filecoin-ocean-eda.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "execution": {
     "iopub.execute_input": "2022-12-08T20:57:43.834763Z",
     "iopub.status.busy": "2022-12-08T20:57:43.834326Z",
     "iopub.status.idle": "2022-12-08T20:57:44.388068Z",
     "shell.execute_reply": "2022-12-08T20:57:44.386622Z",
     "shell.execute_reply.started": "2022-12-08T20:57:43.834729Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:00.682450Z",
     "iopub.status.busy": "2022-12-08T20:46:00.682056Z",
     "iopub.status.idle": "2022-12-08T20:46:00.695025Z",
     "shell.execute_reply": "2022-12-08T20:46:00.693855Z",
     "shell.execute_reply.started": "2022-12-08T20:46:00.682416Z"
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('/kaggle/input/filecoinoceanchallenge/FilecoinGreenEnergyConsumption-FilecoinGreenEnergyConsumption.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:00.697580Z",
     "iopub.status.busy": "2022-12-08T20:46:00.696306Z",
     "iopub.status.idle": "2022-12-08T20:46:00.716019Z",
     "shell.execute_reply": "2022-12-08T20:46:00.714458Z",
     "shell.execute_reply.started": "2022-12-08T20:46:00.697531Z"
    }
   },
   "outputs": [],
   "source": [
    "df.Date = pd.to_datetime(df.Date)\n",
    "df['year'] = df.Date.dt.year\n",
    "df.Date = df.Date.dt.strftime('%Y-%m-%d')\n",
    "df = df.set_index(\"Date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:00.720070Z",
     "iopub.status.busy": "2022-12-08T20:46:00.719075Z",
     "iopub.status.idle": "2022-12-08T20:46:00.796745Z",
     "shell.execute_reply": "2022-12-08T20:46:00.795285Z",
     "shell.execute_reply.started": "2022-12-08T20:46:00.720018Z"
    }
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>Energy used to seal data estimate</th>\n",
       "      <th>Energy used to seal data upper bound</th>\n",
       "      <th>Cumulative energy use lower bound</th>\n",
       "      <th>Cumulative energy use estimate</th>\n",
       "      <th>Cumulative energy use upper bound</th>\n",
       "      <th>Energy used to store data lower bound</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.300000e+02</td>\n",
       "      <td>1.300000e+02</td>\n",
       "      <td>1.300000e+02</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>1.300000e+02</td>\n",
       "      <td>1.300000e+02</td>\n",
       "      <td>1.300000e+02</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9.172850e+08</td>\n",
       "      <td>1.519408e+07</td>\n",
       "      <td>3.419768e+07</td>\n",
       "      <td>28.533072</td>\n",
       "      <td>211.998913</td>\n",
       "      <td>434.262171</td>\n",
       "      <td>5868.304266</td>\n",
       "      <td>41100.180833</td>\n",
       "      <td>88867.157630</td>\n",
       "      <td>4084.473512</td>\n",
       "      <td>23223.700725</td>\n",
       "      <td>38067.256666</td>\n",
       "      <td>8.112800e+06</td>\n",
       "      <td>5.800796e+07</td>\n",
       "      <td>1.230695e+08</td>\n",
       "      <td>888.665697</td>\n",
       "      <td>2954.758404</td>\n",
       "      <td>7977.902728</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5.639737e+08</td>\n",
       "      <td>3.425864e+06</td>\n",
       "      <td>1.078490e+07</td>\n",
       "      <td>131.554397</td>\n",
       "      <td>995.218304</td>\n",
       "      <td>2005.377628</td>\n",
       "      <td>1541.942892</td>\n",
       "      <td>10092.433410</td>\n",
       "      <td>23212.937590</td>\n",
       "      <td>920.940831</td>\n",
       "      <td>5236.330746</td>\n",
       "      <td>8583.160318</td>\n",
       "      <td>5.257421e+06</td>\n",
       "      <td>3.676172e+07</td>\n",
       "      <td>7.960536e+07</td>\n",
       "      <td>546.377724</td>\n",
       "      <td>1816.672094</td>\n",
       "      <td>4905.048493</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.984480e+05</td>\n",
       "      <td>2.053024e+06</td>\n",
       "      <td>1.573466e+07</td>\n",
       "      <td>3.600785</td>\n",
       "      <td>23.384402</td>\n",
       "      <td>54.201516</td>\n",
       "      <td>651.804634</td>\n",
       "      <td>4929.158175</td>\n",
       "      <td>9935.604259</td>\n",
       "      <td>551.893912</td>\n",
       "      <td>3137.985593</td>\n",
       "      <td>5143.646330</td>\n",
       "      <td>1.564318e+04</td>\n",
       "      <td>1.182999e+05</td>\n",
       "      <td>2.384543e+05</td>\n",
       "      <td>0.482896</td>\n",
       "      <td>1.605601</td>\n",
       "      <td>4.335152</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.399166e+08</td>\n",
       "      <td>1.364505e+07</td>\n",
       "      <td>2.496173e+07</td>\n",
       "      <td>5.288415</td>\n",
       "      <td>36.151441</td>\n",
       "      <td>79.927263</td>\n",
       "      <td>4687.715063</td>\n",
       "      <td>34469.718200</td>\n",
       "      <td>71351.837405</td>\n",
       "      <td>3668.061803</td>\n",
       "      <td>20856.046520</td>\n",
       "      <td>34186.303262</td>\n",
       "      <td>3.601446e+06</td>\n",
       "      <td>2.661061e+07</td>\n",
       "      <td>5.478655e+07</td>\n",
       "      <td>426.191188</td>\n",
       "      <td>1417.059305</td>\n",
       "      <td>3826.086517</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8.448714e+08</td>\n",
       "      <td>1.602704e+07</td>\n",
       "      <td>3.419701e+07</td>\n",
       "      <td>6.727845</td>\n",
       "      <td>47.040835</td>\n",
       "      <td>101.869532</td>\n",
       "      <td>5792.980918</td>\n",
       "      <td>41429.845125</td>\n",
       "      <td>87799.931120</td>\n",
       "      <td>4308.388893</td>\n",
       "      <td>24496.849825</td>\n",
       "      <td>40154.146020</td>\n",
       "      <td>7.279943e+06</td>\n",
       "      <td>5.257128e+07</td>\n",
       "      <td>1.105277e+08</td>\n",
       "      <td>818.511382</td>\n",
       "      <td>2721.499654</td>\n",
       "      <td>7348.099758</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.380350e+09</td>\n",
       "      <td>1.787266e+07</td>\n",
       "      <td>4.343102e+07</td>\n",
       "      <td>12.153555</td>\n",
       "      <td>88.086710</td>\n",
       "      <td>184.577494</td>\n",
       "      <td>7360.989879</td>\n",
       "      <td>50639.833890</td>\n",
       "      <td>111289.579775</td>\n",
       "      <td>4804.529536</td>\n",
       "      <td>27317.830743</td>\n",
       "      <td>44778.172390</td>\n",
       "      <td>1.235879e+07</td>\n",
       "      <td>8.790267e+07</td>\n",
       "      <td>1.873973e+08</td>\n",
       "      <td>1337.282860</td>\n",
       "      <td>4446.382689</td>\n",
       "      <td>12005.316080</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.966270e+09</td>\n",
       "      <td>2.114131e+07</td>\n",
       "      <td>5.266258e+07</td>\n",
       "      <td>1404.098113</td>\n",
       "      <td>10618.245610</td>\n",
       "      <td>21402.982540</td>\n",
       "      <td>8395.849442</td>\n",
       "      <td>58207.598740</td>\n",
       "      <td>127037.128800</td>\n",
       "      <td>5683.207492</td>\n",
       "      <td>32313.861150</td>\n",
       "      <td>52967.443080</td>\n",
       "      <td>1.830898e+07</td>\n",
       "      <td>1.282327e+08</td>\n",
       "      <td>2.772653e+08</td>\n",
       "      <td>1904.922699</td>\n",
       "      <td>6333.749997</td>\n",
       "      <td>17101.242970</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Data storage capacity  Data storage capacity added per day  \\\n",
       "count           1.300000e+02                         1.300000e+02   \n",
       "mean            9.172850e+08                         1.519408e+07   \n",
       "std             5.639737e+08                         3.425864e+06   \n",
       "min             4.984480e+05                         2.053024e+06   \n",
       "25%             4.399166e+08                         1.364505e+07   \n",
       "50%             8.448714e+08                         1.602704e+07   \n",
       "75%             1.380350e+09                         1.787266e+07   \n",
       "max             1.966270e+09                         2.114131e+07   \n",
       "\n",
       "       Cumulative renewable energy purchases  Energy intensity lower bound  \\\n",
       "count                           1.300000e+02                    130.000000   \n",
       "mean                            3.419768e+07                     28.533072   \n",
       "std                             1.078490e+07                    131.554397   \n",
       "min                             1.573466e+07                      3.600785   \n",
       "25%                             2.496173e+07                      5.288415   \n",
       "50%                             3.419701e+07                      6.727845   \n",
       "75%                             4.343102e+07                     12.153555   \n",
       "max                             5.266258e+07                   1404.098113   \n",
       "\n",
       "       Energy intensity estimate  Energy intensity upper bound  \\\n",
       "count                 130.000000                    130.000000   \n",
       "mean                  211.998913                    434.262171   \n",
       "std                   995.218304                   2005.377628   \n",
       "min                    23.384402                     54.201516   \n",
       "25%                    36.151441                     79.927263   \n",
       "50%                    47.040835                    101.869532   \n",
       "75%                    88.086710                    184.577494   \n",
       "max                 10618.245610                  21402.982540   \n",
       "\n",
       "       Energy consumption rate lower bound  Energy consumption rate estimate  \\\n",
       "count                           130.000000                        130.000000   \n",
       "mean                           5868.304266                      41100.180833   \n",
       "std                            1541.942892                      10092.433410   \n",
       "min                             651.804634                       4929.158175   \n",
       "25%                            4687.715063                      34469.718200   \n",
       "50%                            5792.980918                      41429.845125   \n",
       "75%                            7360.989879                      50639.833890   \n",
       "max                            8395.849442                      58207.598740   \n",
       "\n",
       "       Energy consumption rate upper bound  \\\n",
       "count                           130.000000   \n",
       "mean                          88867.157630   \n",
       "std                           23212.937590   \n",
       "min                            9935.604259   \n",
       "25%                           71351.837405   \n",
       "50%                           87799.931120   \n",
       "75%                          111289.579775   \n",
       "max                          127037.128800   \n",
       "\n",
       "       Energy used to seal data lower bound  \\\n",
       "count                            130.000000   \n",
       "mean                            4084.473512   \n",
       "std                              920.940831   \n",
       "min                              551.893912   \n",
       "25%                             3668.061803   \n",
       "50%                             4308.388893   \n",
       "75%                             4804.529536   \n",
       "max                             5683.207492   \n",
       "\n",
       "       Energy used to seal data estimate  \\\n",
       "count                         130.000000   \n",
       "mean                        23223.700725   \n",
       "std                          5236.330746   \n",
       "min                          3137.985593   \n",
       "25%                         20856.046520   \n",
       "50%                         24496.849825   \n",
       "75%                         27317.830743   \n",
       "max                         32313.861150   \n",
       "\n",
       "       Energy used to seal data upper bound  \\\n",
       "count                            130.000000   \n",
       "mean                           38067.256666   \n",
       "std                             8583.160318   \n",
       "min                             5143.646330   \n",
       "25%                            34186.303262   \n",
       "50%                            40154.146020   \n",
       "75%                            44778.172390   \n",
       "max                            52967.443080   \n",
       "\n",
       "       Cumulative energy use lower bound  Cumulative energy use estimate  \\\n",
       "count                       1.300000e+02                    1.300000e+02   \n",
       "mean                        8.112800e+06                    5.800796e+07   \n",
       "std                         5.257421e+06                    3.676172e+07   \n",
       "min                         1.564318e+04                    1.182999e+05   \n",
       "25%                         3.601446e+06                    2.661061e+07   \n",
       "50%                         7.279943e+06                    5.257128e+07   \n",
       "75%                         1.235879e+07                    8.790267e+07   \n",
       "max                         1.830898e+07                    1.282327e+08   \n",
       "\n",
       "       Cumulative energy use upper bound  \\\n",
       "count                       1.300000e+02   \n",
       "mean                        1.230695e+08   \n",
       "std                         7.960536e+07   \n",
       "min                         2.384543e+05   \n",
       "25%                         5.478655e+07   \n",
       "50%                         1.105277e+08   \n",
       "75%                         1.873973e+08   \n",
       "max                         2.772653e+08   \n",
       "\n",
       "       Energy used to store data lower bound  \\\n",
       "count                             130.000000   \n",
       "mean                              888.665697   \n",
       "std                               546.377724   \n",
       "min                                 0.482896   \n",
       "25%                               426.191188   \n",
       "50%                               818.511382   \n",
       "75%                              1337.282860   \n",
       "max                              1904.922699   \n",
       "\n",
       "       Energy used to store data estimate  \\\n",
       "count                          130.000000   \n",
       "mean                          2954.758404   \n",
       "std                           1816.672094   \n",
       "min                              1.605601   \n",
       "25%                           1417.059305   \n",
       "50%                           2721.499654   \n",
       "75%                           4446.382689   \n",
       "max                           6333.749997   \n",
       "\n",
       "       Energy used to store data upper bound    year  \n",
       "count                             130.000000   130.0  \n",
       "mean                             7977.902728  2020.0  \n",
       "std                              4905.048493     0.0  \n",
       "min                                 4.335152  2020.0  \n",
       "25%                              3826.086517  2020.0  \n",
       "50%                              7348.099758  2020.0  \n",
       "75%                             12005.316080  2020.0  \n",
       "max                             17101.242970  2020.0  "
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.year==2020].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:00.801110Z",
     "iopub.status.busy": "2022-12-08T20:46:00.800018Z",
     "iopub.status.idle": "2022-12-08T20:46:00.892282Z",
     "shell.execute_reply": "2022-12-08T20:46:00.890203Z",
     "shell.execute_reply.started": "2022-12-08T20:46:00.801046Z"
    }
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>Energy used to seal data estimate</th>\n",
       "      <th>Energy used to seal data upper bound</th>\n",
       "      <th>Cumulative energy use lower bound</th>\n",
       "      <th>Cumulative energy use estimate</th>\n",
       "      <th>Cumulative energy use upper bound</th>\n",
       "      <th>Energy used to store data lower bound</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3.650000e+02</td>\n",
       "      <td>3.650000e+02</td>\n",
       "      <td>3.650000e+02</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>3.650000e+02</td>\n",
       "      <td>3.650000e+02</td>\n",
       "      <td>3.650000e+02</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8.573107e+09</td>\n",
       "      <td>3.904893e+07</td>\n",
       "      <td>7.626805e+08</td>\n",
       "      <td>3.192743</td>\n",
       "      <td>20.297538</td>\n",
       "      <td>47.981446</td>\n",
       "      <td>22187.254965</td>\n",
       "      <td>137062.262803</td>\n",
       "      <td>332724.402647</td>\n",
       "      <td>10497.132212</td>\n",
       "      <td>59685.111496</td>\n",
       "      <td>97833.178500</td>\n",
       "      <td>9.854931e+07</td>\n",
       "      <td>6.414550e+08</td>\n",
       "      <td>1.483698e+09</td>\n",
       "      <td>8305.626233</td>\n",
       "      <td>27615.692837</td>\n",
       "      <td>74562.885046</td>\n",
       "      <td>2021.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.594770e+09</td>\n",
       "      <td>1.302226e+07</td>\n",
       "      <td>3.976652e+08</td>\n",
       "      <td>0.809995</td>\n",
       "      <td>6.127666</td>\n",
       "      <td>12.347326</td>\n",
       "      <td>7724.244445</td>\n",
       "      <td>44931.468890</td>\n",
       "      <td>115209.659590</td>\n",
       "      <td>3500.644670</td>\n",
       "      <td>19904.137931</td>\n",
       "      <td>32625.977068</td>\n",
       "      <td>5.990165e+07</td>\n",
       "      <td>3.746910e+08</td>\n",
       "      <td>8.991130e+08</td>\n",
       "      <td>4451.413455</td>\n",
       "      <td>14800.674053</td>\n",
       "      <td>39962.095629</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.984233e+09</td>\n",
       "      <td>1.797949e+07</td>\n",
       "      <td>5.559982e+07</td>\n",
       "      <td>1.742985</td>\n",
       "      <td>9.330019</td>\n",
       "      <td>25.881753</td>\n",
       "      <td>8055.022281</td>\n",
       "      <td>53740.794780</td>\n",
       "      <td>121517.395200</td>\n",
       "      <td>4833.245964</td>\n",
       "      <td>27481.108020</td>\n",
       "      <td>45045.809240</td>\n",
       "      <td>1.850230e+07</td>\n",
       "      <td>1.295242e+08</td>\n",
       "      <td>2.801817e+08</td>\n",
       "      <td>1922.325089</td>\n",
       "      <td>6391.611868</td>\n",
       "      <td>17257.471100</td>\n",
       "      <td>2021.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.364039e+09</td>\n",
       "      <td>2.751014e+07</td>\n",
       "      <td>4.198907e+08</td>\n",
       "      <td>2.744859</td>\n",
       "      <td>16.909260</td>\n",
       "      <td>41.154021</td>\n",
       "      <td>16246.926750</td>\n",
       "      <td>107237.956900</td>\n",
       "      <td>244867.987100</td>\n",
       "      <td>7395.276910</td>\n",
       "      <td>42048.429800</td>\n",
       "      <td>68923.914780</td>\n",
       "      <td>4.428372e+07</td>\n",
       "      <td>3.006904e+08</td>\n",
       "      <td>6.689297e+08</td>\n",
       "      <td>4227.880619</td>\n",
       "      <td>14057.441220</td>\n",
       "      <td>37955.353120</td>\n",
       "      <td>2021.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.814262e+09</td>\n",
       "      <td>3.726186e+07</td>\n",
       "      <td>7.615898e+08</td>\n",
       "      <td>3.202048</td>\n",
       "      <td>20.367931</td>\n",
       "      <td>48.123288</td>\n",
       "      <td>22290.228700</td>\n",
       "      <td>136932.060300</td>\n",
       "      <td>334780.206800</td>\n",
       "      <td>10016.732130</td>\n",
       "      <td>56953.629040</td>\n",
       "      <td>93355.854020</td>\n",
       "      <td>8.582973e+07</td>\n",
       "      <td>5.670852e+08</td>\n",
       "      <td>1.293703e+09</td>\n",
       "      <td>7570.457141</td>\n",
       "      <td>25171.301140</td>\n",
       "      <td>67962.981930</td>\n",
       "      <td>2021.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.304972e+10</td>\n",
       "      <td>5.141136e+07</td>\n",
       "      <td>1.147426e+09</td>\n",
       "      <td>3.952146</td>\n",
       "      <td>26.042473</td>\n",
       "      <td>59.557563</td>\n",
       "      <td>28133.686260</td>\n",
       "      <td>172122.106600</td>\n",
       "      <td>420364.854100</td>\n",
       "      <td>13820.401800</td>\n",
       "      <td>78580.721420</td>\n",
       "      <td>128806.021300</td>\n",
       "      <td>1.515867e+08</td>\n",
       "      <td>9.833888e+08</td>\n",
       "      <td>2.281611e+09</td>\n",
       "      <td>12642.571410</td>\n",
       "      <td>42035.766970</td>\n",
       "      <td>113497.353800</td>\n",
       "      <td>2021.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.621590e+10</td>\n",
       "      <td>6.615507e+07</td>\n",
       "      <td>1.355702e+09</td>\n",
       "      <td>4.494727</td>\n",
       "      <td>30.147135</td>\n",
       "      <td>67.828509</td>\n",
       "      <td>34539.414020</td>\n",
       "      <td>218115.448200</td>\n",
       "      <td>518189.013900</td>\n",
       "      <td>17783.806460</td>\n",
       "      <td>101116.042900</td>\n",
       "      <td>165744.917400</td>\n",
       "      <td>2.126684e+08</td>\n",
       "      <td>1.328899e+09</td>\n",
       "      <td>3.191929e+09</td>\n",
       "      <td>15709.968200</td>\n",
       "      <td>52234.671320</td>\n",
       "      <td>141034.585500</td>\n",
       "      <td>2021.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Data storage capacity  Data storage capacity added per day  \\\n",
       "count           3.650000e+02                         3.650000e+02   \n",
       "mean            8.573107e+09                         3.904893e+07   \n",
       "std             4.594770e+09                         1.302226e+07   \n",
       "min             1.984233e+09                         1.797949e+07   \n",
       "25%             4.364039e+09                         2.751014e+07   \n",
       "50%             7.814262e+09                         3.726186e+07   \n",
       "75%             1.304972e+10                         5.141136e+07   \n",
       "max             1.621590e+10                         6.615507e+07   \n",
       "\n",
       "       Cumulative renewable energy purchases  Energy intensity lower bound  \\\n",
       "count                           3.650000e+02                    365.000000   \n",
       "mean                            7.626805e+08                      3.192743   \n",
