJevQgJ2FANuNrg8DwYxpXuAbnbMQfk1gT9ALSLCQXhjErCxlgnZ31cj08H0GIqkkIjZ4Gtf1VZrJfmxTD8GP4h2tNQgISf2wyCHHI9HpH03ba9MbHayDTYcSW016XeovmNuZX6BwMxKx/fAM0USfuCQkCM3r/c0kf1Smtvhr71lwjwS3I8PwZwxRr/KkfQl6YqLfO5kQ9dtFjuTu28AwK3Vs0MGKBp1eg7TSTRPh5m1ew1ihvJHbsy3ftRzNGZsFh8RJ0AnQ89Dy2/YhlP8rrkxOESB5kP3TQC4WGHMfcldtyXUvSC0r8sQlr5/O36dc10RnIrRrVNuoYx4vRLMTvSXowht/DYjAG38e0znbhvASXqYvppldHDTA8jTdNnGO0ag4qQatgYWJm/dpdeo8e5CCFVxAa84x9mxZjHDLj6NlBL9b6x1Z4c0Xj2OsSQxHgLF4n6M863K2rbuL0OPSYh+clCGV20fNTeIVJ/9Yl44Qb9ZA5prB8ZNA8yGaYxbzMPeoAQtfKGnvnwECON/7YWuptm989yDCI/4HFndBSrTv0NiHBSG9YR71wVX+VuWe/Gvv2XCPZKWjwPyljkIMWXuFUoh6vB2OQg1LBIjQOOQtTkqxIEsvNAMsWVjS8wu/NQvD3PLEMneT1+QlCKCyjtnNfgS/HZHo7GfrhRqIexxMmj7cImAeZDIGzorD4cJnXiWM1x954wysC5UEGZ0KnYvCdQGH9dL1NSEAGtWuk/npuD/Xzqp2ISV7u2PssyMxWY96cq/75hb3vwYE452BRID3IjLvq1iJZLbTRg8zrkYvrEUQD2YxDjsWLTO8xiceDHIBmIYIQuAQ9P1WwsDbOYttpN1pOl9ZADqCBPBDjKWf1ZqyNPBabXvj+bSo+9oY6KnZ6HOoWbSplimW94tWfhUBw2aDW6tphbdWEaevU5NmZtr42E6iumTBLnfvcNPXN0m3qxalr1PsZWbaXEwqigWyGWSy1KVGP2dkXvzjdyAa2667eTfg3pBdheixF6vH9YiLQMXH8/Zv52INsg0FQDZoHfaYfPwJtguZrjbTs+yC0GloBnWbZ3p+l5vRzT0PBCW4XXMcck/0YYkE4Nq7HLBVbJLtRA5n5EUGjHkIwmUReVtI0a8/XTaqmOjerb8t7cuznz6DTf5d4DWSGU3BAfR2aqEu9/d3Z0xK85uEzu6oRxzRRf/h4kWF0xDvN/ws80pe+NAMG2wwYgHvV/ad3UbP/cIoR2/Qw3sOuJAmzgkUHhCsEkZ42JOoxNOapb1epi3CtOS329k1DVF+b4sLchHbXcHwHZ8CDHG2Nbt6Asf4xE08rSuN6NQ1viY+76cUDw+WWhWx7Ate3j9YUfe27YXEZ1F3PGj5P41rv/wI0WlczoqRxlFBmBQv+f/LrLBYbhlhbJDvtQQ5iiAXhb/VChP/l4fcpHAy/4O+MXcngqWY3PQ9LvUWTpPc2FkN0a9MPoKHY9o7TJyZ4P93/7BV9jekgdtoz/3PHAo2ab+ElPv/56eqq8TONNsp/Oqub+vm+k9StJ3RQDerUUE9d3gd3pzXUbQi3iPQfL9YEvdo1qqnmASppFrajXgXjkDfgGl+MG5Envl2pzu7VXE2581g1BANbUGGiHsNEVkRxA0VPA2+QKlr/2IQDfCqM5K17/ZekByN1DFQ6o4f1htBtUR6brsPjXo1i93Ohd/B/OB9igfTV0CC8RnMsk7FtxuGSu5ZJ0HkxfxChUoVYtILXNKl6Vd86Jdga2ek4ZMboNqqbpOokVXf0fZwci4vg0jXLaFqhU2f51pzSmw07+K2bnneOimi/sUOhE6Dj9bpQCWCbyVdHDVT5hYfUjRPnqP0F0RmwDA+YsmiLGvn0L+rGSXOMOKJx5/dQP913orp+RDujna+1Y87Tl/UxpuH++HH83fxoIDMZJB4PopcwNIBtlmNtGMLrxnCYkU/9rFZv36eewjV98rK+vqs7Giv0IJNpUZR7YwY1qWgHPStpiEP2cmAug5vwty51dek20zdFeeyT0H1QaPbtWBi+C6EJNLj1tpaQNb4qS2+jssJsF4QyxmT/zuixJTLLSjpdySKIJd6sDEBsMW8kwtVDZk4RwyHsDOUzS8V5magXTRUL1tm8BWJ708XQzdj2XDQvjv1O1/FrjFV7IMzzVXQM22o9QBt1PLFsBf0ALYOWQHdajokYMyfYzzEIVXganuQVuDu8d/KCMmNjObX/4dws9bsnfzI8wvmFxeqxi3urH35/grpycBujhXA4hsEIuvPkTurDeZvU5DmZlbLEWzwd9XbnFahb35ir7vtgoeGB/vKu49S5fRLDZuEPStvGddT01eUn6jEUiF4q1uyMl2bwXvg0Sa+qNeZXhz0klXcQ9jsLi+0wqBkiZ4XhEh10+bgtulyccUiYl+F//kjbw73naGgOtWNH8BsQCbHD3wvOHLb3afyxCRP1aOQVOli5aXPADeTacGz1aZUSth4yve8clfq2tqarxQdn8cg2PxvI2mt8GgbW1yisj9Te5DLRAzcN6TMgxrNdruParJxhiWMbrQdrQlflvXi/rjq8Y0zIsUfFzAnOcWLnpurBM7qqLxZvVU9/v+qo5/OLitXbszaqkx6fqu6BEV0d3ttnLu+rvrnneHVR//So2mqOPekYI+b5T58sUcu25FToPNkrntNYQTaQSS8YeEtgIEeTqMfOh6fjhuS75dvUQyO7qLduHBLoQTjSDdTMdbvLLTvIChZ90lMi3ojFmqjn0xjkr6DJGA9PhljWjSFwX0Zx3HDoHByzHkuGyJ2E9Tcwfm6DiiFe3FegQRbPcCvL8QzP2Ky3p4fZfhR4zZehAVRqamoMH1FIFLbg/9BBzEC282GJNyv0fOYXHTISpJ2AM3xB7KIXLg6Zzpucg4VHzd51TqtvNBWxiyQ4OxoiDNPvIRYroNaWxxw0F0ZxHAfa1ey6BxXoQZlxbVb4eBJj2QA79qUwxg3rW6C53AHLXJ1UkhgusYBy47Ht1AX9Wqonv12lvkD4hGmQvj5tnTrh3z+qBz9chJCMGuqVawaoKXccq87u3SKmYH3u+yTCAhgSwPJvjGmqSKwbIzT8WG8zFugBzSsoVmt1eaRw8No/8ukSNWrCLOOafTxmuBp9XIfAhpaUxfAOTYzvQ1nl71jAng1W4ql/HBpiwfJ40YYVucj90PfQrdAY6DsdNlEmGEcfhNKhtjr57nusX6Vjik3O17OE5FPuh+drQu20E2MWx2Ysc7FtiPZkXwN9YteHExKzgoUfu+iFtpwmTsUh79lfqA5gzA6682II4pDpt5kNh4UJHTnzcN3sjD+2lnrzMkkvmmhxZvgw1GGWfjwQmoHHn+qB95wIx4WLYRscxT7cVmKBAbwPB/S+0MyQmDkOzHO0p3lPuOk9LCjVurXVvhcqAn8L/35+T8MIpZd48ea96t3ZWUZ8MWM+/3VhL3VsxybGfhWlCaZUnobn+YpXfjUMbsYmx/J6ZovsoHuQzUQ9GnwMcQllCa79Xe/MV6sQa8xyfA+c0cWIo0tUhrQvSbpjmAWnQsMxH9OjTCBhvU47SNMZ1Ayz8FP8pPb0vmCZbYuXR/F/jOEVnK6gd/lm/T4MbZusm0PxLmEMPc36GBrnr0P8tf9CSxAi1kDu4HOnBdvSt8BNMeOQr1e8H3SmxFvQPcj9MP7Ss8tybyd3TTO28XcoFw4MuzroWUk1moUc9LWB/KcKvnY0sWpl7oMBup6unHEXBmdz7oM/DH/V+/1Vx8xdH256DwtKDRgwwLtK0wkEjbCXru6vzn12mnruhzWGQTz2xL5qsI1VElhx4d7fdVb//mqFGtyukbpqSJuYygnRnvZrvc2KJOqd17flEXfqr/y8Vj329QojgXLi9YPU8Z0Sf+qaZdcYl81EvbEn0ZEZPv6Yf3sO4HZgNgth/JsfDGQaqxjTLmH9YTw8ajzDc72ifS3s+yMWP+r1q8vYbxwW48Jsp2OiR7TvJ1ReOCazNi4NHb9DD6hTDUM2ZZd0Aw26B7kWbIB+iDO2JuqZXne7Zu+sMImfSee+NZAxGE6t4GtHimGLah/8ENTQxvGbOIcPLeezzVzHPoyZMwreC+7AL+wHtw7DlFGBkfnrBLce38EoJfN//1tqJAVEm3RFDzIHICYTBBmjox4T9Syl3pjgcc/k+erXtbvVad3T1D8u6GWUDKosDMfU3qRfNxihJRykQ5mtY+BYOtAOfNhu2kxUZrKdIASqgkUQeskwDvmzhVvUlr0HDI+ynTA3JhEMZDK0fRP15HcrVTZsADpqaCCzXbcTda5Z6o3tq+kc8iJ80MnChLOhjoxfg5J03JsRlmGBj6/R1SyYjLeXMW46tm08tAyP/2M9oIyYOcElWOjcKeOY8D/Cfy7pA89hklENIzQhIFErWITW5mQoBQeGTxdsVqc9+ZNhMD96US/14lX9K5VxbJZ7Kyg6FDZGkK1I6fmxK7ziiHbTPjGQ9bjIO4PxWN8QKq/PTxAihVgEZUbPnH2auyHbkRJvdeC4YZ5O0BkKZwVzfZg4TTI27DaunRM3Qeymx9A5OuS8wDEDGYM249bG6qxrJtlN1nFtt1B6N1agWKuL0NMbfJsl4/pqnWkdWs7tUd3mlImCJ0J3O/UZBO+gAchKGBxY7n9/Ybn1kWlIrtmelzgGcnqKkah37euz1R1vz1MdEYvMph+XDGgVCG+M3QxEuA2ro0wLU+6NBeqZxGfnFB9bq1J+KvWmY4D34+/v3N2pINgEZ3s4fgclabpbi2QjtM2JRD2jggUcS4kwdvdu1cC4ToxDZg4S23TbWf84XC1kr0q9lRtigT8ov90HdHIIH9OoroXHJUE1ZaBLsE0J2faiZf2wzsQOPe4XvlWE14wYMyckFuyIdt9pndU/vliuJk5fr64dHjl5gp4+Zgl3aBqMwTgaDzKhQXjPqZ3UbSd0MEIvKis0Vnsj3GZamBqcZka1nR5k0hTTez5sFsITooPgGyzzLOPiHd6dkiAczQYYTiVVhYLhtGA50l5wTGQ40DDEaBIS8AQ9E5bRZNOQXxGHPAzeZKfij00PMuE43E0lO/IeZRHNLy7LCFmDS7j+rTOnIwhHctOx7dXJXZqqcVOWGYXcE72ChUmntHrqDyO7GvHed5zcsVIbx9Y45EVZ2WrvgcKj4o/pnWHoj50YtZB95EHWfA79EfoJYtMPiklzguDTEm/BcVowVGApQtvo/baToHfRCxdmsXxrrvpm6TaVhN8mp0IuzVwQr0q9RfOrS29xaRqhXrc/GlsQIsQjP35JbyM5cMxbc9Xe/eHjkdfoTNegTOeVB6fibjquvZGkKPzWMIQ1OGdaMqg5CcUKFk54MGgge9nFKQIp+MwTrcI2Z9w3ghAHZh33oMQgE4YKFBYfjqmTaXnkIfwrG79bieJBNqtNkY/nb1I9WjI0xZnEeLP6CRP1/Gog55ktoAnW+2NRkpIpCC7ATNlnr+hrVBT4/fsLwsYjr9mRp+rXql7anlJIPNjGlLFv0y1hFswOpxHLcBy7YbMQfuei6WjoIqPCbLvW9bMQhChKvPEmsy7Co4ICS5gRu+KQ+Vs1eU5Jq4f0honjV+yV3sBIOuTNhFPxx4SGdzJ+172qJhTNN/cu6D0YxmaJNlaRuNS5UxKEo+mLqa8Hzuiq/vrZUjX+l3XqRoReWFm7s6SCRSIkQQiRY98YZzx9zW+JeiwHSNisxm74484M6l15BZ7XccX3+nIsroBYFchaDag+dHRgtiB4DMfkIHmPzZrrPGc76iHvwbjxwIcL1VdLtqnhxzRWp3RtasMZ+ideeyDG4qkrdzhqIJd20/Nrkh7ugGZjQO6C1c4QrY/l2BZd3S1BsJHrh7dVs9btUv/8YrlR1N3aFIIVLFgKTEhshnVoov715XIjaYNhN7PX7zFmDjo1pZ1ofw1OQu+F1wYymK47jDbRzZFMciFW9BEchF0tWdbqqiGtjRs1oXzPKT3IZ/WyVmUNzkzVTzD8+Bkq6nBh1092nN2Vl68eGtlF3TiivSd1fJ3k+E6phrOifxv7Z+/8kiwdMcQCX4yT9PICLM6GOkFsY3W23iYIrsLB6tGLeqvmKbXU2DfnGnfohCW+WMUiUSpYCJGhJ4awxBAx4o9xs+TEj4+fmoXoesfsfnclNJMNnHQTp2W6wZLgEJm796trJswyZq/OevqXMpOFhRL2IOaWybRB8yATekR37itQG/F3jxXWav/HF8vUleNnqjo1q6mPbhuuRh/XIeGMY3LN0Dbq67uPd9x5QEeIV7kgZcUgH6+XNI5DJd2cBE9oULuGeu6KfsYAdu97C4z40LUJVsFCiAyzpRmTxvJ3vEFatX2fI/HHfmwWopkMGSU3NUy3f8+jc0l4ePN948Q5qqj4kPrnBT2Nx+c/P82YxcgvsrfSQSIR5DHZDBmYG2O5N37mC1+Yrl6aulZdNrC1+uz2EVF3gQ0i1RFm4cYNEEu9MUmvvF4IroZY4GT+rGsef4F1DsqC4AtYq/IPZ3ZVf/50iXr557WlU+FBHIyF2KgGTwxLDDFRz0ykGdTOGQOZCZ90/GzzV6m36hiPS9tKcV13KhVshh0a73x7nloNw2fidYPUiI5N1EiEDPwNnuQXflyjvl26TT12cW+jPrdwJAyvCGpVoY4I12LddY4v5/dNjzoR75FPl6qaNaoanU5P79HMhTOtHDTFTF4BblA5I8GEfd9UsdDNQdgNTxB8N71zZs/m6t9frVAfZGwyuqy1aZw4WcJCZBhrzuoVH87LMmpwmk1VnPCQNIGR7DMP8g4YxOeYD7B+LhZHtxcU4ubRr5ar75ZvV4+c3c0wjklyrRpGmNfr1w0Ub3I5Jd5qVKsSyNq/vAlnHHJGFC2ns/cXqNsQ7nf/B4uMY7688zgxjh1rFpLvyzJv32AQ/j3UCmpkyvEzE4Ry4pH/cWFPld6wtvoF0+2tG9UxMmuFxMfs3jRl0Vaj3JBTNTjNOGSf1UK+BXoI3/9MaCPW74du9vicEo73M7KMqfKrh7RRVw9te9TzJ3Ruqr66+zh1Uf90w5sssclHhxu0aVw3sA2OmAC+QrewjwTzIM546mf17bJt6sEzuqg3bhhcGpYl2G8ge5ELEs2393rdDlo6Nwm+gt4cxiMnVa+qjmkq4RWVBYbSmIOmU/HHRxrI/vEgY1ZvDTQEq12h7lgfBq32+rwSiYwNu9VDHy4yEkL/BO9xJExv8mvwJuceLFIXIP70UYlNNlgHD3IQE/RMWCWJ5c/DJWQWYrqfMehXvPqrqo2b8w9vHa5uPj4xE/H8EmJBvCj1Fo2B3BUDcDursC3yqCEILsIkiMk3D1UPnylfyco0e2CW9HOi/rGVZg38FWKBz54GjcfqexiLc7HeDbrB6/NKFLL27FejJ2UYXc+ev6J/VLNSJ2pv8oX9WqrnxZtsxG5v2LU/kPHHJuxgygpvoQ1DaPgzEY+zBpcNbKU+u2OE6olZLKHyhliw/mY02wTBs8GstcQfVypYX5UDp9MeZDYLYZvYg4W+qVjwOvQV1EI/XqmbOQk2tARmxQp6CF8dNUA1qFMjpuo64k3+7SaDSVUdmgR3Vo9/T9ZWNytZGIl4szPVmU//bBj/L17VT/3jgl6qTlJwugQGlbo1qxtJk74KsYBXopluK10by75sN611ArZJNpQgCJ5xctc0NesPpxg/ZE7ip1rImia6qpBR6g3rDJL0jfUeVFgu8q535xtlA5+7sl+FK+KEepPPfuYXtTAru9Il6JF2AfYgk35tUoyOekzEG/vWPHXfBwtV7/QU9eVdx6rTewSvAUqQaapLvblNWbc/p0HXQum6c5MZYJMDPeTweQmCIHjObwZyvpF05APy4KRglqJRFBTrjEfe6+0pBZ9/f71CfbN0m/rLOd3VsR1T43ot05t8Rs/m6sEPFqnzn5+ubjm+vbrj5I6VogtfaYm3AMcgm4l6b8/KVCc9PlXlHChU95/eRY0+rr1R5UJwF6+66ZVVB3kiFhMxAF+I9Q9cPCdBEARf4MNmIfdAn0IdMDZPw5LW3EXenlKw+XBulhFTeuXg1kb5SLswvcnjPl+qnvthjWGAs24y67gnegUL3iQ0qhvs8twDEb7FOGR+lteuHSj1rj2kaf1aaoEHMzHRxCD3x0Bc+j8a6w2hvzl4ToIgCP7yIPukWQicFXN1l9NhurwbK1ks9PasgguTsB6Al5elAx+B95gJoHZijU3OOcAufNPVi1PX2Poefq1gYfe1dJu2+Az/GzvC6IgnzWC8D7FgmJvb3fSiMZDPwEmVmu5YZ9T6SOdOSRAEwR+wrTVLOXntQYaxcYEpPGSjkM5QJ+hsvU2IkU3ZB9TN/52jWqTUUs8j7tjJOuqmN/mkLk2NUnBMZEvtH1JbAAAgAElEQVTkEIsgV7AIrZLEJDHB+xCLg4WHVG4ZdamdIJq/fDUMwDVhGBsR0lhna5ySuhuCIAgJDL1gbGXutYEMzi7jObpVPnTrRBKpYkV+0SH1zuiBrrSwpTeZMc7fL9+uJk5fr/6QgKUpeV35fyXo8ceCv0iz1EJm/XE/GchvQN/hh+I1PRCzcQjjkwVBECrF4LzdYwMZDorrPD2BBKtYcfe7841OaRMQW+pmk6EWKbXVyJ7N1TuzMtWdp3QyylclWngFaV/BKiCCEI5UsxYyxmE3/79WjWJgfhSLv5mdm6C/6m2CIAiVIlHPBx7kIxqFQF/ox9IoJEYe/2aF+nrpNqO5EFtGu80NI9oZU8Xvzcl0/b3dKvGWKCEWgn+S9LxoFhJt0NUy6EsYxvdi+TMG5foOnpMgCIJvYLMQlnlzO0EkAtIoJA4+nrfJqChx+aBW6rrhbe36m8Tc2Kh/m4bqdYRZsOtcIrEO8cfMzWvrj5KIQoKQhjA34napt3INZBjDN2HxPvSS3tQS+tjJkxIEQfBTiEUBYlX37C/0+lSINAqpIPM27jGaPQxu1wixwD08rbJw/fB2Rke275Zt8+wcyHp4fDN325cwuHbnPtWiQW1Vq0bi13sW3IOhSEyWZgyy3zzIY6DhukEIvSirsHB/XkoQBMHDBJGt/ij1Jo1CKsDm7APqpkkZxmzAi1f1V0nVnatYEQ2ndU9TLRGPPP6XdZ6dw/6CInXxSzPUqU9MVR/Ny7LlNROpgoXgH3gzy0oW23wYYpEPo7jAcqLMKkiseSFBEIQINGtQMr23zYNOTlE0CpkE3R7twTiGVYnmQZ/px42gb6BVetnQsu+D0GpoBXSaZTtr4y/Szz1dxecFb2kIGhUrCovV+FEDVEMfNLCoXq2qunZYWzVz3W61eJM3jRAnTt9gtO9t16SeuvvdBerhjxep/KKKdy1nCBKT9KSCheBULWS3k6WjSaGdivGPraVrY3kqlrdB/3P2tARBEPyBn5qFsFEIxuHjdR1kGqYrsC2W2I87dU5Jsn78APQdXuOfeF2uU/cz+Q/Ly3RidgvoW2zrhP1oQb0AjYZ+haZAp0NG0qBd0Fu/anuu0dYXFn3JUqsqHlevduT2sNv0sfdOXqCWb81R468dqDqm+Sd95lLEQT/57Uo1AV7k/1zax9X3zjlYaDQsOaFzqnr1mgHq31+tUC/9tBbGeo5RE5rVNmKFxva+/CKpYCE4QlOMw8s2G4EMvjKQOWDeAC3SnZs4IL7q5EkJgiD4LYPaD5UsYKSyCOit0HF604/Y9lI0RjL2S8fiTGic9kSTc6ET9DrLd/4I3a+3v6Pr36+jtxjLQViuxzIZ22fo16QH+zy7DeSpK7er+z/gT449PHxmV6NZh59gPdeLB7RSb87coB44o4thALjFqzCG9x4oVL//XWfDm/3gyK6qb+sU9fv3FqqznvlFPX1ZXzWiY5MKVbBgFz1BcMKD/KPfPMgYCA9h8YqWIAhCpSIJ8apN6iUZrU59AL23NJKf14+v1ttujOLYJ6H7IKsbNQ1j/BaucAmDt6klGZseYpMsvY2GeFaY7UeB16KXmVKtW7eO4vR+46Quaeq9W+oZVR5KhSn84uKSJWsZF0GHsF4UZpv1OHpDz+rVPKb3dwtW0pg4Y72aNGOD+v1pnBRwnl378o3Y55E9mxmd4kxO79FcdYKH/ZY3MtTVE2aqe0/tpG474RjDEx9t/DGRGGTBKUdFXkGx0YzGre6GEd+FMWZlxRpjMO3lyBkJgiD4cHBmqTcfMBBjb2/L4+8xVi8o7yDscxYW23FsBtZNj3GZh4TZxt+DSNuP3nj48MtYUGrAgAGHY20MYDYHSGTaNK6rTu2aZniRx550jCvVHxhacQDx2PfAAA6FDT4+HjNcPfjhIvXY1yvV/Mxs9fglfYwugOWxdsc+VRM3k6xiIQjOlXrLV+28NpABB1RBEIRKj9EsxAcxyKAYBm4HGJ9r+ADr7bktiuNYiegc7D8SS87lJ2OdXVK3Ydlce4/pZt1u8Qy3shzP8IzNent6mO1CBbl+RDujccmHczepKwbH5mmPFX6HJ8JbfX7fdHVM0/Dx2HWSqqsnERPdr3VD9bfPl6qzEXLxwlX9VPcWv3mbw8EEPYZXROtxFoQKNQvBTJ5bYTwRq1hgwNxgSm/qqNc5gO525ewEQRB8kqjnkxCL/wf9AGOWscdTsf49xAZOZYKx+0EoHWqrk+++x/pVuiLGKL0bl5/odW6/DO9RE2qH9Y7QLB2OkYttQ3T1imssxwgVgHWZu7dIVhOmrXO8Gc0z368y3uOuU/jnjAz/tKOGtVXvjB5q1AC/4Pnp6v2MrHJjkCW8QnAKlnkjbpZ6q0ijEHoMpFGIIAiVBtbP3ZVXEFcZrHjBWMzx+gBE6+YOrc4weH6I42X/CZ3KMm9c6sc0opZgMRlaCn0JjdEVLJROEmSiNhP31tidoFfZoDHK9tOrt+9TU1fucOx9Nu7ar96dnakuHdhKtWpUJ6pj2PHvsztGGN7k37+3wAi9CPd/gEb0xt37JUFPcDRJj7hZ6k0ahQiCIERZC9ntTk5hEqYfZ2UJaCG0QFeZiPV1foSMEDosd0EnQ5wh5LJ0dhDr4yCGc9AILzWCsT4H6qGfGwtJXfw4OatXC8MAcLJxCEvKsfzd7SeV7T0OpUm9muq/NwxSt57QQb09a6O6+MUZKmvPkd33MvGYCZHtm9Sz85QFoRTGwTNhmuUE3UIahQiCIJSDWYJru/fNQr6Gx/FCvzfnEGKDP/zXDG2jfl61U63clmv75eNrfjR/kxE2Ydb1jgWWgrv/9C7q5av7q3U78oxScFZvt1SwEFzppoebSDdD3apWoFHIe5A0ChEEoVKFWJCtez2vZHGPHoPzMR7nQIwHdrd6vuAIVwxuY1SBeA2xyHbzn69XqrpJ1dUtx3eI63V+172Z+vT2Ecb/h2tfm6We+naVUV5v3c59xvPiQRYc76bnMw8yG4XsCGkU8rCTJyUIguBLA9njRD1EM9SHqkJJULJ+bHbFEwJMo7pJ6oJ+6UY1i915Bba97sKs/9/emYBJUV17vNj3TRxANnEBNx4BRNS4I6Lkub8Ylxh86gtq1KiJJpKYqDHmRVxI1DyNa8AYlcQlxhgEibuggCCCBkFFBJVNdgSG5f1PcxqbSc/QM9O1dPfv933/71bdruo6U1Nz+8ztc89ZHoyZ+XkqztmuUVssg8CT3zskOLl3p2CEwjbOHzkplQ6urd67VdMdp4MDqCn27UeUDnJOhUI0Q2EVllKVk7y0KTFnAFAytNYHv30NHlcmC43BfXdUgjoqWyA8zjukWyrO9+GJHweXHl29WOHKsHzG9vz+z2GWjCQ/NGlYL7jtW18L+u7aJvjF32YG5Zu2BAd0a5O39weobAb5tTlLsr0Uj4PsSeXNQbYSoxb31kV952hAfjls4wAAkhL/ZrPIMeZCvtVbm8ruJ73t47EVbHpDOjQmuyCPdG/fIji8R1kwSg7y0CN2V8hF7QqHvPHh0uBlxQoPG7x30KJxg7z/TXznoF2Dnh1bBpc/Ni04ePe2eX1/gGxrQVau2xisK98USVGdujkOzIPkEB8hHa7tY6UR4ZoFAJC8Sk5xzSBr7D3KpE3LRd9X2/2k/bXdx9OtQZFgoRC2Uv+Zt1MVwGuMfdF7y9hZqVm3IQdb+utw6NO1TfDSVUcFV2SpzAeQT8q2pXqLJswiFwe5gf7QZqV3tP2+9YVnEgBA8khIsZC9NQbbepAU2p6hpneM9kCeObz7zkH3ds1TKd9qE81oWSYmzV0WXDpgz1RIRNiQWAXCpn3E2YRycZAn68G/30ItXPeqb0rYhgEAJIlUiIUc5JiXYLynMfg+H4uP8PH4vTgNgvw7mlZ++t3PVgYTP/yiVrPHnds0CU4/INzy1QBRFwtZmKAZZKuaNNOrNl3mlZUuDNMoAICk0aFVY8W+bQ5WfrkxTjPO9fHYxuLLfTy2PigiTunTKZVxoqaFQ8bM+DyYsWBlcPnAHqnFpQBFVU1v1br4F+npP1n7XuZ+/Td6ttrbIrEIACDBX+/ZLHKM6awGSr/VmMw6kCLGFiB9+8CuwZ0vzAnmLlkTdNu5Wc7nWkW7W8e9H+ypMA1ztAGKhTZNGwYN6tWJLNVblf9aahC2outlcpRrnzwRAKAIHOSY45DPkGZrTB4u7ROnIRAuliGift061S4c8tTUBcGcRauDHxzTI1VaGqBYqKvnuax5o0Qt0rP0bq9pMP6Z9IO0wjYMACBJJKFYiH+bZ5krPpAe1Fg8QRoqtYjNKAgtpdUJvToGf54yP1jxZXlO52zYuDlVvKNnp5bBcft14DcDRUdZqlhIchbpfSo948faIJwWAEDJ0K6lLxCJLxdy2km20tKPS49Ku0inSG/JSb40VsMg79hivbUbNgWPTZqX0/GPTf4kmL/sy+CHg/ZKzbYBFGW56ZXrE1NJ7/ooDAEASHpcaBvFHsc5gywn+AQ150l7SA9J/TVGL1J/U89mcUdsxkHe6dmpVXDgbjsFI1//ODjvkN2C+vUqn9Oy4gl3jJ+dqmh3ZI8yfhtQtPnoJ8+tWXaXvDnIGnD/pqbSfEYalE8MxSIAgISSgFzIp0kjKlYy1f5ajdnmOEMRFg4Z+tCUYMzMz4PjFXJRGaMmzE0tXrrjzD7kJIaipV2LxsGyteXB+o2bal1psjYhFrd4FT1bIfClZPk2TaslS04PAFCCDnI0X+9lQ47wkIrOccZr46O2B8Ln6H3aB7u2bVplyrdV68qDu178IFWm+kBKPkMJpHpbHEEmi0odZA22L5m02Uft6dLfXGep79DQLQMASGixkLjQLPGpkmWxWCGtlFZZG5tBEDqWieLcr3cLps5bHrw1b1nWY8x5tlm1KwdR7hlKpZre+kQs0rM0b7und7S9m/WFZxIAQDJp36pxsGT1+qB80+a4TBgunaiJilZSS6mFtXEZA9FwWr8uQYvG9bPOIi9bsyG475WPUlkrenVuza8EipqydLGQlclwkK+QXpRjnJK2X/AqTgAAJTeDbJWmo/h6rxIWyiGmtHSJ0axR/eDM/l1TFfIWLLeIx6+4+6UPgjUbNgY/YPYYSiib0KIIUr3t0EHWYDxGTXd3ik17qW9sLm8uh/o4aZY0R7o6y+vG7f76dKmv93eRXpDek2ZK2xxybe8kjfOvGa1tk+sPCwBQ2xXURtRhFh5acao2J6t9TDoz3ef9UOQMOXhX+zwORr5upQm2skjP4cgJc4NTencKerQn+yoUP22bNQosg2EiZpA1+E5Wc740T3+cb0s5WeVlqn8nDZb2lWxAtzaTwe58m4ZKd3n/RumHupZVijpIujjjXHO0x+s1O8cWpfyb4w0AEGr8W/RxyJbezWThFGulQRl9x0dtDERP5zZNg8E9dwkeeXNesGa9fUQGqVLUGzdtCS4fSOwxlE5MfpnlQo5gBnmHeZC9tOm50iR3lh+UxspBrTQFnNNfmqPDPrQdnWtJ7U+S3s04xvZH+XtN1DGtpV20+5n2TfYfsy1Csa8UO/m5ds6Rfv5IycI+fpzDzwEAUCs6KAbZ+DziYiEaB20MhhLHCof8/Z3Pgj9P/iSV3cKc5dMP6BJ0bWtpsAFKJ9XboiQs0tPAbE7uT7Vp/6L+SXpAmien9XoLd6jiVHNoP8nYn+991TpG1+jmpVXf8K727kCbbda2y3ZxL79qX0dOXrx4cVU/IgBATuzUtGHQoF4dhVjEFoMMJcz+u7YJendpHTyoMIsR497XV811gksH2JepAKWV6m1hEkIsDDmZvTwn8s1e4vSbkqUW+mdVp2XpqzjrXOUxum5zv97lXl41Z3T8PVI/U1kZSTcAoPZY+V6bvYi5WAiUeOGQj5euDZ6YuiAVl5z+VgOgVGinULfFSQixkJM6Rc1y6X7p6owY5Df02iFVnGqzwV0y9jtLn+Z6jN67gTvHD+uaT2QcszAdhmGt9hft6GcAAMjnQr24HGRb26Gxb1MsF4dEMLhnh6CjnOIVX5YHFx25Z9zmAMQyg7x0zYZUus0GVZRfry25vPNpGpCPlv5UcYGe9qtaPT1J6m55k6WGHsv8dIVjbH+IZ7OwxXgr3PGt4w75e9q/Lcs55/i2tX/N4WcAAMgLNmMXY7EQy/hzc5YFz1Ai1JdDcMdZfYN7hvQLdmpmH60ApZfqbYtiDSwnfdyL9BZoMLbqed0yj5fj+ouqTtLrG3XeJdp8TrKMFg+oz1K2Xeiv363mWekb0hxfmZ1eiGIz09+R3tHx07zvJzrHjv+1NFr9qcwa0mk5/aQAAHnKZPHSrNjWNfTyyYb7NAbW9TUhj1Y3BA0KPxYZoFRppzA3w1K97dKqSawOss3QrpAs1KJa7ro7tM9W6DPHOL1t8cYXZznv1Urik+21pWqOro4dAAD5LBayZsOmYNW68qBFY4sEiw7L6qPmXpMc5MPVPiKN0PZf1N5gi6qznafX7RPlZamRj/t/0bHXqv86bX9XWlxhIsLOGabGJiIspOP76n/O+/dX8wfJPpns2MtyyGoEAJDXfPRhZ7LIxUHurLHvuFCtAAAoENKLoiwOOWoH2fPL/6d/29bNF08/LB3mzmplCXHtk2SAxvLVvr7jVbX/8NdGqP+WCtfZ12eq95M6Ss+rr4fHP9/leesn+jXt8yH9XgAA0cwgrwo31C2XGOTXNTD+R6hWAAAU2OAcRZqhLMz2XPA3y1ntY2s0JCs/bTPIVvU0KzbDa86x75qDbKpq1vckD91YL32kbZuZ7u8Lo1uqb4LPGo+STs7DzwUAkBM7N2+of+LDH4MrnUHWQPiOmi1+zLnat4If6z30wcZGi4UDACgp4ioW4vTKcHS3Q/3fz2H22ULlLPXB73S8ZSKyaqaXqB2idrJXMF3m+ehthrhijvpy367YDwAQ2UJVKzkddqq3qkIsKF8KAJAlBtmIKZPFr7Ym+dkOWyMyWY5tlRl9PDyit1UsVfuk2p4eLnGDveythWycV0WO+lzy228r1qTGFHTt2rUq0wAAqp3qzRbpxRJiocH046oUqlUAAAmlScN6QcvG9ePKhWzeeW8PtTDZN3lW0fR8OaS/yeUNNH5bXvsXpeM8PGOTtNkX//XfQY76+b5dsT/bdSjWBAChpXpbmIAYZAAAqJgLOZ4Qiz19sd0dJm0PlPaRTpEGVXaSnOcynzm27SZ+3r88pjiNvceMjHzzZ+j1RpbLXttWz/hNy1OvdpXlrfd89RaaQS56ACi6GeRcslgAAECFXMgLQ04xVAkW79vMwyoC3+5os8DyV6syyBzhkR6HbBMjo3XOM9p/SOrtYRJzpQvsYM9ZP1qb70obpYszKvhdlJHmzbJXkMECACIfg61QyKbNW4J6dbNmBa41OMgAADUYnGcvXBLHfRsuTZPzaiES9qlwuMclm6P8fGUnybmdrqZPlv7vVHHOjWpuzNJvi/ksfhkAILYZZPnGwdI167dlFso3OMgAADVYqLc45NmLinhIw1jPPWyxwnW8sEc6BviqSAwBAIiZsoxqejjIAAAJob1ikM05tq/4bDY5Ciy3pnzkp9RYJTvifgGgZGm/rZqerQVpFco1WKQHAFDTVG/RL9SbKCf5gKgvCgCQJNr5GBzmQj1CLAAAajh7EUOqt6OkC+Uk24K6NRKFmwCg5Chrnh6DcZABABI3g7wwegfZKt8BAJQ0DevXDdo0beAhFuFAiAUAQDVpq9kLW5wXdTU9L9LUxXMh2/ZaiXEcAEqO9pqoWBRiuk0GVgCAamLOsaUZ+nxFtLmQFVpxrZofS8O8q4H0x0iNAABIAGVWLAQHGQAgebMXMYRYWLW7Ez3+OPAUby2iNgIAIG4svduiEMdgZpABAGq4UC8GB3mDpXtTu8VnlK1ACABAydFOY/BizSBvtoohIYCDDABQw4V6Uccgi9Fyin+vtrXa73r1vHujNgIAIG7aK8Rio5zjZWs3hPL+pHkDAKhhsZBV6zYGazdsDJo2jGYo1eTxLXKMj9HmSmkv6efqGxfJxQEAEpgL2VK92cLpfIODDABQy2Ihu5c1j+weukOMUwwAJU07zSAblupt36Bl3t+fEAsAgBou0gs7UX1FNHt8qjRbWiGtlFZZG5kBAAAJG4PDymTBDDIAQK0c5EjjkIdLJ2gW+b0oLwoAkMQ0b4Yt1AsDZpABAGpAB8UgGxEv1FuIcwwAEASNG9QLWjauH9okBTPIAAA1oHmj+ilZDHKETFZIxWNqn5K2TZvIaX4iSiMAAJKyUG9RSGFuOMgAAIWTC7mll5celNFnSUBxkAGgJMfgRauYQQYAKOlqepopPjeyiwEAFEA1vTc/+iKU9yYGGQCgFqneIs5i0UMaL83w/V7SNZEZAACQsFRvtkhva4HR/IKDDABQi2IhNoMcVqnTLFjVvGFSue3oQ2G6mjOiujgAQNJikDds2hys+DI1JOYVHGQAgFrMIFup06Vrwil1moWmcorfrNC3MaqLAwAks1hI/r/Jw0EGACicXMhLFFKxh9rUlLW2v6nms6guDgCQRAc5jDGYLBYAALVYQZ0enHt2ahXFfbxYukfaW87xArUfSd+O4sIAAEkMsTDCSPWGgwwAUCDFQhRe8aGagXKOm6mtq/1VkVwYAKDEQixwkAEAakhZ80ZB3TqaQY62WIg5ymsivSAAQAJp5gWbwgixIAYZAKCG1K9XN9hZTnLE5aYBAKBCqrd8g4MMAFDLMIvPI8yFDAAAX9EupGp6OMgAALWs5LQoohlkxR43lX4m3ev73aXjI7k4AEBSx2BmkAEAkkWHVpGGWDwo2XT1wb4/X/rljk6SE91YelN6W5opXe/9O0njpNnetsk4Z5g0R5olHZvRv7/0jr92u6QobACA+EIsLAY539X0mEEGAKhlsZDla8uDdeWboriPe+hDYHhGJb0v1eTioJpTPUDHf01tb+k4+bUHqb1aGq/+7tb6vjnB+3qFvv3sWOn/1FfP3+suaahk53T31wEAYguxWFe+OVi1Pr81k3CQAQAKp1jIBjmqTTIKhVjRkB0GQMsBNlb7bgOXvcdJ0kjvt/Zk37b+R3XOeslyLc+R+ut6u6htqb4J9obaHpVxDgBAbGNwvnMh4yADAOQjF3I0qd6ulcZIXeSsPuyzvj/K5USbAZamaXORNE7+7Rtq26tNVeLztp0f3kn6JOP0+d7Xybcr9me73lBpsmnx4sW5/nwAANWibFsu5PyOweRBBgDIxwxyCItEKiIn1uKE39LmQR5acZn6luR4rsWA9Nb5rdU+qbZnFYdnC9uwGePK+rNdzyr+mYJ+/frlNzgQACBjkV4YM8g4yAAA+XCQQ5xBljPbt0JXatZXdNVrXeWMmtOcEzp2uc550WOHF1rYhM0ee/iEzS6nZ4a7ZJzWWfrU+ztn6QcAiIX2ikE2mEEGAEgQLRvXD5o0qBd2Jotbq3jNZmcHVHWynN8yNeXuHFsM80DpJulp6Rzp197+1U+x/j/p2NvUdvTFeG/aLLT6VvkCPwvRGCLdUfMfCwCgdlglPRuDmUEGAEgQluVsa7GQ8BxkOaZH1fItbHZ4pGeisLUno/Wez2h/gm2rPV/tPOk0v56lghutzXclWxp+sYdoGBdJf5DM0f6HCwAgtjHYMlnkO8yNEAsAgDx8xRdmiEVmPmM135MO9ZnjV6S75bxWeXG9Pl1Nnyz9S9UcXck5N6q5MUv/ZDVVxS8DAESeCznfBZvIYgEAkIc45IUhlDrNwijPTWxhDXdKlq/4oSguDACQVNppDF7MDDIAQLLo3KZJMH3+ilQlp5ALy+3lxT7SvGDV8cK8IABA0uncukkwe+GqvL4nM8gAALXkqmP3Dl648siwnWNjqi+QS6HtA9W8FvZFAQCSzLBv7BOMveKIvL4nMcgAAAlHjvA7HnNsFfCGaH+e7+/qC+kAACCP4CADACSf4+M2AACglMBBBgBIOIo7/jhzXzPIVhJ6a4USAADIO8QgAwAUCHKMT5Rma/Mj6SVprkQeYgCAQnKQNZAfJ82S5khXZ3nduN1fn55ZTlXbD0iLpBkVzrlOWiBNc30jzJ8BACBB3CDZIr33Nau8m+cwZpEeAEChOMhesel30mDP1Xmm+qzNZLCXMDUNle7KeM0qNR1XyduP0IdDb9ez+bUcACCxlHtxj7oaT+tq+wVt947bKACAYiPMGOT+0hwN4B/ajgbzR9WcVGHFte2P0jG2Gnuijmkt7aLdz6SXtd0tRPsAAAqN5RoXm6t9WXrYvmXzUtAAAFAgIRadpE8y9ud7X3WPycYlHpJhYRhtsh2g/qHSZNPixYurYzcAQFKxSYW10hXSGOkD6YRYLQIAKELCdJCzZcy3meLqHlMRC8PYw79W/Ey6NdtBmoG+R+pnKisr25GtAACFwOnSHhrXNkojpds95AIAAAokxMJmg7tk7HeWPq3BMduhD4OF6W3NDt+r5pnamQkAUDBY2NnZHn42WXrFpHFxWrxmAQAUF2HOIE+Sumsg301qqO0zpKcrHPO0V4UybGX2Cos/rupNLUY5Y/cUabssFwAAxcqWLVt+Lg3Q5n7Sq9JV0pR4rQIAKD7qaLAN7823pmD7jWQZLR7QtW5U34X2mrbvNq9Ym3d6tgqLqztX/ZP93EfUHCntLNms8bV67X71P+ThFVs8B+gFOTjVFoS8XaL9HLDrLqnmOWGCPdyfYnl+kmRLEuzZVWNYTnFgGsuuUXOIZAv1prqT/MqOxsC4YQwuyue2IthTOPcnSbYkdgwO1UEuZGxxn+5Nv7jtSIM93J9ieX6SZIuRNHt2YOtbnrXi714oZKJsXxevVaXxe8Ee7k+xPD9JssVImj1pqKQHAFAg6EOkrxcHeVM6RnpHHy42iwwAAAWySA8AAPKInOGeag6TjpD6eZpMW6gHAAB5BAe5cu7J433OB9jD/SmW5ydJtiY6qu8AAAf8SURBVBhJs6cqbvIiIbdLkzSjXB6zPaX0e8Ee7k+xPD9JssVImj0piEEGACisWeQmarrKOZ4Vty0AAMUKMcgAAIXjHFvVvGleRc/2e0sV02cCAEAtwUF29CFzmTRDmildnnmTtH+ltEWyVCSx2aLtS6VZ3j88Clsqs8c/mCdK07ykd/8Qr28lxReZDRl9O0njpNnebis5ru1h0hy/V8fGaY/aY6Qpki2msnZAnPZkvN5VWm3Pdtz2aLuXNMGfL7tPjeOyR20DaaTb8Z49S/m0JQ9cJ9nf2nLb0SyyOctWNKTgYQyu3r1hDGYMruJ5YQzOB5bmrdQlbOGLfXg29bjs56Xu/ppV+nvO8yjvHJct0lG+3ciPaxfnvZHGSoP9GMt3/WKINhwu2er9GRl99g/C1b59tXSTb+8rvW33SdpN+kCqF6M9faSOGfdyQZz3J+P1x6U/S1fG/PuyZ2q69DXfbxvz7+ss6VHfbuq51ruF9WzX4Gd5w9upGX3T47YrDz8XY3A17w1jMGMwY/CWUMclZpC3so/nE10rbfT8olalzxgh/UjaErMtF0m/Vt96O0jtopjtsfvR0o9ptaMS4bVB17VFSV9U6D5JGunb1p6c0W8OznrpI23PkfrHZY+ONUcmfW9mSo31332juOwxdH3b/tDtyTvVtGeQO3hv+7lLpU0x2mPPdTPdI3NELNZ3g7Qyn/bUEptFNCe+nlqrVHqHtl+P26g8wBhc/XvDGLw9jMEOY3B+wEHeiv13frg+bNpKTX1GtIu2T/QZv9SHd5y2SD2kw9T3hvSSdEDM9tjXfDerz9JM3SJF/VV0+3T1MG/beX8nyWxKM9/74rInk/+Spqb/yYnDHv2+mqn5sXR9BDbs0B5/ri186TkrgiH9KGZ7/iKtkaxvnnSLXq/oXMfJpV5m2p6hR9x53y4krEBhDK7mvZEYg7eHMbhqGIOrCWnehD4ALdbQ0ieNk1ZL5hDbf+o/9RmuJNhivyuLkzxIMud4tI7bXcdvickem9G+Qq8/rte/pe37pYFh2pIjVr68IrGXi9Q9MqfmpqifpyyYYzxCvzeLP47ZlBT2XB/qz7SVmx9vsdqyb3xM9ti3DTaD3dH/3l6RPc/LHptxjx2bRfRxyVQ0MAbX6N4wBlcDxuBKYQyuBGaQvxqE7pf6Shav+IXHHloM69v6w7LtzpLNcHWo5F6Gactsnwl9whxiYVW0NkuRLBqsxJ5zzB4/xGJZQ1ukVwkL9bvYxTa8TYeczPfZlTSdwwz/yMEe2zcbnpSG6B5aTHQQoz0HSsP9mbYZqJ9o+5KYf18v6b4scefvWY8XjsseC18YI1vKPYzpNSkxJVBlaw/pHmms9M+04rYrHzAGV+veMAb/O4zBVcMYXE1wkB19yKS/gu6q5lRplAYjWwhnC3S6+Qe5DVCfV/Me58MW+yr1KWlA+kNSTUNpSdi2VGHPp17NK3C7bMCOkqfdSTes/WtG/xkW5yvt5otZ3ozLHtnQWs3fpWF6dszZioqs9siGwzKe6d9Iv9L2nXHZ4wtgLYtFU4/7tWfq3RjtsbCKAbKljoej2Dc2/4rAnlyxf0anStdIV2Wo4GEMrta9YQz+dxiDq4YxuLqEuQKwkOTlWt/1r6+OzvL63CiyWFRmizvEf/R4tLekAXHeG/9afIr3vSHtH+L1H/GY0HL/R+V8z3Yw3h1za3fKON6+fraZ2lnpTBtx2eOOjMW0WjqutNrFeX8yzrsupCwW1f19ne0LBu3ZHh7z76u5O6Ez/Zm/KqznuoY/y5Qk2BHSz8YYXI17wxjMGMwYvCXUMYlKegAABYJmEO2fmkUesrNtsWfCFhICABQ8OMgAAIXjIFvqworIP96ye+TGAAAUMTjIAAAAAAAZsEgPAKBA8MWM11gmC9+3YiHHx20XAECxgYMMAFA4POjV/b7u+7bo8JfxmQMAUJzgIAMAFA57KN54uGfksODjL9UkouILAEAxgYMMAFA4bFBIRRO1qTxf2t5DTRSlywEASgpKTQOEhJyXeprhs7LFAPniWmmM1EXP18NqD5H+O19vDlBMMAZDrZ4fTzgOUOoD6Q1qrNzxb33/RjULpUbSt7x9Uq9f668/5SWtG0u/VX960dRqNbdJx0o/VP+rUf8sUJxYaT81VrZ8rVf4s/2JesYiqagJECaMwZA0cJAB7A+hTh0rvfyEnI2+2q7rFdZ+Ih0tXWCHeKlOq/T2so6xymtf+Nfdk6QjtL9U+/Yf5+naHs2NhbwP2HXqWCW9/bmzUGwwBkPSIMQCQMjpmKsB2hzcPtptL02VDpAG+Xa6DHF36WXp+zr2FO/v4v1LJQupeJybCiExUc/dAXpe7Z8ygKKBMRiSBg4ywFfc5/GcHaQHfPb4fzVw/z7zJslBOVLNQOlgvbZW+y96qIWxjrhjCJGjpAv0zH2sdo09jl5Jrxd3HYoAxmBIDDjIAF/xpPQLqYF0lrRRusEWQ8kBWa22k6fXaiUtc+d4b48HBYiCwdxmKGIYgyEx4CADOHJ4LYXWC9pc7rPAY7W/j9oJW9dHBbYA72zPInCh+qarnSVN5CZCFOi5tJljgKKEMRiSBIv0ANJ/DFsX570lnaaB2hbpAQBAVA4JYzAkCAqFAGwdmPdVM0caj3MMABAtjMGQNJhBBgAAAADIgBlkAAAAAAAcZAAAAACA7DCDDAAAAACAgwwAAAAAkB1mkAEAAAAAcJABAAAAALLz/9WX2WNlXb3iAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(10,5))\n",
    "\n",
    "ax0 = sns.lineplot(ax=axes[0], x='year', y='hydroelectric power rate(in total)', data=tpc_df)\n",
    "ax0.set_title('hydroelectric power rate')\n",
    "\n",
    "ax1 = sns.lineplot(ax=axes[1], x='year', y='renewable energy hydroelectric power net power generation(TPC)', data=tpc_df)\n",
    "ax1.set_title('hydroelectric power')\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a7737e06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(10,5))\n",
    "\n",
    "ax0 = sns.lineplot(ax=axes[0], x='year', y='geothermal power rate(in total)', data=tpc_df)\n",
    "ax0.set_title('geothermal power rate')\n",
    "\n",
    "ax1 = sns.lineplot(ax=axes[1], x='year', y='renewable energy geothermal power(TPC)', data=tpc_df)\n",
    "ax1.set_title('geothermal power')\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "336ef92e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(10,5))\n",
    "\n",
    "ax0 = sns.lineplot(ax=axes[0], x='year', y='solar power rate(in total)', data=tpc_df)\n",
    "ax0.set_title('solar power rate')\n",
    "\n",
    "ax1 = sns.lineplot(ax=axes[1], x='year', y='renewable energy solar power(TPC)', data=tpc_df)\n",
    "ax1.set_title('solar power')\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3a5aafa0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(10,5))\n",
    "\n",
    "ax0 = sns.lineplot(ax=axes[0], x='year', y='wind power rate(in total)', data=tpc_df)\n",
    "ax0.set_title('wind power rate')\n",
    "\n",
    "ax1 = sns.lineplot(ax=axes[1], x='year', y='renewable energy wind power(TPC)', data=tpc_df)\n",
    "ax1.set_title('wind power')\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2a932620",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2661c98c748>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tpc_renewable_df = tpc_df[['year', 'renewable energy hydroelectric power net power generation(TPC)', 'renewable energy solar power(TPC)', 'renewable energy wind power(TPC)']]\n",
    "\n",
    "tpc_renewable_df.plot(x='year', figsize=(10,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a9b0bdf3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2661ca0f108>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tpc_non_renewable_df = tpc_df[['year', 'pumped storage net power generation(TPC)', 'heat power net power generation(TPC)', 'nuclear power net power generation(TPC)']]\n",
    "\n",
    "tpc_non_renewable_df.plot(x='year', figsize=(10,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f031d701-c20a-4a9e-a1fa-b5c83969d397",
   "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>hydroelectric power rate(in renewable)</th>\n",
       "      <th>solar power rate(in renewable)</th>\n",
       "      <th>wind power rate(in renewable)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.881550</td>\n",
       "      <td>0.007488</td>\n",
       "      <td>0.110963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.059034</td>\n",
       "      <td>0.016446</td>\n",
       "      <td>0.047997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.734076</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.018835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.852398</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.084243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.876359</td>\n",
       "      <td>0.002451</td>\n",
       "      <td>0.120647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.914018</td>\n",
       "      <td>0.004763</td>\n",
       "      <td>0.141951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.981165</td>\n",
       "      <td>0.065295</td>\n",
       "      <td>0.200630</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       hydroelectric power rate(in renewable)  solar power rate(in renewable)  \\\n",
       "count                               16.000000                       16.000000   \n",
       "mean                                 0.881550                        0.007488   \n",
       "std                                  0.059034                        0.016446   \n",
       "min                                  0.734076                        0.000000   \n",
