Part 4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>REF_DATE</th>\n",
       "      <th>GEO</th>\n",
       "      <th>DGUID</th>\n",
       "      <th>Class of electricity producer</th>\n",
       "      <th>Type of electricity generation</th>\n",
       "      <th>UOM</th>\n",
       "      <th>UOM_ID</th>\n",
       "      <th>SCALAR_FACTOR</th>\n",
       "      <th>SCALAR_ID</th>\n",
       "      <th>VECTOR</th>\n",
       "      <th>COORDINATE</th>\n",
       "      <th>VALUE</th>\n",
       "      <th>STATUS</th>\n",
       "      <th>SYMBOL</th>\n",
       "      <th>TERMINATED</th>\n",
       "      <th>DECIMALS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>2016A000011124</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total all types of electricity generation</td>\n",
       "      <td>Megawatt hours</td>\n",
       "      <td>210</td>\n",
       "      <td>units</td>\n",
       "      <td>0</td>\n",
       "      <td>v52300346</td>\n",
       "      <td>1.1.1</td>\n",
       "      <td>604369965.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>2016A000011124</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total hydro, tidal, wind, solar and other gene...</td>\n",
       "      <td>Megawatt hours</td>\n",
       "      <td>210</td>\n",
       "      <td>units</td>\n",
       "      <td>0</td>\n",
       "      <td>v52300348</td>\n",
       "      <td>1.1.2</td>\n",
       "      <td>360025505.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>2016A000011124</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Hydraulic turbine</td>\n",
       "      <td>Megawatt hours</td>\n",
       "      <td>210</td>\n",
       "      <td>units</td>\n",
       "      <td>0</td>\n",
       "      <td>v52300349</td>\n",
       "      <td>1.1.3</td>\n",
       "      <td>358446082.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>2016A000011124</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Tidal power turbine</td>\n",
       "      <td>Megawatt hours</td>\n",
       "      <td>210</td>\n",
       "      <td>units</td>\n",
       "      <td>0</td>\n",
       "      <td>v52300350</td>\n",
       "      <td>1.1.4</td>\n",
       "      <td>27643.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>2016A000011124</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Wind power turbine</td>\n",
       "      <td>Megawatt hours</td>\n",
       "      <td>210</td>\n",
       "      <td>units</td>\n",
       "      <td>0</td>\n",
       "      <td>v52300351</td>\n",
       "      <td>1.1.5</td>\n",
       "      <td>1551780.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   REF_DATE     GEO           DGUID  \\\n",
       "0      2005  Canada  2016A000011124   \n",
       "1      2005  Canada  2016A000011124   \n",
       "2      2005  Canada  2016A000011124   \n",
       "3      2005  Canada  2016A000011124   \n",
       "4      2005  Canada  2016A000011124   \n",
       "\n",
       "               Class of electricity producer  \\\n",
       "0  Total all classes of electricity producer   \n",
       "1  Total all classes of electricity producer   \n",
       "2  Total all classes of electricity producer   \n",
       "3  Total all classes of electricity producer   \n",
       "4  Total all classes of electricity producer   \n",
       "\n",
       "                      Type of electricity generation             UOM  UOM_ID  \\\n",
       "0          Total all types of electricity generation  Megawatt hours     210   \n",
       "1  Total hydro, tidal, wind, solar and other gene...  Megawatt hours     210   \n",
       "2                                  Hydraulic turbine  Megawatt hours     210   \n",
       "3                                Tidal power turbine  Megawatt hours     210   \n",
       "4                                 Wind power turbine  Megawatt hours     210   \n",
       "\n",
       "  SCALAR_FACTOR  SCALAR_ID     VECTOR COORDINATE        VALUE STATUS SYMBOL  \\\n",
       "0        units           0  v52300346      1.1.1  604369965.0    NaN    NaN   \n",
       "1        units           0  v52300348      1.1.2  360025505.0    NaN    NaN   \n",
       "2        units           0  v52300349      1.1.3  358446082.0    NaN    NaN   \n",
       "3        units           0  v52300350      1.1.4      27643.0    NaN    NaN   \n",
       "4        units           0  v52300351      1.1.5    1551780.0    NaN    NaN   \n",
       "\n",
       "   TERMINATED  DECIMALS  \n",
       "0         NaN         0  \n",
       "1         NaN         0  \n",
       "2         NaN         0  \n",
       "3         NaN         0  \n",
       "4         NaN         0  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dependencies and Setup\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as st\n",
    "\n",
    "# File to Load \n",
    "energy_data_filepath = \"Resources/Raw Data/Table 5 - Canadian Electricity by source.csv\"\n",
    "\n",
    "# Read Data File and store into Pandas DataFrames\n",
    "raw_energy_data = pd.read_csv(energy_data_filepath)\n",
    "raw_energy_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract and Clean Raw Energy Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>REF_DATE</th>\n",
       "      <th>GEO</th>\n",
       "      <th>Class of electricity producer</th>\n",
       "      <th>Type of electricity generation</th>\n",
       "      <th>VALUE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total all types of electricity generation</td>\n",
       "      <td>604369965.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total hydro, tidal, wind, solar and other gene...</td>\n",
       "      <td>360025505.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Hydraulic turbine</td>\n",
       "      <td>358446082.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Tidal power turbine</td>\n",
       "      <td>27643.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Wind power turbine</td>\n",
       "      <td>1551780.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4828</th>\n",
       "      <td>2019</td>\n",
       "      <td>Nunavut</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total electricity production from combustible ...</td>\n",
       "      <td>192222.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4829</th>\n",
       "      <td>2019</td>\n",
       "      <td>Nunavut</td>\n",
       "      <td>Electricity producer, electric utilities</td>\n",
       "      <td>Total all types of electricity generation</td>\n",
       "      <td>192222.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4830</th>\n",
       "      <td>2019</td>\n",
       "      <td>Nunavut</td>\n",
       "      <td>Electricity producer, electric utilities</td>\n",
       "      <td>Total thermal generation</td>\n",
       "      <td>192222.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4831</th>\n",
       "      <td>2019</td>\n",
       "      <td>Nunavut</td>\n",
       "      <td>Electricity producer, electric utilities</td>\n",
       "      <td>Internal combustion turbine</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4832</th>\n",
       "      <td>2019</td>\n",
       "      <td>Nunavut</td>\n",
       "      <td>Electricity producer, electric utilities</td>\n",
       "      <td>Total electricity production from combustible ...</td>\n",
       "      <td>192222.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4833 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      REF_DATE      GEO              Class of electricity producer  \\\n",
       "0         2005   Canada  Total all classes of electricity producer   \n",
       "1         2005   Canada  Total all classes of electricity producer   \n",
       "2         2005   Canada  Total all classes of electricity producer   \n",
       "3         2005   Canada  Total all classes of electricity producer   \n",
       "4         2005   Canada  Total all classes of electricity producer   \n",
       "...        ...      ...                                        ...   \n",
       "4828      2019  Nunavut  Total all classes of electricity producer   \n",
       "4829      2019  Nunavut   Electricity producer, electric utilities   \n",
       "4830      2019  Nunavut   Electricity producer, electric utilities   \n",
       "4831      2019  Nunavut   Electricity producer, electric utilities   \n",
       "4832      2019  Nunavut   Electricity producer, electric utilities   \n",
       "\n",
       "                         Type of electricity generation        VALUE  \n",
       "0             Total all types of electricity generation  604369965.0  \n",
       "1     Total hydro, tidal, wind, solar and other gene...  360025505.0  \n",
       "2                                     Hydraulic turbine  358446082.0  \n",
       "3                                   Tidal power turbine      27643.0  \n",
       "4                                    Wind power turbine    1551780.0  \n",
       "...                                                 ...          ...  \n",
       "4828  Total electricity production from combustible ...     192222.0  \n",
       "4829          Total all types of electricity generation     192222.0  \n",
       "4830                           Total thermal generation     192222.0  \n",
       "4831                        Internal combustion turbine          NaN  \n",
       "4832  Total electricity production from combustible ...     192222.0  \n",
       "\n",
       "[4833 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select the columns of concerns\n",
    "clean_energy_data1 = raw_energy_data[[\"REF_DATE\",\"GEO\",\"Class of electricity producer\",\"Type of electricity generation\",\"VALUE\"]]\n",
    "clean_energy_data1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>REF_DATE</th>\n",
       "      <th>GEO</th>\n",
       "      <th>Class of electricity producer</th>\n",
       "      <th>Type of electricity generation</th>\n",
       "      <th>VALUE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total all types of electricity generation</td>\n",
       "      <td>604369965.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total hydro, tidal, wind, solar and other gene...</td>\n",
       "      <td>360025505.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Hydraulic turbine</td>\n",
       "      <td>358446082.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Tidal power turbine</td>\n",
       "      <td>27643.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Wind power turbine</td>\n",
       "      <td>1551780.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4470</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Conventional steam turbine</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4471</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Nuclear steam turbine</td>\n",
       "      <td>95469256.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4472</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Internal combustion turbine</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4473</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Combustion turbine</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4474</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total electricity production from combustible ...</td>\n",
       "      <td>127263359.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>182 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      REF_DATE     GEO              Class of electricity producer  \\\n",
       "0         2005  Canada  Total all classes of electricity producer   \n",
       "1         2005  Canada  Total all classes of electricity producer   \n",
       "2         2005  Canada  Total all classes of electricity producer   \n",
       "3         2005  Canada  Total all classes of electricity producer   \n",
       "4         2005  Canada  Total all classes of electricity producer   \n",
       "...        ...     ...                                        ...   \n",
       "4470      2019  Canada  Total all classes of electricity producer   \n",
       "4471      2019  Canada  Total all classes of electricity producer   \n",
       "4472      2019  Canada  Total all classes of electricity producer   \n",
       "4473      2019  Canada  Total all classes of electricity producer   \n",
       "4474      2019  Canada  Total all classes of electricity producer   \n",
       "\n",
       "                         Type of electricity generation        VALUE  \n",
       "0             Total all types of electricity generation  604369965.0  \n",
       "1     Total hydro, tidal, wind, solar and other gene...  360025505.0  \n",
       "2                                     Hydraulic turbine  358446082.0  \n",
       "3                                   Tidal power turbine      27643.0  \n",
       "4                                    Wind power turbine    1551780.0  \n",
       "...                                                 ...          ...  \n",
       "4470                         Conventional steam turbine          NaN  \n",
       "4471                              Nuclear steam turbine   95469256.0  \n",
       "4472                        Internal combustion turbine          NaN  \n",
       "4473                                 Combustion turbine          NaN  \n",
       "4474  Total electricity production from combustible ...  127263359.0  \n",
       "\n",
       "[182 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select data for the entire Canada and total class of electricity producer\n",
    "clean_energy_data2 =clean_energy_data1[(clean_energy_data1[\"GEO\"] == \"Canada\") & \n",
    "                                       (clean_energy_data1[\"Class of electricity producer\"] \n",
    "                                       == \"Total all classes of electricity producer\")]\n",
    "clean_energy_data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "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>GEO</th>\n",
       "      <th>Class of electricity producer</th>\n",
       "      <th>Type of electricity generation</th>\n",
       "      <th>VALUE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total all types of electricity generation</td>\n",
       "      <td>604369965.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total hydro, tidal, wind, solar and other gene...</td>\n",
       "      <td>360025505.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Hydraulic turbine</td>\n",
       "      <td>358446082.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Tidal power turbine</td>\n",
       "      <td>27643.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Wind power turbine</td>\n",
       "      <td>1551780.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4470</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Conventional steam turbine</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4471</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Nuclear steam turbine</td>\n",
       "      <td>95469256.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4472</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Internal combustion turbine</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4473</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Combustion turbine</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4474</th>\n",
       "      <td>2019</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Total all classes of electricity producer</td>\n",
       "      <td>Total electricity production from combustible ...</td>\n",
       "      <td>127263359.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>182 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Year     GEO              Class of electricity producer  \\\n",
       "0     2005  Canada  Total all classes of electricity producer   \n",
       "1     2005  Canada  Total all classes of electricity producer   \n",
       "2     2005  Canada  Total all classes of electricity producer   \n",
       "3     2005  Canada  Total all classes of electricity producer   \n",
       "4     2005  Canada  Total all classes of electricity producer   \n",
       "...    ...     ...                                        ...   \n",
       "4470  2019  Canada  Total all classes of electricity producer   \n",
       "4471  2019  Canada  Total all classes of electricity producer   \n",
       "4472  2019  Canada  Total all classes of electricity producer   \n",
       "4473  2019  Canada  Total all classes of electricity producer   \n",
       "4474  2019  Canada  Total all classes of electricity producer   \n",
       "\n",
       "                         Type of electricity generation        VALUE  \n",
       "0             Total all types of electricity generation  604369965.0  \n",
       "1     Total hydro, tidal, wind, solar and other gene...  360025505.0  \n",
       "2                                     Hydraulic turbine  358446082.0  \n",
       "3                                   Tidal power turbine      27643.0  \n",
       "4                                    Wind power turbine    1551780.0  \n",
       "...                                                 ...          ...  \n",
       "4470                         Conventional steam turbine          NaN  \n",
       "4471                              Nuclear steam turbine   95469256.0  \n",
       "4472                        Internal combustion turbine          NaN  \n",
       "4473                                 Combustion turbine          NaN  \n",
       "4474  Total electricity production from combustible ...  127263359.0  \n",
       "\n",
       "[182 rows x 5 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Change column name\n",
    "clean_energy_data3 = clean_energy_data2.rename(columns = {\"REF_DATE\" : \"Year\"})\n",
    "clean_energy_data3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Combustion turbine</th>\n",
       "      <th>Conventional steam turbine</th>\n",
       "      <th>Hydraulic turbine</th>\n",
       "      <th>Internal combustion turbine</th>\n",
       "      <th>Nuclear steam turbine</th>\n",
       "      <th>Other types of electricity generation</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Tidal power turbine</th>\n",
       "      <th>Total all types of electricity generation</th>\n",
       "      <th>Total electricity production from combustible fuels</th>\n",
       "      <th>Total hydro, tidal, wind, solar and other generation</th>\n",
       "      <th>Total thermal generation</th>\n",
       "      <th>Wind power turbine</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>25892974</td>\n",
       "      <td>130320252</td>\n",
       "      <td>358446082</td>\n",
       "      <td>1301338</td>\n",
       "      <td>86829896</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27643</td>\n",
       "      <td>604369965</td>\n",
       "      <td>0</td>\n",
       "      <td>360025505</td>\n",
       "      <td>244344460</td>\n",
       "      <td>1551780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>25811955</td>\n",
       "      <td>118877657</td>\n",
       "      <td>349468303</td>\n",
       "      <td>3591329</td>\n",
       "      <td>92418514</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19144</td>\n",
       "      <td>592635237</td>\n",
       "      <td>0</td>\n",
       "      <td>351935782</td>\n",
       "      <td>240699455</td>\n",
       "      <td>2448335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>32237570</td>\n",
       "      <td>127778534</td>\n",
       "      <td>364055135</td>\n",
       "      <td>1498789</td>\n",
       "      <td>88190431</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>22524</td>\n",
       "      <td>616760189</td>\n",
       "      <td>0</td>\n",
       "      <td>367054865</td>\n",
       "      <td>249705324</td>\n",
       "      <td>2977206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>30782510</td>\n",
       "      <td>117666179</td>\n",
       "      <td>373822743</td>\n",
       "      <td>1425052</td>\n",
       "      <td>90585015</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15018</td>\n",
       "      <td>618047146</td>\n",
       "      <td>0</td>\n",
       "      <td>377588390</td>\n",
       "      <td>240458756</td>\n",
       "      <td>3750629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>32728246</td>\n",
       "      <td>102607748</td>\n",
       "      <td>365110421</td>\n",
       "      <td>1570922</td>\n",
       "      <td>84991779</td>\n",
       "      <td>1918497</td>\n",
       "      <td>4502</td>\n",
       "      <td>29954</td>\n",
       "      <td>595537304</td>\n",
       "      <td>0</td>\n",
       "      <td>373638609</td>\n",
       "      <td>221898695</td>\n",
       "      <td>6575235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>38019362</td>\n",
       "      <td>103118558</td>\n",
       "      <td>347980845</td>\n",
       "      <td>1615274</td>\n",
       "      <td>85526588</td>\n",
       "      <td>2975953</td>\n",
       "      <td>115745</td>\n",
       "      <td>27680</td>\n",