       "std                             3.976652e+08                      0.809995   \n",
       "min                             5.559982e+07                      1.742985   \n",
       "25%                             4.198907e+08                      2.744859   \n",
       "50%                             7.615898e+08                      3.202048   \n",
       "75%                             1.147426e+09                      3.952146   \n",
       "max                             1.355702e+09                      4.494727   \n",
       "\n",
       "       Energy intensity estimate  Energy intensity upper bound  \\\n",
       "count                 365.000000                    365.000000   \n",
       "mean                   20.297538                     47.981446   \n",
       "std                     6.127666                     12.347326   \n",
       "min                     9.330019                     25.881753   \n",
       "25%                    16.909260                     41.154021   \n",
       "50%                    20.367931                     48.123288   \n",
       "75%                    26.042473                     59.557563   \n",
       "max                    30.147135                     67.828509   \n",
       "\n",
       "       Energy consumption rate lower bound  Energy consumption rate estimate  \\\n",
       "count                           365.000000                        365.000000   \n",
       "mean                          22187.254965                     137062.262803   \n",
       "std                            7724.244445                      44931.468890   \n",
       "min                            8055.022281                      53740.794780   \n",
       "25%                           16246.926750                     107237.956900   \n",
       "50%                           22290.228700                     136932.060300   \n",
       "75%                           28133.686260                     172122.106600   \n",
       "max                           34539.414020                     218115.448200   \n",
       "\n",
       "       Energy consumption rate upper bound  \\\n",
       "count                           365.000000   \n",
       "mean                         332724.402647   \n",
       "std                          115209.659590   \n",
       "min                          121517.395200   \n",
       "25%                          244867.987100   \n",
       "50%                          334780.206800   \n",
       "75%                          420364.854100   \n",
       "max                          518189.013900   \n",
       "\n",
       "       Energy used to seal data lower bound  \\\n",
       "count                            365.000000   \n",
       "mean                           10497.132212   \n",
       "std                             3500.644670   \n",
       "min                             4833.245964   \n",
       "25%                             7395.276910   \n",
       "50%                            10016.732130   \n",
       "75%                            13820.401800   \n",
       "max                            17783.806460   \n",
       "\n",
       "       Energy used to seal data estimate  \\\n",
       "count                         365.000000   \n",
       "mean                        59685.111496   \n",
       "std                         19904.137931   \n",
       "min                         27481.108020   \n",
       "25%                         42048.429800   \n",
       "50%                         56953.629040   \n",
       "75%                         78580.721420   \n",
       "max                        101116.042900   \n",
       "\n",
       "       Energy used to seal data upper bound  \\\n",
       "count                            365.000000   \n",
       "mean                           97833.178500   \n",
       "std                            32625.977068   \n",
       "min                            45045.809240   \n",
       "25%                            68923.914780   \n",
       "50%                            93355.854020   \n",
       "75%                           128806.021300   \n",
       "max                           165744.917400   \n",
       "\n",
       "       Cumulative energy use lower bound  Cumulative energy use estimate  \\\n",
       "count                       3.650000e+02                    3.650000e+02   \n",
       "mean                        9.854931e+07                    6.414550e+08   \n",
       "std                         5.990165e+07                    3.746910e+08   \n",
       "min                         1.850230e+07                    1.295242e+08   \n",
       "25%                         4.428372e+07                    3.006904e+08   \n",
       "50%                         8.582973e+07                    5.670852e+08   \n",
       "75%                         1.515867e+08                    9.833888e+08   \n",
       "max                         2.126684e+08                    1.328899e+09   \n",
       "\n",
       "       Cumulative energy use upper bound  \\\n",
       "count                       3.650000e+02   \n",
       "mean                        1.483698e+09   \n",
       "std                         8.991130e+08   \n",
       "min                         2.801817e+08   \n",
       "25%                         6.689297e+08   \n",
       "50%                         1.293703e+09   \n",
       "75%                         2.281611e+09   \n",
       "max                         3.191929e+09   \n",
       "\n",
       "       Energy used to store data lower bound  \\\n",
       "count                             365.000000   \n",
       "mean                             8305.626233   \n",
       "std                              4451.413455   \n",
       "min                              1922.325089   \n",
       "25%                              4227.880619   \n",
       "50%                              7570.457141   \n",
       "75%                             12642.571410   \n",
       "max                             15709.968200   \n",
       "\n",
       "       Energy used to store data estimate  \\\n",
       "count                          365.000000   \n",
       "mean                         27615.692837   \n",
       "std                          14800.674053   \n",
       "min                           6391.611868   \n",
       "25%                          14057.441220   \n",
       "50%                          25171.301140   \n",
       "75%                          42035.766970   \n",
       "max                          52234.671320   \n",
       "\n",
       "       Energy used to store data upper bound    year  \n",
       "count                             365.000000   365.0  \n",
       "mean                            74562.885046  2021.0  \n",
       "std                             39962.095629     0.0  \n",
       "min                             17257.471100  2021.0  \n",
       "25%                             37955.353120  2021.0  \n",
       "50%                             67962.981930  2021.0  \n",
       "75%                            113497.353800  2021.0  \n",
       "max                            141034.585500  2021.0  "
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.year==2021].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:00.895090Z",
     "iopub.status.busy": "2022-12-08T20:46:00.894571Z",
     "iopub.status.idle": "2022-12-08T20:46:00.979541Z",
     "shell.execute_reply": "2022-12-08T20:46:00.978049Z",
     "shell.execute_reply.started": "2022-12-08T20:46:00.895045Z"
    }
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>Energy used to seal data estimate</th>\n",
       "      <th>Energy used to seal data upper bound</th>\n",
       "      <th>Cumulative energy use lower bound</th>\n",
       "      <th>Cumulative energy use estimate</th>\n",
       "      <th>Cumulative energy use upper bound</th>\n",
       "      <th>Energy used to store data lower bound</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.890000e+02</td>\n",
       "      <td>2.890000e+02</td>\n",
       "      <td>2.890000e+02</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>2.890000e+02</td>\n",
       "      <td>2.890000e+02</td>\n",
       "      <td>2.890000e+02</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>289.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.989474e+10</td>\n",
       "      <td>2.242077e+07</td>\n",
       "      <td>1.416390e+09</td>\n",
       "      <td>1.623427</td>\n",
       "      <td>8.425554</td>\n",
       "      <td>24.059245</td>\n",
       "      <td>29855.386647</td>\n",
       "      <td>154416.427071</td>\n",
       "      <td>442362.786531</td>\n",
       "      <td>6027.152491</td>\n",
       "      <td>34269.480573</td>\n",
       "      <td>56173.007405</td>\n",
       "      <td>3.152389e+08</td>\n",
       "      <td>1.870609e+09</td>\n",
       "      <td>4.713701e+09</td>\n",
       "      <td>19274.022634</td>\n",
       "      <td>64084.931573</td>\n",
       "      <td>173030.508933</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.020504e+09</td>\n",
       "      <td>7.252472e+06</td>\n",
       "      <td>3.560490e+07</td>\n",
       "      <td>0.148454</td>\n",
       "      <td>1.123066</td>\n",
       "      <td>2.262992</td>\n",
       "      <td>1913.962730</td>\n",
       "      <td>13199.453528</td>\n",
       "      <td>28657.505775</td>\n",
       "      <td>1949.609501</td>\n",
       "      <td>11085.185751</td>\n",
       "      <td>18170.343142</td>\n",
       "      <td>6.111920e+07</td>\n",
       "      <td>3.182913e+08</td>\n",
       "      <td>9.059729e+08</td>\n",
       "      <td>1957.464659</td>\n",
       "      <td>6508.448760</td>\n",
       "      <td>17572.932882</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.624013e+10</td>\n",
       "      <td>7.650816e+06</td>\n",
       "      <td>1.356034e+09</td>\n",
       "      <td>1.342260</td>\n",
       "      <td>6.298506</td>\n",
       "      <td>19.773216</td>\n",
       "      <td>25492.355260</td>\n",
       "      <td>128556.939700</td>\n",
       "      <td>377294.180200</td>\n",
       "      <td>2056.692357</td>\n",
       "      <td>11694.042730</td>\n",
       "      <td>19168.354410</td>\n",
       "      <td>2.132991e+08</td>\n",
       "      <td>1.332270e+09</td>\n",
       "      <td>3.201294e+09</td>\n",
       "      <td>15733.435360</td>\n",
       "      <td>52312.698160</td>\n",
       "      <td>141245.259400</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.800405e+10</td>\n",
       "      <td>1.437181e+07</td>\n",
       "      <td>1.379935e+09</td>\n",
       "      <td>1.449733</td>\n",
       "      <td>7.111543</td>\n",
       "      <td>21.411496</td>\n",
       "      <td>29007.113250</td>\n",
       "      <td>143504.615000</td>\n",
       "      <td>429276.067200</td>\n",
       "      <td>3863.429427</td>\n",
       "      <td>21966.877370</td>\n",
       "      <td>36007.127760</td>\n",
       "      <td>2.605878e+08</td>\n",
       "      <td>1.583674e+09</td>\n",
       "      <td>3.903182e+09</td>\n",
       "      <td>17442.319730</td>\n",
       "      <td>57994.632870</td>\n",
       "      <td>156586.589000</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.022467e+10</td>\n",
       "      <td>2.431549e+07</td>\n",
       "      <td>1.425743e+09</td>\n",
       "      <td>1.676417</td>\n",
       "      <td>8.826421</td>\n",
       "      <td>24.866998</td>\n",
       "      <td>29705.647130</td>\n",
       "      <td>147460.941500</td>\n",
       "      <td>438849.166100</td>\n",
       "      <td>6536.489484</td>\n",
       "      <td>37165.493940</td>\n",
       "      <td>60920.023640</td>\n",
       "      <td>3.152991e+08</td>\n",
       "      <td>1.878830e+09</td>\n",
       "      <td>4.716005e+09</td>\n",
       "      <td>19593.660820</td>\n",
       "      <td>65147.708740</td>\n",
       "      <td>175900.027100</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.175660e+10</td>\n",
       "      <td>2.864445e+07</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.749087</td>\n",
       "      <td>9.376178</td>\n",
       "      <td>25.974766</td>\n",
       "      <td>31571.728450</td>\n",
       "      <td>168615.268900</td>\n",
       "      <td>469034.798800</td>\n",
       "      <td>7700.200511</td>\n",
       "      <td>43782.179430</td>\n",
       "      <td>71765.800020</td>\n",
       "      <td>3.686084e+08</td>\n",
       "      <td>2.151154e+09</td>\n",
       "      <td>5.505276e+09</td>\n",
       "      <td>21077.796590</td>\n",
       "      <td>70082.368270</td>\n",
       "      <td>189223.699700</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.270389e+10</td>\n",
       "      <td>3.458179e+07</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.862770</td>\n",
       "      <td>10.236194</td>\n",
       "      <td>27.707707</td>\n",
       "      <td>33541.436070</td>\n",
       "      <td>180134.763600</td>\n",
       "      <td>497762.033700</td>\n",
       "      <td>9296.277325</td>\n",
       "      <td>52857.231620</td>\n",
       "      <td>86641.221680</td>\n",
       "      <td>4.197450e+08</td>\n",
       "      <td>2.399932e+09</td>\n",
       "      <td>6.260157e+09</td>\n",
       "      <td>21995.524110</td>\n",
       "      <td>73133.755430</td>\n",
       "      <td>197462.501900</td>\n",
       "      <td>2022.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Data storage capacity  Data storage capacity added per day  \\\n",
       "count           2.890000e+02                         2.890000e+02   \n",
       "mean            1.989474e+10                         2.242077e+07   \n",
       "std             2.020504e+09                         7.252472e+06   \n",
       "min             1.624013e+10                         7.650816e+06   \n",
       "25%             1.800405e+10                         1.437181e+07   \n",
       "50%             2.022467e+10                         2.431549e+07   \n",
       "75%             2.175660e+10                         2.864445e+07   \n",
       "max             2.270389e+10                         3.458179e+07   \n",
       "\n",
       "       Cumulative renewable energy purchases  Energy intensity lower bound  \\\n",
       "count                           2.890000e+02                    289.000000   \n",
       "mean                            1.416390e+09                      1.623427   \n",
       "std                             3.560490e+07                      0.148454   \n",
       "min                             1.356034e+09                      1.342260   \n",
       "25%                             1.379935e+09                      1.449733   \n",
       "50%                             1.425743e+09                      1.676417   \n",
       "75%                             1.452033e+09                      1.749087   \n",
       "max                             1.452033e+09                      1.862770   \n",
       "\n",
       "       Energy intensity estimate  Energy intensity upper bound  \\\n",
       "count                 289.000000                    289.000000   \n",
       "mean                    8.425554                     24.059245   \n",
       "std                     1.123066                      2.262992   \n",
       "min                     6.298506                     19.773216   \n",
       "25%                     7.111543                     21.411496   \n",
       "50%                     8.826421                     24.866998   \n",
       "75%                     9.376178                     25.974766   \n",
       "max                    10.236194                     27.707707   \n",
       "\n",
       "       Energy consumption rate lower bound  Energy consumption rate estimate  \\\n",
       "count                           289.000000                        289.000000   \n",
       "mean                          29855.386647                     154416.427071   \n",
       "std                            1913.962730                      13199.453528   \n",
       "min                           25492.355260                     128556.939700   \n",
       "25%                           29007.113250                     143504.615000   \n",
       "50%                           29705.647130                     147460.941500   \n",
       "75%                           31571.728450                     168615.268900   \n",
       "max                           33541.436070                     180134.763600   \n",
       "\n",
       "       Energy consumption rate upper bound  \\\n",
       "count                           289.000000   \n",
       "mean                         442362.786531   \n",
       "std                           28657.505775   \n",
       "min                          377294.180200   \n",
       "25%                          429276.067200   \n",
       "50%                          438849.166100   \n",
       "75%                          469034.798800   \n",
       "max                          497762.033700   \n",
       "\n",
       "       Energy used to seal data lower bound  \\\n",
       "count                            289.000000   \n",
       "mean                            6027.152491   \n",
       "std                             1949.609501   \n",
       "min                             2056.692357   \n",
       "25%                             3863.429427   \n",
       "50%                             6536.489484   \n",
       "75%                             7700.200511   \n",
       "max                             9296.277325   \n",
       "\n",
       "       Energy used to seal data estimate  \\\n",
       "count                         289.000000   \n",
       "mean                        34269.480573   \n",
       "std                         11085.185751   \n",
       "min                         11694.042730   \n",
       "25%                         21966.877370   \n",
       "50%                         37165.493940   \n",
       "75%                         43782.179430   \n",
       "max                         52857.231620   \n",
       "\n",
       "       Energy used to seal data upper bound  \\\n",
       "count                            289.000000   \n",
       "mean                           56173.007405   \n",
       "std                            18170.343142   \n",
       "min                            19168.354410   \n",
       "25%                            36007.127760   \n",
       "50%                            60920.023640   \n",
       "75%                            71765.800020   \n",
       "max                            86641.221680   \n",
       "\n",
       "       Cumulative energy use lower bound  Cumulative energy use estimate  \\\n",
       "count                       2.890000e+02                    2.890000e+02   \n",
       "mean                        3.152389e+08                    1.870609e+09   \n",
       "std                         6.111920e+07                    3.182913e+08   \n",
       "min                         2.132991e+08                    1.332270e+09   \n",
       "25%                         2.605878e+08                    1.583674e+09   \n",
       "50%                         3.152991e+08                    1.878830e+09   \n",
       "75%                         3.686084e+08                    2.151154e+09   \n",
       "max                         4.197450e+08                    2.399932e+09   \n",
       "\n",
       "       Cumulative energy use upper bound  \\\n",
       "count                       2.890000e+02   \n",
       "mean                        4.713701e+09   \n",
       "std                         9.059729e+08   \n",
       "min                         3.201294e+09   \n",
       "25%                         3.903182e+09   \n",
       "50%                         4.716005e+09   \n",
       "75%                         5.505276e+09   \n",
       "max                         6.260157e+09   \n",
       "\n",
       "       Energy used to store data lower bound  \\\n",
       "count                             289.000000   \n",
       "mean                            19274.022634   \n",
       "std                              1957.464659   \n",
       "min                             15733.435360   \n",
       "25%                             17442.319730   \n",
       "50%                             19593.660820   \n",
       "75%                             21077.796590   \n",
       "max                             21995.524110   \n",
       "\n",
       "       Energy used to store data estimate  \\\n",
       "count                          289.000000   \n",
       "mean                         64084.931573   \n",
       "std                           6508.448760   \n",
       "min                          52312.698160   \n",
       "25%                          57994.632870   \n",
       "50%                          65147.708740   \n",
       "75%                          70082.368270   \n",
       "max                          73133.755430   \n",
       "\n",
       "       Energy used to store data upper bound    year  \n",
       "count                             289.000000   289.0  \n",
       "mean                           173030.508933  2022.0  \n",
       "std                             17572.932882     0.0  \n",
       "min                            141245.259400  2022.0  \n",
       "25%                            156586.589000  2022.0  \n",
       "50%                            175900.027100  2022.0  \n",
       "75%                            189223.699700  2022.0  \n",
       "max                            197462.501900  2022.0  "
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.year==2022].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:00.981319Z",
     "iopub.status.busy": "2022-12-08T20:46:00.980896Z",
     "iopub.status.idle": "2022-12-08T20:46:00.990760Z",
     "shell.execute_reply": "2022-12-08T20:46:00.989134Z",
     "shell.execute_reply.started": "2022-12-08T20:46:00.981286Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22703885332"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataStorageCapacity = 'Data storage capacity'\n",
    "dfDatastorageCapacity = df[dataStorageCapacity]\n",
    "dfDatastorageCapacity.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:00.993732Z",
     "iopub.status.busy": "2022-12-08T20:46:00.992522Z",
     "iopub.status.idle": "2022-12-08T20:46:01.021274Z",
     "shell.execute_reply": "2022-12-08T20:46:01.019954Z",
     "shell.execute_reply.started": "2022-12-08T20:46:00.993688Z"
    }
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>Energy used to seal data estimate</th>\n",
       "      <th>Energy used to seal data upper bound</th>\n",
       "      <th>Cumulative energy use lower bound</th>\n",
       "      <th>Cumulative energy use estimate</th>\n",
       "      <th>Cumulative energy use upper bound</th>\n",
       "      <th>Energy used to store data lower bound</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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>2022-10-16</th>\n",