       "25%                                  0.852398                        0.000024   \n",
       "50%                                  0.876359                        0.002451   \n",
       "75%                                  0.914018                        0.004763   \n",
       "max                                  0.981165                        0.065295   \n",
       "\n",
       "       wind power rate(in renewable)  \n",
       "count                      16.000000  \n",
       "mean                        0.110963  \n",
       "std                         0.047997  \n",
       "min                         0.018835  \n",
       "25%                         0.084243  \n",
       "50%                         0.120647  \n",
       "75%                         0.141951  \n",
       "max                         0.200630  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = tpc_df[[\n",
    "    'year', \n",
    "    'hydroelectric power rate(in renewable)',\n",
    "    'solar power rate(in renewable)',\n",
    "    'wind power rate(in renewable)'\n",
    "]].plot(x='year', figsize=(15,10), kind='bar', stacked=True, title='Renewable Rate(TPC)')\n",
    "ax.set_ylabel(\"percentage\")\n",
    "\n",
    "tpc_df[[\n",
    "    'hydroelectric power rate(in renewable)',\n",
    "    'solar power rate(in renewable)',\n",
    "    'wind power rate(in renewable)'\n",
    "]].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6b44ad48-dfd0-40ca-9a37-42220d868da3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'GWh 百萬度')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']\n",
    "ax = tpc_df[[\n",
    "    'year', \n",
    "    'renewable energy hydroelectric power net power generation(TPC)',\n",
    "    'renewable energy solar power(TPC)', \n",
    "    'renewable energy wind power(TPC)',\n",
    "]].plot(x='year', figsize=(15,10), kind='bar', stacked=True, title='Renewable Power Generation(TPC)')\n",
    "ax.set_ylabel(u\"GWh 百萬度\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4cf5c025-5611-44e1-9a50-7c5444dae2fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# tpc_df['renewable energy power generation(TPC)'] = tpc_df.apply(get_renewable_energy_sum, axis = 1)\n",
    "# tpc_df['non-renewable energy power generation(TPC)'] = tpc_df.apply(get_non_renewable_energy_sum, axis = 1)\n",
    "# tpc_df['renewable energy rate'] = tpc_df.apply(lambda row: row['renewable energy power generation(TPC)'] / row['total power generation(TPC)'], axis = 1)\n",
    "# tpc_df['non-renewable energy rate'] = tpc_df.apply(lambda row: row['non-renewable energy power generation(TPC)'] / row['total power generation(TPC)'], axis = 1)\n",
    "\n",
    "# tpc_df['hydroelectric power rate(in renewable)'] = tpc_df.apply(lambda row: row['renewable energy hydroelectric power net power generation(TPC)'] / row['renewable energy power generation(TPC)'], axis=1)\n",
    "# tpc_df['geothermal power rate(in renewable)'] = tpc_df.apply(lambda row: row['renewable energy geothermal power(TPC)'] / row['renewable energy power generation(TPC)'], axis=1)\n",
    "# tpc_df['solar power rate(in renewable)'] = tpc_df.apply(lambda row: row['renewable energy solar power(TPC)'] / row['renewable energy power generation(TPC)'], axis=1)\n",
    "# tpc_df['wind power rate(in renewable)'] = tpc_df.apply(lambda row: row['renewable energy wind power(TPC)'] / row['renewable energy power generation(TPC)'], axis=1)\n",
    "\n",
    "# tpc_df['hydroelectric power rate(in total)'] = tpc_df.apply(lambda row: row['renewable energy hydroelectric power net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "# tpc_df['geothermal power rate(in total)'] = tpc_df.apply(lambda row: row['renewable energy geothermal power(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "# tpc_df['solar power rate(in total)'] = tpc_df.apply(lambda row: row['renewable energy solar power(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "# tpc_df['wind power rate(in total)'] = tpc_df.apply(lambda row: row['renewable energy wind power(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "# tpc_df['pumped storage rate(in total)'] = tpc_df.apply(lambda row: row['pumped storage net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "# tpc_df['heat power rate(in total)'] = tpc_df.apply(lambda row: row['heat power net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n",
    "# tpc_df['nuclear power rate(in total)'] = tpc_df.apply(lambda row: row['nuclear power net power generation(TPC)'] / row['total power generation(TPC)'], axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b0486de4-a348-46c1-973e-0c738e7a7e98",
   "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>hydroelectric power rate(in total)</th>\n",
       "      <th>solar power rate(in total)</th>\n",
       "      <th>wind power rate(in total)</th>\n",
       "      <th>pumped storage rate(in total)</th>\n",
       "      <th>heat power rate(in total)</th>\n",
       "      <th>nuclear power rate(in total)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>1.600000e+01</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.027088</td>\n",
       "      <td>2.006419e-04</td>\n",
       "      <td>0.003367</td>\n",
       "      <td>0.020238</td>\n",
       "      <td>0.729624</td>\n",
       "      <td>0.219482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.004680</td>\n",
       "      <td>3.767219e-04</td>\n",
       "      <td>0.001360</td>\n",
       "      <td>0.003378</td>\n",
       "      <td>0.050427</td>\n",
       "      <td>0.048942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.015753</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000545</td>\n",
       "      <td>0.017066</td>\n",
       "      <td>0.671826</td>\n",
       "      <td>0.118944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.024789</td>\n",
       "      <td>6.661603e-07</td>\n",
       "      <td>0.002384</td>\n",
       "      <td>0.017786</td>\n",
       "      <td>0.695480</td>\n",
       "      <td>0.173591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.026732</td>\n",
       "      <td>9.056334e-05</td>\n",
       "      <td>0.004103</td>\n",
       "      <td>0.018545</td>\n",
       "      <td>0.708197</td>\n",
       "      <td>0.241794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.029285</td>\n",
       "      <td>1.386715e-04</td>\n",
       "      <td>0.004304</td>\n",
       "      <td>0.022419</td>\n",
       "      <td>0.769016</td>\n",
       "      <td>0.252726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.036429</td>\n",
       "      <td>1.401158e-03</td>\n",
       "      <td>0.004915</td>\n",
       "      <td>0.027136</td>\n",
       "      <td>0.829354</td>\n",
       "      <td>0.277673</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       hydroelectric power rate(in total)  solar power rate(in total)  \\\n",
       "count                           16.000000                1.600000e+01   \n",
       "mean                             0.027088                2.006419e-04   \n",
       "std                              0.004680                3.767219e-04   \n",
       "min                              0.015753                0.000000e+00   \n",
       "25%                              0.024789                6.661603e-07   \n",
       "50%                              0.026732                9.056334e-05   \n",
       "75%                              0.029285                1.386715e-04   \n",
       "max                              0.036429                1.401158e-03   \n",
       "\n",
       "       wind power rate(in total)  pumped storage rate(in total)  \\\n",
       "count                  16.000000                      16.000000   \n",
       "mean                    0.003367                       0.020238   \n",
       "std                     0.001360                       0.003378   \n",
       "min                     0.000545                       0.017066   \n",
       "25%                     0.002384                       0.017786   \n",
       "50%                     0.004103                       0.018545   \n",
       "75%                     0.004304                       0.022419   \n",
       "max                     0.004915                       0.027136   \n",
       "\n",
       "       heat power rate(in total)  nuclear power rate(in total)  \n",
       "count                  16.000000                     16.000000  \n",
       "mean                    0.729624                      0.219482  \n",
       "std                     0.050427                      0.048942  \n",
       "min                     0.671826                      0.118944  \n",