       "      <td>588016955</td>\n",
       "      <td>0</td>\n",
       "      <td>359737173</td>\n",
       "      <td>228279782</td>\n",
       "      <td>8636950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>44283027</td>\n",
       "      <td>99411207</td>\n",
       "      <td>372076377</td>\n",
       "      <td>1609096</td>\n",
       "      <td>88291216</td>\n",
       "      <td>2509521</td>\n",
       "      <td>256935</td>\n",
       "      <td>26095</td>\n",
       "      <td>618550162</td>\n",
       "      <td>0</td>\n",
       "      <td>384955616</td>\n",
       "      <td>233594546</td>\n",
       "      <td>10086688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>45330296</td>\n",
       "      <td>89871261</td>\n",
       "      <td>376574355</td>\n",
       "      <td>1555195</td>\n",
       "      <td>89492389</td>\n",
       "      <td>2723937</td>\n",
       "      <td>315843</td>\n",
       "      <td>27128</td>\n",
       "      <td>617088777</td>\n",
       "      <td>0</td>\n",
       "      <td>390839636</td>\n",
       "      <td>226249141</td>\n",
       "      <td>11198373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>43756123</td>\n",
       "      <td>90388012</td>\n",
       "      <td>387980873</td>\n",
       "      <td>1645827</td>\n",
       "      <td>97584431</td>\n",
       "      <td>2441392</td>\n",
       "      <td>360478</td>\n",
       "      <td>14830</td>\n",
       "      <td>635205955</td>\n",
       "      <td>0</td>\n",
       "      <td>401831562</td>\n",
       "      <td>233374393</td>\n",
       "      <td>11033989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>378786255</td>\n",
       "      <td>0</td>\n",
       "      <td>101207807</td>\n",
       "      <td>2238903</td>\n",
       "      <td>325184</td>\n",
       "      <td>15483</td>\n",
       "      <td>629581402</td>\n",
       "      <td>134318871</td>\n",
       "      <td>394054724</td>\n",
       "      <td>235526678</td>\n",
       "      <td>12688899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>378481214</td>\n",
       "      <td>0</td>\n",
       "      <td>96045793</td>\n",
       "      <td>139421</td>\n",
       "      <td>1426619</td>\n",
       "      <td>12820</td>\n",
       "      <td>640327058</td>\n",
       "      <td>137524464</td>\n",
       "      <td>406756801</td>\n",
       "      <td>233570257</td>\n",
       "      <td>26696727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>381687991</td>\n",
       "      <td>0</td>\n",
       "      <td>95687312</td>\n",
       "      <td>177803</td>\n",
       "      <td>1779083</td>\n",
       "      <td>18547</td>\n",
       "      <td>646331002</td>\n",
       "      <td>136356480</td>\n",
       "      <td>414287210</td>\n",
       "      <td>232043792</td>\n",
       "      <td>30623786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>390751401</td>\n",
       "      <td>0</td>\n",
       "      <td>95565022</td>\n",
       "      <td>202863</td>\n",
       "      <td>2001842</td>\n",
       "      <td>5957</td>\n",
       "      <td>648919804</td>\n",
       "      <td>129194240</td>\n",
       "      <td>424160542</td>\n",
       "      <td>224759262</td>\n",
       "      <td>31198479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>382144912</td>\n",
       "      <td>0</td>\n",
       "      <td>95029596</td>\n",
       "      <td>210747</td>\n",
       "      <td>2192046</td>\n",
       "      <td>19525</td>\n",
       "      <td>640326756</td>\n",
       "      <td>127916909</td>\n",
       "      <td>417380251</td>\n",
       "      <td>222946505</td>\n",
       "      <td>32813021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>375982127</td>\n",
       "      <td>0</td>\n",
       "      <td>95469256</td>\n",
       "      <td>168289</td>\n",
       "      <td>2195412</td>\n",
       "      <td>920</td>\n",
       "      <td>633412436</td>\n",
       "      <td>127263359</td>\n",
       "      <td>410679821</td>\n",
       "      <td>222732615</td>\n",
       "      <td>32333073</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Combustion turbine  Conventional steam turbine  Hydraulic turbine  \\\n",
       "Year                                                                      \n",
       "2005            25892974                   130320252          358446082   \n",
       "2006            25811955                   118877657          349468303   \n",
       "2007            32237570                   127778534          364055135   \n",
       "2008            30782510                   117666179          373822743   \n",
       "2009            32728246                   102607748          365110421   \n",
       "2010            38019362                   103118558          347980845   \n",
       "2011            44283027                    99411207          372076377   \n",
       "2012            45330296                    89871261          376574355   \n",
       "2013            43756123                    90388012          387980873   \n",
       "2014                   0                           0          378786255   \n",
       "2015                   0                           0          378481214   \n",
       "2016                   0                           0          381687991   \n",
       "2017                   0                           0          390751401   \n",
       "2018                   0                           0          382144912   \n",
       "2019                   0                           0          375982127   \n",
       "\n",
       "      Internal combustion turbine  Nuclear steam turbine  \\\n",
       "Year                                                       \n",
       "2005                      1301338               86829896   \n",
       "2006                      3591329               92418514   \n",
       "2007                      1498789               88190431   \n",
       "2008                      1425052               90585015   \n",
       "2009                      1570922               84991779   \n",
       "2010                      1615274               85526588   \n",
       "2011                      1609096               88291216   \n",
       "2012                      1555195               89492389   \n",
       "2013                      1645827               97584431   \n",
       "2014                            0              101207807   \n",
       "2015                            0               96045793   \n",
       "2016                            0               95687312   \n",
       "2017                            0               95565022   \n",
       "2018                            0               95029596   \n",
       "2019                            0               95469256   \n",
       "\n",
       "      Other types of electricity generation    Solar  Tidal power turbine  \\\n",
       "Year                                                                        \n",
       "2005                                      0        0                27643   \n",
       "2006                                      0        0                19144   \n",
       "2007                                      0        0                22524   \n",
       "2008                                      0        0                15018   \n",
       "2009                                1918497     4502                29954   \n",
       "2010                                2975953   115745                27680   \n",
       "2011                                2509521   256935                26095   \n",
       "2012                                2723937   315843                27128   \n",
       "2013                                2441392   360478                14830   \n",
       "2014                                2238903   325184                15483   \n",
       "2015                                 139421  1426619                12820   \n",
       "2016                                 177803  1779083                18547   \n",
       "2017                                 202863  2001842                 5957   \n",
       "2018                                 210747  2192046                19525   \n",
       "2019                                 168289  2195412                  920   \n",
       "\n",
       "      Total all types of electricity generation  \\\n",
       "Year                                              \n",
       "2005                                  604369965   \n",
       "2006                                  592635237   \n",
       "2007                                  616760189   \n",
       "2008                                  618047146   \n",
       "2009                                  595537304   \n",
       "2010                                  588016955   \n",
       "2011                                  618550162   \n",
       "2012                                  617088777   \n",
       "2013                                  635205955   \n",
       "2014                                  629581402   \n",
       "2015                                  640327058   \n",
       "2016                                  646331002   \n",
       "2017                                  648919804   \n",
       "2018                                  640326756   \n",
       "2019                                  633412436   \n",
       "\n",
       "      Total electricity production from combustible fuels  \\\n",
       "Year                                                        \n",
       "2005                                                  0     \n",
       "2006                                                  0     \n",
       "2007                                                  0     \n",
       "2008                                                  0     \n",
       "2009                                                  0     \n",
       "2010                                                  0     \n",
       "2011                                                  0     \n",
       "2012                                                  0     \n",
       "2013                                                  0     \n",
       "2014                                          134318871     \n",
       "2015                                          137524464     \n",
       "2016                                          136356480     \n",
       "2017                                          129194240     \n",
       "2018                                          127916909     \n",
       "2019                                          127263359     \n",
       "\n",
       "      Total hydro, tidal, wind, solar and other generation  \\\n",
       "Year                                                         \n",
       "2005                                          360025505      \n",
       "2006                                          351935782      \n",
       "2007                                          367054865      \n",
       "2008                                          377588390      \n",
       "2009                                          373638609      \n",
       "2010                                          359737173      \n",
       "2011                                          384955616      \n",
       "2012                                          390839636      \n",
       "2013                                          401831562      \n",
       "2014                                          394054724      \n",
       "2015                                          406756801      \n",
       "2016                                          414287210      \n",
       "2017                                          424160542      \n",
       "2018                                          417380251      \n",
       "2019                                          410679821      \n",
       "\n",
       "      Total thermal generation  Wind power turbine  \n",
       "Year                                                \n",
       "2005                 244344460             1551780  \n",
       "2006                 240699455             2448335  \n",
       "2007                 249705324             2977206  \n",
       "2008                 240458756             3750629  \n",
       "2009                 221898695             6575235  \n",
       "2010                 228279782             8636950  \n",
       "2011                 233594546            10086688  \n",
       "2012                 226249141            11198373  \n",
       "2013                 233374393            11033989  \n",
       "2014                 235526678            12688899  \n",
       "2015                 233570257            26696727  \n",
       "2016                 232043792            30623786  \n",
       "2017                 224759262            31198479  \n",
       "2018                 222946505            32813021  \n",
       "2019                 222732615            32333073  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Genearate a pivot table for the electricity production of each energy type by year\n",
    "final_energy_data = pd.pivot_table(clean_energy_data3, index=\"Year\", columns=\"Type of electricity generation\", \n",
    "                                      values=\"VALUE\", aggfunc=sum, fill_value = 0).rename_axis(None, axis=1)\n",
    "final_energy_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use Raw Data to Generate Renewable Energy Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Hydraulic turbine</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Tidal power turbine</th>\n",
       "      <th>Wind power turbine</th>\n",
       "      <th>Other types of electricity generation</th>\n",
       "      <th>Total hydro, tidal, wind, solar and other generation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>358446082</td>\n",
       "      <td>0</td>\n",
       "      <td>27643</td>\n",
       "      <td>1551780</td>\n",
       "      <td>0</td>\n",
       "      <td>360025505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>349468303</td>\n",
       "      <td>0</td>\n",
       "      <td>19144</td>\n",
       "      <td>2448335</td>\n",
       "      <td>0</td>\n",
       "      <td>351935782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>364055135</td>\n",
       "      <td>0</td>\n",
       "      <td>22524</td>\n",
       "      <td>2977206</td>\n",
       "      <td>0</td>\n",
       "      <td>367054865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>373822743</td>\n",
       "      <td>0</td>\n",
       "      <td>15018</td>\n",
       "      <td>3750629</td>\n",
       "      <td>0</td>\n",
       "      <td>377588390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>365110421</td>\n",
       "      <td>4502</td>\n",
       "      <td>29954</td>\n",
       "      <td>6575235</td>\n",
       "      <td>1918497</td>\n",
       "      <td>373638609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>347980845</td>\n",
       "      <td>115745</td>\n",
       "      <td>27680</td>\n",
       "      <td>8636950</td>\n",
       "      <td>2975953</td>\n",
       "      <td>359737173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>372076377</td>\n",
       "      <td>256935</td>\n",
       "      <td>26095</td>\n",
       "      <td>10086688</td>\n",
       "      <td>2509521</td>\n",
       "      <td>384955616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>376574355</td>\n",
       "      <td>315843</td>\n",
       "      <td>27128</td>\n",
       "      <td>11198373</td>\n",
       "      <td>2723937</td>\n",
       "      <td>390839636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>387980873</td>\n",
       "      <td>360478</td>\n",
       "      <td>14830</td>\n",
       "      <td>11033989</td>\n",
       "      <td>2441392</td>\n",
       "      <td>401831562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>378786255</td>\n",
       "      <td>325184</td>\n",
       "      <td>15483</td>\n",
       "      <td>12688899</td>\n",
       "      <td>2238903</td>\n",
       "      <td>394054724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>378481214</td>\n",
       "      <td>1426619</td>\n",
       "      <td>12820</td>\n",
       "      <td>26696727</td>\n",
       "      <td>139421</td>\n",
       "      <td>406756801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>381687991</td>\n",
       "      <td>1779083</td>\n",
       "      <td>18547</td>\n",
       "      <td>30623786</td>\n",
       "      <td>177803</td>\n",
       "      <td>414287210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>390751401</td>\n",
       "      <td>2001842</td>\n",
       "      <td>5957</td>\n",
       "      <td>31198479</td>\n",
       "      <td>202863</td>\n",
       "      <td>424160542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>382144912</td>\n",
       "      <td>2192046</td>\n",
       "      <td>19525</td>\n",
       "      <td>32813021</td>\n",
       "      <td>210747</td>\n",
       "      <td>417380251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>375982127</td>\n",
       "      <td>2195412</td>\n",
       "      <td>920</td>\n",
       "      <td>32333073</td>\n",
       "      <td>168289</td>\n",
       "      <td>410679821</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Hydraulic turbine    Solar  Tidal power turbine  Wind power turbine  \\\n",
       "Year                                                                        \n",
       "2005          358446082        0                27643             1551780   \n",
       "2006          349468303        0                19144             2448335   \n",
       "2007          364055135        0                22524             2977206   \n",
       "2008          373822743        0                15018             3750629   \n",
       "2009          365110421     4502                29954             6575235   \n",
       "2010          347980845   115745                27680             8636950   \n",
       "2011          372076377   256935                26095            10086688   \n",
       "2012          376574355   315843                27128            11198373   \n",
       "2013          387980873   360478                14830            11033989   \n",
       "2014          378786255   325184                15483            12688899   \n",
       "2015          378481214  1426619                12820            26696727   \n",
       "2016          381687991  1779083                18547            30623786   \n",
       "2017          390751401  2001842                 5957            31198479   \n",
       "2018          382144912  2192046                19525            32813021   \n",
       "2019          375982127  2195412                  920            32333073   \n",
       "\n",
       "      Other types of electricity generation  \\\n",
       "Year                                          \n",
       "2005                                      0   \n",
       "2006                                      0   \n",
       "2007                                      0   \n",
       "2008                                      0   \n",
       "2009                                1918497   \n",
       "2010                                2975953   \n",
       "2011                                2509521   \n",
       "2012                                2723937   \n",
       "2013                                2441392   \n",
       "2014                                2238903   \n",
       "2015                                 139421   \n",
       "2016                                 177803   \n",
       "2017                                 202863   \n",
       "2018                                 210747   \n",
       "2019                                 168289   \n",
       "\n",
       "      Total hydro, tidal, wind, solar and other generation  \n",
       "Year                                                        \n",
       "2005                                          360025505     \n",
       "2006                                          351935782     \n",
       "2007                                          367054865     \n",
       "2008                                          377588390     \n",
       "2009                                          373638609     \n",
       "2010                                          359737173     \n",
       "2011                                          384955616     \n",
       "2012                                          390839636     \n",
       "2013                                          401831562     \n",
       "2014                                          394054724     \n",
       "2015                                          406756801     \n",
       "2016                                          414287210     \n",
       "2017                                          424160542     \n",
       "2018                                          417380251     \n",
       "2019                                          410679821     "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select renewable energy columns\n",