       "      <td>22703885332</td>\n",
       "      <td>7650816</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.34226</td>\n",
       "      <td>6.298506</td>\n",
       "      <td>19.773216</td>\n",
       "      <td>28381.61543</td>\n",
       "      <td>133179.6431</td>\n",
       "      <td>418097.5527</td>\n",
       "      <td>2056.692357</td>\n",
       "      <td>11694.04273</td>\n",
       "      <td>19168.35441</td>\n",
       "      <td>419744961.6</td>\n",
       "      <td>2.399932e+09</td>\n",
       "      <td>6.260157e+09</td>\n",
       "      <td>21995.52411</td>\n",
       "      <td>73133.75543</td>\n",
       "      <td>197462.5019</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Data storage capacity  Data storage capacity added per day  \\\n",
       "Date                                                                     \n",
       "2022-10-16            22703885332                              7650816   \n",
       "\n",
       "            Cumulative renewable energy purchases  \\\n",
       "Date                                                \n",
       "2022-10-16                           1.452033e+09   \n",
       "\n",
       "            Energy intensity lower bound  Energy intensity estimate  \\\n",
       "Date                                                                  \n",
       "2022-10-16                       1.34226                   6.298506   \n",
       "\n",
       "            Energy intensity upper bound  Energy consumption rate lower bound  \\\n",
       "Date                                                                            \n",
       "2022-10-16                     19.773216                          28381.61543   \n",
       "\n",
       "            Energy consumption rate estimate  \\\n",
       "Date                                           \n",
       "2022-10-16                       133179.6431   \n",
       "\n",
       "            Energy consumption rate upper bound  \\\n",
       "Date                                              \n",
       "2022-10-16                          418097.5527   \n",
       "\n",
       "            Energy used to seal data lower bound  \\\n",
       "Date                                               \n",
       "2022-10-16                           2056.692357   \n",
       "\n",
       "            Energy used to seal data estimate  \\\n",
       "Date                                            \n",
       "2022-10-16                        11694.04273   \n",
       "\n",
       "            Energy used to seal data upper bound  \\\n",
       "Date                                               \n",
       "2022-10-16                           19168.35441   \n",
       "\n",
       "            Cumulative energy use lower bound  Cumulative energy use estimate  \\\n",
       "Date                                                                            \n",
       "2022-10-16                        419744961.6                    2.399932e+09   \n",
       "\n",
       "            Cumulative energy use upper bound  \\\n",
       "Date                                            \n",
       "2022-10-16                       6.260157e+09   \n",
       "\n",
       "            Energy used to store data lower bound  \\\n",
       "Date                                                \n",
       "2022-10-16                            21995.52411   \n",
       "\n",
       "            Energy used to store data estimate  \\\n",
       "Date                                             \n",
       "2022-10-16                         73133.75543   \n",
       "\n",
       "            Energy used to store data upper bound  year  \n",
       "Date                                                     \n",
       "2022-10-16                            197462.5019  2022  "
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[dfDatastorageCapacity==22703885332]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:01.023396Z",
     "iopub.status.busy": "2022-12-08T20:46:01.022957Z",
     "iopub.status.idle": "2022-12-08T20:46:01.035567Z",
     "shell.execute_reply": "2022-12-08T20:46:01.034638Z",
     "shell.execute_reply.started": "2022-12-08T20:46:01.023363Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "66155072"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfDataStorageCapacityAddedPerDay = df['Data storage capacity added per day']\n",
    "\n",
    "dfDataStorageCapacityAddedPerDay.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:01.040364Z",
     "iopub.status.busy": "2022-12-08T20:46:01.039931Z",
     "iopub.status.idle": "2022-12-08T20:46:01.068030Z",
     "shell.execute_reply": "2022-12-08T20:46:01.066802Z",
     "shell.execute_reply.started": "2022-12-08T20:46:01.040332Z"
    },
    "scrolled": true
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>Energy used to seal data estimate</th>\n",
       "      <th>Energy used to seal data upper bound</th>\n",
       "      <th>Cumulative energy use lower bound</th>\n",
       "      <th>Cumulative energy use estimate</th>\n",
       "      <th>Cumulative energy use upper bound</th>\n",
       "      <th>Energy used to store data lower bound</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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>2021-09-10</th>\n",
       "      <td>11738170303</td>\n",
       "      <td>66155072</td>\n",
       "      <td>1.081768e+09</td>\n",
       "      <td>3.147064</td>\n",
       "      <td>19.951975</td>\n",
       "      <td>47.285131</td>\n",
       "      <td>34403.7801</td>\n",
       "      <td>218115.4482</td>\n",
       "      <td>516922.1405</td>\n",
       "      <td>17783.80646</td>\n",
       "      <td>101116.0429</td>\n",
       "      <td>165744.9174</td>\n",
       "      <td>134463336.8</td>\n",
       "      <td>876354737.3</td>\n",
       "      <td>2.024601e+09</td>\n",
       "      <td>11371.93939</td>\n",
       "      <td>37810.99418</td>\n",
       "      <td>102090.3886</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Data storage capacity  Data storage capacity added per day  \\\n",
       "Date                                                                     \n",
       "2021-09-10            11738170303                             66155072   \n",
       "\n",
       "            Cumulative renewable energy purchases  \\\n",
       "Date                                                \n",
       "2021-09-10                           1.081768e+09   \n",
       "\n",
       "            Energy intensity lower bound  Energy intensity estimate  \\\n",
       "Date                                                                  \n",
       "2021-09-10                      3.147064                  19.951975   \n",
       "\n",
       "            Energy intensity upper bound  Energy consumption rate lower bound  \\\n",
       "Date                                                                            \n",
       "2021-09-10                     47.285131                           34403.7801   \n",
       "\n",
       "            Energy consumption rate estimate  \\\n",
       "Date                                           \n",
       "2021-09-10                       218115.4482   \n",
       "\n",
       "            Energy consumption rate upper bound  \\\n",
       "Date                                              \n",
       "2021-09-10                          516922.1405   \n",
       "\n",
       "            Energy used to seal data lower bound  \\\n",
       "Date                                               \n",
       "2021-09-10                           17783.80646   \n",
       "\n",
       "            Energy used to seal data estimate  \\\n",
       "Date                                            \n",
       "2021-09-10                        101116.0429   \n",
       "\n",
       "            Energy used to seal data upper bound  \\\n",
       "Date                                               \n",
       "2021-09-10                           165744.9174   \n",
       "\n",
       "            Cumulative energy use lower bound  Cumulative energy use estimate  \\\n",
       "Date                                                                            \n",
       "2021-09-10                        134463336.8                     876354737.3   \n",
       "\n",
       "            Cumulative energy use upper bound  \\\n",
       "Date                                            \n",
       "2021-09-10                       2.024601e+09   \n",
       "\n",
       "            Energy used to store data lower bound  \\\n",
       "Date                                                \n",
       "2021-09-10                            11371.93939   \n",
       "\n",
       "            Energy used to store data estimate  \\\n",
       "Date                                             \n",
       "2021-09-10                         37810.99418   \n",
       "\n",
       "            Energy used to store data upper bound  year  \n",
       "Date                                                     \n",
       "2021-09-10                            102090.3886  2021  "
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[dfDataStorageCapacityAddedPerDay==66155072]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:01.071752Z",
     "iopub.status.busy": "2022-12-08T20:46:01.071178Z",
     "iopub.status.idle": "2022-12-08T20:46:01.103874Z",
     "shell.execute_reply": "2022-12-08T20:46:01.102140Z",
     "shell.execute_reply.started": "2022-12-08T20:46:01.071707Z"
    }
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>Energy used to seal data estimate</th>\n",
       "      <th>Energy used to seal data upper bound</th>\n",
       "      <th>Cumulative energy use lower bound</th>\n",
       "      <th>Cumulative energy use estimate</th>\n",
       "      <th>Cumulative energy use upper bound</th>\n",
       "      <th>Energy used to store data lower bound</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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>2020-08-24</th>\n",
       "      <td>498448</td>\n",
       "      <td>2053024</td>\n",
       "      <td>15734658.47</td>\n",
       "      <td>1404.098113</td>\n",
       "      <td>10618.24561</td>\n",
       "      <td>21402.98254</td>\n",
       "      <td>651.804634</td>\n",
       "      <td>4929.158175</td>\n",
       "      <td>9935.604259</td>\n",
       "      <td>551.893912</td>\n",
       "      <td>3137.985593</td>\n",
       "      <td>5143.64633</td>\n",
       "      <td>15643.17893</td>\n",
       "      <td>118299.9113</td>\n",
       "      <td>238454.2728</td>\n",
       "      <td>0.482896</td>\n",
       "      <td>1.605601</td>\n",
       "      <td>4.335152</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Data storage capacity  Data storage capacity added per day  \\\n",
       "Date                                                                     \n",
       "2020-08-24                 498448                              2053024   \n",
       "\n",
       "            Cumulative renewable energy purchases  \\\n",
       "Date                                                \n",
       "2020-08-24                            15734658.47   \n",
       "\n",
       "            Energy intensity lower bound  Energy intensity estimate  \\\n",
       "Date                                                                  \n",
       "2020-08-24                   1404.098113                10618.24561   \n",
       "\n",
       "            Energy intensity upper bound  Energy consumption rate lower bound  \\\n",
       "Date                                                                            \n",
       "2020-08-24                   21402.98254                           651.804634   \n",
       "\n",
       "            Energy consumption rate estimate  \\\n",
       "Date                                           \n",
       "2020-08-24                       4929.158175   \n",
       "\n",
       "            Energy consumption rate upper bound  \\\n",
       "Date                                              \n",
       "2020-08-24                          9935.604259   \n",
       "\n",
       "            Energy used to seal data lower bound  \\\n",
       "Date                                               \n",
       "2020-08-24                            551.893912   \n",
       "\n",
       "            Energy used to seal data estimate  \\\n",
       "Date                                            \n",
       "2020-08-24                        3137.985593   \n",
       "\n",
       "            Energy used to seal data upper bound  \\\n",
       "Date                                               \n",
       "2020-08-24                            5143.64633   \n",
       "\n",
       "            Cumulative energy use lower bound  Cumulative energy use estimate  \\\n",
       "Date                                                                            \n",
       "2020-08-24                        15643.17893                     118299.9113   \n",
       "\n",
       "            Cumulative energy use upper bound  \\\n",
       "Date                                            \n",
       "2020-08-24                        238454.2728   \n",
       "\n",
       "            Energy used to store data lower bound  \\\n",
       "Date                                                \n",
       "2020-08-24                               0.482896   \n",
       "\n",
       "            Energy used to store data estimate  \\\n",
       "Date                                             \n",
       "2020-08-24                            1.605601   \n",
       "\n",
       "            Energy used to store data upper bound  year  \n",
       "Date                                                     \n",
       "2020-08-24                               4.335152  2020  "
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfEnergyIntensityEstimate = df[\"Energy intensity estimate\"]\n",
    "\n",
    "df[dfEnergyIntensityEstimate==dfEnergyIntensityEstimate.max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:01.105378Z",
     "iopub.status.busy": "2022-12-08T20:46:01.105051Z",
     "iopub.status.idle": "2022-12-08T20:46:01.130404Z",
     "shell.execute_reply": "2022-12-08T20:46:01.129154Z",
     "shell.execute_reply.started": "2022-12-08T20:46:01.105350Z"
    }
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>Energy used to seal data estimate</th>\n",
       "      <th>Energy used to seal data upper bound</th>\n",
       "      <th>Cumulative energy use lower bound</th>\n",
       "      <th>Cumulative energy use estimate</th>\n",
       "      <th>Cumulative energy use upper bound</th>\n",
       "      <th>Energy used to store data lower bound</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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>2022-10-16</th>\n",
       "      <td>22703885332</td>\n",
       "      <td>7650816</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.34226</td>\n",
       "      <td>6.298506</td>\n",
       "      <td>19.773216</td>\n",
       "      <td>28381.61543</td>\n",
       "      <td>133179.6431</td>\n",
       "      <td>418097.5527</td>\n",
       "      <td>2056.692357</td>\n",
       "      <td>11694.04273</td>\n",
       "      <td>19168.35441</td>\n",
       "      <td>419744961.6</td>\n",
       "      <td>2.399932e+09</td>\n",
       "      <td>6.260157e+09</td>\n",
       "      <td>21995.52411</td>\n",
       "      <td>73133.75543</td>\n",
       "      <td>197462.5019</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Data storage capacity  Data storage capacity added per day  \\\n",
       "Date                                                                     \n",
       "2022-10-16            22703885332                              7650816   \n",
       "\n",
       "            Cumulative renewable energy purchases  \\\n",
       "Date                                                \n",
       "2022-10-16                           1.452033e+09   \n",
       "\n",
       "            Energy intensity lower bound  Energy intensity estimate  \\\n",
       "Date                                                                  \n",
       "2022-10-16                       1.34226                   6.298506   \n",
       "\n",
       "            Energy intensity upper bound  Energy consumption rate lower bound  \\\n",
       "Date                                                                            \n",
       "2022-10-16                     19.773216                          28381.61543   \n",
       "\n",
       "            Energy consumption rate estimate  \\\n",
       "Date                                           \n",
       "2022-10-16                       133179.6431   \n",
       "\n",
       "            Energy consumption rate upper bound  \\\n",
       "Date                                              \n",
       "2022-10-16                          418097.5527   \n",
       "\n",
       "            Energy used to seal data lower bound  \\\n",
       "Date                                               \n",
       "2022-10-16                           2056.692357   \n",
       "\n",
       "            Energy used to seal data estimate  \\\n",
       "Date                                            \n",
       "2022-10-16                        11694.04273   \n",
       "\n",
       "            Energy used to seal data upper bound  \\\n",
       "Date                                               \n",
       "2022-10-16                           19168.35441   \n",
       "\n",
       "            Cumulative energy use lower bound  Cumulative energy use estimate  \\\n",
       "Date                                                                            \n",
       "2022-10-16                        419744961.6                    2.399932e+09   \n",
       "\n",
       "            Cumulative energy use upper bound  \\\n",
       "Date                                            \n",
       "2022-10-16                       6.260157e+09   \n",
       "\n",
       "            Energy used to store data lower bound  \\\n",
       "Date                                                \n",
       "2022-10-16                            21995.52411   \n",
       "\n",
       "            Energy used to store data estimate  \\\n",
       "Date                                             \n",
       "2022-10-16                         73133.75543   \n",
       "\n",
       "            Energy used to store data upper bound  year  \n",
       "Date                                                     \n",
       "2022-10-16                            197462.5019  2022  "
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[dfEnergyIntensityEstimate==dfEnergyIntensityEstimate.min()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:01.134452Z",
     "iopub.status.busy": "2022-12-08T20:46:01.133676Z",
     "iopub.status.idle": "2022-12-08T20:46:01.142116Z",
     "shell.execute_reply": "2022-12-08T20:46:01.140520Z",
     "shell.execute_reply.started": "2022-12-08T20:46:01.134411Z"
    }
   },
   "outputs": [],
   "source": [
    "# convert to exobytes\n",
    "df[dataStorageCapacity] = dfDatastorageCapacity * 1.073741824E-9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:01.144670Z",
     "iopub.status.busy": "2022-12-08T20:46:01.144140Z",
     "iopub.status.idle": "2022-12-08T20:46:01.355747Z",
     "shell.execute_reply": "2022-12-08T20:46:01.354755Z",
     "shell.execute_reply.started": "2022-12-08T20:46:01.144607Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(y=dataStorageCapacity, kind='area')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:01.358335Z",
     "iopub.status.busy": "2022-12-08T20:46:01.357198Z",
     "iopub.status.idle": "2022-12-08T20:46:01.571066Z",
     "shell.execute_reply": "2022-12-08T20:46:01.569422Z",
     "shell.execute_reply.started": "2022-12-08T20:46:01.358270Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(y='Data storage capacity added per day')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:01.573256Z",
     "iopub.status.busy": "2022-12-08T20:46:01.572859Z",
     "iopub.status.idle": "2022-12-08T20:46:01.763492Z",
     "shell.execute_reply": "2022-12-08T20:46:01.761706Z",
     "shell.execute_reply.started": "2022-12-08T20:46:01.573221Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[:10].plot(y='Energy intensity estimate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:01.765647Z",
     "iopub.status.busy": "2022-12-08T20:46:01.765070Z",
     "iopub.status.idle": "2022-12-08T20:46:02.038665Z",
     "shell.execute_reply": "2022-12-08T20:46:02.037454Z",