       "25%                     0.695480                      0.173591  \n",
       "50%                     0.708197                      0.241794  \n",
       "75%                     0.769016                      0.252726  \n",
       "max                     0.829354                      0.277673  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_tpc_df= tpc_df[[\n",
    "    'year', \n",
    "    'hydroelectric power rate(in total)',\n",
    "    'solar power rate(in total)',\n",
    "    'wind power rate(in total)',\n",
    "    'pumped storage rate(in total)',\n",
    "    'heat power rate(in total)',\n",
    "    'nuclear power rate(in total)'\n",
    "]].copy()\n",
    "\n",
    "n_tpc_df.rename(columns = { \n",
    "    'hydroelectric power rate(in total)': '慣常水力',\n",
    "    'solar power rate(in total)': '太陽光電',\n",
    "    'wind power rate(in total)': '風力',\n",
    "    'pumped storage rate(in total)': '抽蓄水力',\n",
    "    'heat power rate(in total)': '火力',\n",
    "    'nuclear power rate(in total)': '核能'\n",
    "}, inplace = True)\n",
    "\n",
    "ax = n_tpc_df.plot(x='year', figsize=(15,10), kind='bar', stacked=True, title='Total Power Generation Rate(TPC)')\n",
    "\n",
    "\n",
    "ax.set_ylabel(\"percentage\")\n",
    "\n",
    "tpc_df[[\n",
    "    'hydroelectric power rate(in total)',\n",
    "    'solar power rate(in total)',\n",
    "    'wind power rate(in total)',\n",
    "    'pumped storage rate(in total)',\n",
    "    'heat power rate(in total)',\n",
    "    'nuclear power rate(in total)'\n",
    "]].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3ae6c11d-1904-42b3-b979-79b5134a1a75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'GWh 百萬度')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']\n",
    "ax = tpc_df[[\n",
    "     'year', \n",
    "     'renewable energy hydroelectric power net power generation(TPC)', 'renewable energy solar power(TPC)', 'renewable energy wind power(TPC)',\n",
    "     'pumped storage net power generation(TPC)', 'heat power net power generation(TPC)', 'nuclear power net power generation(TPC)'\n",
    "]].plot(x='year', figsize=(15,10), kind='bar',stacked=True)\n",
    "ax.set_ylabel(u\"GWh 百萬度\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "331cb9da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2661cb1a508>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ipp_df = new_df[[\n",
    "    'year',\n",
    "    'heat power net power generation(IPP)',\n",
    "    'renewable energy hydroelectric power(IPP)',\n",
    "    'renewable energy solar power(IPP)', \n",
    "    'renewable energy wind power(IPP)'\n",
    "]].copy()\n",
    "\n",
    "def ipp_sum(row):\n",
    "    sum = 0\n",
    "    sum += row['heat power net power generation(IPP)']\n",
    "    sum += row['renewable energy hydroelectric power(IPP)']\n",
    "    sum += row['renewable energy solar power(IPP)']\n",
    "    sum += row['renewable energy solar power(IPP)']\n",
    "    return sum\n",
    "\n",
    "ipp_df['total power generation(IPP)'] = ipp_df.apply(ipp_sum, axis = 1)\n",
    "ipp_df['heat power rate'] = ipp_df.apply(lambda row: row['heat power net power generation(IPP)'] / row['total power generation(IPP)'], axis=1)\n",
    "ipp_df['hydroelectric power rate'] = ipp_df.apply(lambda row: row['renewable energy hydroelectric power(IPP)'] / row['total power generation(IPP)'], axis=1)\n",
    "ipp_df['solar power rate'] = ipp_df.apply(lambda row: row['renewable energy solar power(IPP)'] / row['total power generation(IPP)'], axis=1)\n",
    "ipp_df['wind power rate'] = ipp_df.apply(lambda row: row['renewable energy wind power(IPP)'] / row['total power generation(IPP)'], axis=1)\n",
    "\n",
    "ipp_df[[\n",
    "   'year', 'heat power rate', 'hydroelectric power rate', 'solar power rate', 'wind power rate'\n",
    "]].plot(x='year', figsize=(10,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4ca1239d-a6fc-4b0c-9b1b-dc0d99f219e8",
   "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>heat power rate</th>\n",
       "      <th>hydroelectric power rate</th>\n",
       "      <th>solar power rate</th>\n",
       "      <th>wind power rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.994243</td>\n",
       "      <td>0.003035</td>\n",
       "      <td>0.001361</td>\n",
       "      <td>0.016157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.006211</td>\n",
       "      <td>0.000843</td>\n",
       "      <td>0.003173</td>\n",
       "      <td>0.009602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.972390</td>\n",
       "      <td>0.001167</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.994153</td>\n",
       "      <td>0.002651</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.995965</td>\n",
       "      <td>0.003187</td>\n",
       "      <td>0.000073</td>\n",
       "      <td>0.017909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.997087</td>\n",
       "      <td>0.003715</td>\n",
       "      <td>0.001040</td>\n",
       "      <td>0.022353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.998833</td>\n",
       "      <td>0.003992</td>\n",
       "      <td>0.012741</td>\n",
       "      <td>0.036945</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       heat power rate  hydroelectric power rate  solar power rate  \\\n",
       "count        16.000000                 16.000000         16.000000   \n",
       "mean          0.994243                  0.003035          0.001361   \n",
       "std           0.006211                  0.000843          0.003173   \n",
       "min           0.972390                  0.001167          0.000000   \n",
       "25%           0.994153                  0.002651          0.000000   \n",
       "50%           0.995965                  0.003187          0.000073   \n",
       "75%           0.997087                  0.003715          0.001040   \n",
       "max           0.998833                  0.003992          0.012741   \n",
       "\n",
       "       wind power rate  \n",
       "count        16.000000  \n",
       "mean          0.016157  \n",
       "std           0.009602  \n",
       "min           0.000000  \n",
       "25%           0.009762  \n",
       "50%           0.017909  \n",
       "75%           0.022353  \n",
       "max           0.036945  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_ipp_df = ipp_df[[\n",
    "   'year', 'heat power rate', 'hydroelectric power rate', 'solar power rate', 'wind power rate'\n",
    "]].copy()\n",
    "\n",
    "n_ipp_df.rename(columns ={ \n",
    "    'heat power rate': '火力',\n",
    "    'hydroelectric power rate': '慣常水力', \n",
    "    'solar power rate': '太陽光電', \n",
    "    'wind power rate': '風力'\n",
    "}, inplace = True)\n",
    "\n",
    "\n",
    "ax =n_ipp_df.plot(x='year', figsize=(10,8),kind='bar', stacked=True)\n",
    "ax.set_ylabel(\"percentage\")\n",
    "\n",
    "ipp_df[[ \n",
    "    'heat power rate', 'hydroelectric power rate', 'solar power rate', 'wind power rate'\n",
    "]].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b63b4edb-b772-4368-bd3e-1ec381c87710",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7e7d5946-478d-4d00-8ea5-dbde85bc4c08",
   "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>heat power net power generation(IPP)</th>\n",
       "      <th>renewable energy hydroelectric power(IPP)</th>\n",
       "      <th>renewable energy solar power(IPP)</th>\n",
       "      <th>renewable energy wind power(IPP)</th>\n",
       "      <th>total power generation(IPP)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>40029.365566</td>\n",
       "      <td>122.555883</td>\n",
       "      <td>58.430555</td>\n",
       "      <td>667.362755</td>\n",
       "      <td>40268.782561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2034.518196</td>\n",
       "      <td>34.680708</td>\n",
       "      <td>138.650287</td>\n",
       "      <td>416.304693</td>\n",
       "      <td>2188.773761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>36480.256780</td>\n",
       "      <td>43.830523</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>36624.591590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>38805.636100</td>\n",
       "      <td>107.587916</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>381.608153</td>\n",
       "      <td>38934.517693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>40738.385710</td>\n",
       "      <td>131.411337</td>\n",
       "      <td>2.907906</td>\n",
       "      <td>735.089822</td>\n",
       "      <td>40890.579143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>41406.548155</td>\n",
       "      <td>146.971085</td>\n",
       "      <td>44.419479</td>\n",