    "renewable_energy_data = final_energy_data[[\"Hydraulic turbine\", \"Solar\", \"Tidal power turbine\", \"Wind power turbine\",\n",
    "                                             \"Other types of electricity generation\",\n",
    "                                             \"Total hydro, tidal, wind, solar and other generation\"]]\n",
    "renewable_energy_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\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>Hydraulic turbine</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Tidal power turbine</th>\n",
       "      <th>Wind power turbine</th>\n",
       "      <th>Other types of electricity generation</th>\n",
       "      <th>Total renewable energy generation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>358446082</td>\n",
       "      <td>0</td>\n",
       "      <td>27643</td>\n",
       "      <td>1551780</td>\n",
       "      <td>0</td>\n",
       "      <td>360025505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>349468303</td>\n",
       "      <td>0</td>\n",
       "      <td>19144</td>\n",
       "      <td>2448335</td>\n",
       "      <td>0</td>\n",
       "      <td>351935782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>364055135</td>\n",
       "      <td>0</td>\n",
       "      <td>22524</td>\n",
       "      <td>2977206</td>\n",
       "      <td>0</td>\n",
       "      <td>367054865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>373822743</td>\n",
       "      <td>0</td>\n",
       "      <td>15018</td>\n",
       "      <td>3750629</td>\n",
       "      <td>0</td>\n",
       "      <td>377588390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>365110421</td>\n",
       "      <td>4502</td>\n",
       "      <td>29954</td>\n",
       "      <td>6575235</td>\n",
       "      <td>1918497</td>\n",
       "      <td>373638609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>347980845</td>\n",
       "      <td>115745</td>\n",
       "      <td>27680</td>\n",
       "      <td>8636950</td>\n",
       "      <td>2975953</td>\n",
       "      <td>359737173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>372076377</td>\n",
       "      <td>256935</td>\n",
       "      <td>26095</td>\n",
       "      <td>10086688</td>\n",
       "      <td>2509521</td>\n",
       "      <td>384955616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>376574355</td>\n",
       "      <td>315843</td>\n",
       "      <td>27128</td>\n",
       "      <td>11198373</td>\n",
       "      <td>2723937</td>\n",
       "      <td>390839636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>387980873</td>\n",
       "      <td>360478</td>\n",
       "      <td>14830</td>\n",
       "      <td>11033989</td>\n",
       "      <td>2441392</td>\n",
       "      <td>401831562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>378786255</td>\n",
       "      <td>325184</td>\n",
       "      <td>15483</td>\n",
       "      <td>12688899</td>\n",
       "      <td>2238903</td>\n",
       "      <td>394054724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>378481214</td>\n",
       "      <td>1426619</td>\n",
       "      <td>12820</td>\n",
       "      <td>26696727</td>\n",
       "      <td>139421</td>\n",
       "      <td>406756801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>381687991</td>\n",
       "      <td>1779083</td>\n",
       "      <td>18547</td>\n",
       "      <td>30623786</td>\n",
       "      <td>177803</td>\n",
       "      <td>414287210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>390751401</td>\n",
       "      <td>2001842</td>\n",
       "      <td>5957</td>\n",
       "      <td>31198479</td>\n",
       "      <td>202863</td>\n",
       "      <td>424160542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>382144912</td>\n",
       "      <td>2192046</td>\n",
       "      <td>19525</td>\n",
       "      <td>32813021</td>\n",
       "      <td>210747</td>\n",
       "      <td>417380251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>375982127</td>\n",
       "      <td>2195412</td>\n",
       "      <td>920</td>\n",
       "      <td>32333073</td>\n",
       "      <td>168289</td>\n",
       "      <td>410679821</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Hydraulic turbine    Solar  Tidal power turbine  Wind power turbine  \\\n",
       "Year                                                                        \n",
       "2005          358446082        0                27643             1551780   \n",
       "2006          349468303        0                19144             2448335   \n",
       "2007          364055135        0                22524             2977206   \n",
       "2008          373822743        0                15018             3750629   \n",
       "2009          365110421     4502                29954             6575235   \n",
       "2010          347980845   115745                27680             8636950   \n",
       "2011          372076377   256935                26095            10086688   \n",
       "2012          376574355   315843                27128            11198373   \n",
       "2013          387980873   360478                14830            11033989   \n",
       "2014          378786255   325184                15483            12688899   \n",
       "2015          378481214  1426619                12820            26696727   \n",
       "2016          381687991  1779083                18547            30623786   \n",
       "2017          390751401  2001842                 5957            31198479   \n",
       "2018          382144912  2192046                19525            32813021   \n",
       "2019          375982127  2195412                  920            32333073   \n",
       "\n",
       "      Other types of electricity generation  Total renewable energy generation  \n",
       "Year                                                                            \n",
       "2005                                      0                          360025505  \n",
       "2006                                      0                          351935782  \n",
       "2007                                      0                          367054865  \n",
       "2008                                      0                          377588390  \n",
       "2009                                1918497                          373638609  \n",
       "2010                                2975953                          359737173  \n",
       "2011                                2509521                          384955616  \n",
       "2012                                2723937                          390839636  \n",
       "2013                                2441392                          401831562  \n",
       "2014                                2238903                          394054724  \n",
       "2015                                 139421                          406756801  \n",
       "2016                                 177803                          414287210  \n",
       "2017                                 202863                          424160542  \n",
       "2018                                 210747                          417380251  \n",
       "2019                                 168289                          410679821  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rename the total column\n",
    "renewable_energy_data = renewable_energy_data.rename(columns = {\n",
    "    \"Total hydro, tidal, wind, solar and other generation\" : \"Total renewable energy generation\"\n",
    "})\n",
    "renewable_energy_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Output this cleaned renewable energy production table\n",
    "renewable_energy_data.to_csv(\"Resources/Clean Data/Table 5a.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use Raw Data to Generate Oil Energy Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Combustion turbine</th>\n",
       "      <th>Conventional steam turbine</th>\n",
       "      <th>Internal combustion turbine</th>\n",
       "      <th>Nuclear steam turbine</th>\n",
       "      <th>Total electricity production from combustible fuels</th>\n",
       "      <th>Total thermal generation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>25892974</td>\n",
       "      <td>130320252</td>\n",
       "      <td>1301338</td>\n",
       "      <td>86829896</td>\n",
       "      <td>0</td>\n",
       "      <td>244344460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>25811955</td>\n",
       "      <td>118877657</td>\n",
       "      <td>3591329</td>\n",
       "      <td>92418514</td>\n",
       "      <td>0</td>\n",
       "      <td>240699455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>32237570</td>\n",
       "      <td>127778534</td>\n",
       "      <td>1498789</td>\n",
       "      <td>88190431</td>\n",
       "      <td>0</td>\n",
       "      <td>249705324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>30782510</td>\n",
       "      <td>117666179</td>\n",
       "      <td>1425052</td>\n",
       "      <td>90585015</td>\n",
       "      <td>0</td>\n",
       "      <td>240458756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>32728246</td>\n",
       "      <td>102607748</td>\n",
       "      <td>1570922</td>\n",
       "      <td>84991779</td>\n",
       "      <td>0</td>\n",
       "      <td>221898695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>38019362</td>\n",
       "      <td>103118558</td>\n",
       "      <td>1615274</td>\n",
       "      <td>85526588</td>\n",
       "      <td>0</td>\n",
       "      <td>228279782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>44283027</td>\n",
       "      <td>99411207</td>\n",
       "      <td>1609096</td>\n",
       "      <td>88291216</td>\n",
       "      <td>0</td>\n",
       "      <td>233594546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>45330296</td>\n",
       "      <td>89871261</td>\n",
       "      <td>1555195</td>\n",
       "      <td>89492389</td>\n",
       "      <td>0</td>\n",
       "      <td>226249141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>43756123</td>\n",
       "      <td>90388012</td>\n",
       "      <td>1645827</td>\n",
       "      <td>97584431</td>\n",
       "      <td>0</td>\n",
       "      <td>233374393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>101207807</td>\n",
       "      <td>134318871</td>\n",
       "      <td>235526678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>96045793</td>\n",
       "      <td>137524464</td>\n",
       "      <td>233570257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>95687312</td>\n",
       "      <td>136356480</td>\n",
       "      <td>232043792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>95565022</td>\n",
       "      <td>129194240</td>\n",
       "      <td>224759262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>95029596</td>\n",
       "      <td>127916909</td>\n",
       "      <td>222946505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>95469256</td>\n",
       "      <td>127263359</td>\n",
       "      <td>222732615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Combustion turbine  Conventional steam turbine  \\\n",
       "Year                                                   \n",
       "2005            25892974                   130320252   \n",
       "2006            25811955                   118877657   \n",
       "2007            32237570                   127778534   \n",
       "2008            30782510                   117666179   \n",
       "2009            32728246                   102607748   \n",
       "2010            38019362                   103118558   \n",
       "2011            44283027                    99411207   \n",
       "2012            45330296                    89871261   \n",
       "2013            43756123                    90388012   \n",
       "2014                   0                           0   \n",
       "2015                   0                           0   \n",
       "2016                   0                           0   \n",
       "2017                   0                           0   \n",
       "2018                   0                           0   \n",
       "2019                   0                           0   \n",
       "\n",
       "      Internal combustion turbine  Nuclear steam turbine  \\\n",
       "Year                                                       \n",
       "2005                      1301338               86829896   \n",
       "2006                      3591329               92418514   \n",
       "2007                      1498789               88190431   \n",
       "2008                      1425052               90585015   \n",
       "2009                      1570922               84991779   \n",
       "2010                      1615274               85526588   \n",
       "2011                      1609096               88291216   \n",
       "2012                      1555195               89492389   \n",
       "2013                      1645827               97584431   \n",
       "2014                            0              101207807   \n",
       "2015                            0               96045793   \n",
       "2016                            0               95687312   \n",
       "2017                            0               95565022   \n",
       "2018                            0               95029596   \n",
       "2019                            0               95469256   \n",
       "\n",
       "      Total electricity production from combustible fuels  \\\n",
       "Year                                                        \n",
       "2005                                                  0     \n",
       "2006                                                  0     \n",
       "2007                                                  0     \n",
       "2008                                                  0     \n",
       "2009                                                  0     \n",
       "2010                                                  0     \n",
       "2011                                                  0     \n",
       "2012                                                  0     \n",
       "2013                                                  0     \n",
       "2014                                          134318871     \n",
       "2015                                          137524464     \n",
       "2016                                          136356480     \n",
       "2017                                          129194240     \n",
       "2018                                          127916909     \n",
       "2019                                          127263359     \n",
       "\n",
       "      Total thermal generation  \n",
       "Year                            \n",
       "2005                 244344460  \n",
       "2006                 240699455  \n",
       "2007                 249705324  \n",
       "2008                 240458756  \n",
       "2009                 221898695  \n",
       "2010                 228279782  \n",
       "2011                 233594546  \n",
       "2012                 226249141  \n",
       "2013                 233374393  \n",
       "2014                 235526678  \n",
       "2015                 233570257  \n",
       "2016                 232043792  \n",
       "2017                 224759262  \n",
       "2018                 222946505  \n",
       "2019                 222732615  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select oil energy columns\n",
    "oil_energy_data = final_energy_data[[\"Combustion turbine\", \"Conventional steam turbine\",\"Internal combustion turbine\",\n",
    "                                     \"Nuclear steam turbine\",\"Total electricity production from combustible fuels\",\n",
    "                                     \"Total thermal generation\"]]\n",
    "oil_energy_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\laich\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Combustion turbine</th>\n",
       "      <th>Conventional steam turbine</th>\n",
       "      <th>Internal combustion turbine</th>\n",
       "      <th>Nuclear steam turbine</th>\n",
       "      <th>Total electricity production from combustible fuels</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>2005</th>\n",
       "      <td>25892974</td>\n",
       "      <td>130320252</td>\n",
       "      <td>1301338</td>\n",
       "      <td>86829896</td>\n",
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       "      <td>244344460</td>\n",
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       "      <td>25811955</td>\n",
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       "      <td>3591329</td>\n",
       "      <td>92418514</td>\n",
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       "      <td>240699455</td>\n",
       "      <td>148280941</td>\n",
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       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>32237570</td>\n",
       "      <td>127778534</td>\n",
       "      <td>1498789</td>\n",
       "      <td>88190431</td>\n",
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       "      <td>249705324</td>\n",
       "      <td>161514893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>30782510</td>\n",
       "      <td>117666179</td>\n",
       "      <td>1425052</td>\n",
       "      <td>90585015</td>\n",
       "      <td>0</td>\n",
       "      <td>240458756</td>\n",
       "      <td>149873741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>32728246</td>\n",
       "      <td>102607748</td>\n",
       "      <td>1570922</td>\n",
       "      <td>84991779</td>\n",
       "      <td>0</td>\n",
       "      <td>221898695</td>\n",
       "      <td>136906916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>38019362</td>\n",
       "      <td>103118558</td>\n",
       "      <td>1615274</td>\n",
       "      <td>85526588</td>\n",
       "      <td>0</td>\n",
       "      <td>228279782</td>\n",
       "      <td>142753194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>44283027</td>\n",
       "      <td>99411207</td>\n",
       "      <td>1609096</td>\n",
       "      <td>88291216</td>\n",
       "      <td>0</td>\n",
       "      <td>233594546</td>\n",
       "      <td>145303330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>45330296</td>\n",
       "      <td>89871261</td>\n",
       "      <td>1555195</td>\n",
       "      <td>89492389</td>\n",
       "      <td>0</td>\n",
       "      <td>226249141</td>\n",
       "      <td>136756752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>43756123</td>\n",
       "      <td>90388012</td>\n",
       "      <td>1645827</td>\n",
       "      <td>97584431</td>\n",
       "      <td>0</td>\n",
       "      <td>233374393</td>\n",
       "      <td>135789962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>101207807</td>\n",
       "      <td>134318871</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>96045793</td>\n",
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       "      <td>233570257</td>\n",
       "      <td>137524464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>95687312</td>\n",
       "      <td>136356480</td>\n",
       "      <td>232043792</td>\n",
       "      <td>136356480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>95565022</td>\n",
       "      <td>129194240</td>\n",
       "      <td>224759262</td>\n",
       "      <td>129194240</td>\n",
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       "    <tr>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>95029596</td>\n",
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       "      <td>222946505</td>\n",
       "      <td>127916909</td>\n",
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       "      <th>2019</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>95469256</td>\n",
       "      <td>127263359</td>\n",
       "      <td>222732615</td>\n",
       "      <td>127263359</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Combustion turbine  Conventional steam turbine  \\\n",
       "Year                                                   \n",
       "2005            25892974                   130320252   \n",
       "2006            25811955                   118877657   \n",
       "2007            32237570                   127778534   \n",
       "2008            30782510                   117666179   \n",
       "2009            32728246                   102607748   \n",
       "2010            38019362                   103118558   \n",
       "2011            44283027                    99411207   \n",
       "2012            45330296                    89871261   \n",
       "2013            43756123                    90388012   \n",
       "2014                   0                           0   \n",