     "shell.execute_reply.started": "2022-12-08T20:46:01.765608Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXAAAAEGCAYAAAB8Ys7jAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAAsTAAALEwEAmpwYAAA8LUlEQVR4nO3dd3zU9f3A8dfnsvcmRAKEvUOAACqIiAxX1TqrOCuOti6srVhrHb9qVayjWkVE1LZukKJixQWKIiMghL0DBEISEjLIvCSf3x/f7x2X5C65zMsl7+fjcQ/uvvN9X+7e+dzn+xlKa40QQgjvY/F0AEIIIZpHErgQQngpSeBCCOGlJIELIYSXkgQuhBBeyrc9TxYbG6uTkpLa85RCCOH1NmzYcFxrHVd3ebsm8KSkJNLS0trzlEII4fWUUgedLZcqFCGE8FKSwIUQwktJAhdCCC/VrnXgQnQ0VquVzMxMysvLPR2KEAQGBpKYmIifn59b20sCF11aZmYmYWFhJCUloZTydDiiC9Nak5eXR2ZmJn369HFrH6lCEV1aeXk5MTExkryFxymliImJadKvQUngosuT5C06iqZ+Fr0mge/IKmLDwXxPhyGEEB2G1yTw819cxeWv/uTpMIRodT4+PqSkpNgfTz31lKdDAuCCCy6goKCgwW3eeustjh492urnPvPMMwHIyMjg3XffbfXjO3ryySednrulVq5cyerVq1vlWK54TQIXorMKCgpi06ZN9secOXNafMyqqqoWH+Pzzz8nMjKywW3aKoHbEp8nEnhrJV1J4EJ0YUlJSTzyyCOMHj2aESNGsHPnTgBKSkr49a9/zbhx4xg1ahRLly4FjGR68cUXM2XKFM4991xKS0u56qqrGDp0KL/85S8ZP348aWlpLFy4kHvvvdd+ntdff53Zs2c7Pf/x48fJyMhgyJAh3HrrrQwbNozp06dTVlbGokWLSEtLY+bMmaSkpFBWVsaGDRs4++yzGTNmDDNmzCArKwuAyZMn88ADDzBu3DgGDhzIqlWrANi2bRvjxo0jJSWF5ORk9uzZA0BoaCgAc+bMYdWqVaSkpPD8888zadIkNm3aZI9x4sSJbN68uVbc1dXV/OEPf2Ds2LEkJyfz2muvAZCVlcWkSZNISUlh+PDhrFq1ijlz5lBWVkZKSgozZ86sde6VK1dy9tlnc8kll9C3b1/mzJnDO++8w7hx4xgxYgT79u0D4NNPP2X8+PGMGjWKqVOnkp2dTUZGBvPmzeP5558nJSWFVatWkZuby+WXX87YsWMZO3YsP/74Y/M/HCZpRiiE6bFPt7H9aFGrHnPoaeE88othDW5jSyA2Dz74IFdffTUAsbGxbNy4kVdeeYVnn32WBQsW8MQTTzBlyhQWLlxIQUEB48aNY+rUqQBs3LiR9PR0oqOjefbZZ4mKimL79u1s3brVfo6rrrqKJ554grlz5+Ln58ebb75pT3Ku7Nmzh/fee4/XX3+dq666isWLF3Pdddfx8ssv8+yzz5KamorVauWuu+5i6dKlxMXF8cEHH/DQQw+xcOFCwPhVsG7dOj7//HMee+wxvv76a+bNm8c999zDzJkzqayspLq6utZ5n3rqKZ599lk+++wzAKKjo3nrrbd44YUX2L17N+Xl5YwcObLWPm+88QYRERGsX7+eiooKJkyYwPTp0/n444+ZMWMGDz30ENXV1ZSWlnLWWWfx8ssv1/qj4Gjz5s3s2LGD6Oho+vbty6xZs1i3bh0vvvgiL730Ei+88AITJ05kzZo1KKVYsGABzzzzDH//+9+54447CA0N5f777wfg2muvZfbs2UycOJFDhw4xY8YMduzY0eB1b4wkcCE8zFaF4sxll10GwJgxY/j4448B+PLLL/nkk0949tlnAaMp5KFDhwCYNm0a0dHRAPzwww/cc889AAwfPpzk5GTAKGFOmTKFzz77jCFDhmC1WhkxYkSDMfbp08f+B2DMmDFkZGTU22bXrl1s3bqVadOmAUZJOCEhwel7se1/xhln8MQTT5CZmclll13GgAEDGozjyiuv5P/+7/+YO3cuCxcu5Kabbqq3zZdffkl6ejqLFi0CoLCwkD179jB27Fh+/etfY7VaufTSS2v90XRl7Nix9vfQr18/pk+fDsCIESNYsWIFYPQluPrqq8nKyqKystJlG+6vv/6a7du3218XFRVx8uRJe4m/OSSBC2FqrKTsCQEBAYBxo9NWr621ZvHixQwaNKjWtmvXriUkJMSt486aNYsnn3ySwYMHc/PNN7sdhy2WsrKyettorRk2bBg//eS8sYGz93Lttdcyfvx4li1bxgUXXMBrr73GlClTXMYRHBzMtGnTWLp0KR9++CEbNmxwGsdLL73EjBkz6q37/vvvWbZsGTfddBP33XcfN9xwg9vv22Kx2F9bLBb7e7jrrru47777uPjii1m5ciWPPvqo02PV1NSwZs0aAgMDGzxnU0gduBBeZsaMGbz00ktorQH4+eefnW43YcIEPvzwQwC2b9/Oli1b7OvGjx/P4cOHeffdd7nmmmuaHUtYWBjFxcUADBo0iNzcXHsCt1qtbNu2rcH99+/fT9++fbn77ru55JJLSE9Pd3l8m1mzZnH33XczduxYoqKi6h1zxowZvPrqq1itVgB2795NSUkJBw8eJD4+nltvvZVZs2axceNGAPz8/OzbNkdhYSE9evQA4O2333YZ+/Tp03nppZfsr1396moKSeBCeJitDtz2aKwVysMPP4zVaiU5OZlhw4bx8MMPO93ut7/9Lbm5uQwdOpQ///nPDBs2jIiICPv6q666igkTJjhNgu666aabuOOOO0hJSaG6uppFixbxwAMPMHLkSFJSUhpthfHhhx8yfPhwUlJS2Lp1a70ScXJyMj4+PowcOZLnn38eMKpgwsPDXf5ymDVrFkOHDmX06NEMHz6c22+/naqqKlauXMnIkSMZNWoUH3zwgb166bbbbiM5Odl+E7OpHn30Ua688krGjBlDbGysffkvfvELlixZYr+J+Y9//IO0tDSSk5MZOnQo8+bNa9b5HCnbX/H2kJqaqps7oUPSnGUAZDx1YWuGJLq4HTt2MGTIEE+H0Saqq6uxWq0EBgayb98+pk6dyq5du/D39wfgoosuYvbs2Zx77rkejrRpjh49yuTJk9m5cycWS+crgzr7TCqlNmitU+tuK3XgQnRSpaWlnHPOOVitVrTWvPLKK/j7+9tbrowcOdLrkve//vUvHnroIZ577rlOmbybyu0ErpTyAdKAI1rri5RSfYD3gRhgA3C91rqybcIUQjRVWFiY0ykMIyMj2b17twciarkbbrih0RuPXUlT/oTdAzg2WnwaeF5r3R84AdzSmoEJ0V7asxpRiIY09bPoVgJXSiUCFwILzNcKmAIsMjd5G7i0SWcWogMIDAwkLy9PkrjwONt44E1pZuhuFcoLwB+BMPN1DFCgtbYNuJAJ9HC2o1LqNuA2gF69erkdmBDtITExkczMTHJzcz0dihD2GXnc1WgCV0pdBORorTcopSY3NSCt9XxgPhitUJq6vxBtyc/Pz+3ZT4ToaNwpgU8ALlZKXQAEAuHAi0CkUsrXLIUnAkfaLsxTamo0FosMwC+EEI3WgWutH9RaJ2qtk4BfAd9qrWcCK4ArzM1uBJa2WZQOqmqkEC+EENCynpgPAPcppfZi1Im/0TohNaxGbjYJIQTQxI48WuuVwErz+X5gXOuH1LBqKYELIQTghWOhSBWKEEIYvC6B10gCF0IIwEsSuGMni2qpAxdCCMBLEvjTX+yyP5c6cCGEMHhFAi+tPDXDtiRwIYQweEUCD/TzsT+XBC6EEAZJ4EII4aW8IoEH+zskcLmJKYQQgJck8EDfU2FWVtWQNGcZr67c58GIhBDC87wigQc5lMBPlBiT/ryyYq+nwhFCiA7BSxL4qR7/1y5YC0CAn1eELoQQbcYrsqBjFYqNv49XhC6EEG3GK7Lg2KToessCHFqmCCFEV+QVCTwqxJ/nrx5Za1mAk1K5EEJ0JV6TBY8XV9Z6LQlcCNHVeU0WvGx0D5ITI+yvpQpFCNHVeU0CjwkN4JM7J9pfW6trPBiNEEJ4ntckcJtNf5nG2QPjKKus9nQoQgjhUY0mcKVUoFJqnVJqs1Jqm1LqMXP5W0qpA0qpTeYjpc2jBSKD/QkP8qOiSkrgQoiuzZ05MSuAKVrrk0opP+AHpdT/zHV/0FovarvwnAvys1BUZm3v0wohRIfSaAlcG06aL/3Mh0dHlAoJ8CWvpJLvd+d6MgwhhPAot+rAlVI+SqlNQA7wldZ6rbnqCaVUulLqeaVUgIt9b1NKpSml0nJzWyfh3npWXwC2ZxW1yvGEEMIbuZXAtdbVWusUIBEYp5QaDjwIDAbGAtHAAy72na+1TtVap8bFxbVK0KdFBhEa4MuxwvJWOZ4QQnijJrVC0VoXACuA87TWWWb1SgXwJjCuDeJzKT48gOwiSeBCiK7LnVYocUqpSPN5EDAN2KmUSjCXKeBSYGvbhVlf94hAjkkCF0J0Ye60QkkA3lZK+WAk/A+11p8ppb5VSsUBCtgE3NF2YdYXHx7Imn157XlKIYToUBpN4FrrdGCUk+VT2iQiN3UPDySnuILqGo2PRXkyFCGE8Aiv64lp0z0ikKoaTd7JCk+HIoQQHuG1CTw+PBBA6sGFEF2W1ybwoQnhWBR8uvmop0MRQgiP8NoE3jM6mNP7xrAu44SnQxFCCI/w2gQO0DMqmKMFZZ4OQwghPMKrE3iPqCByiysot8rQskKIrserE3jP6CAAth4p9HAkQgjR/rw6gU8dEk94oC8fpWV6OhQhhGh3Xp3AwwL9GBAfxqH8Uk+HIoQQ7c6rEzhAj8ggMgskgQshuh6vT+CJUUFkFZRTXePROSaEEKLdeX0Cjwz2o6pGU1pZ5elQhBCiXXl9AvexGG8hu0jGRBFCdC3en8DNgQinPvedZwMRQoh25v0J3GEo2Yoq6dAjhOg6vD6BWxwS+PGTlR6MRAgh2pfXJ3AfdSqBT3jqW25YuI6TFXJDUwjR+Xl9ArfUmY3n+925PLJ0m4eiEUKI9uP1CdzXyXRqizdmUlAq1SlCiM7NnVnpA5VS65RSm5VS25RSj5nL+yil1iql9iqlPlBK+bd9uPW5mg+zqEyqUYQQnZs7JfAKYIrWeiSQApynlDodeBp4XmvdHzgB3NJmUTbA4lAHfuMZve3P53yc3q5xlFZWMevt9ezNOdmu5xVCdF2NJnBtsGUlP/OhgSnAInP528ClbRFgYxxL4I9dMpzpQ+MBWL0vr13HCf9xbx5f78jh/z7b3m7nFEJ0bW7VgSulfJRSm4Ac4CtgH1CgtbbVU2QCPVzse5tSKk0plZabm9sKIdfmWAIHuGvKAPvzoX/5giteXd3q53TmRIlR5+6qSkcIIVqbWwlca12ttU4BEoFxwGB3T6C1nq+1TtVap8bFxTUvygbUTZhhgb725zUa0g66N2emtbqmRSX2A3kl5jllUC0hRPtoUisUrXUBsAI4A4hUStmyZSJwpHVDc49PnXcQHuTXrOPMfH0tgx/+otlxFJRaAUjPLJR26EKIduFOK5Q4pVSk+TwImAbswEjkV5ib3QgsbaMYG2QbzMrGsQTujr05xew6Vsy6jHwANh8uQDejFF1dUwNAfkklC3840OT9hRCiqdwpgScAK5RS6cB64Cut9WfAA8B9Sqm9QAzwRtuF6ZpPnTpwPx8LL1ydUmtZQ1UjU5/7nhkvfG9/fck/f+STzUebHEdVjSYxKohxSdF8syO7yfsLIURTudMKJV1rPUprnay1Hq61ftxcvl9rPU5r3V9rfaXW2iPjuVqcvINLR/UgwPfUipkL1tZa/88Vexn88P9cHvOe9zdxuInTtFXXaHwtiuE9ItiVXSwTTAgh2pzX98SsWwK3+eTOiYzqFQnAhjo3Mucu30W5tYaaBpLsFfNWc55DybwxVTUaH4siOTGCcmsNizYcprjc6vb+QgjRVN6fwF002xvUPYwHzjvVWMZZNUphmZFg758+kM/umlhrXXZRBTuPFbtdH15drfG1WLgwOYHkxAgeWLyF819c1az6dCGEcIfXJ/C6g1k5Or1vDPOuGw3AzmPF9dbnFBu1PmGBfgzvEcH3fziHA3+7gCEJ4fZt1h3IdysOWwncz8fCoxcPAyDzRBkrd+eyN6f+uYUQoqW8PoE7G8zK0fAeEQCkZeTz9Bc7OX7yVFX9saJyAEIDjJYrvWKCUUqRFBNs3+bq+WtYtafxDkjVNTX4mtMDje4VxX9uGQ/AzW+uZ+pz37N4Q2YT3pUQQjTO6xN43Z6YdfWIDCIs0Je3f8rg1ZX7SP3r1/Z1Ny5cB0BonaaH5w6Jr/V6+bZjjcZhK4HbDIgPrbX+9x9t5t21hxo9jhBCuMvrE3hjXdeVUvSJDeFwfpnLbcICaifwK8YksvL+yfbXX23PbvCGJ5xqhWLTLSyg3jZ/WrKlwWMIIURTdJoE3lBBvHdMCAAh/j5O19ctgQMkxYbw88PTeOqyEWQXVXCokWaFdUvgykVAclNTCNFavD6BN1aFAjChXwwA15+R5HR97+gQp8ujQvztyf9IgesSPNhK4LUv5yszR3P3uQO4bNSpcb7KrUaPTWt1DYVlVgpLpamhEKJ5mtbvvAOyl8Ab2OZX43qRmhRFn9hQ7p06gFveXs+Pe/Ps6yOCXY+fkhgVBMDvP9zMxSmncfOEJBIijGXF5Vb+/uVu/jBjUL0SOMAFIxK4YEQC1TWaj382horJL61k7dY81mfk8966wwC8fkMq04bWrncXQojGeH0J3NaRp7GKif7dwvCxKAL9fPi/S4bbl4c3MnZK94hAwGixMv/7/fxq/hr7uvnf7+et1Rl8sP6w0QrFRX28j0XxzOXJgDHx8n0fbrYnbzDm8RRCiKby/hK4T9PH344PN5Ly3CuS+cXI0xrc1s/Hwt1T+vOPb/cCcDCvlFv/lcYPe45T5tA5qKq6fgncUZCL+neAaqkXF0I0Q6cpgTcljYcE+JLx1IVcmdqTQD/XidXmvumDar3+ant2reRdXlVt1IE38MckuE4CdxyrZcXOHD5cf1imYxNCNInXJ3Bng1m1hXnXjWHyIOcTUuQWV1Bdo+sNbevIsQR+15T+rP/zVPvrrMJy/rg4nanPfdd6AQshOj2vT+CuBrNqbecN715rmNp5141hyW/PJDrEn5ziCqrqtAOvK9j/VG3VL0f1IDzQD/+6s1FAo+3NhRDCxvsTuL0deNsn8giH2X66hQcwqlcUw04L52BeiVkCd68KxVYaX/3gFD7+7Zm1tiuplNl8hBDu8foE3tBgVq1NKUWvaGOcFFvzwoHxYezNOUlltetWKFA7gQf6Gs9jQwNISYystV1xuSRwIYR7vL4VSmODWbW2pb+bQGGZlW5hRkuWwd3DKLfWUG6taLAE7jhXp2N9uMWiGNw9jJziCvJLKiWBCyHc5v0l8HaqA7eJCvEnKfZUz82pQ+LtddkN/TFxHG/FsQUKwBf3TuJ5s379ZIX0zBRCuMedSY17KqVWKKW2K6W2KaXuMZc/qpQ6opTaZD4uaPtw62tsMKu2FhXiz7RhRi/KhurhHdc52842GXNReRUrd+Xw18+28/B/tzLhqW/ZnS3jiQsh6nOnCqUK+L3WeqNSKgzYoJT6ylz3vNb62bYLr3G+FkVogC9zzh/c+MZtZGzvKJalZ7Wo+sPWIzT/ZCW//2hzrXXPfLGTBTeObVGMQojOp9EErrXOArLM58VKqR1Aj4b3aj9KKbY+NsOjMUSHGkPH2qZoa47QAKOO/F8/ZdRbl13kkfmihRAdXJPqwJVSScAowDbN+51KqXSl1EKlVJSLfW5TSqUppdJyczvnmB8xIf4AFLUggduqUDZnFtZbl19S2ezjCiE6L7cTuFIqFFgM3Ku1LgJeBfoBKRgl9L87209rPV9rnaq1To2Lc96T0dtFmqMZNlYCf/ryEcyeOtDpOsdmhhclJ9Rad6K0ksONjEcuhOh63ErgSik/jOT9jtb6YwCtdbbWulprXQO8DoxruzA7NlsHn4KyhkvKV4/txT1TBzhd53hj846z+9VaV1pZzVnPrOBQniRxIcQp7rRCUcAbwA6t9XMOyx2Lib8EtrZ+eN7B1ib8Xhel66aKDPbjhatTCA/0ZdbEPvbl/9ua1SrHF0J0Du60QpkAXA9sUUptMpf9CbhGKZWCMRR3BnB7G8TnFfx9LWQ8dWGrHS8y2J9LR/Xg0lE90FozvEcE936wiX25MlqhEOIUd1qh/IDz0Vo/b/1wBNSeu1MpxaWjerDwxwMck9YoQggHXt8TszNy1tEnPjyQnKJyAPbmFHOssNy+rqBUWqkI0RVJAu9AxvR22hITgO7hgRwzE/jU577n9L99Q3G5lffWHSLl8a9Iy8hvrzCFEB2E1w9m1Zl8cNvpuBoOPC4sgIJSK79+a7192XUL1trbja/LyCc1Kbo9whRCdBCSwDsQXycTPNjY2pp/uzPHvsyx009lVU3bBSaE6JCkCsVLOE4m4cyxwnKKy60yo48QXYiUwL1EZLB/g+vfX3+Y99cfpld0MP+8djQjEiPaKTIhhKdICdxLRLoogZ83rDvnDu5mf30ov5RfvPwDJRWtOzGE1prvdudSUFpJubWad9cektK+EB4mJXAvERJQ/79q2tB45l0/Bq01fR6s3Sx/8+ECzuwf22rn/yw9i7ve+5lrx/ciwNfCmz9mkBAZyDmDujW+sxCiTUgC9xLdI4zu+r8a25P31x9m+b2T6N8tFHDebjz3ZOt2+rFNKpGeWUCQn9HRKP+ktD8XwpMkgXuJ0ABfe3f9py5PbnT7zBNlVNfoVpuxKM8c0nbXsWJOizQmdD4kIyQK4VFSB97JRIf44+9rYe7yXdz34aZWO26eWaK3VmsOmqMiSgIXwrMkgXcSo3pFArD2T+cSaE6avHTT0VY7fn5JJYPiw2otO5hX0mrHF0I0nSTwTuKtm8bx8W/PxM/HUqtDkNat01Ik72Ql/buF8smdE1AKRiZG2EviD36czk1vrqNaWqUI0a4kgXcSEcF+jO5ljKUSFXyqyeH5L65qlePnlVQSE+pPcmIkB/52IecNTyCvpNIcj+UwK3flsuVIIRsOnqCssrpVzimEaJgk8E7o2StH2oek3XmsmKLy5s/VCWCtrqGwzEp0yKnORL1jggH4cW+efdmy9KNc/upqbnl7fb1jCCFanyTwTmhUryi2PX4er9+QCsCitMwWHe+E2QIlJjTAvqxXtJHAP00/Vc++4IcDAKzel9fo/KBCiJaTBN6J2W5svr/+EDMXrCHl8S/Zm9P0WX2Om+29Y5yUwJelZ+HvYyHQz4Jjdfu6AzK8rRBtTRJ4JxYbGsDNE5I4mFfKj3vzKCi1MvW57yi3Nq2OOr+kfgIPC/RjRA9jvJUxvaMY1yem1j7ZReW1Xv/unY28unJfc96GEMIFdyY17qmUWqGU2q6U2qaUusdcHq2U+koptcf81/VsBMJjkmJCqKgz1Ozgh7/g50Mn3D5GXonRBjwmtPaAWo9dMoy+sSHcfnZf/jhjUO19TlbyxdZjHMwroaq6hmVbsnj6i531jn2yoorr31jLHrOn5/GTFVRVy9C4QrjDnRJ4FfB7rfVQ4HTgd0qpocAc4But9QDgG/O16GD6xIY4XX7Zq6vdbvaXZ69CCai1fHSvKL69fzKTB3VjQLzRrf/0vtFEBPmxO6eYO/6zgbPnruTyeT/V2s9aXcOiDZmcKKlk7f48Vu05zkP/3UpRuZXUv37N3OW7mvo2heiSGk3gWussrfVG83kxsAPoAVwCvG1u9jZwaRvFKFpggosBrbQ+Nb5JY/JLKvGxqAbHJA/w9eF/95zFa9enEhvqz7L0LPu6zYcLAPD3tfDB+kMMeOh/3P/RZv64OJ1sc6LmdQfyueGNdQAs33bMrbiE6OqaVAeulEoCRgFrgXitte1begyIb93QRGvwsSj6xZ0qhQf7+3DDGb2BU3XbjckrqSAq2B9LI+OqDEkIJyLIj4SIoFrLu4UFcOMZvQn0tfDA4i325bnFFezPPXVTdZOZ6LuFGQN3/WnJFhZtaFkLGiE6M7cTuFIqFFgM3Ku1LnJcp43ufk5/jyulblNKpSml0nJzc1sUrGieF381im5hRvWHAnsCP+7GiIX//fkI7607XOsGZmP+dtkIzh/enbMHxgFgUYrIYH+KymuPUb7pcIG96aGj4ooqisutvLv2EPd/tBmr1IkL4ZRbCVwp5YeRvN/RWn9sLs5WSiWY6xOAHGf7aq3na61TtdapcXFxrRGzaKLhPSL47+8mAMbQs7a67LyTlWw/WsTa/Xku9733g01A/RuYDekZHcyr143h7nP7A8avgEiH3qGxoQHMHN/L/rpvbAh9HerqD+eXsvXIqTKCO39ohOiKGh1OVhmDTb8B7NBaP+ew6hPgRuAp89+lbRKhaBXBZs/MIH8fIoL88LEo8ksqufjlH6iq0Wx5dDphgbXruB1n3IkNrX0D0x2O08DFhwfan886qw8+DmOYz79hDP27hbH1SCHf7c5l7vJdfLH1VB367uyTVNdoEqOCmxyDEJ2ZOyXwCcD1wBSl1CbzcQFG4p6mlNoDTDVfiw4qIsiPO8/pz39uGY/FoogN9edYUTlVZpL+Ymv9G4c5xadKvoMTwuqtb4wtad82qS89HZJvj8ggRveOBODq1J7072Yce3iPCCYNMH6lvb/+sH37GxeuY+LTK9hw0P2mj0J0BY2WwLXWP2BUnTpzbuuGI9qKUor7Hdpq94wKZu2BU1UnK3blcGVqz1r7lFQaddZTh8Rz21l9m3xOx0koCkpP3TDtERXE6F5RLLt7Ij0ia9/wHNg9FF+LoqKqhv7dQmv1HH352z28efO4JschRGclPTG7qJAAXw7nlwEQ6Gfh8y3HmLt8Z63hZ209Nq8Yk1hriNrmcGyCmGgm7WGnRdSqZgGjOeIAc9zx5ESjp6evRXHxyNNYsz+/yb1IhejMJIF3UYlRp0q+144zWqX8c8U+9h8/NUmDLVkG+rX8Y6KU4o6z+xEZ7Ndofbqt2WOv6GC+nD2JbY/P4JejelBmrea5r3a3OBYhOgtJ4F3UgxcMYclvz2TPE+czIjHcvjwt41Qpt9xqNN8LNCcxbqk55w/m54enNdqe3HYzNSzQj4HxYQT4+nDO4G6cO7gb//35CJknSlttogohvJkk8C4qNMCXUb2i8POxcPHIHnw1exJJMcE8sHgLgx/+gnfWHnQogbdOAgejJN6Y6BAjgdfU6ep/ccpp5BRXMPHpFfzjm72tFpMQ3koSuMDHohgQH8YjFw+zL3vrxwx7CTyoFRO4O247qx9XpSZy1djaN1WnDO5mf75g1f52jUmIjkgSuLCbPDCOhy8aSoi/D0cLyihrxTrwpogI9uOZK0bWG3slLNCP5fdOYtLAOIorqsgqLGvXuIToaCSBCzulFLdM7MOfLhxCSWU1e3KMwa5aswqlpQZ1D2P21AEAbMks5Kn/7bQPliVEVyMJXNQzprcxtPt3u4yxawJ9O04CB6OrPsAX244x77t99u7+QnQ1ksBFPYPiw4gK9mPnMbME7t+xPiYxIf4E+Fr4eOMRABnsSnRZHeubKToEpZS9rbZS4N/CTjytTSlVqwdndlE5FVXSwUd0PR3rmyk6jHDzBmKgr49bTf/a2/kjugPGrwVrtWbToQLPBiSEB0gCF06FBxrD5Pj5dLzkDfD7aYNYfu8k3rgpFYCr56+xTwghRFchCVw4ZesN6dfBqk9sLBbFoO5hJEYF89xVIwFYfyDfw1EJ0b465rdTeFx4kFEC9+2gJXBHl41OJD48gB1ZRY1vLEQnIglcOBVulsB9Ld7xERnQLYx9DgNxCdEVeMe3U7Q7WxVKVY13NNHrHRPMwTxJ4KJrkQQunLJ1n/eWJtZJMSEUlFprTRwhRGcnCVw4Zbt56S3DtvaMNtqFZ56Q8VFE1yEJXDjl72smcA/H4S5bx6O8EimBi66j0QSulFqolMpRSm11WPaoUupInUmORSfi72UlcFsC/3p7NoVlVg9HI0T7cKcE/hZwnpPlz2utU8zH560blvA0WxVKjXfkb2JCjbk1/73mIFe/9pOHoxGifTSawLXW3wPSQ6KLsfXArPGSEnhogK/9+c5jxWw7WujBaIRoHy2pA79TKZVuVrFEudpIKXWbUipNKZWWm5vbgtOJ9uRn1oF7SyW4Uopoc5RCgBU7czwckRBtr7kJ/FWgH5ACZAF/d7Wh1nq+1jpVa50aFxfXzNOJ9hbg4103MQG+/f3ZpD86nV7RwezIKvZ0OEK0uWYlcK11tta6WmtdA7wOjGvdsISn2Urg3nITEyAy2J8AXx+GnRbOmv15FJXLzUzRuTUrgSulEhxe/hLY6mpb4Z38vLAEbnPjmUnklVTaZxQSorNypxnhe8BPwCClVKZS6hbgGaXUFqVUOnAOMLuN4xTtzNtuYjpK6RkJwMcbMym3ykQPovPybWwDrfU1Tha/0QaxiA4kwF6F4uFAmsE2CfOKXbk89ul2/nbZCA9HJETbkJ6YwilvrkIBuP3svgAyxKzo1BotgYuuyT6Rg5dm8AfPH0JJRRWfbDqK1rpDTgsnREtJCVw4daonppdmcKBPbChF5VXky/goopOSBC6c8vfyKhSAxChjhMIjBTJCoeicJIELp2yjEXpzCbxHpJnAZYhZ0UlJAhdO2ZoRenH+tpfAf/PORnYek5uZovORBC6c8rEorj+9N4vuOMPToTRbRJAf04fGA/DnJVtZnyFjsonORbVnV+nU1FSdlpbWbucTAiBpzjL789TeURwpKOM/s8bTLy7Ug1EJ4T6l1AatdWrd5VICF53eNeN62p+nHTxBVmE5r3+/n93ZxSxLz/JgZEK0jCRw0en99dIRbHtsRq1lmw4XcNFLP/C7dzey/ajUjwvvJAlcdHo+FkWIw4QP45Ki2XmsmMqqGgC+3ZntqdCEaBFJ4KLLGNcnGoAJ/WNrLf96h0z+ILyTJHDRZcy7bgxzr0hm6tBu9mUXJiewObNARi0UXknGQhFdRnSIP1emGjc0n/jlcAJ9fQjws7AsPYsr5q3mrAFx3Dt1AAG+PmQVllFhrSEpNsTDUQvhmiRw0SXNHN8bODVa4dYjRWw9UsSe7JM8eMFgzv37dwC8d+vpnNEvxmNxCtEQSeCiS+sbF8LoXpFcd3pvDueX8fzXuxkQf6p9+KfpRyWBiw5L6sBFlxbg68PHv53AZaMTmTTQuLn58cZMwgJ8Gd8nml3HZHJk0XFJAhfC1K+bUfLOLqpgeI8IkmJCOJhXQrm1mtkfbOJwfqmHIxSiNnfmxFyolMpRSm11WBatlPpKKbXH/DeqbcMUou2FB/oxZbDRQqVftxB6xwZz/GQly7cdY8nPR3j8s+0ejlCI2twpgb8FnFdn2RzgG631AOAb87UQXu/V60Zzx9n9uOnMPvQ3x0pZvTcPwO0RDVfuyuFPS7aQeaLjltjzSyr5+dAJ0jMLeO27fezOlqoib+TOpMbfK6WS6iy+BJhsPn8bWAk80JqBCeEJAb4+zDl/MAChZu/ND9IOA3A4v4z1GfmMTYqmsqqG1fuOM7F/LL4+p8pBK3bmcPNb6wFjONvfTu7fzu/APfe8/zOr9hy3v37uq928e+vpjOktP6a9SXPrwOO11rZRgI4B8a0UjxAdRnx4QL1ld/x7A5sOFzD7w03c9OZ6Lnt1NdlF5XyzI5tyazX/WXOQhIhAYkP9eeaLXR2qg9ArK/dy+7/TWL7tmD15RwT58egvhhIW6Me87/Y167jVNZpDeR3310Zn1uJmhFprrZRyOSatUuo24DaAXr16tfR0QrQbx4mQ3711PO+uPcRn6Vlc+s8fAYgN9Sc9s5DxT35Ta79bz+rD8ZOVLPn5CLe8vZ6nL08mMSrY7fMWlFby5fZsxveJpndM63QkqqnRPPPFLgCWb8vG39fCD388h+gQf3x9LBw+Uca/fzpIYZnV/svDx6I4UlBGXGgA/r4Wamo0Fottoo9TE0X/ZelW3ll7iCmDuzE0IZz7ZwxqlZhF45qbwLOVUgla6yylVALgcjAJrfV8YD4Y44E383xCeMSNZ/Tm7Z8Okto7mrFJ0Vx/em8W/HCAQ3mlfHrXRGYuWMP6jBP27YP9fbju9N7EhwfSNzaEed/t4/cfbuaD242JMbTWVFbXsOtYMaEBvsSHB9oH2qqsquFPS7bwWfpRyq01dAsL4Ls/nEOQv0+L38c2c8TF8X2iiQjy48LkBLqFB9rXXzzyNN744QAjH/sSi4LY0AB+d05/HvlkG93DA0mKDWbN/nzuPncAW48Usu1oIR/dfiY9ooL40Kxi+nZnDt/uzCEhMpCqas0lKacRGezf4tiFa25N6GDWgX+mtR5uvp4L5Gmtn1JKzQGitdZ/bOw4MqGD8DbVNZqSyirCA/1qLbeVRg/llfLVjmyOFZZxotTK45cMI9j/VLlowar9/HXZDkb2jOSB8wbxyNJt7Mk5WetYK++fzO7sYv72v50cOF7CRckJpPSM5K/LdvDir1K4JKVHk+J9/NNtlFZWk1dSSWVVDT2jgwnwtfD2TxmkPTSVmND6VUNaay57dTU/Hyrg6tSefLn9GCdKrQ2eKyzAl2tP78Vr3+1n7hXJDIgP46ElW+x/LEb1iuStm8cREeTX4HFE41xN6NBoAldKvYdxwzIWyAYeAf4LfAj0Ag4CV2mtG52vShK46GpKKqqY9tx3HC0sr7W8X1wI+3JLADijbww/7Tdausy/fgzTh3WnukYz6vEvOX94Ak9fkVzvuNU1Gq11rRuoAMvSs/jduxsB8LUogvx9KC6vAuDcwd1446axDcZaUVVDdIg/mw8XcOu/0njkF8NYvDGTvrEh9I0L5U9LtnDrWX2YNDCO2/+9gdLKaiKC/Fh+7yS6RwSyPiOfK+f9VOu4QX4+LL93EluOFHJmvxiiQqRU3lTNTuCtSRK46IqKy618viWLN3/M4M8XDuX0vtH4+ljQWjP44S+oMMclv2ZcT/522alkfee7G/lh73F+mnMuAb4WXvxmDy9+s4e/XzmSnceKeH3VAc7oG8M143tx9sA4IoL8eOmbPfz9q93cdGYS900fSHigH+mZBXy3K5drxvci1knp2xXHem6bY4XldI8wql62Hilky5FCLkxOqPUL5XB+KeGBfqw9kMfsDzZRUln/Ru790wdy55QBjcZwOL+U2R9s4t6pA5k4ILbR7TsrSeBCdECr9x7nv5uOEBsawLXje9W62bnhYD6Xv/oTt03qy/zv9zd6rP/cMp5lW7L4ctsxNjw8rS3Ddlt1jeadtQf5y9Jt9dbdNaU/saEB3HhmEgA5xeX86rU1pPSM5LTIIL7ZmcNpEYF8szOHYH8ffv7LNAJ8W34/wBu5SuAymJUQHnRm/1jO7O+8ZDmmdzTnDevuMnkvuuMM/rPmID8fLuBgXilzl+8kKsSfhMhAp9t7go9F0Sv61B+lA3+7gA0HT3DFvJ946du9ADzyyTa++8NkFm3IZP/xEvYfL7FvbxstsrSympW7cpkxrHv7voEOThK4EB3YnPMH88W2YwC8/etx+PtYKCq30r9bKP3iQklNMmYZ+veagzz8X2O0i2lDO1a3jGiHOm+lFKlJ0bw6czRLfj7CvtyT7Mst4ey5KwGjXfqUwd2YOb4X7647xMcbj/DC1Sk89uk2lqVnSQKvQxK4EB1YUmwIOx4/jyMFZfTvFupyu/OGdbcn8N7R7rc5bw9RTpoSnj8igfNHJFBZVcPSTUf4w6J0AP5xzSjOHhgHQGpSNI/8Yhjhgb6sPZDP0k1HKC63EhYorVpsJIEL0cEF+fs0mLzB6FRk09FmEYpuoNWJv6+FK1N7MnlQN8KDfOvVcduaIP5qbE/eW3eIRRsyuXlCnzaN15vIcLJCdAKOrUX6drAEHmx2RApuoENSXFhAgzcoR/aMZGB8KF/vyG71+LyZlMCF6CRmTezDliOFjOsT7elQalFKMf/6MQzqHtai45zZL5b31x9y2ryxq5IELkQn8eeLhno6BJemt8LNx35xIZRba8gpriA+PJBNhwsIDfChd0wIq/flMb5PNEXlVrqFdZxWOG1NErgQwiv0NG/OHswrxc/HYh9UzFGAr4UPbj+DlJ6R9mVaa/YfL6FHZBCBfp2rHbkkcCGEV0gyR2bMOF5CRp7RVvzC5AQ2HjxBVmE50SH+5JdUctOb6xgUH0agnw8XJieYnaWOAkYTy+tO782EfjG1hiEot1bzt893kJwYyfd7cjlwvIQ55w2u10Y/v6SSMms1PSKD2uldN0x6YgohvEJ1jSb50eWcPSiOzYcLCfY3xlgBqDHHhflmRzZ/WrKF7KIKp8ewKKjRxo3e+PBADuaVcMmoHny4/jB5JZX1tp81sQ/Xju9F94hAPkrL5PHPtlNdown0s/CHGYOJDPKjT1wI0cH+rD2Qx+l9Y1ptCGBH0pVeCOH1rn7tJ9YeyMfXovjojjMY1av+DELl1moyT5ThY1H8uPc46zPyGdQ9jCHdwxnYPYw/LtrMj+Y0eY7GJUVzvKSC6UO7M+y0cJ7/anetXqFgNNecOiSe99cfdhpfj8ggpg+LZ9vRIsID/fCxwM5jxVw2KpF7pjY+9osrksCFEF7viWXbeX3VAaYPjWf+DfXymVsOHC9hzuJ0nrxsBAG+FixK4e9rITzQD3/f2i2rv96ezbItWRSWWTl/eHcuH52IxaIot1bzw57jBPhZ+G5XLntyTlJmrWbdgVODsvr7WLDW1KC10Z598yPTm/2+ZSwUIYTXO82se+4d0/zepn1iQ+wTbDRm6tB4pjoZmiDQz8e+/KwBRs/RiqpqPt54hN4xwcSEBDCgWyil1mreX3eIvy7bwYmSylYfSlcSuBDCa1wxJpE9OSf5TQecLDrA14drxtWeNjI0wJe+cUad+P7jJxkT0rpt9CWBCyG8RligH0/+coSnw2iSgfFhzBgWj79P6zdhlAQuhBBtKDEqmNeub159fWNkLBQhhPBSksCFEMJLtagKRSmVARQD1UCVs2YuQggh2kZr1IGfo7U+3grHEUII0QRShSKEEF6qpQlcA18qpTYopW5ztoFS6jalVJpSKi03N7eFpxNCCGHT0gQ+UWs9Gjgf+J1SalLdDbTW87XWqVrr1Li4uBaeTgghhE2LErjW+oj5bw6wBBjXGkEJIYRoXLMHs1JKhQAWrXWx+fwr4HGt9RcN7JMLHGzWCSEW8Labpd4Ws7fFC94Xs7fFCxJze2gs3t5a63pVGC1phRIPLDHnpvMF3m0oeQM4C8BdSqk0b2um6G0xe1u84H0xe1u8IDG3h+bG2+wErrXeD4xs7v5CCCFaRpoRCiGEl/KmBD7f0wE0g7fF7G3xgvfF7G3xgsTcHpoVb7vOyCOEEKL1eFMJXAghhANJ4EII4a201s16AD2BFcB2YBtwj7k8GqNN+B7z3yhz+UwgHdgCrAZGOhzrPGAXsBeY08A5vwAKgM/qLH/H3H8rsBDwc7H/mUARUAkUAveZyx8CTgIVQB4wwo2YFwI5wNZGrpPT9wa8AWw2j78ICHVxjTMAK8aIj47XeJcZbzHwHdC7jeNVwBPAbmAHcLeL/ZcApUA5cAKY7RDzIfPaFwNnt8M1ngJsND8XbwO+Lq7xMfNalgNrAD8z3hXm56LYfM83u4oXF9+HJsZ7p7lMA7EN7O/qcxxtxlZhxv1RQ9e4NWJ2WP8P4GQDuSID55/jr4AsM94dwLttfI1XAZvMx1Hgvy72d5pTgMnmNbcd4y8NfTbb+tGSBJ4AjDafh2F8sYcCz9guGDAHeNrhQ2dL5ucDa83nPsA+oC/gj5HUhro457nAL6ifwC/ASDAKeA/4jYv9P3GI7Q0g24z5PeBhc/kSYEdDMZuvJwGjaSC5NPTegHCH7Z5z8aVIAG40/z1Z5xrPB4LNa7wc+KCN470Z+BdG5y2Abi6OMdM8jwI+crjGi8wvhAL+CRxty2uM8evyMDDQ3O5x4BYX1/guM64wjMT4mHmNvwCeNq/xP4B8MyZnn2On34cmXuNRQBJGsmsogbv6HL8OHAGizJhfauS71+KYzfWpwL9xncAb+hzPBX42r/nTQLe2jtdhu8XADS5idppTMBL4Z8728cSj9Q4ES4FpGF/SBIcLvsvJtlHAEfP5GcByh3UPAg82cJ4GLyAwG3jCyXKF0dPJ1+G8OU5ingaUNRSzw7IkGk4ujb43M65XgQcaub4nG7jGGcCPbRkvsA7o38TPxGzzSzYN45fTbxxirrS9h7aIGYgD9jksPwv43I2Yt2CUAncBTwKvmPHuxyjNWRqKt+73oZmfiQxcJPBGPsf5wO/d/e61RswYyXKFeT6nCbyRz/E/gVntFa/DsnCMX4jhbsRszyl0sATeKnXgSqkkjNLDWiBea51lrjqG0WOzrluA/5nPe2CUlGwyzWXNicMPuB6j5FRXDFCgta5yWBbpJOZLXBzeMWZ3NfjelFJvYlyjwcBLjRxL4foaJziJrbXj7QdcbY4s+T+l1IAGgzX+L24BIsyYQzCSoy1mRf3/59aM+Tjgq5Sy9W67AuMneEMx9wcGYVS3xAN/A4ZgVMP0wfjJXtNYvHW+D+7G666GPsdhQLxS6keMX5LOjtvaMd8JfOLweWxMrc+xeZyBGL/Q+imlzmvjeG0uBb7RWhc1GKzznHKGUmqz+T0Y1tD+ba3FEzoopUIxforcq7UuMrvWA6C11kopXWf7czD+Uya29NxOvAJ8r7Ve1dBGZsyvAcccY1ZKXYfxc7C8PWLWWt+slPLBSN5XA282EG8gTq4xRpWFD8ZP0baMNwAo11qnKqUuw6gXPKuB7edjlIJ/4+JzUWvj1o7ZPMevgOeVUgHAlxj1r06Z1/gnjJLbcjO+GRj1nFMwfkG8rJRaZb4fp/HW/T60xntpJOa6n+MBGKXERGCfUipSa11gbt+qMSulTgOuNM/nbrx1P8e+DjEfB15XSo3QWhe08TW+BljgxnZ1c8pGjHFJTiqlLgD+a8bvES0qgZt/nRYD72itPzYXZyulEsz1CRg/72zbJ2NctEu01nnm4iPULhklAkeUUuOVUpvMx8VuxPIIRsK4z2HZcnP/BRg3JyOVUoFmzCswbprYYr4K42bmLDdidhVDT4eY73D13hz30VpXA+8DlyulfBz2f9w8pu0aV9W9xkqpqcAjQIbWuqKN480EbOdfAiSbx3C8xrbjPoZRh/iMQ8wlwAhzfQLGjbojbRmz1vonrfVZWutxwPcY1Tn1Yjav8SaMXwa2X2DZwB3me+5urjsADHYVr7PvQ3M+E07es7uf4xLgO621FaMQUoaZXNoo5lFAf2CvMqZXDFZK7W3K5xij2ucTjMGcjpn/RwPa8horpWIxRk5d5uIa25bVyyla6yKt9Unz+eeAn3k8z2hu3QvGT6F/AS/UWT6X2jcxnzGf98KoQzyzzva+GPWLfTh1w2FYA+edTP2bmLMw7lYHNRLzRxhf5BeAecBvzeVvY3wxBrgTs8Pxkmi4ftbpezOvXX+H6/gs8GxD1xiH+kXzGv8D40bN3LaO11z3FPBrh/+D9S6OYfsD+FKd5YupfRMzqx1i7mb+GwB8A0xxcY1XY7RICHJYPhejRcqj5mfiZYwkMNJZvLj4PjQlXodtMmj4Jqarz/FHwAbz+eMYN2RjXF3j1ozZ3M7VTcyGPscLMb5/czB+iR7GKBy0WbwYf5jfbuQYTnMKxh9zWwfIcRgtq1RDx2rLR/N3NH7WaIzmPpvMxwXmB+YbjGaEXwPR5vYLMG4a2LZNczjWBRh/efcBDzVwzlVALkbJIhOYYS6vMve1Hdtp0x7gKjPmCoyfxJvNc39nLrM1y/ufGzG/h9H8yWrGUq+Fg6v3hvHL50eMOuGtGE2W6t1McbjGlQ7/vmNe43zzfRebx/mkreI1l0dilFi2YFQ1jHSxf5UZa5n5yHL4XBw238NJzGTaxjHPxSid7sL4ud3Q57jCIeZ/m/GuwijV2pq4XecqXlx8H5oY793m+6zC+IOyoImf4xiMhGJrRnhLQ9e4NWKus42rBN7Q5/gbM7aTGM0Df9XW8QIrgfMayW9OcwpGnf8285qvwUXBo70e0pVeCCG8lPTEFEIILyUJXAghvJQkcCGE8FKSwIUQwktJAhdCCC8lCVx0WkqparNzxjaz6/PvlVINfuaVUklKqWvbK0YhWkISuOjMyrTWKVrrYRiDJ52P0XO1IUmAJHDhFaQduOi0lFIntdahDq/7Ausxum33xuiwE2KuvlNrvVoptQZjAKsDGD0E/4HRC3UyRo/Of2qtX2u3NyFEAySBi06rbgI3lxVgjDhYDNRorcuVMbLie9oYqGsycL/W+iJz+9swuuT/1RwU60fgSq31gXZ8K0I41eLRCIXwUn4YowumYIxSONDFdtOBZKXUFebrCIwxcySBC4+TBC66DLMKpRpjsK1HMEbDG4lxL6jc1W7AXVrr5e0SpBBNIDcxRZeglIrDGLnvZW3UG0ZgjIhYgzFgv4+5aTHGxAg2y4HfmMOYopQaqJQKQYgOQErgojMLUkptwqguqcK4afmcue4VYLFS6gaM2VZKzOXpQLVSajPwFvAiRsuUjcqYgSAXYzYXITxObmIKIYSXkioUIYTwUpLAhRDCS0kCF0IILyUJXAghvJQkcCGE8FKSwIUQwktJAhdCCC/1/9E0Sea+hLiZAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[100:].plot(y='Energy intensity estimate')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:02.041585Z",
     "iopub.status.busy": "2022-12-08T20:46:02.040742Z",
     "iopub.status.idle": "2022-12-08T20:46:02.052835Z",
     "shell.execute_reply": "2022-12-08T20:46:02.051012Z",
     "shell.execute_reply.started": "2022-12-08T20:46:02.041544Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1452033144.0"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Cumulative renewable energy purchases\"].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:02.055688Z",
     "iopub.status.busy": "2022-12-08T20:46:02.055139Z",
     "iopub.status.idle": "2022-12-08T20:46:02.340137Z",
     "shell.execute_reply": "2022-12-08T20:46:02.339199Z",
     "shell.execute_reply.started": "2022-12-08T20:46:02.055640Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(y='Cumulative renewable energy purchases', kind='area')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:02.342060Z",
     "iopub.status.busy": "2022-12-08T20:46:02.341673Z",
     "iopub.status.idle": "2022-12-08T20:46:02.349097Z",
     "shell.execute_reply": "2022-12-08T20:46:02.347657Z",
     "shell.execute_reply.started": "2022-12-08T20:46:02.342029Z"
    }
   },
   "outputs": [],
   "source": [
    "df['ren_share'] = df['Cumulative renewable energy purchases']  / df['Cumulative energy use estimate']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:02.351601Z",
     "iopub.status.busy": "2022-12-08T20:46:02.350868Z",
     "iopub.status.idle": "2022-12-08T20:46:02.635914Z",
     "shell.execute_reply": "2022-12-08T20:46:02.634654Z",
     "shell.execute_reply.started": "2022-12-08T20:46:02.351561Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[5:].plot(y='ren_share', kind='area')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:02.638397Z",
     "iopub.status.busy": "2022-12-08T20:46:02.637886Z",
     "iopub.status.idle": "2022-12-08T20:46:02.720158Z",
     "shell.execute_reply": "2022-12-08T20:46:02.719261Z",
     "shell.execute_reply.started": "2022-12-08T20:46:02.638345Z"
    }
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>Energy used to seal data estimate</th>\n",
       "      <th>Energy used to seal data upper bound</th>\n",
       "      <th>Cumulative energy use lower bound</th>\n",
       "      <th>Cumulative energy use estimate</th>\n",
       "      <th>Cumulative energy use upper bound</th>\n",
       "      <th>Energy used to store data lower bound</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "      <th>ren_share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>784.000000</td>\n",
       "      <td>7.840000e+02</td>\n",
       "      <td>7.840000e+02</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>7.840000e+02</td>\n",
       "      <td>7.840000e+02</td>\n",
       "      <td>7.840000e+02</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "      <td>784.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>12.323393</td>\n",
       "      <td>2.896389e+07</td>\n",
       "      <td>8.828581e+08</td>\n",
       "      <td>6.816098</td>\n",
       "      <td>47.708476</td>\n",
       "      <td>103.214836</td>\n",
       "      <td>22307.951987</td>\n",
       "      <td>127547.317417</td>\n",
       "      <td>332704.059650</td>\n",
       "      <td>7786.073831</td>\n",
       "      <td>44270.442189</td>\n",
       "      <td>72566.138596</td>\n",
       "      <td>1.634301e+08</td>\n",
       "      <td>9.978036e+08</td>\n",
       "      <td>2.448735e+09</td>\n",
       "      <td>11118.970225</td>\n",
       "      <td>36969.887376</td>\n",
       "      <td>99819.384538</td>\n",
       "      <td>2021.202806</td>\n",
       "      <td>1.197482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.314818</td>\n",
       "      <td>1.395735e+07</td>\n",
       "      <td>5.526074e+08</td>\n",
       "      <td>54.276706</td>\n",
       "      <td>410.607117</td>\n",
       "      <td>827.378599</td>\n",
       "      <td>9766.188277</td>\n",
       "      <td>50683.267537</td>\n",
       "      <td>144468.339031</td>\n",
       "      <td>3752.014906</td>\n",
       "      <td>21333.391206</td>\n",
       "      <td>34968.745429</td>\n",
       "      <td>1.323638e+08</td>\n",
       "      <td>7.679557e+08</td>\n",
       "      <td>1.975944e+09</td>\n",
       "      <td>7502.171475</td>\n",
       "      <td>24944.255529</td>\n",
       "      <td>67349.954556</td>\n",
       "      <td>0.702808</td>\n",
       "      <td>4.778555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000535</td>\n",
       "      <td>2.053024e+06</td>\n",
       "      <td>1.573466e+07</td>\n",
       "      <td>1.342260</td>\n",
       "      <td>6.298506</td>\n",
