8. Spatial Econometrics.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e2fe7cc6",
   "metadata": {},
   "source": [
    "# 8. Spatial Econometrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b7061f7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import esda\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "from geopandas import GeoDataFrame\n",
    "import libpysal as lps\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from shapely.geometry import Point\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8de918d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "covidvisual = pd.read_excel('covidvisualApril5th2023.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9f7a68bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .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>Country</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>HDI rank</th>\n",
       "      <th>Human Development Index 2021 (HDI)</th>\n",
       "      <th>Life expectancy at birth</th>\n",
       "      <th>Expected years of schooling</th>\n",
       "      <th>Mean years of schooling</th>\n",
       "      <th>Gross national income (GNI) per capita</th>\n",
       "      <th>...</th>\n",
       "      <th>NewRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>Serious,Critical</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>Population</th>\n",
       "      <th>Continent</th>\n",
       "      <th>New Cases/1M pop</th>\n",
       "      <th>New Deaths/1M pop</th>\n",
       "      <th>Active Cases/1M pop</th>\n",
       "      <th>covid_mortality_rate (per 100000)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Albania</td>\n",
       "      <td>ALB</td>\n",
       "      <td>41.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>67</td>\n",
       "      <td>0.796</td>\n",
       "      <td>76.4626</td>\n",
       "      <td>14.448000</td>\n",
       "      <td>11.286455</td>\n",
       "      <td>14131.110390</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,709</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,941,032</td>\n",
       "      <td>2866374</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>596</td>\n",
       "      <td>125.663992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>DZA</td>\n",
       "      <td>28.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>91</td>\n",
       "      <td>0.745</td>\n",
       "      <td>76.3767</td>\n",
       "      <td>14.626896</td>\n",
       "      <td>8.069284</td>\n",
       "      <td>10800.225460</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81,825</td>\n",
       "      <td>NaN</td>\n",
       "      <td>230,861</td>\n",
       "      <td>45350148</td>\n",
       "      <td>Africa</td>\n",
       "      <td>0.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,804</td>\n",
       "      <td>15.173049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Angola</td>\n",
       "      <td>AGO</td>\n",
       "      <td>-12.5</td>\n",
       "      <td>18.5</td>\n",
       "      <td>148</td>\n",
       "      <td>0.586</td>\n",
       "      <td>61.6434</td>\n",
       "      <td>12.172100</td>\n",
       "      <td>5.417391</td>\n",
       "      <td>5465.617791</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,499,795</td>\n",
       "      <td>35027343</td>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>5.518546</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 43 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Country Country Code  Latitude  Longitude  HDI rank  \\\n",
       "0  Albania          ALB      41.0       20.0        67   \n",
       "1  Algeria          DZA      28.0        3.0        91   \n",
       "2   Angola          AGO     -12.5       18.5       148   \n",
       "\n",
       "   Human Development Index 2021 (HDI)  Life expectancy at birth  \\\n",
       "0                               0.796                   76.4626   \n",
       "1                               0.745                   76.3767   \n",
       "2                               0.586                   61.6434   \n",
       "\n",
       "   Expected years of schooling  Mean years of schooling  \\\n",
       "0                    14.448000                11.286455   \n",
       "1                    14.626896                 8.069284   \n",
       "2                    12.172100                 5.417391   \n",
       "\n",
       "   Gross national income (GNI) per capita  ...  NewRecovered  ActiveCases  \\\n",
       "0                            14131.110390  ...           NaN        1,709   \n",
       "1                            10800.225460  ...           NaN       81,825   \n",
       "2                             5465.617791  ...           NaN           41   \n",
       "\n",
       "   Serious,Critical  TotalTests  Population Continent New Cases/1M pop  \\\n",
       "0               NaN   1,941,032     2866374    Europe              NaN   \n",
       "1               NaN     230,861    45350148    Africa              0.1   \n",
       "2               NaN   1,499,795    35027343    Africa              NaN   \n",
       "\n",
       "   New Deaths/1M pop Active Cases/1M pop  covid_mortality_rate (per 100000)  \n",
       "0                NaN                 596                         125.663992  \n",
       "1                NaN               1,804                          15.173049  \n",
       "2                NaN                   1                           5.518546  \n",
       "\n",
       "[3 rows x 43 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covidvisual.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9dcaa116",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(149, 43)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covidvisual.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7c131c96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Country', 'Country Code', 'Latitude', 'Longitude', 'HDI rank',\n",
       "       'Human Development Index 2021 (HDI)', 'Life expectancy at birth',\n",
       "       'Expected years of schooling', 'Mean years of schooling',\n",
       "       'Gross national income (GNI) per capita', 'GDP 2021 (US$)',\n",
       "       'GDP per capita 2021 (US$)', 'GDP growth 2021 (annual %)',\n",
       "       'Inflation Rate 2021 (%)', 'Unemployment Rate 2021 (%)', 'Region',\n",
       "       'IncomeGroup', 'total_vaccinations', 'date', 'people_vaccinated',\n",
       "       'people_fully_vaccinated', 'daily_vaccinations_raw',\n",
       "       'daily_vaccinations', 'total_vaccinations_per_hundred',\n",
       "       'people_vaccinated_per_hundred', 'people_fully_vaccinated_per_hundred',\n",
       "       'daily_vaccinations_per_million', 'Country,Other', 'TotalCases',\n",
       "       'NewCases', 'TotalDeaths', 'NewDeaths', 'TotalRecovered',\n",
       "       'NewRecovered', 'ActiveCases', 'Serious,Critical', 'TotalTests',\n",
       "       'Population', 'Continent', 'New Cases/1M pop', 'New Deaths/1M pop',\n",
       "       'Active Cases/1M pop', 'covid_mortality_rate (per 100000)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covidvisual.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b30ade36",
   "metadata": {},
   "outputs": [],
   "source": [
    "import shapely\n",
    "shapely.speedups.disable()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5c076abc",
   "metadata": {},
   "outputs": [],
   "source": [
    "world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b3dd4f18",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pop_est</th>\n",
       "      <th>continent</th>\n",
       "      <th>name</th>\n",
       "      <th>iso_a3</th>\n",
       "      <th>gdp_md_est</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>920938</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>FJI</td>\n",
       "      <td>8374.0</td>\n",
       "      <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>53950935</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>150600.0</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>603253</td>\n",
       "      <td>Africa</td>\n",
       "      <td>W. Sahara</td>\n",
       "      <td>ESH</td>\n",
       "      <td>906.5</td>\n",
       "      <td>POLYGON ((-8.66559 27.65643, -8.66512 27.58948...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35623680</td>\n",
       "      <td>North America</td>\n",
       "      <td>Canada</td>\n",
       "      <td>CAN</td>\n",
       "      <td>1674000.0</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>326625791</td>\n",
       "      <td>North America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>USA</td>\n",
       "      <td>18560000.0</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -120.0000...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>7111024</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Serbia</td>\n",
       "      <td>SRB</td>\n",
       "      <td>101800.0</td>\n",
       "      <td>POLYGON ((18.82982 45.90887, 18.82984 45.90888...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>642550</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Montenegro</td>\n",
       "      <td>MNE</td>\n",
       "      <td>10610.0</td>\n",
       "      <td>POLYGON ((20.07070 42.58863, 19.80161 42.50009...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>1895250</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Kosovo</td>\n",
       "      <td>-99</td>\n",
       "      <td>18490.0</td>\n",
       "      <td>POLYGON ((20.59025 41.85541, 20.52295 42.21787...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>1218208</td>\n",
       "      <td>North America</td>\n",
       "      <td>Trinidad and Tobago</td>\n",
       "      <td>TTO</td>\n",
       "      <td>43570.0</td>\n",
       "      <td>POLYGON ((-61.68000 10.76000, -61.10500 10.890...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>13026129</td>\n",
       "      <td>Africa</td>\n",
       "      <td>S. Sudan</td>\n",
       "      <td>SSD</td>\n",
       "      <td>20880.0</td>\n",
       "      <td>POLYGON ((30.83385 3.50917, 29.95350 4.17370, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>177 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       pop_est      continent                      name iso_a3  gdp_md_est  \\\n",
       "0       920938        Oceania                      Fiji    FJI      8374.0   \n",
       "1     53950935         Africa                  Tanzania    TZA    150600.0   \n",
       "2       603253         Africa                 W. Sahara    ESH       906.5   \n",
       "3     35623680  North America                    Canada    CAN   1674000.0   \n",
       "4    326625791  North America  United States of America    USA  18560000.0   \n",
       "..         ...            ...                       ...    ...         ...   \n",
       "172    7111024         Europe                    Serbia    SRB    101800.0   \n",
       "173     642550         Europe                Montenegro    MNE     10610.0   \n",
       "174    1895250         Europe                    Kosovo    -99     18490.0   \n",
       "175    1218208  North America       Trinidad and Tobago    TTO     43570.0   \n",
       "176   13026129         Africa                  S. Sudan    SSD     20880.0   \n",
       "\n",
       "                                              geometry  \n",
       "0    MULTIPOLYGON (((180.00000 -16.06713, 180.00000...  \n",
       "1    POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...  \n",
       "2    POLYGON ((-8.66559 27.65643, -8.66512 27.58948...  \n",
       "3    MULTIPOLYGON (((-122.84000 49.00000, -122.9742...  \n",
       "4    MULTIPOLYGON (((-122.84000 49.00000, -120.0000...  \n",
       "..                                                 ...  \n",
       "172  POLYGON ((18.82982 45.90887, 18.82984 45.90888...  \n",
       "173  POLYGON ((20.07070 42.58863, 19.80161 42.50009...  \n",
       "174  POLYGON ((20.59025 41.85541, 20.52295 42.21787...  \n",
       "175  POLYGON ((-61.68000 10.76000, -61.10500 10.890...  \n",
       "176  POLYGON ((30.83385 3.50917, 29.95350 4.17370, ...  \n",
       "\n",
       "[177 rows x 6 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b91a2968",
   "metadata": {},
   "outputs": [],
   "source": [
    "world.drop(['pop_est', 'continent', 'gdp_md_est'], axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7a660d03",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>geometry</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fiji</td>\n",
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       "      <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>W. Sahara</td>\n",
       "      <td>ESH</td>\n",
       "      <td>POLYGON ((-8.66559 27.65643, -8.66512 27.58948...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "        name iso_a3                                           geometry\n",
       "0       Fiji    FJI  MULTIPOLYGON (((180.00000 -16.06713, 180.00000...\n",
       "1   Tanzania    TZA  POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...\n",
       "2  W. Sahara    ESH  POLYGON ((-8.66559 27.65643, -8.66512 27.58948..."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4cfe7123",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>HDI rank</th>\n",
       "      <th>Human Development Index 2021 (HDI)</th>\n",
       "      <th>Life expectancy at birth</th>\n",
       "      <th>Expected years of schooling</th>\n",
       "      <th>Mean years of schooling</th>\n",
       "      <th>Gross national income (GNI) per capita</th>\n",
       "      <th>...</th>\n",
       "      <th>NewRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>Serious,Critical</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>Population</th>\n",
       "      <th>Continent</th>\n",
       "      <th>New Cases/1M pop</th>\n",
       "      <th>New Deaths/1M pop</th>\n",
       "      <th>Active Cases/1M pop</th>\n",
       "      <th>covid_mortality_rate (per 100000)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Albania</td>\n",
       "      <td>ALB</td>\n",
       "      <td>41.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>67</td>\n",
       "      <td>0.796</td>\n",
       "      <td>76.4626</td>\n",
       "      <td>14.448000</td>\n",
       "      <td>11.286455</td>\n",
       "      <td>14131.110390</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,709</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,941,032</td>\n",
       "      <td>2866374</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>596</td>\n",
       "      <td>125.663992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>DZA</td>\n",
       "      <td>28.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>91</td>\n",
       "      <td>0.745</td>\n",
       "      <td>76.3767</td>\n",
       "      <td>14.626896</td>\n",
       "      <td>8.069284</td>\n",
       "      <td>10800.225460</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81,825</td>\n",
       "      <td>NaN</td>\n",
       "      <td>230,861</td>\n",
       "      <td>45350148</td>\n",
       "      <td>Africa</td>\n",
       "      <td>0.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,804</td>\n",
       "      <td>15.173049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Angola</td>\n",
       "      <td>AGO</td>\n",
       "      <td>-12.5</td>\n",
       "      <td>18.5</td>\n",
       "      <td>148</td>\n",
       "      <td>0.586</td>\n",
       "      <td>61.6434</td>\n",
       "      <td>12.172100</td>\n",
       "      <td>5.417391</td>\n",
       "      <td>5465.617791</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,499,795</td>\n",
       "      <td>35027343</td>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>5.518546</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 43 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Country Country Code  Latitude  Longitude  HDI rank  \\\n",
       "0  Albania          ALB      41.0       20.0        67   \n",
       "1  Algeria          DZA      28.0        3.0        91   \n",
       "2   Angola          AGO     -12.5       18.5       148   \n",
       "\n",
       "   Human Development Index 2021 (HDI)  Life expectancy at birth  \\\n",
       "0                               0.796                   76.4626   \n",
       "1                               0.745                   76.3767   \n",
       "2                               0.586                   61.6434   \n",
       "\n",
       "   Expected years of schooling  Mean years of schooling  \\\n",
       "0                    14.448000                11.286455   \n",
       "1                    14.626896                 8.069284   \n",
       "2                    12.172100                 5.417391   \n",
       "\n",
       "   Gross national income (GNI) per capita  ...  NewRecovered  ActiveCases  \\\n",
       "0                            14131.110390  ...           NaN        1,709   \n",
       "1                            10800.225460  ...           NaN       81,825   \n",
       "2                             5465.617791  ...           NaN           41   \n",
       "\n",
       "   Serious,Critical  TotalTests  Population Continent New Cases/1M pop  \\\n",
       "0               NaN   1,941,032     2866374    Europe              NaN   \n",
       "1               NaN     230,861    45350148    Africa              0.1   \n",
       "2               NaN   1,499,795    35027343    Africa              NaN   \n",
       "\n",
       "   New Deaths/1M pop Active Cases/1M pop  covid_mortality_rate (per 100000)  \n",
       "0                NaN                 596                         125.663992  \n",
       "1                NaN               1,804                          15.173049  \n",
       "2                NaN                   1                           5.518546  \n",
       "\n",
       "[3 rows x 43 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covidvisual.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "dfad0d44",
   "metadata": {},
   "outputs": [],
   "source": [
    "world.rename({'iso_a3':'Country Code'}, axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "91373129",
   "metadata": {},
   "outputs": [],
   "source": [
    "worldmerge = world.merge(covidvisual, how = 'inner', on ='Country Code', indicator = True) \n",
    "#in order to preserve the map and to avoid empty spaces on the map, the merge is how='left'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "496bffe8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>geometry</th>\n",
       "      <th>Country</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>HDI rank</th>\n",
       "      <th>Human Development Index 2021 (HDI)</th>\n",
       "      <th>Life expectancy at birth</th>\n",
       "      <th>Expected years of schooling</th>\n",
       "      <th>...</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>Serious,Critical</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>Population</th>\n",
       "      <th>Continent</th>\n",
       "      <th>New Cases/1M pop</th>\n",
       "      <th>New Deaths/1M pop</th>\n",
       "      <th>Active Cases/1M pop</th>\n",
       "      <th>covid_mortality_rate (per 100000)</th>\n",
       "      <th>_merge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>FJI</td>\n",
       "      <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>-18.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>99</td>\n",
       "      <td>0.730</td>\n",
       "      <td>67.1140</td>\n",
       "      <td>14.736790</td>\n",
       "      <td>...</td>\n",
       "      <td>1,017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>669,911</td>\n",
       "      <td>909466</td>\n",
       "      <td>Australia/Oceania</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,118</td>\n",
       "      <td>97.089941</td>\n",
       "      <td>both</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>160</td>\n",
       "      <td>0.549</td>\n",
       "      <td>66.2007</td>\n",
       "      <td>9.221490</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63298550</td>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>662</td>\n",
       "      <td>1.336524</td>\n",
       "      <td>both</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Canada</td>\n",
       "      <td>CAN</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "      <td>Canada</td>\n",
       "      <td>60.0</td>\n",
       "      <td>-95.0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.936</td>\n",
       "      <td>82.6565</td>\n",
       "      <td>16.396259</td>\n",
       "      <td>...</td>\n",
       "      <td>32,425</td>\n",
       "      <td>99</td>\n",
       "      <td>66,343,123</td>\n",
       "      <td>38388419</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>845</td>\n",
       "      <td>135.772718</td>\n",
       "      <td>both</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       name Country Code                                           geometry  \\\n",
       "0      Fiji          FJI  MULTIPOLYGON (((180.00000 -16.06713, 180.00000...   \n",
       "1  Tanzania          TZA  POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...   \n",
       "2    Canada          CAN  MULTIPOLYGON (((-122.84000 49.00000, -122.9742...   \n",
       "\n",
       "    Country  Latitude  Longitude  HDI rank  \\\n",
       "0      Fiji     -18.0      175.0        99   \n",
       "1  Tanzania      -6.0       35.0       160   \n",
       "2    Canada      60.0      -95.0        15   \n",
       "\n",
       "   Human Development Index 2021 (HDI)  Life expectancy at birth  \\\n",
       "0                               0.730                   67.1140   \n",
       "1                               0.549                   66.2007   \n",
       "2                               0.936                   82.6565   \n",
       "\n",
       "   Expected years of schooling  ...  ActiveCases  Serious,Critical  \\\n",
       "0                    14.736790  ...        1,017               NaN   \n",
       "1                     9.221490  ...          NaN                 7   \n",
       "2                    16.396259  ...       32,425                99   \n",
       "\n",
       "   TotalTests  Population          Continent  New Cases/1M pop  \\\n",
       "0     669,911      909466  Australia/Oceania               NaN   \n",
       "1         NaN    63298550             Africa               NaN   \n",
       "2  66,343,123    38388419      North America               NaN   \n",
       "\n",
       "   New Deaths/1M pop Active Cases/1M pop covid_mortality_rate (per 100000)  \\\n",
       "0                NaN               1,118                         97.089941   \n",
       "1                NaN                 662                          1.336524   \n",
       "2                NaN                 845                        135.772718   \n",
       "\n",
       "   _merge  \n",
       "0    both  \n",
       "1    both  \n",
       "2    both  \n",
       "\n",
       "[3 rows x 46 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "worldmerge.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "319d629f",
   "metadata": {},
   "outputs": [],
   "source": [
    "worldmerge.drop('_merge', axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c2935b34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>geometry</th>\n",
       "      <th>Country</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>HDI rank</th>\n",
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       "      <th>Active Cases/1M pop</th>\n",
       "      <th>covid_mortality_rate (per 100000)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>FJI</td>\n",
       "      <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>-18.0000</td>\n",
       "      <td>175.0</td>\n",
       "      <td>99</td>\n",
       "      <td>0.730</td>\n",
       "      <td>67.1140</td>\n",
       "      <td>14.736790</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>669,911</td>\n",
       "      <td>909466</td>\n",
       "      <td>Australia/Oceania</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,118</td>\n",
       "      <td>97.089941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>-6.0000</td>\n",
       "      <td>35.0</td>\n",
       "      <td>160</td>\n",
       "      <td>0.549</td>\n",
       "      <td>66.2007</td>\n",
       "      <td>9.221490</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63298550</td>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>662</td>\n",
       "      <td>1.336524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Canada</td>\n",
       "      <td>CAN</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "      <td>Canada</td>\n",
       "      <td>60.0000</td>\n",
       "      <td>-95.0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.936</td>\n",
       "      <td>82.6565</td>\n",
       "      <td>16.396259</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32,425</td>\n",
       "      <td>99</td>\n",
       "      <td>66,343,123</td>\n",
       "      <td>38388419</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>845</td>\n",
       "      <td>135.772718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>USA</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -120.0000...</td>\n",
       "      <td>United States</td>\n",
       "      <td>38.0000</td>\n",
       "      <td>-97.0</td>\n",
       "      <td>21</td>\n",
       "      <td>0.921</td>\n",
       "      <td>77.1982</td>\n",
       "      <td>16.280979</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,062,241</td>\n",
       "      <td>1,895</td>\n",
       "      <td>1,174,878,661</td>\n",
       "      <td>334805269</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,173</td>\n",
       "      <td>345.176169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>UZB</td>\n",
       "      <td>POLYGON ((55.96819 41.30864, 55.92892 44.99586...</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>41.0000</td>\n",
       "      <td>64.0</td>\n",
       "      <td>101</td>\n",