       "2015                   0                           0   \n",
       "2016                   0                           0   \n",
       "2017                   0                           0   \n",
       "2018                   0                           0   \n",
       "2019                   0                           0   \n",
       "\n",
       "      Internal combustion turbine  Nuclear steam turbine  \\\n",
       "Year                                                       \n",
       "2005                      1301338               86829896   \n",
       "2006                      3591329               92418514   \n",
       "2007                      1498789               88190431   \n",
       "2008                      1425052               90585015   \n",
       "2009                      1570922               84991779   \n",
       "2010                      1615274               85526588   \n",
       "2011                      1609096               88291216   \n",
       "2012                      1555195               89492389   \n",
       "2013                      1645827               97584431   \n",
       "2014                            0              101207807   \n",
       "2015                            0               96045793   \n",
       "2016                            0               95687312   \n",
       "2017                            0               95565022   \n",
       "2018                            0               95029596   \n",
       "2019                            0               95469256   \n",
       "\n",
       "      Total electricity production from combustible fuels  \\\n",
       "Year                                                        \n",
       "2005                                                  0     \n",
       "2006                                                  0     \n",
       "2007                                                  0     \n",
       "2008                                                  0     \n",
       "2009                                                  0     \n",
       "2010                                                  0     \n",
       "2011                                                  0     \n",
       "2012                                                  0     \n",
       "2013                                                  0     \n",
       "2014                                          134318871     \n",
       "2015                                          137524464     \n",
       "2016                                          136356480     \n",
       "2017                                          129194240     \n",
       "2018                                          127916909     \n",
       "2019                                          127263359     \n",
       "\n",
       "      Total thermal generation  Combustion fuels  \n",
       "Year                                              \n",
       "2005                 244344460         157514564  \n",
       "2006                 240699455         148280941  \n",
       "2007                 249705324         161514893  \n",
       "2008                 240458756         149873741  \n",
       "2009                 221898695         136906916  \n",
       "2010                 228279782         142753194  \n",
       "2011                 233594546         145303330  \n",
       "2012                 226249141         136756752  \n",
       "2013                 233374393         135789962  \n",
       "2014                 235526678         134318871  \n",
       "2015                 233570257         137524464  \n",
       "2016                 232043792         136356480  \n",
       "2017                 224759262         129194240  \n",
       "2018                 222946505         127916909  \n",
       "2019                 222732615         127263359  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combined columns that contain 0 into one complete column\n",
    "oil_energy_data[\"Combustion fuels\"] = (oil_energy_data[\"Combustion turbine\"] + \n",
    "                                        oil_energy_data[\"Conventional steam turbine\"] + \n",
    "                                        oil_energy_data[\"Internal combustion turbine\"] + \n",
    "                                        oil_energy_data[\"Total electricity production from combustible fuels\"])\n",
    "oil_energy_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Nuclear steam turbine</th>\n",
       "      <th>Total thermal generation</th>\n",
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       "  <tbody>\n",
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       "      <td>86829896</td>\n",
       "      <td>244344460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>148280941</td>\n",
       "      <td>92418514</td>\n",
       "      <td>240699455</td>\n",
       "    </tr>\n",
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       "      <th>2007</th>\n",
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       "      <td>88190431</td>\n",
       "      <td>249705324</td>\n",
       "    </tr>\n",
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       "      <th>2008</th>\n",
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       "      <td>90585015</td>\n",
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       "      <td>221898695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>142753194</td>\n",
       "      <td>85526588</td>\n",
       "      <td>228279782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>145303330</td>\n",
       "      <td>88291216</td>\n",
       "      <td>233594546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>136756752</td>\n",
       "      <td>89492389</td>\n",
       "      <td>226249141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>135789962</td>\n",
       "      <td>97584431</td>\n",
       "      <td>233374393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>134318871</td>\n",
       "      <td>101207807</td>\n",
       "      <td>235526678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>137524464</td>\n",
       "      <td>96045793</td>\n",
       "      <td>233570257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>136356480</td>\n",
       "      <td>95687312</td>\n",
       "      <td>232043792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>129194240</td>\n",
       "      <td>95565022</td>\n",
       "      <td>224759262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>127916909</td>\n",
       "      <td>95029596</td>\n",
       "      <td>222946505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>127263359</td>\n",
       "      <td>95469256</td>\n",
       "      <td>222732615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Combustion fuels  Nuclear steam turbine  Total thermal generation\n",
       "Year                                                                   \n",
       "2005         157514564               86829896                 244344460\n",
       "2006         148280941               92418514                 240699455\n",
       "2007         161514893               88190431                 249705324\n",
       "2008         149873741               90585015                 240458756\n",
       "2009         136906916               84991779                 221898695\n",
       "2010         142753194               85526588                 228279782\n",
       "2011         145303330               88291216                 233594546\n",
       "2012         136756752               89492389                 226249141\n",
       "2013         135789962               97584431                 233374393\n",
       "2014         134318871              101207807                 235526678\n",
       "2015         137524464               96045793                 233570257\n",
       "2016         136356480               95687312                 232043792\n",
       "2017         129194240               95565022                 224759262\n",
       "2018         127916909               95029596                 222946505\n",
       "2019         127263359               95469256                 222732615"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use the combined column as new table\n",
    "oil_energy_data = oil_energy_data[[\"Combustion fuels\", \"Nuclear steam turbine\", \"Total thermal generation\"]]\n",
    "oil_energy_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Output this cleaned oil energy production table\n",
    "oil_energy_data.to_csv(\"Resources/Clean Data/Table 5b.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract and Clean Currency Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Date</th>\n",
       "      <th>USD/CAD</th>\n",
       "      <th>CAD/USD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>1.205198</td>\n",
       "      <td>0.829739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005-02-01</td>\n",
       "      <td>1.239963</td>\n",
       "      <td>0.806476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005-03-01</td>\n",
       "      <td>1.233808</td>\n",
       "      <td>0.810499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005-04-01</td>\n",
       "      <td>1.214291</td>\n",
       "      <td>0.823526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005-05-01</td>\n",
       "      <td>1.249595</td>\n",
       "      <td>0.800259</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date   USD/CAD   CAD/USD\n",
       "0  2005-01-01  1.205198  0.829739\n",
       "1  2005-02-01  1.239963  0.806476\n",
       "2  2005-03-01  1.233808  0.810499\n",
       "3  2005-04-01  1.214291  0.823526\n",
       "4  2005-05-01  1.249595  0.800259"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# File to Load \n",
    "currency_data_filepath = \"Resources/Clean Data/Monthly_Exchange_Rate.csv\"\n",
    "\n",
    "# Read Data File and store into Pandas DataFrames\n",
    "raw_currency_data = pd.read_csv(currency_data_filepath)\n",
    "raw_currency_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        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>Date</th>\n",
       "      <th>USD/CAD</th>\n",
       "      <th>CAD/USD</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>1.205198</td>\n",
       "      <td>0.829739</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005-02-01</td>\n",
       "      <td>1.239963</td>\n",
       "      <td>0.806476</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005-03-01</td>\n",
       "      <td>1.233808</td>\n",
       "      <td>0.810499</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005-04-01</td>\n",
       "      <td>1.214291</td>\n",
       "      <td>0.823526</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005-05-01</td>\n",
       "      <td>1.249595</td>\n",
       "      <td>0.800259</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>2020-06-01</td>\n",
       "      <td>1.369917</td>\n",
       "      <td>0.729971</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>1.358661</td>\n",
       "      <td>0.736019</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>2020-08-01</td>\n",
       "      <td>1.341830</td>\n",
       "      <td>0.745251</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>2020-09-01</td>\n",
       "      <td>1.301410</td>\n",
       "      <td>0.768397</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>2020-10-01</td>\n",
       "      <td>1.328795</td>\n",
       "      <td>0.752561</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>190 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date   USD/CAD   CAD/USD  Year\n",
       "0    2005-01-01  1.205198  0.829739  2005\n",
       "1    2005-02-01  1.239963  0.806476  2005\n",
       "2    2005-03-01  1.233808  0.810499  2005\n",
       "3    2005-04-01  1.214291  0.823526  2005\n",
       "4    2005-05-01  1.249595  0.800259  2005\n",
       "..          ...       ...       ...   ...\n",
       "185  2020-06-01  1.369917  0.729971  2020\n",
       "186  2020-07-01  1.358661  0.736019  2020\n",
       "187  2020-08-01  1.341830  0.745251  2020\n",
       "188  2020-09-01  1.301410  0.768397  2020\n",
       "189  2020-10-01  1.328795  0.752561  2020\n",
       "\n",
       "[190 rows x 4 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extreact from date column to get year \n",
    "raw_currency_data[\"Year\"] = raw_currency_data[\"Date\"].str[0:4] \n",
    "raw_currency_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        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>CAD/USD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>0.825173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>0.883881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>0.930507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>0.955629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>0.874752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>0.963620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>1.016032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>0.999054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>0.971670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0.908495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0.788476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0.755048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0.767798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0.774668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0.751779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>0.742354</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       CAD/USD\n",
       "Year          \n",
       "2005  0.825173\n",
       "2006  0.883881\n",
       "2007  0.930507\n",
       "2008  0.955629\n",
       "2009  0.874752\n",
       "2010  0.963620\n",
       "2011  1.016032\n",
       "2012  0.999054\n",
       "2013  0.971670\n",
       "2014  0.908495\n",
       "2015  0.788476\n",
       "2016  0.755048\n",
       "2017  0.767798\n",
       "2018  0.774668\n",
       "2019  0.751779\n",
       "2020  0.742354"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Groupby to get yearly currency data\n",
    "yearly_exchange_rate = pd.DataFrame(raw_currency_data.groupby(\"Year\")[\"CAD/USD\"].mean())\n",
    "yearly_exchange_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>Candian Dollar Index</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>0.825173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>0.883881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>0.930507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>0.955629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>0.874752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>0.963620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>1.016032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>0.999054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>0.971670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0.908495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0.788476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0.755048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0.767798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0.774668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0.751779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>0.742354</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Candian Dollar Index\n",
       "Year                      \n",
       "2005              0.825173\n",
       "2006              0.883881\n",
       "2007              0.930507\n",
       "2008              0.955629\n",
       "2009              0.874752\n",
       "2010              0.963620\n",
       "2011              1.016032\n",
       "2012              0.999054\n",
       "2013              0.971670\n",
       "2014              0.908495\n",
       "2015              0.788476\n",
       "2016              0.755048\n",
       "2017              0.767798\n",
       "2018              0.774668\n",
       "2019              0.751779\n",
       "2020              0.742354"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Change column name\n",
    "yearly_exchange_rate = yearly_exchange_rate.rename(columns = {\"CAD/USD\" : \"Candian Dollar Index\"})\n",
    "yearly_exchange_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Output this cleaned yearly exchange rate table\n",
    "yearly_exchange_rate.to_csv(\"Resources/Clean Data/Table 6.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Transformation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# File to Load \n",
    "renewable_data_filepath = \"Resources/Clean Data/Table 5a.csv\"\n",
    "oil_data_filepath = \"Resources/Clean Data/Table 5b.csv\"\n",
    "yearly_currency_filepath = \"Resources/Clean Data/Table 6.csv\"\n",
    "\n",
    "# Read Data File and store into Pandas DataFrames\n",
    "renewable_energy_data = pd.read_csv(renewable_data_filepath)\n",
    "oil_energy_data = pd.read_csv(oil_data_filepath)\n",
    "yearly_currency_data = pd.read_csv(yearly_currency_filepath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Year</th>\n",
       "      <th>Candian Dollar Index</th>\n",
       "      <th>Hydraulic turbine</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Tidal power turbine</th>\n",
       "      <th>Wind power turbine</th>\n",
       "      <th>Other types of electricity generation</th>\n",
       "      <th>Total renewable energy generation</th>\n",
       "      <th>Combustion fuels</th>\n",
       "      <th>Nuclear steam turbine</th>\n",
       "      <th>Total thermal generation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>0.825173</td>\n",
       "      <td>358446082</td>\n",
       "      <td>0</td>\n",
       "      <td>27643</td>\n",
       "      <td>1551780</td>\n",
       "      <td>0</td>\n",
       "      <td>360025505</td>\n",
       "      <td>157514564</td>\n",
       "      <td>86829896</td>\n",
       "      <td>244344460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2006</td>\n",
       "      <td>0.883881</td>\n",
       "      <td>349468303</td>\n",
       "      <td>0</td>\n",
       "      <td>19144</td>\n",
       "      <td>2448335</td>\n",
       "      <td>0</td>\n",
       "      <td>351935782</td>\n",
       "      <td>148280941</td>\n",
       "      <td>92418514</td>\n",
       "      <td>240699455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>0.930507</td>\n",
       "      <td>364055135</td>\n",
       "      <td>0</td>\n",
       "      <td>22524</td>\n",
       "      <td>2977206</td>\n",
       "      <td>0</td>\n",
       "      <td>367054865</td>\n",
       "      <td>161514893</td>\n",
       "      <td>88190431</td>\n",
       "      <td>249705324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>0.955629</td>\n",
       "      <td>373822743</td>\n",
       "      <td>0</td>\n",
       "      <td>15018</td>\n",
       "      <td>3750629</td>\n",
       "      <td>0</td>\n",
       "      <td>377588390</td>\n",
       "      <td>149873741</td>\n",
       "      <td>90585015</td>\n",
       "      <td>240458756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>0.874752</td>\n",
       "      <td>365110421</td>\n",
       "      <td>4502</td>\n",
       "      <td>29954</td>\n",
       "      <td>6575235</td>\n",
       "      <td>1918497</td>\n",
       "      <td>373638609</td>\n",
       "      <td>136906916</td>\n",
       "      <td>84991779</td>\n",
       "      <td>221898695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2010</td>\n",
       "      <td>0.963620</td>\n",
       "      <td>347980845</td>\n",
       "      <td>115745</td>\n",
       "      <td>27680</td>\n",
       "      <td>8636950</td>\n",
       "      <td>2975953</td>\n",
       "      <td>359737173</td>\n",
       "      <td>142753194</td>\n",
       "      <td>85526588</td>\n",
       "      <td>228279782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2011</td>\n",
       "      <td>1.016032</td>\n",
       "      <td>372076377</td>\n",
       "      <td>256935</td>\n",
       "      <td>26095</td>\n",
       "      <td>10086688</td>\n",
       "      <td>2509521</td>\n",
       "      <td>384955616</td>\n",
       "      <td>145303330</td>\n",
       "      <td>88291216</td>\n",
       "      <td>233594546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2012</td>\n",
       "      <td>0.999054</td>\n",
       "      <td>376574355</td>\n",
       "      <td>315843</td>\n",
       "      <td>27128</td>\n",
       "      <td>11198373</td>\n",
       "      <td>2723937</td>\n",
       "      <td>390839636</td>\n",
       "      <td>136756752</td>\n",
       "      <td>89492389</td>\n",
       "      <td>226249141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2013</td>\n",
       "      <td>0.971670</td>\n",
       "      <td>387980873</td>\n",
       "      <td>360478</td>\n",
       "      <td>14830</td>\n",
       "      <td>11033989</td>\n",
       "      <td>2441392</td>\n",
       "      <td>401831562</td>\n",
       "      <td>135789962</td>\n",
       "      <td>97584431</td>\n",