       "      <td>894.585779</td>\n",
       "      <td>41603.540077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>42567.212010</td>\n",
       "      <td>166.172400</td>\n",
       "      <td>557.750862</td>\n",
       "      <td>1617.292927</td>\n",
       "      <td>43775.867134</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       heat power net power generation(IPP)  \\\n",
       "count                             16.000000   \n",
       "mean                           40029.365566   \n",
       "std                             2034.518196   \n",
       "min                            36480.256780   \n",
       "25%                            38805.636100   \n",
       "50%                            40738.385710   \n",
       "75%                            41406.548155   \n",
       "max                            42567.212010   \n",
       "\n",
       "       renewable energy hydroelectric power(IPP)  \\\n",
       "count                                  16.000000   \n",
       "mean                                  122.555883   \n",
       "std                                    34.680708   \n",
       "min                                    43.830523   \n",
       "25%                                   107.587916   \n",
       "50%                                   131.411337   \n",
       "75%                                   146.971085   \n",
       "max                                   166.172400   \n",
       "\n",
       "       renewable energy solar power(IPP)  renewable energy wind power(IPP)  \\\n",
       "count                          16.000000                         16.000000   \n",
       "mean                           58.430555                        667.362755   \n",
       "std                           138.650287                        416.304693   \n",
       "min                             0.000000                          0.000000   \n",
       "25%                             0.000000                        381.608153   \n",
       "50%                             2.907906                        735.089822   \n",
       "75%                            44.419479                        894.585779   \n",
       "max                           557.750862                       1617.292927   \n",
       "\n",
       "       total power generation(IPP)  \n",
       "count                    16.000000  \n",
       "mean                  40268.782561  \n",
       "std                    2188.773761  \n",
       "min                   36624.591590  \n",
       "25%                   38934.517693  \n",
       "50%                   40890.579143  \n",
       "75%                   41603.540077  \n",
       "max                   43775.867134  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ipp_df[[\n",
    "    'year', \n",
    "    'heat power net power generation(IPP)', \n",
    "    'renewable energy hydroelectric power(IPP)', \n",
    "    'renewable energy solar power(IPP)', \n",
    "    'renewable energy wind power(IPP)'\n",
    "]].plot(x='year', figsize=(10,8),kind='bar', stacked=True)\n",
    "\n",
    "ipp_df[[\n",
    "   'heat power net power generation(IPP)', 'renewable energy hydroelectric power(IPP)', 'renewable energy solar power(IPP)', 'renewable energy wind power(IPP)', 'total power generation(IPP)'\n",
    "]].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1c2e8135",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2661d124ac8>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ipp_df[[\n",
    "   'year', 'heat power net power generation(IPP)', 'renewable energy hydroelectric power(IPP)', 'renewable energy solar power(IPP)', 'renewable energy wind power(IPP)', 'total power generation(IPP)'\n",
    "]].plot(x='year', figsize=(10,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "92cddf18",
   "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>heat power rate</th>\n",
       "      <th>hydroelectric power rate</th>\n",
       "      <th>geothermal power rate</th>\n",
       "      <th>solar power rate</th>\n",
       "      <th>wind power rate</th>\n",
       "      <th>biomass rate</th>\n",
       "      <th>Waste-to-energy rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>1.600000e+01</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.890742</td>\n",
       "      <td>4.404087e-07</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.023522</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>0.005881</td>\n",
       "      <td>0.079552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.037288</td>\n",
       "      <td>1.761635e-06</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.035786</td>\n",
       "      <td>0.000168</td>\n",
       "      <td>0.001121</td>\n",
       "      <td>0.004815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.794895</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000023</td>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.003888</td>\n",
       "      <td>0.071373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.878721</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000198</td>\n",
       "      <td>0.000206</td>\n",
       "      <td>0.005105</td>\n",
       "      <td>0.076838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.905817</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005635</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>0.005921</td>\n",
       "      <td>0.080182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.916105</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.030042</td>\n",
       "      <td>0.000292</td>\n",
       "      <td>0.006690</td>\n",
       "      <td>0.083422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.921528</td>\n",
       "      <td>7.046540e-06</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>0.119427</td>\n",
       "      <td>0.000688</td>\n",
       "      <td>0.007615</td>\n",
       "      <td>0.086008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       heat power rate  hydroelectric power rate  geothermal power rate  \\\n",
       "count        16.000000              1.600000e+01              16.000000   \n",
       "mean          0.890742              4.404087e-07               0.000004   \n",
       "std           0.037288              1.761635e-06               0.000011   \n",
       "min           0.794895              0.000000e+00               0.000000   \n",
       "25%           0.878721              0.000000e+00               0.000000   \n",
       "50%           0.905817              0.000000e+00               0.000000   \n",
       "75%           0.916105              0.000000e+00               0.000000   \n",
       "max           0.921528              7.046540e-06               0.000043   \n",
       "\n",
       "       solar power rate  wind power rate  biomass rate  Waste-to-energy rate  \n",
       "count         16.000000        16.000000     16.000000             16.000000  \n",
       "mean           0.023522         0.000300      0.005881              0.079552  \n",
       "std            0.035786         0.000168      0.001121              0.004815  \n",
       "min            0.000023         0.000162      0.003888              0.071373  \n",
       "25%            0.000198         0.000206      0.005105              0.076838  \n",
       "50%            0.005635         0.000231      0.005921              0.080182  \n",
       "75%            0.030042         0.000292      0.006690              0.083422  \n",
       "max            0.119427         0.000688      0.007615              0.086008  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "self_df = new_df[[\n",
    "    'year', \n",
    "    'heat power net power generation(self)',\n",
    "    'renewable energy hydroelectric power(self)',\n",
    "    'renewable energy geothermal power(self)',\n",
    "    'renewable energy solar power(self)',\n",
    "    'renewable energy wind power(self)',\n",
    "    'renewable energy biomass(self)',\n",
    "    'renewable energy Waste-to-energy(self)', \n",
    "    'total power generation(self)'\n",
    "]].copy()\n",
    "\n",
    "def self_total(row):\n",
    "    sum = 0\n",
    "    sum += row['heat power net power generation(self)']\n",
    "    sum += row['renewable energy hydroelectric power(self)']\n",
    "    sum += row['renewable energy geothermal power(self)']\n",
    "    sum += row['renewable energy solar power(self)']\n",
    "    sum += row['renewable energy wind power(self)']\n",
    "    sum += row['renewable energy biomass(self)']\n",
    "    sum += row['renewable energy Waste-to-energy(self)']\n",
    "    return sum\n",
    "\n",
    "self_df['total power generation(self)'] = self_df.apply(self_total, axis=1)\n",