       "      <td>0.727</td>\n",
       "      <td>70.8616</td>\n",
       "      <td>12.477140</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8,716</td>\n",
       "      <td>23</td>\n",
       "      <td>1,377,915</td>\n",
       "      <td>34382084</td>\n",
       "      <td>Asia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>254</td>\n",
       "      <td>4.761201</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>131</th>\n",
       "      <td>Bosnia and Herz.</td>\n",
       "      <td>BIH</td>\n",
       "      <td>POLYGON ((18.56000 42.65000, 17.67492 43.02856...</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>18.0</td>\n",
       "      <td>74</td>\n",
       "      <td>0.780</td>\n",
       "      <td>75.3003</td>\n",
       "      <td>13.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6,686</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,884,721</td>\n",
       "      <td>3249317</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,058</td>\n",
       "      <td>501.828538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Macedonia</td>\n",
       "      <td>MKD</td>\n",
       "      <td>POLYGON ((22.38053 42.32026, 22.88137 41.99930...</td>\n",
       "      <td>Macedonia</td>\n",
       "      <td>41.8333</td>\n",
       "      <td>22.0</td>\n",
       "      <td>78</td>\n",
       "      <td>0.770</td>\n",
       "      <td>73.8415</td>\n",
       "      <td>13.624432</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,226,216</td>\n",
       "      <td>2081304</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>364</td>\n",
       "      <td>464.420383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>SRB</td>\n",
       "      <td>POLYGON ((18.82982 45.90887, 18.82984 45.90888...</td>\n",
       "      <td>Serbia</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>21.0</td>\n",
       "      <td>63</td>\n",
       "      <td>0.802</td>\n",
       "      <td>74.1923</td>\n",
       "      <td>14.400090</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14,155</td>\n",
       "      <td>12</td>\n",
       "      <td>12,648,684</td>\n",
       "      <td>8653016</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,636</td>\n",
       "      <td>207.788822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>MNE</td>\n",
       "      <td>POLYGON ((20.07070 42.58863, 19.80161 42.50009...</td>\n",
       "      <td>Montenegro</td>\n",
       "      <td>42.0000</td>\n",
       "      <td>19.0</td>\n",
       "      <td>49</td>\n",
       "      <td>0.832</td>\n",
       "      <td>76.3426</td>\n",
       "      <td>15.081610</td>\n",
       "      <td>...</td>\n",
       "      <td>+60</td>\n",
       "      <td>679</td>\n",
       "      <td>6</td>\n",
       "      <td>2,736,615</td>\n",
       "      <td>627950</td>\n",
       "      <td>Europe</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,081</td>\n",
       "      <td>448.443347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>Trinidad and Tobago</td>\n",
       "      <td>TTO</td>\n",
       "      <td>POLYGON ((-61.68000 10.76000, -61.10500 10.890...</td>\n",
       "      <td>Trinidad and Tobago</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>-61.0</td>\n",
       "      <td>57</td>\n",
       "      <td>0.810</td>\n",
       "      <td>72.9709</td>\n",
       "      <td>14.535453</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81</td>\n",
       "      <td>8</td>\n",
       "      <td>907,114</td>\n",
       "      <td>1406585</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58</td>\n",
       "      <td>310.823733</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136 rows × 45 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name Country Code  \\\n",
       "0                        Fiji          FJI   \n",
       "1                    Tanzania          TZA   \n",
       "2                      Canada          CAN   \n",
       "3    United States of America          USA   \n",
       "4                  Uzbekistan          UZB   \n",
       "..                        ...          ...   \n",
       "131          Bosnia and Herz.          BIH   \n",
       "132                 Macedonia          MKD   \n",
       "133                    Serbia          SRB   \n",
       "134                Montenegro          MNE   \n",
       "135       Trinidad and Tobago          TTO   \n",
       "\n",
       "                                              geometry  \\\n",
       "0    MULTIPOLYGON (((180.00000 -16.06713, 180.00000...   \n",
       "1    POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...   \n",
       "2    MULTIPOLYGON (((-122.84000 49.00000, -122.9742...   \n",
       "3    MULTIPOLYGON (((-122.84000 49.00000, -120.0000...   \n",
       "4    POLYGON ((55.96819 41.30864, 55.92892 44.99586...   \n",
       "..                                                 ...   \n",
       "131  POLYGON ((18.56000 42.65000, 17.67492 43.02856...   \n",
       "132  POLYGON ((22.38053 42.32026, 22.88137 41.99930...   \n",
       "133  POLYGON ((18.82982 45.90887, 18.82984 45.90888...   \n",
       "134  POLYGON ((20.07070 42.58863, 19.80161 42.50009...   \n",
       "135  POLYGON ((-61.68000 10.76000, -61.10500 10.890...   \n",
       "\n",
       "                    Country  Latitude  Longitude  HDI rank  \\\n",
       "0                      Fiji  -18.0000      175.0        99   \n",
       "1                  Tanzania   -6.0000       35.0       160   \n",
       "2                    Canada   60.0000      -95.0        15   \n",
       "3             United States   38.0000      -97.0        21   \n",
       "4                Uzbekistan   41.0000       64.0       101   \n",
       "..                      ...       ...        ...       ...   \n",
       "131  Bosnia and Herzegovina   44.0000       18.0        74   \n",
       "132               Macedonia   41.8333       22.0        78   \n",
       "133                  Serbia   44.0000       21.0        63   \n",
       "134              Montenegro   42.0000       19.0        49   \n",
       "135     Trinidad and Tobago   11.0000      -61.0        57   \n",
       "\n",
       "     Human Development Index 2021 (HDI)  Life expectancy at birth  \\\n",
       "0                                 0.730                   67.1140   \n",
       "1                                 0.549                   66.2007   \n",
       "2                                 0.936                   82.6565   \n",
       "3                                 0.921                   77.1982   \n",
       "4                                 0.727                   70.8616   \n",
       "..                                  ...                       ...   \n",
       "131                               0.780                   75.3003   \n",
       "132                               0.770                   73.8415   \n",
       "133                               0.802                   74.1923   \n",
       "134                               0.832                   76.3426   \n",
       "135                               0.810                   72.9709   \n",
       "\n",
       "     Expected years of schooling  ...  NewRecovered  ActiveCases  \\\n",
       "0                      14.736790  ...           NaN        1,017   \n",
       "1                       9.221490  ...           NaN          NaN   \n",
       "2                      16.396259  ...           NaN       32,425   \n",
       "3                      16.280979  ...           NaN    1,062,241   \n",
       "4                      12.477140  ...           NaN        8,716   \n",
       "..                           ...  ...           ...          ...   \n",
       "131                    13.800000  ...           NaN        6,686   \n",
       "132                    13.624432  ...           NaN          758   \n",
       "133                    14.400090  ...           NaN       14,155   \n",
       "134                    15.081610  ...           +60          679   \n",
       "135                    14.535453  ...           NaN           81   \n",
       "\n",
       "     Serious,Critical     TotalTests  Population          Continent  \\\n",
       "0                 NaN        669,911      909466  Australia/Oceania   \n",
       "1                   7            NaN    63298550             Africa   \n",
       "2                  99     66,343,123    38388419      North America   \n",
       "3               1,895  1,174,878,661   334805269      North America   \n",
       "4                  23      1,377,915    34382084               Asia   \n",
       "..                ...            ...         ...                ...   \n",
       "131               NaN      1,884,721     3249317             Europe   \n",
       "132               NaN      2,226,216     2081304             Europe   \n",
       "133                12     12,648,684     8653016             Europe   \n",
       "134                 6      2,736,615      627950             Europe   \n",
       "135                 8        907,114     1406585      North America   \n",
       "\n",
       "     New Cases/1M pop New Deaths/1M pop Active Cases/1M pop  \\\n",
       "0                 NaN               NaN               1,118   \n",
       "1                 NaN               NaN                 662   \n",
       "2                 NaN               NaN                 845   \n",
       "3                 NaN               NaN               3,173   \n",
       "4                 NaN               NaN                 254   \n",
       "..                ...               ...                 ...   \n",
       "131               NaN               NaN               2,058   \n",
       "132               NaN               NaN                 364   \n",
       "133               NaN               NaN               1,636   \n",
       "134              97.0               NaN               1,081   \n",
       "135               NaN               NaN                  58   \n",
       "\n",
       "     covid_mortality_rate (per 100000)  \n",
       "0                            97.089941  \n",
       "1                             1.336524  \n",
       "2                           135.772718  \n",
       "3                           345.176169  \n",
       "4                             4.761201  \n",
       "..                                 ...  \n",
       "131                         501.828538  \n",
       "132                         464.420383  \n",
       "133                         207.788822  \n",
       "134                         448.443347  \n",
       "135                         310.823733  \n",
       "\n",
       "[136 rows x 45 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "worldmerge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "76b1a17f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "worldmerge.plot(column='covid_mortality_rate (per 100000)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f2b17eb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uuphdu3ap1Wo1BwCffPJJ4YQJEzwWi4VZuHBhTHFxsVQqlQqffPJJ4ejRo73n7n/ixAnJggUL4mw2myg9Pd39/fffF8pkMuHgwYOyO+64IyY7O1vx5JNPlj///PNdWzzfjh4piNRTSLVeordxAo9Chx3HrHWo83lAgQJFNabr2lk/ErV6XN1KsMkLAmq9HpS4HKApCiaZHCaZ/IIGZNypMfg4DgGBA8vzENMMYlWdr5r5S3kxtlY1r0QuZ0TwcoFOtZiRMQzi1TpEKtVI0RmaZnAJgiCIvmFzerFuVx6yCqqRVVCDo/nVqKh1QCET4+rJybjtimGYnBlD1qESg0pnCyKVuYrM1Z6KNnPbQ+Rh5T0RoG7atEmZkJDgT0lJST87uHzppZdMR44ckX/55ZclH3zwgX716tX6NWvWFHR2/x9//FF9ySWXuNRqNf/yyy+bfvvtN3Vr+7fluuuui5kzZ47tjjvusJ79+N133x2hUqm4119/vfLgwYOy++67L2rnzp255+5/5ZVXxl1zzTXWRYsWWRcuXBiVmZnpeeKJJyzl5eWikydPSr777ju9Xq8PdCc47bWCSATR3wmCgGKXA/trq3G8ob7NViwyhkGiRtfqczRFIViuQLC8ZduTGo8brMBDL5FCIRL32Lg5gW9Kjz1mrcOXBSdAAxDRNEQUDb1UhmStHoIggKaopuBSJ5HCIJU1HeeX8mIUOmyw+r1wsC3TeLvSmqbxPAIKnY19Uy8Lj252LoIgiN5QY3XhQE4Faqwu1Ds8aHB4oFHKcM81o6GQ9dzn7kAiCAJeWPor3v1+NxzulhMpbIDDb4eKkZVfA71GBr1ajncemw2jRoGS6gYIQuPykdM3NymKgkmngFx6cb6fxOAT4FmmxlMV2t42NZ6qULM8okZEi86r5+n06dNbbaXw008/6Z577rkKALjjjjusTzzxRBTP86BpulP7z507t6kwyKRJk5zLly83ns84T8vJyZH99a9/rQKA4cOHe8vKyiSlpaWiyMjIpotCnuexc+dO9erVqwsA4M4776x77rnnwp544glLeHh4IDw8PLB69WpdT4znbCQ4JQYtXhCQ3VCH7dXlKHU5mz0noWlEKTWIVmsaZ0BpBlEqNXwch92WSlS6XdCc6guqk0ihl8qgFkuaVZ0VBAE/lBRgT23jDTeGonBPcgbCFJ1rTF/n9aDS4wJDUajxeFDktKPU5QAn8JDQDDhBQIYhCFdExCJNb8Tj6SOR72iAg2XhPbW2tNztwtaqcgSE5p+po4NCcE10AoDG1jFaiQQcLyAg8PBxHFwBFq4AC04QIGMYSGkRpAzT9H8fx8Hu98PG+pr+lDMiRKk0iFaqEa3SIEgm73LFYYIgiLNxHI/88npYbG7YnV7YXD7YXT7Y3T7YnV6UWezYfawMBRXNbvpDxNDISDBj+BAzpo2M66PRXxgcx+NIfjW2HylGYUUDaJoCTTWm7n6+/nCb+7EBHuUWO8ot9qbH8svrUVXnRK2t9aUcIoZG5hAzxqZGYGxaBCZlRCMsSN3jr4kgLoQ6n0V/dipvawTwdJ2vRh8iD6vrjTFUV1dLYmNj/QAgFouhUqm46upqUWhoaOdnBk55//33TTNmzLB1db+///3v4f/6179CJ0+e7Hj33XfL5HK5kJ6e7vn22291M2fOdG7ZskVRWVkpLSoqkpwdnFZXV4vUajUnFjfesIqJifFXV1dLunr+riLBKTFosTwHhUiMYYZgJGj0UIvFUIsl0EmkCJErWwSae2qrsLa0EIE2Ut1pUIjXaJGhD0KKzgi5SITZkbGQMQy2VZeDEwQsy8vGFHMEarxueAIBiGkaMyNioBG3/F0udzuxvLBFBgUAwM83Bpu7LVUYHxwKk0wBg1QGg7RlcQsXy2JjZQn2WM5kpeTarFhRlIcIpRqpOgPi25gRPvu98nIc/BwHP8+D5TkwNA0JTUNCM9CIJaTXIUEQ54XjeOSW1uFgbiUO5FbiYG4FDudVtag2expNU4gx65AQYcDMsUOQEGFo/H+4AVFm3YBcT8kGODjcfjjcPjg9fqz9PRert5+A1xeAx8fC7WPh9QUQEazBpMxoFFVY8XtWKewuX4+cP6ug/cYJAY7H/hMV2H+iAktW7AFDU7hxxlC8/5erwAyw99vjY/Hkkg04VlSD/PJ6eLwsxCIGIoaGSERDxNAI0iqQGBmEIZEGDIkMQmKkEQkRBjJ7PEiwvL9T/yE7u113tLZ8kqKoLq+pXLJkieHw4cOK999/P6cr+73xxhvlkZGRrM/no26++eboZ555xvzaa69VPv/885WLFi2KSk5OTk1OTvYkJye7RSJRs3H11Ni7igSnxKAlZUSIU2sR10FrE5bn8H3RSRy11ra7HQ8BefYG5NkbwJTkI0KphoxhIKEZBMsUqPa64QywWFtW2LSPhKYxISSs1eB0iEaPB1OGQcIw4AUB/z52oMU24YrGgkcAYPP7sLe2ChVuF6rcLkQq1ZgYEo4olRqXhkZif211U2VfG+vH/roa7K+rwY8lBdBJpRBRNMQ0DSnDQMYwENM0bH4/6nxeONj219YbpDIMM5gw1RwBET2wLlAIgugbHh+LvcfLsf1wMbYfKcGe7LI2A9Hk6CCkxQYjOToISVEmJEcHYUikETLJwL1McXr82HGkGFsOFOLXA0XIKamF19+5yZIGp7fDQPJCEIsYqJXSAReYAsCzH23GBz+0X8ekqLIB+05UtHj82qkp+PyZ68AwNP63/jD251bApFUgSKdEsF6JsCA1wk0amA2qAfneXCzEtKRTLQk6u113mM1mf2FhoSQ+Pp5lWRZOp5MJDg7uUpXgVatWqV977bXQbdu25cjl8i4Fh9HR0SwAyOVy4c4776x7/fXXQwDAYDDw3333XRHQmL4bGRk5NCkpqdldMLPZHHA4HAzLshCLxSgqKpIEBwf32nt12sD91CeIHiKmGcyPGYIZYVGw+X2gKAoiigJzam2nO8Ci3O1EhduFSrcTFq8HnCCgxGmHUSqDSaZAuFKFWLUWEqZxplFKM5AwDKJV6qaepOeSi0SQixp/BQM8jxtiExsLHvEc5IwIMkaEBI2ucZ2nIGCXpRJZ9XWo9zcWU7M11KHc7cQDqcOgFkswMzwGB+tq0OD3NVtHyqOxbc35qPd5scdShWSdAeGdTFsmCOLiVWaxI/MP/4G7nVnRCemRuGpyMq6alIxos+7CDrAXlNbY8PT7m7DjaAn8bABWhxcB7ryWsV1werUMo1PCMSY1AuPSIjBhaNSAnUV8cdEMXDoiFt//mo0fd+TA7vJBo5QiIcKIsCA1KAoQeAG8IIA/9acgAHq1HG8/emVT0Hn52AToNTLsyS7Hyq3ZKLPYYXf5YHN6kRJjwkPXj8f8aakQi5g+fsXEuYxSk7XcVRLZXmovBZo3SoOtbT1/vmbPnt3wySefGGfMmOFaunSpfvz48Y5z15u2Z8eOHfIHH3wweu3atXnh4eHN7m7FxsamFRYWHmtv/+LiYnF0dDTL8zxWrFihS0lJ8QBAbW0to1KpeJlMJvz73/8OGjNmjMNgMDT7wKJpGuPGjXMsXbpUv2jRIusnn3xinDNnTkPnX333kGq9xKDhCrCo9rhPpaZy8PEc/BwPH89BRFEwSuUIksmhFInAUDQYmgJD0aCBdlNWj9RbUOS0g6EatzfJ5Ag5VRxJQl/4LyMfx8HLBeDnOajFklYrBnu5ABp8vqYiSO4AC3egcR+aopqqFIuoMzOpUkYEKd245tTLBeBgWQR4HkaZDEFSOQxSGZk1JQiiXYIgYMfREvxv/WF8tfEo/GzzCYLLRsdj3tRUzJ6YCJNO2Uej7HkVtQ5MvPtDVNU7O964n5kxKg4LpqdjXFokEiIMg3IJh88fgM3lg0mnGJSv72LU36r13nPPPRErV640WCwWsclkYm+++ebaN954o8LtdlPXXXdd7LFjxxRarZZbvnx5fmpqqh8AkpOTU0+cOJHd3v4TJkxIzMnJkZtMJhYAwsLC/Js3bz5ZWVkpGj9+fHJRUVFWe+MaN25cYn19vUgQBCo1NdX92WefFWu1Wn7jxo3Ku+66K5amaWHIkCHeL774oshkMnEAMHXq1IRly5YVx8TEsNnZ2ZIbbrgh3mazMWlpae4VK1YUyuVyoaSkRDR69OhUl8vFUBQlKBQK/vjx41nnBrjtaataLwlOiUGDEwTsrKnAxvISsELX7labZHKkaA0YZjQhRN43F0wNfh/cARbBMkVTEBjgG4Nr5VlVgAsdNhyqt6DIYQcvCKCpxiq6DEVDK5GcWpsqw3BjcJutbnhBgCvAggKgaiXlWBAEsKcKMwGN760rwEJM0ZAwdFMVYYIgCACot3vw4Q/78Pn6w8gvr2/xvNmgwruPz8bsCUl9MLru43kBVfVOlFQ3oN7ugYihIWboxrWLIhp+lkOD0wu704ejBdV49/vd4Pn+c13VEYoCwk0aRAZrERemR2psMNLjgiFmaOzLqcAf546EXt24tEQQBNhcPnAcD41S2q2ZQp8/AGk/SNW2Ob0oqmpAnc0NhUyMUcnhA3IN88Wss8Ep0HqfUwo035N9Ti+0r776Spufny99+umn+z7/v5tIKxli0GMoCmEKFSQMAzbQteDU4vWg3leBAocNE4JDEaZQQSWWNKXddgUnCKAEATtqKnGwvgYBnoeMEWFaaCRSdIYW27sCLFYVn8TxhnoIaCy8pBaL4eEC8PM8dBIp7knOgFoswdH6WiwvzGmzJ2mlx4UQuQLp+qCmwFQQBBQ67ThQV4M6rwd21g8H60eEQoVbE1IBAFVuFwqdNlR73KjxelDjccPPc5hijsBUcwQ2V5bgt6rypvOIKAoSmkGEUo00vRGpOkOPttEhCGJgCXA8GpxelFQ3tHjuhunpeOOhK2DQDKy+yAdzKzH1/o+7/H0ykAgCUFZjR1mNHTuzSls8//uREoQYVNh2uBiVdQ54fGeyCmUSEdQKCdQKKdQKKRYvnIj509LaPZ957isQMTRMeiVMOgW0StmpcQhQK6WYOzEJsyckQaOU9uwLPYXjeHz80wF8sHofaqxO2F0++FgOWqUU00bG4f2/XNVr5yb6ToQypsosj6ip89XoWd4vFtMS1igNtp5v+5i+dNNNN3W5au9AQYJTYtDYV1uN1cUn0ZVPGq1YgiFaPYxSGQI8jzK3Ez+UFsDLcaAA3BKfArNCiTqvB3U+L+QiEZK1BohPzWwWO+2w+X1I0Rkgphn8dKq1jIiiESJXIFalgdXvg1EqQ6JW1+zcXi4Aq88HGcNghDEEFq8HFq8HPATYThUoUosluCoqDvJTgWaD39dqYBoiVyBEpkCMWoNRQSFNM5sBnsenecdQ6LS32McglUFM0zhSb8F3RXlNxZTOtqWyFEfqLbgqMg6R8Wr8VlUOq88LvVQGpUgMXuBxtL4WR+otuCQ0ssPiUwRBDC45JbX499e/4+uNR+E7J4U32qzD249eicvHJPTqGPZkl2HF1my4PCxCjSqEBWkQGqRCqFGNlBhTsxm+Q3mVCDWqEWLoeO28QSMf1IFpZ6zffbLN57z+ALz+ACwNjW1p7n/9J/x7+U4opCLIpWLIpCIopOKmv0vFTFNBKKfHj8KKlsv8Vm49DqmYwc2XZ+Ldx2f3eAouw9CYMzEJaXHBMGrkMGgU0KlkEItoku47yIloEd9b7WKInkWCU2JQyLLWYlXxyTZnFM/GUBTGmUIxzGhCgd2GzZWl8PEtC6dRoPBlwYkWQZuMYZCuD4LF60HxqaBPxjC4MzEdE0PCsL+uGj6eQ4nLgRKXAxSAOxPTWqTCugMBbKksRa7dCpZv/QLIwfrx2cnjkNIM5scOwbhgM/bXVcPi9QAAFIwI82ISkKJr2ZNZEASsKslvNTAFgIP1FpS6HKjtoFhSnc+LdeXFeDB1GFK0BthZP6o8buyrrUKe3YZgmQIxKg1cLAu73weNhNx1JoiLxXsr9mDZukMtHr/timF4/cFZUMp7tyVeXmkdrnj88zYLLy17Zh4WXJre9O/P1x/G5v0F+PXdO6FVNc7asQEOlgY32AAHnz8AH8sh3KRBWJAa49MjW51RJFqyu3w4kNOy8m1X+VgOn6w5gGumJOOyHryxsetYKZ75oLFg1bn3YrVKKQxaBQwaeVPQ2uzv2uaPGzRyqOSkxRpB9AYSnBIDXo3HjVXF+Z0KTOPVWlwVFQ+dRIpvCnNxrKHtm2g8BLR2UC/HYV9tdYvHvsw/gT8mpiNErkSpy9H0nABgdXE+Hkgd3jTjCjTOXC6MT4af53DS3oBj1jqcsNXDy7UMlE9X8D1dWfhgXQ2kDINMQ/trZIsc7Wd9dBSYnuZk/Xg3+xDqfJ6mHqynVXpcqPS4sNNSCQCIVKqQaQhGhiGo2VpZgiAGj9XbTuClz3/D0fzqVp9PjQ3u9cC0pNqG219c2WZgOiTSiNHJjXVQfP4Aftieg73Hy1FV50SD04v/fL8bO46WYNexshbHYGgKU4bFYPaERNTZ3MgtJRMuF9IV44Zg+qj4Vp+zu3xgaKrLP1+pMcGorHO2CEwBwObywebytTqb2xaZRIQnb52MxTdNJO1kCKIHkYJIbaisc+Cp/24ETVFIiDBgRFIoRiWHw6htvS1If1Fv96CyzoG4MP2ALf/eHZwgoMrtQrHTjmKnHSds9Qic87NtkMqwIDYRkUo1Kt0uHLFaYPF6UOv1wM9xoCgKXi7QanDYWQxFtZoeCwBzI+MwLji03f39PIftVeU41lAPJ+uHTiJFjFqDGJUWCWotshrqsLa0EO6zWsUkafWYEhKOmFZSan8qLcDOmspuv57zkaTVY7wpFFZ/Y9VgChSmmMPbLNJEEMTAcSivEm8u34m80jrkltbB6WneKzk9Lhj/fvgKTBwa1eOzS2UWO177Yjs+WXOgzbRbo0aOPR/fg7AgNT5bdwh//e8G1NsbM06uuyQV7/15Lqbc9zFOFLff35roO5Mzo7Fk8RwkRJzJDHJ7WVzx+Gc4lFeFyZnRmDk2AVqlDMeLLcgprkV1vRPxEQYkRwUhOcYEn5/DN5uOQgAQrFeitsGNdbvyenScw4eE4vrpaZg9PhGJUUE9euz+os7mxo/bc3DrrMx+E4h3pSAS0T+Rar1dVFBej1uf/x5KuQRGrQLj0iIwd2IS4sJbFrTpC4IgoKTahoLyeug1cpwsq8fyjUfx856TTV/W4SYNbrtiGB65YTz2n6gAQ1OQScUwG1WIDB7cawNLnA7sq61CqEKJULkSZoWy1aCozOXAUWstqj1uVHlccLC911tYL5FiTmQc4jVaiLvRgqbAYcPHuW1XDL8sLApTzRHNLgQ5gUe9z4vfqytxoK4GgS5WMe5parEY00OjEKlSI0gqJ61pCGIQEAQBr321A89+uLnFcyOSwvDAdWN7rA/kt5uP4Y8vrWrRoqY1sWF67PnobkjFDN76dhf+sfTXpnWxp2fe7C5fB0ch+pJEzGBKZjSmjYzDtBGx+Oeyrfjp99y+HlabEiIMuHJ8ImaOTYBMIoLL44fD44fL44fT44fT3finy8tCq5TCpFPCpFciKkSLUclh/TJNeOvBQvzxpdWQikU4tOy+flPVuKvBqTvAMgfravQOlhWrxWJ2uDHYqhCJuz8bQZw3EpwOcCXVNuQUW1BQYcXOrFJsP1KCckvrawnPJWLoZo3A48L0mD4qDhEmDUIMKlidXtTZ3IgwaZAUFYQhkacbVPe/D0leEHCgrgZmuQIRSvV5Hy/A8zhYXwM/x+F09X8JQ0NM0U0BpI31oc7nRZHDjhqv+7zPKaZoxGt0SNLqkaDRwSCVdWq/LGstvirIaXebEcZgXB0V3yzocwVY7LFUodBhg4P1w8Gy8HCBdo5yYdAAjDI5QmQKxGm0GGEM7lbQThBE/8DzAjw+Fm4fC7e38f8urx8MTSM5OqhHsnkOn6zCpHs+avad1p53H5uNu+aOBAA8+vY6/Hfl3vMeA0H0hrFpEfj6+QUwd6JYF9G14HR9WZF5V01lKCucaSUjpmh+XHBo5ayInmklM2bMmKSamhqxTCbjAWDTpk254eHhgdzcXMltt90WU1dXJ9LpdNxXX31VEB8f32ImZNu2bYq77rorxuv10pdeeqntk08+KaVpGuvWrVM9/vjjkbm5uYoPP/yw4I477ugw9/zBBx8M//bbb412u51xu90HTz/+9ttvG//2t79FhISEsACwaNGimscee6wWABiGGTlkyBAPcKaX6rnHfe6550I+//zzIIZhBKPRGFi2bFlRYmKiH2js07px40Ytz/OYMmWK/fT420NayQxQx4sseH7pr1i97Xir6yQ649wv8YIKKwp+2N/uPkqZGAatAmq5BCqFBHq1HImRRsilYhRXNaDcYkdsmB4jk8IwPDEUQyKNTb3QzpePC+Ck3YZKjwu1XjdqvV6k6o3I0AfhQF0NtlaVAWhMG50ZHo0QuRKCICDHZoU7wGJEUAiAxhRZm98HCc1AIRI3W+95moimMTrIjHqfFzuqK2D1e2Hz+2Dz+8ELAsQ0DYai4GDZxjWoPYAVeJyw1eOErbEXoEEqw8TgsGYpv4Ig4Ii1FtnWOsRptEjU6BEiV2CoPgjHG+rbnAHlBQE+jmsWnCpFYkwLjcS00Mimx/wch3qfF7W+xqJOdtYPlucb+6pyHDyn0ps9gQB4CGAoCgqRCApGjHiNFhFKNXbXVKLG64GXC3TrneGBpgrFWQ112FxRioXxyYhWabpxNIIYGOrdfuwpacDBChtyapxID1XjsiEmDA3VgD7nhqDT40dBeT2Gxof0y5uF56JPzUZ2ZS1gaY0NGoUUGqW0U68xM8GMu+aOxPuruhZkrtuZSwJTol/bfawMDN2zv+cl1Tb8/eMtMGjlCNYrEaJXIVivRLBeCaNWgQDHw3eq6nKA4xEfbuj3y9e6an1ZkXlbdXn4uY+zAk+ffrynAtTPPvusYMqUKc1mMR5++OGIhQsX1j344IN1P/zwg/rxxx+PWLVqVeG5+953333RS5YsKb700ktdl1xyyZDvvvtOs2DBAntcXJx/6dKlRS+99FJIZ8dxzTXXNCxevLgmJSUl/dzn5s6da/3ss89Kzn1cKpXyJ06cyG7vuCNHjnQ//vjjx9VqNf/yyy+bHn300Yg1a9YUbNiwQblnzx7ViRMnjgHAqFGjkteuXaueM2eOo73jtYUEp/2Y0+PHH174HlkFF76/rsvLwuVtXkzn53NKym8/UoLP1x9u+veY9Ahcf+8IGKUy6KUymGRyJGn1UIlbXqg0+H3Is1tR6LCBFwQoRGLIGRHK3U4UOGwt1m1WelzYVNH8dynHZkWuzYphxmDUeT0ocTkQrdKAoijU+bw4Zq1rmukUURRiVFoM0eoQp9bCJJM3m6UzSGVI0GixuqS2WWpva1V8e0qIXIFMgwlSmkGE8syd0uyGOvxaWYZytxMAkHWqaFO0SoOro+JxTXQ8tldXYFtVWbN1tWKKRr3Pix9L86ERSzHGZEaQrPUbBhKGgVnRmO68uaIU1WfNCMsYBhqxBEP1QRhhbCy4xFBUiwvHTIMJQGOxpJ/Li3Gg7vx+Tp0BFsvysnFHYhoie2BWnCAupAYPC5WUaTdV3c/xuOubQ8itdTU9tresAVtO1mLl7WMgphurz24/UoKN+/KxflcePL4AkqODcMvMTNwwYyjC+2lWS3ds2V+AuX/5AhwvQCkTI+xUhdywIDWGRBgxPj0So1PCmwW7giCAoSlMzIhCVn41bB2k5SZFN64BfOvbXb36WgiiJ1zzxJeYkBGFtJhglFQ3IKekDtVWJwIcjwDHQxCAYJ0CYUEahJvU0KpkcHr8aHB6YXf6MDYtAgsvz2hKvd17vBzfbsnqUksks0GF1FgTUmKCkRZrwuiUcKTFBg/Izx13gGV21VS2W+xjV01l6BRzRI1C1Ds9T/Py8uRXXnllKQDMmTPHsXDhwhYlqIuLi8VOp5OeMWOGCwBuvvnmulWrVukXLFhgT0pK8gNAR7OQZ5s+fbqr4626bu7cuU3B5qRJk5zLly83AgBFUfD5fJTX66UEQaACgQAVFhbW7XVyJDhtg83pRWWdA8nRpl4/V4DjsT+nAmyAQyDAw+72YfVvJ7Bq2/E2qxD2Rx4f21S59TQKQKRSjWStAXqpFBKGwcG6Ghyz1vXIPKQA4OBZQdHpgkjnCggCTjoacNLR0DQuvUQGk1yOYJkCBqkMeqkUN8cnw8WykDEiyBgRKjwuHK6zNO3XHq1YAvOpNa4hcgWUp2ZrPRwHi9cNi9eDOq8HDpaFM+BHjceNaKW6RSGjZK0BSpEYx6x1oChAyohQ7nKg2OnAT6UF+ENCCmaERSFVZ8B/jp+5OcAKPEpcDuDU23+65+hPpQWQMSJcHh7dagrxuQG4l+Pg5Tyo8Xqwy1KJicFhuDIyts3XrRJLMNUcgXK3E9We7qU90wDClWrSJ5UYcFYcrcTOonrUuHyweljcNioSoyJ08LCNmQhxBiUUEgZlDR68ub2gWWB6WizFYv5fv8KRk1WotrZ8/kRxLZ7+YBOe/mATJGIGJp0SIadmP4L1KoxMDsPsCYkIN/Vd1oHV4YHd5YPZoIJU0valRY3VBa1SCqlEhGkj47Drw0WY++cvUFXvRF5pHfLOqYrL0BQmZUbj2ikpuGpyMkKNarz+4CwAwOb9BXj0rXXtVtJtcDRWJP/HounYvK8A2w4XY+O+gh54xQTR8w7kVuJAbveLGH6y5gDe+Pp3PHvnJbhmcgrGpUXgtiuG46Mf28+WO1tVvRNV9U5s3n9mci8uTI+rJyfjH4tmgO7h2d3edLCuRn92Km9rWIGnD9bV6CeGnH8P1D/+8Y8xNE1j7ty51pdffrmSpmmkpKS4v/zyS/0zzzxT8/nnn+tcLhddVVXFmM3mpouv4uJicWhoaNMFf3R0tL+ysrJXqpquW7dOl5iYqIqLi/O+++67pQkJCSwA+P1+Oj09PYVhGGHx4sVVt956a0N7x3n//fdNM2bMsAHAjBkzXBMnTnSEhoZmAsDtt99uGTFiROfaQbSCBKdtqKh1YMQd7yEpKghXT07GNVNSMGyIucfvHAmCgLtf/gFfbjjSo8ftC60FmwLQ1O+zPxEA1Pu9qPd7kWNrPX1fK5ZgtMmMhfHJOFhXA14QIGUYSBnmVPDa/M9arwdbKkuR72jAcVs9nCwLTyCAGLUGo4NCMDE4rEWxonN7nwIATVGIVmmgEolxwlYPVyCAkUEhuCYqHirxmb5qBR20idllqWw2C53dUIdH0kY0C1CPWevQ4G975kFM081mddsSJJPjgZRhqPd5Ue1xo9TlQHZDHeo62arGKJMj4VT6criCrLch+q/vjlSg3u2HUSmBQSHB0r0lKKhvvCmjljBYnVWFJb8XocrR+HsloinEGRXIr3W3Wcl7y/ZsFBS23pLlXH6WQ7nF3qzmwGfrD+HhN9diRFIY5k5MxJyJSR3OdDjcPny69iCCtEpEhmgQGaxFuEnT6WInNqcX248UY+vBIvx2qBg5JbV4/KYJ+PPCSfD5A9hyoBAeX+DUjA+H3NI6/LL7JA7kViImVIfn7roUQyIMePTtdaiqd7Z5Ho4XsPVgEbYeLMKjb6/DuLRIXDMlBVdPTsalI+Pwy5u3YfzdH6KytvXvmOufXo6rJyfjv3+5CulxIfjfLwP/u5Yg2pNTUoubn/sOQVoFam3nXycDaFwO9u/lO/H8n6aDxsAJTh0s26kAz8H6zzsQXL58eUFsbCxrtVrpOXPmxC9ZssT4wAMP1L3zzjtlixYtikpJSQkaN26cIzg4mBWLm5+utfo/vTFTvWDBgoY//elP9XK5XHjllVdMt9xyS+yuXbtyAeDkyZNHYmJi2OzsbMlll12WNGLECE9aWlqrF4hLliwxHD58WPH+++/nAEBWVpY0NzdXVlZWdgQApk6dmrhu3TrVFVdc0faHeztIcNqBnJJavPLFdrzyxXZEm3W4dVYmbp01DFEhPTPDQ1EUliyegz9eNRLbDhXhkzUHUVzV0CPHvtAGzsdVx+SMCCODQjDWZIaUYVq0gBEEAV6OQ7nbCb1UCpVYApVYDLNCiROV1mZrQgscNhQ4bPi9pgKJWgM8ARb0qTTjWLWmWRVh/tQHFIXGWeC1ZUXNzvuHhFQ0+L2weDxN6b5tybM3NPu3TiKFXiJt+ne5y4lvi9qvejjMYEK6vv3S+Jwg4PuiPBQ6bKAATAoJx6yIGMwMj0aVx43fqspwxNp+uwaL14MtlWXYUlkGOSPCEI0OoQoljFI5jDIZgmWKFuvxCOJCqXX58dPxKggC8Oa2AgT41oNMh5/D/vLGm0ZDzRpYXD5UOXzItbSfYaUdkYqrRiZi56+HYantXKG71hzIqcCBnAr8/ZNfEROqw+wJSbjpsqEYmRTWYlu1QopRyeGY/tDSpnoGNE1h0dWj8MaDs1pcGNXbPdh1rBTbDhfjt0PFOJRXCf6s98GkU+D3o6X408urseNICSraCBYBoKiyAbf/Y0WXX58gADuzSrEzqxRPLPkFI5LCUGdztxmYnlZR64BG0fjZN214bIvZWYIYjHoqMB3I1GJxp9IP1WLJeacpxsbGsgCg1+v5G264oX7Pnj1KAHUxMTHsL7/8kg8ANpuNXrt2rd5oNDZLWYuJiWHPniktLi6WmM3mHk+dPHu29rHHHrO88MILTWtxY2JiWABITU31jxs3zrFnzx5Fa8HpqlWr1K+99lrotm3bcuRyuQAAy5cv140ePdql1Wp5AJgxY4Ztx44dShKcXgDFVQ34x6db8eKyrbhsdDxuv3IEZk9IhER8fhVGpRIRxqdHYnx6JB67aSK+3nAUi99d3+FaGqL3eLgANleW4reqMugkUohpBn6eg5/n4ec4sDyH0+EnQ1GYGBIGs1yJLGttm8WKSl1OlLrO/J5ur64ADSBMoQJFUbD7fc0KL7UWimU31GFfbedmWM5V5/Pix9ICzIqIwf7aaqwvK2rRC/Zce2uroZfIMDU0os1t8mxWHK63NP271tfYS5CiKIQqlFgQmwh3INCp1Gig8b0/Yq1tFtDGqjS4NjoBxjbW0BJEb3H5A7h3xWFkV3ftO/ZolR3DwzRNM6jtsXkDsAEYP3M0fvhiUzdH2lxRZQP+8/1u/Of73bj32jF446FZLbb5YfuJpsA0LEiN/7ttKkKNKri8LFRyCarrnXhx2Vb8frQUxwrbX1NuaXBjy4EWNT561YGcig63GZsWgc+fvQ40TaG4qoFcsBPERWS4Mdi6obwksr3UXjFF88ONwR1WwG0Py7Kora0VhYaGBnw+H7V27VrtpZde6gCAyspKUXBwcIBhGDz99NOhN910U4u79dHR0axSqeQ3bdqknDZtmuuLL74w3n///R0W8oiNjU0rLCw81tlxFhcXi6Ojo1kA+PLLL3VxcXFeALBYLIxKpeLlcrlQWVkp2rdvn+qpp55qUSRqx44d8gcffDB67dq1eeHh4U1tH6KiovxLly41sSxbyfM8tWPHDvWDDz7YvYtVkOC0WwQB+GVPPn7Zk48pw6Lx8n2XY9O+AmiVMqiVUmiVjZUHRyaFtbv2pjUihsYtszIxeVg0/vP9bvywPWfAzqQOBgFBQG0HqamcIOC3qvJuHZ8HUOZu/aK3tbCxu4HpabstVThcb4GX67jQEwVgiEaPIVpdu9slaHS4JjoeEpqBSSZH2DlpuRavBzb2/G60FDrteCf7EKaHRSFGrYGEZiBjGGjPmgkmiJ7Gcjwe/eFYlwPT07qSljVUI8LqHgpMz/XfVXvwyv2Xt0jZnT8tDT9sO4GCCitEDI3LxsQ39cD2+gN4f9VefNhBZff+7LEbJ+C5u6ZBLGJgd/kw6Z6PSHBKEBcRhUjMjQsOrWytWu9p44JDK8+3GJLH46FnzJgxhGVZiud5avLkyfbHHnvMAgDr169XP/fcc+EURWHs2LGOTz/9tKm6Z3JycurpCrlLliwpvuuuu2K9Xi81bdo0+/XXX28DgK1btyoWLFiQYLfbmU2bNulefPHFsJMnTx6rrKwUCYLQ6pfMPffcE7Fy5UqD1+ulQ0JCMm6++ebaN954o+KVV14J/vnnn3UMwwg6nS7w6aefFgHAoUOHZPfff380RVEQBAGPPPJI1ciRI70A8Mgjj4SNHj3adfPNN9v+/Oc/R7rdbub666+PB860nLnjjjusW7Zs0SQlJaVRFIVp06bZFi5c2P7as3aQPqdtOF5kwYg73utwu8RII/68cBL+9PLqFs+FmzRYfNNE3D57OGSdCFJrrC7sPlaGQ3mVCHA8nrnjEjA0hQ1783HXP1f1+y/VjEQzZixK6+thEF0QKldCxjAodtrBozGdOUgmQ7o+CJkGE9StVFruiqP1tVhRnAc/3/nPfRnDgBeEDvfJNARhQWzSeY3vYsMJPBwsCxFFtVpF+1y8IKDY2djfV0ozENMMYtUaKES9UqehXxEEAc/+nIMVWd0vTjIiXIsD5Z37fjYpxajceQQlpa2nwEcEa/DGg1fApFfgWEENjhVacKywGscKalBn97Q9hsRQPHnrFMyZmIiiygbklNTCoJFjeGIoxCIGi9/9Gf/5fjeAxuJDo1PCUVHrQGmNrdvty/qaUSPHR3+9BrPGDcFPO3KwfFMWth8ubndtK0EQHXNsfLrT69J7W3/rc3qhffXVV9r8/Hzp008/feFbevSQtvqckuC0DceLLLj1+e8xOiUcWw4UntfspdmowodPXI0Zo+ObPV5v92D9rjxs2leAXcdKUVBxJqtAo5Ti7qtHgeV4+FkORZVWrN2Z1+0xXAgkOB1YZAyDu5MyECxXwMsFQIOChDm/FPWz5dqsWHay3ZZZzSRrDbghLhESmoE7wGJ9WRH2t9GexiST45b4lDZb5RDNlbud+DL/RFPxKxoUMgxBmBQSjhC5AsVOOw7W1aDY6UCYQokolRq1Xi+yrLVwBs4se2EoCn/NGAO5aHAn3QiCgNd/y8fSvaXdPkaQUoJREVpU2H04Utm5daTBSjHKdx5BaRsBKk1TuGZyCp68dTKGxoc0jbWq3oljBTXIKqxBXkkdzEYVUmJMSIsNRnJ0ELYeLMJ/vt+NNTtzmwLOYL0SU4bF4Lstnc4IGzBomkK4SYPwIDV2HSvr6+EQxKAxUINTAHAHAvTBuhq9g/WL1WIJO9wYbO2t9jFE57QVnA7uK4zzNC4tAu88