       "      <td>233374393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014</td>\n",
       "      <td>0.908495</td>\n",
       "      <td>378786255</td>\n",
       "      <td>325184</td>\n",
       "      <td>15483</td>\n",
       "      <td>12688899</td>\n",
       "      <td>2238903</td>\n",
       "      <td>394054724</td>\n",
       "      <td>134318871</td>\n",
       "      <td>101207807</td>\n",
       "      <td>235526678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2015</td>\n",
       "      <td>0.788476</td>\n",
       "      <td>378481214</td>\n",
       "      <td>1426619</td>\n",
       "      <td>12820</td>\n",
       "      <td>26696727</td>\n",
       "      <td>139421</td>\n",
       "      <td>406756801</td>\n",
       "      <td>137524464</td>\n",
       "      <td>96045793</td>\n",
       "      <td>233570257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2016</td>\n",
       "      <td>0.755048</td>\n",
       "      <td>381687991</td>\n",
       "      <td>1779083</td>\n",
       "      <td>18547</td>\n",
       "      <td>30623786</td>\n",
       "      <td>177803</td>\n",
       "      <td>414287210</td>\n",
       "      <td>136356480</td>\n",
       "      <td>95687312</td>\n",
       "      <td>232043792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2017</td>\n",
       "      <td>0.767798</td>\n",
       "      <td>390751401</td>\n",
       "      <td>2001842</td>\n",
       "      <td>5957</td>\n",
       "      <td>31198479</td>\n",
       "      <td>202863</td>\n",
       "      <td>424160542</td>\n",
       "      <td>129194240</td>\n",
       "      <td>95565022</td>\n",
       "      <td>224759262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2018</td>\n",
       "      <td>0.774668</td>\n",
       "      <td>382144912</td>\n",
       "      <td>2192046</td>\n",
       "      <td>19525</td>\n",
       "      <td>32813021</td>\n",
       "      <td>210747</td>\n",
       "      <td>417380251</td>\n",
       "      <td>127916909</td>\n",
       "      <td>95029596</td>\n",
       "      <td>222946505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019</td>\n",
       "      <td>0.751779</td>\n",
       "      <td>375982127</td>\n",
       "      <td>2195412</td>\n",
       "      <td>920</td>\n",
       "      <td>32333073</td>\n",
       "      <td>168289</td>\n",
       "      <td>410679821</td>\n",
       "      <td>127263359</td>\n",
       "      <td>95469256</td>\n",
       "      <td>222732615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year  Candian Dollar Index  Hydraulic turbine    Solar  \\\n",
       "0   2005              0.825173          358446082        0   \n",
       "1   2006              0.883881          349468303        0   \n",
       "2   2007              0.930507          364055135        0   \n",
       "3   2008              0.955629          373822743        0   \n",
       "4   2009              0.874752          365110421     4502   \n",
       "5   2010              0.963620          347980845   115745   \n",
       "6   2011              1.016032          372076377   256935   \n",
       "7   2012              0.999054          376574355   315843   \n",
       "8   2013              0.971670          387980873   360478   \n",
       "9   2014              0.908495          378786255   325184   \n",
       "10  2015              0.788476          378481214  1426619   \n",
       "11  2016              0.755048          381687991  1779083   \n",
       "12  2017              0.767798          390751401  2001842   \n",
       "13  2018              0.774668          382144912  2192046   \n",
       "14  2019              0.751779          375982127  2195412   \n",
       "\n",
       "    Tidal power turbine  Wind power turbine  \\\n",
       "0                 27643             1551780   \n",
       "1                 19144             2448335   \n",
       "2                 22524             2977206   \n",
       "3                 15018             3750629   \n",
       "4                 29954             6575235   \n",
       "5                 27680             8636950   \n",
       "6                 26095            10086688   \n",
       "7                 27128            11198373   \n",
       "8                 14830            11033989   \n",
       "9                 15483            12688899   \n",
       "10                12820            26696727   \n",
       "11                18547            30623786   \n",
       "12                 5957            31198479   \n",
       "13                19525            32813021   \n",
       "14                  920            32333073   \n",
       "\n",
       "    Other types of electricity generation  Total renewable energy generation  \\\n",
       "0                                       0                          360025505   \n",
       "1                                       0                          351935782   \n",
       "2                                       0                          367054865   \n",
       "3                                       0                          377588390   \n",
       "4                                 1918497                          373638609   \n",
       "5                                 2975953                          359737173   \n",
       "6                                 2509521                          384955616   \n",
       "7                                 2723937                          390839636   \n",
       "8                                 2441392                          401831562   \n",
       "9                                 2238903                          394054724   \n",
       "10                                 139421                          406756801   \n",
       "11                                 177803                          414287210   \n",
       "12                                 202863                          424160542   \n",
       "13                                 210747                          417380251   \n",
       "14                                 168289                          410679821   \n",
       "\n",
       "    Combustion fuels  Nuclear steam turbine  Total thermal generation  \n",
       "0          157514564               86829896                 244344460  \n",
       "1          148280941               92418514                 240699455  \n",
       "2          161514893               88190431                 249705324  \n",
       "3          149873741               90585015                 240458756  \n",
       "4          136906916               84991779                 221898695  \n",
       "5          142753194               85526588                 228279782  \n",
       "6          145303330               88291216                 233594546  \n",
       "7          136756752               89492389                 226249141  \n",
       "8          135789962               97584431                 233374393  \n",
       "9          134318871              101207807                 235526678  \n",
       "10         137524464               96045793                 233570257  \n",
       "11         136356480               95687312                 232043792  \n",
       "12         129194240               95565022                 224759262  \n",
       "13         127916909               95029596                 222946505  \n",
       "14         127263359               95469256                 222732615  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combine the three data together\n",
    "merged_canada_data = pd.merge(yearly_currency_data, renewable_energy_data, on = \"Year\", how = \"inner\")\n",
    "merged_canada_data = pd.merge(merged_canada_data, oil_energy_data, on = \"Year\", how = \"inner\")\n",
    "merged_canada_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Candian Dollar Index</th>\n",
       "      <th>Hydraulic turbine</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Tidal power turbine</th>\n",
       "      <th>Wind power turbine</th>\n",
       "      <th>Other types of electricity generation</th>\n",
       "      <th>Total renewable energy generation</th>\n",
       "      <th>Combustion fuels</th>\n",
       "      <th>Nuclear steam turbine</th>\n",
       "      <th>Total thermal generation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>0.825173</td>\n",
       "      <td>358446082</td>\n",
       "      <td>0</td>\n",
       "      <td>27643</td>\n",
       "      <td>1551780</td>\n",
       "      <td>0</td>\n",
       "      <td>360025505</td>\n",
       "      <td>157514564</td>\n",
       "      <td>86829896</td>\n",
       "      <td>244344460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>0.883881</td>\n",
       "      <td>349468303</td>\n",
       "      <td>0</td>\n",
       "      <td>19144</td>\n",
       "      <td>2448335</td>\n",
       "      <td>0</td>\n",
       "      <td>351935782</td>\n",
       "      <td>148280941</td>\n",
       "      <td>92418514</td>\n",
       "      <td>240699455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>0.930507</td>\n",
       "      <td>364055135</td>\n",
       "      <td>0</td>\n",
       "      <td>22524</td>\n",
       "      <td>2977206</td>\n",
       "      <td>0</td>\n",
       "      <td>367054865</td>\n",
       "      <td>161514893</td>\n",
       "      <td>88190431</td>\n",
       "      <td>249705324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>0.955629</td>\n",
       "      <td>373822743</td>\n",
       "      <td>0</td>\n",
       "      <td>15018</td>\n",
       "      <td>3750629</td>\n",
       "      <td>0</td>\n",
       "      <td>377588390</td>\n",
       "      <td>149873741</td>\n",
       "      <td>90585015</td>\n",
       "      <td>240458756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>0.874752</td>\n",
       "      <td>365110421</td>\n",
       "      <td>4502</td>\n",
       "      <td>29954</td>\n",
       "      <td>6575235</td>\n",
       "      <td>1918497</td>\n",
       "      <td>373638609</td>\n",
       "      <td>136906916</td>\n",
       "      <td>84991779</td>\n",
       "      <td>221898695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>0.963620</td>\n",
       "      <td>347980845</td>\n",
       "      <td>115745</td>\n",
       "      <td>27680</td>\n",
       "      <td>8636950</td>\n",
       "      <td>2975953</td>\n",
       "      <td>359737173</td>\n",
       "      <td>142753194</td>\n",
       "      <td>85526588</td>\n",
       "      <td>228279782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>1.016032</td>\n",
       "      <td>372076377</td>\n",
       "      <td>256935</td>\n",
       "      <td>26095</td>\n",
       "      <td>10086688</td>\n",
       "      <td>2509521</td>\n",
       "      <td>384955616</td>\n",
       "      <td>145303330</td>\n",
       "      <td>88291216</td>\n",
       "      <td>233594546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>0.999054</td>\n",
       "      <td>376574355</td>\n",
       "      <td>315843</td>\n",
       "      <td>27128</td>\n",
       "      <td>11198373</td>\n",
       "      <td>2723937</td>\n",
       "      <td>390839636</td>\n",
       "      <td>136756752</td>\n",
       "      <td>89492389</td>\n",
       "      <td>226249141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>0.971670</td>\n",
       "      <td>387980873</td>\n",
       "      <td>360478</td>\n",
       "      <td>14830</td>\n",
       "      <td>11033989</td>\n",
       "      <td>2441392</td>\n",
       "      <td>401831562</td>\n",
       "      <td>135789962</td>\n",
       "      <td>97584431</td>\n",
       "      <td>233374393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0.908495</td>\n",
       "      <td>378786255</td>\n",
       "      <td>325184</td>\n",
       "      <td>15483</td>\n",
       "      <td>12688899</td>\n",
       "      <td>2238903</td>\n",
       "      <td>394054724</td>\n",
       "      <td>134318871</td>\n",
       "      <td>101207807</td>\n",
       "      <td>235526678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0.788476</td>\n",
       "      <td>378481214</td>\n",
       "      <td>1426619</td>\n",
       "      <td>12820</td>\n",
       "      <td>26696727</td>\n",
       "      <td>139421</td>\n",
       "      <td>406756801</td>\n",
       "      <td>137524464</td>\n",
       "      <td>96045793</td>\n",
       "      <td>233570257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0.755048</td>\n",
       "      <td>381687991</td>\n",
       "      <td>1779083</td>\n",
       "      <td>18547</td>\n",
       "      <td>30623786</td>\n",
       "      <td>177803</td>\n",
       "      <td>414287210</td>\n",
       "      <td>136356480</td>\n",
       "      <td>95687312</td>\n",
       "      <td>232043792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0.767798</td>\n",
       "      <td>390751401</td>\n",
       "      <td>2001842</td>\n",
       "      <td>5957</td>\n",
       "      <td>31198479</td>\n",
       "      <td>202863</td>\n",
       "      <td>424160542</td>\n",
       "      <td>129194240</td>\n",
       "      <td>95565022</td>\n",
       "      <td>224759262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0.774668</td>\n",
       "      <td>382144912</td>\n",
       "      <td>2192046</td>\n",
       "      <td>19525</td>\n",
       "      <td>32813021</td>\n",
       "      <td>210747</td>\n",
       "      <td>417380251</td>\n",
       "      <td>127916909</td>\n",
       "      <td>95029596</td>\n",
       "      <td>222946505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0.751779</td>\n",
       "      <td>375982127</td>\n",
       "      <td>2195412</td>\n",
       "      <td>920</td>\n",
       "      <td>32333073</td>\n",
       "      <td>168289</td>\n",
       "      <td>410679821</td>\n",
       "      <td>127263359</td>\n",
       "      <td>95469256</td>\n",
       "      <td>222732615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Candian Dollar Index  Hydraulic turbine    Solar  Tidal power turbine  \\\n",
       "Year                                                                          \n",
       "2005              0.825173          358446082        0                27643   \n",
       "2006              0.883881          349468303        0                19144   \n",
       "2007              0.930507          364055135        0                22524   \n",
       "2008              0.955629          373822743        0                15018   \n",
       "2009              0.874752          365110421     4502                29954   \n",
       "2010              0.963620          347980845   115745                27680   \n",
       "2011              1.016032          372076377   256935                26095   \n",
       "2012              0.999054          376574355   315843                27128   \n",
       "2013              0.971670          387980873   360478                14830   \n",
       "2014              0.908495          378786255   325184                15483   \n",
       "2015              0.788476          378481214  1426619                12820   \n",
       "2016              0.755048          381687991  1779083                18547   \n",
       "2017              0.767798          390751401  2001842                 5957   \n",
       "2018              0.774668          382144912  2192046                19525   \n",
       "2019              0.751779          375982127  2195412                  920   \n",
       "\n",
       "      Wind power turbine  Other types of electricity generation  \\\n",
       "Year                                                              \n",
       "2005             1551780                                      0   \n",
       "2006             2448335                                      0   \n",
       "2007             2977206                                      0   \n",
       "2008             3750629                                      0   \n",
       "2009             6575235                                1918497   \n",
       "2010             8636950                                2975953   \n",
       "2011            10086688                                2509521   \n",
       "2012            11198373                                2723937   \n",
       "2013            11033989                                2441392   \n",
       "2014            12688899                                2238903   \n",
       "2015            26696727                                 139421   \n",
       "2016            30623786                                 177803   \n",
       "2017            31198479                                 202863   \n",
       "2018            32813021                                 210747   \n",
       "2019            32333073                                 168289   \n",
       "\n",
       "      Total renewable energy generation  Combustion fuels  \\\n",
       "Year                                                        \n",
       "2005                          360025505         157514564   \n",
       "2006                          351935782         148280941   \n",
       "2007                          367054865         161514893   \n",
       "2008                          377588390         149873741   \n",
       "2009                          373638609         136906916   \n",
       "2010                          359737173         142753194   \n",
       "2011                          384955616         145303330   \n",
       "2012                          390839636         136756752   \n",
       "2013                          401831562         135789962   \n",
       "2014                          394054724         134318871   \n",
       "2015                          406756801         137524464   \n",
       "2016                          414287210         136356480   \n",
       "2017                          424160542         129194240   \n",
       "2018                          417380251         127916909   \n",
       "2019                          410679821         127263359   \n",
       "\n",
       "      Nuclear steam turbine  Total thermal generation  \n",
       "Year                                                   \n",
       "2005               86829896                 244344460  \n",
       "2006               92418514                 240699455  \n",
       "2007               88190431                 249705324  \n",
       "2008               90585015                 240458756  \n",
       "2009               84991779                 221898695  \n",
       "2010               85526588                 228279782  \n",
       "2011               88291216                 233594546  \n",
       "2012               89492389                 226249141  \n",
       "2013               97584431                 233374393  \n",
       "2014              101207807                 235526678  \n",
       "2015               96045793                 233570257  \n",
       "2016               95687312                 232043792  \n",
       "2017               95565022                 224759262  \n",
       "2018               95029596                 222946505  \n",
       "2019               95469256                 222732615  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_canada_data = merged_canada_data.set_index(\"Year\")\n",
    "merged_canada_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Output this combined data\n",
    "merged_canada_data.to_csv(\"Transformed Data/Part 4.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# File to Load\n",
    "canada_data_filepath = \"Transformed Data/Part 4.csv\"\n",
    "\n",
    "# Read Data File and store into Pandas DataFrames\n",
    "canada_complete_data = pd.read_csv(canada_data_filepath)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis of Production Growth of Each Rewanable Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate and Format each renewable energy electricity production scatter plot in one figure\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Hydraulic turbine\"]/1000, color = \"orange\", s = 100, \n",
    "            marker = \"o\", label = \"Hydraulic\")\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Solar\"]/1000, color = \"navy\", s = 100, marker = \"+\", \n",
    "            label = \"Solar\")\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Tidal power turbine\"]/1000, color = \"green\", s = 100, \n",
    "            marker = \"*\",label = \"Tidal\")\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Wind power turbine\"]/1000, color = \"darkred\", s = 100, \n",
    "            marker = \"s\", label = \"Wind\")\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Other types of electricity generation\"]/1000, \n",
    "            color = \"indigo\", s = 100, marker = \"x\", label = \"Other\")\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Total renewable energy generation\"]/1000, \n",
    "            color = \"dimgrey\", s = 100, marker = \"p\",label = \"Total\")\n",
    "plt.xticks(canada_complete_data[\"Year\"], canada_complete_data[\"Year\"], rotation = 45)\n",