       "      <td>19.773216</td>\n",
       "      <td>651.804634</td>\n",
       "      <td>4929.158175</td>\n",
       "      <td>9935.604259</td>\n",
       "      <td>551.893912</td>\n",
       "      <td>3137.985593</td>\n",
       "      <td>5143.646330</td>\n",
       "      <td>1.564318e+04</td>\n",
       "      <td>1.182999e+05</td>\n",
       "      <td>2.384543e+05</td>\n",
       "      <td>0.482896</td>\n",
       "      <td>1.605601</td>\n",
       "      <td>4.335152</td>\n",
       "      <td>2020.000000</td>\n",
       "      <td>0.410680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.772380</td>\n",
       "      <td>1.765826e+07</td>\n",
       "      <td>3.172574e+08</td>\n",
       "      <td>1.736222</td>\n",
       "      <td>9.278855</td>\n",
       "      <td>25.778658</td>\n",
       "      <td>14296.304280</td>\n",
       "      <td>95153.889037</td>\n",
       "      <td>215414.372125</td>\n",
       "      <td>4746.894528</td>\n",
       "      <td>26990.126780</td>\n",
       "      <td>44241.014628</td>\n",
       "      <td>3.506156e+07</td>\n",
       "      <td>2.395145e+08</td>\n",
       "      <td>5.298815e+08</td>\n",
       "      <td>3403.687944</td>\n",
       "      <td>11317.051620</td>\n",
       "      <td>30556.250168</td>\n",
       "      <td>2021.000000</td>\n",
       "      <td>0.707985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>13.258516</td>\n",
       "      <td>2.671651e+07</td>\n",
       "      <td>1.111867e+09</td>\n",
       "      <td>2.890687</td>\n",
       "      <td>18.012463</td>\n",
       "      <td>43.376990</td>\n",
       "      <td>26957.239715</td>\n",
       "      <td>143085.935100</td>\n",
       "      <td>400413.281000</td>\n",
       "      <td>7181.932756</td>\n",
       "      <td>40835.387095</td>\n",
       "      <td>66935.549165</td>\n",
       "      <td>1.422385e+08</td>\n",
       "      <td>9.252870e+08</td>\n",
       "      <td>2.141360e+09</td>\n",
       "      <td>11962.698660</td>\n",
       "      <td>39775.232175</td>\n",
       "      <td>107393.867750</td>\n",
       "      <td>2021.000000</td>\n",
       "      <td>0.963523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>20.024617</td>\n",
       "      <td>3.664840e+07</td>\n",
       "      <td>1.387952e+09</td>\n",
       "      <td>4.070181</td>\n",
       "      <td>26.935415</td>\n",
       "      <td>61.356853</td>\n",
       "      <td>29812.862725</td>\n",
       "      <td>166143.901575</td>\n",
       "      <td>440678.766650</td>\n",
       "      <td>9851.822888</td>\n",
       "      <td>56015.979950</td>\n",
       "      <td>91818.901357</td>\n",
       "      <td>2.757045e+08</td>\n",
       "      <td>1.666040e+09</td>\n",
       "      <td>4.127909e+09</td>\n",
       "      <td>18067.517245</td>\n",
       "      <td>60073.375878</td>\n",
       "      <td>162199.233800</td>\n",
       "      <td>2022.000000</td>\n",
       "      <td>1.283973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>24.378111</td>\n",
       "      <td>6.615507e+07</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1404.098113</td>\n",
       "      <td>10618.245610</td>\n",
       "      <td>21402.982540</td>\n",
       "      <td>34539.414020</td>\n",
       "      <td>218115.448200</td>\n",
       "      <td>518189.013900</td>\n",
       "      <td>17783.806460</td>\n",
       "      <td>101116.042900</td>\n",
       "      <td>165744.917400</td>\n",
       "      <td>4.197450e+08</td>\n",
       "      <td>2.399932e+09</td>\n",
       "      <td>6.260157e+09</td>\n",
       "      <td>21995.524110</td>\n",
       "      <td>73133.755430</td>\n",
       "      <td>197462.501900</td>\n",
       "      <td>2022.000000</td>\n",
       "      <td>133.006511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Data storage capacity  Data storage capacity added per day  \\\n",
       "count             784.000000                         7.840000e+02   \n",
       "mean               12.323393                         2.896389e+07   \n",
       "std                 8.314818                         1.395735e+07   \n",
       "min                 0.000535                         2.053024e+06   \n",
       "25%                 3.772380                         1.765826e+07   \n",
       "50%                13.258516                         2.671651e+07   \n",
       "75%                20.024617                         3.664840e+07   \n",
       "max                24.378111                         6.615507e+07   \n",
       "\n",
       "       Cumulative renewable energy purchases  Energy intensity lower bound  \\\n",
       "count                           7.840000e+02                    784.000000   \n",
       "mean                            8.828581e+08                      6.816098   \n",
       "std                             5.526074e+08                     54.276706   \n",
       "min                             1.573466e+07                      1.342260   \n",
       "25%                             3.172574e+08                      1.736222   \n",
       "50%                             1.111867e+09                      2.890687   \n",
       "75%                             1.387952e+09                      4.070181   \n",
       "max                             1.452033e+09                   1404.098113   \n",
       "\n",
       "       Energy intensity estimate  Energy intensity upper bound  \\\n",
       "count                 784.000000                    784.000000   \n",
       "mean                   47.708476                    103.214836   \n",
       "std                   410.607117                    827.378599   \n",
       "min                     6.298506                     19.773216   \n",
       "25%                     9.278855                     25.778658   \n",
       "50%                    18.012463                     43.376990   \n",
       "75%                    26.935415                     61.356853   \n",
       "max                 10618.245610                  21402.982540   \n",
       "\n",
       "       Energy consumption rate lower bound  Energy consumption rate estimate  \\\n",
       "count                           784.000000                        784.000000   \n",
       "mean                          22307.951987                     127547.317417   \n",
       "std                            9766.188277                      50683.267537   \n",
       "min                             651.804634                       4929.158175   \n",
       "25%                           14296.304280                      95153.889037   \n",
       "50%                           26957.239715                     143085.935100   \n",
       "75%                           29812.862725                     166143.901575   \n",
       "max                           34539.414020                     218115.448200   \n",
       "\n",
       "       Energy consumption rate upper bound  \\\n",
       "count                           784.000000   \n",
       "mean                         332704.059650   \n",
       "std                          144468.339031   \n",
       "min                            9935.604259   \n",
       "25%                          215414.372125   \n",
       "50%                          400413.281000   \n",
       "75%                          440678.766650   \n",
       "max                          518189.013900   \n",
       "\n",
       "       Energy used to seal data lower bound  \\\n",
       "count                            784.000000   \n",
       "mean                            7786.073831   \n",
       "std                             3752.014906   \n",
       "min                              551.893912   \n",
       "25%                             4746.894528   \n",
       "50%                             7181.932756   \n",
       "75%                             9851.822888   \n",
       "max                            17783.806460   \n",
       "\n",
       "       Energy used to seal data estimate  \\\n",
       "count                         784.000000   \n",
       "mean                        44270.442189   \n",
       "std                         21333.391206   \n",
       "min                          3137.985593   \n",
       "25%                         26990.126780   \n",
       "50%                         40835.387095   \n",
       "75%                         56015.979950   \n",
       "max                        101116.042900   \n",
       "\n",
       "       Energy used to seal data upper bound  \\\n",
       "count                            784.000000   \n",
       "mean                           72566.138596   \n",
       "std                            34968.745429   \n",
       "min                             5143.646330   \n",
       "25%                            44241.014628   \n",
       "50%                            66935.549165   \n",
       "75%                            91818.901357   \n",
       "max                           165744.917400   \n",
       "\n",
       "       Cumulative energy use lower bound  Cumulative energy use estimate  \\\n",
       "count                       7.840000e+02                    7.840000e+02   \n",
       "mean                        1.634301e+08                    9.978036e+08   \n",
       "std                         1.323638e+08                    7.679557e+08   \n",
       "min                         1.564318e+04                    1.182999e+05   \n",
       "25%                         3.506156e+07                    2.395145e+08   \n",
       "50%                         1.422385e+08                    9.252870e+08   \n",
       "75%                         2.757045e+08                    1.666040e+09   \n",
       "max                         4.197450e+08                    2.399932e+09   \n",
       "\n",
       "       Cumulative energy use upper bound  \\\n",
       "count                       7.840000e+02   \n",
       "mean                        2.448735e+09   \n",
       "std                         1.975944e+09   \n",
       "min                         2.384543e+05   \n",
       "25%                         5.298815e+08   \n",
       "50%                         2.141360e+09   \n",
       "75%                         4.127909e+09   \n",
       "max                         6.260157e+09   \n",
       "\n",
       "       Energy used to store data lower bound  \\\n",
       "count                             784.000000   \n",
       "mean                            11118.970225   \n",
       "std                              7502.171475   \n",
       "min                                 0.482896   \n",
       "25%                              3403.687944   \n",
       "50%                             11962.698660   \n",
       "75%                             18067.517245   \n",
       "max                             21995.524110   \n",
       "\n",
       "       Energy used to store data estimate  \\\n",
       "count                          784.000000   \n",
       "mean                         36969.887376   \n",
       "std                          24944.255529   \n",
       "min                              1.605601   \n",
       "25%                          11317.051620   \n",
       "50%                          39775.232175   \n",
       "75%                          60073.375878   \n",
       "max                          73133.755430   \n",
       "\n",
       "       Energy used to store data upper bound         year   ren_share  \n",
       "count                             784.000000   784.000000  784.000000  \n",
       "mean                            99819.384538  2021.202806    1.197482  \n",
       "std                             67349.954556     0.702808    4.778555  \n",
       "min                                 4.335152  2020.000000    0.410680  \n",
       "25%                             30556.250168  2021.000000    0.707985  \n",
       "50%                            107393.867750  2021.000000    0.963523  \n",
       "75%                            162199.233800  2022.000000    1.283973  \n",
       "max                            197462.501900  2022.000000  133.006511  "
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:02.721439Z",
     "iopub.status.busy": "2022-12-08T20:46:02.721111Z",
     "iopub.status.idle": "2022-12-08T20:46:02.734022Z",
     "shell.execute_reply": "2022-12-08T20:46:02.732956Z",
     "shell.execute_reply.started": "2022-12-08T20:46:02.721409Z"
    }
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"/kaggle/input/filecoinoceanchallenge/FIL-USD-FIL-USD.csv\",index_col='Date', parse_dates=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:02.739700Z",
     "iopub.status.busy": "2022-12-08T20:46:02.738276Z",
     "iopub.status.idle": "2022-12-08T20:46:02.778532Z",
     "shell.execute_reply": "2022-12-08T20:46:02.776752Z",
     "shell.execute_reply.started": "2022-12-08T20:46:02.739658Z"
    }
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>Energy used to seal data estimate</th>\n",
       "      <th>Energy used to seal data upper bound</th>\n",
       "      <th>Cumulative energy use lower bound</th>\n",
       "      <th>Cumulative energy use estimate</th>\n",
       "      <th>Cumulative energy use upper bound</th>\n",
       "      <th>Energy used to store data lower bound</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "      <th>ren_share</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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>2020-08-24</th>\n",
       "      <td>0.000535</td>\n",
       "      <td>2053024</td>\n",
       "      <td>1.573466e+07</td>\n",
       "      <td>1404.098113</td>\n",
       "      <td>10618.245610</td>\n",
       "      <td>21402.982540</td>\n",
       "      <td>651.804634</td>\n",
       "      <td>4929.158175</td>\n",
       "      <td>9935.604259</td>\n",
       "      <td>551.893912</td>\n",
       "      <td>3137.985593</td>\n",
       "      <td>5143.64633</td>\n",
       "      <td>1.564318e+04</td>\n",
       "      <td>1.182999e+05</td>\n",
       "      <td>2.384543e+05</td>\n",
       "      <td>0.482896</td>\n",
       "      <td>1.605601</td>\n",
       "      <td>4.335152</td>\n",
       "      <td>2020</td>\n",
       "      <td>133.006511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-25</th>\n",
       "      <td>0.009919</td>\n",
       "      <td>13984256</td>\n",
       "      <td>1.602074e+07</td>\n",
       "      <td>516.832219</td>\n",
       "      <td>3906.016457</td>\n",
       "      <td>7877.754829</td>\n",
       "      <td>4446.472725</td>\n",
       "      <td>33604.707650</td>\n",
       "      <td>67774.841940</td>\n",
       "      <td>3759.247698</td>\n",
       "      <td>21374.515770</td>\n",
       "      <td>35036.15498</td>\n",
       "      <td>1.223576e+05</td>\n",
       "      <td>9.248137e+05</td>\n",
       "      <td>1.865049e+06</td>\n",
       "      <td>8.949526</td>\n",
       "      <td>29.756621</td>\n",
       "      <td>80.343431</td>\n",
       "      <td>2020</td>\n",
       "      <td>17.323212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-26</th>\n",
       "      <td>0.024217</td>\n",
       "      <td>13212864</td>\n",
       "      <td>1.630683e+07</td>\n",
       "      <td>200.762976</td>\n",
       "      <td>1514.930303</td>\n",
       "      <td>3059.685608</td>\n",
       "      <td>4217.004054</td>\n",
       "      <td>31820.943110</td>\n",
       "      <td>64268.357070</td>\n",
       "      <td>3551.882100</td>\n",
       "      <td>20195.466240</td>\n",
       "      <td>33103.50947</td>\n",
       "      <td>2.235649e+05</td>\n",
       "      <td>1.688517e+06</td>\n",
       "      <td>3.407488e+06</td>\n",
       "      <td>21.850149</td>\n",
       "      <td>72.650391</td>\n",
       "      <td>196.157408</td>\n",
       "      <td>2020</td>\n",
       "      <td>9.657485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-27</th>\n",
       "      <td>0.039043</td>\n",
       "      <td>14277536</td>\n",
       "      <td>1.659291e+07</td>\n",
       "      <td>134.966149</td>\n",
       "      <td>1017.172660</td>\n",
       "      <td>2056.697582</td>\n",
       "      <td>4570.510617</td>\n",
       "      <td>34445.662720</td>\n",
       "      <td>69648.265260</td>\n",
       "      <td>3838.087228</td>\n",
       "      <td>21822.785450</td>\n",
       "      <td>35770.93869</td>\n",
       "      <td>3.332562e+05</td>\n",
       "      <td>2.515214e+06</td>\n",
       "      <td>5.079045e+06</td>\n",
       "      <td>35.226855</td>\n",
       "      <td>117.127110</td>\n",
       "      <td>316.245378</td>\n",
       "      <td>2020</td>\n",
       "      <td>6.597019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-28</th>\n",
       "      <td>0.055220</td>\n",
       "      <td>16174560</td>\n",
       "      <td>1.687900e+07</td>\n",
       "      <td>108.350558</td>\n",
       "      <td>815.823835</td>\n",
       "      <td>1650.977121</td>\n",
       "      <td>5189.484114</td>\n",
       "      <td>39074.139640</td>\n",
       "      <td>79074.069440</td>\n",
       "      <td>4348.045219</td>\n",
       "      <td>24722.329720</td>\n",
       "      <td>40523.74262</td>\n",
       "      <td>4.578028e+05</td>\n",
       "      <td>3.452994e+06</td>\n",
       "      <td>6.976821e+06</td>\n",
       "      <td>49.822674</td>\n",
       "      <td>165.657306</td>\n",
       "      <td>447.277813</td>\n",
       "      <td>2020</td>\n",
       "      <td>4.888221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-12</th>\n",
       "      <td>24.327384</td>\n",
       "      <td>11987424</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.407692</td>\n",
       "      <td>6.793503</td>\n",
       "      <td>20.770641</td>\n",
       "      <td>29703.212830</td>\n",
       "      <td>143347.270200</td>\n",
       "      <td>438273.868800</td>\n",
       "      <td>3222.459320</td>\n",
       "      <td>18322.417960</td>\n",
       "      <td>30033.29209</td>\n",
       "      <td>4.169129e+08</td>\n",
       "      <td>2.386328e+09</td>\n",
       "      <td>6.218382e+09</td>\n",
       "      <td>21949.754940</td>\n",
       "      <td>72981.575780</td>\n",
       "      <td>197051.614000</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.608480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-13</th>\n",
       "      <td>24.340873</td>\n",
       "      <td>12611296</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.416966</td>\n",
       "      <td>6.863659</td>\n",
       "      <td>20.912006</td>\n",
       "      <td>29915.470500</td>\n",
       "      <td>144907.904400</td>\n",
       "      <td>441501.417100</td>\n",
       "      <td>3390.168591</td>\n",
       "      <td>19275.987600</td>\n",
       "      <td>31596.34100</td>\n",
       "      <td>4.176309e+08</td>\n",
       "      <td>2.389806e+09</td>\n",
       "      <td>6.228978e+09</td>\n",
       "      <td>21961.925060</td>\n",
       "      <td>73022.040660</td>\n",
       "      <td>197160.869900</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.607595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-14</th>\n",
       "      <td>24.353995</td>\n",
       "      <td>12329664</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.412635</td>\n",
       "      <td>6.830892</td>\n",
       "      <td>20.845981</td>\n",
       "      <td>29840.106090</td>\n",
       "      <td>144293.880100</td>\n",
       "      <td>440344.754700</td>\n",
       "      <td>3314.460276</td>\n",
       "      <td>18845.521530</td>\n",
       "      <td>30890.74019</td>\n",
       "      <td>4.183471e+08</td>\n",
       "      <td>2.393269e+09</td>\n",
       "      <td>6.239546e+09</td>\n",
       "      <td>21973.765220</td>\n",
       "      <td>73061.408490</td>\n",
       "      <td>197267.163800</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.606715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-15</th>\n",
       "      <td>24.367511</td>\n",
       "      <td>12360032</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.412988</td>\n",
       "      <td>6.833563</td>\n",
       "      <td>20.851364</td>\n",
       "      <td>29864.128600</td>\n",
       "      <td>144430.411500</td>\n",
       "      <td>440702.883800</td>\n",
       "      <td>3322.623802</td>\n",
       "      <td>18891.938110</td>\n",
       "      <td>30966.82417</td>\n",
       "      <td>4.190638e+08</td>\n",
       "      <td>2.396735e+09</td>\n",
       "      <td>6.250123e+09</td>\n",
       "      <td>21985.959760</td>\n",
       "      <td>73101.954550</td>\n",
       "      <td>197376.638900</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.605838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-16</th>\n",
       "      <td>24.378111</td>\n",
       "      <td>7650816</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.342260</td>\n",
       "      <td>6.298506</td>\n",
       "      <td>19.773216</td>\n",
       "      <td>28381.615430</td>\n",
       "      <td>133179.643100</td>\n",
       "      <td>418097.552700</td>\n",
       "      <td>2056.692357</td>\n",
       "      <td>11694.042730</td>\n",
       "      <td>19168.35441</td>\n",
       "      <td>4.197450e+08</td>\n",
       "      <td>2.399932e+09</td>\n",
       "      <td>6.260157e+09</td>\n",
       "      <td>21995.524110</td>\n",
       "      <td>73133.755430</td>\n",
       "      <td>197462.501900</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.605031</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>784 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Data storage capacity  Data storage capacity added per day  \\\n",
       "Date                                                                     \n",
       "2020-08-24               0.000535                              2053024   \n",
       "2020-08-25               0.009919                             13984256   \n",
       "2020-08-26               0.024217                             13212864   \n",
       "2020-08-27               0.039043                             14277536   \n",
       "2020-08-28               0.055220                             16174560   \n",
       "...                           ...                                  ...   \n",
       "2022-10-12              24.327384                             11987424   \n",
       "2022-10-13              24.340873                             12611296   \n",
       "2022-10-14              24.353995                             12329664   \n",
       "2022-10-15              24.367511                             12360032   \n",
       "2022-10-16              24.378111                              7650816   \n",
       "\n",
       "            Cumulative renewable energy purchases  \\\n",
       "Date                                                \n",
       "2020-08-24                           1.573466e+07   \n",
       "2020-08-25                           1.602074e+07   \n",
       "2020-08-26                           1.630683e+07   \n",