NhsvLtuK73/NRlSIFkq5BCdL63GixNJm3yizQYW0uGBolTIYtXJcOyUFl4xo3orjQE4Fbn3++2YB6dnsLh9e/XJHj7+m3kTq1QwcGrEEtw9JxaF6C6o8LtwQmwSmCz202hLgeXi5ADxcANWerrXZsrM+WH0+hMgVUIjEmBczBMOMwfixpKCpXy0FYGJIGGaERUPcA+O9GAinZj/j1FrY/D7Y/H7U+Tw4VG/BoXoLlCIxXGcFoLU+T5sFrHhBwObKEswIi4KUGZxfHxwv4IWNufj2SMfrGc+lEDN46tIhmJYQBJ38zOxySYMH3x+pwEd7WvQ9b6beE4Ber24zOOV5ASu2ZsPPBvDtizcCOLW226hGqFHd4gbob4eK2uyVXWN1DcrAFGh8n0qrbSit7nZWGUEQg4xCJOJ7ol0M0fsG59VFD1ArpVh4eQYoisLTt1+Cp2+/pNnzn645iIfeXNNqgLpgejpevu/ydo8/IikMh5bdh682HMUjb62Fxxdod3uC6CkSmsYfk9KhFkuwq6YSPp7Dv4/tB8vzGBUUgqH6IISfKtLUngq3E0vzjsHP8RAgQBAEnM8tyAq3C+9kH8TIoBCMNIYgUqlCnFqLh1KHodztxJH6WqTqDC36whLtoygKY01mVHncTcHpxoripnXHZwemHREA/F5TCQfL4obYxAHZlL09fo7HU2uPY11O17OkDHIx/rdwBKL1ihbPaWUiROg6nuVPFHH46UjHRYUs5yzxyC6swdcbj2JiRhQmZkRDJW9M2R4aH9Ksoi5BEER3mY2qQdWVgei/SHDahgiTBhHtNDS/ffZw3HjZUBzIqcCmfQX4YPW+pjWhBk3nUg3FIgZ/uGIYMoeYsWFvPo4XWpBfUQ+1XIIgnRIcz2PrwSLMGjsE00bGQhCAF5dtRX55fY+8RuLiEyJX4OqoeBilchQ4bPDxjQGKg20MULZXV2B7dQW0YgmGaPVI0RqQrDO0OI4gCNhaWQZ3oOVNFRFFYZgxGPU+LwodtlYLO7VFQGPRp3211dBLpJgQHIZxwaGIUKoRoVR35yUTABiKhlosgdXnhdXnhV4iQ2UXZ7YBQCkSY1Z4NIYZ2++hOVA5vIFOp+Cey8NyCNfKmj1W5/Lj032l+PpQOdxsx0XIasVSJCWGIye3/QJrtQ1u+FmuqVL8iq3ZeO2rHXj1yx0Qi2iMTY3AtBGxaCxu0a2XQxDERW7OhEREhugAAFdNSsLkzGgw/SSllxjcSHB6HmQSESYMjcKEoVF4/KaJKK2xIcDxSI0xdek4mQlmZCaYW31OEISmi0CfP4C9x8vx3so95z124uKQoNFBL5FCyjAIksoxIigEzKlqbPnn9EE9LVqphoNlsa+2GgfranBTXBICvIBknaEplZaiKNwUn4wajxuswEPGMJDRIkgZBqKz0m3tfh+yrHU4VG9BeRtVidti9fuwpqwQFAWMD27Zp5HoGo1YgnR9ECQ0gxxb56rmS2kG0SoNYtUaxKi0CFcqwVCD7+Ikz+LE/nIbvCyHmm608JoWH4QHJ8U2/ezXOH34ZG8Jvj1cAW8byz9aU+NiETcqpcPgNL+8HqFXvdIUhN44Yyj+u3Iv6uwesAEe24+UYPuR9lOICYIg2rNuVx4ev2ki/v7HS/t6KMRFhgSnPUQhEyMpKqjZY7c+/z3iwvSosbowKSMKl46Kg9nQcbrk2SiKQnZhDcosdvhZDscKz6+VSG8afPMoAxcN4I9JQxGtajn7zwsCjjXUQQAwzGDCoVM9SiOVakwOCUeqzgAPF8BuSxUsXjc2V5ZCRNGgKQppemOzYwXLW6Ywnk0jkWJCSBgmhIThmLUOXxacaHU7pUiMcIUKxU5702zuab+UFyNFZ4SOtI3pEYlaPYZodHAHAmhgfbD5fWjw+WA79XcKFCKVakSrNQiVK0EPwhnSs3lYDo/8kIUia9sVb9syJdaAe8bHIDOsMdVcEAR8ebAcr/+WD18XgtKzSVydm9F2e1lsOVCILQcK8exHm7t1LoIgiLZwvIBXvtiOlBgTbpwxtK+Hc94aPCyz+liV3uLyiU1KKXt1mtmqk4s7TmkhLjgSnPai/zw+BxIxg6o6B7745QjufvkHTBsZiweuGwuxqPWqqDwv4O+fbEFeWR3CTRrwvID3V+0FR9YNEZ3EUBRC5cpWA1MAoCkKQ/VBGKoPQoDnESSTI11vhEnWGGiyPA8BwFiTGRK6+Uzo+UjU6nBddAJ2WapazKK6AizK3U5cGRkLpUiEY9Y65NiscHMBBMjPfo+jKApKsRhKceNNgYvZlwfLuhSYimgKc1JCcMfoKCQEKZse5wUBi388hp9zLec1nhMBEWbefBnshWXY+XunilASBEH0mof+vQaCIOCmyzL6eijd9vrWfPOXB8tCvYEzrWTe3l4QuXB4ROXjU+O73Urm+uuvj9m0aZPWaDQG8vLymirMPfbYY2H/+9//ggwGQwAA/v73v5ffcMMNtpycHElmZmZ6TEyMFwBGjBjh/PLLL1ukudx9990Rv/zyi1YsFgvR0dG+r776qigoKIjz+XzUTTfdFJ2VlaUIBALUDTfcUPevf/2r3fG3daz33nvP8NZbbzWlbebm5sq3b9+ePXToUN/cuXPjiouLpQzD4PLLL29YsmRJm+k8eXl5kszMzLTFixdXPP/889UA8OCDD4Z/++23Rrvdzrjd7oNdfV9JK5l+hOcFPL90C17+3/a+Hkq3DEsy49I/kVYyfSVcocK8mASEyBTdXg94oqEeq0pOwsGyiFVpcFVUfLPZ0bPTzAHA5vehyuNCkEwOvUTWbJZNONWrVNpKe5oGvw95divybA3IdzQ0FecBgDi1FnMj42CSyVHn88Lm9yFeo+vW6yGIjiz5vRD/+b2oU9uqJAxW3jYGYeesLQWAH45V4a/rei6YTNTJsP6LDT12PIIgBi6apjA8MRQGtRxHTlah2tr1mgFdkZlgBkNTKKm2odbmRkSwBrlfP9yvag10tpXM61vzzZ/sLQlv6/k7R0eVdzdAXbdunUqtVvN33HFH7LnBqUql4k4Ha6fl5ORI5syZM+TsbVuzYsUKzdy5c+1isRj33ntvOAC899575f/9738NP/30k+6nn34qcDgcdHJyctrmzZtzkpKS/F091tnb7NmzRz5v3ryEsrKyow6Hg/7111+Vc+fOdXi9XmrixImJTzzxROWCBQtaLcgwc+bMeJqmhdGjR7tOv95NmzYpExIS/CkpKentBaeklUw/Z3N6seCZ5fjtUHFfD6Xb+s9tjovP9LAoTDVHgDnPLw6VWIwp5giEKVSIOWfm9Zi1Dt8U5uD62ESk64PgDrB45eiZm0kiikaQTAaNWAqFSIQipx0O1o8UrQHjgkMRo9I0fbHpJFKMDjJjdJAZnCCg1utGrdeLWq8HFp8Hq0vycfWpwJj0MiV6k1zc+d6+t46MbDUwBYBJsQYoxEynCh91JF0jxq8/DMyblARB9Ly/3DwJf7tzGkqqbci49d0eP36IXonpo+IxY3Q8po+KQ7D+TFaI28vC42P7VWDaWQ0elvnyYFloe9t8ebAs9I9jo2q0MnGX12JcccUVzpycHEn3R9i6efPmNQWC48ePd3333Xd6oDHrye120yzLwuVyUWKxWNDpdO1+6bR1rLN99tlnhmuvvbYeANRqNT937lwHAMhkMiEjI8NdWlra6mv8/PPPdTExMT6lUtnsvZs+ffp53T0hwWk/8c/PfhvQgSmAAfnBNRjMiYztsYJB7VXFjVapMSsiBimnqvcqRGLoJFI0+BsLyAQEHlUeN6o8zdtcZDXUIauhDtEqDS4Pj24R9DIUhRC5EiFyJQjiQpsWH4TlhytQ2tB+aq9aKsKtIyPafN6gkGBqnLFbbWhOi9BI4cotwg9rTnb7GARB9H/RZh3iw/WIDdUjNkyPuDADlm86itXbmtdlEDE0Fl6Wgaf+MAUA8NzHm+HrgRtgerUMt185HBkJZqTGmJAeFwKabv0aTiETQyETt/pcf7f6WJX+7FTe1ngDPL36WJX+DyMje7QH6scffxz89ddfGzMzM91LliwpNZlMHACUlZVJUlJSUlUqFffCCy+Uz5o1q91qkZ9++mnQ/Pnz6wHg9ttvt/7444+64ODgTK/XS7/wwgulISEhnf6BOPtYZ1u9erV+xYoVLb54amtrmQ0bNuj+/Oc/tyh4Y7fb6ddff928devW3L///e+tV3Xtph4JTimK0gH4CEA6GifQ7gSQA2A5gBgARQAWCILQuRKRF6Gnb58Kl8ePj386cMHOOWyIGTdfnokXl21Fg9N7wc5L9JzpYVEXrJKtSixpca4IhaopOO1IsdOOZXnHcEloJKQ0AwlNwyRXIJK0iCH6UIxBgWdmJGLRd4fb3Y6hKVicfmjbuUg7Wde9m8UyEY1YmsX6bzaD486nWzBBEP2ZQSPH24/OxnWXpLZ4blJmFLYfLkad3QO9WoY/zh2Ju68ZjXCTBgGOx+frD+GrDUfP6/yhQWo8fP043DV3ZFM/5MHM4vJ1Kqq2OP09Gn0/+uijNa+88koFRVF45JFHwu+7777Ib7/9tigqKootLCw8YjabuW3btimuv/76hOzs7CyDwdDqB/8TTzxhZhhGuOeee+oBYOvWrQqapoWqqqojtbW1zMSJE5OvvPJKe2pqaptpvW0d67TNmzcr5XI5P3r06GaBAMuymDdvXtyiRYuqWzv+4sWLwx544IFqrVbb419aPTVz+haA9YIgzKcoSgJAAeApAJsEQXiJoqgnATwJ4IkeOt+go1ZIccusTCxde7DXm6ZrlVIse2Yelq07hP/7YCP859yFG58eiaf+MAUpMSbsOlaGL385jA1788F2s/ok0TsilSpMM7c9k3MhJGh0yGro/M1GP8/jl/IzGQIjjcEkOCX63P6yhg63afCwuPObQ3jr6nQMD9e2eF4QBEyKMcDmZVHjbPs6gQKgkoogF9NQiBkYxDR2bdiLNWU9etOeIIh+ZtbYBCz581yEGlv/zjPplFjy57mosDhw66xMKOUSOD1+vPvdbrzz3S6UVNs6dZ7YMD1oikJ++ZkYZGRyGB64bizmTU1t6o98MTAppWyntlNJOrVdZ0VGRjY1gX/ggQcsc+bMGQIAcrlckMvlHABMnjzZHRUV5cvKypJNmTLFfe4x3nnnHePPP/+s27ZtWy59qjDl559/bpw5c6ZNKpUK4eHhgdGjRzt///13ZUfBaWvHOu2LL74wzJs3r8Vs6sKFC2Pi4uK8zz77bKvpQPv371euWbNG/7e//S3CbrczNE1DJpPxTz311PlVBUQPBKcURWkATAFwOwAIguAH4Kco6moAl5zabBmAX0GC02ZsTi+e+XATVm87AaNGgW9fvAH53z6Kd7/bhXe+293UZF0qZuBwd3hTpFPMRhW+e/FGWO0erNza+hpyhqYwY3Q8AOC6S1Jx3SWpcHtZ7D1ehh2n+uc1OLzQqqRQySXIK6tHTkkt8opqQX98HFIJg5h4A0IStaCDBmYqyEAwMTi8z1OphxlN2FBRAlege5/rXCcKslm8bmyrKsfcqDiI6YvnS5W4MLwsh80nazu1bZ3bj1u+OoCbhoXj6RmJzZ6jKAqLL0nAo1Pi8ezPJ7DqWBXkYgaROhli9QpkhGowNFSD1BB1s3WufpbD8mAJ/vzuz7B1o8cqQRD9m1Imxsv3XY4754zo8Dv7qknJABoLZH784348+9Fm1NtbX3IwJjUcbi+LrIIajEgKw9yJiZg7KRmpMSZwvIBvN2fhX59vw/3zxmDR1aP6/HqhL1ydZra+vb0gsr3UXpmI5q9OM/doZmdxcbE4OjqaBYCvv/5al5SU5AGAiooKUXBwcEAkEiE7O1tSVFQkTUpKavHB/91332nefPNN87Zt23LUanXTzFBUVJR/y5Ytmnvvvbfe6XTSBw4cUC5evLgaAK699tqYhx56qGbatGnuzhwLADiOw08//aTfsmVLs3zyhx56KMxutzNff/11UVuvcf/+/Tmn/366AFRPBKZAz8ycxgGwAFhKUVQmgP0AHgYQIghCJQAIglBJUVRwaztTFLUIwCIAiIqK6oHhDBxalQxvPXIl7rlmNOxuH6LNOogYGv9YNAP3XDsGLMshKkQLl5fFHS+uwNqded0+V4heicULJ+GuuSMgl4rxyFvrmp4bEmnELZdnYExqBIbGh8Cobdm7UiETY+rwWEwdHtvq8W1OLw7kVGBfTgUO5FTih7XZcK1gMfvSJCTOCAMlafxcEFge7kIPyk42IHFaKCh5z7QpuRjppX3f99Pq86GNZSqdUuxstfhbkyq3Cx/kHIWP5+DneSyITRz0fTeJC8fi8uHBlUeRV9u1dNxREbo2n2NoCi/MSsZjU+JhUIhBURQaPCxKGzyodHixt7QBsQYF9HIx/ByPvUdL8MHqfSQwJYgBJixIjTkTkmBzeVFZ50B2oQW1thYTYLjn2tGdCkxPO3KyCg/+ew32ZDfv3vHWI1diZHIYKiwOBOkUGJcWAafHD5vLhwhT81oOIobCTZdlYMGl6WCYi/c6SycXcwuHR1S2V6134fCIyu4UQwKAuXPnxu7atUtttVpFISEhGU8++WTFo48+Wvvwww9HZGdnywEgIiLCv3Tp0mIA+OWXX1T/+Mc/whmGERiGEd58883i02tGb7jhhuj777/fMmXKFPdjjz0W5ff76UsvvTQRONNy5i9/+UvNjTfeGJOYmJgmCAIWLlxYO3bsWA8AHD9+XBEZGdlipqCtYwHAunXr1Gaz2X/2zGt+fr74nXfeCY2NjfWmpaWlAsCiRYtqHnvssdovvvhCu3fvXuWbb75Z0d77cs8990SsXLnS4PV66ZCQkIybb7659o033mh3n7OddysZiqJGAdgFYKIgCLspinoLgB3Ag4Ig6M7azioIQosKUWe72FvJtOeaJ7/Ez7sb1ypHBGtQVtP+Rf257pozAq8+MBNyaeNM5u9HS3CyrB7DE0ORHhfc43fULA0uvP7VDry/ah9CTWpcfetQuCw+rPz+KGobGj+8EyINmL0wHYyJzK52x8Opw5u1ebnQSl0OLMvLhocLdLxxOx5PHwmDtGUFVCfrx3snjjRb0zrWZMbcyLiL8g4w0bN8AQ4LvzyAEzXt1qJo4Y7RkVg8NaHD7QRBwFPrTuBgeQNKba2v6dfJRLAfPoGTJyu7NAaCIHpOaowJceEGmA0qhBiUCDGoEKxXIVivBENTsLt8sLl8sLu8jX86vcgcEorZExIhOivwe/CNNfjox/1N/5aKGUSZdYgM1uDRGyY0ZaS1JcDxeHHZVrz6xfYWve0nZ0Zj7eu3Njvfxa6zrWSA1vucykQ0f759TvuL+vp6+uabb45Zt25dQV+PpSvaaiXTE8GpGcAuQRBiTv17MhrXlyYAuOTUrGkogF8FQUhq71gkOG3bt5uP4XhRDa6bloa4MD2+3XwM+eX1+PVgIWaPTwRFUeAFAc99vKXV/aNCtFjxr5uQFtvqBHavKbfY8eoX2/H5z4fh9rZM/aRpCjOnDEHylDBQGpKy2RU0KGglEmglUsyLToDxArdc+aW8GL9VlZ13CyEaFEwyOS4JjUCGwYQAz+N4Qz22VJWi2tPyLvQ4UyjmRMaSAHWAs7t8+GXPSYTolXCfalNw+ZiOg76eUmx1Y84nu9HZJf4vzEzGuGg9wjStt5JpzQ3/24esKkebz0tOFuJETlmnj0cQRM8J0irw0r2XYeHlGT3yfXIorxIuLwuDWg6jVgGTrvM9x4urGnDbP1Zg97GWnwd3zB6ONx++8qJaK9oZXQlOAcDmZenVx6r0FqdfbFJJ2KvTzNbuzpgSPaPXglMAoChqG4A/CoKQQ1HUcwBO94SoO6sgkkEQhL+0dxwSnHadIAiNgSkvIHre6y1SSkQMjXlTU/HGQ7OgU8lA01SfXNT7/AHsPV6OvSfK4fMHEOB4+FgOdqcPu46V4nixBfc8NBHisMFfPa43jA4KwTXRF+7C/rRSlwPfF+XB4m2/DUdnpeoMKHLa4Q60Pxs7ITgUV0aQAHWg8vhYXP3El9h2uLE4lkYpxdrXb8XIpAtTefq0p9Ydx+pjHd80D1FJsfmeCV0+Psvx2FPagAdWHoW/lSq8MT4nNm9ssz85QRC95PYrh+Mfi6a3uozpQhEEAdVWFzbuycfid9e3mtp//aVpWPb0PPJd14quBqdE/9NWcNpT1XofBPDFqUq9BQDuAEAD+IaiqLsAlAC4vofORZzl9AfWgdyKZoHpmNRwXDUpGTfNGIrDJ6tw72s/YuPefDA0jVfvn4nbZw+/oOOUSkSYlBmNSZnRLZ4rrLAi87b/4H8f7sVtj4wDrSV3B7vqYF0NppgjWk2P7U2RSjXuGJKGd48f6jCg7IzshhYF41r1e00l1GIJpvRxtWKie/720eamwBQA7p83Bnuzy7F5XwEYhsYjC8a32XPvfNn9PpS6nEjTG3Hf+BisOV6NQAfTp5lhmnafP43jeGzaX4CqOif+cMUwiBkaQTQPOq8QZQUVGJYZh+DEKOTbWTA0hYDr/H9nCILovJRoE95+7EpMymh5LXIh/eml1fhh+wnYO1hrvv1ICR58Yw0mD4vBDdPTL9DoCKJv9UhwKgjCIQCjWnlqek8cn2ib1x/AX/+7AR+ftc5h2TPzsODSxg+xBqcXNzz7DdgAjxC9Eg9ePw43Xja0r4bbqtgwPZ69cxqe/XATVn50CPPuG04KJXVRQBDwQ0k+RhiDUevzwub3IVimQIxKA7NCCaYX77pqJVJcHRWPrwpyOt64B/1cXgy1WILhxgubqk6cH47j8c2mrGaP/evzbU1/nzA0Eo/d2PVZyvbY/D4UOe2weN3YWlmOTKMJaXojInRy3DM+Bu/uKGx3/84Ep36Ww2WPfNpUxKSkugF3zR2Jn3bkIPt4CQBgz55cYE9u0z6TMi6uIoAE0VdkEhH+eutkPHLDhD5Pj12xNRsrtma3utTpXJW1Dnz80wEcPllFglPiotFTM6fEBWZpcOGjH/bj/VV7UW11ISHCgPnT0jB/WlqzdaU6lQy7P7wbeWV1uGLcEIhF/XNWcvFNEzEhPRL3vfYTtnxxAtNuTQYlJQFqV+TZG5Bnb2jxuJRmEK/RYmRQCBI1+l6pdhuuUPX4MTvD6mu90AzRf1md3hbFPk6TiBn8321Te/R8AZ7Hx7lZqDvrZyVSqQIn8GAoGovGRuP3onocKG+9h6BOLsY1aaEdnufDH/Y1q6754rLf8OKy39rdJ7vIAomIhp/0kCaIXjNtRCzeeWw24sMNfT0U/Hv573jqvxu7vF+IoW++YwmiL5DgdIDhOB7f/ZqNe1/9AR5fY0rYnIlJ+OaFBW2uSUiJMSElxnQhh9ktE4ZGYdeHi5Dxh//g/Re2Y+rYWAwZGQwmVELWW5wHH88hu6Ee2Q31CJUrMT92CMxyZcc7dsHOmr6pNurjOdj9Pmgkfd9Wh+icIK0CHz91Da5+4stmj4tFNL76+/W4dGRcj57PHWCbBaZAY/p4tEoDs1wJLx/AUzPiMX/ZgabnwzUyjIvWw+phMTMpGDp5xxXF7W4fxqdHgud5cLwAhqZB0431ANw+P1RyKUqrbSiznKm07mc5LLx2GPYfq8DR7AFfMJIg+hWjRo6X77u8xwoenS9BEPD+qq7VVQnWKzE2LQKXdVDpl+hYvd3N/O/nI/qqOofYbFSzt8zMsBo0Cq6vx0W0RILTAeDwySr8Y+mv2JdTgXq7B8MTQzE0PgQhBhX+MGsYZo5N6BcfvD1BJhFh7sQkLFmxB+u25mLd1lzcdtNIGEfq+npog0Klx4V3sg8hSCpDlEqDJK0eKToDGKp7s9QBnsevVaXYUdPp9lU9ant1BX6vrkSmIQgzI2KgFpOCWgNBbKgeo5LD4PNzOFpQDQBgAzzueHElTDolfnzlZsSGtdt5rNNEdPOf7RlhUZgWGolj1jp8XZADi9eDaJUGaSFqHKt2gKaAV+ekIjNM26XzhOhV2JlV2u42FAWMT4+EUi1BXHoQlLFKUBIKl43V43pqOFw1Xvi9AezdXYrtu4q6+lIJgjhl4WUZeOm+y2DS9eyN2POxP6cCxVUNXdrnxUUzcMuszN4Z0EXk/97faH5v5Z5Qjy/Q9IXw3MebI++9dkzli3fP6NadwZMnT4pvvvnmWIvFIqZpGrfddpvlmWeeqQGA2bNnx+Xn58sAwOFwMGq1mjtx4kT2ypUrNU8//XQ4y7KUWCwW/vWvf5VdddVVbZZ0f/bZZ0NeeOGFiIqKisOhoaGBqqoq5uqrr44/evSocv78+XWfffZZSWfG+uKLLwZ/+OGHwSKRSJgxY4btv//9b1lOTo4kMzMzPSYmxguc6X/qcDjouXPnxhUXF0sZhsHll1/esGTJkvLWjrt792753XffHe10OhmapoVDhw4dVygUTalRl156aUJpaak0Ly/vWFfeWxKc9lMOtw9rfs/F91uOYf3uk5g6PAZ/u2Ma5kxKQlAfVpe7EP559wxMzozGO9/tws6sUih0JODoabU+L2p9Xhyoq4FaLMYQjR5imoaYpiGhGShFYkQoVYhQqlvdnxN4nLTbsK6ssMcq9XYXDwEH6y04YbPiktAIhCtUCJEroBCR/rn9hc3jx/aDReB5AbPGJSAiWIOfXr0Fc/78v2bb2V0+2F0+/OGF77Hp7Tt6ZG2YnBFhqN6Io9Y6AEC8WgcAiFCqYJTKYfF6kKEPwuWztbD7WGhlYkTru/YZW2/3gKaAEYmhqKh1oKq+9d6pggAcOVmFux4YB5G5+edag+AHTDQoSDApeggJTjtBrZBg0dWjMH1kHMosdpRU23AgpwJrd+b19dCIPhITqsM7j87usKdoX8gpru3S9hQFTCTr0s/b/72/0fzG17+Hn/u4xxegTz/enQBVLBbj9ddfL5s0aZLbarXSw4cPT73yyivtI0eO9K5Zs6ap3+if/vSnCK1WywFAcHAwu2bNmpMxMTHs3r17ZbNnz06sqak50trxT548Kd68ebMmNDTUf/oxhUIhPP/88xWHDx+WZ2Vldap/4I8//qhes2aN7vjx48fkcrlQXl7eFPtFRkb6Tpw4kX3uPo8//nj13LlzHV6vl5o4cWLiN998o1mwYIH97G1YlsWtt94au2zZssLx48d7qqqqGIlE0hSYLlu2TKdUKrs1M02C036motaBN77+HWt+z0FksBaTMqLwxsNXIDK4a3fxBzKpRIRrpqTgqknJ+GjXIRRLW/a6JHqOg2VxoK6mxeOXhUW1CE5rPG5srixFnt0KL9e/smE8XADryoqa/q2XSDE1NAKjg8x9N6iLnCAI+DnHgn9uzkMgKwcHj5c1Vst89EpMyozG3VePxojEcmQVVuP3o2dmHfedqMBflvyCv915CfTq8+vfS1EUUuWhWLPfDoWUxnJnJR6drIRWIsWtCSkodzkRplC2m31SUevAxr352HqwCDq1DJeOjMXsCUlwevyY+cgyHMhtntY+Pj2y1VnU8ZmRGHdDAihJ+5kKcoggFtFgyVrUJklRQchMMCMxyoghkUYkRhqRGBkEhaz5TSi7y4eIa14l791FKFivxCMLxoMNcMgtqUViVFBfD6mZ8emRnd5Wo5TistHxKK5q6LEskotRvd3NvLdyT7tFA95buSd08cKJNXq1vEsfGtHR0Wx0dDQLAHq9no+Pj/eUlJRIRo4c2bSOhOd5/Pjjj4YNGzbkAMDEiROb7uaPHDnS6/f7aY/HQ8nl8haFGB544IHIV199tWz+/PlNfQI1Gg0/c+ZMZ05OTqfXMr333numv/zlL5WnzxEeHt5umXi1Ws3PnTvXAQAymUzIyMhwl5aWtpglWrFihTYlJcUzfvx4DwCYzeami0KbzUa//fbbIR988EHxjTfe2OU7RSQ47WfUCgn+vHAiXr3/8kGTqttZVW4XlGIxXAEWITIFaJrCuOQIVBSdBCuQC40LTdvKOs4gmRxBMjmOWrt2B7gvWP0+rCrOR7RSg2D54M426I9O1rrwz8252F3SAEEQoBEEKOUSHC+2oMHZ+N19y6zMppS1V7/Yjmc/2ty0//ur9uKD1Xvx/Ys34orxiec1lhi9AierfbB7A9gOB745VIVHJsdhRIQWh8rt+PbIcaSGqDA31YwxkToAjcspftqRgzW/5+JQXvOb6h/9uB8RJg1omoJUIsLolHCImFMBpyCAohor8W4/0phxRVHAmKERGDMrtsPAFABsvB9P//0yvPnqb7A29G1mwoUiETMIMahgNqgQYlAh1Khq+ndChAFThsV06jtRo5Ti4QXjoZZLEB9hxK5jpdi4Nx8nzpm1Sow04tYrhuHTNQeRX965FlZE/1ZjdeGRt9YBAORSEX5bchfS40IAABv2nMSxIgt0ShnmXZIKjfLM99vpdNt5U1N7dXyxYXqEBalRUdtmFicA4P2/XIUbZwzt86rCg8H/fj6iPzuVtzUeX4D+38+H9Q/OH1fX3fPk5ORIsrOzFVOnTm2WNvPzzz+rgoKC2KFDh7boGbRs2TJ9amqqu7XA9IsvvtCGhoaypwO/81FQUCDbunWr+tlnnw2XSqXCa6+9Vjp16lQ3AJSVlUlSUlJSVSoV98ILL5TPmjWr2fhra2uZDRs26P785z9Xt/KapRRFYdKkSUPq6+tF8+bNq//HP/5RDQCPPfZY+MMPP1ytUqm6dfFOgtN+Rq2QQq24OIu7fFOYi2qvG8EyOR5OGwEAyDCYEKFU48eSAuTarX08wotLgcPWok0LTVG4NDQSeyxVcAU6LoPfH5xusZOsM5BU3wvE5Q/gpi/2w8023kilKAqO+DiExsViglmBOROTWuzz4PXj8OKyrfCxZ2bkBQF47uMtmDl2SJf7nta7/dh0shZyMQOr2w+3/8xx3SyHf25unvqZY3FiZVYVLk8Iwq61O1sEpGfzsxwKKjr+PFp0x1jITVLQShqUsmsXmjZpAI8+cwkObS3Fih+yOt5hALv7mtF448FZPdbb9oU/nelid90lqThZVoeht/4HWqUUV01Oxu1XDsf49EhQFIWbZgzF4nd/xqrfjvfIuYn+weMLYNoDSzExIwpmgwrL1h1qeu6N5b9j+fMLmgpFquUSvLdiT68HpxRFYVJGNL7Z3Pbvs14tw8LLM87c7CLOS1Wdo1Nf+lV1zm5fHNhsNnrevHnxL730UqnBYGgWjP3vf/8zXHfddS3ufu3bt0/27LPPhq9fv77FGgSHw0G//PLLoVu2bOmR9Qkcx1FWq5U5dOjQia1btyoWLlwYX1paejQqKootLCw8YjabuW3btimuv/76hOzs7KzTr4FlWcybNy9u0aJF1ampqf5zjxsIBKi9e/eq9u3bd1ylUvGTJ09OHD16tNtkMgUKCwulH3/8cWlOTk631uWR4JToN66Kjsd3hbmIO7Um7DSDVIYb4xLxwqHdaL0BBdEbTtjq4ec4SJjmF9U0RSFFZ8C+2hY30vqlQqcdhU47QmuUeCB1WF8P56KglIhwTboZXx5sXkOBpygcaWAhCAIoisKOoyW46dlvoFXJIBWLmgWmpx3Jr8YXvxzGrbOGtXvOUpcDx6x1yG6og93vh14sxwe/dP2G1uaCOthsPTNbWVpoRUpa51P5ziahaVA8MHxKJHJya3DsRMvU+8Hipx05eOC6MUiIMPbK8WNC9bBv+L9WW6mFmzT46u/XY+maA7jvtZ965fwXq5fum4apI6JgNiqgkIpA0RQoADanH3klVmw5UIK3lu9p9fe+Jzg9fvy8+2SLx/NK6zD53o/w4ZPXoMbqxOJ3f0aA43Gi2ILk6N7tbDA5s/XgVMTQGBJhxILpaSQw7UFmo7pTd9HNRlW37rb7fD5q9uzZ8ddff339bbfd1nD2cyzLYv369fo9e/Y0W9OZn58vnj9/fsLHH39cmJaW1mJG9fjx49KysjJpRkZGKgBUV1dLRowYkbJ79+7jUVFR7abktsZsNvvnz5/fQNM0pk2b5qZpWqiqqhKFhYUF5HI5BwCTJ092R0VF+bKysmRTpkxxA8DChQtj4uLivM8++2yrXz4RERH+cePGOUJDQwMAcNlll9n27dunUKlUfFZWliI8PHxoIBCg6uvrRWPGjEnas2dPTmfHTH4DiH4jRqXBnYnpqPN54D5nVk7KiDAqKATiblaVJbrOHQhgU2XrheBSdb1zEdmbqjwu8AK5vXGhZIZqWn380SlxTemZTrcPlgY3TpbV41hh28HXI2+tw3VPfYWn/rsB1a0UG6ryuPD+iSPYVl2OOp8XrMCD6+ZKALmYhraHKnzW13c/yBUEYOl/duOZxesGdWB6eimLRNx798pFDN1hj+87Zo/AE7dM6rUxXGw2vn0T7p6XgeQYHXRqCSQSGmIRBZGIglEnxbgMM/56+xiU//QA/nbX5As+PpeXxRtf78DOrFIETn1Y/LDtRK+fd8bolq2y7pozAnXr/ooDn96LJ2+d0utjuJjcMjPDKpeK2v02kEtF/C0zM7t8J5Pnedx4443RiYmJ3ueee67F3frVq1dr4uLivPHx8U0XtLW1tcyVV1455Lnnniu7/PLLXa0dd8yYMZ76+vrD5eXlR8vLy4+GhIT4Dxw40GFgeu2118Zs2bKlxRqmuXPnNmzcuFENAEeOHJGyLEubzeZARUWFKBBoPGR2drakqKhImpSU5AOAhx56KMxutzMff/xxmyXor732Wvvx48flDoeDZlkWO3bsUKelpXmfeOIJS01NzZHy8vKjv/3224mYmBhfVwJTgASnRD9jkMpwdVQ8dtVUtggkrolOwF8zx2BySIuia0Qv2VFdgRJny/Ux9ef0jRwIaIoCy5O1yxdChd3bIm02SCnBI5PjsCCz8fdXEASEGFQYk9rx77Pby2Ltzjy8+c1OMOfMKgiCgDWlhS2yKhx2dIvDxyFhzPmn9wXpFJhwQ0LHG7ZCEAQEOAFXXZWBYcPicMVV4zB3/mTMmTcRg6kUgUouwUPXj8Ndc0ciKqTvi/49e8c0zJ+W1tfDGBRmPPQVOvNxyzDAQzeMQLT5wv/3l4gZ2Jxnvsvcvt5fqhITqkdiZPObu9dOTSHrS3uJQaPg7r12TLuN2O+9dkxlV4shAcCGDRtUq1atMm7fvl2dnJycmpycnLp8+fKmH+SvvvrKcP311zdL6X3llVeCS0pKpC+99FLY6X1OV8+94YYbon/77bcOC2SEh4cPfeaZZyK/++47Y0hISMb+/ftlAHD8+HFFZGRkix/ihx56qLawsFA6ZMiQtBtvvDHugw8+KKRpGr/88osqOTk5LSkpKXX+/Pnxb775ZnFISAiXn58vfuedd0Lz8vJkaWlpqcnJyalvvPFGENC4FvaRRx4JAwCTycQ98MAD1cOHD09JTU1Ny8jIcN944422rr6PraGEfjSTMGrUKGHfvq41KCYuPpsrS7GpolOtnYgewJxaZzrZHA6GosHyHF7P2g8HOzDWnFIAhhmDMd4UCoNUBrmIrGbobVvya7GtoA5VDh9MKgmuTA7BqAgdmLPWFB4+WYXpDy6Fy9v5n6MV/2xZHCnLWouvCs7clFWLJHBYxVh7sAF+rnvfbxFqKX77emO39j3bvXdPgCrSgPIqAV6/ALGIglxCQ6OkIFVwEEQseIqHQPGAAFCn3h9HlQKbjje0esw0mYAfv99+3mPrLrVCgolDoyASMRCLaJRb7NiT3WoLvA6NT4/EU3+Ygumj4vpNAUCPj8Wsxz7r9mvqTU89NR2yIAmqc23YtDkPeQV14PphVWKxiMY3L87DJSPCGz+AOyG/zI5Rty/t3YGdRSYRYet/7sTStQfx35V7AQCLF05stl65tzz53i9465tdAIC7rx6FV+6fSYLTbjh+/Dg4jnOnp6d3uGC8tT6ncqmIP58+p/1JfX09ffPNN8esW7euoOOt+4/Dhw8HZWZmxpz7OAlOiQGnwe/DW8cOwE9mwS6oMIUSmQYT9tVW93lv047oJVJEKtWIUqlhlimx01KJXJsVdySmIVrVeropceEJgoDlm7Lw0Y/7seNIxzecnr59Kv7vtqlgAxxW/nYcBwsrIY+Qw+X0IzfHgokzYuGTCPhyY/fbTwmCAAaA2V6H7dvPr0jOpFEJqAhpt4sBaAoIUUuhkjLQK0QQABTWelDraj1oT9eK4aiux+7fs+H2tKhR0WvEIhqLrh6NJ2+d3KLXdkWtAz9sO4FV245j2+Fi8HzXriuSo4Pw+bPXNVVW7Ws1Vhem3PcxhsYFw6RX4qsNR+H1d3mpV4964olpYE3NswZoUNDQYrC2AFZ9exRHs/vHNfZv792CoUO6vvTjszXH8fC/f+mFEbX06v0z8cD8sai1uTH0lnfR4PQiIcKAI5/d3+s3SkqqbbjqL1/grUeuwNThsb16rsGsK8EpAFgdHvp/Px/WV9U5xWajir1lZqa1OzOmRM8hwSkxKNR6PbCzfjhYP47U16LYaYeH69uLBqL/UInEuDo6vmlNrNXnxYc5R2Fj/bg6Kh5jTKTnaX/h9Pjx8L/X4ssNjf3HxSIaRq0CVXVOhJs0SIkOQmyYHjRFgRcEzBybgNkTGqv8CoKA55f+im82ZbWomnvVlanIYQxg+a5dYDIQEMt5UFdag2N5jVlgo5LD4PGx2J/TblZYu8bPnYhqvudX0AzViLD6qy09ftzWLLg0Hc/dNa1T/RZrrC6s3JqNb7ccQ3yYAX+8aiQyE8xgaAo0TSGroAYfrN6Hn/ecxKKrR4HjePj8ASxeOKlFz9K+VFzVgFCjGhIxgzqbG99tOYYgnRIZ8SEIMajw8U/78dR/uze7HmRUYPYVqbDUOLF2wwl0VOmPpoHnXrsCDXzbNyOYqgBefW1rt8bTk5YsnoWbZrWsxt0ZPA/EXfsebK7ev+my5d07MO5UsbJFL6/G5+sPAwDWvnYLpo1suS60p3Ec32KJAtE1XQ1Oif6HBKfEoFDldmHJicPgBQFhChXMcgUkNAMBAnZbqkg130FCzogwRKODXCSC6FQRLAECfBzXdHPCzvoR4HmoxRKoxRKEyBWYERbV1C5GEAR8kncMBQ4bMg0mXBUVBxlDUnr7g+KqBsz9yxeIMeswbIgZ5RYHHpg/FulxwXB7WWhVsk4dx9Lgwh0vrsSmfWcymcJMGsjGZHZpPAk+B05kFaGkqqHFcwqpGCOSQuH0+KGQivF7Vpv1IZrRKKUYNyEVJRIl/J3NbewCCkCMVgol64PX6YVMo8CeLYdQVdMjS35w5+wRqLO7sftYGQq/f6xHjnm20xWbB7J3v9uNT9cebLeY12mMiMbNNwzHkGHBsFEs+FPfVnJaBDFFg+aB3346iY2tdI+QShk89cwM2GRt34iV0DTkbho5R6qxY2cRUpJDEB9vhEYvg0wpBsfyaKjzYOXKoygt79rPCE0Ds2emoKzchoNHKtrdtuzH+6GUd/9z9v0VR/Dkkt6/6XJo2X1IigoCANz5z5X4asNRAMDolHBs/c+dA/5n82JAgtOBjwSnxKBR7XGj3OXA3tpqlLgai/XEq7W4LCwaW6pKkWMj/VAHMr1EituGpMIkO5M66OMC2FRRCpqiEKZQIlGr7zDQPFBXg++LGi/0gqRy2Fgf7k3ORIi8w3oDRC8TBAEl1TZEm3XnfSyeF7D1YCG8/gBe/mI7ZHGRENQqlNk6X7QrzmXFxl877iXK0BRMeiUSwg3Y3k4askEjR/LU4ajiL+w6Mr1cBLOMAcPz8NbbcTK3DAUFXU/1zEww47cld0EiZpBTUtt0EU+0JAgCnv5gE3JL6xBu0mDv8XIcyDkTwKmUEtx26ygYkzRwcu2vr6YAqBgxaIECHQDcVh+qKxyIyQxqd9a0K0QUDcbC4fU3tsLvb7+FC00Dty4cidgRwbCfOr/WJ4Lb5odWKUGaQoMPVh7E+t35eGHRVNw+Ox1y2fn9zDvdATzz/jb8tCMPtQ29s3xEJhGh4oc/Qy5tvJG58LlvsXLrmfjm82evI4WxBoDjx48jEAi4hw4dSoLTAYjneero0aP6zMzMFqkKJDglBiwvF8CB2hrsrKlEvd8Ls1yJySFh0Iol2FRZikJnN8t1DgC1+6wwjtA1FVAZDCKVKmQaTMg0mMBQNBysH+5AAAIERCnV4AEcs9Yiz96AcrcTcWot5kS2nn7lYlm8eewA3OekfIcrVIhWqZFrsyJKpcFUcwSCZPIL8OqIC0EQBByusOFQhR0rsipRbvPC24mCMXLwCHXZsfm3rA7XS4YYVIgM1qDe7kawXgWGpsELAmiagsfHQipmoArSIV/ZcQpsb9PJRDjwfddnod58+Arcfc3oXhjR4GdpcGLpmv1gDQwkBgm8Eh5evnf6eJ4PPSQoz7GCoihYrW4UFVnBBXiMmxCNoDAVKBkNH8XB08bY70tOhlHWeINQENArVaRZVsCBnBrc9MwqWB09VyF+xqg4/PjqLU3/HnrruzhZVo/po+JQXe+ExxfA/k/ugVRCMm36s8LCQlitVt+wYcOO0TTdf4IZokM8z1MWi0VbVVWVnZmZedW5z5PglBjw7Kwfa0oKcNLRAC/HIUqpxl2J6dh6rAiL//1zXw+v07ryu1hc0YCFNw6HNkEFyKgBHaQyFIUbYpOQqjOgzO3EbksVjtbXIiCcCSqilWrckpDSlLILtJ0WWO52YnlBDuo6aHdDA3g4bQQ0EgkkNKmUOBgJgoDP9pfhlV9Pdmr7EWoaOftz4fb4ETE8ESKBh7eqFgGWg8vhhk4lQ2mNHcXnpP9SVOMFOgCYjWqETchAQy+sM+2qONaFjb8c6PJ+P75yM2aMju+FEQ1ugiAgIHjBCX4crLPhp9LOpYAPNBODg3FpWPAFO1+AE/D0f7fh/ZUHe+R4/7r3MjyyYDwAoKreidjr3oBWKUX+t49CKZegwemFmKGhlEt65HxE72BZFp9++qltzJgx9SCtMQcaHkBWIBD448iRI1usiyC3hYgBTyOW4Kb4ZLAch3988RvEMRxc0X5MS4uFx8O2uJAcLD75rLH8vVTMICZcj4Q4I2LSgiDRieBvCECsFoHSMaBoCoKXh7fcB1m4FJSs/3yGi2kat8SnwB1g8Z/jh1HpadmTWsYwmBgS3iwwBdDmmqATDfUdBqanjoC3sw/i2ugEDDdeuAst4sKxeQNY8nthp7ZNN6uRV++GKzEBlCCg9HRBpZAwAEBweSm2Hypq2p6mKSRHBUGjlCK3pA4MQ2FIhBFKtRwN7ZxHT/EIoji4q2pBixhwQUZUcTT4Xph6UmiVXd4nNcaECUOjenwsg52fc4EHh9PVjYYZtGAoCqtLBlfbM41IjGmhF/bzUsRQeGHRZHyw6iDOvocrl4pw25UZmJgRgaRoA65/aiWKq9pfTxsWpG6WsqtVSgEAN8/MbApGdZ1c8070LbFYjEWLFp0UBGFUX4+F6FkkOCUGDTHDoLC4Hq8s3YZHxWvx0ys345LhMVi27lBfD61X+VgOOUW1yCmqBTbnNHtOrZAgzKRBflk9AhwPqZjBJePjkDTGDCZE3KdFH2QMg1viU5DdUIffa9quhjpUH4Q0fefaEjT4fdhe3bI/IYXmBTHljAgCBHg5Dvtrq0lwOkhl1zjg9HOI0cvB0BTy61q2mNHJxJCJachENByn1uAJ5/xemGgeFEVhUkYU2AAPsYjGjqMlyC6yNNvO0uCGSadARiKPsoJqqBRSyOUSBIcaQTM07HV2ZOWWY7/bj4kZUdi2tzFw0apkGDptBCp6YI2qlKExRMVA8PmRd7S4y/tnF1kw46FP8dJ9l0EqEWFsasR5j+liwKP5EgKKAjIMGqTr01HnY5Frs+PXykoM9L4Vfp6Hg+Xg4TioxCJQoLCjugZ6iRTDjDqIeunep1hMYeXL81FQ3gAAiAzRYNrISDCnfmWOF1o7DEwjgjX4+Y0/IMJ0pp2YXCqGRinFpIzo3hk4QRBdRtJ6iUFld3YZLrn/EwDAyOQwjE+PxLvf7e7jUfVPSTFBmHRJHDSJKlCSCxukBkllWBCbhF+KirBnZwlUJhl4loc0RtYiYNZJpFicPrJTgbQgCOAEAbwggEfj38UUDTFNw876sa6sEPU+H26KS8L68iJkWeugFUuweOgo0KQ646DB8QL+b/1x7CttQKXD1/R4glEBb4CHUSFBlcMLCkCVs7HQi04mQoO39Wqo4ZYqbNvTsorquWQSBiadEqU1nVvvPi4tAruOlQEARg+NgjUy6rxnUJPgQ+nxIuSV1sHHnv9ax1fuvxwPzh933scZLARBAC+woCgGFGhQFAVOCIDlW2Z9nMviYfHfnJwOtxuoRBSNPyUNQdAFbgnkdAcw+vZPUVXf9n+DyBAtfn7jDy3aIbEBDtrLX4ReLcemt29HcrSpt4dL9CCKovaTmdPBh8ycEoPKmJRwhJs0KLfYsf9EBfafaL/s/cUsp6gWOZ/WQquSYcGCDKhT1RfkvCKKRqRKg69zj2PFR4dxIPvMf6OH/zoFjLH5hU2D34cylxNHrBZcHh4N8TnrQ3lBQL69AUO0elAUBVEbF/cCgBiVFvNjQiCiaQR4HjQoTAoJJ4HpIOLyB/DoD8ewo6i+xXOlNi9STCrQTifUdhcsRVWwV9Zj2IR0VPkE4KyWL7QgQEkDGnAoL6/t1LmHJ4ZiZ1ZZp8e693g50uOCkVVQg71HS3B5iBEnpSoAgFREQ0RTcLVTUVVEU9BIRQjTynD7qEiEKUQ4kFWCTS4ncko6N+aOvP7lDhKcnoUXWLCCpykVgwINoZPzoSa5GGNNJuy2WDreeIBQi8SIUClhlEghF4mwo7oGV0WF90qBpLa8tXx/u4EpRQGrX1rYap/eWpsbggD4WQ6zF/8PWf97oKmKL0EQfYMEp8SgQlEUkqODUG4ZvJV6e5rN6cUnn+7F9IkJSJsVAUrau2tSAwKPg3U1aDhibxaYAgAltH5F83tNBcIUKnxVkAOFSAwxTWNicBiCZHKsKyuExetBvEbXbpCpk0gxLji06d+3JqQOil6LRHNWN4tEkxK7S6wInKq8KwgCVLSAYGs9nB47ThwpbNbTdOPaPQCA0CA1YiKDwDAMck5W4mSDC+PSIhCsV8KoUWDv8eYp4xKpCKw/gMhgLSJDtNjRTnuZ1nC8AK1KBqVcgomT0yEEAoAg4LW5aZiZFIyNeRZ8vr8MJ+tcsHsDUEoYuPwcxAyFRybF4bqMMKilZ77GD+RU4O8fbUa1teNZvM5qcHrx3so9uPfaMT12zIGME5q3dOlsYHparq1n+tD2Na1YjNuGJEArOTcV/cJWqRYE4P2V7Rf9uvnyTKTEtD4jGqJXYfiQUKx6eSFe+nxbh9W6CYLofSQ4JQad2NC+b+Ew0HC8gF+25WHLznzc9+hEMCG9XKWQE7Bja8tCNW0tMzhirUWh044RBhP0Mhn8HIdChw07aiqwx9LYx3FLZSmmh3WtkAsJTAefCJ0ci6cmwFVhwb5yGwS7E7m55bBRFI62UxxNq5TC62NRVGJBZZ0TADAqOawp7RYA0uOCoVXJwLIcIkYkIcsegCAISBRzWLPy926NNxDgMXFSGk6KlYAYuG1kJK5IDgEAXJ4YjMsTgyEIAjYcLsFNT32FiMggpA5LwG2jIlv8/OaW1qGmoecC02C9EmmxwbhqUnKPHXMg4wXuVNGj7vFxAqz+nulX2peilSosjI/ptfWlXbHraBUc7rbf0z/MGoZ3H5/d5vM0TWHtG7dCp5LhjYdm9cYQCYLoIhKcEoOO5lT1PaLr2ACPt1/bhmnj4pE5NwqUpGevPgRBgL/EiyM7K5BT3DLtcON3JzDztjQoNVJoxBJIGAYMRcHm96HO58XWc4odUQDi1FrMCItCtErT4njExWtklAEvfbChU9s+ftME/PXWKXB5/bjh2W8QEayFAAE5xbUQi2jIpWKoFRJkFZypeM/KpKAiIhAQgON+BjNnj8Zvmw7D4+1a8GGxuaCNCEasox5Txifjz5c0b+EiCAIefWsdPvhhHwQByM2tQG5uBaZnF2Jkchh0KhmumZKClVuz8dLn29BTZSSevHUy/nbntPM+jiAIEMA1BnZCY99iES0FDdGAuDnUeMNMAC8EEBDOL7CUMhQuDQ1DdkM9qjw917fzQhhnMmG40QCDVIy+7FzGcYDN6YNGKQEb4HHdX79vc9v/u20K/u+2qe3+nPk4LziRAwCp0EsQ/QUJTolBZ7C2jrlQBAHYvDMfqWPMkER27Qtb4AU4c1zIO1qDANcy3Y1leew+0nbvv2P5NRizOxwvLp4LALB43fi1sgyFjjOpcFqxBEO0egzR6BCv1kEuIh9jREsrtmZ3etsJQ6OglEsglYhw5+wRWHhZBm567lvsO16BxEgjahpcKLc4oJCJEaxXQiJmEKpXIe+sSDAPMlw6axTWrPodNEOB5zoXJRaUW8EGeMyZkIQbh0e0uJCmKApvPnIl7r9uLIbdvgQ8LyApKghXTU7GsAQz0uNDQKGxyi7XQymJ91w7Gs/eccl5H4flPS3SYBsfd4MCDYaSgqH6tmp4WwSBB8t7mrWH6QkTQwyYGGIAAHACwPIC6r1+rCwuQb3f18HeF8ZDqSmQMQwa/CyqPB4katSQi/r+v9HJUjsmLfqsw0JfDE3h3cfm4PbZwzs8Zp3Pgkp3KQICixB5WE8NlSCI80Cu6ohBp4gEpz2itsSJsC4Ep4KLw64V+dh5uOuN5ykKmJQRjQfmj8WcCUkAgB3V5VhXVtR0WZimM2JccChiVZp+eTFL9C9zJibh+1+z4Wc5mA0qjEoOw8Z9BfD6W1bktTkbZ7FEDI1bZw0DALx6/0xs2lcAhqHg8bIAALeXRVFlQ+NOUinoZB24swLU4yyD6QtnQOH34sfvtnd6rFeOG9JhSqFeI8czt0/FiKQwzBgVD/qc6asv/jYfWQU1+G7LMXy27hCq6p2dPv+5hsaF9MjvmCC0HUQI4BEQPAgIXogpGRi6l5cSdBl1aj1p761BZCiAYSiEKaW4P3UISp1eHLU2YH9dzxSz6o5Mg6FpHWmIXIwQef8pDhSkk3cYmCplYnzx3HzMHDukU8d0sI03PstcRXAHXDDLwyEXKSAIArycG3JR13sFEwRxfkhwSgw6RRXWvh7CoFBUUI+wiUGd2parDWDZf3ajwdH5VDWJmMHUYTGYOTYBV09JadZ7DgBsfj8ENBYymhedgHiNrgujJ/oLQRBQ6/YjSCG5oDcV5k1NhUYhxfur9+GDJ66CXi1Hvd2Dtb/n4vF318PuOjNL9chb61Brc+Puq0dDIm68MI826/DCn6Zj8bvrMSo5HEdOVjW7MM7Nq8BVI4Ygy9k8eCm0+RBmrcP49EhwHI9qqwturx9efwBalQzRZh3qbW6U1tiRmWBGrc2NcemRHb6eIK0CT946pc3nKYrC0PgQDI0PwSM3jMfj76zHVxuOdvVtAwA8+O810KllmDc1tVv7nzWqTmwjgBU8EHhAdFaAemb9eWMV5Qt9Q4qiKIhoGVi+ZW/c3hKpkiFSZYaYprCrjyr6Hq6vx7RQM9TifrCg9BxqRfuXrEFaBVa9vBAjkzo3AyoIAtyBM2u0630W1PsskDPKpuJ6ybqM7g+YIIhuIX1OiUFlf04FJt3zUV8PY1AYmxGJiX9IbPG44Oex/sMs1DacuWhzuHytzki1RSETY8Obt2FEOxcR7gCLWq8XIXI5pAy5jzbQCIKAXSVWvLmtAFlVDijEDCJ1cogZCoIAyMU04oxKhKqlcPk5BHgBIpqCmKExNc6IoaG9t4b4thdW4JvNWS0eH5Maji3v3NlsVnLTvnx8/NMBHC+ywO1lUVJtA00BEzOioYgLR56fgVzMwBfgcDqrNlEnxfZV2+B0dZymefc1o/HaAzMhYno+GFi97TjeW7EXAZ6HzxeA3e1DVb2zWWDelqnDY7D+jT+c1/n9nAs8Ov+5QEOExg7FzZcEUGAgpuWgqXMrw3aeIPDw8T5I6Za9lNveR4Cfd3a5Iu/58nECXjl67IKeEwAMEilujo+DTtr997k3OVwsoq5eArVC0qII0uiUcHzwxFWd6lPq53xwBuzwcz6Uu9uusC2ixMgwjCKZOv0Y6XM6OJErPmJQWfpT+yXlic5haApjL49p/UlWgNPth+U82lW88eCsdgNTAFCIxIhS9Z+UMqJrfi2owwMrz8zcuVkOOZbmqab7ylpvq/HZ/lJcmx6KsVE6jIzQQSMVodbth6mHip3dduUwrNia3WJd9J7scixdcwB3zR3Z9Nj0UfGYPioepTU2/Ouz35BTUguOE7DtcDFwuBhTRsXjL4sug14hwVPrTqC0wQMx0JQK3J7YMD1evf/yXglMAeDqySkYkxqBjXvz8exHm1FV5wRFAZlDzJBLRDiUVwlvG31UPT4WAY7vtbG1pq1AVgAHP++EhFaCpjq+bAnwAbgDLkgZKSR0489MdsNheDkPJLQEWokBIkoEVmBBnfofTdEQUSIwtAhaiR5iWoKA4L3ggSnQWDjp3uQkfFP4/+zdd3wkd334/9dnyvaiXk7Sna73Yvts44aNscFgYzAdY0qoKV8SQkgC6ZBfOgmEBJIQSgIkAQwBDJgYYzA2uOA72+fr/XQqd+pt+87M5/fHqu1pV9pdrdrp8+Rx+LQ7OzPSraR5z/v9eb/PYWo6adumfx7Xo3o0jevrG7iurmpRmx3lo2GQSKf51k9P8huvu5aPvu0mnjrczif++xesqgnx66+7hut3TO9enYuUkjOjx4laucveDWGyOrAWnxHApblVYKooi0BlTpXLyl9/5TE+9sVHF/s0lr133nsVVVdWACBtCSM28d4kR5/v5uf7zs258cqPP/1ObthZ3NgXZfm564tPc2EkQcIq/QJfAKtCHjpHElzfWsldWxuIp23StsPbrpq9HDafn+w/w30f+yaDl5Si65rgT37lFj58743T1nUCtPcM841HDvJXX36ce+7ewc5djbzvRXtwazrfOdDBF59pZ/jYWZ559vSs53Dn9Zv45l+8ueTPoRjH2nq54p3/kvXYqpogw9EkYb+btasqp81p/ZU7r+Azv3NXyRfol2ZONWFiCi8SG0umcOTsAfxUhQSnjuNweOg5Uk4mmDOEgc8IMJIeKvg4hjCp9TZQ5a6ARQhO83HGGijZUuLSNHSRKXqOWw7Hhkf4cVcXKSf/+a4NBNlWUcEqvxdTaOiawKVp+JZAs6NcMk2zXBiam8cPnCHo87JnY+PsL5xB1IpwbOiFif1vCm9nINlLf6IHCWwOb8dvBstw9spCUJnTy5MKTpXLyunOAXbc98+LfRrLmqFrfOCPXgyGoGt/P//34xMTDWPK5a7rN/Hqm7byltt3oi9gZkZZWL/6rQMcujhCyGMSdBtoQvDChZGy7HtrXYBvvv3qOe3jfPcw7/z//pcnD01v4nXLFa1cu72ZPRsbec2Lt057/mfPneVJp5dR0jRFPHz6X38x0Sm8tsJHPJkmEp8efF21q4lX3rMNI2yg2XDv5q2sCgbynmPacWiPjnBmdISBZBxHShwJAdPk6poGGn2FN2xZ94ZPcqFvNO/zV25upGVtJY88fopINFM2+ee/9lI+/MYbCj7GVOPBqYaRGR9zSWBZdNmvMDGFByGm/8yQ0sGSCaLpKOejbaSd0sa+aGjUeRuocIXRteX1s0lK6IolGU5l3ncHBwfoTSS4e/VqWvwelksSUEPHmGMZdz5pJ8ULA5nrzFpPA6sD64BMtj3pJPAb+b8XlaVHBaeXp7KV9QohdGAf0CmlvEsIUQV8HWgFzgFvlFKqTjXKvKoIqFllc2XZDp/+858hhMg5DqYUPo9JfVWALatruHZ7Mz6PybqmShWYXuY0IRiMWwzGMwGILqA+4KI7Mrd5ka/YUsef3r55zue3uj7Mw596B5//3n7+6suP0T2lVP3R587x6HPnuG3vOrasqZm2lu3mK9Zy+kSU0dFhfvzoyawRVtFEmj0bGxgcjVMT9mE7ks7eUWzHQbcEZshgyEmBgG+eP8m1dQ3sra7PCoYcKXm+v4cfdZ1nNJ376/V070XW+INcU9vAlooqPHnWZsctiycvdvGaN+5ENwV9bRG+939HiI6VHtdU+FizqoL9R7rYtbeJ3/v4S/ns3zzONXtXE9+o8/jFDm5qaC766yuEhpA6ujBzZjw1YeBIi0x+fPYb5Y5MY2NgiOzGSZZMYstkpvlWope0kyJgBInZMZwZOgZfapW3iUpPRcHbLzVCQJPfTdNY+fu2yuUTaOnCjSFc2GOl1vMRmEImK74huBVb2mja5DEMzcDQls/XS1EuZ2XLnAohPgTsBUJjwenfAgNSyr8WQnwEqJRS/v5M+1CZU2WuTnX0s/Ntn1ns