    "plt.xlim(2004,2020)\n",
    "plt.ylim(-50000, 450000)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Electricty Production (Gigawatt Hours)\")\n",
    "plt.title(\"Annual Electricity Production by Renewable Energy (2005 - 2019)\")\n",
    "plt.legend(loc=\"right\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"Plots\\Question 5 - Time vs. Types of Renewable Sources for Canada.png\", bbox_inches = \"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate and Format a line graph for electricity production by solar, wind, and other source to see the capacity growth trend \n",
    "plt.plot(canada_complete_data[\"Year\"], canada_complete_data[\"Solar\"]/1000, color = \"darkorange\", linewidth = 2.5, \n",
    "         label = \"Solar\")\n",
    "plt.plot(canada_complete_data[\"Year\"], canada_complete_data[\"Tidal power turbine\"]/1000, color = \"green\", linewidth = 2.5,\n",
    "         label = \"Tidal\")\n",
    "plt.plot(canada_complete_data[\"Year\"], canada_complete_data[\"Other types of electricity generation\"]/1000, linewidth = 2.5, \n",
    "         color = \"royalblue\", label = \"Other\")\n",
    "plt.xticks(canada_complete_data[\"Year\"], canada_complete_data[\"Year\"], rotation = 45)\n",
    "plt.xlim(2004,2020)\n",
    "plt.ylim(-100, 3100)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Electricty Production (Gigawatt Hours)\")\n",
    "plt.title(\"Canada Electricity Production by Solar, Wind, and Other (2005 - 2019)\")\n",
    "plt.legend(loc=\"upper right\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"Plots\\Question 5 - Closer Look of Time vs. Types of Renewable Sources Graph for Canada.png\", bbox_inches = \"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis of Production Growth of Each Oil Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HcbP70q9fP1240JZ4MQzDyDYiknCWlqyMg1LVb3FTYJwArPNuu9jU9V/501ZRfsR7B1yH5ioCo8AD6eXy+HFJLXFjbCqSZRiGYeQIUUbxtfYtp9jUIsfiBny+zM4R+cNwgwjx6Wf5yLxOuEib+d4dWCRusS3BzeIQzBOTdTrwhu+nehU4Xtzo+d1wszAkmovOMAzDqKFE6eJrCzzp+6Hq4SbwfEVE5uIW9LoIt+zAGeBGe4vIs7hR6iXAZbpzhdFLcSP5G+NGKcemy5gATBKRFbiW01le1kYfQrvAn/d7dTMiG4ZhGDmCDdT1WB+UYRhG9SAii1R1l9V2bS4+wzAMo0aS1MUnIh1wbrMjcINnt7BzEsHpuuvqmoZhGIaRESo0UCLyOG7s0CvAH3HRdvm4tVBOAG4SkVGq+mY2FDUMwzDqFslaUH9St8x1PEuBF8Stq1Lhqo2GYRiGURUq7INKZJx82PbB/vg2VV0RpXKGYRhG3aXSIAkRmS0iLfwErIuBx0XkruhVMwzDMOoyYaL4Wqrq97hZyB9X1b64QbeGYRiGERlhDFSen5LoTALLkhuGYRhGlIQxUL/DTRO0QlUXiMh+wPJo1TIMwzDqOpWNg6qPWwL54Fiaqn4KnBa1YoZhGEbdJmkLys+Fd3KWdDEMwzCMMsJMFvuOiNwPTAE2xxJV9d3ItDIMwzDqPGEM1I/95+8DaQocnXl1DMMwDMNRqYFS1aOyoYhhGIZhBKnUQInIbxOlq+rvE6UbhmEYRiYI4+LbHPieD5wIfBCNOoZhGIbhCOPi+1NwX0TuxC21bhiGYRiRkc6ChU2A/TKtiGEYhmEECdMHtQQXtQdQH2hN+Yg+wzAMw8g4YfqgTgx8LwHWqWpJRPoYhmEYBhDCxaeq/wN+BJwEDAW6RayTYRiGYYRaD+oqYDKwp98mi8gVUStmGIZh1G3CuPguAg5V1c0AIvJHYC5wX5SKGdlHVfn4g7V0OagNIlLd6hiGUccJE8UnQGlgv9SnGbUIVeXh+2dz9cjJPHz/bFS18kyGYRgREqYF9TgwT0Re9PunAhMi08jIOjHjNP3viwHKPkdcPshaUoZhVBthgiTuAi4ANgLfABeo6j2V5RORvUVkloh8ICLLfF8WIjJWRL4UkUK//TSQZ7SIrBCRj0RkcCC9r4gs8cfuFV9rikgjEZni0+eJSMdAnmEistxvw8IXSeZQVT56f02Nbo0EjdPWYhecubW4hOl/X2wtKcMwqpUKW1Aisntgd6Xfyo6p6sZKZJcA16rquyLSHFgkIjP8sbtV9c6463UDzgK6A+2AmSLSxa9J9RAwAvgP8E/gBGA6rn/sG1U9QETOAv4I/MLrfgvQDzeGa5GIvKyq31Sic8aIVfzTnlvEqWf0rZGtkUTGKUbMSIG1pAzDqB6SufgW4Sp3AdoCq326+PSks0mo6hpgjf9eJCIfAO2TZDkFeEZVtwKficgKoL+IrARaqOpcABGZiHMzTvd5xvr8U4H7fetqMDAjZkS9YTwBeDqZzpkiF1xmyYxTDDNShmFUJxW6+FS1k6rup6qdgA/89/1i6alcxLveegPzfNLlIvKeiDwmIrv5tPbAF4Fsq3xae/89Pr1cHj94+DugVRJZ8XqNEJGFIrJw/fr1qfykCsmGy6yqrsMwxilGJnTPBVenYRg1j7Bz8aVds4hIM+B54GpV/R7nrtsfKMC1sGKT0SZ6Pdck6enm2Zmg+rCq9lPVfq1bt072M0IRxmVWVSOViWi7jz9Yy7TnFlVqnGJsLS5h2nOL+PiDtSlfy6IDDcNIl3Qmiw2NiDTAGafJqvoCgKquU9VSVd0BPAL096evAvYOZO+Acyuu8t/j08vlEZE8oCUumKMiWZGRisss3Yo6keswHVldDmrDqWf0pVF+mCBOaJSfx6ln9KXLQW2qRV/DMOomyYIkrgns7hm3H4vuqxDfFzQB5x68K5De1vdPgZs6aan//jLwlIjchQuS6AzMV9VSESkSkQE4F+H57Bwk/DIwDDdw+HTgDVVVEXkV+EPAfXg8MDqZvlUhHZcZpNavk8x1mKosEWHE5YMAKtW5UX4eQ07qlXIfVCb1NWoXNiDcCEuyV+jmge+PxO2H4XDgPGCJiBT6tN8AZ4tIAc7lthL4JYCqLhORZ4H3cRGAl/kIPoBLgSeAxrjgiOk+fQIwyQdUbMRFAaKqG0VkHLDAn/f7EFGHaRNzmYUl5jIbdMyBdO3WttLzo4i2C2OkMmmcqqqvUTvIhehWo+Yg5m5x9OvXTxcuXJhW3lRaUJBaxR9WdqaNSRTGKRP65jK51nLItL7x90am74FcK19jJyKySFX7xadH2gdVV4i1Roac1KvSfp0ojBOk37+VSPeojVNV9M1Vci1YJNP6Rh3dGmX5WhRq9WEGKkOEMVKpVvzZirYL6g6k/VabzejAXCLXgkUyrW/U0a1Rlm+uvVjUNsIst9EpTJqR3Eil0yrJVrRdUPd7/nJO2i6XbOobJZl8Y861qaQyrW/U0a1Rlm+uvVjURsK0oJ5PkDY104rUFjLpMovKdZjsel27ta1S/mzqGwWZfGPOxri4TJJpfaN2+UZZvrn2YlFbSRZmfiBuXryWIvLzwKEWQH7UiuUywQi5ac8tqlJFHGW0XRTkmr5BMjlFVTankspEcEAU+kYZ3Rpl+VoUas0h2WtuV+BEdi73HqMIuCRCnWoFsYp60DEHVjmqKFmlXxMr+1zTFzI7bisb4+Lir1WVsO2o9I25fFONbq3M5Rtl+ebai0VtJ9lcfC+p6gXAUFW9ILBdiS1YGIqqusziZWXKdZgNcknfTLuKshUskqk+kqj0jcrlG5W+2YxCzcWow+qIZgzTB3VPgjRb7r0ayFS0XbaIWt9MPDBRdOJnI1gkk30kUeobRXRrVPrm2otFMtmZNnzVFc2YrA/qMODHQOu4aY5aAPWjVsxITCZdh9kgKn1rsmsr6qmkMt1HErW+mXb5RqVvVC7JIFFOAZbJPtRsyA1DshZUQ6AZzog1D2zf4+a9M6qJTLoOs0Gm9a3pri2IpuUA0YVtR6VvMvmZlldVfaOOQs3FqMPqjmas8F9Q1TnAHBF5QlX/F6kWhhGSTL6BRv3GnOmWQ9TBF1EHt2QyujUqfaOKQs3FqMOaEM0Yxon7g4j8Hy7kvCy8XFWPjkQjw6iAXHNtVXSNdGVFPSlxpvVNJj9TLt8o9M2lF4uoDF82oxmTESZIYjLwIdAJ+B1uBvIFyTIYRqbJVddW/DUg/WCRbM3UEXVwS6ZdvlHom0mXZK5FHdakOTUrnc1c3CyzfUXkPVU92KfNUdWBGdemGqnKbOZGtKTywEBm33Iz2XrI1oBayIzeuTZOJwp9sx2MA+H/u4/eX8PVIyenpAvAPX85J2mLOiq5yZAqzGa+3X+uEZGfiUhvyq9waxiRko3w32yM28pEyyEbLb7gtepyME5MZlXnqIwq+CKqFnVNmlMzjIG6VURaAtcC1wGPAr/OuCaGUQG1xbWVKZJVeDV1MHQuU1NfLKIyfFFHM6ZCGBdfvqoWZ/zKNQxz8dVszLW1K/FlYsap5hOFK7myZyOq9d0yHDyT0MUX5pV0qYisA94C3gT+rarfVUkbw0iRqMJ/K7pWur70bJLpsG0jenIh6jBqualQqYFS1QNEZB/gCNzksQ+KyLeqWhCZVoaRgJrwwNQ0Mh22bURPFC8WUQ0PiHrYQWVUaqBEpANwOM5A9QKWAW9HqpVhVEB1PzA1kVxp8Rk7ieLFIqoWdXW21MP0Qe3AjXv6g6q+FLlG1YT1QeUWmQj/NYzaSFR9qFH2zVbUBxXGQPUCfgIcCewDLAfmqOqEjGpYzZiByj1yJZjBMIzkpB0koaqLReQT4BOcm+9cnLGqVQbKyD3MtWUYtZswfVALgUbAO7i+pyNt8ljDMAwjasKEmQ9R1fWRa2IYhmEYASqdSUJV1/spjm4Qkd/GtsryicjeIjJLRD4QkWUicpVP311EZojIcv+5WyDPaBFZISIficjgQHpfEVnij90rvsNBRBqJyBSfPk9EOgbyDPPXWC4iw1IsF8MwDKOaqdRAichfgF8AVwACnAHsG0J2CXCtqh4EDAAuE5FuwCjgdVXtDLzu9/HHzsIt63ECbrxVbOXeh4ARQGe/neDTLwK+UdUDgLuBP3pZuwO3AIcC/YFbgobQMAzDqPmEmYvvx6p6Ps4Q/A44DNi7skyqukZV3/Xfi4APgPbAKcCT/rQngVP991OAZ1R1q6p+BqwA+otIW6CFqs5VF3I4MS5PTNZU4BjfuhoMzFDVjar6DTCDnUbNMAzDyAHCGKgt/vMHEWmHm928UyoX8a633sA8YC9VXQPOiAF7+tPaA18Esq3yae399/j0cnlUtQT4DmiVRFa8XiNEZKGILFy/3rrZDMMwahJhDNQrIvIj4P+Ad3ELFj4T9gIi0gx4HrhaVb9PdmqCNE2Snm6enQmqD6tqP1Xt17p16ySqGYZhGNkmTJDEOFX9VlWfx/U9HaiqN4cRLiINcMZpsqq+4JPXebcd/vMrn76K8q7DDsBqn94hQXq5PCKSB7QENiaRZRiGYeQIYYIkfh7bgJ/h+nmOEZE9K8knuMG8H6jqXYFDLwOxqLphwEuB9LN8ZF4nXDDEfO8GLBKRAV7m+XF5YrJOB97w/VSvAseLyG4+OOJ4n2YYhmHkCGHGQV2EC4yY5fcHAf8BuojI71V1UgX5DgfOA5aISKFP+w0wHnhWRC4CPsdFBaKqy0TkWeB9XATgZapa6vNdCjwBNAam+w2cAZwkIitwLaezvKyNIjION4cgwO9VdWOI32oYhmHUEMLMxfd34GJVXef398KFfV8MvKmqPSLXMgvYXHyGYRjVQ0Vz8YUJkugYM06er4AuvkWyPVMKGoZhGEaQMC6+t0TkFeA5v3868KaINAW+jUoxwzAMo24TxkBdBvwct+SG4AbGPu+DEY6KUDfDMAyjDhNmuQ31M5p/p6ozRaQJ0Awoilw7wzAMo84SJsz8Etw0Qn/1Se2BaRHqZBiGYRihgiQuw4WMfw+gqsvZOT2RYRiGYURCGAO1VVW3xXb8jA3JY9MNwzAMo4qEMVBzROQ3QGMROQ4Xzff3aNUyDMMw6jphDNQoYD2wBPgl8E9gTJRKGYZhGEaYKL4dwCN+MwzDMIysUKGBEpH3kmVU1YMzr45hGIZhOJK1oHbggiGewvU5bUlyrmEYhmFklAr7oFS1ADgbNyj3KeA2oDvwpar+LyvaGYZhGHWWpEESqvqhqt6iqn1wraiJwK+zoplhGIZRp0kaJCEi7XFrLA0FvsEZpxezoJdhGIZRx0kWJDEHaA48CwzHLQgI0FBEdrcFAA3DMIwoSdaC2hcXJPFLYEQgXXz6fhHqZWSZbUVFLH/xRTavXUvTNm3oPHQoDZs3r261DMOow1RooFS1Yxb1MKoJVWX++PHMHTcOqV+fkuJi8vLzmTFyJIfdfDP9R41CRKpbTcMw6iDJXHwdVXVlkuMCtFfVVVEoluvkSotk/vjxzL31Vkq27BxFsH3TJgDm3norAIeOHl0tuhmGUbcRt+5gggMiz+Gi/F4CFuGmO8oHDsAtVHgMcIuqzsiOqtHSr18/XbhwYZXlVNQi0dLSGtci2VZUxIN77VXOOMWT16QJv1q3jobNmmVRM8Mw6hIiskhV+8WnJxsHdQZwM9AVeAB4C2esLgY+Ao6uLcYpkwRbJNs3bUJLSti+aRMlW7Yw99ZbmT9+fHWrWMbyF19E6tdPeo7Uq8fyFy1w0zCM7JM0zFxV3wduypIuOc+2oiLmjhtXYYuk5IcfmHvrrfS+4ooa0SLZvHYtJcXFSc8pLS5m85o1WdLIMAxjJ2FmMzdCkmstkqZt2pCXn5/0nPr5+TRt2zZLGhmGYezEDFQGybUWSeehQ9HS0qTn6I4ddB46NEsaGYZh7MQMVAbJtRZJw+bNOezmm8lr0iTh8bwmTThszJgquSO3FRWxbOJE5t9xB8smTmRbUVHasgzDqFuEMlAi0l5EfiwiR8a2EHkeE5GvRGRpIG2siHwpIoV++2ng2GgRWSEiH4nI4EB6XxFZ4o/d68PbEZFGIjLFp88TkY6BPMNEZLnfhoUsiyqTjRZJpiv8/qNGcdiYMeQ1bkyDZs2ol5dHg2bNyGvcmMPGjKH/qFFpyVVV5t1+Ow/utRczL7uMt266iZmXXcaDe+3FvNtvp6LoUcMwjBgVhpmXnSDyR+AXwPtArPZVVT25knxHApuAiaraw6eNBTap6p1x53YDngb6A+2AmUAXVS0VkfnAVcB/cKv53quq00XkV8DBqjpSRM4ChqrqL0Rkd2Ah0A8348UioK+qfpNM30yFmc+7/XYXxffDD7sci7VI0hlXFHX4+raiIpZPm8bmNWto2ratG7dVhZZTVOVgGEbto6Iw80pX1AVOBbqq6tZULqiqbwZbNZVwCvCMv8ZnIrIC6C8iK4EWqjoXQEQmen2m+zxjff6pwP2+dTUYmBGbK1BEZgAn4Axg5MRaHDFDUlpcTP2YIalCiyTqAbUNmzen+3nnpZ0/SK5FM2aDXBm4bRg1iTAG6lOgAZCSgUrC5SJyPq6Vc61v2bTHtZBirPJp2/33+HT85xcAqloiIt8BrYLpCfJEjohw6OjR9L788oy1SHKtwk8lmjFTRjFTZNqQ2FRShpE+YQzUD0ChiLxOwEip6pVpXO8hYBzO9TYO+BNwIW4C2ng0STpp5imHiIzAT4S7zz77JNM7ZTLZIsm1Cj/XohkhOkNiU0kZRvqECZJ4GWdM3sH158S2lFHVdapaqqo7gEdwfU7gWjl7B07tAKz26R0SpJfLIyJ5QEvckiAVyUqkz8Oq2k9V+7Vu3Tqdn5QVcq3Cz7VoRohmBpCylm+CfjjY2fLd5g2WYRjlqdRAqeqTuP6bmGF6yqeljIgEa6ShQCzC72XgLB+Z1wnoDMxX1TVAkYgM8P1L5+OmW4rliUXonQ68oS7i41XgeBHZTUR2A473aTlLrlX4uTa+KipDkmsDtw2jplGpgRKRQcBy3Hx8DwIfhwwzfxqYC3QVkVUichFwhw8Zfw834eyvAVR1GW5hxPeBfwGXqWqshrsUeBRYAXyCC5AAmAC08gEV1wCjvKyNuBbfAr/9PtcXV8y1Cj/XxldFZUhyreWby9h4u9pJmD6oPwHHq+pHACLSBdei6pssk6qenSB5QpLzbwNuS5C+EOiRIL0YOKMCWY8BjyXTL5eIVfiVhW3XhACJGFFFM0bRVxSVIYm1fLcnaXlVteUbVXRgrkQdRh2EkivlUFsJMw7qPVU9uLK0XCdT46CiIv5BLFfh1+BosFwYX7Vs4kRmXnZZUkPSoFkzjn3wwZSCUKJcziSqcXFZGW+XwQo/V8cdGuWpaBxUGAP1GC4KbpJPOgfIU9ULMq5lNVLTDVSMTFf4uURUFX6UhiSqCjTX5EZR4efi/2YkJuX1oAJcCiwDrsTN6PA+MDKz6hlhiYWv97/hBrqfd16dMU4QXV9RlH1mUUwlFVVQR5RRh1FESUZ1P1j0Zc0hTBTfVlW9S1V/rqpDVfXuVGeVMIxMEGXQQVRzEsYGbv9q3TqOffBBfnLbbRz74IP86quvOHT06LTcRFFVzLlW4Ud1P1j0Zc2hwiAJEXlWVc8UkSUkGOha2/qgjJpPlEEHUcwAEiSTA7ejqphrQoWfShlFdT9kI/rSgi/CkSyK7yr/eWI2FDGMyug8dCgzRib3Llc13D6ThiQqoqqYc63Cj+p+iPJFKFejDqvLoFbo4vODZAF+par/C27AryLXzDDiyMb4qlwgqnFxUcmNaqB5VPdDlOMOo+iLg+iWt6nuZXPCBEkclyBtSKYVMYwwRNVXlEtEVTHnYoUfxf0QVTnkWhBKlHLDUmGYuYhcimsp7Y+bxSFGc+AdVT0nUs2yTK6EmRuOuhxuD9GNi4tKbtRh25m+H6Ioh1wbbxdlGH886awH9RRuWqHb8dMIeYpyfeogI/fJhb6iKIkqqCMquVHNLBIj0/dDFOWQa0EoNWEVhQoNlKp+B3wnIn8GNqpqEYCINBeRQ1V1XiQaGYYRmqgMdS5U+Nkgk+WQa0EoNWEuyTBz8T0E9Ansb06QZhiGUSl1ueWba1GH2ZhLsjLCBEmIBjqq/FpOYQybYRiG4cm1IJSasIpCGAP1qYhcKSIN/HYVbhl4wzAMIwVyKeqwJgzrCDNZ7J7AvcDRuBklXgeuVtWvItOqGrAoPsMwskUuRB1GKTeetGczryuYgTIMI9eJavhF1MM6qrLcxuMknovvwoxpVwMwA2UYhlE9pDMOKsYrge/5wFBgdaYUMwzDMIxEVGqgVPX54L6IPA3MjEwjwzAMwyBcFF88nYF9Mq2IYRiGYQSptAUlIkW4Pijxn2uBGyPWyzAMw6jjhHHx2SpahmEYRtZJtqJu0qmMVPXdzKtjGIZhGI5kLag/+c98oB+wGOfmOxiYB/wkWtUMwzCMukyy2cyPAhCRZ4ARqrrE7/cArsuOeoZh1AbOv/bHFG9NvFAfQH6jJkz80ztZ1MjIBcJE8R0YM04AqroUKKgsk4g8JiJficjSQNruIjJDRJb7z90Cx0aLyAoR+UhEBgfS+4rIEn/sXvHzaohIIxGZ4tPniUjHQJ5h/hrLRWRYiN9oGEaEJDNOYY4bdZMwA3U/EJFHgb/hovjOBT4Ike8J4H5gYiBtFPC6qo4XkVF+/0YR6QacBXQH2gEzRaSLqpbilvYYAfwH+CdwAm4hxYuAb1T1ABE5C/gj8AsR2R24BeeWVGCRiLysqt+E0Nkw6jTW0jFqEmEM1AXApcBVfv9NnNFIiqq+GWzVeE4BBvnvTwKzcSHrpwDPqOpW4DMRWQH0F5GVQAtVnQsgIhOBU3EG6hRgrJc1Fbjft64GAzNiq/6KyAycUXs6xG81jDpNrrV0zKDWbsKEmReLyAO42SMU+EhVt6d5vb1UdY2Xu8bPlA7QHtdCirHKp2333+PTY3m+8LJKROQ7oFUwPUEewzBqEVEZ1KgMn8lNjTADdQfhWjsrcVF8e4vIMFV9M4N6JJqvXZOkp5un/EVFRuDch+yzj02OYRiGIyrDZ3JTI4yL70/A8ar6EYCIdMG5y/qmcb11ItLWt57aArE1pVYBewfO64CbkHaV/x6fHsyzSkTygJbARp8+KC7P7ETKqOrDwMPgZjNP4/dkjep+kzEMw8g2YQxUg5hxAlDVj0WkQZrXexkYBoz3ny8F0p8SkbtwQRKdgfmqWioiRSIyADf26nzgvjhZc4HTgTdUVUXkVeAPgQjB44HRaepbY6juN5lUMYNqGEZVCWOgFonIBGCS3z8HWFRZJj/r+SBgDxFZhYusGw88KyIXAZ8DZwCo6jIReRZ4HygBLvMRfOACNJ4AGuOCI6b79AnAJB9QsREXBYiqbhSRccACf97vYwETRvbINYOaa+TaC0B+oyaV6msY8YQxUCOBy4Arcf07bwIPVpZJVc+u4NAxFZx/G3BbgvSFQI8E6cV4A5fg2GPAY5XpaOReRZdrRFW+ufYCYPeQkQ5JDZSI1AMWqWoP4K7sqJTb5FqFn2sVXVSYIXFYS8eoSSQ1UKq6Q0QWi8g+qvp5tpTKZXKtQso1zJBES016eQqDGdTaTRgXX1tgmYjMBzbHElX15Mi0MowKMENiBInKoEZl+ExuaoQxUL+LVAPDMIwaRlSGz+SmRrL1oPJxARIHAEuACapaki3FjPJU95uMYRhGtknWgnoSN9XQW8AQoBs75+Mzskx1v8mkihlUwzCqSjID1U1VewL4cVDzs6OSURvINYOaa9gLgFEXSGagyiaE9ZOxZkEdI9tYRRctUZWvvQAYdYFkBqqXiHzvvwvQ2O8LoKraInLtcpBcq/CtonOYITGMmkeyJd/rZ1OR2oJVSNFihsQw6g5hwswNo8ZghqR2sn37dlatWkVxcXF1q2JESH5+Ph06dKBBg3DzjZuBMgyj2lm1ahXNmzenY8eOWH937URV2bBhA6tWraJTp06h8tSLWCfDMIxKKS4uplWrVmacajEiQqtWrVJqJVdqoETk8sDaSoZhGJFgxqn2k+p/HKYF1QZYICLPisgJYneRYRjVzLaiIpZNnMj8O+5g2cSJbCsqqrLMtWvXctZZZ7H//vvTrVs3fvrTn/Lxxx9XWe7w4cOZOnVqleU88cQTrF69umz/4osv5v3336+y3K1bt3LsscdSUFDAlClTUs4/e/ZsTjzxxCrrkYhK+6BUdYyI3IxbmfYC4H6/uOAEVf0kEq0MwzASoKrMHz+euePGIfXrU1JcTF5+PjNGjuSwm2+m/6hRabXEVJWhQ4cybNgwnnnmGQAKCwtZt24dXbp0yfTPSIsnnniCHj160K5dOwAeffTRjMj973//y/bt2yksLMyIvEwSqg9KVRVY67cSYDdgqojcEaFuhmEY5Zg/fjxzb72Vki1b2L5pE1pSwvZNmyjZsoW5t97K/PHj05I7a9YsGjRowMiRI8vSCgoKOOKII1BVrr/+enr06EHPnj3LWhmzZ89m4MCBnHnmmXTp0oVRo0YxefJk+vfvT8+ePfnkk53v7zNnzuSII46gS5cuvPLKK4AzOJdffnnZOSeeeCKzZ8+mtLSU4cOHl13v7rvvZurUqSxcuJBzzjmHgoICtmzZwqBBg1i4cCEATz/9ND179qRHjx7ceOONZTKbNWvGTTfdRK9evRgwYADr1q0r97u/+uorzj33XAoLCykoKOCTTz6hY8eOfP311wAsXLiQQYMGAbB582YuvPBCDjnkEHr37s1LL720SznOmTOHgoICCgoK6N27N0VVbNmG6YO6UkQWAXcA/wZ6quqlQF/gtCpd3TAMIyTbioqYO24cJT8kHgdX8sMPzL31VrZt2pSy7KVLl9K3b9+Ex1544QUKCwtZvHgxM2fO5Prrr2fNmjUALF68mD//+c8sWbKESZMm8fHHHzN//nwuvvhi7rvvvjIZK1euZM6cOfzjH/9g5MiRSQMFCgsL+fLLL1m6dClLlizhggsu4PTTT6dfv35MnjyZwsJCGjduXHb+6tWrufHGG3njjTcoLCxkwYIFTJs2DXBGZcCAASxevJgjjzySRx55pNy19txzTx599FGOOOIICgsL2X///SvU67bbbuPoo49mwYIFzJo1i+uvv57NmzeXO+fOO+/kgQceoLCwkLfeequcnukQpgW1B/BzVR2sqs+p6nZwixkC0TgeDcMw4lj+4otI/eTzB0i9eix/8cWMXvftt9/m7LPPpn79+uy1114MHDiQBQsWAHDIIYfQtm1bGjVqxP7778/xxx8PQM+ePVm5cmWZjDPPPJN69erRuXNn9ttvPz788MMKr7fffvvx6aefcsUVV/Cvf/2LFi2ST9qzYMECBg0aROvWrcnLy+Occ87hzTffBKBhw4Zl/UN9+/Ytp1OqvPbaa4wfP56CggIGDRpEcXExn39efh3bww8/nGuuuYZ7772Xb7/9lry8qo1kCmOgOqnq/4IJIjIJQFU/qNLVDcMwQrJ57VpKKglRLi0uZrNv3aRC9+7dWbRoUcJjrocjMY0aNSr7Xq9evbL9evXqUVKyc3Wi+H4xESEvL48dO3aUpcVaVbvtthuLFy9m0KBBPPDAA1x88cVJdU+mX4MGDcquXb9+/XI6VURQr2BLT1V5/vnnKSwspLCwkM8//5yDDjqoXN5Ro0bx6KOPsmXLFgYMGJDUEIchjIHqHtwRkfo4955hGEbWaNqmDXn5+UnPqZ+fT9O2bVOWffTRR7N169ZyLrAFCxYwZ84cjjzySKZMmUJpaSnr16/nzTffpH///inJf+6559ixYweffPIJn376KV27dqVjx44UFhayY8cOvvjiC+bPdwtGfP311+zYsYPTTjuNcePG8e677wLQvHnzhH06hx56KHPmzOHrr7+mtLSUp59+moEDB6ZcBjE6duxYZqyff/75svTBgwdz3333lRnE//73v7vk/eSTT+jZsyc33ngj/fr1i85AichoESkCDhaR7/1WBHwF7No7ZhiGESGdhw5FS0uTnqM7dtB56NCUZYsIL774IjNmzGD//fene/fujB07lnbt2jF06FAOPvhgevXqxdFHH80dd9xBmzZtUpLftWtXBg4cyJAhQ/jLX/5Cfn4+hx9+OJ06daJnz55cd9119OnTB4Avv/ySQYMGUVBQwPDhw7n99tsBF64+cuTIsiCJGG3btuX222/nqKOOolevXvTp04dTTjkl5TKIccstt3DVVVdxxBFHUD/gUr355pvZvn07Bx98MD169ODmm2/eJe8999xDjx496NWrF40bN2bIkCFp6wEgyZqHACJyu6qOrtJVcoB+/fppLCLGMIzs8sEHH+ziLkrEvNtvd1F8CQIl8po04bAxYzh0dK2vrnKaRP+1iCxS1X7x54Zx8c0XkZYBQT8SkVOrrKVhGEaK9B81isPGjCGvcWMaNGtGvbw8GjRrRl7jxhw2Zgz9R42qbhWNDBImxOIWVS0Li1HVb0XkFmBaZFoZhmEkQEQ4dPRoel9+OcunTWPzmjU0bduWzkOH0rBZs+pWz8gwYQxUolZWlWIHRWQlUASUAiWq2k9EdgemAB2BlcCZqvqNP380cJE//0pVfdWn9wWeABoD/wSuUlUVkUbARFwwxwbgF6q6sio6G4ZRc2jYvDndzzuvutUwIiaMi2+hiNwlIvuLyH4icjeQOB4zNY5S1YKA33EU8LqqdgZe9/uISDfgLFw04QnAgz6SEOAhYATQ2W8n+PSLgG9U9QDgbuCPGdDXMAzDyCJhDNQVwDZc6+Y5oBi4LAJdTgGe9N+fBE4NpD+jqltV9TNgBdBfRNoCLVR1rp+KaWJcnpisqcAxNsmtYRhGbhFmstjN+NZMBlHgNRFR4K+q+jCwl6qu8ddcIyJ7+nPbA/8J5F3l07b77/HpsTxfeFklIvId0Ar4OsO/wzAMw4iIZOOg7vGffxeRl+O3Kl73cFXtAwwBLhORI5Ocm6jlo0nSk+UpL1hkhIgsFJGF69evr0xnwzBqMSLCtddeW7Z/5513Mnbs2LRkZWqJjbpOshbUJP95Z6Yvqqqr/edXIvIi0B9YJyJtfeupLW5AMLiW0d6B7B2A1T69Q4L0YJ5VIpIHtAQ2JtDjYeBhcOOgMvTzDMOIiPOv/THFWxNPFguQ36gJE//0TlqyGzVqxAsvvMDo0aPZY4890lUxo5SUlFR5PrtcpsIWlKou8sEIl6jqnPgt3QuKSFMRaR77jltnainwMjDMnzaMnbNVvAycJSKNRKQTLhhivncHFonIAN+/dH5cnpis04E3tLIRyYZh1HiSGacwx5ORl5fHiBEjuPvuu3c5Ft8iahYIab/jjjvo2bMnvXr1YlSCcViLFi1i4MCB9O3bl8GDB5fNhP7II49wyCGH0KtXL0477TR+8IOPhw8fzjXXXMNRRx1VbumMukhS06yqpSLSWkQaquq2DF1zL+BFH7OQBzylqv8SkQXAsyJyEfA5cIbXYZlfIPF93FpUl6lqbL6TS9kZZj7dbwATgEkisgLXcjorQ7obhlGLueyyyzj44IO54YYbQp0/ffp0pk2bxrx582jSpAkbN5Z31Gzfvp0rrriCl156idatWzNlyhRuuukmHnvsMX7+859zySWXADBmzBgmTJjAFVdcAcDHH3/MzJkzy001VBcJ03ZcCfzb9zuVLf6hqnelc0FV/RTolSB9A3BMBXluA25LkL4Q6JEgvRhv4AzDMMLSokULzj//fO69995QaxnNnDmTCy64gCZNmgCw++67lzv+0UcfsXTpUo477jgASktLaesns126dCljxozh22+/ZdOmTQwePLgs3xlnnFHnjROEM1Cr/VYPaO7TzF1mGEat5Oqrr6ZPnz5ccMEFZWnBJShUlW3btpV9TzaCRVXp3r07c+fO3eXY8OHDmTZtGr169eKJJ55g9uzZZceaNm2aoV+T24QZB/W+qv4uuAG2DpRhGLWS3XffnTPPPJMJEyaUpQWXoHjppZfYvn07AMcffzyPPfZYWf9RvIuva9eurF+/vsxAbd++nWXLlgFQVFRE27Zt2b59O5MnT478d+UiYQxUoqmBbbpgwzBqLddeey1ff71z2OQll1zCnDlz6N+/P/PmzStr4ZxwwgmcfPLJ9OvXj4KCAu68s3zQc8OGDZk6dSo33ngjvXr1oqCggHfecVGG48aN49BDD+W4447jwAMPzN6PyyEqXG5DRIYAPwXOxM0iEaMF0E1VU1uxq4Zjy20YRvURdrmNMy8vqPScZ+8vrLpCRmSkstxGsj6o1cBC4GTKz71XBPw6A3oahmGkRH6jJpWOgzJqDxUaKFVdDCz2A2k3x0K7/dioRlnSzzAMo4x0B+EauUmYPqjXcOOMYjQGZkajjmEYhmE4whiofFXdFNvx360dbRiGYURKGAO1WUT6xHb8IoFbolPJMAyjclSVj95fg81iVnsJM1D3auA5EYlNxNoW+EVkGhmGYVSCqvLw/bOZ9twiTj2jLyMuH5R0wKyRm1TaglLVBcCBuHnvfgUcpKqZWFHXMAwjZWLGafrfFwMw/e+Lefj+2VVqSW3YsIGCggIKCgpo06YN7du3L9uPzRoR45577ikbmJuMQYMGYUNXqkalLSgRaQJcA+yrqpeISGcR6aqqr0SvnmEYxk6CxmlrcQkAW4tLyoxVui2pVq1aUVhYCMDYsWNp1qwZ1113XcJz77nnHs4999yy+feM6AjTB/U4bsn3w/z+KuDWyDQyDMNIQCLjFCNmpKrakgry+uuv07t3b3r27MmFF17I1q1buffee1m9ejVHHXUURx11FACXXnop/fr1o3v37txyyy0ZubbhCGOg9lfVO3BLrKOqW0i8Yq1hGEYkJDNOMTJppIqLixk+fDhTpkxhyZIllJSU8NBDD3HllVfSrl07Zs2axaxZswC47bbbWLhwIe+99x5z5szhvffeq9K1jZ2EMVDbRKQxfgZzEdkf2BqpVoZhGJ4wxilGpoxUaWkpnTp1okuXLgAMGzaMN998M+G5zz77LH369KF3794sW7aM999/P+3rGuUJY6BuAf4F7C0ik4HXgXCreRmGYVSRjz9Yy7TnFlVqnGJsLS5h2nOL+PiDtWlfM+xyF5999hl33nknr7/+Ou+99x4/+9nPKC4uTvu6RnnCRPHNAH4ODAeeBvqp6uxo1TIMw3B0OagNp57Rl0b5YUbFQKP8PE49oy9dDmqT9jWLi4tZuXIlK1asAGDSpEkMHDgQgObNm1NUVATA999/T9OmTWnZsiXr1q1j+vTpFco0UqfCfzw4ONezxn/uIyL7qOq70allGIbhEBFGXD4IoFI3X6P8PIac1KvK46Ly8/N5/PHHOeOMMygpKeGQQw5h5MiRAIwYMYIhQ4bQtm1bZs2aRe/evenevTv77bcfhx9+eNrXNHYl2XIbs5LkU1U9OhqVqgdbbsMwqo8wy21U1heVKeNkREtGlttQ1aMi0M0wDCMtkrWkzDjVTirsgxKRGwLfz4g79ocolTIMw0hEzEgNOalXWZ+UGafaS7IgibMC3+OXeD8hAl0MwzAqJWikADNOtZhkYTFSwfdE+4ZhGFVCVUMbmZiRGnTMgXQ5qI0Zpxwh1bFpyVpQWsH3RPuGYRhpk5+fz4YNG1KqwESErt3amnHKEVSVDRs2kJ+fHzpPshZULxH5Htdaauy/4/fDX8EwDKMSOnTowKpVq1i/fn11q2JESH5+Ph06dAh9frIovvoZ0agaEZETgD8D9YFHVXV8NatkGEYCGjRoQKdOnapbDaOGEWaqo5xEROoDDwBDgG7A2SLSrXq1MgzDMMJSaw0U0B9Yoaqfquo24BnglGrWyTAMwwhJbTZQ7YEvAvurfJphGIaRA4SbfTE3SRTaUy5ESERGACP87iYR+SgCPfYAvja5JtfkmlyTWyH7JkqszQZqFbB3YL8DsDp4gqo+DDwcpRIisjDRHFMm1+SaXJNrcpNTm118C4DOItJJRBriZsZ4uZp1MgzDMEJSa1tQqloiIpcDr+LCzB9T1WXVrJZhGIYRklproABU9Z/AP6tZjahciCbX5Jpck1tb5CakwvWgDMMwDKM6qc19UIZhGEYOYwbKMAzDqJGYgaol+EjFKOTuFoXcKJGIpreOSm5U5Fo5+OnJcgJ73nYS5XNhBiqLiMhRInJwBHKPAy4UkZYZlns08KCIZHQGDhHpJSLdRKRLhuV28GWQ0YpORPb2FUckFWimK2YRaSciLYAGGZbbSUT2ADJ9n/UTkXaqWioiGauT7Hkrk5tTz1sQM1BZQkSOBx4FmgXSqvzm4R+WJ3DzDn5XVXkBuYOBx3FzGu7t06p8v4jIicAk4EbgWhFpnyG5J3u5DwHX+Znsq4yInAo8i5vL8Wavfybkniwi9wD4ijkjD7nX7yngBeDXIpKRKcJF5GfA08BfgKtFZI8M3b8dgb8DL4hIB1XdkaH7wZ43cu952wVVtS3iDRgIfAgc7feb4kL8G1ZBpngZjwLn+bTdgXbA/lXU92TgXeBA4DygENg9A+WwL/Ae0BvYC/egtweaVlHuPsBioAfQFfg1MAc4pYpy9wCWAAOAnsAw4CXg7CrK7Y+bJ/Ib4KlAev0qyj0GeB/oBRwJTAB+loH/7Xjgv8AhXvY0oF1V5QbkP+DvhQXAfhmQZ8+b5t7zlmir1eOgahD9cZXRXP9G+wec+2W5iMxU1ddTFajuTikRkc+AT0WkKW7M13Kgg4i8qKr3pqnvAOBGVf1QRNYARwB9gJkiUk9Vd6QptzmwXlX/610DPwHuBTaLyHRVfTpNuc2Ar1V1KZT58QcCw0TkW1Wdk6bc7cBHQKGqFovI58C3wHAR+UZV/5Wm3N2AK1X1RRH5r4g8rapnq29JqWppmnJ7AA+o6mIAv7zMWSIyHXfLpDumpCvwG1VdICKtgYOAO0TkXWBxOvev168ezouzA1fxDwCeEJE/A9tVNd2ZX/qRW89bf6J53poSzfPWlGiet10wF18WUNX/A2bgplp6Hve2cR+wBjhZRJpXwf2gwB9xbzF/BYYDNwC/SNf/rqq/UdUZvgL53m+/9MfSfVjwN3R9Efk3ruJ/GLgaeBE4Q0QSThgZQu77wHci8rCvOE4CVgBvAh2roO93wGacKyO2/yauYuoL6bmNVPVV4C2/2wfoIiJT/LFSEdkrTZUfAKYE9FoB5KvqDlVVEWmejlBVvU9Vp4tIPs6QPIZbCHQ7cJqItEy1HEREvF4luDLtoap3Ap/hXJSt/Hkp11Gq+ifcDDIvkaHnLaBHKTCezD5vY/zzJmT2eXsfqCcib5PZ5+0D4FsR+Wsmn7eKLmZbBBtwHHAZ8OtA2nXANYH9HriHqFkacq8KpD2Im2G4byDtUaBbGnKv9PsSONYIeAe4sArlcHUg7QBcX0ZsoHgrXD/PvunKBbrg+kimAlN92rFebmjXGdAZ2Cuw3xzXN3BPIK03zkil8r+Vk+vT6sc+gUXAI8DpuLfcxqnKDf5nfr8r8KL/fi6uIg3l5qpILtAm8L07zt3XPJ1yAOr5z5/iWjmH4lokf8O5VlO5HxKV72/i7rt0nrdEch8Fvqri87ZL+QbKoyrPWyJ9D8LVEVV53uKfiwNwxv/ZqjxvlV43U4JsK/dn/gRYD1wEvI3rSDwkcDx2o5wGvA7sVhW5QBNc6+xdYE/cW927wN5pyr3Pp+UFzrkIGF+Fcvi3f0h+7I/dDTzkv58C/IeQ/RoJ5P4Z6O+PNWRnxT8cZ1zyQso9Bfgc1xLZJ/Zf4VZkfgL35vkj4Bxgdgr/W0K5/jNYxt8DG4CeVZXrv3fGBXeMBJYCB1ZBbr0E8n8OvEHI/pJEcgP/2fM49+lQn3Yj0Kkqcv2xBoHvqT5vFenbAJgOLCS95y3Z/RAr53Set2TlcD/wYJrPW1DuvnHHmgV0Hk4Kz1uYzaY6igARuQb3Vvk77xYZA7QAnlbVuf6cq3EdosPU+3KrIPdxdX7mu4AtOKP1aw05OW4FcpsBUwL6DsC5NI5Q1e+rILcl8CSuMr4XZ1xbAueq6pIqyn1KVed6V8kluBbWear6XgiZLYHJuM71r3Cdyveq6v+8vMa4h7whrjP7YlUtTFPun1X1c+/mUn/eINzDfWKY/60SufVwrt8OuOCGT3D32YeZ0NeXx9W4Vlmo+7cSuQ1xxmNl4H4rK5uq6uvPu5oUnrdkcgPn3AlsJYXnLQV9D8N5GUI9b5XpKyKdcS9yzUjheUsgtw3Om/B53HkjSOF5C02mLJ1t5d4qjgP+BXTx+41wLoz7A+f8lpBvyiHk/iXuvPxM6+vTQ7tGKpH758A53YA9Iijf84GuKcrthDP4/YHbgLuIe4v310opCqoCuR3jzjkBOCACuX8DemVSLq6TfCyu3ygj5UughUacqzJD5XBzGs9bpXL9eak+b5WVb6zhkOrzFqYcDkzjeQsj99xUn7dQ1860wLq64cYuNMK9oTTAva1cBLT1x/OB+cAFEclNyV+dgtzhgTyVVhwh5S4ALqoh5bAPCYwOrj/kD/5hrOf3W0Ug9xCgZQRy++PelENV9inI7Qf8KMP61vflEFX5toiofENX9CmWb+sUnrew5dufkK7NNMohdPmmulkUXwYQN4hxOq7v5lFcM3gSLlz0ZyJyoKoW4wYkhg4hTlFuSURyy6KI1N+hGZD7Mi4CLAp9Uy2Hf3q5j4tI19gxVZ2H61Bfg+uXexXnjsy03BmEnJkhHbmV/WdpyH0d9zadSX3f8vpGUb4zcf2GmZb7Gs7tG4W++f5YmOctbPm+hgv4ybS+rxGyfNMiKstXFzacO2JvXMTRIJzf9wbcIMx9cG9Df8KFuf4ZWAccZHJrpNxrgdVA97hz78GFPlfqzjK5JtfkZnaLTHBd2XDN54dxI7RjvuNf46JeOvj9I4CLSaGPweRWi9wrgS/Z2be1G27EfG+Ta3JNbvpy090iFV6bN9w4gENwYwqmADfEHR+Fi8oKNZ7F5NYYuTfgQsqb+P1QHeAm1+Sa3MxvkV+gNm7Aibg5rubgQo9PBlYCowPndMS9iYSOSDK5NUbuX9n59himo9rkmlyTG8EW+QVq2wb8GDcmoLfffxi4FTdp5Oe4MTkH4AatLST8oECTa3JNrsmtFXIztWXtQrVl83/o8MB+a+Af/vt+uHnKHvR/ZuhxFybX5Jpck1tb5GZqy+rFasOG60RsEfgeG60fG4+zL25a/pYm1+SaXJNbF+VmarNxUCmiqqW6c+oRwc0ftlFV14jIubgJKhtoiouZmVyTa3JNbm2RmylsLr4MICJP4AauHY9rLoeaU87kmlyTa3Lrity0dDEDlT5+0swGwAf+8xhVXW5yTa7JNbkmt+qYgcoAIjIcWKAhZw83uSbX5JrcuiY3LV3MQFWdsEsDmFyTa3JNbl2Vmw5moAzDMIwaiUXxGYZhGDUSM1CGYRhGjcQMlGEYhlEjMQNlGIZh1EjMQBlGDUUcb4vIkEDamSLyr+rUyzCyhUXxGUYNRkR6AM8BvXFzpRUCJ6jqJ2nIqq+qpZnV0DCiwwyUYdRwROQOYDPQ1H/uC/TETeI5VlVfEpGOwCR/DsDlqvqOiAwCbsFNXVOgqt2yq71hpI8ZKMOo4YhIU+BdYBvwCrBMVf8mIj8C5uNaVwrsUNViEekMPK2q/byB+gfQQ1U/qw79DSNd8qpbAcMwkqOqm0VkCrAJOBM4SUSu84fzgX2A1cD9IlIAlAJdAiLmm3EychEzUIaRG+zwmwCnqepHwYMiMhZYB/TCBT8VBw5vzpKOhpFRLIrPMHKLV4Er/MzTiEhvn94SWKOqO4DzcAEVhpHTmIEyjNxiHG4phPdEZKnfB7cs9zAR+Q/OvWetJiPnsSAJwzAMo0ZiLSjDMAyjRmIGyjAMw6iRmIEyDMMwaiRmoAzDMIwaiRkowzAMo0ZiBsowDMOokZiBMgzDMGok/x+JoD9S0ip00AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate and Format each oil energy electricity production scatter plot in one figure\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Combustion fuels\"]/1000, color = \"darkred\", s = 80, \n",