    "self_df['heat power rate'] = self_df.apply(lambda row: row['heat power net power generation(self)'] / row['total power generation(self)'], axis=1)\n",
    "self_df['hydroelectric power rate'] = self_df.apply(lambda row: row['renewable energy hydroelectric power(self)'] / row['total power generation(self)'], axis=1)\n",
    "self_df['geothermal power rate'] = self_df.apply(lambda row: row['renewable energy geothermal power(self)'] / row['total power generation(self)'], axis=1)\n",
    "self_df['solar power rate'] = self_df.apply(lambda row: row['renewable energy solar power(self)'] / row['total power generation(self)'], axis=1)\n",
    "self_df['wind power rate'] = self_df.apply(lambda row: row['renewable energy wind power(self)'] / row['total power generation(self)'], axis=1)\n",
    "self_df['biomass rate'] = self_df.apply(lambda row: row['renewable energy biomass(self)'] / row['total power generation(self)'], axis=1)\n",
    "self_df['Waste-to-energy rate'] = self_df.apply(lambda row: row['renewable energy Waste-to-energy(self)'] / row['total power generation(self)'], axis=1)\n",
    "\n",
    "n_self_df = self_df[[\n",
    "    'year', 'heat power rate', 'hydroelectric power rate', 'geothermal power rate', 'solar power rate', 'wind power rate', 'biomass rate', 'Waste-to-energy rate'\n",
    "]].copy()\n",
    "\n",
    "\n",
    "n_self_df.rename(columns = { \n",
    "    'heat power rate': '火力',\n",
    "    'hydroelectric power rate': '慣常水力',\n",
    "    'geothermal power rate': '地熱',\n",
    "    'solar power rate': '太陽光電',\n",
    "    'wind power rate': '風力',\n",
    "    'biomass rate': '生質能',\n",
    "    'Waste-to-energy rate': '廢棄物發電'\n",
    "}, inplace = True)\n",
    "\n",
    "ax = n_self_df.plot(x='year', figsize=(15,10), kind='bar', stacked=True)\n",
    "ax.set_ylabel(\"percentage\")\n",
    "\n",
    "self_df[[\n",
    "    'heat power rate', 'hydroelectric power rate', 'geothermal power rate', 'solar power rate', 'wind power rate', 'biomass rate', 'Waste-to-energy rate'\n",
    "]].describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c5f0e6cb",
   "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>heat power net power generation(self)</th>\n",
       "      <th>renewable energy hydroelectric power(self)</th>\n",
       "      <th>renewable energy geothermal power(self)</th>\n",
       "      <th>renewable energy solar power(self)</th>\n",
       "      <th>renewable energy wind power(self)</th>\n",
       "      <th>renewable energy biomass(self)</th>\n",
       "      <th>renewable energy Waste-to-energy(self)</th>\n",
       "      <th>total power generation(self)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>36655.311556</td>\n",
       "      <td>0.019468</td>\n",
       "      <td>0.166869</td>\n",
       "      <td>1002.920497</td>\n",
       "      <td>12.557447</td>\n",
       "      <td>241.796510</td>\n",
       "      <td>3271.966350</td>\n",
       "      <td>41184.738697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1906.344582</td>\n",
       "      <td>0.077872</td>\n",
       "      <td>0.502115</td>\n",
       "      <td>1570.800323</td>\n",
       "      <td>7.612348</td>\n",
       "      <td>46.971049</td>\n",
       "      <td>194.134721</td>\n",
       "      <td>2089.066178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>33734.752180</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>6.455651</td>\n",
       "      <td>169.779996</td>\n",
       "      <td>3036.144627</td>\n",
       "      <td>37564.302140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>35566.819518</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.855020</td>\n",
       "      <td>8.242341</td>\n",
       "      <td>204.698873</td>\n",
       "      <td>3117.849358</td>\n",
       "      <td>39685.385733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>36389.843745</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>222.592172</td>\n",
       "      <td>9.361393</td>\n",
       "      <td>238.775536</td>\n",
       "      <td>3221.311763</td>\n",
       "      <td>40579.269918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>37444.894432</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1180.742299</td>\n",
       "      <td>12.375143</td>\n",
       "      <td>270.652258</td>\n",
       "      <td>3387.286008</td>\n",
       "      <td>42753.375411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>40842.610700</td>\n",
       "      <td>0.311488</td>\n",
       "      <td>1.911729</td>\n",
       "      <td>5279.211029</td>\n",
       "      <td>29.954504</td>\n",
       "      <td>323.479207</td>\n",
       "      <td>3630.396197</td>\n",
       "      <td>44320.516544</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       heat power net power generation(self)  \\\n",
       "count                              16.000000   \n",
       "mean                            36655.311556   \n",
       "std                              1906.344582   \n",
       "min                             33734.752180   \n",
       "25%                             35566.819518   \n",
       "50%                             36389.843745   \n",
       "75%                             37444.894432   \n",
       "max                             40842.610700   \n",
       "\n",
       "       renewable energy hydroelectric power(self)  \\\n",
       "count                                   16.000000   \n",
       "mean                                     0.019468   \n",
       "std                                      0.077872   \n",
       "min                                      0.000000   \n",
       "25%                                      0.000000   \n",
       "50%                                      0.000000   \n",
       "75%                                      0.000000   \n",
       "max                                      0.311488   \n",
       "\n",
       "       renewable energy geothermal power(self)  \\\n",
       "count                                16.000000   \n",
       "mean                                  0.166869   \n",
       "std                                   0.502115   \n",
       "min                                   0.000000   \n",
       "25%                                   0.000000   \n",
       "50%                                   0.000000   \n",
       "75%                                   0.000000   \n",
       "max                                   1.911729   \n",
       "\n",
       "       renewable energy solar power(self)  renewable energy wind power(self)  \\\n",
       "count                           16.000000                          16.000000   \n",
       "mean                          1002.920497                          12.557447   \n",
       "std                           1570.800323                           7.612348   \n",
       "min                              0.960000                           6.455651   \n",
       "25%                              7.855020                           8.242341   \n",
       "50%                            222.592172                           9.361393   \n",
       "75%                           1180.742299                          12.375143   \n",
       "max                           5279.211029                          29.954504   \n",
       "\n",
       "       renewable energy biomass(self)  renewable energy Waste-to-energy(self)  \\\n",
       "count                       16.000000                               16.000000   \n",
       "mean                       241.796510                             3271.966350   \n",
       "std                         46.971049                              194.134721   \n",
       "min                        169.779996                             3036.144627   \n",
       "25%                        204.698873                             3117.849358   \n",
       "50%                        238.775536                             3221.311763   \n",
       "75%                        270.652258                             3387.286008   \n",
       "max                        323.479207                             3630.396197   \n",
       "\n",
       "       total power generation(self)  \n",
       "count                     16.000000  \n",
       "mean                   41184.738697  \n",
       "std                     2089.066178  \n",
       "min                    37564.302140  \n",
       "25%                    39685.385733  \n",
       "50%                    40579.269918  \n",
       "75%                    42753.375411  \n",
       "max                    44320.516544  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "self_df[[\n",
    "    'year', \n",