       "2020-08-27                           1.659291e+07   \n",
       "2020-08-28                           1.687900e+07   \n",
       "...                                           ...   \n",
       "2022-10-12                           1.452033e+09   \n",
       "2022-10-13                           1.452033e+09   \n",
       "2022-10-14                           1.452033e+09   \n",
       "2022-10-15                           1.452033e+09   \n",
       "2022-10-16                           1.452033e+09   \n",
       "\n",
       "            Energy intensity lower bound  Energy intensity estimate  \\\n",
       "Date                                                                  \n",
       "2020-08-24                   1404.098113               10618.245610   \n",
       "2020-08-25                    516.832219                3906.016457   \n",
       "2020-08-26                    200.762976                1514.930303   \n",
       "2020-08-27                    134.966149                1017.172660   \n",
       "2020-08-28                    108.350558                 815.823835   \n",
       "...                                  ...                        ...   \n",
       "2022-10-12                      1.407692                   6.793503   \n",
       "2022-10-13                      1.416966                   6.863659   \n",
       "2022-10-14                      1.412635                   6.830892   \n",
       "2022-10-15                      1.412988                   6.833563   \n",
       "2022-10-16                      1.342260                   6.298506   \n",
       "\n",
       "            Energy intensity upper bound  Energy consumption rate lower bound  \\\n",
       "Date                                                                            \n",
       "2020-08-24                  21402.982540                           651.804634   \n",
       "2020-08-25                   7877.754829                          4446.472725   \n",
       "2020-08-26                   3059.685608                          4217.004054   \n",
       "2020-08-27                   2056.697582                          4570.510617   \n",
       "2020-08-28                   1650.977121                          5189.484114   \n",
       "...                                  ...                                  ...   \n",
       "2022-10-12                     20.770641                         29703.212830   \n",
       "2022-10-13                     20.912006                         29915.470500   \n",
       "2022-10-14                     20.845981                         29840.106090   \n",
       "2022-10-15                     20.851364                         29864.128600   \n",
       "2022-10-16                     19.773216                         28381.615430   \n",
       "\n",
       "            Energy consumption rate estimate  \\\n",
       "Date                                           \n",
       "2020-08-24                       4929.158175   \n",
       "2020-08-25                      33604.707650   \n",
       "2020-08-26                      31820.943110   \n",
       "2020-08-27                      34445.662720   \n",
       "2020-08-28                      39074.139640   \n",
       "...                                      ...   \n",
       "2022-10-12                     143347.270200   \n",
       "2022-10-13                     144907.904400   \n",
       "2022-10-14                     144293.880100   \n",
       "2022-10-15                     144430.411500   \n",
       "2022-10-16                     133179.643100   \n",
       "\n",
       "            Energy consumption rate upper bound  \\\n",
       "Date                                              \n",
       "2020-08-24                          9935.604259   \n",
       "2020-08-25                         67774.841940   \n",
       "2020-08-26                         64268.357070   \n",
       "2020-08-27                         69648.265260   \n",
       "2020-08-28                         79074.069440   \n",
       "...                                         ...   \n",
       "2022-10-12                        438273.868800   \n",
       "2022-10-13                        441501.417100   \n",
       "2022-10-14                        440344.754700   \n",
       "2022-10-15                        440702.883800   \n",
       "2022-10-16                        418097.552700   \n",
       "\n",
       "            Energy used to seal data lower bound  \\\n",
       "Date                                               \n",
       "2020-08-24                            551.893912   \n",
       "2020-08-25                           3759.247698   \n",
       "2020-08-26                           3551.882100   \n",
       "2020-08-27                           3838.087228   \n",
       "2020-08-28                           4348.045219   \n",
       "...                                          ...   \n",
       "2022-10-12                           3222.459320   \n",
       "2022-10-13                           3390.168591   \n",
       "2022-10-14                           3314.460276   \n",
       "2022-10-15                           3322.623802   \n",
       "2022-10-16                           2056.692357   \n",
       "\n",
       "            Energy used to seal data estimate  \\\n",
       "Date                                            \n",
       "2020-08-24                        3137.985593   \n",
       "2020-08-25                       21374.515770   \n",
       "2020-08-26                       20195.466240   \n",
       "2020-08-27                       21822.785450   \n",
       "2020-08-28                       24722.329720   \n",
       "...                                       ...   \n",
       "2022-10-12                       18322.417960   \n",
       "2022-10-13                       19275.987600   \n",
       "2022-10-14                       18845.521530   \n",
       "2022-10-15                       18891.938110   \n",
       "2022-10-16                       11694.042730   \n",
       "\n",
       "            Energy used to seal data upper bound  \\\n",
       "Date                                               \n",
       "2020-08-24                            5143.64633   \n",
       "2020-08-25                           35036.15498   \n",
       "2020-08-26                           33103.50947   \n",
       "2020-08-27                           35770.93869   \n",
       "2020-08-28                           40523.74262   \n",
       "...                                          ...   \n",
       "2022-10-12                           30033.29209   \n",
       "2022-10-13                           31596.34100   \n",
       "2022-10-14                           30890.74019   \n",
       "2022-10-15                           30966.82417   \n",
       "2022-10-16                           19168.35441   \n",
       "\n",
       "            Cumulative energy use lower bound  Cumulative energy use estimate  \\\n",
       "Date                                                                            \n",
       "2020-08-24                       1.564318e+04                    1.182999e+05   \n",
       "2020-08-25                       1.223576e+05                    9.248137e+05   \n",
       "2020-08-26                       2.235649e+05                    1.688517e+06   \n",
       "2020-08-27                       3.332562e+05                    2.515214e+06   \n",
       "2020-08-28                       4.578028e+05                    3.452994e+06   \n",
       "...                                       ...                             ...   \n",
       "2022-10-12                       4.169129e+08                    2.386328e+09   \n",
       "2022-10-13                       4.176309e+08                    2.389806e+09   \n",
       "2022-10-14                       4.183471e+08                    2.393269e+09   \n",
       "2022-10-15                       4.190638e+08                    2.396735e+09   \n",
       "2022-10-16                       4.197450e+08                    2.399932e+09   \n",
       "\n",
       "            Cumulative energy use upper bound  \\\n",
       "Date                                            \n",
       "2020-08-24                       2.384543e+05   \n",
       "2020-08-25                       1.865049e+06   \n",
       "2020-08-26                       3.407488e+06   \n",
       "2020-08-27                       5.079045e+06   \n",
       "2020-08-28                       6.976821e+06   \n",
       "...                                       ...   \n",
       "2022-10-12                       6.218382e+09   \n",
       "2022-10-13                       6.228978e+09   \n",
       "2022-10-14                       6.239546e+09   \n",
       "2022-10-15                       6.250123e+09   \n",
       "2022-10-16                       6.260157e+09   \n",
       "\n",
       "            Energy used to store data lower bound  \\\n",
       "Date                                                \n",
       "2020-08-24                               0.482896   \n",
       "2020-08-25                               8.949526   \n",
       "2020-08-26                              21.850149   \n",
       "2020-08-27                              35.226855   \n",
       "2020-08-28                              49.822674   \n",
       "...                                           ...   \n",
       "2022-10-12                           21949.754940   \n",
       "2022-10-13                           21961.925060   \n",
       "2022-10-14                           21973.765220   \n",
       "2022-10-15                           21985.959760   \n",
       "2022-10-16                           21995.524110   \n",
       "\n",
       "            Energy used to store data estimate  \\\n",
       "Date                                             \n",
       "2020-08-24                            1.605601   \n",
       "2020-08-25                           29.756621   \n",
       "2020-08-26                           72.650391   \n",
       "2020-08-27                          117.127110   \n",
       "2020-08-28                          165.657306   \n",
       "...                                        ...   \n",
       "2022-10-12                        72981.575780   \n",
       "2022-10-13                        73022.040660   \n",
       "2022-10-14                        73061.408490   \n",
       "2022-10-15                        73101.954550   \n",
       "2022-10-16                        73133.755430   \n",
       "\n",
       "            Energy used to store data upper bound  year   ren_share  \n",
       "Date                                                                 \n",
       "2020-08-24                               4.335152  2020  133.006511  \n",
       "2020-08-25                              80.343431  2020   17.323212  \n",
       "2020-08-26                             196.157408  2020    9.657485  \n",
       "2020-08-27                             316.245378  2020    6.597019  \n",
       "2020-08-28                             447.277813  2020    4.888221  \n",
       "...                                           ...   ...         ...  \n",
       "2022-10-12                          197051.614000  2022    0.608480  \n",
       "2022-10-13                          197160.869900  2022    0.607595  \n",
       "2022-10-14                          197267.163800  2022    0.606715  \n",
       "2022-10-15                          197376.638900  2022    0.605838  \n",
       "2022-10-16                          197462.501900  2022    0.605031  \n",
       "\n",
       "[784 rows x 20 columns]"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:02.781047Z",
     "iopub.status.busy": "2022-12-08T20:46:02.780483Z",
     "iopub.status.idle": "2022-12-08T20:46:02.806120Z",
     "shell.execute_reply": "2022-12-08T20:46:02.804760Z",
     "shell.execute_reply.started": "2022-12-08T20:46:02.781003Z"
    }
   },
   "outputs": [],
   "source": [
    "columns = data.columns\n",
    "\n",
    "for x in columns:\n",
    "    df[x] = data[\"2020-08-24\":'2022-10-16'][x].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T20:46:02.809021Z",
     "iopub.status.busy": "2022-12-08T20:46:02.808081Z",
     "iopub.status.idle": "2022-12-08T20:46:02.849700Z",
     "shell.execute_reply": "2022-12-08T20:46:02.848264Z",
     "shell.execute_reply.started": "2022-12-08T20:46:02.808971Z"
    }
   },
   "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>Data storage capacity</th>\n",
       "      <th>Data storage capacity added per day</th>\n",
       "      <th>Cumulative renewable energy purchases</th>\n",
       "      <th>Energy intensity lower bound</th>\n",
       "      <th>Energy intensity estimate</th>\n",
       "      <th>Energy intensity upper bound</th>\n",
       "      <th>Energy consumption rate lower bound</th>\n",
       "      <th>Energy consumption rate estimate</th>\n",
       "      <th>Energy consumption rate upper bound</th>\n",
       "      <th>Energy used to seal data lower bound</th>\n",
       "      <th>...</th>\n",
       "      <th>Energy used to store data estimate</th>\n",
       "      <th>Energy used to store data upper bound</th>\n",
       "      <th>year</th>\n",
       "      <th>ren_share</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <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>2020-08-24</th>\n",
       "      <td>0.000535</td>\n",
       "      <td>2053024</td>\n",
       "      <td>1.573466e+07</td>\n",
       "      <td>1404.098113</td>\n",
       "      <td>10618.245610</td>\n",
       "      <td>21402.982540</td>\n",
       "      <td>651.804634</td>\n",
       "      <td>4929.158175</td>\n",
       "      <td>9935.604259</td>\n",
       "      <td>551.893912</td>\n",
       "      <td>...</td>\n",
       "      <td>1.605601</td>\n",
       "      <td>4.335152</td>\n",
       "      <td>2020</td>\n",
       "      <td>133.006511</td>\n",
       "      <td>20.470207</td>\n",
       "      <td>23.807421</td>\n",
       "      <td>20.411312</td>\n",
       "      <td>22.020189</td>\n",
       "      <td>22.020189</td>\n",
       "      <td>16525999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-25</th>\n",
       "      <td>0.009919</td>\n",
       "      <td>13984256</td>\n",
       "      <td>1.602074e+07</td>\n",
       "      <td>516.832219</td>\n",
       "      <td>3906.016457</td>\n",
       "      <td>7877.754829</td>\n",
       "      <td>4446.472725</td>\n",
       "      <td>33604.707650</td>\n",
       "      <td>67774.841940</td>\n",
       "      <td>3759.247698</td>\n",
       "      <td>...</td>\n",
       "      <td>29.756621</td>\n",
       "      <td>80.343431</td>\n",
       "      <td>2020</td>\n",
       "      <td>17.323212</td>\n",
       "      <td>21.975246</td>\n",
       "      <td>22.780449</td>\n",
       "      <td>21.049786</td>\n",
       "      <td>22.193523</td>\n",
       "      <td>22.193523</td>\n",
       "      <td>12692456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-26</th>\n",
       "      <td>0.024217</td>\n",
       "      <td>13212864</td>\n",
       "      <td>1.630683e+07</td>\n",
       "      <td>200.762976</td>\n",
       "      <td>1514.930303</td>\n",
       "      <td>3059.685608</td>\n",
       "      <td>4217.004054</td>\n",
       "      <td>31820.943110</td>\n",
       "      <td>64268.357070</td>\n",
       "      <td>3551.882100</td>\n",
       "      <td>...</td>\n",
       "      <td>72.650391</td>\n",
       "      <td>196.157408</td>\n",
       "      <td>2020</td>\n",
       "      <td>9.657485</td>\n",
       "      <td>22.218300</td>\n",
       "      <td>22.588533</td>\n",
       "      <td>20.349331</td>\n",
       "      <td>21.462585</td>\n",
       "      <td>21.462585</td>\n",
       "      <td>11780846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-27</th>\n",
       "      <td>0.039043</td>\n",
       "      <td>14277536</td>\n",
       "      <td>1.659291e+07</td>\n",
       "      <td>134.966149</td>\n",
       "      <td>1017.172660</td>\n",
       "      <td>2056.697582</td>\n",
       "      <td>4570.510617</td>\n",
       "      <td>34445.662720</td>\n",
       "      <td>69648.265260</td>\n",
       "      <td>3838.087228</td>\n",
       "      <td>...</td>\n",
       "      <td>117.127110</td>\n",
       "      <td>316.245378</td>\n",
       "      <td>2020</td>\n",
       "      <td>6.597019</td>\n",
       "      <td>21.287678</td>\n",
       "      <td>22.822914</td>\n",
       "      <td>20.498943</td>\n",
       "      <td>22.159378</td>\n",
       "      <td>22.159378</td>\n",
       "      <td>12722236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-28</th>\n",
       "      <td>0.055220</td>\n",
       "      <td>16174560</td>\n",
       "      <td>1.687900e+07</td>\n",
       "      <td>108.350558</td>\n",
       "      <td>815.823835</td>\n",
       "      <td>1650.977121</td>\n",
       "      <td>5189.484114</td>\n",
       "      <td>39074.139640</td>\n",
       "      <td>79074.069440</td>\n",
       "      <td>4348.045219</td>\n",
       "      <td>...</td>\n",
       "      <td>165.657306</td>\n",
       "      <td>447.277813</td>\n",
       "      <td>2020</td>\n",
       "      <td>4.888221</td>\n",
       "      <td>22.072380</td>\n",
       "      <td>24.722673</td>\n",
       "      <td>21.962742</td>\n",
       "      <td>24.273489</td>\n",
       "      <td>24.273489</td>\n",
       "      <td>14827319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-12</th>\n",
       "      <td>24.327384</td>\n",
       "      <td>11987424</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.407692</td>\n",
       "      <td>6.793503</td>\n",
       "      <td>20.770641</td>\n",
       "      <td>29703.212830</td>\n",
       "      <td>143347.270200</td>\n",
       "      <td>438273.868800</td>\n",
       "      <td>3222.459320</td>\n",
       "      <td>...</td>\n",
       "      <td>72981.575780</td>\n",
       "      <td>197051.614000</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.608480</td>\n",
       "      <td>5.130931</td>\n",
       "      <td>5.217824</td>\n",
       "      <td>5.116322</td>\n",
       "      <td>5.145176</td>\n",
       "      <td>5.145176</td>\n",
       "      <td>79402437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-13</th>\n",
       "      <td>24.340873</td>\n",
       "      <td>12611296</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.416966</td>\n",
       "      <td>6.863659</td>\n",
       "      <td>20.912006</td>\n",
       "      <td>29915.470500</td>\n",
       "      <td>144907.904400</td>\n",
       "      <td>441501.417100</td>\n",
       "      <td>3390.168591</td>\n",
       "      <td>...</td>\n",
       "      <td>73022.040660</td>\n",
       "      <td>197160.869900</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.607595</td>\n",
       "      <td>5.145351</td>\n",
       "      <td>5.174136</td>\n",
       "      <td>4.755543</td>\n",
       "      <td>5.137164</td>\n",
       "      <td>5.137164</td>\n",
       "      <td>189209228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-14</th>\n",
       "      <td>24.353995</td>\n",
       "      <td>12329664</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.412635</td>\n",
       "      <td>6.830892</td>\n",
       "      <td>20.845981</td>\n",
       "      <td>29840.106090</td>\n",
       "      <td>144293.880100</td>\n",
       "      <td>440344.754700</td>\n",
       "      <td>3314.460276</td>\n",
       "      <td>...</td>\n",
       "      <td>73061.408490</td>\n",
       "      <td>197267.163800</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.606715</td>\n",
       "      <td>5.136155</td>\n",
       "      <td>5.295793</td>\n",
       "      <td>5.012370</td>\n",
       "      <td>5.066583</td>\n",
       "      <td>5.066583</td>\n",
       "      <td>143976527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-15</th>\n",
       "      <td>24.367511</td>\n",
       "      <td>12360032</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.412988</td>\n",
       "      <td>6.833563</td>\n",
       "      <td>20.851364</td>\n",
       "      <td>29864.128600</td>\n",
       "      <td>144430.411500</td>\n",
       "      <td>440702.883800</td>\n",
       "      <td>3322.623802</td>\n",
       "      <td>...</td>\n",
       "      <td>73101.954550</td>\n",
       "      <td>197376.638900</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.605838</td>\n",
       "      <td>5.066464</td>\n",
       "      <td>5.259690</td>\n",
       "      <td>4.987403</td>\n",
       "      <td>5.184858</td>\n",
       "      <td>5.184858</td>\n",
       "      <td>136423790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-16</th>\n",
       "      <td>24.378111</td>\n",
       "      <td>7650816</td>\n",
       "      <td>1.452033e+09</td>\n",
       "      <td>1.342260</td>\n",
       "      <td>6.298506</td>\n",
       "      <td>19.773216</td>\n",
       "      <td>28381.615430</td>\n",
       "      <td>133179.643100</td>\n",
       "      <td>418097.552700</td>\n",
       "      <td>2056.692357</td>\n",
       "      <td>...</td>\n",
       "      <td>73133.755430</td>\n",
       "      <td>197462.501900</td>\n",
       "      <td>2022</td>\n",
       "      <td>0.605031</td>\n",
       "      <td>5.185954</td>\n",
       "      <td>5.273813</td>\n",
       "      <td>5.106390</td>\n",
       "      <td>5.153086</td>\n",
       "      <td>5.153086</td>\n",
       "      <td>105048220</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>784 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Data storage capacity  Data storage capacity added per day  \\\n",
       "Date                                                                     \n",
       "2020-08-24               0.000535                              2053024   \n",
       "2020-08-25               0.009919                             13984256   \n",
       "2020-08-26               0.024217                             13212864   \n",
       "2020-08-27               0.039043                             14277536   \n",
       "2020-08-28               0.055220                             16174560   \n",
       "...                           ...                                  ...   \n",
       "2022-10-12              24.327384                             11987424   \n",
       "2022-10-13              24.340873                             12611296   \n",
       "2022-10-14              24.353995                             12329664   \n",
       "2022-10-15              24.367511                             12360032   \n",
       "2022-10-16              24.378111                              7650816   \n",
       "\n",
       "            Cumulative renewable energy purchases  \\\n",
       "Date                                                \n",
       "2020-08-24                           1.573466e+07   \n",
       "2020-08-25                           1.602074e+07   \n",