    "            marker = \"o\", label = \"Combustion fuels\")\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Nuclear steam turbine\"]/1000, color = \"darkolivegreen\", s = 80, \n",
    "            marker = \"s\",label = \"Nuclear\")\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Total thermal generation\"]/1000, color = \"darkslateblue\", \n",
    "            s = 80, marker = \"D\", label = \"Total\")\n",
    "plt.xticks(canada_complete_data[\"Year\"], canada_complete_data[\"Year\"], rotation = 45)\n",
    "plt.xlim(2004,2020)\n",
    "plt.ylim(0, 300000)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Electricty Production (Megawatt Hours)\")\n",
    "plt.title(\"Annual Electricity Production by Oil Energy (2005 - 2019)\")\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"Plots\\Question 5 - Time vs. Types of Oil Sources for Canada.png\", bbox_inches = \"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparing Renewable Energy and Oil Energy Production"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate and Format scatter plot of electricity production by total renewable energy and total oil energy\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Total renewable energy generation\"]/1000, s= 80, \n",
    "            facecolor = \"green\", edgecolor = \"black\", label = \"Renewable\")\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Total thermal generation\"]/1000, s= 80, \n",
    "            facecolor = \"grey\", edgecolor = \"black\", label = \"Non-Renewable\")\n",
    "plt.xticks(canada_complete_data[\"Year\"], canada_complete_data[\"Year\"], rotation = 45)\n",
    "plt.xlim(2004,2020)\n",
    "plt.ylim(200000, 450000)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Electricty Production (Gigawatt Hours)\")\n",
    "plt.title(\"Electricity Production by Different Energy (2005 - 2019)\")\n",
    "plt.legend(loc = \"right\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"Plots\\Question 5 - Time vs. Oil and Renewable for Canada.png\", bbox_inches = \"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the regression line for renewable energy production\n",
    "renewable_regression = st.linregress(canada_complete_data[\"Year\"], \n",
    "                                     canada_complete_data[\"Total renewable energy generation\"]/1000)\n",
    "renewable_regression_line = renewable_regression[0] * canada_complete_data[\"Year\"] + renewable_regression[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the regression line for oil energy production\n",
    "oil_regression = st.linregress(canada_complete_data[\"Year\"], \n",
    "                                     canada_complete_data[\"Total thermal generation\"]/1000)\n",
    "oil_regression_line = oil_regression[0] * canada_complete_data[\"Year\"] + oil_regression[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Put two regression lines into the scatter plot generated above\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Total renewable energy generation\"]/1000, s= 80, \n",
    "            facecolor = \"green\", edgecolor = \"black\", label = \"Renewable\")\n",
    "plt.scatter(canada_complete_data[\"Year\"], canada_complete_data[\"Total thermal generation\"]/1000, s= 80, \n",
    "            facecolor = \"dimgrey\", edgecolor = \"black\", label = \"Non-Renewable\")\n",
    "plt.plot(canada_complete_data[\"Year\"], renewable_regression_line, color = \"darkred\")\n",
    "plt.plot(canada_complete_data[\"Year\"], oil_regression_line, color = \"mediumblue\")\n",
    "plt.annotate(\"y =  \" + str(round(renewable_regression[0],2)) + \"x+  \" + str(round(renewable_regression[1],2)), (2010,340000), \n",
    "             fontsize = 13, color = \"darkred\")\n",
    "plt.annotate(\"y =  \" + str(round(oil_regression[0],2)) + \"x+  \" + str(round(oil_regression[1],2)), (2010,250000), \n",
    "             fontsize = 13, color = \"mediumblue\")\n",
    "plt.xticks(canada_complete_data[\"Year\"], canada_complete_data[\"Year\"], rotation = 45)\n",
    "plt.xlim(2004,2020)\n",
    "plt.ylim(200000, 450000)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Electricty Production (Gigawatt Hours)\")\n",
    "plt.title(\"Electricity Production by Different Energy (2005 - 2019)\")\n",
    "plt.legend(loc = \"best\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"Plots\\Question 5 - Time vs. Oil and Renewable (with Regression) for Canada.png\", bbox_inches = \"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Relationship between Canadian Dollar (Index) and Energy Source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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b5JbU5Le4fsmU1LlWYNwtRwCEhYXpxYspmWdpsVgswYWIJJz3lS7xp4VtBdwpInsw8xw6iMj3qnrUidMVi/Hfb+ocf4DrZ/uXxgycHnDWE5ZfV0dMUNR8mLlKScmyWCwWSzrBbwZKVV9X1dKqWh4zAe5vVX1IXBJxYaIibHLWZwA9Hc+8ChiPnhWqehg4Lyapl2CiWk93qRPnoXefcw4FZgGdxEQ/KICZ2DjLX9dqsVgsFt8TiFh8g0SkPqbLbQ9O4i1V3Swm7tYWIBp4xgl5A/AUJrRHTsxs6LiwHKOB8SKyE9Ny6unIOuW4Za90jntPTeRli8VisaQT7ERdBzsGZbFYMgoicklVwzwfGdykey8Pi8VisWRMrIGyWCwWS1BiDZTFYrFYghK3BsrJK3KfiAwWkR9F5DsReU1EaqWVghZLIAn/5Rdm9unDhcOHA62KxZLpSNJAOTHzFgMtgOWY/CNTMB52H4nIHDHJ7SyWDEnM1avMe+klNDaWcXXrsnbYMGJjYjxXtFgsPiFJLz4RuV1Vf0+yokhRoKyTpCzdY734LAlZ9/XX7Jw+nfv+/JMTmzcz96mniL5yhVu++YZiDRoEWj2LJUkyihdfstzMRSQEyK2q5/ynUmCwBsriStSlS4yuUoW7Z8ygeKNGAGhsLJvGjuWf11+nxoMP0uq998iWO3eANbVYbiSjGCiPThIi8oOI5BWRMMwk2u0i8qr/VbNYAsfar76iRIsW8cYJQEJCqNO3L302bSLy1CnG1KxJ+C+/BE5JiyWD47EFJSLrVLW+iDwINAIGAKtVNUONP9kWlCWOK+fOMapyZXrMn0/hmjWTPG7f/PnM7d+fAtWq0WHIEPKVK5eGWlosSZNpWlBAVhHJisnBNF1Vo0gkMrjFklFY9b//UeHWW90aJ4Cy7drxyPr1FG/ShO8bNWLlp58SExWVRlpaLBkfbwzUN5iYeWHAQhEpB2S4MSiLBeDSiROs/fJLWg4c6NXxWbJnp8Wbb/LAsmXsmT2b7xs35tCyZZ4rWiwWj7jt4nOcIu5T1SkuZQKEqmp0GuiXZtguPgvA/FdfJeriRW4ZNizZdVWVbZMmMf/ll6l81120/s9/yFGggB+0tFjckym6+JycTc8mKNOMZpwsFoDzBw+y6dtvafHmmymqLyLU6NWLR7dsAWBMrVps/eEHbEBmS7AhIt+KyDER2ZTEfhGRISKyU0Q2iEhDl31dRGS7s+/fftXTCyeJt4DLwGQgvomR0dJX2BaUZc5TT5EtTx7aDhrkE3mHli1jzpNPkqtYMW4eNowClSv7RK7F4glPLSgRaQNcAL5T1dqJ7L8NeA64DWgGDFbVZiISCuwAbsEkhl0J9FLVLX64DK/GoPoCzwALgdXOkiEm51oscZzZvZsdP/5I0wEDfCazZPPmPLx6NeU7d+aH5s1Z+v77RF+54jP5FktKUdWFmBx6SXEXxnipqi4D8jvJZpsCO1V1t6pexWRLv8tfeno0UKpaIZGlor8UslgCwZKBA2nw3HPkLFTIp3JDsmShycsv8/CaNRxZtYrvmzTh4tGjPj2HxTNbjm3h9Vmv0+SrJvSZ2ocxq8cQcSoiI3e/ZhGRVS7LE8msXwrY77J9wClLqtwveMyoKyKPJFauqt/5Xh2LJe05sXkze2bNol94uN/OkbdsWbpNn86Sd99lcvv29Jg3j7Bixfx2PgtcjbnKrPBZjF87noNnD9KrXi9+fOBHth/fzvyI+YxcOZLsWbLTrkI72lZoS/MyzcmRNUeg1fYV0araOBX1JZEydVPuF7xJ+d7EZT0H0BFYA1gDZckQLH7rLZq89hrZ8+b1+7lavvMOqmqNlB85cv4IE9dPZPLGyVQqWIm+jfpyc+WbyRJiXnflC5Snc9XOxuvy+DbmR8zn6+Vf88JvL9C4VGPaVTQGq2z+sgG+koByACjjsl0aOARkS6LcLyQ75buI5APGq+qd/lEpMFgniczJ4ZUrmd6tG/3Cw8maM2eanXfxwIFsnzLFGikfoaos37+c79d9z5J9S7ij+h08WP9Bqhau6rWMs5FnWbRnEfMj5rMwYiF5c+SNb101Kd2E7Fmy++8CfIw3buYiUh74LQknidsxHtxxThJDVLWpiGTBOEl0BA5inCQeUNXNPr4Eo0cKDFRWYIOq1vCHQoHCGqjMydTOnancrRv1+/dP83NbI5V6Ll69yC9bfmH82vHEaiwP1X+IbrW6kSd7nlTJjdVYNh/dzPyI+SzYvYDwk+E0L9OcthXb0q5CO0rmLembC/ATXnjxTQTaAYWBo8A7QFYAVf3Gme86FOgCXAIejctc4Xj4fQGEAt+q6od+uw4v3Mx/5VofYyhQA5iiqn71f09rrIHKfOxfsIA/+/al79athGbLFhAdrJFKGbtO7uL7dd8zfet0mpVpxsMNHqZFmRaY96rvOXXpFIv2LmL+7vks3LOQwrkK07ZCW9pVbEejUo3IFhqY5ycpMspEXW8MVFuXzWhgr6oe8KtWAcAaqMyFqjKpdWvqPvkktR5+OKC6WCPlHdGx0fy962/Grx3P9hPb6VG3B73q9krz1kxMbAwbj25k/u75LIhYwO5Tu2letrkxWBWCo3WVaQwUgIgU45qzxApVPeZXrQKANVCZi91//MGCV1+l94YNhISGBlodFg8cyI4ff6T7339bI5WAk5dOMmXjFCasm0DxPMV5uP7DdKnaJWjGhE5cPMGivYtYELGAf/b8Q+FchWlToQ1tK7SlcanGAdEz0xgoEekOfALMx7gYtgZeVdWpftcuDbEGKvOgsbGMb9SIFm+/TZVu3QKtTjzWSF3j9OXT/LXrL2aHz2bFgRV0qdKFhxo8RO1iN4znBxVxrauFEQtZELGAnSd30qxMM9pWaEvbCm0pna90muiRmQzUeuCWuFaTiBQB5qpqvTTQL82wBirzsP3HH1kxaBAPrVjhtzGLlJKZjdTRC0eZEz6HWeGz2HBkA63KtaJTlU50qNiBvDn8PwXAH8SNXS2IWMDCiIUUyFkg3lj50zMwMxmojapax2U7BFjvWpYRsAYqcxAbHc3Y2rXpMGQI5Tt1CrQ6iZKZjNTeM3uZHT6bWeGz2H1qN+0rtqdTlU60Kd+GnFnTzu0/LYjVWDYd2cSCPQtYELGA8BPhNC3dNN5glclfxrMQL8lMBuoToC4w0SnqgXEz913QsiDAGqjMwcYxY9g8bhw95s0LutaTKxnVSKkqO07sYFb4LGaFz+LExRPcXPlmOlfpTPOyzYPOG86fnL582rSudi9g4Z6FPN7kcR5v8rhPZGcaAwUgIvcCrTBjUAtVdZq/FUtrrIHK+ERfucK31apx+4QJlGrVKtDqeCSjGKlYjWXDkQ3M2mGMUnRsNJ2rdKZzlc40KNmA0JDAO6kEmliN5Ur0FZ+1GjOVgcoMWAOV8VkzdCgRM2dy7++/B1oVr0mvRio6NpqVB1YyK3wWc8LnkDtbbjpV7UTnKp2pVbRWULdeMwIZ3kCJyHkSDwIomLyF6XPUMgmsgcrYXL14kdFVqnDP779TrEGDQKuTLOKN1Lx5hBUtGmh13HLm8hmGrxjO1E1TKZW3FJ2rdqZT5U5UKlQp0KplKjKKgUoyWKyqxscKEZG1qpq+ftUWiwtrhw6ldOvW6c44AbQaOBCAKe3bB62RioyKZNzacYxaOYpOVTrx84M/+3TQ35I58SaaOfgxnLrF4m8iz5xh1aef0vOffwKtSooJViMVExvDz5t/5oslX1CveD0m9ZxkW0sWn+FNRt1UISKhIrJWRH5ztguKyBwRCXf+FnA59nUnz/12EensUt5IRDY6+4Y4gQwRkewiMtkpX+5E542r09s5R7iI9Pb3dVqCl1WffUalO+6gUPXqgVYlVbQaOJCq99/PlPbtuXgssMFcVJW/dv3F7eNu56fNPzH0jqEMu2uYNU4Wn5JkC0pE7nHZzJ9gG1X92ctzvABsBeLGrP4N/KWqH4nIv53tASJSE+gJ1AJKAnNFpKqqxgBfA08Ay4A/MBF2ZwL9gNOqWllEegIfAz1EpCAmOm9jTOtvtYjMUNXTXupsySBcPHaMdcOG8fCaNYFWxSe0GjgQVBnTqinhb3ekZrWm3Fr11jTNXbT64GoGLRzE2cizvNbmNdpXbG+dHix+wV0X3x0u6wsSbCvg0UCJSGngduBD4F9O8V2YMO8A4zAhlAY45ZNU9QoQISI7gaYisgfIq6pLHZnfAXdjDNRdwEBH1lRgqNO66gzMUdVTTp05GKMWN5fLkklY8dFH1HjgAfKVKxdoVVJNVEwUv2//nREVVlKhVlaqvDuLfZ8X4t6V91Iibwluq3obXap2oXyB8n45/86TO/n0n0/ZdHQTL7Z6kW41u1kXcYtfceck8agP5H8BvAa4JmcppqqHnXMcFpG4zvRSmBZSHHG57qOc9YTlcXX2O7KiReQsUMi1PJE68YjIE5iWGdkClG7B4j/O7d/P5nHjeHSzX3KppRmXoy4zZeMURq8aTem8pRnQdgBterfh565d6XC0Ku8+9R9WHFjBn9v/pMfEHhTNXZRbq97KrVVvpULBCqk+/5HzRxi8ZDBzd87liaZP8MXtX2Sk1OiWIMZbJ4lkIyJdgWOqulpE2nlTJZEydVOe0jrXClRHACPAuJl7oaMlHbHs/fep+8QThBUvHmhVUsSZy2cYv24849eOp2HJhgzuOpgGJa95ITZ+6SXmvfQSdfr1o2XZlrQs25J3Or7DygMr+XPHn/Sa3ItCuQrRpWoXbqt6W7LHh85FnmP4iuFM3DCRHnV6MLffXPLlyOfry7RYksRvBgoTeeJOJ/tiDiCviHwPHBWREk7rqQQQN9p7gMRz3R9w1hOWu9Y54KQizgeccsrbJagz33eXZgl2Tu/cSfi0afTdvj3QqiSbQ+cOMWb1GH7a/BO3VL6FH3r8QOVClW84rmzHjmhsLPvnzaNshw4AhIaE0rxsc5qXbc5bHd5izaE1/LH9Dx7+8WHyZs/LbdVu49aqt1KlcJUkz38l+grfr/ueb5Z/Q8dKHfntkd+CIseRJfPhTSy+7M64kNsyDzLaAa+oalcntt9JFyeJgqr6mojUAn4AmmKcJP4CqqhqjIisBJ4DlmOcJL5U1T9E5Bmgjqr2d5wk7lHV7o6TxGqgoaPCGqBR3JhUYtiJuhmL3x98kII1atDizTcDrYrX7Dy5kxErRjB311zuq3UfjzZ+lBJ5Srits374cHb/8Qfdpk93e1ysxrLm0Br+3PEnM3fMJHfW3NxazXQDVi1cFREhJjaG6Vun8/miz6lZtCYvt36ZqoWr+vISLWlERpmo642BWqOqDT2VeZDRjmsGqhAwBSgL7APud3Fm+D+gLyZz74uqOtMpbwyMBXJinCOeU1UVkRzAeKABpuXUU1V3O3X6Am84KnyoqmPc6WgNVMbh+MaN/HjLLTwWHk62PHk8Vwgwaw+t5ZsV37D20FoeafAID9V/iPw583tVN+rSJUaUK8eDy5aRv5J3XXixGsu6w+v4c7sxVjmy5qBjpY4sjFhIWLYwBrQZQOPSjVNxRZZAk+ENlIgUxzgWfA88wLVxnbzAN6qavieVJMAaqIzD7w89RNEGDWjy8suBViVJVJUFEQsYvmI4h84d4rEmj3Ff7ftSFCx0wYABxF69SvvPP0+RHhuObGDOzjnULV6XWyrfYl3GMwDBYqCcRkRXTKLbksBlYBPwu6p69F5yZ6B6A30wc4lWcs1AnQPGJWMeVLrAGqiMQczVqwwrVoy+W7cGpXNEdGw0f2z/g+ErhqOq9G/Wn9uq3UaWkJQPB5/bt4/vGjTgiT170kWL0eJ/gsFAichAzPSk+Zghl2MYf4SqQHtn/WVV3ZCUDHdu5uOAcSLymqoOSnDi1PuuWix+YP+CBRSsXj2ojNOZy2dYcWAFy/cvZ+7OuZTMW5JXWr9CuwrtfNJayVu2LGU7dGDT2LE0fO651CtssfiGlao6MIl9/3OmGLmdYZ7SMajVqtooOZoGO7YFlTGY++yz5Cldmmb//nfAdHA1SMv3L2f/2f00KNmA5mWac1P5m6hdrLbPz3lg0SJm9e1L323bkBC/RzCzBDnB0IKKQ0RyqGpkgrLCqnrCU113oY6qY8IO5UsQ5igvpmlmsQQVqsquGTO4988/0/S87gzS+7e8T+1itckamtWvOpRq1YpsefKwe+ZMKt1+u1/PZbEkk5Ui8riqLoP4BLj/xXT1ucVdx3c1zOBWfq4Pc3Qe8E1eYku6JSYqimNr11KiadNAqxLPsbVrCc2enUI1avj1PMFgkBIiIjR84QXWDB5sDZQl2HgA+FZE5mMcJQoBHbyp6E0XX4u4OHgZGdvF5z1Rly4x4/772TtnDk8fPUqOAgU8V0oDFr/zDlEXL9Lu0099KtedQWpWpllADFJiRF+5wsjy5bn/r78oXLNmoNWxBJBg6uIDEJG7MVOCzgNtVHWnV/W8MFA5MFHDa+HStaeqfVOqbDBiDZR3XD51iml33EH+ihW5cu4cle++mzqP+iJsY+oZV78+Hb/8ktKtW/tEnqry2aLPGL92fFAapMRYPHAgl44e5Zavvw60KpYA4o2BEpEuwGAgFBilqh8l2F8A+BaoBEQCfVV1k7NvD8bYxADRqprkxDkRGe3IeBTTrfcFMFRVv/J0Hd6Mpo4HimMihC/AhA0670U9SwbjwqFDTG7blhLNmnHruHHUePBBtk+eHGi1ADi7Zw8XDh6kZMuWPpP5zYpvmLtzLvMfn8/Y+8bSv1l/GpRsELTGCaB+//5smzSJyNM2s4wlaUQkFPgKuBWoCfRyUh658gawTlXrAo9gjJkr7VW1vjvj5LDJOTZCVWcBzbkW5cct3hioyqr6FnDRcT2/HajjjXBLxuF0eDgTb7qJGg88QLvPPkNCQqh4++0cWrqUSyc8OuP4nV2//krFrl0JCfVN+ocJ6yYwZcMUxt0/jgI5g6ML0xvCihenUteubBg1KtCqWIKbpsBOVd2tqleBSZj0Ra7UxIScQ1W3AeVFpFhyT6SqnwNlReRmp+gq8KI3db0xUFHO3zMiUhsTkLV8MnW0pGOOrl3LpLZtafb66zR7/fX4uTvZwsKo0KULO6dNC7CGsHP6dCrfeadPZM3YOoOvln3F2PvHUix3sn+PAafhCy+wduhQYqOjA62KJXBkEZFVLssTCfZ7k5JoPXAPgIg0BcpxLXC3ArNFZHUisq9DRB7H5Osb7hSVBn7x5iK8MVAjnL7It4AZwBZM5lpLJmDf/PlM7dyZjkOHUvfxG503q/XowbYAd/NFnjnDkRUrKNepU6plzds1jw/mfcCYe8dQLn/6THJYvHFj8pQuzU4PAWQtGZpoVW3ssoxIsN+blEQfAQVEZB0mWPdaTJxUgFbO/NhbgWdEpI0bXZ7BZLc4B6Cq4UBRN8fH49FAqeooVT2tqgtUtaKqFlXV4Z7qWdI/4b/8wq/du3PHpElUveeeRI+pcOutHF21iotHj6axdteI+OMPSrdtS7aw1DktLd+/nNf+fI3hdw+nWpFqPtIuMMS5nFssSZBUeqN4VPWcqj6qqvUxY1BFgAhn3yHn7zFgGqbLMCmuON2IADipkbzKv+fRQInILhGZICL9ExlEs2RQNo4ezdynnuLemTPjcw3Fsef0HgbOHUjr4a3pPb0fFxqVYcLgASzfv5xTl5LMaOI3dk6fTuW7EnafJ4+NRzby7Ixn+aLrF9clBUyvVOnWjbMRERxduzbQqliCk5VAFRGpICLZgJ6YHrJ4RCS/sw/gMWChqp4TkTARyeMcEwZ0wjhCJMUCEXkDyCkitwA/Ar96o6RX+aCAZphotK2A6sB6Ve3mzQnSC9bN3KCqrBg0iPVff819s2dTsGrV+PLVB1czatUoVh1cRc+6Pbmzxp0cu3CMzT9P4dTYX1j976aEnwgne5bsVClUhSqFq1C1UFWqFK5ClUJVvE4hkRyir1zh62LF6Lt9O2HFUjZetOvkLh6Y/ADv3fwenat29rGGgWP5Rx9xats2bh07NtCqWNIYL93Mb8O4fIcC36rqhyLSH0BVvxGRFsB3GFfyLUA/VT0tIhUxrSYwwR5+UNUP3ZwnBDNVqROma3EWxq3dYyvKGwOVBWgCtAVuwswC3qCqT3oSnp6wBgo0NpYFr71GxMyZ3Dd7NnlKlSI6Npo/d/zJ6FWjORt5lr6N+nJPrXvIlS1XfL3oK1f4pkQJ+mzeTFjx4hy9cJTwk+GEnwi/7m/OrDmpXKjyDcYrNWnE98yezZKBA3lgyZIU1T949iA9JvXgxVYvcl/t+1KsRzBy+eRJRlWuTN9t21JsvC3pk2CbqJtSvDFQl4CNwP+Auap6Mi0US2syu4GKjY5m1mOPcWr7du75/Xeiw7IyZeMUxq4eS6l8pejXuB8dKnYgNCRxN+4/evemeOPGSUbTVlUOnz98g+HaeXInYdnCqFakGo81foybyt+ULL3nPvMMecqUSVFw2BMXT9BjUg8eqv8QjzYKjsnGvmb2E0+Qu3RpWr79dqBVsaQhwWCgRGQjbsaanPlV7mV4YaDuwrScmmL815dg+iL/Spa2QU5mNlBRly/zW48exERF0fTbL/l+2xR+2vwTN5W/iX6N+lG3hMfniF2//86K//6XXosWJevcsRrL4XOHWX1oNf9b9D9qFq3JG+3eoHS+0h7rqiojypblvtmzkx1/71zkOR6Y/AA3V76ZF1u9mKy66YnjmzYx9ZZbeGLvXkKzZfNcwZIhCBIDFecG+4zzd7zz90Hgkqq+51GGF92AcSerjnEpfBEoqqrJT/0ZxGRWAxV55gy/3Hkn0YVys+LhCiw+tIx7a99L7wa9KZUv4bSIpIm5epWvS5Sg9/r15Cnt2bgkqktUJCNXjWTs6rH0btibJ5o8QY6sSQfOP7J6Nb/36kXf7duTlVfpctRlek/tTa2itXi7w9sZPoPslJtvpnafPtR86KFAq2JJI4LBQMUhIotVtZWnssTwxovvJxHZhQlzEYZxN0w/U+stSXLu0EFGtWjE6lyHGdH5PPXLNmL+4/N5o90byTJOAKHZslH57rvZ/uOPKdYnR9YcPNfiOWY8PIMdJ3bQeUxnZoXPIqmPqJ3Tp1PprruSZWCuxlzl6elPUzZfWd7q8FaGN04ADZ9/ntWDByd5Hy0WPxMmIvF99yLSEmNLPOJNF18TYI2qxqRKxSAnM7WgLl29xOQ/h7Hvsbc42aYCnd4fRJdqXVKVdhwgYtYslrzzDg8uW+YTPRfvXcx7f71HibwleKv9W1QqVOm6/ePq1aPjV19R+ibvxq1iYmN48bcXuRp7la/u/CrV15teiI2JYXTVqtz+/feUbNEi0OpY0oAga0E1wgSdjfOGOoMJPLvGY11vvqqcEEc1uT6a+XcpUTZYyQwG6tSlU3y7+ltm/TGGjiP2UuOVZ7nz3//1WSsiJiqKb0qW5KGVK8lXvrxPZEbFRDF+7Xi+Xv4199S6h2dbPEue7Hk4ExHBhGbNeOrwYa/i76kqb8x+g/1n9zP6ntFkz5LdJ/qlF1Z/8QWHli3jjkmTAq2KJQ0IJgMVh4jkxdics17X8aIF9Q7QDmOg/sCMQy1S1Qzlk5uRDZSq8uu2X/lw3ofcGlmdQv/9nVu+Gkb17t19fq7ZTz5J/sqVafrqqz6Ve/zicT5Z+AmL9i7itTavUWbOXo6tW8etY8Z4rKuqfLzwY1bsX8F33b8jd7bcPtUtPXDl7FlGVqhA7w0bUjxGaEk/BJOBcubS3ouJ4RrfbeGNk4Q3sfjuAzoCR1T1UaAekLk+P9Mxh84d4rGfH+Ob5d8wqNRTFPloJndOnOQX4wRQrXt3tk+Z4nO5RcKKMOjWQXx151eMWT2GX0b+h+xtvYv48M2Kb5i/ez6j7x2dKY0TQPZ8+ajx0EOsGzYs0KpYMh/TMZHSo4GLLotnVNXtAqxw/q4G8mJmAm/2VC+9Lbly5dKMRHRMtI5dPVYbD22sXy39SiMjL+mY2rV1248/+vW8MVFR+lXRonp6506/nePCieP6aVhObfG/Rvrm7Df11KVTSR77/drvtd2Idnrk/BG/6ZNeOLVjhw4tUkSvXroUaFUsfgaTHing71WjCptSWtebFtQqEckPjHSM1BpghffG05LW7Dixgx6TejBzx0wm95rM082fZvOIUeQqVoyq997r13OHZMlClXvv9UsrKo69f86iYoebmfnUX4SGhNJ5TGd+WPcDMbHX+/HM2DqDYcuGpdu0Gb6mQJUqlGjalK0TJgRaFUvmYomIpCyHYDItYXmgbqAtsj+WjNCCioyK1C8WfaGNhzbWCWsnaExsjKqqXjx2TIcWLqzHN21KEz32zZ+v4+rX95v86fffrxtGjYrf3npsq/ac2FPvGHeHrjywUlVV/975tzb5qoluO7bNb3qkRyJmz9YxtWtrbGxsoFWx+BGCqwW1BRPkYTuwAROZaIM3db1xkkgsNe9ZYK+qZpiMaL50khi+fDjlCpSjXYV2biea+pI1h9bwxqw3KJe/HO/e/C7F8xSP3zf7ySfJkjMnHb74Ik10iY2JYXiZMvSYPz8+2KyvSCo4rKpxBPl4wcfULVGXVQdWMfKekdQvUd+n50/vqCpja9em45df3hCl3pJxCDIniUQTq6nqXo91vTBQyzD54zdgxp9qO+uFgP6qOju5CgcjvjRQP236iV+2/MLGoxvpWKkjXat1pVX5VmQL9X2omQtXL/DZP5/x544/eavDW9xa9dbr3MaPrlnDT7fdRt9t28iRP7/Pz58Ufz3/PLmKFKHFW2/5VG7ErFksfffdJIPDXrx6kdGrRtO0dFOal23u03NnFNYPH87uP/6gm01omGEJBgMlIgXd7VdVj7l5vDFQk4D3VXWzs10TeBV4H/hZTTKrdI8/3MyPXzzOzO0z+W37b+w6uYtOVTrRtXpXmpVp5pNJovN2z+PtOW/TslxLXm/7+g3pLFSViTfdRJ2+fanTr1+qz5ccDi5ezJz+/emzcaNP5c55+mnylitHswEDfCo3MxF16RIjypXjwWXLyF+pkucKlnRHkBioCEyw2ESz96pqRY8yvDBQ6xIaobiyxPalV/w9D+rQuUP8vv13ftv2G4fPH+a2qrfRtXpXGpZqSIh446tyjZOXTvLBvA9Yd2gdH3T6gFblEg9pteX771k9eDAPLV+OhCTvHKlFY2MZUa4c986aReGavslzqaoML1OG++fOpVD16j6RmVlZMGAAsVev0v7zzwOtisUPBIOB8gXeGKjJwCkgbgp6D6Aw8DBmwm4Tv2qYRqTlRN2I0xH8vs0Yq/NXz3N7tdu5o/od1C5W221UB1Vl+tbp/Hf+f7m75t282OpFcmZNPGbv1fPn+bZ6de786SdKNg9MV9e8f/2LbHny0Ordd30i78iqVfz+4IP0277dJ/IyM2f37mV8gwY8sXcv2fLkCbQ6Fh8TDAZKRMqr6h43+wUopaoHkjzGCwOVE3gak3JDgEXAMCASyKWqF5KvevARqEgS249v57ftv/Hbtt8QhK7Vu9K1eleqFr7eueDg2YP835z/48TFE/yn83+oW9x9CowFAwZw6ejRgGZTPbx8OTP79OHRLVt8Ek5p0VtvEXPlCm0HDfKBdpbp991HmbZtk8zhZUm/BImB+hETDGI6ZorScUy4vMpAe0wAiHdUdU6SMjwZqFQolwNYiIk6kQWYqqrviMhA4HFHWYA3VPUPp87rmNTAMcDzqjrLKW8EjAVyYsItvaCq6oTQ+A5oBJwEesRZbBHpDbzpnOMDVR3nTt9AhzpSVTYe3chv237j9+2/kydbHrpW78pt1W5jQcQCvlr2Ff0a9+Oxxo+RNTSrW1mnduxgYsuW9N64kdwlSqTRFdyIqjKyQgW6zZhBkbqec0p5Ymzdutw8bJjXwWEt7jnwzz/M6tePvtu2ISEhREVFceDAASIjIwOtmsVLcuTIQenSpcma9fp3QjAYKEePmpj8T62AEsAlYCvmPT5VVd0+bEkaKBGZoqrdk8qKqB6yITrNtzBVvSAiWTEtrxeALsAFVf00kQuZiEmMWBKYC1RV1RgRWeHUXeZc2BBVnSkiT2PmZfUXkZ5AN1Xt4XiPrAIaO7qvBhqp6umk9A20gXIlVmNZc3ANv237jT92/EHlgpX5sNOHVChYwav6P91+O2Xbt6fJK6/4WVPPLHjtNUKzZeOmDz5IlZzkBoe1eEZVGd+oETd98AEVb7uNiIgI8uTJQ6FChTJFGpL0jqpy8uRJzp8/T4UK178bgsVApRZ3rmQvOH+7pkSwM1ksrvsvq7O4a67dBUxS1StAhIjsBJqKyB4gr6ouBRCR74C7gZlOnYFO/anAUMcwdgbmxLkxisgcjGGcmJJrSWtCJITGpRvTuHRj3un4TrJeFrt+/52zu3bRcNo0P2roPdV69OC3nj1p9f77qXrp7Zoxg0pdu1rj5ENEhIYvvMCawYOpeNttREZGUr58eWuc0gkiQqFChTh+/Ljng9MpSbp2qeph5+/exBZvhItIqIisA45hDMZyZ9ezIrJBRL4Vkbjkh6WA/S7VDzhlpZz1hOXX1XEmDZ/FzM9KSlZC/Z4QkVUisio6OjjnHCfnZRF95QrzXnyR9l98ETTpvYs1bIjGxnJs7dpUydk5fTqV77rLR1pZ4qjesyfH1q/n5NatQPKeN0vgyej/ryQNlIj0E5FXXbYPisg5ETkvIk95I1xVYxw39NKY1lBt4GugElAfOAx8FneKxES4KU9pHVf9RqhqY1VtnCVL+k9et/rzzylUsyYVunQJtCrxiAjVe/RIVWy+y6dOcXTVKsrdcosPNbMAZMmenXpPPsmaIUMCrUpQMnbsWJ599tlE9+XOnTkj4ycHMZRJaX13k2P6Y7IgxnFMVfMCRYBeyTmJqp4B5gNdVPWoY7hiMQFomzqHHQBcL6Q0cMgpL51I+XV1RCQLJmPjKTeyMiznDx5k1aef0v5//wu0KjdQrUcPtk2eHBeXK9lE/PEHZdq3J2uuXD7WzAJQ/6mn2DZpEhobG2hVrkNViQ0ynSzJwxnq+SWl9d0ZqBBVPemy/aNzwkiMN51bRKSIEwU9zlX9ZmCbiLi6lXUDNjnrM4CeIpJdRCoAVTCpPg4D50WkuTO+9AjGbTGuTm9n/T7gb+eGzAI6iUgBpwuxk1OWYVk4YAD1+vcPysgARerWJTRbNo6sXJmi+junT6fynXf6WCtLHGHFi1O2Y0eiLl0KtCrs2bOHGjVq8PTTT9OwYUPef/99mjRpQt26dXnnnXeuO+bxxx+nVq1adOrUicuXLwOwa9cuunTpQqNGjWjdujXbtm0jJiaGihUroqqcOXOGkJAQFi5cCEDr1q3ZuXMnK1asoGXLljRo0ICWLVuy3WWu3f79++nSpQvVqlXj3STm9H3yySc36GmJZ5mIpGy+rJsItDuTKA8BdnsRwbYusBYTt28T8LZTPh4nmi3GwJRwqfN/wC5M1NtbXcobOzJ2AUO55n2YA2M4d2JSgFR0qdPXKd8JPOpJ3/QczXz/P//oN6VL65ULFwKtSpL889ZbOu/ll5NdLyoyUgfnzasXjth8Tv5k9ZAhuvqffwKthkZERKiI6NKlS3XWrFn6+OOPa2xsrMbExOjtt9+uCxYs0IiICA0NDdW1a9eqqur999+v48ePV1XVDh066I4dO1RVddmyZdq+fXtVVe3cubNu2rRJf/31V23cuLF+8MEHGhkZqeXLl1dV1bNnz2pUVJSqqs6ZM0fvueceVVUdM2aMFi9eXE+cOKGXLl3SWrVq6cqVJmJ+WFiYqmqSeqYVW7ZsuaGM4ItmHu28v5MVzdzdwMtsEflAVd9MUP4e4DFArKpuAG5IeaqqD7up8yHwYSLlqzBBahOWRwL3JyHrW67vosyQxMbE8Pdzz9H2k0/IFha8XqXVunfn59tuo+2gQckKu7R/3jwK1659XeRyi+8p1aoV+05fPwuj0qe+b43vemWXx2PKlStH8+bNeeWVV5g9ezYNGpjXyIULFwgPD6ds2bJUqFCB+vXrA9CoUSP27NnDhQsXWLJkCffff+2VcOXKFcC0lBYuXEhERASvv/46I0eOpG3btjRpYj7sz549S+/evQkPD0dEiIqKipdxyy23UKhQIQDuueceFi1aROPGjeP3z549O1E927Rpk4o7laG4NaUV3RmoV4FRjrv3eqesHmZ+0WMpPaHFt2wcNYpsefNSrUePQKviliK1a5MtTx4OL19OyRYtvK5nvffShiJ167Lnr7+IjY4mxHEY8saY+IMw50NLVXn99dd58sknr9u/Z88esmfPHr8dGhrK5cuXiY2NJX/+/Kxbt+4Gma1bt+abb77h0KFDvPfee3zyySfMnz8/3oi89dZbtG/fnmnTprFnzx7atWsXXzehp1zC7aT0DHZEpAswGAgFRqnqRwn2F8B85FfCRA7qq6qbvKnrijpe3yJSFNPr5TXu3MwvqmovzPjNWGfprKo9NYOEN0rvXD51isVvv02HIUPShbtpnLOEt2hsLLtmzLAGKg0IyZKF0OzZiQqSyeoAnTt35ttvv+XCBfO6OXjwIMeOHUvy+Lx581KhQgV+/PFHwBiO9evNt3WzZs1YsmQJISEh5MiRg/r16zN8+HBat24NmBZUqVJmJsrYBOHB5syZw6lTp7h8+TK//PILrVpdH5w5uXoGAyISCnyFad3UBHo5wRJceQNYpyYowyMYg+RtXddz3Ski4UAEsADYg5nH6hF3bublAVR1t6r+6iy7XPaLiJROqr7F/yx++22q3ncfRevVC7QqXlGte3d2/Pij195iR1avJluePBSsVs3PmlkAQrNn5+qF4Pn27NSpEw888AAtWrSgTp063HfffZw/f95tnQkTJjB69Gjq1atHrVq1mO7kvMqePTtlypShuRM4uXXr1pw/f546dUwm8tdee43XX3+dVq1aERMTc53Mm266iYcffpj69etz7733Xte9l1I9g4CmGD+D3ap6FRMMPOGXYE3gLwBV3QaUF5FiXtZ15X2gObBDVStgYvAt9kZJd6GOUh3oLz0RTKGOvOH4hg1Muflm+m7dSk6nfzw9MK5ePToOHUpp58vVHYvefJOYq1dtcNg0YuOaNZQKC7MfBOmMrVu3UqNGjevKROQqxhkhjhGqOsJl/32YaT+POdsPA81U9VmXY/4D5FDVf4lIU2AJ0Ayo4KluAl1WqWpjEVkPNFDVWBFZoapNEzvelSTHoFT1fpdAf325MdDfh+oh0J/FP6gqfz3/PK3efTddGSe41s3njYHaOX06t3zzTRpoZQHiu/hUNV10GVvcEq2qjd3s9yaYwUfAYCca0EaMV3a0l3VdOSMiuTHBwyeIyDFHjkfchk9Q1S0Y129LELH9xx+5cuYMdZ94ItCqJJtq3bsz8aab6DB4sNu4emd27+bSsWOUCFAuq8yIhIQQmj070ZcukTWIPUItPsFjMANVPQc8CvHBvyOcJZenugm4C+Nk8RKmwZMP4w3ukbRNs2pJNVcvXmTBK6/Q8csv02Xg1AKVK5OnVCkOOBMlk2LXjBlUtMFh05ysYWFBNQ5l8RsrgSoiUkFEsgE9MfNS4xGR/M4+MJ7bCx2j5bGuK47DXYyqRqvqOFUdotcHgUgSa6DSGSs++ohSN93kVRdZsFKtRw+2e/Dms+7lgSFb7txEWQOV4VETXPtZTISdrcAUVd0sIv1FpL9zWA1gs4hsw3jsveCubsJzOHFbzyWynBeRc97o6beEhemN9OAkcWb3biY0bcoj69eTp9QNwdnTDfG5nQ4dip9z48rlU6cYWb48Tx05YuPvpSFbt26lSoUKnN6xwycJJi1pQxJOEhk+H1Q8IlIKKOd6vKq676Ox+Jz5L79M45dfTtfGCSB/hQrkq1CBffPmUT6RCOW7f//dBocNEKHZs6OxscRcvRo0KVss6RMncWySqJOvzx0eDZSIfAz0wMRTipsgoBiPDEsasWf2bE5s3EjXieki56JHqnXvzvbJkxM1ULZ7L3CICFlz5+bqhQvkLOj2/WJJJblz546f3OtKnz596Nq1K/fdd18AtPIpq3Gf/qiiJwHetKDuBqqpyXRrCQAxV6/y9/PP0/7zz8mSI1mRQoKWat27M75BA27++mtCs2aNL4+OjGTvnDncPGxYALXL3MSNQ2VUAxUdHU1GyP8W7DiTclOFN04SuzHp2i0BYu3QoeSrWJGKXbsGWhWfkbdMGQpUq8beuXOvK983bx5F6tQhrGjRAGlmyRpAR4mkUmmsW7eO5s2bU7duXbp168ZpJ7Btu3btGDBgAE2bNqVq1ar8888/icpt164db7zxBm3btmXw4MGsXr2atm3b0qhRIzp37szhw4fdyouJieHVV1+NT6kxfPhwAJ5++mlmzDAObN26daNv374AjB49mjffNHG27777bho1akStWrUYMWLEdXq9/PLLNGzYkI4dOyaauj0pPdMbTrijT53F6xeZNwbqErBORIaLyJC4JeWqWpLDxSNHWP7f/9L+888z3OTJuG4+V3ZNn04l270XULLmykV0ZCSxCUL+pBXh4eE888wzbN68mfz58/PTTz/xyCOP8PHHH7Nhwwbq1KlzXV6m6OhoVqxYwRdffJFkviaAM2fOsGDBAp5//nmee+45pk6dyurVq+nbty//93//51be6NGjyZcvHytXrmTlypWMHDmSiIgI2rRpE2/EDh48yJYtWwBYtGhRfJy/b7/9ltWrV7Nq1SqGDBnCyZPGw/rixYs0bNiQNWvW0LZt2xt0j4qKcqtnekFEPsJ4AG5xlhdE5L/e1PWmnTsDNz7uFv+yZOBAavXpkyHDz1S7/36Wvvsu0VeukMUZnN85YwY95s8PtGqZGgkJIUvOnDz73HM+lz3Mi67bhKk0du3axZkzZ2jbti0AvXv3vi6lxj333BN/7J49e5KU28OJ+L99+3Y2bdrELc74Z0xMDCVKXMujmpi82bNns2HDBqZOnQqY4LLh4eG0bt2aL774gi1btlCzZk1Onz7N4cOHWbp0KUOGmO/4IUOGMG3aNMAkPwwPD6dQoUKEhITE6/TQQw/FnzcOT3qmI24D6qvJoo6IjMNEpXjdU0WPBkpVxzmTsao6RdtVNcpdHYtvuHD4MNunTKHvjh2BVsUv5C5ZksJ16rB39mwq3XEHR1atInvevBSsWtVzZYtfyZY7N4PeeovcAXghJkylcebMGa+ODw0NJTraRNB59NFHWbt2LSVLluSPP/4Ark/jUatWLZYuXeq1PFXlyy+/pHPnzjccf/r0af7880/atGnDqVOnmDJlCrlz5yZPnjzMnz+fuXPnsnTpUnLlykW7du2IjEw8QlxiaTzc6ZnOyA/Eee3l87aSxy4+EWkHhGPCqw8DdoiIzcSVBqz+4gtqPPQQuQoXDrQqfqNa9+5snzIFMN57tnsvOAjkOFRC8uXLR4ECBeK70saPHx/fmkqKMWPGsG7dunjj5Eq1atU4fvx4/Is/KiqKzZtvmGd6HZ07d+brr7+OT2S4Y8cO4uZNtmjRgi+++II2bdrQunVrPv300+vSeBQoUIBcuXKxbds2li1bFi8zNjY2vkX2ww8/cNNNN6VazyDlv8BaERnrtJ5WA//xpqI3XXyfAZ1UdTuAiFQFJgKNUqisxQuunD3LxlGjeHj16kCr4leq3nsvi958k+jISHZOn06nBIPIlsCQNXduzu3ZEzSBY8eNG0f//v25dOkSFStWZMyYMSmWlS1bNqZOncrzzz/P2bNniY6O5sUXX6RWrVpJ1nnsscfYs2cPDRs2RFUpUqQIv/zyC2BSd8yePZvKlStTrlw5Tp06FW+gunTpwjfffEPdunWpVq1afLoPMC26zZs306hRI/Lly8fkBOOxKdEzGFHViSIyH2iCcTkfoKpHvKnrMZKEiGxwEla5LUvvBFskieUff8zJTZu4bfz4QKvidyZ36EDF229n5aBB9D90yMbfCxAJIxIc37iR/JUrkzVnzgBqZfFEMEeSEJEsmDBJ1Z2ircCfTrgkj3jTglolIqOBuDflg5gmmsVPREdGsuaLL7hv9uxAq5ImVO/Rg3kvvUSNBx6wximIyBYWRtSFC9ZAWVKEiJQE5gGHMU4RAnQFPhOR9qrqLgI64J2b+VPAZuB5rrkK9ndbw5IqNn/3HUUbNqSIk+0zo1PlnnuIuXrVRo8IMoJpHMqSLvkP8LWqtlPVl1T1RVVti/Fn8I2buRNB4n/OYvEzsTExrPzkE7p8+22gVUkzchUpwj2//UbZDh0CrYrFhay5c3Px2LFAq2FJvzRX1T4JC1V1iIhs90ZAkgZKRKaoancR2Ugi2RIz2hhUsBD+88/kKlKEUgk8ejI6Fbp0CbQKlgRkyZmT2KgoYqKirgtHZbF4yWU3+y55I8BdC+oF52/Gia8T5KgqKz7+mBZvvRUUnlOWzI2IkDUsjKiLFwnNnz/Q6ljSH/lE5J5EygXI642AJA2UqsYFfXpaVQdcJ91EOB9wYy1Latj3999EXbpEpTvuCLQqFgtwLXBsDmugLMlnAZDUy8yrbBjeOEncmA/BuA1afMyKjz6i6WuvISE20bElOEhrR4kjR47Qs2dPKlWqRM2aNbntttvY4RJJ5fPPPydHjhycPXs2vmz+/Pnky5ePBg0aUK1aNdq0acNvv/2WqPyxY8fy7LPPJkunPn36xE+otXiPqj7qbvFGhrsxqKeAp4FKIrLBZVceYEnqVLck5Mjq1Zzato0aDzwQaFUslniyhoURdekSGhvr9w8nVaVbt2707t2bSZMmAbBu3TqOHj1KVSf81cSJE2nSpAnTpk2jT58+8XVbt24db5TWrVvH3XffTc6cOenYsaNfdbb4F3dP3A+Y5tl052/c0khVH0wD3TIVKwcNotG//mWzmFqCipDQUEKzZyfqkldj2qli3rx5ZM2alf79r81iqV+/fnxUhl27dnHhwgU++OADJrpJ3Fm/fn3efvtthg4d6vZ8ffr04fnnn6dly5ZUrFgxvpWkqjz77LPUrFmT22+/nWMunoyJpb84e/Ys1apVY/t245jWq1cvRo4cmeL7YLlGkgZKVc+q6h5gMHBKVfeq6l4gSkSapZWCmYHTO3ey7++/qfv444FWxWK5gWxp1M23adMmGjVKOoLaxIkT6dWrF61bt2b79u3XGY6ENGzYkG3btnk85+HDh1m0aBG//fYb//73vwGYNm0a27dvZ+PGjYwcOZIlS0yHUVLpL/Lly8fQoUPp06cPkyZN4vTp0zxuf8s+wZtIEl8DDV22LyZSZkkFqz79lHr9+5Mtd+5Aq2KxxPOpHzxJX/EQWs0dkyZNYtq0aYSEhHDPPffw448/8swzzyR6rKcQbnHcfffdhISEULNmTY4ePQrAwoUL6dWrF6GhoZQsWZIOzvw8d+kvbrnllnh91q9fn+JrzKiISEugPC42R1W/81TPGwMl6vLfVtVYJ76SxQdcPHLEpNTY7tW8NYslzYgzJtFXrnBq2zaK1K3r1+kPtWrVStIZYcOGDYSHh8cbh6tXr1KxYsUkDdTatWtviE+XGK6pPVyNWmLX6S79RWxsLFu3biVnzpycOnWK0qVLezx3ZkFExgOVgHVAXBZMBTwaKK9SvovI8yKS1VlewKSBt/iA1YMHU/2BB8hVpEigVbFYEiVuXDTm6lW/nqdDhw5cuXLluvGblStXsmDBAiZOnMjAgQPZs2cPe/bs4dChQxw8eJC9e/feIGfDhg28//77SRovT7Rp04ZJkyYRExPD4cOHmTdvHuA+/cXnn39OjRo1mDhxIn379o1Py2EBoDHQSlWfVtXnnOV5byp6Y6D6Ay2Bg8ABoBnwhKdKIpJDRFaIyHoR2Swi7zrlBUVkjoiEO38LuNR5XUR2ish2EensUt5IRDY6+4aI83kjItlFZLJTvlxEyrvU6e2cI1xEentzM9KaK+fOsXHkSBq//HKgVbFYkkRE0mQcSkSYNm0ac+bMoVKlStSqVYuBAwdSsmRJJk2aRLdu3a47vlu3bvHefv/880+8m/kzzzzDkCFDUuzB161bN6pUqUKdOnV46qmn4nNPxaW/GDBgAPXq1aN+/fosWbKEHTt2MGrUKD777DNat25NmzZt+OCDD1J3MzIWm4DiKanoMd1GSnGMSJiqXhCRrMAiTHSKezBOFx+JyL+BAqo6QERqYvJMNQVKAnOBqqoaIyIrnLrLgD+AIao6U0SeBuqqan8R6Ql0U9UeIlIQWIWx3IqJvt5IVU8npW8g0m2s+OQTjq9bx+0TJqTpeS2WxEgsbUMcF48eJSYykrzlyqWxVhZPBHO6DQARmQfUB1YAV+LKVfVOT3U9jiWJyBgSj8XX1109Z9wq7pMrq7MocBfQzikfB8zHRKW4C5jkBKeNEJGdQFMR2QPkVdWljj7fAXcDM506Ax1ZU4GhjmHsDMxR1VNOnTlAF4wBDAqir1xh9eefc+/MmYFWxWLxSNawMC6fOBFoNSzpk4EpreiNs4PrlOwcQDfAYx4PABEJxbReKgNfqepyESkWF0ZJVQ+LSFHn8FKYFlIcB5yyKGc9YXlcnf2OrGgROQsUci1PpI6rfk/gdFdmS+P5R1vGj6dIvXoUrVcvTc9rsaSErLlyEXPlCrExMTZnVwZBRLpgphGFAqNU9aME+/MB3wNlMbbiU1Ud4+zbA5zHOD1Eq2rjpM6jqgtSqqM36TZ+SqD0REz3m0dUNQaoLyL5gWkiUtvN4Ym5B6mb8pTWcdVvBDACTBefG918SlxKDZve3JJekJAQsubKRdTFi2TP61WcT0sQ4zQevsKEsjsArBSRGaq6xeWwZ4AtqnqHiBQBtovIBFWN85Zpr6oem9Ui0hz4EqgBZMMYxIuq6vFBSknskioYi+o1qnoG05XXBTgqIiUAnL9xs+0OAGVcqpXGtNQOOOsJy6+r47i+5wNOuZEVFOz85RdyFChA6TZtAq2KxXId7sakbQLD4CMVPgRNgZ2qutsxOJMwQybXiQfyOMMmuTHvVq9StSdgKNALCAdyAo85ZR7xaKBE5LyInIv7C/yKF5HMRaSI03JCRHICNwPbgBlAnFddb0woJZzyno5nXgWMIVzhdAeeF5Hmzo16JEGdOFn3AX87Y1+zgE4iUsDxEuzklAWcuJQaTQcMsCk1LEFFjhw5OHnyZJIvvay5c3PVGqigQVU5efIkOXLkSGx3FhFZ5bIk9Lz2ZhhkKKbVcwjYCLygqrFxpwdmi8jqRGQnputOIFRVY5xuwnae6oB3XXx5vBGUCCWAcU5TMgSYoqq/ichSYIqI9AP2Afc759ksIlMwKeWjgWecLkIwaefHYqzvTGcBGA2MdxwqTgE9HVmnROR9YKVz3HtxDhOBZv/8+Vw9d86mN7cEHaVLl+bAgQMcP3480f2xMTFcOHiQPNHR9uMqSMiRI0dSk4Ldjgvh3TBIZ8zk2g6YibZzROQfVT2Hmdd0yPEhmCMi21Q1qRQal0QkG7BORAYBhwGvPAyTdDMXEbehjFR1jTcnSC+klZv51M6dqdajB3X6unWCtFiCktHVqnHnjz9SpK5NqB3MeHIzF5EWwEBV7exsvw6gqv91OeZ34CNV/cfZ/hv4t6quSCBrIHBBVT9N4lzlMEM5WYGXMEMxw5xWlVvctaA+c/7mwMwnWo+xunWB5UDmyknuA46uXcuJzZu5+0EbDN6SPinVqhUHFy+2Bir9sxKo4gynHMT0PiXM9bMP6Aj8IyLFgGqYyEJhQIiqnnfWOwHvJXUiJ8g4mBTw7yZHSXfRzNurantgL9BQVRuraiOgAeDR8lluZOWgQTR68UWyuMT/sljSEyVbtuTQEpsOLr2jqtHAs5ix+a2YIZjNItJfROLynbwPtBSRjcBfwADHa68YsEhE1mMm3/6uqn8mPIczZIMTBWhDwsUbPT1GkhCRdapa31NZesffXXxndu1iQrNmPLZ7t3XTtaRbTmzZwrQ77uDxXbsCrYrFDcEQSUJESjhzXRMNP+LSskoSbybqbhWRUZgJWwo8hLG4lmSw8rPPqPvkk9Y4WdI1hapX58rp01w8coSw4ikKr2bJJLgEZPBoiJLCGwP1KMaL7gVneyEmH5TFSy4ePcr2SZN4dKu165b0jYSEUKJFCw4uWULVe+4JtDqWIEZEzpNIgIQ4vJmo642beaSIfIWJHqHAdlW1seSTwZohQ6jWsydhxYoFWhWLJdWUatWKQ9ZAWTwQN0VJRN4DjgDjMY52DwJeTV/yZqJuO8wM4KHAMGCHiNgQCF5y9fx5NgwfTpNXXgm0KhaLTyjZsiUHFy8OtBqW9ENnVR2mqudV9Zyqfg3c601Fb0IdfQZ0UtW2qtoGM3nr81Qom6lYP2IEZW++mfwVKwZaFYvFJxRv0oTjGzYQHRkZaFUs6YMYEXlQREJFJEREHuRaZl23eGOgsqpqfD5yVd2BmXBl8UBcSo2mAzxGhrJY0g3ZwsIoVLMmR1atCrQqlvTBA0B34Kiz3M+Nc64SxRsnidUiMhrTfwim/3B1CpTMdGydMIHCtWpRrEGDQKtisfiUUs58qNI32fn6Fveo6h5uDETrFd4YqP6YsOvPYwa4FmLGoixu0NhYVg4axM3D7K2yZDxKtmzJtolBk//TEsSISA6gH1ALE5kI8Jz0Fjx08YlICLBaVf+nqveoajdV/dzJemtxw87p08mWNy9l2rcPtCoWi88p1aoVB5csSU26B0vmYTxQHOO/sACT/ui8NxXdGigntPp6EUlW/qfMjk2pYcno5Cldmiw5cnBmp416ZvFIZVV9C5OkcBxwO1DHm4redPGVADaLyAogPhaQqt6ZEk0zAwcWLiTy1Ckq3313oFWxWPxGXODYAlWqBFoVS3ATN2/2jJNV/QhQ3puK3hioZEWftcDyjz6iyWuvERIaGmhVLBa/ERc4tnafPoFWxRLcjHASx76FSTKbG3jbm4pJGihnYKs/UBmTTXG0EwHX4oGGzz9P2Q4dAq2GxeJXSrZsyfrhwwOthiXIUdVRzuoCIFkTQt0lLJyMaZr9A9wK7FXVFxI9OAOQVgkLLZaMQmx0NF8WKMCT+/aRo0CBQKtjcSEYopnHISLZMZEjyuPSKFLVJHNIxeGui6+mqtZxTjAak/fDYrFYAAjJkoXiTZpwaNkyKt56a6DVsQQv04GzmPmzyfIAd2eg4gPCqmq09UazWCwJiZuwaw2UxQ2lVbVLSiq6czOvJyLnnOU8UDduXUTOpUxPi8WSkSjpePJZLG5YIiJeuZUnJMkWlKpaFzSLxeKWks2bc2TlSmKjownJ4o1TsCUTchPQR0QiMF18Aqiq1vVU0T5RFoslxeQoUIC85cpxbP16ijdqFGh1LMFJivt/vYlmbrFYLEkSNw5lsSSGqu510r5fxiS9jVs8Yg2UxWJJFSWtgbK4QUTuFJFwIAIzF2oPMNObut5k1H3WmQVssVgsN1DKOkpY3PM+0BzYoaoVgI6AVw+MNy2o4sBKEZkiIl3E+ptbLBYX8leuTHRkJOf27w+0KpbgJEpVTwIhIhKiqvOA+t5U9GigVPVNoAowGugDhIvIf0SkUsr1tVgsGQURseNQFnecEZHcmFyCE0RkMOBV2DyvxqDUxEM64izRQAFgqogMSpm+FoslI2HHoSxuuAu4BLwE/AnsAu7wpqI3Y1DPi8hqYBCm37COqj4FNMLEV7JYLJmcki1bctAaKIsLIlJZRFqp6kVVjVXVaCcf1DogvzcyvGlBFQbuUdXOqvqjqkZBfDLDrinU3WKxZCCKN27MyS1buGoDLqcbHJ+C7SKyU0T+ncj+fCLyq4isF5HNIvKot3UdviDxzLmXnH0e8cZAVXB82F0VHw+gqlu9OYnFYsnYZMmRgyJ163Jk5cpAq2LxAhEJBb7CTKKtCfQSkZoJDnsG2KKq9YB2wGciks3LugDlVXVDwkJVXYWXCQu9MVC1XDcc5eyUcYvFch12HCpd0RTYqaq7VfUqMAkzVuSKAnkcz+3cwCmMD4I3dQFyuDl/Tm+UTNJAicjrCYLExgWNPYYJn+4WESkjIvNEZKvTPHzBKR8oIgdFZJ2z3JbgnDudpmNnl/JGIrLR2TckztVdRLKLyGSnfLmIlHep01tEwp2ltzc3w2KxpBw7HypdUQpwnRdwwClzZShQAziESVr7gjO0401dMNOTHk9YKCL9MKk3POIuWOx/gf+KyH9V9XVvhCUgGnhZVdeISB5gtYjMcfZ9rqqfJlC6JtAT02IrCcwVkaqqGgN8DTwBLAP+ALpgZiL3A06ramUR6Ql8DPQQkYLAO0BjzFfAahGZoaqnU3AdFovFC0q1bMnsxx5DY2OREBukJsBkEZFVLtsjVHWEy3Zi81kThh/qjHFo6ABUAuaIyD9e1gV4EZgmIg9yzSA1BrIB3TxdAHjXxbdCRPLFbYhIfhG521MlVT2sqmuc9fPAVhK3snHcBUxS1SuqGgHsBJqKSAkgr6ouddzdvwPudqkzzlmfCnR0WledgTmqesoxSnMwRi3Toqrs2bOHDRs2EB3t1RQEiyVZhBUvTvYCBTi5bVugVbFAtKo2dllGJNh/ACjjsl0a01Jy5VHgZzXsxIQqqu5lXVT1qKq2BN7FhDfaA7yrqi1U9Yg3F+FNNPN3VHWay0nPiMg7wC/enADA6XprACwHWgHPisgjwCpMK+s0xngtc6kW12yMctYTloNLU9NJqngWKISXTVAReQLTMiNbtmzeXk664vz586xYsYKlS5dy9epV8uXLx4QJE2jWrBmtWrWiWLFigVbRkoGIm7BbuGZiY+aWIGIlUEVEKgAHMb1XDyQ4Zh8mLNE/IlIMqAbsBs54UTceJ3LEvJQo6Y2BSqyV5XWaDmcG8U/Ai6p6TkS+xsRmUufvZ0Bfkm42umtOpqTOtQLzVTECICwszKvouumBmJgYtmzZwtKlS9m+fTt169ale/fuVK5cmZCQEI4ePcqSJUv4/PPPKVq0KK1ataJBgwYZ1khb0o44R4m6jz0WaFUsbnA+6J8FZgGhwLequllE+jv7v8G8n8eKyEbMO3WAqp4AE6M1YV1/6OmNoVklIv/DuBUq8BxeDnCJSFaMcZqgqj+Dafa57B8J/OZsJtVsPOCsJyx3rXNARLIA+TCeJgcwbpGudeZ7o3N65ujRoyxdupTly5dTsGBBWrRowcMPP0zOnNc7zBQrVoxu3bpx5513smHDBhYvXszUqVNp3LgxrVq1onTp0kmcwWJxT6lWrVj9xReBVsPiBar6B2ZM37XsG5f1Q0Anb+v6AzHDOm4OEAkD3gJuxljR2cAHqup2Rp4zFjQOOKWqL7qUl1DVw876S0AzVe0pIrWAHzAujCWBv4AqqhojIisxhnE55qZ8qap/iMgzmMgW/R0niXtUtbvjJLEaaOicdg3QSFVPJaVvWFiYXvTRJMMrV66QPXt2n8jyRGRkJGvXrmXJkiUcP36cpk2b0qJFC0qUKJEsOadOnWLJkiUsXbqUPHnycNNNN9GoUaMbjJvF4o7YmBiGFizIY7t2katw4UCrk2kRkUuqGhZoPVKLRwOVYsEiNwH/YNwTY53iN4BemEi2ihk0e9LFYP0fprsvGtMlONMpbwyMxfjOzwSeU1UVkRzAeMz41imgp6rudur0dc4H8KGqjnGnry8N1CeffMKxY8coXrw4xYoVu24pXLgwoaGhqZKvquzevZslS5awbt06qlSpQsuWLalVq1aqZcfGxrJ161YWLVrEjh07qF+/Pq1ataJChQrYQPYWb/ixUycaPvccle7wKtyaxQ9keAMlIl+o6osi8iuJj9/c6W/l0hJfGihV5dy5cxw9evS65ciRI5w9e5bChQvHGyxXI5YrVy63cs+cOcPy5ctZunQpIkLLli1p2rQp+fLlc1svpZw9e5bly5ezePFismTJQqtWrWjatCm5c+f2y/ksGYOlH3zAqW3buP377wOtSqYlMxioRqq6WkTaJrZfVRf4VbM0xpcGyh1Xr17l+PHj1xmtuPXs2bNTtGjR64xW0aJFOXjwIEuXLmXXrl00bNiQFi1apGmLRlUJDw9n8eLFbNq0iVq1atGqVSuqVKlCiJ3vYknAlXPn+KFFCxo8+yz1n3oq0OpkSjK8gYL4sEbjVPWhtFMpMKSVgUoKVeXs2bPXGay4pWDBgrRs2ZIGDRqk2dhWUly8eJEVK1awePFiYmNj6devH6VKuZveZsmMnNm1ix9atqTrpEmUbd8+0OpkOjKFgQIQkVnAHU7MpQxLoA1UekNVWbFiBT/99BPdu3encePGgVbJEmTs/esvfn/wQR5YupT8FSoEWp1MRWYyUMMx3nAzgPg3uKr+z7+qpS3WQKWM/fv3M2LECOrVq0e3bt1S7aRhyVis+fJLNowYwQNLlpAtT55Aq5NpyEwG6p1EilVV3/OPSoHBGqiUc/HiRcaMGUNUVBT9+vUjb968gVbJEiSoKrOfeILLJ05w108/2Rh9aURmMlD3q+qPnsrSO9ZApY7Y2Fh+//13li5dyuOPP04F26UTNMTGxnLx4kXOnz/PuXPnOHfuXKLrWbJkIXfu3OTJk4c8efKQO3fuRLeTG3Ek5upVpnToQNmOHWn17rt+ukqLK5nJQK1R1YaeytI71kD5hvXr1zNhwgTuvPNOWrVqla7nTqkqJ0+eJCYmJihjFl6+fJnTp097NDznz58nZ86c5MmTh7x585I3b95E16Ojozl//jwXLly44a/remhoaLzhcv3raszCwsLIlSsXOXPmJFeuXESeOMH3TZvS7tNPqXb//YG+dRmeDG+gRORW4DagOzDZZVdeoKaqNvW/emmHNVC+4+jRo4wYMYLy5cvTs2dPsmbNGmiVvCIqKop9+/axe/dudu/eTUREBCKCiJAtWzbq1atHvXr1KF++fEDc61WVw4cPs2HDBjZu3MihQ4fInz//DQYnbjtfvnzxBiNLFq/DZ3rUITIyMlEj5mrMLly4wOXLl7l06RKXL18ma9as5D57lryTJxPSvz9hVarEGy9XQ+a6xJVly5YtXX/oBILMYKDqYSI+vAe87bLrPDAvo+VWsgbKt0RGRvL9999z4sQJnnjiCQoWLBholW7gzJkz8cZo9+7dHDp0iOLFi1OxYsX4pUCBAgDs27eP9evXs379ei5evEjdunWpV68eVatW9asBjo6OZufOnfFGSVWpU6cOdevWpUqVKj4zPP4kzqhdvnyZbZMns/bDD2ny3XfE5MzJpUuX4hdXg+Zani1bNmrVqkXdunWpWbMmOXK4S9Sadtd08cgRwooVC8pxtQxvoOIPEMkLXHQSB8bNjcquqpfSQL80wxoo36OqzJ07l7/++os+ffpQvXr1gOkSExPDwYMH2bVrFxEREezevZsrV65QoUKFeGNUrlw5r+aZHTt2jA0bNrB+/XoOHTpEjRo1qFevHrVq1fIYDcQbLl68yObNm9mwYQNbt26lWLFi8UapZMmS6b41seitt9g/fz7d//qLUC/Gs06fPs2GDRvYsGEDERERVKpUiXr16lGnTh2/RVFJjLN79rB//nz2zZvH/vnzuXziBOU6duT2CROCzkMxMxmoZcDNqnrB2c4NzHYSUWUYrIHyH9u3b2fMmDF07NiRm2++OU1esBcuXIg3RLt372bfvn0ULFjwutZR0aJFU63LuXPn2LhxI+vXr2fnzp2UL18+viswf/78XsuJM3obN25k//79VK1alTp16lC7du00fQmnBRoby/R77iFX0aLcMnx4sv4Hly9fjjfemzdvplixYvGt2eLFi/v02Tq7dy/7589nv2OQoiMjKdOuHWXbt6dMu3bkq1CBv559lkPLltHt11/JV66cz86dWjKTgVqnqvU9laV3rIHyL6dOnWLkyJEULFiQhx9+2OfdNJGRkYSHh7Nt2za2bdvG6dOnKV++fLwxKl++vE9aN5502Lp1K+vXr2fz5s0ULlw43lglfHnGxMQQERERb5QiIyOpXbs2devWpVq1ahk+N9fV8+eZ0KIF9Z96igbPPJMiGdHR0YSHh8e3ZrNly0bdunWpW7cuFStWTPY44bl9+65rIUVfukSZdu0o4xikgtWq3WAAVZU1gwezYtAg7pw6lVItg+O7PTMZqMWY6OFrnO1GwFBVbZEG+qUZ1kD5n6ioKCZPnkxERARPPPFEqjzjYmNj2bdvH1u3bmXbtm3s27ePsmXLUqNGDapXr07ZsmUDGicwJiaGnTt3xo9bZcmShXr16lGqVCm2bt3K5s2bKVCgAHXq1KFOnToB1zcQnNm924RD+uEHynbokCpZqsr+/ftZv349GzZs4OzZs/HdojVq1EjU4J/bv/+6FlLUxYvGIDlLwerVvW6R7f7jD2b26UO7zz6j1sMPp+pafEFmMlBNgElcSxJYAuihql4lLUwvWAOVdixatIgZM2bwwAMPUL9+fa/rnTx5kq1bt7J161Z27NhB3rx54w1S5cqVg2LwPDFcX56HDh2ievXq1KlTJygdR9KafX//zW8PPMADS5aQv2JFn8k9ceJEfMsqvsu0enVy7d7N0UWL2L9gAVfPn7/OIBWqUSNVXYQnNm9m2h13UL1nT2764IOAOk9kGgMF8Zlxq2ESFm5T1Sh/K5bWWAOVtkRERDBq1CiaNWtG165dE209XL58me3bt8d3212+fJnq1atTvXp1atSokawxHkvwsvarr1j39dc8uHSpX5wNTh06xN8ffsjeCRO4nD8/l8uXJ6RKFXKWL0+YM38rd+7chIWFERYWFr+e22Wft12ul44fN+NrRYpw6/jxZAsLjI3INAZKRHIB/wLKqerjIlIFqKaqv7mtmM6wBirtOX/+PKNGjSJr1qw8+uij5MiRgz179rBt2za2bt3KwYMHqVChQnwrqVSpUpmuGywzoKrMefJJLh07xl0//+yzlseFw4dZM3gwG0aOpMKtt9L0tdcoXKcOV69e5eLFi/HzteLWk/p74cIFROQ6oxVnzLJmzYqIEBISEj9njpgYjg4bxpXduyk7cCDZHWcc12MSWy9btixlypTxybVnJgM1GZM+/RFVrS0iOYGl1knC4gtiYmL45ZdfWLlyJVFRURQqVCi+hVSpUqUM7yxgMcRcvcqUjh0p064dN73/fqpknQ4PZ+Unn7Bj6lRqPPggjV9+mXzly6dYnqomadRiYmKIjY1FVVHV+PXY2FhO/vQTp3/9lRIDBpCtcuVEj3Etq1evHnXr1k3VtceRmQzUKlVtLCJrVbWBU7ZeVeuliYZphDVQgWX//v3ky5fPBprNxFw8dowJTZvSZtAgqnfvnuz6R1atYsXHH7N//nzqP/00DZ59llxFivhBU+/ZOWMGs/r1o8OQIdTo1SvNzptRDJQ309CvOq0mBRCRSsAVv2plyXT4qmvDkn4JK1qUu3/5hR9vuYUCVapQrEEDj3VUlb1z57Lio484HR5O43/9iy5jxpAtd+400Ngzle+8k3x//cW0O+/k1LZttHznnaCMPBGseNOCugV4E6gJzAZaAX1Udb7ftUtDbAvKYgkOtv/4I/NfeYWHVqwgLImpCLHR0ez46SdWfPwxMVeu0HTAAKr36kVokMZ9vHj0KNO7dSN36dLcOnYsWf08Jy+jtKC89eIrBDTHePEtU9UT/lYsrbEGymIJHha9/Tb7//6b7n//fV04pKjLl9k8bhwrP/mE3CVK0HTAACrefnu6aJVER0Yy67HHOLVtG3dPn06eUqX8dq4Mb6BExG06jbiJuxkFa6AsluBBY2OZfu+95CxUiE4jR3Ll7FnWDRvG2i+/pFjjxjQdMIDSN90UaDWTjaqy/L//Zf3XX3PXtGkUb9zYL+fJDAZqnpt6qqqpm/odZFgDZbEEF1cvXOCHFi3IV6ECBxctouIdd9Dk1VcpUrt2oFVLNTt+/pk5Tz7JzcOG+SU/VoY3UJkNa6AsluDj7J49bBw9mrqPP07esmUDrY5PObp2Lb/cdRd1H3+c5m++6dNAt94YKBHpAgwGQoFRqvpRgv2vAg86m1mAGkARVT0lInswqZdigGhV9UtT0F0L6jVVHeSsX5fiXUT+o6pv+EOhQGENlMViSWsuHD7ML3ffTf6KFen87bdkzZnTJ3I9GSgnbdIO4BbgALAS6KWqW5I4/g7gpbieM8dANfa3P4K7kcWeLuuvJ9jXxQ+6WCwWS6Yid4kS9Jg/H1Vl/ddfp+WpmwI7VXW3ql7FxFu9y83xvYCJaaKZC+7mQUkS64ltWywWiyUFZM2Zk64TJ6KxsWl52lLAfpftA0CzxA50wt11AZ51KVZgtogoMFxVR/hDSXcGSpNYT2zbYrFYLClERJDQUF+KzCIiq1y2RyQwIok1MpJ6r98BLFbVUy5lrVT1kIgUBeaIyDZVXZhKnW/AnYGqJyLnMBeS01nH2Q7OvAYWi8ViAc+OCwcA1/AtpbmWUikhPUnQvaeqh5y/x0RkGqbL0OcGKskxKFUNVdW8qppHVbM463HbwTld22KxWCzesBKoIiIVRCQbxgjNSHiQiOQD2gLTXcrCRCRP3DrQCdjkDyW9icVnsVgslgyEqkaLyLPALIyb+bequllE+jv7v3EO7QbMVlVXF+diwDTHLT4L8IOq/ukPPf02D0pEygDfAcWBWEwf6GARKQhMBsoDe4DuqnraqfM60A/jW/+8qs5yyhsBY4GcwB/AC6qqIpLdOUcj4CQm0+8ep05vTAxBgA9UdZw7fa2bucViyShklIm6/gxgFQ28rKo1MHH8nhGRmsC/gb9UtQrwl7ONs68nUAvjMTLM8dUH+Bp4AqjiLHFu7v2A06paGfgc+NiRVRB4B+OV0hR4R0QK+PFaLRaLxeJj/GagVPVwXLw+VT0PbMW4Nt4FxLVmxgF3O+t3AZNU9YqqRgA7gaYiUgLIq6pL1TT3vktQJ07WVKCjmHZnZ2COqp5yWmdzsHO3LBaLJV2RJiGARaQ80ABYDhRT1cNgjBhQ1DksMb/8Us5yIJHy6+qoajRwFijkRpbFYrFY0gl+d5IQkdzAT8CLqnrOTbyppPzy3fnrp6SOq25PYLoOAVRELielXArIgunmtLICIy8zyPK1vMwgy9fyglWWb2ImBRi/GigRyYoxThNU9Wen+KiIlFDVw0733TGnPCm//APOesJy1zoHRCQLkA845ZS3S1BnfkL9nIlrfpkBLSKrfBVAMTPI8rW8zCDL1/IygyxfywtWWRkFv3XxOWNBo4Gtqvo/l10zgN7Oem+u+dfPAHqKSHYRqYBxhljhdAOeF5HmjsxHEtSJk3Uf8LczTjUL6CQiBRzniE5OmcVisVjSCf5sQbUCHgY2isg6p+wN4CNgioj0A/YB9wM4PvhTgC2YZu4zqhrj1HuKa27mM50FjAEcLyI7MS2nno6sUyLyPmYyGsB7CcJ0WCwWiyXI8ZuBUtVFJB1UtmMSdT4EPkykfBVwQ5YyVY3EMXCJ7PsW+NZbff2AL7sOM4MsX8vLDLJ8LS8zyPK1vGCVlSGwCQstFovFEpSkiZu5xWKxWCzJxRooi8VisQQl1kClQ5zow76SFbQhoMTNpLlgkOcrfKmXH+6ZT5MU+YLM8vxD8D6zaYU1UGmAiLQXkbo+knUL0NcJg59aWR0wMQ9THWVDROqJSE0RqeoDWaWd6/PJy1FEyjgvIp+9bH3x4haRkiKSF0h1+honbUJhzFzAVCMijUWkpKrGiEiq3hOZ4fl35AXtbyC9Yg2UnxGRTsAoILdLWYq+ipwf51hgp6qeTaVenYExmGC6ZZyyFD0PItIVGA8MAF4WkVKpkHWnI+tr4BURSVUMRRG5G5gCTALecnRNqaw7ReQLAOfFneKXh6PHD8DPwEvO3L+Uyrodk1DuG+BFESmcmi9vJzTZr8DPIlJaVWNT8f/M8M+/UzdofwPpGlW1i58WTKKvbUAHZzsM49qfLZlyxKk3CnjYKSsIlAQqpUCvO4E1QHXMXLV1QMEUXmM5YAMm1mIxzAukFBCWAlllgfWYKQXVgJeABcBdKdStMLARE02/DtcmhvdKgaymmPiOpzH5b+LKQ1MgqyNmvl89oA1mPt/tKbzGTsBaoIkj7xegpA+e3a+c/+VKoGIKZWT459+RF7S/gfS+2ISF/qUp5oW21PlC/g+mOydcROaq6l/eCFHz5EaLSASwW0wWyz+AcKC0iExT1SHJ0Ks5MEBVt4nIYaA10BCYKyIhqhqbDFl5gOOqutbpkrgJGAJcFJGZqjrRffXryA2cUNVNED8+0BboLSJnVHVBMmQBRAHbgXWqGiki+4AzQB8ROa3JS7JWAJOjbJqIrBWRiaraS52WlF6bVO4NtYGvVHU9XEs1IyIzMf/u5Mz9qAa8oaorRaQIUAMYJCJrgPXePmNxOF/9IZgcbqMwz8pYERkMRKnqDVlX3dCY4Hz+m+K75x+M4fXVbyAM3/4G0jW2i8+PqOonmFQfMzAxCRcAXwKHgTtFJE8yuzsUk/PqJWA40Ad4DeiRnD5+VX1DVec4L6NzzvKksy9ZP07nhxQqIosxxmAE8CIwDbhfRMolQ9YW4KyIjHBeQndg0q4sxCS4TBZquoEuYrpL4rYXYl5ujcD77iY1yTP/cTYbAlVFZLKzL0ZEiiVDta8wSTvjzr8TyKGqsaqq4qTT9lKvL1V1pojkwBiUb4HBGON8r4jk8/YaRUQcHaIx96m2qn4KRGC6Iws5x3n13lDVzzAhxqaTiuff5XwxmEg0qX3+33SefyGVz79TZwsQIiKLSP1vYCtwRkSG++I3kO4JdBMuoy3ALcAzwEsuZa8A/3LZro350eb2UtYLLmXDgBNAI5eyUUBNL2U972yLy77swBKgbzKv8UWXssqYMZC4yd+FMGM/5ZIjC6iKGU+ZCkx1ym52ZHnsTsPEcCzmsp0HM9bwhUtZA4yR8nT/r5PllIXG/QVWAyMxcSCHADm9keV6753tasA0Z/0hzEs3yW6wpGQBxV3Wa2G6+/Ik554BIc7f2zAtnmaYlsr3mO5ST//PxO7ZGwmeFW+f/8RkjcIEmE7u83/DPXO51mQ9/250q4H5fSb3N5Dwma2MMehTUvIbyEhLwBXISAumaX8ck+l3EWaQs4nL/rgH915MNuECyZUF5MK0yNZgcmn1cdbLJEPWl05ZFpdj+gEfJfMaFzs/yJbOvs+Br531u4BluBkPSUTWYKCpsy8b14xBH4yRyeJBt7sw8R2/AsrG3XOgJmZcYBqQH3gQE93e3f1PVJbz1/W+nQNOAnVSIstZr4Jx4ugPbAKqJ1NWSCIy7wH+xsPYSmLyXO7/T5gu0W5O2QCgQnJlOfuyuqx78/wnpVdWTCzOVXj//Lv7X8bdO6+efy+ucygwLBm/AVdZ5RLsy+2iXx+8+A1ktMWGOvIhIvIvzBfru06Xy5tAXmCiqi51jnkRMzDbW51+5mTKGqOmr/t/wGWM0XpJVTcnU1ZuYLKLXs0x3SatVfVcMmXlw2Q2PodpSeRyyh5S1Y0pkPWDqi51umAex7SwHlbVDW5k5QMmYAblj2EGq4eo6l5HTk7MyyMbZnD8MVVdlwxZg1V1n9MNps5x7TAvja5J3X8PskIw3balMY4OuzDPxbaU6uVc64uYlpinZ8ydvGwYQ7LH5RmJv/ZU3LMX8fD8u5PlcsynwBU8PP/J0KsFpgfA0/PvVjcRqYL50MqNh99AIrKKY1r6+xIc9wRe/AYyJIG2kBlpwXRX/QlUdbazY7pJhroc8zZuvra9kPVNguNy+EIvp9xtl4sHWYNdjqkJFPbR/XoEqObl/a+AMeJNMUGH/0eCL37nHB69q5KQVT7BMV2Ayj6S9T1QL7WyMIPsAzHjR6m6Z7i0zEjQLZmK63zLy+ffo6xkPP+e7lnch7rH5z8Z11ndy9+AN7Ie8vY3kNGWgCuQ3hfMHIrsmC+mrJivp35ACWd/DmAF8KgPZXnsK0+GrD4udRJ9CXkpayXQLy2v0Tm+LIkYHczYyX+cH3yIs13IR7KaAPl8JKsp5ks7SQOQDFmNgfw+umehznX68p7l9eE9c/vyT+Y9K+Lu+U/mPWuKm67LFFyn23uW0RfrxZcKxEyQnIkZ0xmFaaKPx7it3i4i1dWkBPkV44HkK1lu00InU1a815I6v5IUypqB8RxLk2t0kfeHI2+MiFRzuZblmIH4w5hxt1mYrkdfyJqDm4gNKZGV2L1Pgay/MF/jSZIMef84uvnqns3FjP/5QtZs3KQ0T4FeOZx9qf0f/OPolqQXZgquM39SsjIFgbaQ6XHBdHmUwXg1tcP0Q7+GmchZFvNV9hnGrXYwcBSoYWWlXpYbeS8Dh4BaCY79AuMmnWiXV2aQFcy6BausYNctsywBVyC9Lpjm/AjMjPG4PuyXMB45pZ3t1sBjeBinsLKSJ8uNvOeBg1wb0yqAmZXfILPLCmbdglVWsOuWGZaAK5DeFswchSaYOQ6TgdcS7P83xrMryTkxVlbKZHkp7zWMS3kuZzvJQfTMICuYdQtWWcGuW2ZaAq5AelqArpiYWwswLst3AnuA112OKY/5SnLr9WRlJU9WMuUN59oXalKOHxleVjDrFqyygl23zLYEXIH0sgAtMfMVGjjbI4APMAEr92Hm8FTGTKhbhftJiFZWMmQFs27BKiuYdQtWWcGuW2ZcAq5Aelmch62Py3YR4HdnvSImBtow50FzO8/DykqerGDWLVhlBbNuwSor2HXLjEvAFUgvC2aAM6/Letzs/7j5O+UwKQHyWVm+lRXMugWrrGDWLVhlBbtumXGx86C8RFVj9FoIFMHEKDulqodF5CFMQMys6kUiNSsrebKCWbdglRXMugWrrGDXLTNiY/GlAhEZi5lU1wnTlE8y7pyV5VtZwaxbsMoKZt2CVVaw65bRsQYqBTgBObMCW52/HVU13Mryv6xg1i1YZQWzbsEqK9h1yyxYA5UKRKQPsFLdRBK3svwjy9fyMoMsX8vLDLJ8Lc/XumV0rIFKBe7SD1hZ/pXla3mZQZav5WUGWb6W52vdMjrWQFksFoslKLFefBaLxWIJSqyBslgsFktQYg2UxWKxWIISa6AsFovFEpRYA2Wx+AAxLBKRW13KuovIn4HUy2JJz1gvPovFR4hIbeBHoAEm9to6oIuq7kqBrFBVjfGthhZL+sIaKIvFh4jIIOAiEOb8LQfUwQQFHaiq00WkPDDeOQbgWVVdIiLtgHcwoXDqq2rNtNXeYgkurIGyWHyIiIQBa4CrwG/AZlX9XkTyAyswrSsFYlU1UkSqABNVtbFjoH4HaqtqRCD0t1iCiSyBVsBiyUio6kURmQxcALoDd4jIK87uHEBZ4BAwVETqAzFAVRcRK6xxslgM1kBZLL4n1lkEuFdVt7vuFJGBwFGgHsZRKdJl98U00tFiCXqsF5/F4j9mAc85kawRkQZOeT7gsKrGAg9jHCosFksCrIGyWPzH+5jUChtEZJOzDSbNd28RWYbp3rOtJoslEayThMVisViCEtuCslgsFktQYg2UxWKxWIISa6AsFovFEpRYA2WxWCyWoMQaKIvFYrEEJdZAWSwWiyUosQbKYrFYLEHJ/wP0pycWIawcFgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Use subplots to create energy production line graph and currency line graph in one figure with two y-axis\n",
    "fig, ax1 = plt.subplots()\n",
    "\n",
    "fig1, = ax1.plot(canada_complete_data[\"Year\"], canada_complete_data[\"Total renewable energy generation\"]/1000, \n",
    "                color = \"forestgreen\", linewidth = 1, label = \"a\")\n",
    "fig2, = ax1.plot(canada_complete_data[\"Year\"], canada_complete_data[\"Total thermal generation\"]/1000, color = \"dimgrey\", \n",
    "                linewidth = 1, label = \"b\")\n",
    "plt.xticks(canada_complete_data[\"Year\"], canada_complete_data[\"Year\"], rotation = 45)\n",
    "plt.xlim(2004,2020)\n",
    "plt.ylim(200000, 450000)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Electricty Production (Gigawatt Hours)\")\n",
    "plt.title(\"Electricity Production by Different Energy (2005 - 2019)\")\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "fig3, = ax2.plot(canada_complete_data[\"Year\"], canada_complete_data[\"Candian Dollar Index\"], color = \"darkred\", \n",
    "                       linewidth = 1, label = \"dfad\")\n",
    "\n",
    "ax2.set_ylabel(\"Canadian Dollar (Index)\")\n",
    "plt.legend([fig1,fig2,fig3], [\"renewable\", \"non-renewable\", \"CAD Index\"], loc = \"right\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"Plots\\Question 6 - Sources vs. CAD Index.png\", bbox_inches = \"tight\")"
   ]
  },
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   "cell_type": "code",
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   "source": []
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