    "    'heat power net power generation(self)',\n",
    "    'renewable energy hydroelectric power(self)',\n",
    "    'renewable energy geothermal power(self)',\n",
    "    'renewable energy solar power(self)',\n",
    "    'renewable energy wind power(self)',\n",
    "    'renewable energy biomass(self)',\n",
    "    'renewable energy Waste-to-energy(self)', \n",
    "]].plot(x='year', figsize=(10,8), kind='bar', stacked=True)\n",
    "\n",
    "self_df[[\n",
    "    'heat power net power generation(self)',\n",
    "    'renewable energy hydroelectric power(self)',\n",
    "    'renewable energy geothermal power(self)',\n",
    "    'renewable energy solar power(self)',\n",
    "    'renewable energy wind power(self)',\n",
    "    'renewable energy biomass(self)',\n",
    "    'renewable energy Waste-to-energy(self)',\n",
    "    'total power generation(self)'\n",
    "]].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b646ecc9",
   "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>total power generation</th>\n",
       "      <th>total power generation(TPC)</th>\n",
       "      <th>total power generation(IPP)</th>\n",
       "      <th>total power generation(self)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>253674.481269</td>\n",
       "      <td>171612.027813</td>\n",
       "      <td>40877.714760</td>\n",
       "      <td>41184.738695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>16374.709902</td>\n",
       "      <td>13914.241420</td>\n",
       "      <td>2477.648654</td>\n",
       "      <td>2089.066179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>227512.267100</td>\n",
       "      <td>147466.595000</td>\n",
       "      <td>36930.987500</td>\n",
       "      <td>37564.302140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>241913.803250</td>\n",
       "      <td>161821.690600</td>\n",
       "      <td>39455.521610</td>\n",
       "      <td>39685.385730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>252253.925500</td>\n",
       "      <td>172013.898800</td>\n",
       "      <td>41524.534535</td>\n",
       "      <td>40579.269915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>265644.856775</td>\n",
       "      <td>182802.106625</td>\n",
       "      <td>42385.475612</td>\n",
       "      <td>42753.375405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>280139.911400</td>\n",
       "      <td>191100.110100</td>\n",
       "      <td>44835.409200</td>\n",
       "      <td>44320.516550</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       total power generation  total power generation(TPC)  \\\n",
       "count               16.000000                    16.000000   \n",
       "mean            253674.481269                171612.027813   \n",
       "std              16374.709902                 13914.241420   \n",
       "min             227512.267100                147466.595000   \n",
       "25%             241913.803250                161821.690600   \n",
       "50%             252253.925500                172013.898800   \n",
       "75%             265644.856775                182802.106625   \n",
       "max             280139.911400                191100.110100   \n",
       "\n",
       "       total power generation(IPP)  total power generation(self)  \n",
       "count                    16.000000                     16.000000  \n",
       "mean                  40877.714760                  41184.738695  \n",
       "std                    2477.648654                   2089.066179  \n",
       "min                   36930.987500                  37564.302140  \n",
       "25%                   39455.521610                  39685.385730  \n",
       "50%                   41524.534535                  40579.269915  \n",
       "75%                   42385.475612                  42753.375405  \n",
       "max                   44835.409200                  44320.516550  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']\n",
    "compare_df = new_df[[\n",
    "    'year', \n",
    "    'renewable energy',\n",
    "    'total power generation',\n",
    "    'total power generation(TPC)',\n",
    "    'total power generation(IPP)',\n",
    "    'total power generation(self)'\n",
    "]].copy()\n",
    "\n",
    "\n",
    "ax = compare_df[['year','total power generation(TPC)', 'total power generation(IPP)', 'total power generation(self)']].plot(x='year', figsize=(15, 10),  kind='bar', stacked=True)\n",
    "ax.set_ylabel(u\"GWh 百萬度\")\n",
    "compare_df[['total power generation','total power generation(TPC)', 'total power generation(IPP)', 'total power generation(self)']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "dce25480-1399-4c85-9ebb-b8c5707fc830",
   "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>total power generation rate(TPC)</th>\n",
       "      <th>total power generation rate(IPP)</th>\n",
       "      <th>total power generation rate(self)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.675841</td>\n",
       "      <td>0.161274</td>\n",
       "      <td>0.162885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.013483</td>\n",
       "      <td>0.005842</td>\n",
       "      <td>0.012068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.648170</td>\n",
       "      <td>0.152244</td>\n",
       "      <td>0.143736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.666686</td>\n",
       "      <td>0.156720</td>\n",
       "      <td>0.157224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.679373</td>\n",
       "      <td>0.160373</td>\n",
       "      <td>0.159948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.685576</td>\n",
       "      <td>0.164543</td>\n",
       "      <td>0.166963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.694583</td>\n",
       "      <td>0.174635</td>\n",
       "      <td>0.186721</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       total power generation rate(TPC)  total power generation rate(IPP)  \\\n",
       "count                         16.000000                         16.000000   \n",
       "mean                           0.675841                          0.161274   \n",
       "std                            0.013483                          0.005842   \n",
       "min                            0.648170                          0.152244   \n",
       "25%                            0.666686                          0.156720   \n",
       "50%                            0.679373                          0.160373   \n",
       "75%                            0.685576                          0.164543   \n",
       "max                            0.694583                          0.174635   \n",
       "\n",
       "       total power generation rate(self)  \n",
       "count                          16.000000  \n",
       "mean                            0.162885  \n",
       "std                             0.012068  \n",
       "min                             0.143736  \n",
       "25%                             0.157224  \n",
       "50%                             0.159948  \n",
       "75%                             0.166963  \n",
       "max                             0.186721  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare_df['total power generation rate(TPC)'] = compare_df.apply(lambda row: row['total power generation(TPC)'] / row['total power generation'], axis=1)\n",
    "compare_df['total power generation rate(IPP)'] = compare_df.apply(lambda row: row['total power generation(IPP)'] / row['total power generation'], axis=1)\n",
    "compare_df['total power generation rate(self)'] = compare_df.apply(lambda row: row['total power generation(self)'] / row['total power generation'], axis=1)\n",
    "\n",
    "ax = compare_df[[\n",
    "    'year',\n",
    "    'total power generation rate(TPC)', 'total power generation rate(IPP)', 'total power generation rate(self)'\n",
    "]].plot(x='year', figsize=(15,10),  kind='bar', stacked=True)\n",
    "ax.set_ylabel(\"percentage\")\n",
    "\n",
    "compare_df[['total power generation rate(TPC)', 'total power generation rate(IPP)', 'total power generation rate(self)']].describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8d7568a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2661e38ca08>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare_df['renewable energy rate'] = compare_df.apply(lambda row: row['renewable energy'] / row['total power generation'], axis=1)\n",
    "\n",
    "compare_df[[ 'year', 'renewable energy rate']].plot(x='year', figsize=(10,8))"
   ]
  }
 ],
 "metadata": {
  "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": "3.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}