01DGuEydPRsb2LG2nut2tHDfHbsX+5SUBfSNA1187OHjEx9f1RRmf2fudaazecWWOt6yp4n11X4qihxv8dX/O8BjB86xpqGCP3zHzXm3i8ZTvPuvvsN3Hz827blbrmjlg2+6LmtExV8e+CVRK43Tb/HMD8+CDT2DEQZG4/QPxwForAly7bZmgj4X5y4MsXZLNTVXV2JqGi9uaCZkuggYJs/193BiZBCfYeLVDVKOTX+y8IoFDWgJhGgNhIhbFgOpBBoCt65zfHhgerlnQvKz/z7GiXN9uDw6H/zILQxE49hRG6PBhYZACCZG5bxr4/Z57ZgtpSTpjFLY6JbMOlFT8yKRE3NThdBxpIUtLXShY0ubgcQgPYnuvHtq8a8haAaWTVZxudEwZsmOCwzhWdB5t22R0/SNvSd2VF6JW1c3tZcrlTm9PJUlcyqEaAbuBP4C+NDYw68Gbhn7+38CjwIzBqeKMldPHCx+xqYyP3ZvaODffv9uKgIeVteHVWOJFehUX3bTEbvEm6GbawN85CUbqfGXNgvzsQPn+Mr/HQDgVTdsZteGhpzb+b0uvvbxN9J2cYhX/s5XODNlLFV12Mcf/tsjfOH7z/IvH34V1WEf5lims6LOy2A8wZHjPQC0NlagaxqReIp/+fBdWQHtI13nOT0yxI0NTYymUyRtm6FUgkND/QCkUkmGKL75jQO0RUZoixRYNu0RJHEyXU9j8MyjbWy7rYlUUB/bn8yKE79+9gTbKqq4o7k1b4Z2LoQQGMKNJQsJyCUSScrJZLoN4cHQ3JnZlM4wGhpSSkZTUQaS/VmvrPXUUeGqACDtpPGbvjJ/JgowVsrtQRM6tpMiLePTtskEpQs7YspyrInAFKA/0cMqv+p/oChLSbl+w3wK+D1g6iryeinlBQAp5QUhRF2uFwoh3ge8D2D1avUDQpmb17x4K//23X08e7xrsU9lxQv53ezOEwQoK8Mvzg1kfXykO/96x3z8Lp0vvnFP0dnSqVrqwhN/L6T77JqGCn786Xfye5/5Ed/86WHecvtOvvgH9wDwue/uo6N3hOqwj3ds2MZXTx/l6BMXJgJTyDQa+qffvpOvPHSArr5RpJQTF+C3NDbT4PXzjTMnSMvFbbZzz3t388quLXzqHx/n+/93hKtuW0OK3CXE64Nh7mxZNxGQzwdduHCkVdQ61PGmOedGT2JoLtJOisFkH7owsKY0XAqaIVr8LVkZUpeuuoGXXyajrYvM19aRNulLbjhoGOiaa2KbhaQLHQ0NZ6zR1WCqXwWnirLEzPm3jBDiLqBHSrm/lNdLKT8npdwrpdxbWzv7fCpFmUnI7+a333TdYp/GitZUG8LrNvj4e29d7FNRFtEXftnGucHJbMlVzWFSdvGZ09ftbJxTYArgcU3eh22sKawTZ2N1kE/+1iuoCfv4zmNH+dQ3ngTgfa/eO3HTpc7r4yqq+er/ZI+weuJgO88ev8Bf/ert/MqdV2ZlhvoSCb525viiB6YAUdvC9oX46J/dxYd/5xZ++N+HCSczX6sq04sW8ePRM5nUdcHwvAamkMmeunQ/puYjsw41v8waRS+mlmkIFTBDBIwAQTNEhbsaIQRu3YPfCFLhqqLB26hKdxeAS/NlBZ2ZNcUSDQOXFsCthXDp/kUJTCHzHjO1KWuWCyojVxRlIZUjc3oDcLcQ4pWABwgJIb4KdAshGseypo1Az4x7UZQyuXJTI6ahkZ7D+AqleDvX1XPwTDe/e+8N7Fxfz4u2lz7mQ1n+HjyW/SN/MFbc2JBxz3UOYzkOxhwCo9fesg3T1Hn7HXuKappWE/bxq/dczT/d/xTpdO7GOi/evob33b2Xzz2Q3S/hiUPnc66xrvf6eHnzGn7Yca6oz2G+HO9KcOJigrffUsltd2zixIEemne08KWnB1ld7eKaPRqtgRC7qmoW7Jx0YaJpOmknPkMW1UETJtpY594aT/3EM1P/Pi7tJLDl/M0KXckMMZkpnXojJtPTRODS/Aj0JbG0I5IeIelMZnKr3SopoihLzZxvg0opPyqlbJZStgJvBn4ipbwPeAB4x9hm7wC+O9djKUoh1jVV8bnff/Vin8aKommC63ZkgtEvfO9ZrlczTFe8G1qrMPXJi9EqX2mZkr0tFXM+l/VNVXzwjddRFfIWdYFs2Q6f/95+Pvu7r+J333pjzm2EEPz9b97BrVetzXr8K/93gM9862nsSzpeO1JycKCv+E9inuxo8WA5ki/+ZID/ejbBExE/9z89iAQuDqcJCR/XVDfgnod1pjMRQsOl+3FpAbQcWTZbprGKCDZ1YWIIL4L56QK7kmkiE3he+r0lhMDQXGjCKOj7TkpJwrboikU4PTI0L+faFZvsS1HjrqfBW3wXakVR5td8/rb5a+AbQoh3A+eBN8zjsRQly5tv20kyZfGbn3qQVJ6Mh1I+9VUBXnHdRs5dHOR33lLaTETl8vKhF6+n2ufibx89BUDb4PSGKLPZVOPnwzdvKPepTfPIvtN84fvPUhv2YzsOXX2jtPcM89tvup63vXw39+SYczqVoWt8+C038JP9Zyceqwx6+NPP/4RVNSHuuXny9Y6U1Hl9dMQiuXa14EYTk8HzpQFE0pJ84ccDDOxwsfuOwjNMUkoeOdVHNGXzVNsgpi64ZX01t6yvQSsye6YJHZfwIaXEkemx9Yty/EBF7UcTOjgSq4jxMsrs0k4UXWTm2I6PgMlkTWXOmbSXsqVkJJXk62dP0B7NrEsPGCa/ue0K/GZ5yn8dadMRbWM0PdktfHVg7ZLI5iqKkq2swamU8lEyXXmRUvYDLy3n/hWlGO945RXc/9PDPLLvzGKfymXvQt8oJ9r7eeOtO3jxntbFPh1lifC7JrNUdQE3vdHC5psamuCtVzTzyq05++iVbCiexmfquIzsC+aAz008kebzj+/HcTIBT8jv5g23bsc0Csu0XbdzNTVhH33DMYSAra21fPuv7iVlZQdChqbx2jUbMDWNp3svlucTK4IAqtwe4rZFzLJorJ99yuiDx3qoD7i5oinM9a1VeQNMKSUXRpL80y/O8sCR7M/tWwcvsKHaz13b6llf7eeW9dVFBapCCHThwrbTONiAxNCKHwGiCb2waTVKwSQSSybQMRF4ATlRkq0JEw09K3Cd9nop+dqZ41k3bCJWmm+fP8V962e+MZT3nKY0IYtaEc6OniRpF3+DTFGUhVe2OafloOacKuX29JEObvmNLy72aawIb75tJ5/5nbvweVQHTCXjf57r5OnzgwzEU9y5pZ6TfVG+c+gC8VnWg//dXdt45Zbp6wYvJaWDLW1saY/NvXQxlOpnMDmAxMHUXFS6qjndl+RzT13k8bP9CATfeefVHO4e5VXbsrtJd/WN8v1fHOd7Pz/G4wfa6Hrg94p6P//Vlx/j4196FF0THP/ab9FUG8q7bdyy+IdD+4nZhXemnY1H1/HoBkOpTLmrzzDYXlFNky+AoWkEDRcPdpylOxEDwKvp1Pv8HDhh8dPjQwUd48bWKn73lg20VHhwGzpSSvpjaU72Rfj7n53maE9hGeGb11XzN3duI+gu/h65lBKJkzfYycV2bCLWCMOpQQKmH5+hZlsunMyYIENz592iKxbhX4+9MG3c1Id2XEm121v0Ec+MnMBvBnCkM1bKm71fQ5jsqtqrMqfLnJpzenlSwaly2Xv3X36H/374hcU+jRXhR598OzepzKkyg0/87BRfeiaz7uvWDTW8/apmNCGwHYmuCQJug821gazXSCmJWREGU/3ErRgpJ0XaSWHL7MBOExpOji649z/j4nuHJ8fYhNwG//nmK9h0yXGmOts1yNpVlUV9blJKvvPYMT7/vX28666reN0t22bcvjcRI2pZ2I7DY92dnBpbZ/eWdZvxGSaDyQQPdbYRtSabSa0LhnnD2k1cjEXpiEV49EI7r2heS4s/wCpfAAEMppJIJBUuD/rYxffFeJQftJ/lzOjwtPPQbIPv/yJedDflWr8Ly5EMxktrdrWm0svrdjZyVXMFe1aFZ39BEYZSAwwlB4hZEZJOYtr7os5TT6134Zo8rUSaMDGEB8H09ahTDaeS/N3BfTkT2veu28L2yuqijjuaGubEyOEZt1nlW02jT603Xe5UcHp5WtgOB4qyCP7yV2/jycPtnO0aXOxTueydaO9Xwakyo9+8cR0uXSPoNnjn3pYZL1qldIjbcTqi57LWiuWTKzAFcF3ymy7oNlhb5ZtxX8UGppApPb3n5q1Za0xnUuvxMb6Sc10wTGcsgt8wqXSPZfWCYbaEqzg9OoTfMPEaBvVeH7rQCIVdhF1uLsaiXFFdi2dKw6Iq9/Ss4HP9PTkDUwBHt7h9RwUPHRzCcgoPUAst086nbTDOPzx2hjfuXlXW4HQ4NcjpkWMzbtOT6KbGU6PGy8wTXbgygWkBX+Cwy83GUCUnRqb/ji521IuUkvbo2dm3U7XdirJkqeBUuezVVwV48BP38ZIPfImL/UujCcnlSo3vUWajC4eXbBsEJEMpPwEziOVYuHQ3+liZZiQ9Qke0jZgVKctF5Jqq7F91nSMJvn6gi/uunN/MyVf/7wChgJvWhgriKYvm2lDeUl8hBM3+6TNY/abJrqrczYjqvT7uXb+loHMxZmlMY1ZFec11Qb75i5GC9reUBc0QAg3JzD+Pjgwdxqv7qHJXE3IFi27WpEwn0DA1X1El1wAt/sC04FTA5I2aS8StKJH0KAk7TsKOk3ZSeHQvQmjE7disxwuZ5c3UK4pSPio4VVaE1sZKvvDR13Dnh7+62Kdy2XrldRt5791XLfZpKEvcxXgXKSezJvLM6PGs57y6D7fuYSg1UNZjHuyanuFrCOZf/1Yud1y3kaNne/ju48d48lA7LXVhbrt6PW+4dXvB++iOR/l5dxcp22Z7ZTU7K2tKWid3soDRHNJenODs5nXFlW3OJmUnM6XiBdzXiNsxhlMGnbF2tlZsUwHqHJmat+jAFMhqhuTWdNYGw2yvqKLJN730PpMZPz7t5kMhQWnACFLnXUXAzL8eXFGUxaWCU2XFuG5HC3ddv4mjbX2c7x5SWb4y0DTBb7z2Gu6+cQsv2tGCrs95dLJyGYtbMbrjnfmft2PE7Rg+3U/MjpblmI7t45ET2RmZd+5t4Zb15Q2IcqkJ+7hpT+ucSt1rPT7WBcP4DZMNoYqswPRYT4TvHL7A79+yYcaAdSCZoHOW0TWGZfKtp2YvnS43n6lz3ZriS6hncj56FvuScTEuzY0mtMxIGQQSEAhsaRGxMtnik0Mn2FSxWZX6zkHKiWEID7owi7qJUufxkbRtVgeC3FTfhM+Y3ogs7aS5GOugN3FxoqLCq/swNTce3UPUGiVqTb7Paz0N+Aw/Ag1NaHgNHx69+OZKiqIsLBWcKiuG121y/1+8GYAT5/v40oPP8eUfPs/AiGovX4q1qyr561+7nbtvLKysUFnZEnacc5GTBZXplpJ5ybkfXLz/a0NcuozyLXuaMLTlcSNFE4IrqqeP1EnZDh998AgNQTdJy8FjTv+aDaeS/Ly7k2d6u2c9jhV3ISnPDYFi3LaxFneB43pmIqVkINmHxCGaHp32vKm5iFrTH5/KwiJmxfCbM69HVmYisWQ8M/qHwjtd39HcOuPzMSs6sY7YrXsJuyoxhIkt0/QkLhI0gwTMEFErgkCjNbieKnfhs3kVRVk6VHCqrEibVtfwV796O2++bSd/89XH+fbPji72KS0bblPn63/+Rl5+7cbFPhVlGUjaCbrjXfQlugteP+pckvUqnSSenn7MN3xlH/dd2cxv3LC2TMdZeA8d7yFhOXzmtbumlaIOJBM8drGDZ/t7po3myEf44zQE3VwcTc7H6ebVF02StOw5B6hCCEbTw/Qne3I+H7eiCMSs70G9TDdGVjrbSaHrcx8rZjs2w6kBOmNtSCRrg5sImmFOjRxlODWIV/eDlBiaixpXZjRUpasavzl9/baiKMvD8rh1rCjzZPeGBr76J6/n3tt3LfapLAtet8Hf/PrLVGCqFKQnfoFDg89mleEVImbH0Mrw68khzT+9vhq/K3tfI0mLzz3dxteez19ivJQ5UnJydJD33FKbFZjGLYsH28/yrXMneKavu+DAFEBqDjfudFPlW9g5xeuq/WXJnF6ItTOY6s/7vIOD38g/Omhce7R9zueigIM1bdRTKS7E2zkbOTk2PirNieHDxK0YCStOhauKrRW72FF1JTWeOgzNoNnfqgJTRVnmVOZUWfE0TfCht1zPkMeL7nYhDB2pG5BI8MiDvyQWn9u4hMvFy65Zz6d/+07WNFQs9qkoy8BQcqCgkQ65SXxGcGIt4FyEAxH+9tWV/Mb92YGL5Uh6IgubJSyXtsgI0hfD0jQOD/azIVTB/r5ufnKhnbht4dY0NAROkZ2OLXeCF18tkJFKnjgWnfOomEL0l+EYI6khumKzB5UxK0rACBLJU97r1X1Uu9Xs03KxnDiaFiipgde4Bm8zcSvGSHoIyJRne3Qv2yr3YEsLIQSmcJXpjBVFWQpUcKoowPa1dfhX1bK/Yxiwx/4IWl92HesCJtGLvTzz1DEi0eV5MTtX77t7L//wm3eohkdKwfqTvUW/xqv70IWOLR1iVvnWPwb9ET77pmp+/euTAeo9Oxp419Wry3aMhXRieJC4bXF0eIAXBvsQMBGGasCagJvNYRc9cZsTIwkGU0VksDQQoSg37/bwrSdS8z4N8seneknZDq45/GxJOYUFuA4OlrTQMbCZ/jVJO2nCbpV1KxeJQ9qJYWq+kgNUQzPYGN7GwYH9pJwk1e46hBAIBJoKShXlsqSCU0UZ8ytXr2Z/x8GJjz9ww1r6oilO9UU54gnR/NJrWR9yke4fYv/Tx+kfmH73/a7X3kDCk+kGKISg89ljHDm6vMvEbrmiVQWmSlHSTorhIsbBuDQ3hmYSs+ZvDnHAGyXo1gCNX7++lfuubF7QsSGj6WHiVgyJxBQmQVcFppZdQiulJGZFSDlJhNAIGEGMS7ZJOw7PD/RS7fZMdOCVwEsaQ9S4HaRM4JAAEjT5ockPEOKZ3iTtscJvrlnuBFsb/By5OL9NktK25EcnerlpbRVhT+ElxTErQl+iG0fKiazabDy6l4SdvwGeJdM4UqpxMmXkYOHINPocAsmUnZwYP1XtUU2OFOVyp4JTRRlzy7pqrm6u4JmOISAzB/FXr2sF4Mv72/mbn57i6GASNC+V1++hydSRwNRlXSfSDlZy8gLQvWkdr9zYzIMPPLlwn0iZvefuvSowVYoykhoqao2pqZlZIyDmh+QlG/3Ekm7eflXLPB8rmy1tTg0fxblkLqPfCBB2VVHpqsaSFt3xzqwZr34jODH7NTMSQ3BqtJeRdAqvYWR9heOWg+3KF0iOcnUtXEOQH3VGGS1gjJaUknQhg0LL4Pd/cISb11Xz2dfOvva/L9HNhVgHlrSKbpylidl/jh0fOkZrcB1eY/7n4CqFMTUXzf5WgmZIjYJRlBVAXXEqyhghBL97y4aJjw9enMyMXrc6ew6fIyGSsommbGLpyT/WJTMrkpbDMdvgVW+9bX5Pfh7VV/kX+xSUZcZd4AWkV/fhMwJlLeGdyVWrXbRULPzFrYaWs6wxakXoip3n8NBzHB8+mBWYZp4fpS/ZTWesjZMjRzgxchjoxxQCr559b/mp3ggj6ZlLUiUR7mg22BaefVSKEIIdaxaubLK1cvZzStlJ2iKnSTnJogNTXRiknfSs2zk4nBk9RVukHctRs7DnyhAeNDG3JltCCOq9q/AV0NBKUZTlT2VOFWWK7Q1B7tpaz/ePdvPChWEsx8HQNDbWBrihtYpfnCu8VHGqw0NJbnnJLh796QtlPuPZ/e69N/Abr7uWioCHiwMRhiIJmmpDeF0G//3wC/zuPz9EMm2zdU0tHpfBcycvZL3+yYPt3LhrzYKft7J8eY3ZAw2f7idmL+xcze2Ngtdv2zD7hmUWsUaxyzQex5E2V9X4OT06GWgJoNnnptIVZ7Zkpy3TbKlIszoQ5qHO4bz57fXBMFGPxa2bqrhrcyMPn+jFbWh85/DFsnweU92zo4EP37J+1u1K7f6qoWEIg6STKPg1kfQIx4dHqPXUEUlH8Oge6r316MtkPu5S4UgLXZhk3qWKoiizU8Gpolzit1+8jn0dQxzpjvDxh0/wZy/bjCYEf/jSjbzuy/uIp0u8yGyoIxz2MTwcA+Blr7gaUVWBC8mhXxzk7Lnuonb3kivX8rJrN7C9tZYL/REefe4sjdVBTpzv4/tPnJjYznYk9VWZO85rGiqYGma+9+69bG2tZTiS4BUv2oSUkvs+/i2+89jk3Ndv/vQwv/vWG0v7nJUV6WJs+ogWl+bCpXkASdJOLnhgChCzR0nZSVz6wpZsZkoRp7YtKpxb9+JIm/SUpj+r/YKnejNrJ7264FUtbiyZnDUwncpnjPD6Vj+PdCUZuKRh0lXVdby2dWxc1PbMf16+uQ6AWNrmRyeKb3Y1k60NOv2JbsKuKly6C0c6Y8G8zKwRlTCUGphxVMxMfIY/b4femfj1AL2JzNzUuB1jMDVAg3cV1Z7KWV6pjHOwSDtxXLqqwFEUpTBCFjEHbb7t3btX7tu3b7FPQ1FI2Q6ffvwMX9rXzt3bGvjLV2xBCMEnHj3Fl/aV3uCowmPQrFmM9I/Q5Q9PlAF7DY3YgWMFBaguU+dfPvwq7n1Z7vVZUkr+5+GDvHD6IjvX1RP0u7n7xi0Fn2MiZfHy3/5PfnlkMsB45NPv5Pqdy7OzqbJwHOlwIdbOxfjke8etezAwiNrzvaa0MOuCm6hchHEhx4ZeKHldbY2nnr7E5M+GOk8TA8l+HGmgiTSWLL2LuC4M4rYX2wFLgiMFOyvrCbmCuHXPtO3PDcS4+0u/LGqG6mwMTfD/3RVkVVUSU3NNBOICDcncSmvduoekXXjGdKqZGig1+VqocIfmcmpZpISh1DA+w4cjHbrjF2kNXh4VK7pwY2rT30uKMldCiP1Syr2LfR5KeanMqaLk4NI1fufmTJnZl/a101rl5X3XruHd16zmZ2f6OTMQK2m/QwmLIQBvKLNwdUzcclh//c5Zg9OXX7uBP3zHzVy9tSnvNkII7n3ZLu5l9uYiuXhcBn/6rpdw54e/OvHY7/zT//Hzf3mPaoyk5JW0E5waOZp1Me/W3CTtBEtpANOl3W8XiphDiwcpJYYwsKSFQGAIDUtmAi5njjGiLS1c2mhWB4rz0RFccRetwY24NHdWkNpa5ePtVzXP6SbdpSxH8i+Pp3jvDR5W10wGknMNTE3Nhe2UXk5tCAOX5so5qqYz1k7crqHCVTHn5knDyRE6LpnTqqEhJVwOjYM1oS41FUUpnLrSVJQ8hBA0hjIXZZ/++Vme7Rym0ufiS2+6gi115W/McGY4ycvvvDrnc6tqgvziX9/Dd/763hkD03LpHsjO8Dx/8iLDK3TGq5KfIx2GUwP0xC9wbOhgjizT0ruy9uqzr4ddavqTPTT6WhBoVLiqQAiMOTaZmU3KSXFi+DBnR09Me+4DN65lfXV5v45tgwn+6PvDfHv/3BpWGcIYW2NqgsyMhylVxBol5aTwGwFMbXpzqIFkH2dGT3Fy+BSxdBz7kjsF48llgYZAH/uTfdnVEemcFphCpjHT2dGzdMd7MYUPDb3kz2PxiExDpGV57oqiLBYVnCpKDlJK/u7RU/z9Y6cnHvvXp86RtGxq/C6++ba9fOENu8t+3DPCw823ZGc8NU3w/b+7jys3ryr78fJxcqRjHnr61IIdX1n6bMfi+PAhTo0coz16NmcQkOuCfrGVqzHRQhtKDbAxvI1mfyuNvmbWhzYvyHGjVoSe+AUcOZnFdBs6X3rjFfzp7ZvYs6p8pa0A3aOl//sEjGBmxAwOlkyTltMznqWIWhHSTgqfEcg5yiTlJDkbOcOx4SMcHjzM4cHDnB/t4MjQYRgrTZbYY38yX8fBxDBHB48xPMOM1rgdQ6ChCQND884p+74YTM2HoblzdqpWFEXJZ3n9pFOUBSKE4G1XNWddeD1xbpB/fPwsUkqEEFy7upLdjeW9MLMliMa6rMc2tVSztXVhB4+/4dYdbF6dvS7vSz94dtp2JTeHUpa9rlg7sUvWUIqx/wEEzTABM0TAKO/3yFwIBC5tec6vHE0PoyEmmjkFzBCrfAuzDrw9epYLsQ6m9qio9rt44+4mvvzmK3n/i6avjdQE7GgIctvGWtxG4Zcaz3ZEeeRI8VnZgBEsqelRMWJWhIQdxxQuPFpmDJI7z1rK8c7C+W6G+EwfDvl/fla4qmj2txIywwgh0ISOLpbPe1cXJroq51UUpQTqJ4ei5NEQ9PDFN17BE+cG+N6Rbh44cpH/3N9O0nb449s2IYTg82/Yw988epLvHLo4bcZpqc6PJNm9ey0HDpwty/5K4TJ1/v4DL+eu3/2viceeOjxZevbRB48ynEhzz44GzgzEeN+1a9Td8RVkNDVMTyJ75NC64CYqXNXY0saWFm7dQzQ9ysV4B27di5QOKWdxS8MlEomDWKZlhhfjnaw3J5ubNXibGEkPEUmPLMCxO0jYMdaHspur6ZrgN29cx01rq3n4RC9PtA2wsyHEe1+0htVjM2X/+Rdn+ZcnzxV0nBq/ibeEimUHiYY+Y8BXLmmZymRlncza0IARQiKxpUXSToy9yzIZ0mNDR6h212JoBlErimusmiCeZ7avW/ewJrCBoDn9ps7y+QmbKedVFEUphQpOFWUW17dWcX1rFXdsruVPfnSc+w908RvXt1Llc+Fz6XzsZVs42h3hcHf57tq7Nq7lVetXse+JI3T2jhBLpPF5FraRy0v3ruc1L946MVYm6Ju8a///3bEFXctcKn32ibMqMF1BOqLn6I53ZT0WMEJUuKoRQmAIA+OSXy3JsbWoASNExJr/QCqfWk8DmliegSlkSnvjVhSvkRnLIYSgxd/K0aGFmZ8cSWd+xmW66QrMKc2lrmgKc0VTOGv79ugotpTcsblu1uA06Nb5yMsCNFfFEaL4hnMxK4LfCBKd5+zppRycae9pHZ2knSBgBAEYTg1iFTijNWCEcgamUMogosVhCA9CqMI8RVFKo4JTRSnQzetr+JWrY/zdo6f5zqGLvOuayZK6oLu830r98TT9aHiv2sHmkJueSJLWBQ5OAf7pQ3cyEk3wk/1n2b52stx4PDAFeO+1l8e4A2V2cSs2LTDVhYEhTJ4f+OVEWa8Qmf/KSy6nI9ZIpvOrhKRT2niPuRhODWI5Foa2fH/1tUVOszm8c+KGkM8I0Ohr4UKOpjrlJnGwHYszoycwhcm6Wda9hk0XHt3AFdD5vVs2cG4wxvnBOIe7RxlNZgdr164J0FKdYC75QSnn1t23XOyx7K0lbRJ2JtB2a56C3vNVecYcSelgz2Fk0EIR6Ojz3KxLUZTL2/L9Da0oi6A+kMkefvbJc7xyax0NwUzp0uffsJufnu7nYw8fpy9aniYc45qrfLTWlL87cCFqwj4+8f/u4E8+/xN+7Z7sTsJHu0fxmjqtVcuv+6lSmvEL7akq3dVYThpn6tq6GVI84zMnFyOLmnKS9CYu0OhrWdDjllPUijCQ7KXaM3mzqNHbzGCyL+9MznKxpc25yCniVgwjT3ZvqpBrstriHXsnv+aOlLQNxjnZF+F0f4zT/VFu3mBQ6Q7g0lzoQoex1cua0DE119gfk/bIWYbTgzmPF7OjC7L2tFCWk54YAaRrBgEtlAmgRSZwTV7y71Xpqibkqpi2n0xJfHTOo3Xmn8Cl+VQljaIoc6KCU0UpQlPYS33ATXckydee7+SDN2VmoQohuHVDDUG3znvuP1C29acAt2+sm32jebS1tZb7/783TXv8K892YDuSv7lz2yKclbLQpJQMJPuzHjOESZ2nsais3drAWrxGZi1i0k7SGeua96BqqsHkAPXeJqSU6NryLPFtj54lYIYm5o8KIQgYwQX5Og6lBggYIcJm5azbfubo81xRXcf1ddmdxjUhWFvlY20JN7bWhTZzcvhI3hsbC/lemomOkck0j920ubR5WK5O1oE8Ab8jrWUQmIKpeVU5r6Ioc6Z+iihKEXY1hvj+u67lTbtX8dDxXv71yXNZHSyvbqnk82/YTVUpHT3y2NEQLNu+yumDN61jf8fQYp+GsgCklJwZPc5QajI49RkBtlbswmv4oIhMiSWdTNmvEHgMD2uDrdR5GubjtHOK21EODDzDocH9DCR6F+y45WRLm9Mjx7Ky1av8q6lyL0xX74g1wog1POM2luMwkkrxo842zo7OvG0xNKHR6Gue+DhghPDq3rE/viUzvsjGwpNnpq5Lc2et18104jWozvPvd2l5/FIj0HBpflXOqyhKWajMqaIUyefS+ZPbN/PtQxf404eOI4Ffu6514vmrWyr5+tv28u5vPM/5obnfxQ97lua3aV3AzUdu3bjYp6EsgM5YG0OpgYmPw2Yl60Kb0cayJKKIdYJpJ3seqiY0ar3VBM0AnbHOBcl8OdLGAc5GTmLq7rwNaJayhB3HlvZEgydTc7E2uJEKVxVnRo/P+/FHUoM40pl4D1zqkQvniViZf+svnDjEumCYJl+ArRVVrA7M7esdNMNsDG1jKDlAb/LinPY1r+T0oFITOtYl3wO7q64m7aTQ86yFzoxlceFgkXaKbxY1n3ThGmuApEp5FUUpD5U5VZQS3bOjkfdeu5ov728naWWPL1gV8vCvr9tVlsDS71qawSnAbRsXdv6qsvDSToqeePbYmBpPHZrQ6E/0cHrkGCOpoYL3d+mF+TiP4V7wLGrYVQkyTcqOYjnJ7HWzS5xE5pwjWemuznxe88yWNsOp3Gs/U47NCwN9Ex9L4PToMI91d/Jvxw9yfDj36wolhCDkqqAlsJbV/nVF3RxZSJkGSNnn5kgHr+GfKPcVaGhCmyjRzkUILTPrFANR5GVbLD0/N3vGs6WZUt6l+fVXFGV5WrpXvYqyDNx3ZTN3bq3HbUxfu7am0sen7t7Bu77xfMlFWR5DK3snYEUpxvjcxqn8Y5nGztj5sbEihUvL3MEpLFwW1av7aPA24DMza18dLBxpgQRT84GUCKEv+bEzx4cPsT64GZfuznp8la8lb+BYTmdGT+CJefDqPryGD6/uw2P4iKTTDKXyd5a9/+wJ3r5hG6sDc1uyIISg1tuAzwhwfPjQkluXaUkLn+EnNjbTNGRWEHJVMJjsx5bWxNetUEIIXFqApDNKrq5jluPgSGesgVKa3kQPcTuGhkbYVUGDrxFtDnGkhpEJlMc68qqgVFGU+aCuepepvuEYx9p6uXGXGuOxmCp9Lip9+dc4XbO6kldta+CBI6WVnumawJYSfYlmBpTLm5SSi/HOrMeCZnhivZwuDNIUGZzmyZxONZ5F7U8M0pMoX9mmIUwafA2EzGDeC+vxskkDz5IPTmNWhKNDB9gQ2orfnAz03Fr+LFx5SRJ2nIQdZzCV3SzrloYQj17M3bQoblt8r/00v7F1T1nOwsFGExr2EhklM5XG5HsoaIao966i0lXD4aHn0IWBzyiuE3smAM8OTC3Hpit2gdF07rW9Dg6DqQHqfQ0UO6pHQ8fQvEgctaZUUZQFocp6l6mqoJd1q6oAGByNc7K9f5ZXKIvldTsbSw4toymb/zvWU9bzkVLi5FgLpSiX6oy1ZWXgBBrrgpsmPnZr7lwvm1HaLiyYHc+irg9uwKN7iz7OVAJBraeeDeH1hF2hgjI+Sy0Ll48lLdoiZ7IeWwoZrfAsfYnuaGot27HcmmdJza41NRchs4Iqdw0N3ia2Vexhe+UV1HkbAXDpLipd1QghqPeummVv2TSh49L8aBgTfxwpGU0PEzBmzkSfHjlJ3Eoi5Vg58Qz5CV24xsp2/WMNm1RgqijKwpjzT3MhRAvwZaABcIDPSSn/UQhRBXwdaAXOAW+UUs5/ndEKoWmCVTWZX0SaEDxztJOg381wJMHm1bmHeCuLY29LBVc0hXm2s7SOlZ994ix3by9+HZ6UkkMXR3noeA/PdQ1zbjCOW9eIpizu3t7AH7500+w7UVY0t+YhbFZluuuSCfI6om0TN1sSTvFlt2mZRkpZcAA1nkUdSAzSXUIW1aN7afY14TaKC6QdaSGlsyxGY8TtKEk7MbFuURM6PiMwbXzJQjo7mn/97sua1rA+VFG2Y7l0N5vDOzg5fIT42CxegaDSXUPMiizoeJl67yqa/a2zbucz/NQY9SUdQxMGLt0gZScZTPVhjq09jloRdKFPrGe9VNpJcz7SxurAOird1UDm90RaxnFkGl24MYQLEEviBoeiKCtTOW41WsDvSCmfFUIEgf1CiIeBdwKPSCn/WgjxEeAjwO+X4XjKJcIBD/e+bBcAblPn1z/xPT7x/+7A51F3OpeCgViKA125y9sK0T6coH0oTktFcdmjbx68wJ/9KHfXzjWVxc8XVFYel+5m1Boue6MgS1qYRWRiNKFR460mUORa1FpPPTWeqrwdZWcicbBkElPMLWu7EHRhYGjZX881gXUcHTpIrrWJ800TOocHozmf2xqu4uaG5pzPzYWpudgU3j62ntOm2lOLqbloj5xd4NmnhQV11e7aOf3LxK0YJ4YPYUlr4jGJxK170dAAScSKMPXfv8JVxZrA+qz3ihBiYhNDuJbFzRhFUS5vc/4pJKW8IKV8duzvo8BRoAl4NfCfY5v9J/CauR5LmV1l0MtnP/wqXjh9keFIYrFPRwF+cLQbe45ltB958Mi0jsCzOdI9mvPxV2yp461XNM3pfJSVIeyqpNlX/nXtllNasOsx3DT7m2ftWGpqLloD66jz1pQUmI6zZQpnCa5jvJQtrWkda31GgLXBjbhKKL2e+/n4uPRfWBeC927awT2tG+btuIZmUuttoMHXNDHvdKYuuOUWMEKs8hUWeOuaUVIpspSS/kQvnbE2nBzhbcyKELFGiFij+A3/xONBM8y64KZpNzEAdDLjYIpdj6ooijIfynqLTAjRClwBPA3USykvQCaABeryvOZ9Qoh9Qoh9vb3LcyD6UvThf36I7W/9J46f75t9Y2VevWpbAw3BuV0gPt81wicfPzP7hlOc7c89D+9tVzYvaMmW5SRIOTHSToKBRC+nR47TET1HzIog1drXJW/8Ir+cLMeafaM83LqLTeFN1Hsbcwapla4q1gfX4TfnnvEcH/NRKkfaHOh/hgP9zxCxct8sKpekPf1mZJW7hi0VOxcsQDOEj8FkkEe6pmdNW/xBWoNh/MblV9HjNwKsD21hU3j7vDXRStkp+hM9nBk9zrnISYZTg3hnWIttCtdE6OrS3KwPbp6WFZXSIe3ESMsYlkyQdnJnuxVFURZS2ToICCECwLeAD0opRwq9+JVSfg74HMDevXvVlWqZ1Ff68XtMLHvp3/W/3FV4TT796p383g8Oc26w9PKybx+8wLuvWU2tf/ZA95n2QZ7pGMr5XH9s9m6p5aQLN44TwyZJ0okzNNbVszveRZ2nkRpPHd4pd/iVpUWfh4vttCw9OAUwNJ0aTxXDqSFsaePS3IRdIQKmf6KTcDmIOX7uErBmGJ1TTiPpoZxjSUzNxdrgJo4NvTAvxzWEl4GkwfMDMfqS+YObqLWwP3fGzfcM1Bb/Wmo9DfN+w+9ivIPeS9Zcx60YASOY88aHpmkTa46r3DXoObK0aSeOw+T3orFgXZ4VRVHyK0twKoQwyQSm/yWl/N+xh7uFEI1SygtCiEagvC1HlRl96oOvpLm2sK6Uyvzb3hDkO++8hm8dvMDf/PQUqRJuGkRSNr/5nUO8c28L17RUTBthMxRPs69jiJ+c6uOBw7kbx3gMjevWVJb0ORRLSofxxhqG5iFpjxK3soPznsQFBpK9VLpraPG3qvVOS5DHKP+ay7lkTqdaF1w71qxJR04rJJ27qWNASrGQP32HkgN5O7/6dD9uzUPSKW2ph0Dg0b24dU/mj5b5b0c0yX+dOTXja12axktXrWZtMFzSsefKU8Qc0WKt8q2e6MA7nyzHoj85/RLKIfMzNpeknSBgBInbMWJWNGcTsqnzizUMNLF0Oh4rirJylaNbrwC+AByVUv7DlKceAN4B/PXYf78712MphWupW5wLASU/U9d4854mGoJuPvPEWY50F99J84ULI3zoe4fRheBjL9tM3LJ5/Ew/ZwfjtA/lz8oKMl2D335VM16zPJmw5/t7+HHXeUIuN2sCQW6qb8I3pWQvc1fenrjgGS93MzUX1e46LJkmaIRwkGMliepGylJkCBOByLqQnau0U9xs1Hzm++bbXDOnC/mejlgjnB45zprAumnrCoUQNPnXcGY0d4O0mdR5GrPWcE61xZRUuzvoT+YPem+sb+LG+sVb455Zdykod2Ooeu8qGrwL83mdHjmad+2zfUkVgk/3I4RG3IoSsUbx6n5G0kP0Ji5OC6RNzYstUwg0dFHe8v20k+bY0Au4dQ8hs4IKd9WcR0IpirIylOM22Q3A24CDQojnxx77AzJB6TeEEO8GzgNvKMOxFGXZu2V9Dbesr6FrOMGJvgh/9ZOTdAwXl9GwpeSPHjqW9/mXbA3RWJX59pYSnjuV4txAjJvXlW/M0K6qWiwpOTk8SNBwMZhKZgWnppbJWEwNIIJmBRXuaqrcatzRclLOwBQyF67LgTbHtgzzXVJ6qaFUP+FUJTWe6S0eKlxV1Ljr6MuRgcunwdtEkz9/QyxNCG6sb+K7509Pe+662kbqvD52VFYXfLz5kBmr4yNmlW89ZYt/7YJkTMfVeVcRyXNjQQiNgBEkYccxNTcxOwZIvLqfhB0jbkcJGEE6om2EzHBWJlkTOto8daMeTPaRcpKknCSj6WFqPaWNzVEUZeWZc3Aqpfw5+W8Pv3Su+1eUy9WqsIdVYQ9Xt1Twr0+28dVnO0oq971UU4WLdS06/enJzGz7kE19wI2ule9iWROCvTX17K3JfdGRK6tV61UXKMtNykmWfZ/LJThdTtn8anctYVfVxPzKSwkhWBPcgCVthlL9rA1uwnLSGFomM5604yTsBLa0JuZlNvpaZj3uFdW1/LjrfNaa0oBhctfqdWX73ObKbwTLEpx6dC+tgY34zUAZzqpwFa4qqty1DCSnN42cOsvWsiezqJmgNETEGiFqRTA0k7ORk2wJ71yQ5ROXfr0HU/3UqABVUZQCqAUGirLI/C6D37l5Pe+6uoVvHbzA9450c2YgilNisqprKEUqHpj47pZSkrIdKryXX5dMZf71JbrLvs+0k8q5Bq50S7OX3kKt+a9y19Ia3FjQtqt8LQynBgmaobydmFN2EkMzCupUbGo6N9U3cXSonxvqm6hwual0L/z4mpn4jPIEk5vC2+ele/VshBCsCawnMbZ+tFDjFQ8SiS50YlaUrlj7jNnwcrm03Lhc68wVRbn8qeBUUZaISp+L91y7hvdcu4ZI0uLrBzr54jPtDMWnZ5lq/S5StsNwYvovfAl85fEB3v3SKvqdCJrUMDSN+64s/+B75fJnCIPWwAYMzSRkholaETqjbXMajSKRJO0UHmPuQcx8NUMyNV9Zgstyr9fNxVdEt2uv4Zs1yHLpxf273NTQxE0NS3d2sn+OwalH91LvXYUhFu8GnyY01gTWc7SIrsuWk554/yXsOH49wMV4J0k7yerAupLmrBYiYcWwpgSnmtCpcFfNy7EURbn8qOBUUZaggNvg3des4W1XtnDgwjA/PtnHY2f62VIX4FeubmFXY5i07fDU+UH+4WenOdGXuZt+244QtQ0WEhieMrPuV26so6Ve5+neC1iOpMLlJmqlOTo0MPH3TeFKrqyuQ1MdnpUp6n3ZQUfADLG5YieDyf6SGuyMK1/AVt7AT6Bhar45z6u0nPRY5rH8zXguFTSLa4AXMIPzdCZLk0f34tF9JOzcs5/zqfM0UumuwW8ElkTn+3xNkfJJOgl8RmCi9DdqR/AbQQZTfSSG42yp2DmnOb759CV7iKRHgMzNrW2VexYl46woyvIkpFw65VB79+6V+/btW+zTUJRlJWnZ/NZ3D/H42QHecXuQYWv6GsFqtwdHSgZTM68fXBsI8cqWtazyLeyaKmV5uhBrpyvWjiEMajx1DKeG0IQ2MXc0czkvJkKzyct7gddwl3DBr13SZEgiKe8sZ1Pzoc8xQ5Z2UhwafA5Hlj+jeylTc7Gz8qolETwtZdH0KMeGDxa8vSZ0dlftnfNNinJxpM2ZkRMMpweLfq1b94x1RIfxNl0SSb13Fc3+1nKeJgAXY510xtoACJkVbAxvK/sxFAVACLFfSrl3sc9DKS+VOVWUZc5t6Hz61Tv57e8dJC2nB58agsFkYsZL+HqPj7ht4TcMUnYSUMGpMrsGbzMpO4UQUO2ppNpTvhm6mXJdBzGlY67EnvfVpVoZfi12RdsXJDAFCBjBicDUlhZiSgCvAtZJfjNInaeRnsSFgrY3hLFkAlOAlJMqKTCFSzOuEjn2/uhP9NLkW1P290mVu4bueCeOdIrO9iqKoqjgVFEuAy5D45Ov2sGDnWd5pi+7gU1rMMRwKpl3FmG9x8e7NrWiC4EQAo2lc0GmLG1CCFr8a0nJ0tefTtsnGhJnYh2pxJ63daXTjz33976UksFUfxnOpnCWk0QIHctJTPk6ibH5lQa6KCVLfflp8DUVHJymnCSOtJdMgOrRvTR4m7kY75hlOx+G0GHiBgWMpkfw6D40oaGhEbEyJbeWTJN0EmWfP+rS3Wyu2Elb5DSR9ChDqQE0NEzNhXfKKBtFUZRcVHCqKJcJl6HzmjUbuKK6jvboKP3JBP2JOKdHh9GFoDUQAuBcZASXprEhFGZdMMC2igCGNpmdKvcwduXyMJwaREPDbwawpYOpZUpfhRAgy7OuMl8QWkjp7niGdS5lvhIbW6YwROmNmuZj9M5MAmYASyZyfPklEhtL2lgyhVsLLMgIkaXM1Fy4dS9JO17Q9gk7UVSzqfm2ytdC1BplND2c83m/ESSao1GZR/diOxYJmZrIrI+v+Y6kR8oenELma512UhhCpyt6nvjYet+QWUGzv1UFqYqi5KWCU0W5zKwJhFgzFogOpZK0RUZ4YaCXUyNDtPiDVLrcVLjcvK41d3dNsUQyBcriS1gxjg8fQgiNsFmJqZl0J7qo96zCdGWa8AghMIQ7EyCVZLIMNX92VE5kVPOZ+tzUbXO/bvoxx7OmjrSwpY4uSvv1aEtr2hiN+eQr6CJfknQiKkAl09m40OB0qY0/EUJQ4apiND1MhasKnxHgQqwDiYMujJyBKUBiyucrcXBrHpJO5vu1HPNfcxlNDRE0wjT4mnBpbrpi53GkQ0/iAnE7poJTRVHyUsGpolzGKlxuKqpq2V1VC4DjOPQkh9GFWgekzM6te9lZlek1MVNXT0NzY9vpkkpvM1mc2V83vv700kAzV7Z16jaZv4uxzKocyxg50xKNmX1kMkrC0dD10n499sbLPxc2H7fmzqp6mJkk7cQwNf+KLvH1634G6StoW11bejfq9LGbh1XuWoJmmK7YeWD6XNGZ2FljXubnZkXADNEWOYOu6TT7W2nyr0FKiaGZ9MYvUuWumZfjKoqy/KngVFFWEE3TqPeESTmxBVnDN5VlO/zLt3/Jq2/ayur64kZfKItDCJFZxyhtnEsykyDRhD4WHEqmj4bRYNYS28IC03GTQWfm+JN/Zn9lYceRgMDBQkqnpCxjk381o+nhicxUOWhCH2ssM/m5auisDa4raj8O9tga3pX7q7/KU0tXvH3WRj0+I4BPXzolveNCrgoEAkMz0YXOnqprcHDojncxnBrMypLmYgoXaZma+Hi+Zrcamsm60Kasx4QQNPqaqfM0cCHWzkhqmNWBtXiXUOm0oiiLb2XX9yjKCiSEhkvzZ3VBnXgObV4agPQMRrnvY9/kT/79Jzx1uL3s+1fmj4aOg012MJgZ4WLLNJZMYMsk44GdQB97bzllaTCUW+YcxgPj8u9b4JRYmmtoZllLFqvctWyr2E2lqzrr8U3hTegFZ00zdOFCK7Fc+XJhai7qvbmXNExV4apckhlmU3MRdlVNzF7VNQNTc9Hsb6XaXZf3dS7Ng98IZAWmAIY2f++HoBkmaIZJ2HGmji3UNYNaTwNJJ0F3vGvejq8oyvK0sn9LKcoKJYTApflJOdHstXplDEzPdw+TSKbZf/wCH/7n/2NTSzUXvvd7eFzqx85yogkTE7CmjCnKvfZTjv2/PeWRTKlsruxmKR14J8t6px+rnDLdgksPeht9LQylBspyLmkniVv3ZDVaqnJXFx2YAnOe33q5aPA2MZTsn2jSk0v2PN2lI25FMTUzZzluraeBi/HOaSW+hjBJO0lSl2Tzw2bltJsec2U79rRy6Eh6hJOxwwTMEGuDm5BS0p/sxaW5iaTL1+lbUZTLg7pKVJQVSgiNZzvS/MNjJ3nVtlpaKz1sqvNT43OKWMc23U/2n+GP//0nnLswyMBIpsRsQ3MVn/v9V5c9MD1ytof2nmFefu3Gsu5XmSSEyGTcpEnaSeCQmv1FBckdsObazhBunLFOutNfM3OjpOLNrfOwLdPoQuI3/ETL0GzGZ2RmDrt1N1FrFA2NWk/+DNlM0k58rCTUN29rDZcDTWjUeVfRFjm12KdStI5oGw2+5pzPZdZ3rqEtcnriMb8RQKCRdlITpeYaGo2+Zuq9TWXNDkspOR89w9pg9s9jW9qknTQe3ZcpebeTaGh4dA9Noc1IKZdkllpRlMWhglNFWcGkhCPdMY50t0089vGXb+Z1O1eVtL/hSIK7f++/sJ3si/v/+dgb2NhS3jv0Ukre/7cP4HEZKjhdAEIITM1D0ikuOM0Ej9mzNyczqtnyZkKFhih39W6uw0zJ5toyhS5dRV00206KtMzckFkdWMOxoaMTGViX5sZn+GfNqE4Ntitd1TT51gDQ5GslYcVp8jeVfPNIjjWCUmFA5mvbzpmstdTj3JoHt+5ZhLOaWcyKkrDjBIxg3m1qPPX4DD/RdJSeRBdRK5L1fIWrihb/Wlx66eOS8hlJD5J2UtOCzZAZprLySs5HzzCY7CPkqqTZv4b+oR4MYarAVFGULCo4VZQVbE2ll92NIXwunSfbBgH48x+foM7v5qZ1xQeTzx7vmhaYVgQ8bF9bWqZnJsPRJL/xumvZub6+7PtWcssEqH7STozJ7KIge8Zovigyk5EcD/4yjXn0if8yEcZNDxZsmcIU3ok5pFOVc81p5ly0sfJXMdYhuLBSdymdicAUQBOCVb5mOmPtaEJna8UuDM2kI3ou7zq7DaGtuDUPZyMnkFKyOrBu4sLdpbuo867Cpc+9NDftxDE134oOCnRNJ+SqZCjVn/W4JnQ2V+zAECYp28alL52OvT3xLsIFrIX1GQF8RoCwq4IjQwcmynyr3DW0BjbOy797wo4zmBxgY2jrtP17DT/DqUGGU4N4dC+NY2t+N4V3lP08FEVZ/lRwqigrWFPYyxffuIeU7fD9o918/unzdEeSfOGX50naDrdtrJ3YNm07fONAFw+f7OXFa6vZvSrElU3hiQuRvuEY33r0yLRj3HPz9IuVcqgIeHjzbTvLvl9lZrowEFqAlBNhsjnS+KxQbVqwOFlyOz2InBqoZuTPCAoh0HFlBaflLOmdDJQ1dOEu6j0rpUPamd4lNT7WObXCVYmhZYLKJt8aPLoXn+HHkZK+xEUksMrXMpGt2xLelfP4fjMAZSirdrCwZBKD4j7Py02lu2pacOrVfRjCpCcR5/6zJ7hvw1YqXOXPMhZLSslQapCwq7LgMlhb2hOBabW7jjVTbnaUU9yK0R49y/rg5rwdrjWRmS3c5FuNPtaESRMa7ZGzeAwftR51k1FRlAwVnCrKCucxdTymzr1XNHPrhhpe+m9PIpH8xSMnONYT4Zb11exrH+LzvzxP2nZ465XNfO/oRf7+sdO846oWPnTzOi72R7jzd77Cifb+aft/+JnTfPtnR7nn5q2L8Nkp80ETGobwYsk4U4PO/I2SChkrMz7zNMcexsZ+ZEbXaBMZzfI2RBrP21qkZRwTz4yjZNJOfDLXK9M5tzGFgUCjyj15k0cIQc2UC/GAOb1EM18A4S6hrDofWyZxpIUuTHRRXPny5SJsVqILIyuAGw+STo0McSEe5WtnjvG+zbvQFvnrE7VGsaXFQLKXgWQv2yr2zNoV2tAMDGHQ5F+T9Z4rp6Sd6bi7LrhpIujMJWiG2Va5B4/uBcCRDhfjnUSsEXoSF6h218xLp3hFUZYfMbW992Lbu3ev3Ldv32KfhqKsWNGUxUcePEoibXPw4iijycmuj81hDx+9dSO3rK8hadm87X+e43D3KK0j/Tz3/BkGR/PPddy+to4nP/deTGP+Lj5iKZukZVPpc83bMZRJUjoknemdNjUMhNAmMpyT2dTZf9fMlAl1aUE0oZG0R8senObal4aBK8+cS1umx0qbC9m3gasMJbRSTo7umQ+aMNGFOfbvt3IC1Wg6wsmRw2hCZ0fllRONov7z5BFOjGSWOtyzZgN7axY3s9ebuEhHtA1HZt6nNZ561gTWz/o6y7HmdVxMzIri1Qt7f0fSI1yMd9LkW0NfopuexIWJ57aEd+LPcaNGUWYihNgvpdy72OehlJfKnCqKMsHvMvin1+wkkkzj0nWeaBvgA985iCPhPdeu4Zb1NQC4DZ2WCi+Hu0dxV4ZmDEwBDp/t4eJAhJa68Lyc97mBGB984BDdo0n+9PbN3LGl/GtclWxCaNOCOoGGqXkRQkM6ciyjKCgkazq+h/wuDW7LdWNV5AxyHSwc6aAJbaKMUkqJLZNZY3VmI7FIORFMzVdyZkhKScqJzdvoHMhkf8f/vXRhZibWFlnevBz5zQAbQ9vRNT2rg/FoejJD/fPuTq6srlvU7KnfCLA1vItTI0dJOglGUkMFvW4+A1MAn5H7Bs5UUkpOjx5jODWIQGM49fy0bRJ2XAWniqIAMy3wURRlxQq4TVyGxi3ra3jk/dezrT7AT0/1ZTU7umdHAzs8Do898tys+9M1QSJpzbpdqf5jXzsn+6KMJC1+7wdHePzs9PJipfxMzcvUgDLTZCfza0VDxxBuigkiZ1o/Kqb9uipPoDB9v5NsmSLtxEk5EVJ2lKQzUlRgOk7iYMkkpVYqjc8lNsRCdJCV2DKFEPplH5iO85uBiXLTceEp60x7E3G6YpFLX7agfEYAj+FlY3gbhjBIOUmS9vxk0cttJD3ESGqYanctG0Jbc2Z8p87xVRRlZVOZU0VRZlQXcPM/b71q2viKG9dWc2ptJQ9EZ7+osB3Jyz/0Ze572S76h+PEkmlu3tPKO++8Ys7nZzuSK5vC3P9CpgOqLSUPHL7IlU1h/GWeq6pk04SOWwuMBWwyKzNoaJmLe8e2C2xaVNh80cmGS6VmTrWxta2ZcTb5zk2gY08JROfaeMmRadJSltwlVwiRmffq2HnXuJaLKbxjHYtXrspLmiAFzKWxXMCte6j1NHAh3sHJkaOsD27Go3sX/EaClJIjQwOsD4Xx6LP/nN1SsXMiy9qbmGweVu2uRSIxVvj7TVGUSerKTVGUWeWbq/iOV17BJ/7nCU53zjy7EeBC3yh/99+/mPj4az8+iKYJ3v6KPROPlTKM/YMPHOInp/qyHnvwWA8Hukb4/Bv3sLrCm+eVSjkIoWGK3F9jKSVOgaWo2fNQp7NlGkO40IRRcnA2vqZ1agun/MrfjyHTJTeOKWZuZDMTU3ixENNG6pSLITzo2tIIxBbT7upanuzNrImscXsJLZHgFKDB18yp0SSDyTgJ6zn8ZoBNoe0zNiQqt4ODfXz97Ala/EHet3nnjCXPYVdl1seuKe+vTOfqQEHlwYqirAwqOFUUpWRCCLatrS0oOM3lNz/5A/7tu/uIxjMX2omUxeGv/j90vbAVB6NJi/0dQzmf6xxJcN9/P8vv3bKe9TV+XLrGz88OYDkOVzVXsL0+iFngcZTSCCFwawHSMlFAQDlzMOjIFFKamMIDwoOUk11tJQ4pJzrjPooZO1P+TsCTbJlGl3bJ60+FEBh4sGWacgfQunBPZLxXuhZ/kFevXk/ANNkQqlj0br1TaUKj0VvDf5w6ws0NQRwZ4z9OHeGulvXUe+c/yLsYi/K99jMAtEdHOTE8yObw7PNXx4XMSlb5VtMd72IkPUyDr3k+T1dRlGVGBaeKopRMSskvXjhf8uuTaZtnj3dNfPyGW7cXHJgCBN0G775mNf/w2Jmcz/fHUvzJj46TtKYHJf/z1qvY1Rgq/qSVogihYeIlOUtwmgkcp4+c0cZGnWiMr4EUY/udcgx0XFqAVI7uwUtRyomgCzemVtoaUiEyTYvKGaDqwjW2RlgZd01tw4If05EOg8k+DM3Epblx6+6cNzJidmYN/1M9MVKOjWSUL544zG9s2zOvWd4LsWE+f+IoCXvy5s1XTh+l1uPlyuo6bqxvmjWQF0LQ6GumztOAJeevF4GiKMuTShsoilIyIQRb1tSUbX/vfdVVRb/mXVevZmt0gJ2h7Httbl1wVVM4Z2D6qm31KjBdQJdmLDOBkAdT8+HS/GNrHF3oTF6Eaxi4tAAuzYcuZh9vogltxnWSc10zOp1AK2Cd3PgcUV24cGtBXFoAc+xzKpXlJDNNi+b4K3x8fIwh3BjCs2IaIC1lAkFn7DynRo5yZOh5nut/mrbRU9OaabUGQrg1naRjT9yeiFhp/q/j7LyclyMd2iNn6YiezwpMx9mOJGZZRWWYdc3ArS9Eky9FUZYTlTlVFGVOqsOlr5+7VGWouPWhnb0jfPmHz/Pgzw5z621uDE8Aa6yj8IaaAPs7h3O+rtavMkQLSyLQx9aMmtODIMFEWGqMXYSXEigZwosj7bE5qAKBjiYMBBppWdhc0szZzpaNzJQri7ExM5ZMZjVP0jDQtfFsr3bJKwFKn/drOcmJWacSG4E+dsaFB9+ZkT+lj7ZR5o8Qgg2hrZwYPoQ9NtO0L9mDqbtZ5WuZ2C7scrO1oornB3qzXn9yZKjs52RLyanh08SsfhK2HwFoY6OVxt91NR4vdzS3lv3YiqKsPCo4VRRlTkqcjpHTk4fa2bFu+rD7L//wec50DXDrVetY31TFv33nGX5x8DxPHmqfOP4jDz/LXW+9jSNDmSDBY+bPKv38XD+/eeParDWnJ8738adf+Cn//WevVxmkMtOEgVsPFLTtXL72mZErATKlriJrX47jzgogZ+bMuO7UEK6JoFMIgSk8GNKNRCKlhRB62QO/8SD40rW74+eYWVMryS7zFWPZ1bGAH32slFio9/gS5jP8bAht5eTwEZyx8O9CrB2BoMHbNPFv1+jzTwtORZlGLE31k67zPD/QT9g0aIuO8JKGIJXuCFJC2nFR6V7NprCaLa0oSnmo4FRRlJJJKfG6y/dj5M+/9ChvuHUHFYHsUq87XrSRNa/9e/7mqz9HiNwBcU11kFOjkx1Mj3WPUut30Rud3tX0RG+U/R1DvGhN1cTn8YFP/oDHnm/jiUPt3LBzddk+J2VhTV2XOpWpedAcjbSMT39RDuOjZqYGdhPHyFFOK0QmV4uY+3o/RzqknShC6CAlDlPX5eUOPsZzWJPnKcf+Z0+8zqUt/MgRpTQBM8Tmip2cGTlO0slkyrti50k5SVr8a9GExotqGzk6NMC5yMjE61x5OquX6vn+Hh692AHAUMpGA4JmpgpBCEGVx8umUJ16XymKUjZqzamiKCX79mNHuf8nh8u2v9uv3kDQO/3i3pkSjebL1G7c3EzKnnwymnbojabwmdMzWKYuuLKpYuLjHz51kseebwPggcePlXj2ylKnCbPIdZpjGdixLOr4n0tLdcstcxwHR6YvCUwnz2nm147Plp38fnCVOF9VWTw+w8/G8Las92xfoptTI0dwpIOhabyyeW3WawZTSVI51oQWYzCZ4OBgHw91nON/205lPberKoShTZaQuzS3el8pilJWKjhVFKVoyZTFe/7qO/zGJ75f1v2e6uwnmpje1bW+0s8bb93BjnX5S8ciI7kzYlvrM+WkLSE3myrcbKl089L1NSAllu3gOJJ//ubTE9t//xfHpzUfUS4fxTZGunT+qkDLyqLOi1nef8U2Qhpfe6ssP27dk7XWFGA0PUJb5DRSShp9fl7S2JL1jvjBHJoi7e/r5hOH9vO1M8d5rLsTe8p7scLlYm1gJGv7gWQv/Ymeko+nKIpyKfXbSlGUoj1/6iL/9aMXyr7fi/0R/umbT/GH77g563EhBH/6rlv4xP/8gkNncl8IHTx0jpt2bKBzdHJdYdCtc3E4zroqL55olO//7y8AaKoN8cT3n6CpNoTjSH767OTF3JmuQZ49cYGrNq8q++enLD63Fpz2WCZLaWPJ5JQ1eyLnmlNduOY9U6QJEyETeRszlb/zsLKUNfiacOku2iJncMaaJA0ke5HSwa172F3lYXNoJ/efO0l/MsG+vm6urW1glW/2dd5SSvqTUWo8mW1PDA/m3XZD0IMQ028ejqSHqPaUZ82p7VgknQQ+o7A16oqiXH7mPTgVQtwB/COZ9oSfl1L+9XwfU1GU+fWv33mmLPu5fmcLo7EkmtDQBBw/38eJ9v5p243Gknzgkz/gJ/tnzgg4HV0EauvwGBoNusP+xw9yoHP6/jp7R+jsHeH5kxdz7ufFv/4Fvv7xN3LXDZtL+8SUJSnfetRMJlJAjoDw0gB1vjOQUjqknOiMHYMFooCOwsrlpMpdC8DZ0ZMTjw2m+qc8X8P7N+/km+dOcWJkkIMDfQUFpxfjnTzRM0h33CFhW/QnM+tbvbpBncfNxXiCpGPj1jTqvbkbikXSo8StGF6j8M7tUkoGkr3TgtrexEVG0sPUexsJu6oK3p+iKJePef0tK4TQgc8AtwMdwDNCiAeklEfm87iKosyP3miSf3+qjROhGl5x17U89MNf4tilXyRrQtAzGKN7IDLx2JMHz3P/Tw7zhlu30zsU5bc+9SAPPX2KWI5y30v94udH8HlPYboMfjlc+OiQSzmOxHbUxf9KogkdtxYCJElnNO92c50tOpu0TMyaGVXvzJWp0lVDh9ZG2pne5G0g2YepuXjbhq1cjEepcM0+LktKyYVYO80+jZ6Ei0g6RaPXi6EJ9lSmMfUYjoSk7cWtx9HE9OMCpJwkx4cPsjG0Db+ZqUyIWRHaIqcJmZUEzCAuzY2pmUgklmPRHj1D0KyYtq+IFWE0PYwjHRWcKsoKNd+Z02uAU1LKMwBCiK8BrwZUcKooy0zadnj5vz9F0spcOA/h4urXvoTjP3qKoeEYhqFjWYU34qgMepASTCP7Yr+9Z4R3/sX/8o/3P0lH9zDdg9GizjMWT0E890VUod7zqqu4+0aVNV1phBDYzuw3QeaLlM60UTGXmmnEjXJ5E0JQ5a6hO96V8/nueBcBI8QqX2FBnSXTSCSGZrO3OrNmXxOJrG00AV4jwUxNuDaHd+A3AhONwqJWhBPDh3GkQ9JO0p/sQSCwpDVRllzpqqHB2zRtX27NPXZc1RJFUVaq+Q5Om4D2KR93ANfO8zEVRZkHBy+OTASm43pjaapvvIqtfhfRtE1jKsoTPz3AaGz24LCuMsAvDp7P+ZzjSPYfy30BNt+EgNfdso1k2sbjUsvyVxp7WnfcqeZ3rensa0lzr4NVVo4aTz19iR5smft9enr0GI1WM6v8s4/D0qY09tJKfGsHzBABM5T1WHesky3hnXh0T1ZnayklSTuOrhmYWu6RS34zSB2ZdbaKoqxM833llevHXVZFkhDifcD7AFavVrMFFWWp+pcnzuV8XALdY7NET+Lhims2k+4bZP/xC6TS+S+k2y4OceXmRp49fmEezrZ0UsIrfucrAIT9buqqAuz7wq8C4Moxlka5vBjCTSpP9lJDn9dmSONZpXzUWlPFo3vZHN7OieHDWHkCVJ9ZWDMhXdNxaW5STu61pIXQLilzt8YaGuVafyqEwK3PPGs3ZIaJWdG8wStA3IoSSY8SNMO4dY8aZaMol5n5Dk47gKk90JuBrHSIlPJzwOcA9u7dq37rKsoSdKBrmF+2DxW0bSAU4MFHD3LDrtX84oXcmVGARMpiMM/4l6ViOJpkOJrk6cPtvP3P/5fqsI87XrSB1968jSs2NaqLosuQJnQ0dJxpGUqBoc2+jm8unIlgQ0zpGpx9DqWQOEgp1fv1MuE1/LQGN3Jq5GjO56PpCH4jMGOAN67B28T56JmSz+XSrOlwaoCYFaU73kW9dxWR9AjDqSHiVhRd02n0teDRvXn3Z2gmITOMI52s0t6oFaE/0ZMJTK0I43kOU3OxJrCesKuy5M9BUZSlRcznPD8hhAGcAF4KdALPAPdKKQ/n2n7v3r1y375983Y+iqKU5g9+eJTvHs7d2XYqUxOMPHOQCxcz4wj2blnFvhnKc30es6BGR4vNbeokL8kCb19bx9vu2M19L99NdbjwLpXK0pdyYllrPwUClxbIKlEsN0fadMe7GEkNUeupwWfmf0+Vsu5UF25MzTPX01SWCCklJ4YPEbFyN+/ShM6eqmtmvSEhpcO5yGkGkr1FHV+gsT60eVpQeHrkGEOpASCzrnQw1QdAnaeRlsDaoo4xle3YtEVOMZoewbqksqHKXcva4MaS960sX0KI/VLKvYt9Hkp5zeuKcymlBfw/4CHgKPCNfIGpoihL15rK/He6xxmaoH5kcCIwBdh3rIsrNjbkfU1D1fKYZXdpYApw+GwPH/mXh7nrd7+6LAJsJT8pJeM3ajN/z/73NjXfvAamAMOpIbpi7USsUQZSQzNumwlMtSI6B+fLxCrLlRCCJv+avM870mY0PVzAfjTWBjfiKrIqwKW7cmYrY9ZkA7vBVB8uzcWWil1zCkwhU4K8LrSZXVV7qbiki2/Cnt6Z3XYsOqPnOTL4PEcGn6cj2kbSTkzbTlGUpWfeu31IKR8EHpzv4yiKMn/chsaaSi+VXpPnu0amPW9ogvqhAR57/NC05/qGY9y4azUIGI2mCHhdCAHPHO2kOuzjTFf+oe/LwfMnL3KivY940qLt4hA3X9FKY3VwsU9LKZAjLWyZQgI6JlI6WY2JBPq8zzYFGE0PoQuDSlcVPmP2m0HgIBnPojrkHzAjMDUf+gJ8DsrCCpghqty1ebOe5yNnqPU2EHZVzlhKC5ny2GLWnl661hQgkh6Zto+Uk8IqYwdsIQRrAhuos6NE0xGSdpyBZF9W2fpIaogzoyeymkbF4zG6451Uu+uodFfj1f2Ymlm2Uvfxm1uqdF5R5m5ey3qLpcp6FWXpiqdtPvjdQ/z83MDEY6tDbvzxKM/98jhdXQMzvHq6G3etRgjB4wfayn2qCy7kdzMSnbwo27W+ntuvWc/m1TUkUzbJtMX1O1dzxabGRTxL5VKOtEg5M48qMoRn3teaAlyMdaAJQcgVQKAV0Lk3W75SX5fmX5DgWlkclpPm6NALMwaWLs3Ntord6Fr+98GFWDv9yV6klNjSwp6lOVeuUtozIycmynir3LXoQqc3cRFDmGyr3F3QGljIrJkdTPUjpYOhGYTMCnxGYCLwG00Pc3rkeFbw2exvpc7TSMpJcnTohbzdjKfaGt6GS/eiC9ecg0rbSWFjYQg3mlCN8xaKKuu9PKnfWIqiFOS7BzqyAtOGgItnHnicaLT4To/VYS8vnO5m65racp7iohm55GvwwuluXjjdnfWYEPCOV1zBn737JdQvk3Lmy51AJ9NkaKabtAtzA7fWU0dajjcIK/5CWWLnCFDF2OeoXK4MzWRjeBvHhw7m7d6bcpKkZRp9hku+Rl8Ljb5M/8pIeoTeRDcVripMzcXFeAdJO0HCnmxgF7ykERJAtaeWqDVCyklR6aomYmWqbCyZJpIepdJdnfPYQ6kB2iNn8Rl+1oe2ELMiJO0EhmaQsBMMJE8TdlXQ7G8dO3aY1YF1nB09MbGPjug5+hOZDHIhgSmAg4MlE1gygS5MNGGiYZQUqOqaC02aWDKBI7UFuaGlKJcrFZwqijIj23b4o39/hBMJmPojwz7XUVJgCuD3uPB5TAaWeLfecpIS/uPB5/jWo4f50h/ew53Xb17sU1rRpJSknRgzB58CXRSW7ZkzIUAyljUtbZapHCv0nehkKtSYjZXAo3tZG9zMyZHcLT10oeMuohnWpbNLN5hbkdLh2PBB3JqHCnc1fmP6Dbawq5K1wU0cHz6EJdNUu+sYTPaTcpKMpIfyBqdhsxIjaExkHGu9DdR6J3sVSCmJWKNZpbtBM4QmdNYFNxGzolyItRO3Z66CmIkt09hjjZY0YZaUARVCYAovlpPEcpIqQFWUEs1vhwdFUZa9Hzx5gk99/UkMl8HWyswv2wqPwdNPHy96X7om2Lqmhpa6MLUVftouLu/1pqUYjaV40x9/gy//8PnFPhUlJzH2/xruee7Qm0WKksp5s2XWno5nhFU578oRcoVZ7V+Xcy2oR/fN+SaFEBpbwrtYF9pMlbsGt5472B1/3JY2XsPH6sA6APoTvXnXxgohCJghfIY/7/NBM5T1OZiaiz1V1xB2VdLoa2Zb5R7CZmXBpcNA3pnBjkyTciJYTqrgfUEmiE7ao4DIrGNfQsvmFGU5Ub+5FEWZ0RMHM7NKH7j/cQBe9dobOHf8bFH7EAKu39HCobM9HG3rK/s5Lje2I3n/3z7A0bZe/t/rrqWpdnqJnDK/hMg0Cko5USQOunChCwOBTlrGx7KOC3f/VhMaUs4lMJ0ksXGJBQyslSWh1ttAyFUxMXJlnFam90EhAW7CylTDjAdmXt3Hav86HBw6om1Uucu3lGPq+Xh0LxvCWwFI2Ul6EhfoTXTjzLJ2diaWjIMjZ8yATm2EJLEnbi65NP/E+almSYpSHNUQSVGUGZ27MMiO+/4Z2yn9Z8WuDfW8cKp79g1XIE0TNNeGqK3084WPvobNq2sW+5RWFMtJIbExtUI65M6vhD1COda4CnTculrXvFJJKTkXOTWRqQyblROB23zrjnXSEWtj1ZQ1rAAnh48gkWwKb5+X4zrSnlaGazsWfckeOqNtObOkm8KbMWdoEgWZCorMjOPJwHLyJpLAlulMYCollozn3N6R9tgNMLP0T1DJSTVEujypzKmiKDOqqwzQUB2ks3f6CJlCrK4Pq8B0Bo4jOd89zPnuYT7zraf59G/fudintKLowsSRWuYCMk+WRRPlGzmRT+ZGcXluFquL4JVNCEFrYAOm5iLtpPDpfkZSQ2hCw9RceUtyy6HOu4pQjtE160Obi5jLW5y4FeVivGta92BdM6j3rsJy0lyMd+Z45ezfbxKHpDOKLkx04UITmdFNaSc2GfCO/ccUXvQcZcUCjbQTQ2ia6uSrKAVQwamiKDMaiSW5YmNDycFpS32Y892zD4NX4NHnzi32Kaw4QggsJ5E3MAUwkBhifpubCFGONaeKkiGEoNm/BoCe+AVOjhyZeC5sVlLtqaPCVZV108WWNvocgychBF7DN+3x+QzKhlNDmFr+GzIN3ia6413TsqeF3wqS2DKFLVMYwouhuXBpQRwsHGkh0GYcRyOEwNA8pJzo2GgnFaAqykxUcKooyowaqgLc/xdv5t8f2McH//GHOEWU965vqmIosnI68s7VyfZ+2nuGaakLL/aprCjm2IVjPrZMo8vcF5/jJX7lWN85vgZ2rhlUSybAQXULVXCkTSQ9glvzkHQSAAynBxlOD1LnacSlu9GFji502qPn0NAIusKEzArCrsqyrVedT0FXGK+evyxf1wx8hp+oFcl+oshvM1PzTYxmEkKgYxZcpaALEykcpLRJOCkSVpwKd1VxJ6AoK4QKThVFKch7796LQPCBT/6g4NfUV/l54mD7PJ7V5efJQ+203KqC04WkjTVCyjfCRWLjYKEzeSE6PorGwUZDH9uHyFnWV/h56JjCM2XeaemcEsfRKJcXTeisC20maSc4M3qcmDV5E6YncSHna5KJBH2Jbpr9rdR7Vy3UqZYs11ibqTIZ4XJc7oo5BevjN4t0IGnHGU0PEzTDRNKj+I2AapikKGNUcKooSsHedsdu/vw/HqVnsLB5cr0FbqdMWttYudinsCLpwsSaobQ37cTRtMyIFgcbpIODBZBd3sfc5qJqwgSZYK7ZU7XuVJnKrXvYWrEbW9pE06PE7Rhu3UPKTjKSHmYkNTit7LUzep6hZD8u3YNbc1PtqZvX9arzwZE2RwafI5VjLEyeIlx0YaIJA0daY7NPM1+XtBOFPOtKixV2TWZNpXQ4O3qCel/TrIG2oqwEKjhVFKVgbpfBV/7kdbzid75SUHlvddjHyY6BBTizy4PXbbBnY8PsGyplpwljlnhQknRGZ9yHxMGRTtHZFUc6RK1RknaClJPCpZn4DY/KpChlpwudkKuCEBUTj9V5G7Edi9H0CDErQtJJYjsWEolAMJwawJY2F+Kd1HsbafKtmehQm3ZSdMe78BsBTN1F0AyTdlIMpQYxhE6Fq5q0k2Yg2UPQVbHgwddwamhsjaiHeu8q0jLNYLKP0fTwtGBcoGeNgNGFiSE9pJ3oRCVCWsZBirLe/Am6wngNHxdiHWgegaGZWE4ab565r4pyuVPBqaIoRXnxnlZed8s27v/J4Vm3fepwB9ftaOHJQ6q0txDXbGvGNFSzjMWQa9REKUSefMxMOqJn6U1kd7T2GX4qXVX4Td+s4y5ycaStsqdKwXTNoMJdlXMdpCMdhlIDaGiEXBUTwVtPvIuOWBtu3UPaSRE0wxNlqkPJftJOmu74Bby6F58RyFoXKqXEljZGCe/tYlS6q6l0V2c9VuOu41zkFLlyp5feEMo0M/KScibXq2aqKIyy3jwyNJOWwFqklGMzYU+xMbytbPtXlOVEBaeKohTtt990fUHBKUAqrda+FULTBB+576bFPo0Vy5HpRTt2JD09IxuzosSsKAJBraeeOm/92JrYwoJoWyYxpFtlX5U504RGlXv6/OVqTz013oasDr+WY+HVfTMGVkPJAbpi5/EYPtYFN83LOc9kfNTO5IxSZ2wOae5y3cxacO+UteCSlBPBEO6ylPiOc6TDQLKPsKuCak8dQ6kBKlyqaZKy8iz9NmyKoiw5V2xq5Nar1ha07f7jXYQDHlbVBAGoDHi4YefqGV9TWxNi79Ubuf3lV835XJeLv/6127nlysK+pkr5lSvLaMvpa9tmEzTzN8CSSHoSFxlMDuHWiiuJLOVcFKVQhmZkBaa2Y9ERPcfhoedoGz090cl6qoQd58zoCZJOkkZv80KebpZMRtSVKd3V3Jiad8YRL7rmwtQmR+RIHNIygeUky3ZOEsloeoizoycJm5XoqCoaZWVSmVNFUUryoTdfz0/2ny1o2+FIAk1kRssMjMToHojk3M4wdG5/5dWcxcWALcG7MsoS//x9L+UDr3/RYp/GiibQZ+zYWyhHWkBxI1zGR3zMZCDZR4OvCUN4MqNiCmDJJMLR0GeYAako5aJrBq3BDdR7G+lP9mJLB+OS9ddxK0qtp54qT23OeahLmS5MhBbAkRYSBykdLJnEsdMYswS3he1fZ+2UTLIQGrZjoc9z6bOiLDXqHa8oSkluvWod125v5unDHQVtPziaYHA0c1HdOJZFner6G7ZhrWrgeGyyO2LKdtB0gWOXZz3gUvSn77qFD7/lhsU+jRVPCIF5ydqyEncEZNbUZS5g5awXl0l79mBTH7vI14RecCNfgYYtU1kjcBRlvnkNP815mvlUumuozFEivJj6E3EkUOPJPyt1nCb0rCBUSgcHGzEPhYgCaIucZk1gvQpQlRVFvdsVRSmJEIKPvfsl3PGhrxT92lMdA+xYV0f/cJzVL74CYRr0xy3Ssex1fwnLuawD09fdso2PvO3Fi30ayphyXGA6Mk3CHmE8guyN9+HWfRiaSdhVmVUGCZkgNmnPXhpYMdbURcxQ6pc5/7HgGBuJPeP2irLcSCl5tr+H4XSKvTX1hMy5r/l8sOMsAdPFPWs2FP1aITT0eVoh5zeDrDM3z8u+FWUpU2tOFUUp2c1XrOUlJayTTKVtDp3p4UL/KP6+PnqiadJ5RtPccOPl2bHQNDT+/L0vXezTULKU60bI5H5idoz26FnOjp6gbfQUUStCzIrQN9ad15FOQf19XdrUUmEx9v/aRDmyQMtkaseC0ku3VZTLgRCCK6rr6I3H+Kcjz3FwsI+0YyPl5PeclJKUU1h5ftpxODs6Qmc0QspWzfsUZSlQmVNFUebkY++5lZ/++hdKfv0vnjrO9juuY8iZfhFtOZLuimpeefeLePCBp+ZymkvOh958PWtXVS72aShT2PPQsTdohCa68Q6m+hlM9QOgoZG0E4RdlWyr3ENXrH1i1mkuMStCpbt6rKtw5kJcMr3hzKUK2WY2trQQjM2CVZRFIKXk0GA/lnSIWmkuxmPELIuvnTmOS9MwNZ0dldX0JeL0JOJUuty8Z/NO9Fm6VR8c6CXp2FyIRzk+MsjOyqVVcqwoK5H6TaMoypxcvbWJ97zqKj7/vf0lvT6ZtqmQFkN51sU5Eo7ZJle//laq3RpW3wA/fujZuZzyonvFizbyx++8ZbFPQ5nCkVbBjYaKEbNiuY+Hw8V4J93xLjaHd7I2uJHzkTP02hdzbh8eHykhRFEJ3rIEp04SBxu3FlSjaZRF8b9tp3i2vyfncynHIeU4PN07+b1T5fYUVBqYcia/P37a1c62iqqJ9d2KoiwOFZwqijJnH3/vrXzv58foHoyW9PpzjjFr9WF/PE1/HDD83PHW20ld7OUnjzxf0vEW09vv2MPf/+Yd6Lq6AFoqpHRIObmDyGJ1RDoZTg8VfmwkZ0dP0OhrIe3kHv0SMEIEzEwTMW2B15CON3YCiS3TGHlmQSrKfBlKJfMGprm0+IO8vnVjQTdSjg4PTPy9OxFjMJksqDGSoijzR10dKYoyZ5VBL9fuaCnptQGfa6LDaaFODCU45wly9etv5SVvuY1rrln4Qe6l+vXXXUPAqy7wlxJLpijXetNSMpVJJ8G5yEmGUgM5n3fr7ok1dUJomJpvXrqDXsqRFmkZn/icnHkoe1YUyNwEGU5NbwyWdmz++/Sxovb10lUtVLk9BW07mMyulrCcuVcaKIoyNyo4VRSlLHauqyvpdS6j9ExQfzxN20iSho2lBcaLoTq8vGb7Xe6klGUNusp5aevS3KzyNVPtqSblRJBybDSNMDG1wt9HU5vFFMOWVtbXphwlwooyVdK2eGGgl787uI+/PbiPb547SdK2Jp5/vLuLzljh453qPF7WBcMFb1/hyp5JfHion95EjP5EvOB9KIpSXqqsV1GUsvj1117L1x85xKmO3NmffHbtWMP5OR77TNTGNHXS6aXfbTGRVNmnpUWWN+gqMRAcFzCD1Hnq8ejurIICiUPSGUWg4daDmXmLGDhY+Xc2xsEqetapIy1smZ3JGp/bqtadKuXQn4zz/fNnOTEyOPHYc/09jKSSvGntZly6ljObOpO7V6+f05rRn3d38rOLHVS5Pbxz4/ZpwetS5EgbgUCotbLKZUK9kxVFKYuqkJfHPvtuXn5tcbPijMrQnI/d7DfmGhMsmFhCBadLiSNnD+6K29/cAt1qdw1ew5230l0ip5T4FhYkakXeh7acJCkn9/rx+ehorKw8Cdvim2dPZgWm406PDvOXL/ySP3vuKV4Y6C1qv/v6ukkWMRImYGbftEk5DraU9CbiPNI119umC0NKm/Q8NHNTlMWiglNFUcqmMujl23/1Fr7w0ddQU2D5akybewHHqCWxrKWfNQWwbFUauZSUO9iSJa5dNYRJwAiSdmY+H00YU4LS2YNTXbgLDmIdaWM5ibxdi4vZl6LM5FvnTnI+Ojrrdqki14A+P9DLPx95nn193aRnmXWasm2ODuWv9Fku73RNGAveKE1R5pMKTvMYTiWLLidRFCWTzbn3Zbt47j9/nbffsWfW7X2js1+gzOZCJMVLXrqHPXvWsWtHK1u3LN01qOubqhb7FJQxUsqCymKL4TP8Rb9GEzqOdIhYo3TFOjg8eJjjg8dJ2dMDVSltpMx0zrVl7u6+4wQahpi5LDETkCZJ2hFSTgRL5v+9pwuz6CysokxlOQ7P9/fQHi18HWmxBlIJvt12ik8ffp7zkfy/X85HR2cMfs9FRubj9MpOCA1NGNh5un2XgyMlz/f34CyXEiVlWVPBaR4eXSdoqo6ailKqmrCPf/v9u/n5v76H269en3e74b7hshyvzRNkpKmJyJoWKnYtze69LfVhwoHCukgqC6H8F1oNvjrcWuH/xl7dj5DgkJ3lsbA4OXKCo4PHSE1pECNxSMs4ljNzGZ9Ax6X5Z8102jKFJRNICqk8UOtNldLY0uEH7Wc4Fxnh/nMnGU3PXyA1biCV4PMnDrK/r5u4Nf0m1KHBvhlf359M0BMvz4ip+aYJHYRWcvOzmfyiu5NPHX62qMZUijIXKjjNw60baOqXsKLM2VWbV/HA376Vhz/1Dq7fmZ3RFALMtc1lP6ZEYppLr8xpe2vtYp+CkkUQTUue6R3i62fO8/jF/mlrl6Wc/mc260PrcWmZjKUuTESeAkGf7iduR7FnCAwdbIZS2evyHJnO28RJEyYuzT8WmM78K15Kp+CyZg0DoUoHlRL9qLONJ3ou0BmL4NEX7n1kS8n/tp3ibw4+w8GByWA0ZdscKGA961dPH52XgG8+6Fkl/+UhpWR7ZQ2/tf0K7mxZp66LlQWh6nMURVkQN+5ew8Ofeier7/kE/SOZNv0vvmo97U75L1R6ommuuudmzvx0Hz29S6c0a4sKTpcUIQRfOHGS4bEszomREX7e3Y01S1OjF9c3cGNDDRrTR/TaDgylLPoTFTzb30d/KkXIMHhpkx+PlsKSaWxp49G9xOzcTYdKoWFgat6iOnZmsrWFXXhrQldZU6VkJ0eGgEyQuhjSjsP9505wcLCP9aEwv+ztLmg9a38yQV8yTq1nZY0A60/E+crpo9hScmfzWioq1HIUZeGo4FRRlAWjaYKnP/9+/vDffsyBUxc5dqabaze3cmio/CVePdE0V16zhf/7wS/Lvu9S+D0m77rzysU+DeUSq3wBhocnm6LMFpgCPNZ9kce6L058HDAMWvwB0tLBciDt2Iym04RdXnTNojcR5zttw9zZ7MKl25jCRdIuvKeBKWZeYqIJE1N4iw4e82V0c2+rCq2U0qQdm9HU/JfxzsaWksND/Rwe6i/qddqyaY1UXl7dQBeCao9aiqIsrDn9thFC/J0Q4pgQ4gUhxLeFEBVTnvuoEOKUEOK4EOLlcz5TRVEuC021If7jj16LQNA9EKH3TOe8HSsWWTqD1K/cvIqNLdWLfRrKJe5p3UDlHGcZRiyL7nicUyMjnIuM0BmLMpJO0R4dpScRR5LJTx4fcSGlJC1TRc1W9Zv5myzpwlVSYAoUVaarieLmpCoKQNK2+dKJw8Ts8jYeW0iFdBW+3FR7vLx/yy7es3nnissaK4tvrrdCHwZ2SCl3ASeAjwIIIbYBbwa2A3cAnxVCqMUqiqJMWN9UCcChg22sC5d/0HnYY3Dg+dNl32+pWhsrFvsUlBz8hsmb1m2e834KKY49ORJhOB0oet+6lvvXp6n5xkp5S8vsCCEK6r6rUf61bMrK8MveC7Qt8+Duoc5zPNvfg71M1p4qynI3p+BUSvkjKScmmD8FjHc2eTXwNSllUkp5FjgFXDOXYymKcnlZ35xZwzIaidN/9EzRrzc02NscZs+qEGsqvbgNDZcuWF3hZWtdgCavzvDw0um0uHtDw2KfgpJHsy9Ancc7p30U2jTlyZ44cau4MjnbuTTrJDA1H3oZspmamD04LcdxlJUlblk8drGDhxZpjWk5jabTfOvcST51+FlOj62dVRRl/pRzzem7gK+P/b2JTLA6rmPssWmEEO8D3gewevXqMp6OoihLWXV4slSoZWMzw9Hi7krvXhVmX8f0MTTnhzKlvHuWUCXSTbvX8P7XXL3Yp6HkIYTg6toGftB+dt6PFbdtHr2Y4pYGD15j5nEw4y79zjCEq2wBYyHlxaqkV5mNIyWHBvvY399D0rbpiI7Ow6CmxTWQTPDFk4e5vq6R25vW4MpT0aAoytzMGpwKIX4M5Lrl/4dSyu+ObfOHgAX81/jLcmyf8+eUlPJzwOcA9u7de7n9LFMUJQ+/Z2qTF0GxMyfbh2ZeT2obS6PfW12ln//849di6KqhzFJ2ZXUdD3e2FdTBM5di3r1x2+aRC0muqg7S6Ju55NGtuXHr2cFhuX5ROtLGljM3qtGEqUp6lWksx+HM6DCGJjgyOMCz/T0knUJm5S5/T/RcIOxyc2N9zpyLoihzNOvVm5TytpmeF0K8A7gLeKmcrGvqAKYONGwGuko9SUVRLj9+z+QF9y8ffZ7wtbtJO4VddusCBuMzz2dMaksjOP3tN19PY3VwsU9DmYVHN7ihfhU/vdBR0uuLDRhTjsPp0RQNXjlj8NfoWzXtMVsmMaSrqLExl5JSzhqYAuiqqb9yicOD/TzYcZahVOEdpy83P7vQwZZwFTVzXA6gKMp0c+3Wewfw+8DdUsqpi7seAN4shHALIdYCG4GlMc9BUZQlwbInM1QXe4bZHCq8dHBzbYC0PXM4YIilUYixXc02XTZubmimyrVwYxN6EglOjIQYSAZyrlmt89TjN3PXp1sFBJYzsWWyoOBUlfQqkLmZMZhM8GD7Wf77zLEVHZgCxGyLn15oX+zTUJTL0lxvif4z4AYeHrvz+5SU8lellIeFEN8AjpAp9/0NKeXKqPdQFKUg5y4OZX0c7RkAV6aT6Z5VIT7+8i2c6otyoGuE/9zfzrWrK7h1Qy3xtM1TbYOz7j/hwN6rN3LuzEW2bF3NgefPMLrAo2XeeOsOrtnWPPuGypJgajpv27CVzxx9HqvABkf1Hh+DyQQj6dKCxcNDIwBsCoRo9UpCvhTS0Qm7fdR6a/K+zpFppHSXXHLrFPArWXXpVQDOR0YZSiW4/+xJnMtuJWnpjgz105+IEzBduHW1/lRRymVOwamUcsMMz/0F8Bdz2b+iKJevM53ZAeaBZ08RetEeNlb7+cw9u6jwmqyv9vPyzXX4XTov3VjLlrpM8HpDaxXv/+YBBmYo7T0znIS6BkJ1DXQBa2+vpfeJ57nQPTSPn9Wkv/q12/ngG69bkGMp5VPn9dHkD9IWGSlo+7TjkJKlrVMF8OsmsSEXf/+zPqYUE/DRWyt4/e78rytmTmpOQsxai1xIJ1/l8vd07wWODw+qwPQSKcfhk4efZbU/yMubW1kTCC32KSnKZUH95lEUZVGcu5AdnPb1j6I/8wLGxgYqvNmTp379+tasDM62+iBfvfdK3nv/ATpHCut4GknZrN/YNC/BqdvUuXZ7My/e00pzbeYC5e6btpT9OMrC8C1QM60aw8/XfjZMJBWd9twXftnJ63dV5W4vWAY6Bg4zr9tWJb0KQMA0iduXjjNSIHN/py06yrnIiApOFaVMVHCqKMqCk1Jypmt6aW53zzC3vOFF0x7PVVq4ptLHV++9kvd/8wAn+qZf3OcSCPuLP9kZhP1u/vJXb+fel+3C41I/Ti8X+nxFhFNUiQBfeHggby6qJ5JmIOZQ5c/dGkLMrWVEJvCUCfKlTwUCbQ4Nl5TLgyMl50YLqyJYyY4NDXBdbSMuVd6rKHOmrqYURVlwfcMxhiLTM5671tdzz81bC95PXcDNl99yJT873cczHUN8++BF7BnWCsZCIe6+96Xg2DzwtUdLOXUMXeNtd+zm9qs38JKr1lIRWLgGOsrC8JnzmzF0azrfemJ41iLJH58Y5I1XVOd8Ts6xxFIIgUDk3Y/KmioAbZEROmKRxT6NJe98dJQvnjzEfeu3EjBds79AUZS8VHCqKMqCO9nen/Wxrgm+/Vdv4bar1xfdgCXoNrhrWwN3bWvgLXua+djDx3nhQu47/R0jSTqANSF3See9qaWaL/7hPVy1efp4D+Xy0eILzFt7+bDhpqdHYzg+e3Oun57JHZxqGBiaZ87NioTQkXnWy+pCXWAr4NZ1NJjrCucVoT0a4V+PvcC7N+2g0q1uWipKqVTNjqIoC25acKpr3H7NhjlfbG+pC/Bf917J516/m9s35h/hEtSKzzrdetVanvzc+1RgugI0+wufSxsbMgouAg4YLv7z4VF+eGC4oO13N2afhy5cuLUgLt2PJuZePmgI97TyYIGOITxl2b+y/K3yBdgYrlzs01g2BlNJvnTyMKMldu9WFEUFp4qiLIITlwSnaat8k6Y0IbihtYpP3r2dxmDuDKknEWdVTeEByMaWar76p6/H51GljitBjcdbcFOkg+0JKkUg6zGPbtDX6aa73UW16cOrGwQMFyP9hb9/Qm6DlorM+1fDwK0FMTUvoozrQDWh49ICmJoPXZi4ND9uPYChlVZZoFx+0o7DHU2t6GqkUMH6kwl+1Nm22KehKMuWKutVFGXBtfdkZ46kBNt20PXyXXg/3T7EhdHcg+I/+Ss30fXKndz0a18gkZq9C+VnPnQnlUFv2c5NWdo0IdhWUc2+vu6Ctn/mZIL1Y4PVdCGIDbj4+YkhAJ48VfzxQ26DR95/PbZjAQl0zVXWoHQqIQQ6JrpaY6rkkHJsftTZRpMvwPno6GKfzrJxZKife+QGNBXUK0rRVOZUUZQF1zOY3V33mm1NZQ1Mk5bNxx8+nvO5xqCbKr+bHevqqQoVFnBeqUp5V5x1wXDB27r0zAWoVzc4fUrngWeH5nTst13VjM+lE3C7AIHl5L7JoijzbTCZoD06SrsKTIuSsG1STvkqghRlJVHBqaIoC65nIDs47eobJRIv3xqd/3m+k7bB6Q1nVoU8/OvrdgOw/3gXg6OzN6UBOHdxqGznpiwPq4tYd7r/XJRjx3S+/bMEz5+PzfnYPzzWQ/dokuGExcs/9wKff7pnzvtUlFI0+4NsClfOsTf0yiMAU1PrthWlFKqsV1GUBSWlpHtwcjRBa2MFP/rUOwh4y9cd9B1XtXDT2mr2tQ9xfihObzTFxho/r9nRQNDU+bMv/IRP/PcvsJ3CLrlSaXUHfKWpdHvYGq7i6PBAQdsfu1DYjY5CnBmI8aovPU0i7WBLyfVrco+TUZSF8IrmVp7tVzdIitWXiFPv9S32aSjKsqOCU0VRFtTPD7QxMJK5kNc0wRf/4B5a6govoSyEEIL11X7WV/uzHj9ytodb/+QbnOooLOAYP8etrfk7/yqXr1e0tNIeHSVipXFpGiln4QZqRFOTN0TWV6sLXGXx+AyTsOliWHWgLZgEHu5s474Nhc/tVhQlQ5X1KoqyoP7+a09M/P39r76aYYbmlwAAF/FJREFU63a0LMhxH3/+HLd+4EtFBaYAr3jRRjwudR9vJap2e3nXpu34EiF+eUBO61jq102GYrM31JqNNkPPlO31QUKqS7SyyN6yfou6YCxSf7J81RSKspKonzWKoiyYoUiCh56ebF/6a/dcvSDH/cETx7nr9/6L4WhxjWVu2r2Gf/ndV83TWSnLQb3XT5M7zLm+JGdPG3iTAWoMP/50gO8+FqdzqPRs0o4GN//xtkq+/I4QV6+e3pxrU42fv7tr21xOX1HKosUfZHUgtNinsaz4DXVTSVFKodIBiqIsmKDXhaYJHEeyvqmKjS3zv5bup/vP8NY/+2bR60a3rqnl+393Hy5TNbVY6d6yp4mv7O/g2bYoz7ZFZ39BAXavcvO7L9NxiOEAb7oywDPnJzMtN6+r5u9ftR2vev8pS8Rtq1bz+ROHFvs0lo3N4arFPgVFWZZU5lRRlAWj6xq14cz6udHY/I/HePLged7+5/9LsoSGRv/4wVeowFQBwG3o/NaN68q6z3ddF8Ah877UMPmbh4cmnmsJe/i7u7apwFRZUty6ej8WY2uFCk4VpRQqOFUUZcF09o7QM5TJPPnL2J03FyklH3+qg5obr+T6K4sLLN76sl3ctKd1fk5MWZbu2lbPzobCx8vM5g++N4ht+TjfG+Bt/xGhNzp5A+VDN6/Hr9Y5K0tMjceLIWZYIK1M8BkGNZ7C5mgripJNBaeKoiyYh54+hRyb3vIX77ttXo91si/K+eEkKQQXGlZx+yuv5pbrtjDbtVV9pZ+//NXb5/XclOVHE4I/vm3ztKZIpYqmHH7lq4P80Q/6s2ZIvmn3Kl62qa4sx1CUcnJpOlfW1C/2aSwL5fo5oSgrkQpOFUVZMNVjJb2r68O85sVb5vVYT7YNTvxdCMFp4eF8VS033XU9a5tyl1utrg/z40+/k7pKf87nlZVte0OQ979ozbzt/5Vb6vjorRvnbf+KMle3NDQvaODl0w1qPV6afQHWB8P49OVRUbDar5pHKUqplsd3uaIol4WNzZmgsKN3hKFIgsrg/JU9PdM+lPPxDkfHtWcbN7f08rOnjk88ftPuNXzpD++hqVZdVCj53bOzkc8+ea7s+33DrlX88W2b0GeaK6MoiyzsctPiD3IuMjIv+9eANYEQm8OVbApXUufxIaYEw0nb4hc9FzgfGaEvEWcwNf+9C0pxRbWaja0opVLBqaIoC6a5LgyA40h+fuA8r7px87wdazCef8RHGpHJol7j8PgvT3LrVWt54G/eiq6rYhJlZj2R8l8Mv/9Fa/jADWuzLsIVZanylLExUqPXzy2NzYRMN0nHoskXwDfDCBa3bnBrY2Y2tiMlBwf7ePRCBz2JWNnOaa4avD7VqVdR5kAFp4qiLJj9xzon/v6TZ8/Ma3A6GyEEnppKAD5y300qMFUKki8jX4oqr8kfvHQjr9ii1vEpy0d/MjGn1+tCcH3dKjaFK1gbCJd8U0YTgt1VtXh0na+cOpq1dntcwDCJWOk5nW8xdlZWc/fq9WjqRpOilExdjSmKsmB+vO/MxN8//8B+Tpzvm5fjHO+N8HzX7GVnfWc7+c03vIgbd8/fOkLl8nL3toY572NdlY8P37ye77/7WhWYKsuGlJKeeIxoem7B3pZwFXc0t7IuWFGWaoHN4SruXb+FS/dU6/Hy9o3b5rz/QoVNF69v3TRj5ldRlNmpzKmiKAtCSslDT5+a+NiyHaKJ+bmjHUlaBW33ptffyG/dunjZW2X5Cbh1vKZOPM/s3Iagm5esr0HXBKsrvJwfitM+FOeKpjADsRTvf1ErYY+hSniVZWcgleAfjzw363YNXj/Vbg9Vbg+mptEZi2BLSdh0YWr6RFluOW2rqObWVat5pOs8ANsrqrmzZS0nhgdneWX5vLihGUNTOR9FmSsVnCqKsiCeOdrJ4bM9Ex+H/W7WNFTMy7Guaq7gYy/bzE9O9XFhJMGJvui0bW5oreLXXqw6oyrF8bsM7n/bXv7ikRMTHaG31we5ZX01u1eFedHqStXUSLkshUwXdzav5bHuTkbT09f0V7rcbA5X8cqWtYsySqXJFwBgU6iSe9dvwZGShzrb8Bsm0Xku7a33+Limdu5VFQthNJ1CSknI5V7sU1GUnFRwqijKgvjX7zyT9fFH3v5iqkLz16339btW8fpdq5BS8vOzA5weiCIQHO0Z5bU7GrlmdeW8HVu5vK2t8vH5N+zhZ6f7iKZtXr6pTgWkymXP1HSur1/FlTV1/LjzPEeHB3CkxHIcXtzQxPX1q9DF4mUON4cred/mnZhj2ctn+3tw6zr3rt/CZ48emNdj766uXTbrTGOWxX+dPso7N26nyu1Z7NNRlGmElLmWkC+OvXv3yn379i32aSiKUma9Q1E2vPFTpKaUQp771oeorwos4lkpiqIolyNHSi7EotR5fXRGR/n3E4fm7VgBw+QD2/YQMF3zdoxye7izjZ9d7GBjqJK3b9i6bJcZCCH2Syn3LvZ5KOWliuMVRZl3//PwwazAFMjZWVFRFEVR5koTgiZ/AFPTqPf6+dUtu7i5oXlejnV705plFZgCvHTVanZU1nBiZJDu+NIZw6MooIJTRVEWwH89NFlSJQR86rdeQYPKmiqKoijzzGsYtPiDvKxpDdeWeV2oALZVLL+ZppoQvL51Izsqq3mipwtnCVVRKooKThVFmVcvnLrIC6e7Jz5+4607+P/bu9PgusrzgOP/x9psy7IlW17kRbYB22ADgSBMSCCBQIAwkzikQ0qbNCRl6pAhbaczzULJNE0ZOmmYkknbLENmyPLBpW6bOB4IhGUSmJCwxTF4w+ANI++7sYVlS3r74V4bydYFYt2rcyX9fzMa6b7nLo/fx/dcPTrvec7nPnZxhhFJkoaii8YV99JNjcNHDNhLx1QOG8Z1U2awfO8ufrdzGz9/dX3WIUmAxamkElqxfgcLvryox1hVZUVG0UiShrJJI2upLWIxWTfAlvOerKFmOBc3TuKRLZt4Ye8uj6CqLNitV1LJVFdVsH3voR5jG7buzSgaSdJQVhHBZ2fN475XVtLWUfh62HVV1b1eLmd4RQXvGjue2soqhldUclHjhFKG2y8mjRxJR0p0pE6+99ILXNw4iUkjalmzfw9rD+7jtnPelWkXZg09FqeSSqa3brxPr2plz4E2xo0ZmUFEkqShrGlkLV88r4V1B/ez4eABdh5p49VDB+nIHzW8enIz5zU08p+rl3MsdZ143PsnTuGKpqnUVAyuX527F+lb2w7z881vLu9trq2zMFW/K8o7LCL+HrgbGJ9S2p0fux24BegE/ial9MtivJakgaN+1HDePbuJZS9vOzF2+19czqgRA3splCRp4KoeVsHc+nHMrR8HwNHOTl4+uI9hESfG7rhgPs/t2sFvd27lminTOX/s+CxDLomDx46yZn/h1UwXjBt8/2aVvz4XpxExDfgQsLnb2FzgJmAeMBl4LCJmp5Q6e38WSYPVnOmNJ4rTs6c38tXPXJFtQJIkdVNdUcG5DY09xqqGVfDeiZO5dELTgL0O6Fs5cLSde1Yuo6Pb0eHjFjSfSUNNDTNHjckgMg11xThW/y3gS/S8bOEC4P6UUntKaSOwDphfhNeSNID84eVtLH78zYuff+jiMzOMRpKkP85gLEwBRldV89lZc7lw3Knnzc6rH8es0Q1UDnNJr/pfn46cRsRHgS0ppRdOevNOAZ7udrs1P9bbcywEFgI0Nzf3JRxJZeZ/f7WKzq43/271vvOnZxiNJElDW0qJiCAimFE3hhl1Y+hKXbywdzcAF42bQG3VwLw8jgaHty1OI+IxoLerFt8B/ANwTW8P62Ws1/7UKaV7gXsBWlpa7GEtDSIrN+zocfvdc5oyikSSpHdmzf497G1v5+z6BsbVjKArJXa80cauI21Mq62joWZ41iGelp1vtLFk83r+dOZs6qqqSSQg2HPkCAAN1TVcP21mtkFqyHvb4jSldHVv4xFxHjATOH7UdCqwLCLmkztSOq3b3acCW/scraQBZcWGnT1uH2o7tTW/JEnlZE/7ER5q3cQvWjfSNKKWA0fbaevMdbX9YNM0rpo8MFf6PfjaRl49dJClmzdwuOMos0Y3MLNuDDuPtDGqsopPzJzN8EHWjVgDz2n/D0wprQBOLFSPiE1AS0ppd0QsBRZFxD3kGiLNAp7tY6ySBpDdB9rYtvv1HmMbt+3jnBl2/5Mkla/3jG9i2e6d7DjSxrY3DvfYdqSz8PVRy9lvdmxh/ev7AXjpQK5D78QRtZxRN4Zbzz6fhurhVFdUZBihlFOSM51TSquAxcBq4GHgNjv1SkPLsrW5xRJfv+VKmieO4cJZTVw422W9kqTyVjlsGJdNnHzKeABnja7v93j6ascbh/ll66Ye59c1VNdwzZRcH4iJI2otTFU2ilacppRmHL/Gaf72XSmlM1NKc1JKDxXrdSQNDM+v2cJZU8fypU9dznlnTqSqahhN4+qyDkuSpLc1s24MFSd16m0cPoI5Y8ZmFNHp2dd+hEXr19L9gjHDKyr49Flzqa208ZHKjwvLJZVEY30tn7zmfDo7u3jqxc20H+vgWEcnVZX+dVaSVN4aaoZzzZTpPNS6CcidazqvYVy2Qf0RUkqs2LebB17byOGOYyfG66qq+MxZ85gwYmSG0UmFWZxKKomFC1oAeGHddvYfynUCXPivS/nhHTdkGZYkSe/IeydMprl2NMe6OjmjbsyAuebp1rZDPNy6ifWvH+gxXjOsgjFVNYzyUjEqYxankkri7kW/4YKzJrFy45sdeysrhtF+tIOaanc9kqTyNiyC5lED53SUl/bv5dGtm9l+UhMngGumTOeS8ZPsxquy5/9QSUV3rKOTu370BO3HevZBW/Toi9x09blc1XJmRpFJkjS4pJT49fZWHt+6uUfTo+Mmj6zlA5Om9ntc0umwOJVUdKs37TqlMAW48cp5FqaSJBXRks3reX73joLbr2ya1o/RSH1TkkvJSBrannpxc6/jr7e193MkkiQNXiv27X7LwnR6bR3nDLAOwxraPHIqqage/O1abv/+o71ue/8FM/o3GEmSBrHaykrOrR9HW2cHrx46SGfKLewN4JLxTVw9uXnANHKSwOJUUhEdPNzOkidfYsakel5p3UM66eSXq1rOyCYwSZIGoTPq6jmjrh6A/UfbWb1vDx2pi9mjG5g0sjbb4KTTYHEqqWhG19bwg68soHXXQf78a//Dc2u2nNj2wYtmMm/mhAyjkyRp8KqvruG9EydnHYbUJxankorq6VWvceMd/83uA209xu++7VqXFkmSJKkgGyJJKqqv3vv4KYUpwLBhFqaSJEkqzOJUUtG8vHl3r516z5o6lllTx2UQkSRJkgYKi1NJRdPR2XXK2Ecum8MDd3+Kigp3N5IkSSrM3xYlFc3YMSNPGfuXz13N9En1/R+MJEmSBhSLU0lFM7ZuxCljvZ1/KkmSJJ3M4lRS0VRXVfAnV8ztMfbtxU/z5PJN7Nx3OKOoJEmSNBBYnEoqqjv/6qoet5c8uYZr/+4nrNm0M6OIJEmSNBBYnEoqqoefeaXX8ede2trPkUiSJGkgqcw6AEmDy3WXzOLLlY9wrKNn5947f/hrNm7Zx+hRNYypraFuZA0NdSM4Z8Z45jQ3MnJ4VUYRS5IkqRxESinrGE5oaWlJzz//fNZhSOqjzTsO8O3Fv+OHDy7jjfaOU7ZXV1Xw8Q/MZf7cyWzfc5iPXDaHlrOnZBCpJEkaiCLi9ymllqzjUHF55FRS0TWOGcnEhlr+8bNX8MzqLSx5ck2P7c/8YCFfuOdB7n9sBQBdKVmcSpIkDXGecyqp6EYOr+JvP3Epqzbu4rk1W1j40RY+fOksaodXMbq2hrWbd/PUi5uzDlOSJEllxCOnkkqiprqSe7/8Ue57YBlfv+9X7Hv9CJfMncrcmeO5+c6fZh2eJEmSyozFqaSSiQhu+chFfOKqc/nO/z3Dd3/6LE+t8IipJEmSTmVDJEn95o32Yyx65EWeWL6J9a17Wb5uO11difH1I2kaV0dE8JnrL+TWGy7OOlRJklTGbIg0OFmcSsrMq9v3s/jxlbzSuodjHV0suPxsrr90NtVVFVmHJkmSypjF6eDksl5JmZk+qZ4vfvKyrMOQJElSGbBbryRJkiQpcxankiRJkqTMWZxKkiRJkjJncSpJkiRJylyfi9OI+OuIWBsRqyLim93Gb4+Idflt1/b1dSRJkiRJg1efuvVGxJXAAuD8lFJ7REzIj88FbgLmAZOBxyJidkqps68BS5IkSZIGn74eOf088I2UUjtASmlnfnwBcH9KqT2ltBFYB8zv42tJkiRJkgapvhans4HLI+KZiHgiIi7Oj08BXut2v9b8mCRJkiRJp3jbZb0R8RgwqZdNd+Qf3wC8B7gYWBwRZwDRy/1TgedfCCwEaG5ufmdRS5IkSZIGlbctTlNKVxfaFhGfB36aUkrAsxHRBTSSO1I6rdtdpwJbCzz/vcC9AC0tLb0WsJIkSZKkwa2vy3qXAB8EiIjZQDWwG1gK3BQRNRExE5gFPNvH15IkSZIkDVJ96tYL3AfcFxErgaPAzfmjqKsiYjGwGugAbrNTryRJkiSpkD4Vpymlo8CnCmy7C7irL88vSZIkSRoaInegszxExC7g1azjGKIayS3JVvbMRXkwD+XDXJQPc1EezEP5MBfZmZ5SGp91ECqusipOlZ2IeD6l1JJ1HDIX5cI8lA9zUT7MRXkwD+XDXEjF1deGSJIkSZIk9ZnFqSRJkiQpcxanOu7erAPQCeaiPJiH8mEuyoe5KA/moXyYC6mIPOdUkiRJkpQ5j5xKkiRJkjJncTrERMSNEbEqIroioqXb+IyIeCMilue/vt9t20URsSIi1kXEv0dEZBP94FIoF/ltt+fne21EXNtt3FyUWET8U0Rs6fZeuL7btl7zotKIiOvyc70uIr6SdTxDTURsyu9vlkfE8/mxsRHxaES8kv/ekHWcg1FE3BcROyNiZbexgnPvvqk0CuTBzwiphCxOh56VwMeBJ3vZtj6ldEH+69Zu498DFgKz8l/XlT7MIaHXXETEXOAmYB65uf5uRFTkN5uL/vGtbu+FX8Db5kVFlp/b7wAfBuYCf5bPgfrXlfn3wfE/oH0FeDylNAt4PH9bxfcjTt2/9zr37ptK6kf0/jnrZ4RUIhanQ0xKaU1Kae07vX9ENAGjU0q/S7kTlH8CfKxU8Q0lb5GLBcD9KaX2lNJGYB0w31xkrte8ZBzTYDYfWJdS2pBSOgrcTy4HytYC4Mf5n3+M+6CSSCk9Cew9abjQ3LtvKpECeSjEPEhFYHGq7mZGxB8i4omIuDw/NgVo7Xaf1vyYSmcK8Fq328fn3Fz0ny9ExIv5JV3Hl84VyotKw/nOXgIeiYjfR8TC/NjElNI2gPz3CZlFN/QUmnvfK/3PzwipRCqzDkDFFxGPAZN62XRHSunnBR62DWhOKe2JiIuAJRExD+jtnEZbPL9Dp5mLQnNuLorkrfJCbun0neTm9k7g34C/xPnvb8539t6XUtoaEROARyPipawDUq98r/QvPyOkErI4HYRSSlefxmPagfb8z7+PiPXAbHJ/+Zva7a5Tga3FiHMoOJ1ckJvzad1uH59zc1Ek7zQvEfED4IH8zUJ5UWk43xlLKW3Nf98ZET8jt0RxR0Q0pZS25U812JlpkENLobn3vdKPUko7jv/sZ4RUfC7rFQARMf74ifsRcQa5Zjsb8kuHXo+I9+Q7w34aKHTET8WxFLgpImoiYia5XDxrLvpH/pe+424g17gKCuSlv+MbQp4DZkXEzIioJtdoZGnGMQ0ZEVEbEXXHfwauIfdeWArcnL/bzbgP6k+F5t59Uz/yM0IqLY+cDjERcQPwH8B44MGIWJ5SuhZ4P/DPEdEBdAK3ppSONwH4PLmOdSOAh/Jf6qNCuUgprYqIxcBqoAO4LaXUmX+YuSi9b0bEBeSWY20CPgfwNnlRkaWUOiLiC8AvgQrgvpTSqozDGkomAj/LX62qEliUUno4Ip4DFkfELcBm4MYMYxy0IuK/gCuAxohoBb4GfINe5t59U+kUyMMVfkZIpRO5pp+SJEmSJGXHZb2SJEmSpMxZnEqSJEmSMmdxKkmSJEnKnMWpJEmSJClzFqeSJEmSpMxZnEqSJEmSMmdxKkmSJEnKnMWpJEmSJClz/w+UkAblGGhDvQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1008x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(14,10), subplot_kw={'aspect':'equal'})\n",
    "worldmerge.plot(column='covid_mortality_rate (per 100000)', scheme='Quantiles', k=5, cmap='GnBu', legend=True, ax=ax);\n",
    "leg = ax.get_legend()\n",
    "leg.set_bbox_to_anchor((0., 0., 1.15, 1.0))\n",
    "#ax.set_xlim(150000, 160000)\n",
    "#ax.set_ylim(208000, 215000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a32469a",
   "metadata": {},
   "source": [
    "### 8.1 Spatial Autocorrelation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c862568f",
   "metadata": {},
   "source": [
    "Sometimes, we observe visually-clustered patterns, \n",
    "but often there are no discernible statistical patterns, \n",
    "thus requiring testing. \n",
    "Spatial autocorrelation pertains to the combination of two types of similarity - spatial and attribute similarity."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c75c10c9",
   "metadata": {},
   "source": [
    "#### 8.1.1 Spatial Similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4fd2283f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#queen contiguity for spatial weights is defined\n",
    "#w = Queen.from_dataframe(df, idVariable='name')\n",
    "#knn1 = lps.weights.KNN.from_dataframe(df)\n",
    "#queen = lps.weights.Queen.from_dataframe(df)\n",
    "\n",
    "#symm_knn = lps.weights.WSP((knn1.sparse + knn1.sparse.T)>0).to_W()\n",
    "\n",
    "#fully_connected = lps.weights.w_union(symm_knn, queen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "25bb2dae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>geometry</th>\n",
       "      <th>Country</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>HDI rank</th>\n",
       "      <th>Human Development Index 2021 (HDI)</th>\n",
       "      <th>Life expectancy at birth</th>\n",
       "      <th>Expected years of schooling</th>\n",
       "      <th>...</th>\n",
       "      <th>NewRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>Serious,Critical</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>Population</th>\n",
       "      <th>Continent</th>\n",
       "      <th>New Cases/1M pop</th>\n",
       "      <th>New Deaths/1M pop</th>\n",
       "      <th>Active Cases/1M pop</th>\n",
       "      <th>covid_mortality_rate (per 100000)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>FJI</td>\n",
       "      <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>-18.0000</td>\n",
       "      <td>175.0</td>\n",
       "      <td>99</td>\n",
       "      <td>0.730</td>\n",
       "      <td>67.1140</td>\n",
       "      <td>14.736790</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>669,911</td>\n",
       "      <td>909466</td>\n",
       "      <td>Australia/Oceania</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,118</td>\n",
       "      <td>97.089941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>-6.0000</td>\n",
       "      <td>35.0</td>\n",
       "      <td>160</td>\n",
       "      <td>0.549</td>\n",
       "      <td>66.2007</td>\n",
       "      <td>9.221490</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63298550</td>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>662</td>\n",