       "2020-08-26                           1.630683e+07   \n",
       "2020-08-27                           1.659291e+07   \n",
       "2020-08-28                           1.687900e+07   \n",
       "...                                           ...   \n",
       "2022-10-12                           1.452033e+09   \n",
       "2022-10-13                           1.452033e+09   \n",
       "2022-10-14                           1.452033e+09   \n",
       "2022-10-15                           1.452033e+09   \n",
       "2022-10-16                           1.452033e+09   \n",
       "\n",
       "            Energy intensity lower bound  Energy intensity estimate  \\\n",
       "Date                                                                  \n",
       "2020-08-24                   1404.098113               10618.245610   \n",
       "2020-08-25                    516.832219                3906.016457   \n",
       "2020-08-26                    200.762976                1514.930303   \n",
       "2020-08-27                    134.966149                1017.172660   \n",
       "2020-08-28                    108.350558                 815.823835   \n",
       "...                                  ...                        ...   \n",
       "2022-10-12                      1.407692                   6.793503   \n",
       "2022-10-13                      1.416966                   6.863659   \n",
       "2022-10-14                      1.412635                   6.830892   \n",
       "2022-10-15                      1.412988                   6.833563   \n",
       "2022-10-16                      1.342260                   6.298506   \n",
       "\n",
       "            Energy intensity upper bound  Energy consumption rate lower bound  \\\n",
       "Date                                                                            \n",
       "2020-08-24                  21402.982540                           651.804634   \n",
       "2020-08-25                   7877.754829                          4446.472725   \n",
       "2020-08-26                   3059.685608                          4217.004054   \n",
       "2020-08-27                   2056.697582                          4570.510617   \n",
       "2020-08-28                   1650.977121                          5189.484114   \n",
       "...                                  ...                                  ...   \n",
       "2022-10-12                     20.770641                         29703.212830   \n",
       "2022-10-13                     20.912006                         29915.470500   \n",
       "2022-10-14                     20.845981                         29840.106090   \n",
       "2022-10-15                     20.851364                         29864.128600   \n",
       "2022-10-16                     19.773216                         28381.615430   \n",
       "\n",
       "            Energy consumption rate estimate  \\\n",
       "Date                                           \n",
       "2020-08-24                       4929.158175   \n",
       "2020-08-25                      33604.707650   \n",
       "2020-08-26                      31820.943110   \n",
       "2020-08-27                      34445.662720   \n",
       "2020-08-28                      39074.139640   \n",
       "...                                      ...   \n",
       "2022-10-12                     143347.270200   \n",
       "2022-10-13                     144907.904400   \n",
       "2022-10-14                     144293.880100   \n",
       "2022-10-15                     144430.411500   \n",
       "2022-10-16                     133179.643100   \n",
       "\n",
       "            Energy consumption rate upper bound  \\\n",
       "Date                                              \n",
       "2020-08-24                          9935.604259   \n",
       "2020-08-25                         67774.841940   \n",
       "2020-08-26                         64268.357070   \n",
       "2020-08-27                         69648.265260   \n",
       "2020-08-28                         79074.069440   \n",
       "...                                         ...   \n",
       "2022-10-12                        438273.868800   \n",
       "2022-10-13                        441501.417100   \n",
       "2022-10-14                        440344.754700   \n",
       "2022-10-15                        440702.883800   \n",
       "2022-10-16                        418097.552700   \n",
       "\n",
       "            Energy used to seal data lower bound  ...  \\\n",
       "Date                                              ...   \n",
       "2020-08-24                            551.893912  ...   \n",
       "2020-08-25                           3759.247698  ...   \n",
       "2020-08-26                           3551.882100  ...   \n",
       "2020-08-27                           3838.087228  ...   \n",
       "2020-08-28                           4348.045219  ...   \n",
       "...                                          ...  ...   \n",
       "2022-10-12                           3222.459320  ...   \n",
       "2022-10-13                           3390.168591  ...   \n",
       "2022-10-14                           3314.460276  ...   \n",
       "2022-10-15                           3322.623802  ...   \n",
       "2022-10-16                           2056.692357  ...   \n",
       "\n",
       "            Energy used to store data estimate  \\\n",
       "Date                                             \n",
       "2020-08-24                            1.605601   \n",
       "2020-08-25                           29.756621   \n",
       "2020-08-26                           72.650391   \n",
       "2020-08-27                          117.127110   \n",
       "2020-08-28                          165.657306   \n",
       "...                                        ...   \n",
       "2022-10-12                        72981.575780   \n",
       "2022-10-13                        73022.040660   \n",
       "2022-10-14                        73061.408490   \n",
       "2022-10-15                        73101.954550   \n",
       "2022-10-16                        73133.755430   \n",
       "\n",
       "            Energy used to store data upper bound  year   ren_share  \\\n",
       "Date                                                                  \n",
       "2020-08-24                               4.335152  2020  133.006511   \n",
       "2020-08-25                              80.343431  2020   17.323212   \n",
       "2020-08-26                             196.157408  2020    9.657485   \n",
       "2020-08-27                             316.245378  2020    6.597019   \n",
       "2020-08-28                             447.277813  2020    4.888221   \n",
       "...                                           ...   ...         ...   \n",
       "2022-10-12                          197051.614000  2022    0.608480   \n",
       "2022-10-13                          197160.869900  2022    0.607595   \n",
       "2022-10-14                          197267.163800  2022    0.606715   \n",
       "2022-10-15                          197376.638900  2022    0.605838   \n",
       "2022-10-16                          197462.501900  2022    0.605031   \n",
       "\n",
       "                 Open       High        Low      Close  Adj Close     Volume  \n",
       "Date                                                                          \n",
       "2020-08-24  20.470207  23.807421  20.411312  22.020189  22.020189   16525999  \n",
       "2020-08-25  21.975246  22.780449  21.049786  22.193523  22.193523   12692456  \n",
       "2020-08-26  22.218300  22.588533  20.349331  21.462585  21.462585   11780846  \n",
       "2020-08-27  21.287678  22.822914  20.498943  22.159378  22.159378   12722236  \n",
       "2020-08-28  22.072380  24.722673  21.962742  24.273489  24.273489   14827319  \n",
       "...               ...        ...        ...        ...        ...        ...  \n",
       "2022-10-12   5.130931   5.217824   5.116322   5.145176   5.145176   79402437  \n",
       "2022-10-13   5.145351   5.174136   4.755543   5.137164   5.137164  189209228  \n",
       "2022-10-14   5.136155   5.295793   5.012370   5.066583   5.066583  143976527  \n",
       "2022-10-15   5.066464   5.259690   4.987403   5.184858   5.184858  136423790  \n",
       "2022-10-16   5.185954   5.273813   5.106390   5.153086   5.153086  105048220  \n",
       "\n",
       "[784 rows x 26 columns]"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T21:13:25.328902Z",
     "iopub.status.busy": "2022-12-08T21:13:25.328420Z",
     "iopub.status.idle": "2022-12-08T21:13:25.351560Z",
     "shell.execute_reply": "2022-12-08T21:13:25.350268Z",
     "shell.execute_reply.started": "2022-12-08T21:13:25.328857Z"
    }
   },
   "outputs": [],
   "source": [
    "adjClose = 'Adj Close'\n",
    "\n",
    "correlation_seal = df[['Open', 'High', 'Low', 'Close', adjClose, 'Volume', \"Energy used to seal data estimate\"]].corr()\n",
    "correlation_added = df[['Open', 'High', 'Low', 'Close', adjClose, 'Volume', \"Data storage capacity added per day\"]].corr()\n",
    "correlation_cons = df[['Open', 'High', 'Low', 'Close', adjClose, 'Volume', \"Energy consumption rate estimate\"]].corr()\n",
    "correlation_cons_sp = df[['Open', 'High', 'Low', 'Close', adjClose, 'Volume', \"Energy consumption rate estimate\"]].corr('spearman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T21:03:22.140956Z",
     "iopub.status.busy": "2022-12-08T21:03:22.140538Z",
     "iopub.status.idle": "2022-12-08T21:03:22.749193Z",
     "shell.execute_reply": "2022-12-08T21:03:22.747969Z",
     "shell.execute_reply.started": "2022-12-08T21:03:22.140922Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAf8AAAGeCAYAAACaWQhBAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAAsTAAALEwEAmpwYAABnKUlEQVR4nO3dd3wUdf7H8ddnN6H3GnrvvaooCiIKKJbDhgJiOVHOsx2HUgS7nHoonoqiomBDz7OAP4qCQEApoQdBeofQEzokm8/vj5mEJAQSZJPZJZ+nj324O/PN7DuzSz77/c53Z0RVMcYYY0ze4fM6gDHGGGNylxV/Y4wxJo+x4m+MMcbkMVb8jTHGmDzGir8xxhiTx1jxN8YYY/IYK/7GGGNMiBKRsSKyR0RWnmW9iMhbIrJeRFaISMvsbNeKvzHGGBO6PgG6nGN9V6COe3sQGJ2djVrxN8YYY0KUqkYDB87R5CZgvDrmAyVEpEJW27Xib4wxxoSvSsC2NI+3u8vOKSLH4hgTQhL3bQzN81gnnvQ6QeZ81i+4WCxr+bTXETI1M6Kw1xEyNXDLZ3Kh2zifvzf5ytbqhzNcn2KMqo650AxZseJvjDHGBFNyINtN3UJ/IcV+B1AlzePK7rJzso/3xhhjTDBpcvZvF24i0Med9X8pkKCqu7L6Iev5G2OMMUGkgaSgbUtEvgQ6AGVEZDswHIgEUNX3gMlAN2A9cAy4NzvbteJvjDHGBFNyUHr0AKhqzyzWK/C3892uFX9jjDEmmIIznJ+jrPgbY4wxwXQeE/68YsXfGGOMCSbr+RtjjDF5SzAn/OUUK/7GGGNMMAVxwl9OseJvjDHGBJMN+xvjEJHKwDtAQ5yTS/0I/FNVT3ka7DwMfXkk0b8upFTJEnz/2Xu59rxzFyxhxNsfEggk0+P6zjxwd49063fG7eGZV//DgfhDFC9ahBFDniCqXBkARr4/juh5iwHo1+d2ul59RZCzLWbEWx8SSA7Q4/preaDXrWdmG/EWB+ITKF6sKCOGPnk62+hPiJ6/yM12B107tbdcHuUCKNahBVWfvx/x+dj75XTi3vn2jDYlu7ej0pN3girHVm1m4yNvAFB5SB9KdGoFPh+HopexddhHQctV46qmdBreG/H7WDFhFgtGT0q3vvGt7ekwuCeH4w4CsHT8z6yYMAuAqwbdSa2rmyM+YfOclcx49tOg5TqnMJjwZ2f4MzlORAT4FvheVesAdYEiwEueBjtPN3frzHsjX8zV5wwEArw46n1G/2sYE8f9h8m/zGHD5m3p2rw++hNuvLYj340dxcP33MGbHzh/4GbPW8SqtRv55sM3+GL0q3zy1fccOXosuNneeJ/Rrw1n4vh3mDwjmg2bt6bP9u5YbryuI9998h8n25jxbrYYVq3bwDcfjeKL917nk6++C1o2y/Un+HxUe+lB1vV6gZUdH6X0zVdQoE7ldE3y16hAhUd6sPrmQay8+jG2Dh8LQJHW9SjSpj4rr3mClVc/RuHmdSh6WaOgxBKfcM0L9/Dfe17lo2sG0uDGSyldp+IZ7f74cT7jug1hXLchqYW/Yqs6VGpdl4+vG8TYzk8T1awmVS5tEJRcWcrdM/z9KVb8TW64Gjihqh8DqGoAeAK4T0T6i8gPIjJLRNaJyPCUHxKRXiKyUESWicj7IuJ3lx8RkZdEZLmIzBeR8rnxS7Ru3oTixYrmxlOliv1jHVUrVaBKxSgiIyPpevUV/PLrgnRtNmzZRtuWTQBo26IJM39dmLq8dbOGRET4KVSwAHVrVWPuwiXBy7Y6Q7ZO7fllboZsm7fRtmVTJ1vLpsx012/YvI3WzRqdzlazOnMXBCeb5Tp/hVvU4eTmXZzcuhtNTOLAD3MpeV3bdG3K3tWZPZ9MIZBwFICk/QkAqIIvfz4kXwS+fBFIhJ/EvQlByVWheS3iN+8mYdtekhMDrJ40n9qdW2Xvh1WJyB+JPzICf75I/BF+ju4LTq4sJSdn/+YRK/4mNzQCFqddoKqHgK04h57aAj2ApsBtItJaRBoAdwCXq2pzIADc7f54YWC+qjYDooG/5sYv4YU9ew8QVbZM6uPyZUuzZ2/6S3vXq1Wd6dHzAZg+Zz5Hjx0nPuEQ9WpVZ+7CpRw/cZKD8YeIWbqSuD37gpdt3/7UIWknWxn27N2fPlvtGkyPnudki56XJlsN5i5YkiZbLHF79louD3IB5Isqxamdp98bp3btJzKqdLo2BWpWpEDNitT//mUaTBpBsQ4tADi6eA2Hf4ul+ZKxNFs6loTZyzixfntQchWJKsnhXaff74d3HaBoVMkz2tXt2pa+U1/mptGPUrRCKQB2LlnP1nmr6B/zNn+LeZtN0bEcWL8zKLmyFEjK/s0jdszfhIKfVXU/gIh8C1wBJAGtgBjnqAEFgT1u+1M4cwbA+VDROVfThpgBD9/LS6PG8MPUX2jVrBHly5TG5/NxeZsWrPxjPb3+9hQlSxSnWaN6+HP5Ur0D+t/LS2+8zw9TZ9CqaWPKl3WztW3Byj/W0av/QEqWKEazRvVzNZvlOn8S4adAjQqsufUZIiuUpsG3L7Gy02NElCpGgTqVWd76AQDqTXiWhLYNOLJwda7kWj99KasnziNwKolmd11Nt5H9+KrnK5SoVp7StSsx+tJHAbj986ep3KYe22PW5HgmZ3AztFnxN7lhFZBuZpOIFAOq4hT5jNe+VkCAcao6KJPtJbrnswZnRCDT97GIPIh7nex3//0iD/Q55ymyQ1K5sqWI23u6R7Z7737KlS2Vvk2ZUox6wblm+7Fjx5k+ex7FihYBoF/v2+jX+zYABr7wb6pVOfN46Z/OVqZ0upGE3Xv3Ua5s6TPajHpp8Ols0b+dztbndvr1ud3J9vzrVKtSyXJ5kAvgVNwB8lU8PSqRr0JpEuPSj0qc2rWfo0vWokkBTm3bw4mNOylQoyJFL2vMkSVrST52AoCEX5ZQpFW9oBT/I3EHU3vyAEUrlEqd2JfiRPyR1PsrJsykw6A7AajbpTU7l64n8dhJADbNXE7FlrVzpfiHw2x/G/Y3uWEGUEhE+gC4x+7/DXyCcxWqziJSSkQKAjcDv7o/c6uIlHN/ppSIVDufJ1XVMaraWlVbh2PhB2hcrw5bt+9i+67dJCYmMuWXuXRsl/5Y7MH4QyS7xw4/+OJ/3NKtE+BMMItPOATAmg2bWbthC+1atwhetvp12Lp9J9t3xjnZZsyh4+WXnD3b599wS7drMsm2ibUbNtOuTXCyWa7zd3TZOvLXqEC+KuWQyAhK3XQFB3+KSZ9t6gKKtmsMQETJohSoWZETW3dzaudeil7aCPw+JMJP0csacTxIw/67lm+kZI0oilcpiy/ST4Pul7L+5/RzHQqXK5F6v3bnVux3h/YP7dhHlUvqI34fvgg/VS5tkLoux4XBMX/r+Zscp6oqIrcA74rIMzgfOicDg4GewELgf0Bl4DNVXQQgIkOBn0TEByTiXLlqiwe/AgD/HD6CmKUriI8/RKebe9H//t706H5djj5nRISfwY/9lX7/fI5AcoBbul5D7RpVeXvsFzSqV5uOl7clZtlK3vzgU0SEVk0bMvTxfgAkJQXo86jTiyxSqBAjhjxORIQ/uNke70e/Ac8SSE7mlm5uto8+d7JdcQkxy2J58/3xTrZmjRj6xEOnsz3iDOoUKVyQEUOfDFo2y/UnBJLZOvQD6n0xHHw+9n01gxNrt1FxQE+OLV9P/M8xHJq1lOJXNafxzLfQQDLbXhhH4OBhDvw4j6KXN6HxjFGgSsKspST8vCgosTSQzPRh47ht/EDE7yP269nsX7eDK57sQdyKTayfvoRWfa+ldueWJCcFOJFwlMkD3gdgzeSFVG3XiPt+egVV2DR7BRtmLA1KrqyDh37PX06PnhqT+0SkL9BaVR/JyedJ3LcxNN/oiSe9TpC5XD6ebHLOspZPex0hUzMjCnsdIVMDt3wmF7qNEzH/y/bfmwJtelzw8/0Z1vM3xhhjgsnO7W/MuanqJzjH/o0x5uIQBsP+VvyNMcaYYLIL+xhjjDF5jBV/Y4wxJm+xk/wYY4wxeY1N+DPGGGPyGBv2N8YYY/IYm+1vjDHG5DHW8zfGGGPymDDo+ds5PI0xxphgCvKFfUSki4isEZH1InLG+ZpFpJqIzBCRFSIyS0QqZ7VN6/mbvCFUz6Efmd/rBJnSU8e9jpAp8dufrPNVpsyRrBt54ER8Ia8j5JwgzvZ3r4L6DtAZ2A7EiMhEVV2VptnrwHhVHSciVwOvAL3PtV3r+RtjjDHBFNyef1tgvapuVNVTwATgpgxtGgK/uPdnZrL+DFb8jTHGmGDS5OzfslYJ2Jbm8XZ3WVrLgb+4928BiopI6XNt1Iq/McYYE0zn0fMXkQdFZFGa24N/4hkHAFeJyFLgKmAHcM7TDNoBNGOMMSaYzmO2v6qOAcaco8kOoEqax5XdZWm3sRO35y8iRYAeqhp/rue1nr8xxhgTTME95h8D1BGRGiKSD7gTmJi2gYiUEZGUej4IGJvVRq34G2OMMcEUCGT/lgVVTQIeAaYBq4GvVfV3EXleRG50m3UA1ojIWqA88FJW27Vhf2OMMSaYgnyGP1WdDEzOsGxYmvvfAN+czzat+BtjjDHBZKf3NcYYY/KYMDi9rxV/Y4wxJpis529MeiJyRFWLpHncF2itqo+IyEPAMVUdf46fT20f7GxzFyxhxNsfEggk0+P6zjxwd49063fG7eGZV//DgfhDFC9ahBFDniCqXBkARr4/juh5iwHo1+d2ul59RbDjndXQl0cS/etCSpUswfefvZdrzwswd+ES/vX2WAKBZP5y/TU8cNdf0q3fGbeHYa++w4EEZ5+9MuQxosqm7LPxzJnv7rPet9EliPts7oLFjHjrQwLJAXpcfy0P9Lr1jFzPjHiLA/EJFC9WlBFDnzz9Wo7+hOj5i5xcfe6ga6f2F30ugILtWlPqqf6Iz8fh76aQMPardOtLDXiIAm2aA+ArmB9fyRJsbX8L+erVovSQR/EVKQSBZOI//IKj02YHLVetq5py3fDe+Pw+lk6Yxa+jJ6Vb3+zWK7lmcE8Oxx0EIGb8TyydMIvqlzXk2md6pbYrU6sC//v726z5aXHQsp1VNibyec2KvwkZqpq7lSuNQCDAi6Pe54PXnyOqbGnueOifdLy8LbWqn/567eujP+HGaztyU5erWbBkBW9+8CkjhjzB7HmLWLV2I998+AanEhO59/GhtL+kJUUK5865y2/u1pm7etzI4Bdez5XnSxEIBHhp1AeMeW04UWVLc+dDA+nYrk36ffbeOLpf24GbunRkwZJYRn3wOa8MfozoeYtYvW4j//1wJKdOJXLfE89wRZD2WSAQ4MU33ueDkc87r+WD/6DjFW2pVb3q6VzvjuXG6zpyU9dOLFi8nDfHjGfE0CeZPS+GVes28M1Ho5zX8rHBtL+01UWdCwCfj9KD/05cv6dI2r2Pil+8zbFZ80jcuDW1yYHXT//zLNbzJvLVrw1A8okT7B36Kklbd+AvW5qKX77D8d8WkXz46AXHEp/Q9YW+fHb3KxyKO8ADE19gzfQl7FuX7mvu/P7jfKYOG5du2eZ5qxjTbTAABYoX5u/RI9kQHXvBmbIlDHr+9lU/EzJE5FkRGeDeb+NeoWqZiLwmIivTNK0oIlNFZJ2IvBqM5479Yx1VK1WgSsUoIiMj6Xr1Ffzy64J0bTZs2Ubblk0AaNuiCTN/XZi6vHWzhkRE+ClUsAB1a1Vj7sIlwYiVLa2bN6F4saK59nwpYv9YT9WK6fdZyj5JsXHzdi5J3WeN0+yz7bRq2pAIv7vPalZn7sKlwcm1OsNr2ak9v8zN8Fpu3kbblk2dXC2bMtNdv2HzNlo3a3T6taxZnbkLgvNahmougPyN65G4bSdJO+IgKYmjU2dRqEO7s7Yv3KUjR6bMBCBpyw6StjrFOLB3P4ED8fhKlghKrkrNa3Fw827it+0lOTHA75PmU69zq/PeTsNubVk/azlJJ04FJVeWgnt63xxhxd/ktoJuQV8mIsuA58/S7mOgn6o258zTVDYH7gCaAHeISBUu0J69B1KHowHKly3Nnr0H0rWpV6s606PnAzB9znyOHjtOfMIh6tVyCtfxEyc5GH+ImKUriduz70Ijhbw9+/YTVe706cPLly3N7n3p91ndNPtsxpwF7j47TL1a1fk1ZZ8lHGLhspXs3hucfebkSvtalmHP3v3p2tSrXYPp0fMAmB49L81rWYO5C5akeS1jiduz96LOBeAvV4ZA3OntBfbsI6J8mUzbRlQoR0SlKE4sXHbGunyN6yGRkSRt2xmUXEWjSpGw6/Q+OrTrAEWjSp7RrkHXNvSb+gq3jn6MYhVKnbG+0Y2XsfKHeUHJlB2arNm+ecWG/U1uO+4WdOD0Mfy0DUSkBFBUVVP+tX4B3JCmyQxVTXDbrgKqkf7CFzliwMP38tKoMfww9RdaNWtE+TKl8fl8XN6mBSv/WE+vvz1FyRLFadaoHn6ffa4GGPDwPbz81gf8MG0mrZo2pFyZUvj8Ptq1ac7KNevp/cggSpYoRrOGdfHl4j4b0P9eXnrjfX6YOoNWTRtTvqz7WrZtwco/1tGr/0AnV6P6ufpahmqutAp36cjR6XPOGNr2lylF2ZeeYt/Q10Bzr6itnb6ElRN/I3AqiZZ3Xc1NIx/i054vp64vUq4E5epVYUP0ilzLFA7D/lb8TTg6meZ+gLO8j90LZDwI8O6rz/JAr9vPusFyZUsRl6bnuXvvfsqVTd+DKFemFKNeeBqAY8eOM332PIoVdeYu9ut9G/163wbAwBf+TbUqFc/7lwo35cqUJm7P6V7Z7r37KV/mzH325vNPAXDs+HF+jp5HsSKFAXiw16086E54G/jCG1SrHJx95uRK+1ruo1zZ0me0GfWSczz42LHjTI/+7fRr2ed2+vVx3isDn3+dalUyXkDt4soFTk/fH1U29bG/XBmSdmc+ElO4Swf2v/yfdMukcCHKv/0iB//zMSdjVwct1+G4AxSvcHofFatQKnViX4rj8UdS7y+dMJNrBvVMt77h9Zfwx7RFJCfl4iS8MPiqn3VPTMhxL0hxWEQucRfd+Se3M0ZVW6tq63MVfoDG9eqwdfsutu/aTWJiIlN+mUvHdm3TtTkYf4hk9xP9B1/8j1u6dQKciVzxCYcAWLNhM2s3bKFd6xZ/JnJYaVy/Nlt2pN9nHdq1SdfmYMLpffbh599yS9e0++ww4OyzdRs3086dSX7hueqwdftOtu+Mc3LNmEPHyy9J1ybda/n5N9zS7Zo0uVJey02s3bCZdm2C81qGai6Ak7+vIbJqJSIqRUFEBIW7dODY7DOHySOrV8FXtAgnl686vTAigvJvPMuRST9zbPqcoGUC2LF8I6VqRFGiSll8kX4adb+UtT+nn61fpFyJ1Pt1O7di3/r0hxwa39iO3yfm3pA/AEmB7N88Yj1/E6ruBz4QkWRgNpCQk08WEeFn8GN/pd8/nyOQHOCWrtdQu0ZV3h77BY3q1abj5W2JWbaSNz/4FBGhVdOGDH28HwBJSQH6POr01ooUKsSIIY8TEeHPybjp/HP4CGKWriA+/hCdbu5F//t706P7dTn+vBF+P4MffYCHBj5PIDmZW7p2cvfZlzSqVyt1n4364HNEoFXThgx5zLlaaVIgwD2PDQGgSKGCvDLkcSL8wdlnERF+Bj/ej34DnnVydXNfy48+d17LKy4hZlksb74/3nktmzVi6BMPObmSAvR5ZJCTq3BBRgx9MmivZajmAiCQzP5X3iZq9Cvg83H4+2kkbthCif73cOr3takfBAp36cDRabPS/Wjh666iQMsm+IoXo8iNzvtu37DXOLVmwwXH0kAyU4Z9wt3jn0L8PpZ9PZu963bQ4cke7FyxibXTl9C273XU7dyS5KQAJxKO8sOA099KKF65DMUqlmLz/OCNRmRLGAz7i+bisRljsktEiqjqEff+00AFVX3sz24vcdfq0HyjR+b3OkGm9NRxryNkSvzWXzlf268N+ikxguLT+HJeR8jUsC2fy4Vu49ib/bL996bQ4+9f8PP9GfYvyYSq60VkEM57dAvQ19s4xhiTTWHQ87fib0KSqn4FfJVlQ2OMCTUefoUvu6z4G2OMMcFkp/c1xhhj8ha1YX9jjDEmj7Fhf2OMMSaPCYOT/FjxN8YYY4LJev7GGGNMHmPH/I0xxpg8xmb7G2OMMXmMDfsbY4wxeYt91c+YUOHRtc+zErLn0M9X0OsImUsO/eHUULMprqTXETJVOL8np7TPHdbzN8YYY/IYK/7GGGNMHhMG3/MPzbFQY4wxJkxpUnK2b9khIl1EZI2IrHcvcZ5xfVURmSkiS0VkhYh0y2qbVvyNMcaYYErW7N+yICJ+4B2gK9AQ6CkiDTM0Gwp8raotgDuBd7Parg37G2OMMcEU3Nn+bYH1qroRQEQmADcBq9K0UaCYe784sDOrjVrxN8YYY4LpPCb8iciDwINpFo1R1TFpHlcCtqV5vB24JMNmngV+EpG/A4WBa7J6Xiv+xhhjTDCdR/F3C/2YLBueW0/gE1X9t4hcBnwqIo1Vzz7z0Iq/McYYE0QaCOqw/w6gSprHld1lad0PdAFQ1XkiUgAoA+w520Ztwp8xxhgTTEGc8AfEAHVEpIaI5MOZ0DcxQ5utQCcAEWkAFAD2nmuj1vM3xhhjgkiDeJIfVU0SkUeAaYAfGKuqv4vI88AiVZ0I/AP4QESewJn811dVzxnCir/xlIgcUdUiXucAmLtgMSPe+pBAcoAe11/LA71uTbd+Z9wenhnxFgfiEyherCgjhj5JVLkyAIwc/QnR8xcB0K/PHXTt1D54uRYu4V9vjyUQSOYv11/DA3f95Yxcw159hwMJhyhetAivDHmMqLJurvfHM2f+YidX79vocvUVQcuVlaEvjyT614WUKlmC7z97L9eeNytDX3mT6N9iKFWyON+Pz/IbUbnKy2ylOjajzov3In4fuz6fwZb//HBGm3I3XkaNAbehqhxZtYVVD78FQP5KpWkw8iHyVywNCsvvfoUT287Z8cy26lc1peOzvRG/j5UTZrHw3Unp1je6tT1XDunJkbiDACwb9zOxE2YB0H7QHdS8ujkA89/6njWTFgQlU5aCfIY/VZ0MTM6wbFia+6uAy89nm1b8jQECgQAvvvE+H4x8nqiypbnjwX/Q8Yq21KpeNbXN6++O5cbrOnJT104sWLycN8eMZ8TQJ5k9L4ZV6zbwzUejOJWYyL2PDab9pa0oUrhQUHK9NOoDxrw2nKiypbnzoYF0bNeGWtVPHwJ8/b1xdL+2Azd16ciCJbGM+uBzXhn8GNHzFrF63Ub+++FITp1K5L4nnuGKS1oGJVd23NytM3f1uJHBL7yeK8+XXTd3vYa7/nIDg18a6XWUM3iWzSfUG3E/S29/kZM799N62ivsnbaIY2tPH1ouWCOKao/ezOLuz5CUcJTIMsVS1zX8zyNsfvNbDkbH4i+Unyw6ndkmPqHTi/fwzd0jOLzrAHdPep71Py/mwLr032RbM2k+vwwbn25ZjaubU75xdcZ3GYI/XyR3fD2ETTNXcOpILlxPI/RP8GfH/E3oEZHmIjLfPVPVdyJSUkTKichid30zEVERqeo+3iAiF1TRYlevo2qlClSpGEVkZCRdO7Xnl7npewkbNm+jbcumALRt2ZSZ7voNm7fRulkjIiL8FCpYgLo1qzN3wZILiXM61x/rqVoxTa6rr2DmrwvTtdm4eTuXtGzi5GrROHX9hi3badW0IRH+NLkWLg1Kruxo3bwJxYsVzbXny67WzRuHZC7wLluxlrU5timOE1v2oIkB9nz/G2W7tEnXpmKvTmz/eBpJCUcBSNx3CIBCdSshEX4ORscCEDh2kuTjp4KSK6p5LeI37yZh616SEwOsmTSf2te2ytbPlq5Tie0L1qCBZJKOn2Tv6q1U79A0KLmyosma7ZtXrPibUDQeeEpVmwKxwHBV3QMUEJFiQHtgEdBeRKoBe1T12IU84Z59+1OH8AHKly3Dnr3707WpV7sG06PnATA9eh5Hjx0nPuEQ9WrVYO6CJRw/cZKD8YeIWRpL3J7gDHk6uUqnyVWa3fsOpGtTt1Z1pkfPB2DGnAVursPUq1WdXxcudXIlHGLhspXs3rsvKLnMxSV/VClO7jz9fj+5cz/5o0qla1OoVkUK1axAy0nP02ryi5Tq2Cx1edKhozQe+w/aTP8XtYb1Al9wrthXJKokh3eefr8f3nWAIuXPvEphnW5t6TPtZbq/9yhFKzi5967aQvUOTYkokI+CJYtQpV3D1HU5Lkmzf/OIDfubkCIixYESqjrbXTQO+K97/zec41pXAi/jfLVFgDm5kW1A/3t56Y33+WHqDFo1bUz5sqXx+Xxc3rYFK/9YR6/+AylZohjNGtXHn4uXEB7w8D28/NYH/DBtJq2aNqRcmVL4/D7atWnOyjXr6f3IICdXw7r4QvTSxib0SYSPQjUrsPSW58hfsRQtv3+OhR0GIH4fJS5pwMJrBnJy+z4ajXmCCnd2YNcXM3Ml14bpS/lj4jwCp5JoevfVdBnZj//2fIUtc1YS1awmPb8bzvEDh9i1eB0a3DPvnZWXPfrssuJvwkk0Tq+/GvAD8BTOzNb/y6xx2jNnvfvaczzQ+46zbrhcmdLE7TndK969dx/lypY+o82olwYDcOzYcaZH/0axos5cxX59bqdfn9sBGPj861SrUulP/YKZ5zrdI9u9dz/ly5TK0KYUbz7/lJPr+HF+jp5HsSKFAXiw16086E5cHPjCG1SrXDEouczF5WTcAWeynit/xdKcjEs/wnRy5wEOLVmHJgU4sXUvxzbuomDNCpzcdYDDKzdzYovzlfJ9UxZSrFVddnHhxf9I3EGKVjz9fi9aoRRHdh9M1+ZE/JHU+7FfzuTKQXemPl7w9kQWvO18K67bW/05uDHugjNlix3zN+b8qGoCcFBEUqbL9wZSRgHmAL2Ade6Zqw4A3YC5Z9nWGFVtraqtz1X4ARrXr8PW7TvZvjOOxMREpsyYQ8fL059B82D8IZLdnsMHn3/DLd2cM2gGAgHiE5zjn2s2bGLths20a9PifH/1s+SqzZYdu9i+a7eT65e5dGiX/ljswYTTuT78/Ftu6dopTa7Dbq7NrNu4mXZtmgcll7m4HF66gUI1K1Cgalkk0k+5m9uxb9qidG32TllIiXaNAIgsVZRCNStwfMtuDi1dT0TxQkSWduYqlLyiMUfXbg9KrrjlGylRI4piVcrii/RTr/ulbPg5/XyawuVKpN6v1bkV+9c7kwHFJxQo4Xw4L1O/CmUbVGGzOy8hp4XDMX/r+RuvFRKRtH8pRgL3AO+5k/g2AvcCqOpmERGcEQBwin5lVU3fFfgTIiL8DH68H/0GPEsgOZlbul1D7RpVefujz2lUrzYdr7iEmGWxvPn+eESEVs0aMfSJhwBISgrQ55FBABQpXJARQ58kIsJ/oZGcXH4/gx99gIcGPu/k6trJyTX2SxrVq0XHy9sSs2wloz74HBFo1bQhQx5zThOeFAhwz2NDnFyFCvLKkMeJ8AcnV3b8c/gIYpauID7+EJ1u7kX/+3vTo/t1ufb8Z8317KvELI0lPuEQnf5yD/3vu5seN1zrdSzAu2waSGbtoLE0nzAE8fvY+eVMjq7ZTo2Bt3N4+Qb2TVvMgZnLKdWhGZdEj0STk1n//GckHXR63euf/ZQW3wwDEQ4v38jOz6YHLdcvz4yjx6cD8fl9rPxqNvvX7qDdkz3YHbuJDT8vocW911Krc0uSkwKciD/KtH+8D4AvMoI7//cMACcPH2fyY6ODfea9swuDnr8E6ysZxoSyxN1rQvKNroEkryNkSvIV9DpC5pIDXicIO3OaDPE6QqaW5s/ndYRM/WPrZxc8W3F/96uy/fem9KTZwZkdeZ6s52+MMcYEkYbmZ/p0rPgbY4wxwRQGw/5W/I0xxpggOvuFdEOHFX9jjDEmiKz4G2OMMXmMFX9jjDEmj9GAJxP4z4sVf2OMMSaINNmKvzHGGJOn2LC/McYYk8eoWs/fGGOMyVOs52+MMcbkMXbM3xhzTuIP0X+CoXoOfV/uXZjoYlG20HGvI2QqkBya5/YPhmSb7W+MMcbkLdbzN8YYY/KYcLhYrhV/Y4wxJois52+MMcbkMfZVP2OMMSaPCYev+vm8DmCMMcZcTALJvmzfskNEuojIGhFZLyJPZ7L+DRFZ5t7Wikh8Vtu0nr8xxhgTRME85i8ifuAdoDOwHYgRkYmquir1+VSfSNP+70CLrLZrPX9jjDEmiFSzf8uGtsB6Vd2oqqeACcBN52jfE/gyq41az98YY4wJoiDP9q8EbEvzeDtwSWYNRaQaUAP4JauNWvE3xhhjgij5PGb7i8iDwINpFo1R1TF/8qnvBL5R1SxP0WnF3+Q4EYkC3gTaAPHAbuBx4FtVbexZsAzmLljMiLc+JJAcoMf11/JAr1vTrd8Zt4dnRrzFgfgEihcryoihTxJVrgwAI0d/QvT8RQD063MHXTu1v+hzZWXoK28S/VsMpUoW5/vx7+ba82Zl6Msjif51IaVKluD7z97zOk46oZKtyJUtqTj8r+DzcfCrn9n73jfp1lcY+gCFL2sCgK9gfiJKF2dVs545kqXGVU3pNLw34vexYsIsFoyelG5941vb02FwTw7HHQRg6fifWTFhFgBXDbqTWlc3R3zC5jkrmfHspzmSMaPk8+j5u4X+XMV+B1AlzePK7rLM3An8LTvPa8f8TY4SEQG+A2apai1VbQUMAsp7myy9QCDAi2+8z+jXhjNx/DtMnhHNhs1b07V5/d2x3HhdR7775D88fM8dvDlmPACz58Wwat0GvvloFF+89zqffPUdR44eu6hzZcfNXa/hvdefy7Xny66bu3XmvZEveh0jUyGRzeej4vMPsanvs6y79m8Uv/FK8teukq7Jrhc/ZP31j7H++sfYP+5HEqbOy5Eo4hOueeEe/nvPq3x0zUAa3HgppetUPKPdHz/OZ1y3IYzrNiS18FdsVYdKrevy8XWDGNv5aaKa1aTKpQ1yJGdGySrZvmVDDFBHRGqISD6cAj8xYyMRqQ+UBLL1YljxNzmtI5CoqqndGFVdTppjWCJSQEQ+FpFYEVkqIh3d5Y1EZKH79ZUVIlLHXd4rzfL33dmwFyR29TqqVqpAlYpRREZG0rVTe36ZuyBdmw2bt9G2ZVMA2rZsykx3/YbN22jdrBEREX4KFSxA3ZrVmbtgyYVGCulc2dG6eWOKFyuaa8+XXa2bNwnJXBAa2Qo1q8OpLbtI3LYbTUwiYVI0xTpneogZgOLdryRhUnSOZKnQvBbxm3eTsG0vyYkBVk+aT+3OrbL3w6pE5I/EHxmBP18k/gg/R/cl5EjOM59asn3LeluaBDwCTANWA1+r6u8i8ryI3Jim6Z3ABNXsTSO04m9yWmNgcRZt/gaoqjbBmak6TkQKAA8Bo1S1OdAa2C4iDYA7gMvd5QHg7gsNuWff/tShcoDyZcuwZ+/+dG3q1a7B9GjnQ/X06HkcPXac+IRD1KtVg7kLlnD8xEkOxh8iZmkscXv2XmikkM5lLl4RUaVJ3LUv9XFi3H4io0pn2jayUlnyVSnPkd9W5EiWIlElObzrQOrjw7sOUDSq5Bnt6nZtS9+pL3PT6EcpWqEUADuXrGfrvFX0j3mbv8W8zaboWA6s35kjOTMK8mx/VHWyqtZ1R09fcpcNU9WJado8q6pnnAPgbOyYvwkFVwD/AVDVP0RkC1AXZ/hqiIhUxpkfsE5EOgGtcL7rClAQ2JMbIQf0v5eX3nifH6bOoFXTxpQvWxqfz8flbVuw8o919Oo/kJIlitGsUX38vtz7XB2quczFr/gNV5Iw5VdI9u6UduunL2X1xHkETiXR7K6r6TayH1/1fIUS1cpTunYlRl/6KAC3f/40ldvUY3vMmhzPdD4T/rxixd/ktN+BW7NslQlV/UJEFgDXA5NFpB8gwDhVHZTVz6edRfvua8/xQO87ztq2XJnSxO053dvZvXcf5cqWPqPNqJcGA3Ds2HGmR/9GsaJFAOjX53b69bkdgIHPv061KpXO4zc9u1DNZS5eSXH7iaxwerQpMqo0iXH7M21bont7dg7LuYmJR+IOpvbkAYpWKJU6sS/FifgjqfdXTJhJh0F3AlC3S2t2Ll1P4rGTAGyauZyKLWvnSvEPh3P7WzfA5LRfgPxuIQZARJqSfvbqHNyhexGpC1QF1ohITWCjqr4F/AA0BWYAt4pIObd9Kfe7rWdQ1TGq2lpVW5+r8AM0rl+Hrdt3sn1nHImJiUyZMYeOl6c/znkw/hDJbg/ng8+/4ZZu1wDOpLz4hEMArNmwibUbNtOuTZYn2MqWUM1lLl7HVqwjf/WKRFYuj0RGULz7lRyavvCMdvlrVsZfvAjHlvyRY1l2Ld9IyRpRFK9SFl+knwbdL2X9z+nnrRQuVyL1fu3OrdjvDu0f2rGPKpfUR/w+fBF+qlzaIHVdTguoZPvmFev5mxylqioitwBvishTwAlgM85X/VK8C4wWkVggCeirqidF5Hagt4gkAnHAy6p6QESGAj+JiA9IxJkzsOVCckZE+Bn8eD/6DXiWQHIyt3S7hto1qvL2R5/TqF5tOl5xCTHLYnnz/fGICK2aNWLoEw8BkJQUoM8jzkBEkcIFGTH0SSIiLngOYkjnyo5/PvsqMUtjiU84RKe/3EP/++6mxw3X5trznzXX8BHELF1BfPwhOt3ci/7396ZH9+u8jgWESLZAMjuHv0eN8c85X/X773ROrttKuSfu5njsOg67HwSKd29P/KQ5ORpFA8lMHzaO28YPRPw+Yr+ezf51O7jiyR7ErdjE+ulLaNX3Wmp3bklyUoATCUeZPOB9ANZMXkjVdo2476dXUIVNs1ewYcbSHM2bIhyG/SWbEwONCWuJu9fYG/18SIgOCvpy78PLxeKPNo95HSFTU5KLex0hUwO3fHbBlfvXqFuz/ffm8rhvPPmkYD1/Y4wxJojC4Iq+VvyNMcaYYFJCf9jfir8xxhgTRElhcMzfir8xxhgTRNbzN8YYY/IYO+ZvjDHG5DHW8zfGGGPyGOv5G2OMMXmMFX9jjDEmjwmIDfsbY4wxeUqyHfM3xhhj8pZwOJe4FX9jjDEmiOyYvzHGGJPHJNsxf2OMMSZvsWF/Y4wxJo9JCv2OvxV/Y4wxJphstr8xxhiTx9iwvzHGGJPHJId+x9+KvzHGGBNM9lU/Y4wxJo8JhEHP3+d1AGOMMeZiknwet+wQkS4iskZE1ovI02dpc7uIrBKR30Xki6y2aT1/Y4wxJoiCOewvIn7gHaAzsB2IEZGJqroqTZs6wCDgclU9KCLlstquFX+TKRG5GfgOaKCqf5ylzSxggKouEpHJwF2qGp+hTRHg38A1QDxwGHhKVReIyBFVLZJjv8R5mrtgMSPe+pBAcoAe11/LA71uTbd+Z9wenhnxFgfiEyherCgjhj5JVLkyAIwc/QnR8xcB0K/PHXTt1P6iz5WVoa+8SfRvMZQqWZzvx7+ba8+blaEvjyT614WUKlmC7z97z+s46YRKtiJXtqTi8L+Cz8fBr35m73vfpFtfYegDFL6sCQC+gvmJKF2cVc165kiWGlc1pdPw3ojfx4oJs1gwelK69Y1vbU+HwT05HHcQgKXjf2bFhFkAXDXoTmpd3RzxCZvnrGTGs5/mSMaMNLjD/m2B9aq6EUBEJgA3AavStPkr8I6qHgRQ1T1ZbdSG/c3Z9ATmuv/Pkqp2y1j4XR8CB4A6qtoKuBcoE6yQwRIIBHjxjfcZ/dpwJo5/h8kzotmweWu6Nq+/O5Ybr+vId5/8h4fvuYM3x4wHYPa8GFat28A3H43ii/de55OvvuPI0WMXda7suLnrNbz3+nO59nzZdXO3zrw38kWvY2QqJLL5fFR8/iE29X2Wddf+jeI3Xkn+2lXSNdn14oesv/4x1l//GPvH/UjC1Hk5EkV8wjUv3MN/73mVj64ZSIMbL6V0nYpntPvjx/mM6zaEcd2GpBb+iq3qUKl1XT6+bhBjOz9NVLOaVLm0QY7kzCjIw/6VgG1pHm93l6VVF6grIr+KyHwR6ZLVRq34mzO4vfUrgPuBO9MsLygiE0RktYh8BxRMs26ziJTJsJ1awCXAUFVNBlDVTar6fxnaiYi8JiIrRSRWRO5wl1cQkWgRWeaua+8uv1ZE5onIEhH5r5v3gsSuXkfVShWoUjGKyMhIunZqzy9zF6Rrs2HzNtq2bApA25ZNmemu37B5G62bNSIiwk+hggWoW7M6cxcsudBIIZ0rO1o3b0zxYkVz7fmyq3XzJiGZC0IjW6FmdTi1ZReJ23ajiUkkTIqmWOdLztq+ePcrSZgUnSNZKjSvRfzm3SRs20tyYoDVk+ZTu3Or7P2wKhH5I/FHRuDPF4k/ws/RfQk5kjOj8yn+IvKgiCxKc3vwTzxlBFAH6IDTYftAREqc6wes+JvM3ARMVdW1wH4RSfnX9jBwTFUbAMOBrP4VNgKWqWogi3Z/AZoDzXAOD7wmIhWAu4Bpqpqybpn7AWMocI2qtgQWAU+e5+93hj379qcOlQOUL1uGPXv3p2tTr3YNpkc7PZzp0fM4euw48QmHqFerBnMXLOH4iZMcjD9EzNJY4vbsvdBIIZ3LXLwiokqTuGtf6uPEuP1ERpXOtG1kpbLkq1KeI7+tyJEsRaJKcnjXgdTHh3cdoGhUyTPa1e3alr5TX+am0Y9StEIpAHYuWc/WeavoH/M2f4t5m03RsRxYvzNHcmYUkOzfVHWMqrZOcxuTYXM7gLRDL5XdZWltByaqaqKqbgLW4nwYOCs75m8y0xMY5d6f4D5eDFwJvAWgqitEJFj/4q8AvnQ/JOwWkdlAGyAGGCsikcD3qrpMRK4CGgK/inPlrHxAzow5ZjCg/7289Mb7/DB1Bq2aNqZ82dL4fD4ub9uClX+so1f/gZQsUYxmjerj9+Xe5+pQzWUufsVvuJKEKb9CsnffbF8/fSmrJ84jcCqJZnddTbeR/fiq5yuUqFae0rUrMfrSRwG4/fOnqdymHttj1uR4piDvjRigjojUwCn6d+J0jNL6Hufv9MduB6kusPFcG7Xib9IRkVLA1UATEVHAD6iI/PNPbO53oJmI+LPR+z+DqkaLyJXA9cAnIjISOAj8rKpZzkVwh88eBHj3ted4oPcdZ21brkxp4vac7u3s3ruPcmVLn9Fm1EuDATh27DjTo3+jWFHniEO/PrfTr8/tAAx8/nWqVcl4SO7PCdVc5uKVFLefyAqnR5sio0qTGLc/07Ylurdn57Ccm5h4JO5gak8eoGiFUqkT+1KciD+Sen/FhJl0GOQcqazbpTU7l64n8dhJADbNXE7FlrXDrvirapKIPAJMw/l7PFZVfxeR54FFqjrRXXetiKwCAsA/VTXzF81l3QCT0a3Ap6paTVWrq2oVYBPQHojG/cQpIo2BpufakKpuwBmWf07cbrqIVBeR6zM0nQPcISJ+ESmLM8KwUESqAbtV9QOciYMtgfnA5SJS291eYRGpe5bnTx1OO1fhB2hcvw5bt+9k+844EhMTmTJjDh0vT3+c82D8IZLdHs4Hn3/DLd2uAZxJefEJhwBYs2ETazdspl2bFud8vuwK1Vzm4nVsxTryV69IZOXySGQExbtfyaHpC89ol79mZfzFi3BsSaZfBgqKXcs3UrJGFMWrlMUX6adB90tZ/3P6eSuFy5VIvV+7cyv2u0P7h3bso8ol9RG/D1+EnyqXNkhdl9P0PG7Z2p7qZFWtq6q1VPUld9kwt/CjjidVtaGqNlHVCVlt03r+JqOewL8yLPufu/xJnGGl1cBqnEMBaWX2Xn4A56t+60XkOLAPyDiK8B1wGbDc3cZAVY0TkXuAf4pIInAE6KOqe0WkL/CliOR3f34ozjGuPy0iws/gx/vRb8CzBJKTuaXbNdSuUZW3P/qcRvVq0/GKS4hZFsub749HRGjVrBFDn3gIgKSkAH0eGQRAkcIFGTH0SSIi/BcSJ+RzZcc/n32VmKWxxCccotNf7qH/fXfT44Zrc+35z5pr+Ahilq4gPv4QnW7uRf/7e9Oj+3VexwJCJFsgmZ3D36PG+Oecr/r9dzon122l3BN3czx2HYfdDwLFu7cnftKcHI2igWSmDxvHbeMHIn4fsV/PZv+6HVzxZA/iVmxi/fQltOp7LbU7tyQ5KcCJhKNMHvA+AGsmL6Rqu0bc99MrqMKm2SvYMGNpjuZNEQ7n9hfVcLj+kAll7kko9gBRqprodZ7MJO5eY2/08yEhOijoy70PLxeLP9o85nWETE1JLu51hEwN3PLZBZfuEdV6ZfvvzdNBeL4/w3r+Jhh+Bz4M1cJvjDG5KRAGF/W14m8umKrW9zqDMcaECruqnzHGGJPHhH6/34q/McYYE1TW8zfGGGPymHCY7W/F3xhjjAkim/BnjDHG5DE27G+MMcbkMcnW8zfGGGPyltAv/Vb8jTHGmKCyYX9jjDEmj7Fhf2NCxLKWT3sdIVNlyhzJupEHNsWV9DpCpsoWOu51hLBTP2aU1xEy1aJie68jZGpgELZx3tcv94AVf2OMMSaI1Hr+xhhjTN5ix/yNMcaYPMaO+RtjjDF5TOiXfiv+xhhjTFBZz98YY4zJY+zc/sYYY0weYxP+jDHGmDzGvupnjDHG5DHW8zfGGGPymGS1nr+5SInITGCEqk5Ls+xxoJ6qPpxJ+81Aa1Xdl2shz1OxDi2o+vz9iM/H3i+nE/fOt2e0Kdm9HZWevBNUObZqMxsfeQOAykP6UKJTK/D5OBS9jK3DPgparoLtWlPqqf6Iz8fh76aQMPardOtLDXiIAm2aA+ArmB9fyRJsbX8L+erVovSQR/EVKQSBZOI//IKj02YHLRdAqY7NqPPivYjfx67PZ7DlPz+c0abcjZdRY8BtqCpHVm1h1cNvAZC/UmkajHyI/BVLg8Lyu1/hxLa9Qc0HUOTKllQc/lfw+Tj41c/sfe+bdOsrDH2Awpc1AZz9F1G6OKua9Qx6jnDJlZmhL48k+teFlCpZgu8/ey9Xn/u6azswcuTz+H0+xn78Ja++9k669Q/+tTcPP3wPgUAyR48c5aH+A1m9eh0ATZo0YPQ7/6JosSIkJydz6WXXc/LkyRzPbBP+zMXsS+BOYFqaZXcSnFNj5z6fj2ovPcjans9yatd+Gk5+lfifFnJi3fbUJvlrVKDCIz1YffMgAglHiShdHIAiretRpE19Vl7zBAANvn+Zopc14vC834OSq/TgvxPX7ymSdu+j4hdvc2zWPBI3bk1tcuD103+Mi/W8iXz1awOQfOIEe4e+StLWHfjLlqbil+9w/LdFJB8+euG5AHxCvRH3s/T2Fzm5cz+tp73C3mmLOLZ2R2qTgjWiqPbozSzu/gxJCUeJLFMsdV3D/zzC5je/5WB0LP5C+dGc6C35fFR8/iE29X6GpLj91PphJIemL+Dk+m2pTXa9+GHq/dL33ECBhjWDnyNccp3Fzd06c1ePGxn8wuu5+rw+n4+3Rr1El2492b59F/PnTWbSjz+lFneALyd8x5gPPgXghhs68/qrw7m+ey/8fj/jPnmLvvc+xooVqyhVqiSJiYm5kjvYx/xFpAswCvADH6rqiAzr+wKvASn/+N5W1Q85B19QE5q85BvgehHJByAi1YGKQCURiRWRlSLyr4w/JCLVRWRlmscDRORZ9/4sEXlDRBaJyGoRaSMi34rIOhF5Mc3P9BKRhSKyTETeFxH/hf4yhVvU4eTmXZzcuhtNTOLAD3MpeV3bdG3K3tWZPZ9MIZDgFM+k/QkAqIIvfz4kXwS+fBFIhJ/EvQkXGgmA/I3rkbhtJ0k74iApiaNTZ1GoQ7uz/x5dOnJkykwn35YdJG11/hYE9u4ncCAeX8kSQckFUKxlbY5tiuPElj1oYoA93/9G2S5t0rWp2KsT2z+eRpK7zxL3HQKgUN1KSISfg9GxTr5jJ0k+fipo2VIUalaHU1t2kbjNeV0TJkVTrPMlZ21fvPuVJEyKDnqOcMl1Nq2bN6F4saK5/rxt27Rgw4bNbNq0lcTERL7++gdu7H5dujaHD5++OFbhwoVSP0Re2/kqYmNXs2LFKgAOHDhIcnLuHI1PPo9bVty/b+8AXYGGQE8RaZhJ069Utbl7O2fhByv+5k9S1QPAQpw3JDi9/unAv4CrgeZAGxG5+Tw3fUpVWwPvAT8AfwMaA31FpLSINADuAC5X1eY4F9C6+4J+GSBfVClO7Tx9ROLUrv1ERpVO16ZAzYoUqFmR+t+/TINJIyjWoQUARxev4fBvsTRfMpZmS8eSMHsZJ9ZvJxj85coQiDs9FB7Ys4+I8mUybRtRoRwRlaI4sXDZGevyNa6HREaStG1nUHIB5I8qxcmd+1Mfn9y5n/xRpdK1KVSrIoVqVqDlpOdpNflFSnVslro86dBRGo/9B22m/4taw3qBT4KWLUVEVGkSd51+XRPjznxdU0RWKku+KuU58tuKoOcIl1yhpmKlKLZtP/2e3b5jFxUrRp3R7uGH7mHN6l8Z8fJQHn9yGAB16tREFSb/+DkLF0xlwD/OOBqZY5LRbN+yoS2wXlU3quopYAJw04VmtOJvLkTK0D/u/7cAs1R1r6omAZ8DV57nNie6/48FflfVXap6EtgIVAE6Aa2AGBFZ5j7OlfFQifBToEYF1tz6DBv6j6TGa/3xFytE/upRFKhTmeWtH2B5qwcodnkTirRtkBuR0incpSNHp8+BDL0bf5lSlH3pKfYNe90ZpshFEuGjUM0KLL3lOX5/aBT1/92PiGKFEL+PEpc0YP1zn7LoukEUrFaeCnd2yNVsGRW/4UoSpvx6xv7zWqjmCiWj3xtHvQaXM2jISwwe9BgAERF+Lm/Xht73PMJVHW7m5pu6cnXHK3Ilj57Hf9lQCdiW5vF2d1lGPURkhYh8IyJVstqoFX9zIX4AOolIS6AQsCwbP5NE+vddgQzrU2bjJKe5n/I4AhBgXJrhrXqq+mxmTyQiD7qHEBZ9d3TzOUOdijtAvoqne9T5KpQmMW5/+ja79hP/UwyaFODUtj2c2LiTAjUqUrLLpRxZspbkYydIPnaChF+WUKRVvXM+X3YF9uzDH1U29bG/XBmSdmc+Z7Jwlw4cdYf8U0jhQpR/+0UO/udjTsauDkqmFCfjDjiT9Vz5K5bmZNyB9G12HmDftEVoUoATW/dybOMuCtaswMldBzi8crNzyCCQzL4pCynaJPif4ZLi9hNZ4fTrGhl15uuaokT39iRMzJ2h9VDNFWp27oijSuWKqY8rV6rAzp1xZ23/1Vc/cNONzmGB7Tt2MWfuAvbvP8jx4yeYMvUXWrRonOOZ4fyG/dP+nXJvD/6Jp5wEVFfVpsDPwLisfsCKv/nTVPUIMBMYizMKsBC4SkTKuMepegIZp5fvBsq5Q/j5gRvO82lnALeKSDkAESklItXOkm+MqrZW1da3FK5+zo0eXbaO/DUqkK9KOSQyglI3XcHBn2LStTk4dQFF2zl/PCJKFqVAzYqc2LqbUzv3UvTSRuD3IRF+il7WiONBGvY/+fsaIqtWIqJSFEREULhLB47NnndGu8jqVfAVLcLJ5atOL4yIoPwbz3Jk0s8cmz4nKHnSOrx0A4VqVqBA1bJIpJ9yN7dj37RF6drsnbKQEu0aORlLFaVQzQoc37KbQ0vXE1G8EJGlnePIJa9ozNG1wdlnaR1bsY781SsSWbk8EhlB8e5Xcmj6wjPa5a9ZGX/xIhxb8kfQM4RTrlATs2gZtWvXoHr1KkRGRnL77Tcx6cef0rWpXbtG6v3ru13DuvWbAPjpp9k0blyfggUL4Pf7ubL9pekmCuakgCZn+5b275R7G5NhcztwRj1TVOb0xD4AVHW/O0IK8CHO6Og52Wx/c6G+BL4D7lTVXSLyNM4HAgH+T1XTffdLVRNF5HmcDwo7gPP6q6aqq0RkKPCTiPiARJx5AVsu6LcIJLN16AfU+2I4+Hzs+2oGJ9Zuo+KAnhxbvp74n2M4NGspxa9qTuOZb6GBZLa9MI7AwcMc+HEeRS9vQuMZo0CVhFlLSfh5UdbPmc1c+195m6jRr4DPx+Hvp5G4YQsl+t/Dqd/Xpn4QKNylA0enzUr3o4Wvu4oCLZvgK16MIm5vaN+w1zi1ZkNQomkgmbWDxtJ8whDE72PnlzM5umY7NQbezuHlG9g3bTEHZi6nVIdmXBI9Ek1OZv3zn5F00Jmgtf7ZT2nxzTAQ4fDyjez8bHpQcqUTSGbn8PeoMf455yt1/53OyXVbKffE3RyPXcdht+AW796e+EnB/4AUdrnO4p/DRxCzdAXx8YfodHMv+t/fmx4ZJt7lhEAgwGOPD2Xy/32B3+fjk3FfsWrVWp4dPoBFi5fz448/0//hvnTq1J7ExCTiDyZw3/2PAxAfn8Cbo8Ywf95kVJWpU39h8pQZOZ4Zgn6SnxigjojUwPmbeSdwV9oGIlJBVXe5D28Eshzmkxz5eo0xISam0i0h+UYvU+ZI1o08sCmupNcRMlW20HGvI4Sd+jGjvI6QqYIV23sdIVNJp3Zc8MzTG6pen+2/Nz9u/b8sn09EugFv4nzVb6yqvuR2ohap6kQReQWn6CcBB4CHVfWcHSvr+RtjjDFBFOxL+qrqZGByhmXD0twfBAw6n21a8TfGGGOCKBxG1K34G2OMMUEUDl/KtOJvjDHGBFEgDMq/FX9jjDEmiGzY3xhjjMljgj3hLydY8TfGGGOCKNhX9csJVvyNMcaYIEq2YX9jjDEmbwlYz98YY4zJW+yYvzHGGJPH2Gx/Y0LEzIjCXkfI1In4Ql5HyFTh/Bd8evMcEUjO53WEsNMiRM+hf3yn9xcsyinW8zfGGGPyGJvtb4wxxuQxNuxvjDHG5DEBtdP7GmOMMXmKHfM3xhhj8hg75m+MMcbkMXaGP2OMMSaPsZ6/McYYk8fYhD9jjDEmj7Fhf2OMMSaPuSiG/UUkAMSmWTRBVUfkXCTviMgnwI+q+k2G5X2Bn1R1Zy7nqe7maZxFu0/IJHeGNn3Jwd/BzdpOVb9wH7cG+qjqo0HYdl9yYf/XuKopnYb3Rvw+VkyYxYLRk9Ktb3xrezoM7snhuIMALB3/MysmzALgqkF3Uuvq5ohP2DxnJTOe/TRouWpd1ZTrhvfG5/exdMIsfs2Qq9mtV3JNmlwx439i6YRZVL+sIdc+0yu1XZlaFfjf399mzU+Lg5at+lVN6fiss89WTpjFwnfTZ2t0a3uuHNKTI262ZeN+JtbdZ+0H3UHNq5sDMP+t71kzaUHQcoXqaxmquQCuu7YDI0c+j9/nY+zHX/Lqa++kW//gX3vz8MP3EAgkc/TIUR7qP5DVq9cB0KRJA0a/8y+KFitCcnIyl152PSdPngxqvswMfXkk0b8upFTJEnz/2Xs5/nzZdbH0/I+ravNgPqmIRKhqUjC3mcP6AiuBXC3+QdaXnP0dqgN3AV8AqOoiYFGQtt2XHN7/4hOueeEevr57BIfjDtBn4vOsn76Y/evSP+UfP85n+rDx6ZZVbFWHSq3r8vF1gwC463/DqHJpA7bNXx2UXF1f6Mtnd7/CobgDPDDxBdZMX8K+dTvStfv9x/lMHTYu3bLN81YxpttgAAoUL8zfo0eyITqWYBGf0OnFe/jm7hEc3nWAuyc9z/qfF3Mgwz5bM2k+v2TYZzWubk75xtUZ32UI/nyR3PH1EDbNXMGpI8eDkitUX8tQzAXg8/l4a9RLdOnWk+3bdzF/3mQm/fhTanEH+HLCd4z5wPnAccMNnXn91eFc370Xfr+fcZ+8Rd97H2PFilWUKlWSxMTEoOTKys3dOnNXjxsZ/MLrufJ82RUOPX/fn/1BEdksIs+JyBIRiRWR+u7ywiIyVkQWishSEbnJXd5XRCaKyC/ADBEpJCJfi8gqEflORBaISGsRuU9E3kzzPH8VkTcyef4jae7f6vZ+EZHbRGSliCwXkWh3mV9EXhORGBFZISL93OUiIm+LyBoRmQ6Uy+R5bgVaA5+LyDIRKSgindzfLdb9XfNn8nOPur/bChGZkMW+qS4ic9x9uURE2mWx78+aW0SGub/nShEZ47bN7Hc4o10mz1NWRP7ntosRkcvd5Ve521nm/h5FgRFAe3fZEyLSQUR+dNs/KyLj3N9xi4j8RURedfffVBGJPM/srURktogsFpFpIlLhXPsrOyo0r0X85t0kbNtLcmKA1ZPmU7tzq+z9sCoR+SPxR0bgzxeJP8LP0X0JFxoJgErNa3Fw827i3Vy/T5pPvezmSqNht7asn7WcpBOngpILICpln211sq2ZNJ/a12YvW+k6ldi+YA0aSCbp+En2rt5K9Q5Ng5IrVF/LUM0F0LZNCzZs2MymTVtJTEzk669/4Mbu16Vrc/hw6p9cChculHoK22s7X0Vs7GpWrFgFwIEDB0lOzp0Jb62bN6F4saK58lznQzU52zevZKf4F0zzh36ZiNyRZt0+VW0JjAYGuMuGAL+oalugI/CaiKRcUq0lcKuqXgX0Bw6qakPgGSDlX8HXQPeUggDcC4w9j99pGHCdqjYDbnSX3Q8kqGoboA3wVxGpAdwC1AMaAn2AM4quO5S+CLjbHQFR4BPgDlVtgjN68nAmOZ4GWqhqU+ChLPbNHqCzuy/vAN7K4nc8V+63VbWNe6igIHBDxt9BVY9n1i6T5xkFvOHutx7Ah+7yAcDf3P3RHjju/r5z3O2f8WENqAVcjfOafAbMdPffceD67GYHkoD/4LyPWuG8N17KYn9lqUhUSQ7vOpD6+PCuAxSNKnlGu7pd29J36svcNPpRilYoBcDOJevZOm8V/WPe5m8xb7MpOpYD64MzSFE0qhQJu/anPj50llwNurah39RXuHX0YxRzc6XV6MbLWPnDvKBkSlEkqiSHd6bfZ0XKn5mtTre29Jn2Mt3fO73P9q7aQvUOTYkokI+CJYtQpV3D1HVByRWCr2Wo5gKoWCmKbdtPb2/7jl1UrBh1RruHH7qHNat/ZcTLQ3n8yWEA1KlTE1WY/OPnLFwwlQH/yOzPYd4S0ORs37ySneJ/3P2DnnL7Ks26b93/L8YZ9gW4FnhaRJYBs4ACQFV33c+qmvLuvwKYAKCqK4EV7v0jwC/ADeKMJkSq6vmMVf4KfCIifwX8aTL1cTMtAEoDdYArgS9VNeAeT/4lG9uvB2xS1bXu43HudjJagdNb7YVTsFJyZLZvIoEPRCQW+C9OUT+Xc+XuKM4oSixOsW10lm1kp901wNtu3olAMREpgrOPR4rIo0CJbB7CmaKqiTjzR/zAVHd5LKffO9nJVA9oDPzs5hoKVM7G81+w9dOX8v7lj/NJl8FsnrOSbiP7AVCiWnlK167E6Esf5d1L/k7Vdg2p3KZebkQCYO30Jbx1+eO832UQG+fEctPIh9KtL1KuBOXqVWFD9Ipcy5Riw/SlfNjuccZfN5gtc1bSxd1nW+asZNMvy+j53XCuf/tv7Fq8Ds2l3iKE7msZqrlSjH5vHPUaXM6gIS8xeNBjAERE+Lm8XRt63/MIV3W4mZtv6srVHa/I9WyhJBnN9i07RKSLO9K7XkSePke7HiKi4sy5Oqc/PezvSpnREeD0/AEBeqT5sFBVVVMOTB3N5nY/xDnOey/w8VnapN1rBVIXqj6EUxCqAItFpLSb6e9pMtVQ1Z+ymeXPuh54B2e0I0ZEIjj7vnkC2A00wxni/lMXLReRAsC7OL3iJsAHpNk359sO5/1xaZq8lVT1iDvh8wGc3vmv7oe0rJwEUGecK1FPX/YqGYg4j0wC/J4mUxNVvfYs++NBEVkkIosWHFmXWZNUR+IOput5Fq1QKnXSVYoT8UcInHI+56yYMJOoxjUAqNulNTuXrifx2EkSj51k08zlVGxZ+9x7I5sOxx2geIXSqY+LZZLreJpcSyfMpIKbK0XD6y/hj2mLSE4KBCVTiiNxBylaMf0+O7L77Pss9suZlG9yOtuCtyfyadchfHP3v0CEgxvjgpcrBF/LUM0FsHNHHFUqV0x9XLlSBXbuPPvr8dVXP3DTjc5hge07djFn7gL27z/I8eMnmDL1F1q0OOcc5Yueqmb7lhUR8ePUkq44HcOeInJGB9E9/PoYTgc3Sxda/DMzDfh7yjFkEWlxlna/Are7bRoCTVJWqOoCnOJ9F/DlWX5+t4g0EBEfzjA47rZqqeoCVR0G7HW3Mw14OM2x5brucHs0cIc4cwIq4AzFZ+YwkHJgaQ1QXURS/uX1BmanbexmqqKqM4GngOJAkXPsm+LALrcw9ub0iMXZnC13SrHc5/bQbz3L73Cudmn9BPw9ze/V3P1/LVWNVdV/ATFA/Qzb/zOym30NUFZELnOzRIpIpqMbqjpGVVurautLitQ555PvWr6RkjWiKF6lLL5IPw26X8r6n5eka1O4XInU+7U7t2K/O+x6aMc+qlxSH/H78EX4qXJpg9R1F2rH8o2UqhFFCTdXo+6Xsvbn9LP1i6TJVbdzK/ZleO7GN7bj94nBHfIHiFu+kRI1oijmZqvX/VI2nGOf1Uqzz8QnFChRBIAy9atQtkEVNgdpMmKovpahmgsgZtEyateuQfXqVYiMjOT2229i0o/p+0e1a5/+4HZ9t2tYt34TAD/9NJvGjetTsGAB/H4/V7a/NN1EwbwoWTXbt2xoC6xX1Y2qegpnxPymTNq9APwLOJGdjWZntn9Bd3g1xVRVPeuwgxvgTWCFWwQ3kfnx5HeBcSKyCvgD+B1IO4Pla6C5qh7M5GfBOcb8I06BX4RTXME5jl4Hp4c4A1iOMwRfHVjiFt69wM3AdzjDy6uArcDZ/kJ+ArwnIseBy3BGJP7r9uZjgIzfMfEDn4lIcTfHW6oaLyJn2zfvAv8TkT44w+FZjZBkmtt9jg9wZsbHudnO9jucrV1ajwLviMgKnPdKNM78hcdFpCNOr/13YIp7PyAiy93nWprF75DOeWa/FXjL3b8ROPv09/N5vjOeP5DM9GHjuG38QMTvI/br2exft4MrnuxB3IpNrJ++hFZ9r6V255YkJwU4kXCUyQPeB2DN5IVUbdeI+356BVXYNHsFG2ac169/zlxThn3C3eOfQvw+ln09m73rdtDhyR7sXLGJtdOX0LbvddRNk+uHAaffjsUrl6FYxVJsDtKs8IzZfnlmHD0+HYjP72PlV7PZv3YH7Z7swe7YTWz4eQkt7r2WWinZ4o8y7R/OPvNFRnDn/54B4OTh40x+bDQaCM6wfyi/lqGYCyAQCPDY40OZ/H9f4Pf5+GTcV6xatZZnhw9g0eLl/Pjjz/R/uC+dOrUnMTGJ+IMJ3Hf/4wDExyfw5qgxzJ83GVVl6tRfmDxlRtCyncs/h48gZukK4uMP0enmXvS/vzc9MkxU9EKQZ/tXAralebwduCRtAxFpidPh/D8R+Wd2NirZGXbICe5QRqSqnhCRWsB0oJ77yQZxZoq/oaq58y4yF7VXq/UKye/enAjRrwQV1jO+/BESAqEZK6QN3jXT6wiZOr5zjtcRMhVZpuYFv8vKF6+f7X/Yew6t6Qc8mGbRGFUdk/LA/cZTF1V9wH3cG7hEVR9xH/tw5n31VdXNIjILGOB+3fqsvDzDXyFgpjsUL0B/VT0lIiWAhcByK/zGGGPCzfnM4ncL/ZhzNNmBc/g6RWV3WYqiOJOgZ7lHlKOAiSJy47k+AHhW/FX1MM7ktozL44G6uR7IGGOMCYIgn+EvBqjjfj19B3Anznw4AFQ1ASiT8jgcev7GGGPMRSeYh9NVNUlEHsGZMO4Hxqrq7yLyPLBIVSf+me1a8TfGGGOCKLvf388uVZ0MTM6wbNhZ2nbIzjat+BtjjDFB5NVE+vNhxd8YY4wJIi9P25tdVvyNMcaYILpYLulrjDHGmGyyYX9jjDEmjwnyGf5yhBV/Y4wxJois52+MMcbkMeFQ/D07t78x4UpEHkx77u1QYbnOT6jmgtDNZrkuHjlxSV9jLnYPZt3EE5br/IRqLgjdbJbrImHF3xhjjMljrPgbY4wxeYwVf2POX6geW7Rc5ydUc0HoZrNcFwmb8GeMMcbkMdbzN8YYY/IYK/7GGGNMHmPF3xhjjMljrPgbY4JORAp4nSGciEghEXlGRD5wH9cRkRu8zhWqRKS8iHwkIlPcxw1F5H6vc4UTm/BnTBZEpCzwV6A6aU6Jrar3eZUpLRGpBFQjfbZo7xKBiKwHdgNz3NtcVU3wMhOAiAhwN1BTVZ8XkapAlKou9DjXV8BioI+qNhaRQsBvqtrc41yhur+mAB8DQ1S1mYhEAEtVtYmXucKJFX9jsiAiv+EUsMVAIGW5qv7Ps1AuEfkXcAewitPZVFVv9C6Vwy0U7YHLgW5AfAgUs9FAMnC1qjYQkZLAT6raxuNci1S1tYgsVdUW7rLlqtrM41yhur9iVLVNhv21zOv3VzixC/sYk7VCqvqU1yHO4magnqqe9DpIWiJSGafotweaAb8Dcz0N5bhEVVuKyFIAVT0oIvm8DgWcEpGC4FwLVkRqAaHwmobq/joqIqU5vb8uBTwfWQonVvyNydqPItJNVSd7HSQTG4FIQqNQpLUViAFeVtWHvA6TRqKI+DldNMri9Gy9NhyYClQRkc9xPjj19TSRI1T315PARKCWiPwKlAVu8zZSeLFhf2OyICKHgcLAKfcmOEPrxTzM9B+cP8iVcHrWM0jzAUBVH/UoGgAi0gy4ArgSqAqsA2ar6kce57ob5zBJS2AccCswVFX/62UuALcneynO+2u+qu7zOFLI7i8RyY9zmKsezv5aA/hCbQQslFnxNyYMicg951qvquNyK8vZiEgRnA8A7YFeAKpazdNQgIjUBzrhFI0Zqrra40iIyOXAMlU9KiK9cIrtKFXd4nG0UN1fS1S1ZVbLzNlZ8TcmC2lmPNdQ1RdEpApQwesZz6FMRBYB+YGUyZJzQqSQ1QK2q+pJEekANAXGq2q8x7lW4IzgNMWZxf4RcLuqXuVlLgB3kl8V0n+bZIlHWaJwRrs+A+7C+UACUAx4T1Xre5ErHFnxNyYLoTrjGUBEYnGPx6aRACwCXlTV/bmfyjk2rKp7vXjucxGRZUBrnK9t/h/OceNGqtrNw1ipvVYRGQbsUNWPQqEnKyIv4Mw92MDp95mq6tUe5bnHzdMa5z2e4jDwiap+60WucGQT/ozJWqjOeAaYgnPs8wv38Z1AISAO+ATo7k0sTonISJxj/gCzgedD4Lv+yaqaJCJ/Ad5W1f+kvK4eOywig4DeQHsR8eFM5PTa7UAtVT3ldRBIPZw1TkR6hMJXbcOZFX9jshaqM54BrsnQO4xN04vs5VkqGAusxCke4BS1j4G/eJbIkSgiPYE+nP5gFApF9g6cYez7VDXOPUfCax5nAuc1LAHs8ThHOqr6PxG5HmgEFEiz/HnvUoUXK/7GZO0t4DugvIi8hDvj2dtIqfwi0jZl/oGItAH87rok72JRS1V7pHn8nDvk7rV7gYeAl1R1k4jUAD71OBNuwf8caOOe1nehqo73OhfwCrBURFaS/tsknp5ESkTewxnh6gh8iPNv0ubgnAc75m9MNqSZ8QzwSyjMeIbUYj8WKIIz+ekQ8ADOSXWuV9WvPco1D/inqs51H18OvK6ql3mRJy33kE1d9+EaVU30Mg+AiNyO09OfhfM6tsfZf994nOt34H0gljSjXao627NQOBMkVbVpmv8XAaaoansvc4UT6/kbkz2FcHrUChT0OEsqVY0BmohIcfdx2mPqnhR+10PA+JRcwEHgnF9PzA3uDP9xwGacIltFRO7x+loIwBCgjarugdRDS9MBT4s/cExV3/I4Q2aOu/8/JiIVgf1ABQ/zhB0r/sZkwZ2BfRvwP5yC8bGI/FdVX/QwUy9V/UxEnsywHABVHelJMJeqLgeaiUgx9/EhEXkcWOFlLuDfwLWqugZAROoCXwKtPE3lnKAm7XH1/YTGVVfniMgrON+KSDvs78lX/dL4UURK4IyWLMH5UP6hp4nCjA37G5MFEVkDNFPVE+7jgjgnZKnnYaZ+qvq+iAzPbL2qPpfbmbIiIltVtarHGVaoatOsluU2EXkN5zv+X7qL7gBWeH1NCRGZmcliz77qlxn3bH8FQuCbJGHFir8xWXD/AN6SciIYt8fxbSj9AQwHIrJNVat4nGEszrHrz9xFdwN+DYHLM4tID5xz+oNzUqTvvMwTytxv31zPmZfZ9nTEK5xY8TcmCyLyPdAG+NlddA3OzOLt4M159EXknMdhvT63f2ZCpOefH/gbzmmHwTn74Lt2TvjMuYe8zuD1V+pEZDJwgjMnIobciFeosmP+xmRtGs6FcxTn63OZDYXmtsVp7j+Hc1U4z7kXQcqsRyGEwERJt8iPdG+ey2J/eXrxKNfRNPcLADcAofBNl8peH6oJd9bzN+YsRCQCeBm4D9iC8we5Ks7JagaHwlfEAERkqaq28DpHKDvLaZBTWSHJHnfkZJqqdvA4x79wLjL0k5c5wpn1/I05u9eAojgX9DkM4M5ef91d97h30dKxT/BZ+wtQHtiWYXkVnFMhe8I9T0MZVZ2SYXlXYI+qLs78Jz1TCKjsdQhgPvCdexrkREJnpCRsWM/fmLMQkXVAXc3wj8SdbPSHqtbxJll6oXABmFAnIj8Cg1Q1NsPyJsDLqurJNRBE5Bfg3oxXPBSRasDHXk8qzTBi4gfK4lyj4W3vUoGIbAJuAmIz/vs02WM9f2POTjP7w6KqARHx9A9OhmPFhUTkUMoqrAeUmfIZCz+AqsaKSHUP8qQomtmljlV1i4iU8SJQBjekuZ8E7FZVL08bnWIbsNIK/59nxd+Ys1slIn0ynmPdvWDOHx5lAkBVi3r5/GGoxDnWeTkRseQ51hXKtRQZiEgp9+7hDKuKiQiqeiC3M2WwEZglIlNIf/KhkJjIGQ6s+Btzdn8DvhWR+zg9u741TrG4xbNU5s9YJCJ/VdUP0i4UkQdI/82J3DbdvVjU0JRerDinaXwO+MXDXItxRpYkk3UK1MzdOGfY5N7yuTdznuyYvzFZEJGrcS4dCrBKVWd4mcecPxEpj3NlxlOk/yCXD+cETp5M+hORwjinpW0LLHMXNwMWAQ+o6hEvcpmLnxV/Y0yeISIdgcbuw99V1cvedSoRqcnpD5i/q+pGL/OkJSI3Ale6D2ep6o8eZnlTVR8XkUlk8i0Xry81HE6s+BtjjMmUiIzAObvl5+6inkCMqg72KE8rVV0sIldltt7rSw2HEyv+xhhjMiUiK4DmqprsPvYDS70+KZKIPKaqo7JaZs4uFC4ZaYwxJnSVSHO/uFchMrgnk2V9cztEOLPZ/sYY4xERKaaqh9J8tS4tBQ6pasCDXO/gXF74ZWCJiMzCmfl/JfB0budJk6sncBdQQ0QmpllVDPD664dhxYq/McZ45wucE+mc7at1RUTkAw+Osa/FOYV1BZyLWm3G+TbCU159M8L1G7ALKAP8O83yw8AKTxKFKTvmb4wxIco9xr5SVRt49PzVgDvdW0GcDytfquo6L/KkyVUYOK6qySJSF6gPTAmVi22FAyv+xhjjERE55zUZVHVJbmXJioi0AMYCTVXV73GWxUB7nDMk/grEAKdU9W4vc4UTG/Y3xhjvpAxdF8A56dBynKH/pjgn+rnMo1xA6mWtu+L0/DsBs4BnPYyUQlT1mIjcD7yrqq+KyDKvQ4UTK/7GGOMRVe0IICLfAi1TLj4kIo3xsMiKSGec7/R3AxYCE4AHVfWoV5kyEBG5DLgbuN9d5uloRLix4m+MMd6rl/aqg6q6UkQ8Oc7vGoRzfP8fqnrQwxxn8zhOxu9U9Xf3DIkzvY0UXuyYvzHGeExEvgSOAp+5i+4GiqhqT+9ShT4RKaSqx7zOEY7sJD/GGOO9e4Hfgcfc2+/YSWvOSkQuE5FVuJfWFpFmIvKux7HCivX8jTEmxIhIe+BOVf2b11lCkYgsAG4FJqpqC3fZSlVtfO6fNCnsmL8xxoQA96t0PYHbca5V/623iUKbqm4TSXdOpFw/E2I4s+JvjDEecU9Q09O97QO+whmR7ehpsNC3TUTaASoikTiHSlZ7nCms2LC/McZ4RESSgTnA/aq63l22UVVrepsstIlIGWAUcA3OeRF+Ah5T1f2eBgsj1vM3xhjv/AXnBDozRWQqzvfpM57f32SgqvtwvhFh/iTr+RtjjMfcc9XfhDP8fzUwHuc77D95GsxctKz4G2NMCBGRksBtwB2q2snrPObiZMXfGGOMyWPsmL8xxpiwIyLXA41wLooEgKo+712i8GJn+DPGGBNWROQ94A7g7zgTJG8DqnkaKszYsL8xxpiwIiIrVLVpmv8XAaaoanuvs4UL6/kbY4wJN8fd/x8TkYpAIlDBwzxhx475G2OMCTc/ikgJ4DVgCaDAh54mCjM27G+MMSasiEh+VT2Zch9n0t+JlGUmazbsb4wxJtzMS7mjqidVNSHtMpM1G/Y3xhgTFkQkCqgEFHSvgphyKuRiQCHPgoUhK/7GGGPCxXVAX6AyMDLN8sPAYC8ChSs75m+MMSasiEgPVf2f1znCmRV/Y4wxYcfO8HdhbMKfMcaYsGJn+Ltw1vM3xhgTVuwMfxfOev7GGGPCjZ3h7wLZbH9jjDHhxs7wd4Fs2N8YY0zYSjnDn3uiH5NNVvyNMcaEBRH5y7nWq+q3uZUl3NmwvzHGmHDR3f1/OaAd8Iv7uCPwG2DFP5us+BtjjAkLqnovgIj8BDRU1V3u4wrAJx5GCzs2298YY0y4qZJS+F27gapehQlH1vM3xhgTbmaIyDTgS/fxHcB0D/OEHZvwZ4wxJuyIyC3Ale7DaFX9zss84caKvzHGGJPH2DF/Y4wxJo+x4m+MMcbkMVb8jTHGmDzGZvsbY4wJCyISi3Me/zNWAaqqTXM5UtiyCX/GGGPCgohUO9d6Vd2SW1nCnRV/Y4wxJo+xY/7GGGPCiohcKiIxInJERE6JSEBEDnmdK5xY8TfGGBNu3gZ6AuuAgsADwDueJgozVvyNMcaEHVVdD/hVNaCqHwNdvM4UTmy2vzHGmHBzTETyActE5FVgF9aZPS+2s4wxxoSb3jj16xHgKFAF6OFpojBjs/2NMcaEHREpCFRV1TVeZwlH1vM3xhgTVkSkO7AMmOo+bi4iEz0NFWas+BtjjAk3zwJtgXgAVV0G1PAuTvix4m+MMSbcJKpqQoZldgz7PNhsf2OMMeHmdxG5C/CLSB3gUeA3jzOFFev5G2OMCTd/BxoBJ4EvgUPA414GCjc2298YY0zYEhE/UFhV7fS+58F6/sYYY8KKiHwhIsVEpDAQC6wSkX96nSucWPE3xhgTbhq6Pf2bgSk4M/17e5oozFjxN8YYE24iRSQSp/hPVNVEbLb/ebHib4wxJty8D2wGCgPRIlINZ9KfySab8GeMMSasiYjgXOEvyess4cKKvzHGGJPH2LC/McYYk8dY8TfGGGPyGDu9rzHGmLDizvR/GLjSXTQbeM+d9W+ywY75G2OMCSsi8iEQCYxzF/UGAqr6gHepwosVf2OMMWFFRJararOslpmzs2P+xhhjwk1ARGqlPBCRmkDAwzxhx475G2OMCTf/BGaKyEZAgGrAfd5GCi827G+MMSasiEh+92499/9rAFT1pDeJwo8Vf2OMMWFFRJaoasuslpmzs2F/Y4wxYUFEooBKQEERaYEz5A9QDCjkWbAwZMXfGGNMuLgO6AtUBv7N6eJ/CBjsUaawZMP+xhhjwoqI9FDV/3mdI5xZ8TfGGGPyGPuevzHGGJPHWPE3xhhj8hib8GeMMSYsiMhfzrVeVb/NrSzhzoq/McaYcNHd/X85oB3wi/u4I/AbYMU/m6z4G2OMCQuqei+AiPwENFTVXe7jCsAnHkYLO3bM3xhjTLipklL4XbuBql6FCUfW8zfGGBNuZojINOBL9/EdwHQP84Qd+56/McaYsCMitwBXug+jVfU7L/OEGyv+xhhjwo6IVAPqqOp0ESkE+FX1sNe5woUd8zfGGBNWROSvwDfA++6iSsD3ngUKQ1b8jTHGhJu/AZfjXNAHVV2H8/U/k01W/I0xxoSbk6p6KuWBiEQAdgz7PFjxN8YYE25mi8hgoKCIdAb+C0zyOFNYsQl/xhhjwoqI+ID7gWsBAaYBH6oVtGyz4m+MMSZsiUgpoLKqrvA6SzixYX9jjDFhRURmiUgxt/AvBj4QkTe8zhVOrPgbY4wJN8VV9RDwF2C8ql4CdPI4U1ix4m+MMSbcRLgX87kd+NHrMOHIir8xxphw8zzOJL/1qhojIjWBdR5nCis24c8YY4zJY+yqfsYYY8KKiHxMJif1UdX7PIgTlqz4G2OMCTdpj/MXAG4BdnqUJSzZsL8xxpiw5p70Z66qtvM6S7iwCX/GGGPCXR3swj7nxYb9jTHGhBUROUz6Y/5xwFMexQlLNuxvjDHG5DE27G+MMcbkMVb8jTHGmDzGir8xxhiTx1jxN8YYE1ZE5N8i0sjrHOHMir8xxphwsxoYIyILROQhESnudaBwY7P9jTHGhCURqQfcC/QEfgU+UNWZ3qYKD9bzN8YYE3ZExA/Ud2/7gOXAkyIywdNgYcJ6/sYYY8KKiLwBdAdmAB+p6sI069aoaj3PwoUJO8OfMcaYcLMCGKqqRzNZ1za3w4Qj6/kbY4wJKyLSMpPFCcAWVU3K7TzhyIq/McaYsCIi84GWOCMAAjQGfgeKAw+r6k8exgsLNuHPGGNMuNkJtFDV1qraCmgBbAQ6A696mixMWPE3xhgTbuqq6u8pD1R1FVBfVTd6mCms2IQ/Y4wx4WaViIwGUr7Wd4e7LD+Q6F2s8GHH/I0xxoQVESkI9AeucBf9CrwLnAAKqeoRr7KFCyv+xhhjwoZ7cp/pqtrR6yzhzI75G2OMCRuqGgCS7Xz+F8aO+RtjjAk3R4BYEfkZSD3Rj6o+6l2k8GLF3xhjTLj51r2ZP8mO+RtjjAk77qS/qqq6xuss4ciO+RtjjAkrItIdWAZMdR83F5GJnoYKM1b8jTHGhJtncS7gEw+gqsuAmt7FCT9W/I0xxoSbRFVNyLAs2ZMkYcom/BljjAk3v4vIXYBfROoAjwK/eZwprFjP3xhjTLj5O9AIOAl8CRwCHvcyULix2f7GGGNMHmPD/sYYY8KKiNQFBgDVSVPHVPVqrzKFG+v5G2OMCSsishx4D1gMBFKWq+piz0KFGSv+xhhjwoqILFbVVl7nCGdW/I0xxoQVEXkW2AN8hzPpDwBVPeBVpnBjxd8YY0xYEZFNmSxWVbUT/WSTFX9jjDEmj7Hv+RtjjAkLIjIwzf3bMqx7OfcThS8r/sYYY8LFnWnuD8qwrktuBgl3VvyNMcaECznL/cwem3Ow4m+MMSZc6FnuZ/bYnINN+DPGGBMWRCQAHMXp5RcEjqWsAgqoaqRX2cKNFX9jjDEmj7Fhf2OMMSaPseJvjDHG5DFW/I0xxpg8xoq/McYYk8dY8TfGGGPyGCv+xhhjTB7z//3EN4A6s5OIAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(correlation_seal, annot=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T21:07:49.421130Z",
     "iopub.status.busy": "2022-12-08T21:07:49.420721Z",
     "iopub.status.idle": "2022-12-08T21:07:50.019753Z",
     "shell.execute_reply": "2022-12-08T21:07:50.018642Z",
     "shell.execute_reply.started": "2022-12-08T21:07:49.421100Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(correlation_added, annot=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T21:10:20.694710Z",
     "iopub.status.busy": "2022-12-08T21:10:20.694311Z",
     "iopub.status.idle": "2022-12-08T21:10:21.263572Z",
     "shell.execute_reply": "2022-12-08T21:10:21.262383Z",
     "shell.execute_reply.started": "2022-12-08T21:10:20.694678Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(correlation_cons, annot=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-08T21:13:32.507681Z",
     "iopub.status.busy": "2022-12-08T21:13:32.506363Z",
     "iopub.status.idle": "2022-12-08T21:13:33.063972Z",
     "shell.execute_reply": "2022-12-08T21:13:33.062668Z",
     "shell.execute_reply.started": "2022-12-08T21:13:32.507621Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(correlation_cons_sp, annot=True);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}