       "      <td>1.336524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Canada</td>\n",
       "      <td>CAN</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "      <td>Canada</td>\n",
       "      <td>60.0000</td>\n",
       "      <td>-95.0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.936</td>\n",
       "      <td>82.6565</td>\n",
       "      <td>16.396259</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32,425</td>\n",
       "      <td>99</td>\n",
       "      <td>66,343,123</td>\n",
       "      <td>38388419</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>845</td>\n",
       "      <td>135.772718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>USA</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -120.0000...</td>\n",
       "      <td>United States</td>\n",
       "      <td>38.0000</td>\n",
       "      <td>-97.0</td>\n",
       "      <td>21</td>\n",
       "      <td>0.921</td>\n",
       "      <td>77.1982</td>\n",
       "      <td>16.280979</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,062,241</td>\n",
       "      <td>1,895</td>\n",
       "      <td>1,174,878,661</td>\n",
       "      <td>334805269</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,173</td>\n",
       "      <td>345.176169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>UZB</td>\n",
       "      <td>POLYGON ((55.96819 41.30864, 55.92892 44.99586...</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>41.0000</td>\n",
       "      <td>64.0</td>\n",
       "      <td>101</td>\n",
       "      <td>0.727</td>\n",
       "      <td>70.8616</td>\n",
       "      <td>12.477140</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8,716</td>\n",
       "      <td>23</td>\n",
       "      <td>1,377,915</td>\n",
       "      <td>34382084</td>\n",
       "      <td>Asia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>254</td>\n",
       "      <td>4.761201</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>131</th>\n",
       "      <td>Bosnia and Herz.</td>\n",
       "      <td>BIH</td>\n",
       "      <td>POLYGON ((18.56000 42.65000, 17.67492 43.02856...</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>18.0</td>\n",
       "      <td>74</td>\n",
       "      <td>0.780</td>\n",
       "      <td>75.3003</td>\n",
       "      <td>13.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6,686</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,884,721</td>\n",
       "      <td>3249317</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,058</td>\n",
       "      <td>501.828538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Macedonia</td>\n",
       "      <td>MKD</td>\n",
       "      <td>POLYGON ((22.38053 42.32026, 22.88137 41.99930...</td>\n",
       "      <td>Macedonia</td>\n",
       "      <td>41.8333</td>\n",
       "      <td>22.0</td>\n",
       "      <td>78</td>\n",
       "      <td>0.770</td>\n",
       "      <td>73.8415</td>\n",
       "      <td>13.624432</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,226,216</td>\n",
       "      <td>2081304</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>364</td>\n",
       "      <td>464.420383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>SRB</td>\n",
       "      <td>POLYGON ((18.82982 45.90887, 18.82984 45.90888...</td>\n",
       "      <td>Serbia</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>21.0</td>\n",
       "      <td>63</td>\n",
       "      <td>0.802</td>\n",
       "      <td>74.1923</td>\n",
       "      <td>14.400090</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14,155</td>\n",
       "      <td>12</td>\n",
       "      <td>12,648,684</td>\n",
       "      <td>8653016</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,636</td>\n",
       "      <td>207.788822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>MNE</td>\n",
       "      <td>POLYGON ((20.07070 42.58863, 19.80161 42.50009...</td>\n",
       "      <td>Montenegro</td>\n",
       "      <td>42.0000</td>\n",
       "      <td>19.0</td>\n",
       "      <td>49</td>\n",
       "      <td>0.832</td>\n",
       "      <td>76.3426</td>\n",
       "      <td>15.081610</td>\n",
       "      <td>...</td>\n",
       "      <td>+60</td>\n",
       "      <td>679</td>\n",
       "      <td>6</td>\n",
       "      <td>2,736,615</td>\n",
       "      <td>627950</td>\n",
       "      <td>Europe</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,081</td>\n",
       "      <td>448.443347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>Trinidad and Tobago</td>\n",
       "      <td>TTO</td>\n",
       "      <td>POLYGON ((-61.68000 10.76000, -61.10500 10.890...</td>\n",
       "      <td>Trinidad and Tobago</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>-61.0</td>\n",
       "      <td>57</td>\n",
       "      <td>0.810</td>\n",
       "      <td>72.9709</td>\n",
       "      <td>14.535453</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81</td>\n",
       "      <td>8</td>\n",
       "      <td>907,114</td>\n",
       "      <td>1406585</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58</td>\n",
       "      <td>310.823733</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136 rows × 45 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name Country Code  \\\n",
       "0                        Fiji          FJI   \n",
       "1                    Tanzania          TZA   \n",
       "2                      Canada          CAN   \n",
       "3    United States of America          USA   \n",
       "4                  Uzbekistan          UZB   \n",
       "..                        ...          ...   \n",
       "131          Bosnia and Herz.          BIH   \n",
       "132                 Macedonia          MKD   \n",
       "133                    Serbia          SRB   \n",
       "134                Montenegro          MNE   \n",
       "135       Trinidad and Tobago          TTO   \n",
       "\n",
       "                                              geometry  \\\n",
       "0    MULTIPOLYGON (((180.00000 -16.06713, 180.00000...   \n",
       "1    POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...   \n",
       "2    MULTIPOLYGON (((-122.84000 49.00000, -122.9742...   \n",
       "3    MULTIPOLYGON (((-122.84000 49.00000, -120.0000...   \n",
       "4    POLYGON ((55.96819 41.30864, 55.92892 44.99586...   \n",
       "..                                                 ...   \n",
       "131  POLYGON ((18.56000 42.65000, 17.67492 43.02856...   \n",
       "132  POLYGON ((22.38053 42.32026, 22.88137 41.99930...   \n",
       "133  POLYGON ((18.82982 45.90887, 18.82984 45.90888...   \n",
       "134  POLYGON ((20.07070 42.58863, 19.80161 42.50009...   \n",
       "135  POLYGON ((-61.68000 10.76000, -61.10500 10.890...   \n",
       "\n",
       "                    Country  Latitude  Longitude  HDI rank  \\\n",
       "0                      Fiji  -18.0000      175.0        99   \n",
       "1                  Tanzania   -6.0000       35.0       160   \n",
       "2                    Canada   60.0000      -95.0        15   \n",
       "3             United States   38.0000      -97.0        21   \n",
       "4                Uzbekistan   41.0000       64.0       101   \n",
       "..                      ...       ...        ...       ...   \n",
       "131  Bosnia and Herzegovina   44.0000       18.0        74   \n",
       "132               Macedonia   41.8333       22.0        78   \n",
       "133                  Serbia   44.0000       21.0        63   \n",
       "134              Montenegro   42.0000       19.0        49   \n",
       "135     Trinidad and Tobago   11.0000      -61.0        57   \n",
       "\n",
       "     Human Development Index 2021 (HDI)  Life expectancy at birth  \\\n",
       "0                                 0.730                   67.1140   \n",
       "1                                 0.549                   66.2007   \n",
       "2                                 0.936                   82.6565   \n",
       "3                                 0.921                   77.1982   \n",
       "4                                 0.727                   70.8616   \n",
       "..                                  ...                       ...   \n",
       "131                               0.780                   75.3003   \n",
       "132                               0.770                   73.8415   \n",
       "133                               0.802                   74.1923   \n",
       "134                               0.832                   76.3426   \n",
       "135                               0.810                   72.9709   \n",
       "\n",
       "     Expected years of schooling  ...  NewRecovered  ActiveCases  \\\n",
       "0                      14.736790  ...           NaN        1,017   \n",
       "1                       9.221490  ...           NaN          NaN   \n",
       "2                      16.396259  ...           NaN       32,425   \n",
       "3                      16.280979  ...           NaN    1,062,241   \n",
       "4                      12.477140  ...           NaN        8,716   \n",
       "..                           ...  ...           ...          ...   \n",
       "131                    13.800000  ...           NaN        6,686   \n",
       "132                    13.624432  ...           NaN          758   \n",
       "133                    14.400090  ...           NaN       14,155   \n",
       "134                    15.081610  ...           +60          679   \n",
       "135                    14.535453  ...           NaN           81   \n",
       "\n",
       "     Serious,Critical     TotalTests  Population          Continent  \\\n",
       "0                 NaN        669,911      909466  Australia/Oceania   \n",
       "1                   7            NaN    63298550             Africa   \n",
       "2                  99     66,343,123    38388419      North America   \n",
       "3               1,895  1,174,878,661   334805269      North America   \n",
       "4                  23      1,377,915    34382084               Asia   \n",
       "..                ...            ...         ...                ...   \n",
       "131               NaN      1,884,721     3249317             Europe   \n",
       "132               NaN      2,226,216     2081304             Europe   \n",
       "133                12     12,648,684     8653016             Europe   \n",
       "134                 6      2,736,615      627950             Europe   \n",
       "135                 8        907,114     1406585      North America   \n",
       "\n",
       "     New Cases/1M pop New Deaths/1M pop Active Cases/1M pop  \\\n",
       "0                 NaN               NaN               1,118   \n",
       "1                 NaN               NaN                 662   \n",
       "2                 NaN               NaN                 845   \n",
       "3                 NaN               NaN               3,173   \n",
       "4                 NaN               NaN                 254   \n",
       "..                ...               ...                 ...   \n",
       "131               NaN               NaN               2,058   \n",
       "132               NaN               NaN                 364   \n",
       "133               NaN               NaN               1,636   \n",
       "134              97.0               NaN               1,081   \n",
       "135               NaN               NaN                  58   \n",
       "\n",
       "     covid_mortality_rate (per 100000)  \n",
       "0                            97.089941  \n",
       "1                             1.336524  \n",
       "2                           135.772718  \n",
       "3                           345.176169  \n",
       "4                             4.761201  \n",
       "..                                 ...  \n",
       "131                         501.828538  \n",
       "132                         464.420383  \n",
       "133                         207.788822  \n",
       "134                         448.443347  \n",
       "135                         310.823733  \n",
       "\n",
       "[136 rows x 45 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "worldmerge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "51790378",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('WARNING: ', 'FJI', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'BHS', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'JAM', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'MDG', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'GMB', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'VUT', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'KOR', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'SLB', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'NZL', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'AUS', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'LKA', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'ISL', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'PHL', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'JPN', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'CYP', ' is an island (no neighbors)')\n",
      "('WARNING: ', 'TTO', ' is an island (no neighbors)')\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\andre\\anaconda3\\lib\\site-packages\\libpysal\\weights\\weights.py:172: UserWarning: The weights matrix is not fully connected: \n",
      " There are 21 disconnected components.\n",
      " There are 16 islands with ids: AUS, BHS, CYP, FJI, GMB, ISL, JAM, JPN, KOR, LKA, MDG, NZL, PHL, SLB, TTO, VUT.\n",
      "  warnings.warn(message)\n"
     ]
    }
   ],
   "source": [
    "df = worldmerge\n",
    "wq =  lps.weights.Queen.from_dataframe(df, idVariable = 'Country Code')\n",
    "wq.transform = 'r'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ddaf8729",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('WARNING: ', 0, ' is an island (no neighbors)')\n",
      "('WARNING: ', 13, ' is an island (no neighbors)')\n",
      "('WARNING: ', 32, ' is an island (no neighbors)')\n",
      "('WARNING: ', 56, ' is an island (no neighbors)')\n",
      "('WARNING: ', 58, ' is an island (no neighbors)')\n",
      "('WARNING: ', 65, ' is an island (no neighbors)')\n",
      "('WARNING: ', 70, ' is an island (no neighbors)')\n",
      "('WARNING: ', 104, ' is an island (no neighbors)')\n",
      "('WARNING: ', 105, ' is an island (no neighbors)')\n",
      "('WARNING: ', 106, ' is an island (no neighbors)')\n",
      "('WARNING: ', 107, ' is an island (no neighbors)')\n",
      "('WARNING: ', 112, ' is an island (no neighbors)')\n",
      "('WARNING: ', 115, ' is an island (no neighbors)')\n",
      "('WARNING: ', 122, ' is an island (no neighbors)')\n",
      "('WARNING: ', 125, ' is an island (no neighbors)')\n",
      "('WARNING: ', 135, ' is an island (no neighbors)')\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\andre\\anaconda3\\lib\\site-packages\\libpysal\\weights\\weights.py:172: UserWarning: The weights matrix is not fully connected: \n",
      " There are 21 disconnected components.\n",
      " There are 16 islands with ids: 0, 13, 32, 56, 58, 65, 70, 104, 105, 106, 107, 112, 115, 122, 125, 135.\n",
      "  warnings.warn(message)\n"
     ]
    }
   ],
   "source": [
    "df = worldmerge\n",
    "wq =  lps.weights.Queen.from_dataframe(df)\n",
    "wq.transform = 'r'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6b06dc43",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>geometry</th>\n",
       "      <th>Country</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>HDI rank</th>\n",
       "      <th>Human Development Index 2021 (HDI)</th>\n",
       "      <th>Life expectancy at birth</th>\n",
       "      <th>Expected years of schooling</th>\n",
       "      <th>...</th>\n",
       "      <th>NewRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>Serious,Critical</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>Population</th>\n",
       "      <th>Continent</th>\n",
       "      <th>New Cases/1M pop</th>\n",
       "      <th>New Deaths/1M pop</th>\n",
       "      <th>Active Cases/1M pop</th>\n",
       "      <th>covid_mortality_rate (per 100000)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fiji</td>\n",
       "      <td>FJI</td>\n",
       "      <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>-18.0000</td>\n",
       "      <td>175.0</td>\n",
       "      <td>99</td>\n",
       "      <td>0.730</td>\n",
       "      <td>67.1140</td>\n",
       "      <td>14.736790</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>669,911</td>\n",
       "      <td>909466</td>\n",
       "      <td>Australia/Oceania</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,118</td>\n",
       "      <td>97.089941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>-6.0000</td>\n",
       "      <td>35.0</td>\n",
       "      <td>160</td>\n",
       "      <td>0.549</td>\n",
       "      <td>66.2007</td>\n",
       "      <td>9.221490</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63298550</td>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>662</td>\n",
       "      <td>1.336524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Canada</td>\n",
       "      <td>CAN</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "      <td>Canada</td>\n",
       "      <td>60.0000</td>\n",
       "      <td>-95.0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.936</td>\n",
       "      <td>82.6565</td>\n",
       "      <td>16.396259</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32,425</td>\n",
       "      <td>99</td>\n",
       "      <td>66,343,123</td>\n",
       "      <td>38388419</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>845</td>\n",
       "      <td>135.772718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>USA</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -120.0000...</td>\n",
       "      <td>United States</td>\n",
       "      <td>38.0000</td>\n",
       "      <td>-97.0</td>\n",
       "      <td>21</td>\n",
       "      <td>0.921</td>\n",
       "      <td>77.1982</td>\n",
       "      <td>16.280979</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,062,241</td>\n",
       "      <td>1,895</td>\n",
       "      <td>1,174,878,661</td>\n",
       "      <td>334805269</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,173</td>\n",
       "      <td>345.176169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>UZB</td>\n",
       "      <td>POLYGON ((55.96819 41.30864, 55.92892 44.99586...</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>41.0000</td>\n",
       "      <td>64.0</td>\n",
       "      <td>101</td>\n",
       "      <td>0.727</td>\n",
       "      <td>70.8616</td>\n",
       "      <td>12.477140</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8,716</td>\n",
       "      <td>23</td>\n",
       "      <td>1,377,915</td>\n",
       "      <td>34382084</td>\n",
       "      <td>Asia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>254</td>\n",
       "      <td>4.761201</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>131</th>\n",
       "      <td>Bosnia and Herz.</td>\n",
       "      <td>BIH</td>\n",
       "      <td>POLYGON ((18.56000 42.65000, 17.67492 43.02856...</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>18.0</td>\n",
       "      <td>74</td>\n",
       "      <td>0.780</td>\n",
       "      <td>75.3003</td>\n",
       "      <td>13.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6,686</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,884,721</td>\n",
       "      <td>3249317</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,058</td>\n",
       "      <td>501.828538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Macedonia</td>\n",
       "      <td>MKD</td>\n",
       "      <td>POLYGON ((22.38053 42.32026, 22.88137 41.99930...</td>\n",
       "      <td>Macedonia</td>\n",
       "      <td>41.8333</td>\n",
       "      <td>22.0</td>\n",
       "      <td>78</td>\n",
       "      <td>0.770</td>\n",
       "      <td>73.8415</td>\n",
       "      <td>13.624432</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,226,216</td>\n",
       "      <td>2081304</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>364</td>\n",
       "      <td>464.420383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>SRB</td>\n",
       "      <td>POLYGON ((18.82982 45.90887, 18.82984 45.90888...</td>\n",
       "      <td>Serbia</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>21.0</td>\n",
       "      <td>63</td>\n",
       "      <td>0.802</td>\n",
       "      <td>74.1923</td>\n",
       "      <td>14.400090</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14,155</td>\n",
       "      <td>12</td>\n",
       "      <td>12,648,684</td>\n",
       "      <td>8653016</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,636</td>\n",
       "      <td>207.788822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>MNE</td>\n",
       "      <td>POLYGON ((20.07070 42.58863, 19.80161 42.50009...</td>\n",
       "      <td>Montenegro</td>\n",
       "      <td>42.0000</td>\n",
       "      <td>19.0</td>\n",
       "      <td>49</td>\n",
       "      <td>0.832</td>\n",
       "      <td>76.3426</td>\n",
       "      <td>15.081610</td>\n",
       "      <td>...</td>\n",
       "      <td>+60</td>\n",
       "      <td>679</td>\n",
       "      <td>6</td>\n",
       "      <td>2,736,615</td>\n",
       "      <td>627950</td>\n",
       "      <td>Europe</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,081</td>\n",
       "      <td>448.443347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>Trinidad and Tobago</td>\n",
       "      <td>TTO</td>\n",
       "      <td>POLYGON ((-61.68000 10.76000, -61.10500 10.890...</td>\n",
       "      <td>Trinidad and Tobago</td>\n",
       "      <td>11.0000</td>\n",
       "      <td>-61.0</td>\n",
       "      <td>57</td>\n",
       "      <td>0.810</td>\n",
       "      <td>72.9709</td>\n",
       "      <td>14.535453</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81</td>\n",
       "      <td>8</td>\n",
       "      <td>907,114</td>\n",
       "      <td>1406585</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58</td>\n",
       "      <td>310.823733</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136 rows × 45 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name Country Code  \\\n",
       "0                        Fiji          FJI   \n",
       "1                    Tanzania          TZA   \n",
       "2                      Canada          CAN   \n",
       "3    United States of America          USA   \n",
       "4                  Uzbekistan          UZB   \n",
       "..                        ...          ...   \n",
       "131          Bosnia and Herz.          BIH   \n",
       "132                 Macedonia          MKD   \n",
       "133                    Serbia          SRB   \n",
       "134                Montenegro          MNE   \n",
       "135       Trinidad and Tobago          TTO   \n",
       "\n",
       "                                              geometry  \\\n",
       "0    MULTIPOLYGON (((180.00000 -16.06713, 180.00000...   \n",
       "1    POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...   \n",
       "2    MULTIPOLYGON (((-122.84000 49.00000, -122.9742...   \n",
       "3    MULTIPOLYGON (((-122.84000 49.00000, -120.0000...   \n",
       "4    POLYGON ((55.96819 41.30864, 55.92892 44.99586...   \n",
       "..                                                 ...   \n",
       "131  POLYGON ((18.56000 42.65000, 17.67492 43.02856...   \n",
       "132  POLYGON ((22.38053 42.32026, 22.88137 41.99930...   \n",
       "133  POLYGON ((18.82982 45.90887, 18.82984 45.90888...   \n",
       "134  POLYGON ((20.07070 42.58863, 19.80161 42.50009...   \n",
       "135  POLYGON ((-61.68000 10.76000, -61.10500 10.890...   \n",
       "\n",
       "                    Country  Latitude  Longitude  HDI rank  \\\n",
       "0                      Fiji  -18.0000      175.0        99   \n",
       "1                  Tanzania   -6.0000       35.0       160   \n",
       "2                    Canada   60.0000      -95.0        15   \n",
       "3             United States   38.0000      -97.0        21   \n",
       "4                Uzbekistan   41.0000       64.0       101   \n",
       "..                      ...       ...        ...       ...   \n",
       "131  Bosnia and Herzegovina   44.0000       18.0        74   \n",
       "132               Macedonia   41.8333       22.0        78   \n",
       "133                  Serbia   44.0000       21.0        63   \n",
       "134              Montenegro   42.0000       19.0        49   \n",
       "135     Trinidad and Tobago   11.0000      -61.0        57   \n",
       "\n",
       "     Human Development Index 2021 (HDI)  Life expectancy at birth  \\\n",
       "0                                 0.730                   67.1140   \n",
       "1                                 0.549                   66.2007   \n",
       "2                                 0.936                   82.6565   \n",
       "3                                 0.921                   77.1982   \n",
       "4                                 0.727                   70.8616   \n",
       "..                                  ...                       ...   \n",
       "131                               0.780                   75.3003   \n",
       "132                               0.770                   73.8415   \n",
       "133                               0.802                   74.1923   \n",
       "134                               0.832                   76.3426   \n",
       "135                               0.810                   72.9709   \n",
       "\n",
       "     Expected years of schooling  ...  NewRecovered  ActiveCases  \\\n",
       "0                      14.736790  ...           NaN        1,017   \n",
       "1                       9.221490  ...           NaN          NaN   \n",
       "2                      16.396259  ...           NaN       32,425   \n",
       "3                      16.280979  ...           NaN    1,062,241   \n",
       "4                      12.477140  ...           NaN        8,716   \n",
       "..                           ...  ...           ...          ...   \n",
       "131                    13.800000  ...           NaN        6,686   \n",
       "132                    13.624432  ...           NaN          758   \n",
       "133                    14.400090  ...           NaN       14,155   \n",
       "134                    15.081610  ...           +60          679   \n",
       "135                    14.535453  ...           NaN           81   \n",
       "\n",
       "     Serious,Critical     TotalTests  Population          Continent  \\\n",
       "0                 NaN        669,911      909466  Australia/Oceania   \n",
       "1                   7            NaN    63298550             Africa   \n",
       "2                  99     66,343,123    38388419      North America   \n",
       "3               1,895  1,174,878,661   334805269      North America   \n",
       "4                  23      1,377,915    34382084               Asia   \n",
       "..                ...            ...         ...                ...   \n",
       "131               NaN      1,884,721     3249317             Europe   \n",
       "132               NaN      2,226,216     2081304             Europe   \n",
       "133                12     12,648,684     8653016             Europe   \n",
       "134                 6      2,736,615      627950             Europe   \n",
       "135                 8        907,114     1406585      North America   \n",
       "\n",
       "     New Cases/1M pop New Deaths/1M pop Active Cases/1M pop  \\\n",
       "0                 NaN               NaN               1,118   \n",
       "1                 NaN               NaN                 662   \n",
       "2                 NaN               NaN                 845   \n",
       "3                 NaN               NaN               3,173   \n",
       "4                 NaN               NaN                 254   \n",
       "..                ...               ...                 ...   \n",
       "131               NaN               NaN               2,058   \n",
       "132               NaN               NaN                 364   \n",
       "133               NaN               NaN               1,636   \n",
       "134              97.0               NaN               1,081   \n",
       "135               NaN               NaN                  58   \n",
       "\n",
       "     covid_mortality_rate (per 100000)  \n",
       "0                            97.089941  \n",
       "1                             1.336524  \n",
       "2                           135.772718  \n",
       "3                           345.176169  \n",
       "4                             4.761201  \n",
       "..                                 ...  \n",
       "131                         501.828538  \n",
       "132                         464.420383  \n",
       "133                         207.788822  \n",
       "134                         448.443347  \n",
       "135                         310.823733  \n",
       "\n",
       "[136 rows x 45 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "worldmerge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3a61b2a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "worldmerge.drop(worldmerge.index[[0, 13, 32, 56, 58, 65, 70, 104, 105, 106, 107, 112, 115, 122, 125, 135]], axis = 0, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a3496268",
   "metadata": {},
   "outputs": [],
   "source": [
    "worldmerge.reset_index(drop=True, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3c0c2c97",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\andre\\anaconda3\\lib\\site-packages\\libpysal\\weights\\weights.py:172: UserWarning: The weights matrix is not fully connected: \n",
      " There are 5 disconnected components.\n",
      "  warnings.warn(message)\n"
     ]
    }
   ],
   "source": [
    "df = worldmerge\n",
    "wq =  lps.weights.Queen.from_dataframe(df, idVariable = 'Country Code')\n",
    "wq.transform = 'r'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be6a017b",
   "metadata": {},
   "source": [
    "#### 8.1.2 Attribute Similarity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "748558ac",
   "metadata": {},
   "source": [
    "The spatial weight between neighborhoods i and j indicates if the two are neighbors. \n",
    "The spatial lag is a derived variable that is a measure of attribute of similarity that pairs up with the concept of spatial similarity.\n",
    "The spatial lag for neighborhood i is as showed in the equation below."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3a57f44",
   "metadata": {},
   "source": [
    "$$ \n",
    "ylag_{i} = \\sum_{j}w_{i,j}y_{j}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "3e6da446",
   "metadata": {},
   "outputs": [],
   "source": [
    "#so, the spatial lag = average of the neighbors "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "31d00cfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "y = df['covid_mortality_rate (per 100000)']\n",
    "ylag = lps.weights.lag_spatial(wq, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "808b2a99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2.25286833e+02, 1.23920121e+02, 7.45408855e+01, 1.42982756e+02,\n",
       "       1.62136834e+02, 1.36176447e+01, 8.81524279e+01, 2.43354440e+02,\n",
       "       1.34643779e+02, 1.01093603e+02, 2.51060944e+02, 1.69935045e+02,\n",
       "       8.39536133e+01, 8.77366644e+01, 1.59716995e+02, 1.39017614e+02,\n",
       "       5.08116635e+02, 1.04899269e+02, 3.55452728e+02, 1.39874746e+02,\n",
       "       7.49491105e+00, 3.39943514e+01, 1.89598480e+02, 2.08046866e+02,\n",
       "       6.35293136e+01, 2.90751821e+02, 1.28981133e+02, 1.20652953e+02,\n",
       "       2.29415993e+02, 6.42590941e+01, 1.53144378e+02, 3.70415593e+01,\n",
       "       3.00993914e-01, 2.49053548e+02, 1.44565399e+02, 8.36007671e+01,\n",
       "       1.76377825e+02, 1.07161236e+02, 8.09399829e+01, 1.68772153e+02,\n",
       "       2.43743990e+02, 1.99838367e+02, 3.77608473e+01, 1.51297527e+02,\n",
       "       1.51689606e+00, 1.85470986e+02, 7.69355672e+01, 1.64723051e+02,\n",
       "       1.48597309e+02, 2.50305590e+02, 1.55284573e+02, 1.58891373e+02,\n",
       "       4.76622089e+02, 1.72131585e+02, 3.00623979e+00, 2.23171222e+02,\n",
       "       1.72071635e+02, 7.15729613e+01, 1.75353031e+02, 1.51894092e+02,\n",
       "       2.56881233e+01, 5.97493426e+01, 3.10726394e+02, 2.51843430e+02,\n",
       "       2.31214649e+01, 4.64420383e+02, 1.36976705e+02, 1.86043758e+02,\n",
       "       9.06033421e+01, 3.46003616e+00, 1.40475701e+02, 1.57944342e+01,\n",
       "       1.51625762e+02, 1.13624246e+02, 2.10671379e+02, 1.41629885e+02,\n",
       "       2.86880968e+02, 1.18292635e+02, 2.91554777e+02, 3.31546718e+02,\n",
       "       1.21421393e+02, 1.58539484e+02, 1.21009022e+02, 1.86043758e+02,\n",
       "       1.04899269e+02, 3.13774159e+02, 7.49905292e+01, 1.99354639e+02,\n",
       "       1.31729702e+02, 1.62651393e+02, 9.57914135e+01, 1.19615115e+00,\n",
       "       2.35761980e+02, 5.50243508e+01, 3.13774159e+02, 1.33824420e+02,\n",
       "       7.25101798e+01, 4.25685944e+01, 2.60888573e+02, 9.51006093e+01,\n",
       "       1.51689606e+00, 6.71663162e+00, 1.54002271e+02, 1.19416532e+02,\n",
       "       1.04902831e+02, 5.08661361e+01, 4.51297945e+00, 1.87297214e+02,\n",
       "       3.46003616e+00, 7.85609545e+01, 1.07190051e+02, 1.50117287e+01,\n",
       "       1.41982377e+02, 2.17990993e+02, 1.81237925e+02, 4.84287532e+01,\n",
       "       5.41599810e+01, 3.51267957e+02, 2.91133975e+02, 4.10300875e+02])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ylag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "73873870",
   "metadata": {},
   "outputs": [],
   "source": [
    "import mapclassify as mc\n",
    "ylagq5 = mc.Quantiles(ylag, k=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "57146c9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "df.assign(cl=ylagq5.yb).plot(column='cl', categorical=True, \\\n",
    "        k=5, cmap='GnBu', linewidth=0.1, ax=ax, \\\n",
    "        edgecolor='white', legend=True)\n",
    "ax.set_axis_off()\n",
    "leg = ax.get_legend()\n",
    "leg.set_bbox_to_anchor((0., 0., 1.1, 1.0))\n",
    "plt.title('Spatial Lag Covid Mortality Rate (100000) (Quintiles)')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "a9c0141b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#the quintile map for the spatial lag makes us think there's similarity in space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8dffdb4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1198.08x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['lag_coviddeathrate'] = ylag\n",
    "f,ax = plt.subplots(1,2,figsize=(4.16*4,4))\n",
    "df.plot(column='covid_mortality_rate (per 100000)', ax=ax[0], edgecolor='k',\n",
    "        scheme='quantiles',  k=5, cmap='GnBu')\n",
    "ax[0].axis(df.total_bounds[np.asarray([0,2,1,3])])\n",
    "ax[0].set_title('Covid Mortality Rate')\n",
    "df.plot(column='lag_coviddeathrate', ax=ax[1], edgecolor='k',\n",
    "        scheme='quantiles', cmap='GnBu', k=5)\n",
    "ax[1].axis(df.total_bounds[np.asarray([0,2,1,3])])\n",
    "ax[1].set_title('Spatial Lag Covid Mortality Rate')\n",
    "ax[0].axis('off')\n",
    "ax[1].axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7f3fd448",
   "metadata": {},
   "outputs": [],
   "source": [
    "#on the left are the values of covid mortality rate and neighbors\n",
    "#on the right are weighted average of covid death rates' neighbors, which is the spatial lag"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc2f5db3",
   "metadata": {},
   "source": [
    "### 8.2 Global Spatial Autocorrelation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "da39ab53",
   "metadata": {},
   "outputs": [],
   "source": [
    "#converting the attribute to a binary case to see it easily "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "781fd751",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "116.67927528763295"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "79c63c48",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "60"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yb = y > y.median()\n",
    "sum(yb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "b1746204",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "60"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(y < y.median())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "f2216be7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#there are 60 neighborhoods with covid death rate above the median and 60 (120-60=60) below the median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "7c4c50b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        1.336524\n",
       "1      135.772718\n",
       "2      345.176169\n",
       "3        4.761201\n",
       "4        7.210373\n",
       "          ...    \n",
       "115     10.793749\n",
       "116    501.828538\n",
       "117    464.420383\n",
       "118    207.788822\n",
       "119    448.443347\n",
       "Name: covid_mortality_rate (per 100000), Length: 120, dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "d3b0c730",
   "metadata": {},
   "outputs": [],
   "source": [
    "yb = y > y.median()\n",
    "labels = ['0 Low', '1 High']\n",
    "yb = [labels[i] for i in 1*yb] \n",
    "df['yb'] = yb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "4a8768b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,10), subplot_kw={'aspect':'equal'})\n",
    "df.plot(column='yb', cmap='binary', edgecolor='grey', legend=True, ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0aaf366",
   "metadata": {},
   "source": [
    "#### 8.2.1 Join Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d0f357d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# a join is a way to formalize a test for spatial autocorrelation in a binary attribute, it also exists for each \n",
    "#neighbor pair of observations, and the joins are reflected in the binary spatial weights object wq\n",
    "#each unit can take either Black (B) or White (W), there are three type of joins, BB (black black), WW (white white), BW (black white or white black)\n",
    "#finding out what is the number of BB joins if the 65 black polygons were randomly assingned on the map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "5ceca9de",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\andre\\anaconda3\\lib\\site-packages\\libpysal\\weights\\weights.py:172: UserWarning: The weights matrix is not fully connected: \n",
      " There are 5 disconnected components.\n",
      "  warnings.warn(message)\n"
     ]
    }
   ],
   "source": [
    "import esda \n",
    "yb = 1 * (y > y.median()) # convert back to binary\n",
    "wq =  lps.weights.Queen.from_dataframe(df)\n",
    "wq.transform = 'b'\n",
    "np.random.seed(12345)\n",
    "jc = esda.join_counts.Join_Counts(yb, wq)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "08b5bf4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "92.0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jc.bb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "cd6513a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "75.0"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jc.ww"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "8d317926",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "31.0"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jc.bw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "87e14128",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "198.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jc.bb + jc.ww + jc.bw #all possibilites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "7a272e04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "198.0"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wq.s0 / 2 #unique number of joins in the spatial weights object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "5d5fad15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "92.0"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jc.bb #there are 92 BB joins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "292eb871",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48.752752752752755"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jc.mean_bb #The average number of BB joins from the synthetic realizations is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "3baa6924",
   "metadata": {},
   "outputs": [],
   "source": [
    "#less than the observed count, but is it enought to reject the null of complete spatial randomness(CSR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "38218992",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.001"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jc.p_sim_bb #the pseudo p-value summarizes that the observed value is extremely high, it'a bellow 1%, rejecting null of CSR, \n",
    "#meaning there's autocorrelation in covid death rate"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9b8adb4",
   "metadata": {},
   "source": [
    "#### 8.2.2 Continous Case"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "1dfa8bae",
   "metadata": {},
   "outputs": [],
   "source": [
    "#transforming the weights to be row-standardized from the current binary state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "b939f0f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "wq.transform = 'r'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "878d7149",
   "metadata": {},
   "outputs": [],
   "source": [
    "y = df['covid_mortality_rate (per 100000)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "eb753316",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Moran's I is a test for global autocorrelation for a continuous attribute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "ec908301",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6748124515232901"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.seed(12345)\n",
    "mi = esda.moran.Moran(y, wq)\n",
    "mi.I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "834e4abc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, \"Moran's I\")"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sbn\n",
    "sbn.kdeplot(mi.sim, shade=True)\n",
    "plt.vlines(mi.I, 0, 1, color='r')\n",
    "plt.vlines(mi.EI, 0,1)\n",
    "plt.xlabel('Moran\\'s I')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "a5cd4229",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.001"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mi.p_sim"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8047a464",
   "metadata": {},
   "source": [
    "### 8.3 Local Autocorrelation: Hot Spots, Cold Spots, and Spatial Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "67cf6be5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#local Moran statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "74840738",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(12345)\n",
    "import esda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "9fc420c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "wq.transform = 'r'\n",
    "lag_coviddeathrate = lps.weights.lag_spatial(wq, df['covid_mortality_rate (per 100000)'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "a795bd70",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename({'covid_mortality_rate (per 100000)':'coviddeathrate'}, axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "2cabd26e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>geometry</th>\n",
       "      <th>Country</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>HDI rank</th>\n",
       "      <th>Human Development Index 2021 (HDI)</th>\n",
       "      <th>Life expectancy at birth</th>\n",
       "      <th>Expected years of schooling</th>\n",
       "      <th>...</th>\n",
       "      <th>Serious,Critical</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>Population</th>\n",
       "      <th>Continent</th>\n",
       "      <th>New Cases/1M pop</th>\n",
       "      <th>New Deaths/1M pop</th>\n",
       "      <th>Active Cases/1M pop</th>\n",
       "      <th>coviddeathrate</th>\n",
       "      <th>lag_coviddeathrate</th>\n",
       "      <th>yb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>160</td>\n",
       "      <td>0.549</td>\n",
       "      <td>66.2007</td>\n",
       "      <td>9.221490</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63298550</td>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>662</td>\n",
       "      <td>1.336524</td>\n",
       "      <td>225.286833</td>\n",
       "      <td>0 Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Canada</td>\n",
       "      <td>CAN</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "      <td>Canada</td>\n",
       "      <td>60.0</td>\n",
       "      <td>-95.0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.936</td>\n",
       "      <td>82.6565</td>\n",
       "      <td>16.396259</td>\n",
       "      <td>...</td>\n",
       "      <td>99</td>\n",
       "      <td>66,343,123</td>\n",
       "      <td>38388419</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>845</td>\n",
       "      <td>135.772718</td>\n",
       "      <td>123.920121</td>\n",
       "      <td>1 High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>USA</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -120.0000...</td>\n",
       "      <td>United States</td>\n",
       "      <td>38.0</td>\n",
       "      <td>-97.0</td>\n",
       "      <td>21</td>\n",
       "      <td>0.921</td>\n",
       "      <td>77.1982</td>\n",
       "      <td>16.280979</td>\n",
       "      <td>...</td>\n",
       "      <td>1,895</td>\n",
       "      <td>1,174,878,661</td>\n",
       "      <td>334805269</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,173</td>\n",
       "      <td>345.176169</td>\n",
       "      <td>74.540885</td>\n",
       "      <td>1 High</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name Country Code  \\\n",
       "0                  Tanzania          TZA   \n",
       "1                    Canada          CAN   \n",
       "2  United States of America          USA   \n",
       "\n",
       "                                            geometry        Country  Latitude  \\\n",
       "0  POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...       Tanzania      -6.0   \n",
       "1  MULTIPOLYGON (((-122.84000 49.00000, -122.9742...         Canada      60.0   \n",
       "2  MULTIPOLYGON (((-122.84000 49.00000, -120.0000...  United States      38.0   \n",
       "\n",
       "   Longitude  HDI rank  Human Development Index 2021 (HDI)  \\\n",
       "0       35.0       160                               0.549   \n",
       "1      -95.0        15                               0.936   \n",
       "2      -97.0        21                               0.921   \n",
       "\n",
       "   Life expectancy at birth  Expected years of schooling  ...  \\\n",
       "0                   66.2007                     9.221490  ...   \n",
       "1                   82.6565                    16.396259  ...   \n",
       "2                   77.1982                    16.280979  ...   \n",
       "\n",
       "   Serious,Critical     TotalTests  Population      Continent  \\\n",
       "0                 7            NaN    63298550         Africa   \n",
       "1                99     66,343,123    38388419  North America   \n",
       "2             1,895  1,174,878,661   334805269  North America   \n",
       "\n",
       "   New Cases/1M pop  New Deaths/1M pop  Active Cases/1M pop coviddeathrate  \\\n",
       "0               NaN                NaN                  662       1.336524   \n",
       "1               NaN                NaN                  845     135.772718   \n",
       "2               NaN                NaN                3,173     345.176169   \n",
       "\n",
       "  lag_coviddeathrate      yb  \n",
       "0         225.286833   0 Low  \n",
       "1         123.920121  1 High  \n",
       "2          74.540885  1 High  \n",
       "\n",
       "[3 rows x 47 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "94598e01",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df = df[df.coviddeathrate != 0]\n",
    "#df = df[df.lag_coviddeathrate !=0]\n",
    "df = df.dropna(axis=0, subset=['coviddeathrate','lag_coviddeathrate'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "a2fe777e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.33652351e+00],\n",
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       "       [3.45176169e+02],\n",
       "       [4.76120063e+00],\n",
       "       [7.21037252e+00],\n",
       "       [5.76922584e+01],\n",
       "       [3.35045957e+02],\n",
       "       [1.01182561e+01],\n",
       "       [1.09453770e+01],\n",
       "       [7.36283530e+00],\n",
       "       [3.96513503e+01],\n",
       "       [2.72567757e+02],\n",
       "       [1.68863605e+02],\n",
       "       [3.32306997e+01],\n",
       "       [2.53532968e+02],\n",
       "       [2.17990993e+02],\n",
       "       [3.25304997e+02],\n",
       "       [1.86572516e+02],\n",
       "       [6.52641143e+02],\n",
       "       [2.76976024e+02],\n",
       "       [1.93660214e+02],\n",
       "       [1.79628794e+02],\n",
       "       [3.31902465e+00],\n",
       "       [1.08704936e+02],\n",
       "       [6.45763175e+01],\n",
       "       [1.08630853e+02],\n",
       "       [1.66913317e+02],\n",
       "       [1.63466806e+02],\n",
       "       [2.35242472e+02],\n",
       "       [1.98842170e+02],\n",
       "       [3.70415593e+01],\n",
       "       [1.14740439e+02],\n",
       "       [1.55284573e+02],\n",
       "       [3.46003616e+00],\n",
       "       [2.03387161e+01],\n",
       "       [1.27495888e+00],\n",
       "       [1.19615115e+00],\n",
       "       [1.45561459e+00],\n",
       "       [7.05084505e+00],\n",
       "       [4.51297945e+00],\n",
       "       [3.00623979e+00],\n",
       "       [3.36802544e+00],\n",
       "       [8.52974774e+00],\n",
       "       [1.51689606e+00],\n",
       "       [1.79162513e+00],\n",
       "       [2.25248661e+00],\n",
       "       [6.65769201e+00],\n",
       "       [2.08420710e+01],\n",
       "       [6.77557123e+00],\n",
       "       [5.51854590e+00],\n",
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       "       [6.01802942e+01],\n",
       "       [8.69272368e+01],\n",
       "       [1.77998967e+01],\n",
       "       [4.84287532e+01],\n",
       "       [1.01323041e+01],\n",
       "       [4.36427030e+01],\n",
       "       [6.45041352e+01],\n",
       "       [3.77437798e+01],\n",
       "       [1.75393151e+01],\n",
       "       [2.66517417e+00],\n",
       "       [3.97676379e+01],\n",
       "       [1.33557603e+01],\n",
       "       [4.44542142e+01],\n",
       "       [1.68815637e+02],\n",
       "       [2.94047778e+02],\n",
       "       [2.33125233e+02],\n",
       "       [7.54600967e+01],\n",
       "       [2.58283212e+02],\n",
       "       [3.16353154e+02],\n",
       "       [2.44377508e+02],\n",
       "       [5.08116635e+02],\n",
       "       [3.01158361e+02],\n",
       "       [3.56869342e+02],\n",
       "       [3.62248601e+02],\n",
       "       [3.40213875e+02],\n",
       "       [2.24750550e+02],\n",
       "       [2.04055391e+02],\n",
       "       [5.59112538e+02],\n",
       "       [3.53962246e+02],\n",
       "       [1.18618111e+02],\n",
       "       [1.25663992e+02],\n",
       "       [4.45127542e+02],\n",
       "       [1.64720742e+02],\n",
       "       [1.76377825e+02],\n",
       "       [2.91893971e+02],\n",
       "       [1.33585514e+02],\n",
       "       [2.60419286e+02],\n",
       "       [2.57765864e+02],\n",
       "       [1.74554833e+02],\n",
       "       [3.63969906e-01],\n",
       "       [3.13774159e+02],\n",
       "       [1.44080069e+02],\n",
       "       [3.05696932e+02],\n",
       "       [9.89203613e+01],\n",
       "       [4.28826493e+02],\n",
       "       [1.11455109e+02],\n",
       "       [5.05128740e+01],\n",
       "       [3.41669097e+02],\n",
       "       [1.62989472e+02],\n",
       "       [3.86707942e+02],\n",
       "       [3.97539896e+02],\n",
       "       [2.72412095e+02],\n",
       "       [2.68713194e+01],\n",
       "       [4.31422055e+01],\n",
       "       [2.31855378e+01],\n",
       "       [6.26838083e+00],\n",
       "       [7.49491105e+00],\n",
       "       [1.07937494e+01],\n",
       "       [5.01828538e+02],\n",
       "       [4.64420383e+02],\n",
       "       [2.07788822e+02],\n",
       "       [4.48443347e+02]])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['coviddeathrate'].values.reshape(-1,1) #when plotting the graph below there was an error expected x and y to have same length\n",
    "#that's why the need to reshape, but this would be 2d, it has to be 1d, many errors where found when doing the plotting below\n",
    "#what worked was reshaping x and y to 1d with values.reshape(-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "a6d8b40f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.33652351e+00, 1.35772718e+02, 3.45176169e+02, 4.76120063e+00,\n",
       "       7.21037252e+00, 5.76922584e+01, 3.35045957e+02, 1.01182561e+01,\n",
       "       1.09453770e+01, 7.36283530e+00, 3.96513503e+01, 2.72567757e+02,\n",
       "       1.68863605e+02, 3.32306997e+01, 2.53532968e+02, 2.17990993e+02,\n",
       "       3.25304997e+02, 1.86572516e+02, 6.52641143e+02, 2.76976024e+02,\n",
       "       1.93660214e+02, 1.79628794e+02, 3.31902465e+00, 1.08704936e+02,\n",
       "       6.45763175e+01, 1.08630853e+02, 1.66913317e+02, 1.63466806e+02,\n",
       "       2.35242472e+02, 1.98842170e+02, 3.70415593e+01, 1.14740439e+02,\n",
       "       1.55284573e+02, 3.46003616e+00, 2.03387161e+01, 1.27495888e+00,\n",
       "       1.19615115e+00, 1.45561459e+00, 7.05084505e+00, 4.51297945e+00,\n",
       "       3.00623979e+00, 3.36802544e+00, 8.52974774e+00, 1.51689606e+00,\n",
       "       1.79162513e+00, 2.25248661e+00, 6.65769201e+00, 2.08420710e+01,\n",
       "       6.77557123e+00, 5.51854590e+00, 3.00993914e-01, 1.33004504e+02,\n",
       "       1.62651393e+02, 1.01093603e+02, 2.43743990e+02, 1.51730486e+01,\n",
       "       1.37095230e+02, 2.31214649e+01, 6.01802942e+01, 8.69272368e+01,\n",
       "       1.77998967e+01, 4.84287532e+01, 1.01323041e+01, 4.36427030e+01,\n",
       "       6.45041352e+01, 3.77437798e+01, 1.75393151e+01, 2.66517417e+00,\n",
       "       3.97676379e+01, 1.33557603e+01, 4.44542142e+01, 1.68815637e+02,\n",
       "       2.94047778e+02, 2.33125233e+02, 7.54600967e+01, 2.58283212e+02,\n",
       "       3.16353154e+02, 2.44377508e+02, 5.08116635e+02, 3.01158361e+02,\n",
       "       3.56869342e+02, 3.62248601e+02, 3.40213875e+02, 2.24750550e+02,\n",
       "       2.04055391e+02, 5.59112538e+02, 3.53962246e+02, 1.18618111e+02,\n",
       "       1.25663992e+02, 4.45127542e+02, 1.64720742e+02, 1.76377825e+02,\n",
       "       2.91893971e+02, 1.33585514e+02, 2.60419286e+02, 2.57765864e+02,\n",
       "       1.74554833e+02, 3.63969906e-01, 3.13774159e+02, 1.44080069e+02,\n",
       "       3.05696932e+02, 9.89203613e+01, 4.28826493e+02, 1.11455109e+02,\n",
       "       5.05128740e+01, 3.41669097e+02, 1.62989472e+02, 3.86707942e+02,\n",
       "       3.97539896e+02, 2.72412095e+02, 2.68713194e+01, 4.31422055e+01,\n",
       "       2.31855378e+01, 6.26838083e+00, 7.49491105e+00, 1.07937494e+01,\n",
       "       5.01828538e+02, 4.64420383e+02, 2.07788822e+02, 4.48443347e+02])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['coviddeathrate'].values.reshape(-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "763db180",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        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>name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>geometry</th>\n",
       "      <th>Country</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>HDI rank</th>\n",
       "      <th>Human Development Index 2021 (HDI)</th>\n",
       "      <th>Life expectancy at birth</th>\n",
       "      <th>Expected years of schooling</th>\n",
       "      <th>...</th>\n",
       "      <th>Serious,Critical</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>Population</th>\n",
       "      <th>Continent</th>\n",
       "      <th>New Cases/1M pop</th>\n",
       "      <th>New Deaths/1M pop</th>\n",
       "      <th>Active Cases/1M pop</th>\n",
       "      <th>coviddeathrate</th>\n",
       "      <th>lag_coviddeathrate</th>\n",
       "      <th>yb</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>-6.0000</td>\n",
       "      <td>35.0</td>\n",
       "      <td>160</td>\n",
       "      <td>0.549</td>\n",
       "      <td>66.2007</td>\n",
       "      <td>9.221490</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63298550</td>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>662</td>\n",
       "      <td>1.336524</td>\n",
       "      <td>225.286833</td>\n",
       "      <td>0 Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Canada</td>\n",
       "      <td>CAN</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "      <td>Canada</td>\n",
       "      <td>60.0000</td>\n",
       "      <td>-95.0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.936</td>\n",
       "      <td>82.6565</td>\n",
       "      <td>16.396259</td>\n",
       "      <td>...</td>\n",
       "      <td>99</td>\n",
       "      <td>66,343,123</td>\n",
       "      <td>38388419</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>845</td>\n",
       "      <td>135.772718</td>\n",
       "      <td>123.920121</td>\n",
       "      <td>1 High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>USA</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -120.0000...</td>\n",
       "      <td>United States</td>\n",
       "      <td>38.0000</td>\n",
       "      <td>-97.0</td>\n",
       "      <td>21</td>\n",
       "      <td>0.921</td>\n",
       "      <td>77.1982</td>\n",
       "      <td>16.280979</td>\n",
       "      <td>...</td>\n",
       "      <td>1,895</td>\n",
       "      <td>1,174,878,661</td>\n",
       "      <td>334805269</td>\n",
       "      <td>North America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3,173</td>\n",
       "      <td>345.176169</td>\n",
       "      <td>74.540885</td>\n",
       "      <td>1 High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>UZB</td>\n",
       "      <td>POLYGON ((55.96819 41.30864, 55.92892 44.99586...</td>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>41.0000</td>\n",
       "      <td>64.0</td>\n",
       "      <td>101</td>\n",
       "      <td>0.727</td>\n",
       "      <td>70.8616</td>\n",
       "      <td>12.477140</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>1,377,915</td>\n",
       "      <td>34382084</td>\n",
       "      <td>Asia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>254</td>\n",
       "      <td>4.761201</td>\n",
       "      <td>142.982756</td>\n",
       "      <td>0 Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Papua New Guinea</td>\n",
       "      <td>PNG</td>\n",
       "      <td>MULTIPOLYGON (((141.00021 -2.60015, 142.73525 ...</td>\n",
       "      <td>Papua New Guinea</td>\n",
       "      <td>-6.0000</td>\n",
       "      <td>147.0</td>\n",
       "      <td>156</td>\n",
       "      <td>0.558</td>\n",
       "      <td>65.3506</td>\n",
       "      <td>10.360771</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>249,149</td>\n",
       "      <td>9292169</td>\n",
       "      <td>Australia/Oceania</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>235</td>\n",
       "      <td>7.210373</td>\n",
       "      <td>162.136834</td>\n",
       "      <td>0 Low</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>115</th>\n",
       "      <td>Rwanda</td>\n",
       "      <td>RWA</td>\n",
       "      <td>POLYGON ((30.41910 -1.13466, 30.81613 -1.69891...</td>\n",
       "      <td>Rwanda</td>\n",
       "      <td>-2.0000</td>\n",
       "      <td>30.0</td>\n",
       "      <td>165</td>\n",
       "      <td>0.534</td>\n",
       "      <td>66.0722</td>\n",
       "      <td>11.230970</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6,021,981</td>\n",
       "      <td>13600464</td>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>10.793749</td>\n",
       "      <td>48.428753</td>\n",
       "      <td>0 Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>Bosnia and Herz.</td>\n",
       "      <td>BIH</td>\n",
       "      <td>POLYGON ((18.56000 42.65000, 17.67492 43.02856...</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>18.0</td>\n",
       "      <td>74</td>\n",
       "      <td>0.780</td>\n",
       "      <td>75.3003</td>\n",
       "      <td>13.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,884,721</td>\n",
       "      <td>3249317</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,058</td>\n",
       "      <td>501.828538</td>\n",
       "      <td>54.159981</td>\n",
       "      <td>1 High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>Macedonia</td>\n",
       "      <td>MKD</td>\n",
       "      <td>POLYGON ((22.38053 42.32026, 22.88137 41.99930...</td>\n",
       "      <td>Macedonia</td>\n",
       "      <td>41.8333</td>\n",
       "      <td>22.0</td>\n",
       "      <td>78</td>\n",
       "      <td>0.770</td>\n",
       "      <td>73.8415</td>\n",
       "      <td>13.624432</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2,226,216</td>\n",
       "      <td>2081304</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>364</td>\n",
       "      <td>464.420383</td>\n",
       "      <td>351.267957</td>\n",
       "      <td>1 High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>SRB</td>\n",
       "      <td>POLYGON ((18.82982 45.90887, 18.82984 45.90888...</td>\n",
       "      <td>Serbia</td>\n",
       "      <td>44.0000</td>\n",
       "      <td>21.0</td>\n",
       "      <td>63</td>\n",
       "      <td>0.802</td>\n",
       "      <td>74.1923</td>\n",
       "      <td>14.400090</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>12,648,684</td>\n",
       "      <td>8653016</td>\n",
       "      <td>Europe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,636</td>\n",
       "      <td>207.788822</td>\n",
       "      <td>291.133975</td>\n",
       "      <td>1 High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>MNE</td>\n",
       "      <td>POLYGON ((20.07070 42.58863, 19.80161 42.50009...</td>\n",
       "      <td>Montenegro</td>\n",
       "      <td>42.0000</td>\n",
       "      <td>19.0</td>\n",
       "      <td>49</td>\n",
       "      <td>0.832</td>\n",
       "      <td>76.3426</td>\n",
       "      <td>15.081610</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>2,736,615</td>\n",
       "      <td>627950</td>\n",
       "      <td>Europe</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,081</td>\n",
       "      <td>448.443347</td>\n",
       "      <td>410.300875</td>\n",
       "      <td>1 High</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>120 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name Country Code  \\\n",
       "0                    Tanzania          TZA   \n",
       "1                      Canada          CAN   \n",
       "2    United States of America          USA   \n",
       "3                  Uzbekistan          UZB   \n",
       "4            Papua New Guinea          PNG   \n",
       "..                        ...          ...   \n",
       "115                    Rwanda          RWA   \n",
       "116          Bosnia and Herz.          BIH   \n",
       "117                 Macedonia          MKD   \n",
       "118                    Serbia          SRB   \n",
       "119                Montenegro          MNE   \n",
       "\n",
       "                                              geometry  \\\n",
       "0    POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...   \n",
       "1    MULTIPOLYGON (((-122.84000 49.00000, -122.9742...   \n",
       "2    MULTIPOLYGON (((-122.84000 49.00000, -120.0000...   \n",
       "3    POLYGON ((55.96819 41.30864, 55.92892 44.99586...   \n",
       "4    MULTIPOLYGON (((141.00021 -2.60015, 142.73525 ...   \n",
       "..                                                 ...   \n",
       "115  POLYGON ((30.41910 -1.13466, 30.81613 -1.69891...   \n",
       "116  POLYGON ((18.56000 42.65000, 17.67492 43.02856...   \n",
       "117  POLYGON ((22.38053 42.32026, 22.88137 41.99930...   \n",
       "118  POLYGON ((18.82982 45.90887, 18.82984 45.90888...   \n",
       "119  POLYGON ((20.07070 42.58863, 19.80161 42.50009...   \n",
       "\n",
       "                    Country  Latitude  Longitude  HDI rank  \\\n",
       "0                  Tanzania   -6.0000       35.0       160   \n",
       "1                    Canada   60.0000      -95.0        15   \n",
       "2             United States   38.0000      -97.0        21   \n",
       "3                Uzbekistan   41.0000       64.0       101   \n",
       "4          Papua New Guinea   -6.0000      147.0       156   \n",
       "..                      ...       ...        ...       ...   \n",
       "115                  Rwanda   -2.0000       30.0       165   \n",
       "116  Bosnia and Herzegovina   44.0000       18.0        74   \n",
       "117               Macedonia   41.8333       22.0        78   \n",
       "118                  Serbia   44.0000       21.0        63   \n",
       "119              Montenegro   42.0000       19.0        49   \n",
       "\n",
       "     Human Development Index 2021 (HDI)  Life expectancy at birth  \\\n",
       "0                                 0.549                   66.2007   \n",
       "1                                 0.936                   82.6565   \n",
       "2                                 0.921                   77.1982   \n",
       "3                                 0.727                   70.8616   \n",
       "4                                 0.558                   65.3506   \n",
       "..                                  ...                       ...   \n",
       "115                               0.534                   66.0722   \n",
       "116                               0.780                   75.3003   \n",
       "117                               0.770                   73.8415   \n",
       "118                               0.802                   74.1923   \n",
       "119                               0.832                   76.3426   \n",
       "\n",
       "     Expected years of schooling  ...  Serious,Critical     TotalTests  \\\n",
       "0                       9.221490  ...                 7            NaN   \n",
       "1                      16.396259  ...                99     66,343,123   \n",
       "2                      16.280979  ...             1,895  1,174,878,661   \n",
       "3                      12.477140  ...                23      1,377,915   \n",
       "4                      10.360771  ...                 7        249,149   \n",
       "..                           ...  ...               ...            ...   \n",
       "115                    11.230970  ...               NaN      6,021,981   \n",
       "116                    13.800000  ...               NaN      1,884,721   \n",
       "117                    13.624432  ...               NaN      2,226,216   \n",
       "118                    14.400090  ...                12     12,648,684   \n",
       "119                    15.081610  ...                 6      2,736,615   \n",
       "\n",
       "     Population          Continent  New Cases/1M pop  New Deaths/1M pop  \\\n",
       "0      63298550             Africa               NaN                NaN   \n",
       "1      38388419      North America               NaN                NaN   \n",
       "2     334805269      North America               NaN                NaN   \n",
       "3      34382084               Asia               NaN                NaN   \n",
       "4       9292169  Australia/Oceania               NaN                NaN   \n",
       "..          ...                ...               ...                ...   \n",
       "115    13600464             Africa               NaN                NaN   \n",
       "116     3249317             Europe               NaN                NaN   \n",
       "117     2081304             Europe               NaN                NaN   \n",
       "118     8653016             Europe               NaN                NaN   \n",
       "119      627950             Europe              97.0                NaN   \n",
       "\n",
       "     Active Cases/1M pop coviddeathrate lag_coviddeathrate      yb  \n",
       "0                    662       1.336524         225.286833   0 Low  \n",
       "1                    845     135.772718         123.920121  1 High  \n",
       "2                  3,173     345.176169          74.540885  1 High  \n",
       "3                    254       4.761201         142.982756   0 Low  \n",
       "4                    235       7.210373         162.136834   0 Low  \n",
       "..                   ...            ...                ...     ...  \n",
       "115                    6      10.793749          48.428753   0 Low  \n",
       "116                2,058     501.828538          54.159981  1 High  \n",
       "117                  364     464.420383         351.267957  1 High  \n",
       "118                1,636     207.788822         291.133975  1 High  \n",
       "119                1,081     448.443347         410.300875  1 High  \n",
       "\n",
       "[120 rows x 47 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "27fb86e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "coviddeathrate = df['coviddeathrate'].values.reshape(-1)\n",
    "lag_coviddeathrate = df['lag_coviddeathrate'].values.reshape(-1)\n",
    "b, a = np.polyfit(coviddeathrate, lag_coviddeathrate, 1)\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "\n",
    "plt.plot(coviddeathrate, lag_coviddeathrate, '.', color='firebrick')\n",
    "\n",
    " # dashed vert at mean of the price\n",
    "plt.vlines(coviddeathrate.mean(), lag_coviddeathrate.min(), lag_coviddeathrate.max(), linestyle='--')\n",
    " # dashed horizontal at mean of lagged price \n",
    "plt.hlines(lag_coviddeathrate.mean(), coviddeathrate.min(), coviddeathrate.max(), linestyle='--')\n",
    "\n",
    "# red line of best fit using global I as slope\n",
    "plt.plot(coviddeathrate, a + b*coviddeathrate, 'r')\n",
    "plt.title('Moran Scatterplot')\n",
    "plt.ylabel('Spatial Lag of Covid Mortality Rate')\n",
    "plt.xlabel('Covid Mortality Rate')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "20cc3fd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#instead of a single I statistic, there's an array of local Ii statistics, stored in the .Is attribute, and p-value from the simulation are in p_sim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "72a3c54c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#there might be spatial autocorrelation according to the graph,\n",
    "#the positive slope means that neighbors of locations with large values have high values, and neighbors of locations\n",
    "#with small values have small values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "0b5b5b34",
   "metadata": {},
   "outputs": [],
   "source": [
    "li = esda.moran.Moran_Local(y, wq)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "dad0f346",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 2, 1, 3, 3, 3, 1, 3, 3, 3, 3, 1, 4, 2, 1, 1, 1, 1, 1, 1, 1, 4,\n",
       "       3, 3, 3, 3, 1, 1, 1, 1, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n",
       "       3, 3, 3, 3, 3, 3, 3, 3, 4, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n",
       "       3, 3, 3, 3, 3, 4, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2,\n",
       "       2, 1, 1, 1, 1, 2, 1, 1, 1, 3, 1, 2, 1, 2, 1, 3, 3, 1, 1, 1, 1, 1,\n",
       "       3, 3, 3, 3, 3, 3, 1, 1, 1, 1])"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "li.q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "6de37da4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#using conditional random permutations (different distributions for each focal location)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "a60a9f47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "47"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(li.p_sim < 0.05).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "3a5b9482",
   "metadata": {},
   "outputs": [],
   "source": [
    "#distinguishing the specific type of local spatial association reflected in the four quadrants of the Moran Scatterplot above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "26cb5264",
   "metadata": {},
   "outputs": [],
   "source": [
    "sig = li.p_sim < 0.05\n",
    "hotspot = sig * li.q==1\n",
    "coldspot = sig * li.q==3\n",
    "doughnut = sig * li.q==2\n",
    "diamond = sig * li.q==4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "606d0961",
   "metadata": {},
   "outputs": [],
   "source": [
    "spots = ['n.sig.', 'hot spot']\n",
    "labels = [spots[i] for i in hotspot*1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "2186ac33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = df\n",
    "from matplotlib import colors\n",
    "hmap = colors.ListedColormap(['red', 'lightgrey'])\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "df.assign(cl=labels).plot(column='cl', categorical=True, \\\n",
    "        k=2, cmap=hmap, linewidth=0.1, ax=ax, \\\n",
    "        edgecolor='white', legend=True)\n",
    "ax.set_axis_off()\n",
    "leg = ax.get_legend()\n",
    "leg.set_bbox_to_anchor((0., 0., 1.1, .8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "1545367a",
   "metadata": {},
   "outputs": [],
   "source": [
    "spots = ['n.sig.', 'cold spot']\n",
    "labels = [spots[i] for i in coldspot*1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "9398cd45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = df\n",
    "from matplotlib import colors\n",
    "hmap = colors.ListedColormap(['blue', 'lightgrey'])\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "df.assign(cl=labels).plot(column='cl', categorical=True, \\\n",
    "        k=2, cmap=hmap, linewidth=0.1, ax=ax, \\\n",
    "        edgecolor='white', legend=True)\n",
    "ax.set_axis_off()\n",
    "leg = ax.get_legend()\n",
    "leg.set_bbox_to_anchor((0., 0., 1.1, .8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "a21f74fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "spots = ['n.sig.', 'doughnut']\n",
    "labels = [spots[i] for i in doughnut*1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "f29a7836",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = df\n",
    "from matplotlib import colors\n",
    "hmap = colors.ListedColormap(['lightblue', 'lightgrey'])\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "df.assign(cl=labels).plot(column='cl', categorical=True, \\\n",
    "        k=2, cmap=hmap, linewidth=0.1, ax=ax, \\\n",
    "        edgecolor='white', legend=True)\n",
    "ax.set_axis_off()\n",
    "leg = ax.get_legend()\n",
    "leg.set_bbox_to_anchor((0., 0., 1.1, .8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "ce6b4680",
   "metadata": {},
   "outputs": [],
   "source": [
    "spots = ['n.sig.', 'diamond']\n",
    "labels = [spots[i] for i in diamond*1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "d1ccb43c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = df\n",
    "from matplotlib import colors\n",
    "hmap = colors.ListedColormap(['pink', 'lightgrey'])\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "df.assign(cl=labels).plot(column='cl', categorical=True, \\\n",
    "        k=2, cmap=hmap, linewidth=0.1, ax=ax, \\\n",
    "        edgecolor='white', legend=True)\n",
    "ax.set_axis_off()\n",
    "leg = ax.get_legend()\n",
    "leg.set_bbox_to_anchor((0., 0., 1.1, .8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "bb011e2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 0, 0, 0, 0, 0, 1, 3, 3, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 3, 0, 3, 3, 3, 3, 3, 3, 3, 0, 0,\n",
       "       3, 3, 3, 3, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 0, 3,\n",
       "       0, 0, 0, 0, 3, 0, 0, 0, 2, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 2,\n",
       "       2, 1, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0,\n",
       "       0, 0, 0, 0, 3, 3, 1, 1, 1, 1])"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sig = 1 * (li.p_sim < 0.05)\n",
    "hotspot = 1 * (sig * li.q==1)\n",
    "coldspot = 3 * (sig * li.q==3)\n",
    "doughnut = 2 * (sig * li.q==2)\n",
    "diamond = 4 * (sig * li.q==4)\n",
    "spots = hotspot + coldspot + doughnut + diamond\n",
    "spots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "2c2bee0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "spot_labels = [ '0 ns', '1 hot spot', '2 doughnut', '3 cold spot', '4 diamond']\n",
    "labels = [spot_labels[i] for i in spots]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "176fd013",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import colors\n",
    "hmap = colors.ListedColormap([ 'lightgrey', 'red', 'lightblue', 'blue', 'pink'])\n",
    "f, ax = plt.subplots(1, figsize=(9, 9))\n",
    "df.assign(cl=labels).plot(column='cl', categorical=True, \\\n",
    "        k=2, cmap=hmap, linewidth=0.1, ax=ax, \\\n",
    "        edgecolor='white', legend=True)\n",
    "ax.set_axis_off()\n",
    "leg = ax.get_legend()\n",
    "leg.set_bbox_to_anchor((0., 0., 1.1, .8))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}