CO2_emission_by_country.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a385f811",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas\n",
    "import matplotlib.pyplot as plt\n",
    "data = pandas.read_csv(\"API_EN.ATM.CO2E.KT_DS2_en_csv_v2_5871652.csv\",  delimiter=',' , skiprows = 4) # make sure that the location is same as your directory\n",
    "df = data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2c3ce4c4",
   "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>Country Name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>Indicator Name</th>\n",
       "      <th>Indicator Code</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>...</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>Unnamed: 67</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>ABW</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Africa Eastern and Southern</td>\n",
       "      <td>AFE</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>591680.972</td>\n",
       "      <td>576265.992</td>\n",
       "      <td>580219.242</td>\n",
       "      <td>590905.482</td>\n",
       "      <td>598720.9575</td>\n",
       "      <td>610723.50</td>\n",
       "      <td>544952.503</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>9281.340</td>\n",
       "      <td>10057.590</td>\n",
       "      <td>9294.930</td>\n",
       "      <td>10022.780</td>\n",
       "      <td>10972.3800</td>\n",
       "      <td>11238.83</td>\n",
       "      <td>8709.470</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Africa Western and Central</td>\n",
       "      <td>AFW</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>196343.630</td>\n",
       "      <td>194363.640</td>\n",
       "      <td>201399.220</td>\n",
       "      <td>200550.900</td>\n",
       "      <td>210618.8900</td>\n",
       "      <td>222990.35</td>\n",
       "      <td>215915.610</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Angola</td>\n",
       "      <td>AGO</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>29610.500</td>\n",
       "      <td>31648.900</td>\n",
       "      <td>29520.700</td>\n",
       "      <td>25064.800</td>\n",
       "      <td>23637.4000</td>\n",
       "      <td>24382.90</td>\n",
       "      <td>19814.500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>261</th>\n",
       "      <td>Kosovo</td>\n",
       "      <td>XKX</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>YEM</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>27429.900</td>\n",
       "      <td>13552.200</td>\n",
       "      <td>10035.200</td>\n",
       "      <td>9682.200</td>\n",
       "      <td>11349.8000</td>\n",
       "      <td>11194.80</td>\n",
       "      <td>9960.100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>South Africa</td>\n",
       "      <td>ZAF</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>448298.100</td>\n",
       "      <td>425063.100</td>\n",
       "      <td>425682.900</td>\n",
       "      <td>435214.500</td>\n",
       "      <td>439644.6000</td>\n",
       "      <td>446626.00</td>\n",
       "      <td>393241.600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4686.000</td>\n",
       "      <td>4956.600</td>\n",
       "      <td>5315.300</td>\n",
       "      <td>6810.700</td>\n",
       "      <td>7857.2000</td>\n",
       "      <td>7615.70</td>\n",
       "      <td>7607.100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>CO2 emissions (kt)</td>\n",
       "      <td>EN.ATM.CO2E.KT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>12010.700</td>\n",
       "      <td>11988.700</td>\n",
       "      <td>10450.200</td>\n",
       "      <td>9781.000</td>\n",
       "      <td>11069.9000</td>\n",
       "      <td>10185.30</td>\n",
       "      <td>8312.500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>266 rows × 68 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Country Name Country Code      Indicator Name  \\\n",
       "0                          Aruba          ABW  CO2 emissions (kt)   \n",
       "1    Africa Eastern and Southern          AFE  CO2 emissions (kt)   \n",
       "2                    Afghanistan          AFG  CO2 emissions (kt)   \n",
       "3     Africa Western and Central          AFW  CO2 emissions (kt)   \n",
       "4                         Angola          AGO  CO2 emissions (kt)   \n",
       "..                           ...          ...                 ...   \n",
       "261                       Kosovo          XKX  CO2 emissions (kt)   \n",
       "262                  Yemen, Rep.          YEM  CO2 emissions (kt)   \n",
       "263                 South Africa          ZAF  CO2 emissions (kt)   \n",
       "264                       Zambia          ZMB  CO2 emissions (kt)   \n",
       "265                     Zimbabwe          ZWE  CO2 emissions (kt)   \n",
       "\n",
       "     Indicator Code  1960  1961  1962  1963  1964  1965  ...        2014  \\\n",
       "0    EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...         NaN   \n",
       "1    EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...  591680.972   \n",
       "2    EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...    9281.340   \n",
       "3    EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...  196343.630   \n",
       "4    EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...   29610.500   \n",
       "..              ...   ...   ...   ...   ...   ...   ...  ...         ...   \n",
       "261  EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...         NaN   \n",
       "262  EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...   27429.900   \n",
       "263  EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...  448298.100   \n",
       "264  EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...    4686.000   \n",
       "265  EN.ATM.CO2E.KT   NaN   NaN   NaN   NaN   NaN   NaN  ...   12010.700   \n",
       "\n",
       "           2015        2016        2017         2018       2019        2020  \\\n",
       "0           NaN         NaN         NaN          NaN        NaN         NaN   \n",
       "1    576265.992  580219.242  590905.482  598720.9575  610723.50  544952.503   \n",
       "2     10057.590    9294.930   10022.780   10972.3800   11238.83    8709.470   \n",
       "3    194363.640  201399.220  200550.900  210618.8900  222990.35  215915.610   \n",
       "4     31648.900   29520.700   25064.800   23637.4000   24382.90   19814.500   \n",
       "..          ...         ...         ...          ...        ...         ...   \n",
       "261         NaN         NaN         NaN          NaN        NaN         NaN   \n",
       "262   13552.200   10035.200    9682.200   11349.8000   11194.80    9960.100   \n",
       "263  425063.100  425682.900  435214.500  439644.6000  446626.00  393241.600   \n",
       "264    4956.600    5315.300    6810.700    7857.2000    7615.70    7607.100   \n",
       "265   11988.700   10450.200    9781.000   11069.9000   10185.30    8312.500   \n",
       "\n",
       "     2021  2022  Unnamed: 67  \n",
       "0     NaN   NaN          NaN  \n",
       "1     NaN   NaN          NaN  \n",
       "2     NaN   NaN          NaN  \n",
       "3     NaN   NaN          NaN  \n",
       "4     NaN   NaN          NaN  \n",
       "..    ...   ...          ...  \n",
       "261   NaN   NaN          NaN  \n",
       "262   NaN   NaN          NaN  \n",
       "263   NaN   NaN          NaN  \n",
       "264   NaN   NaN          NaN  \n",
       "265   NaN   NaN          NaN  \n",
       "\n",
       "[266 rows x 68 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "019d6b58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Aruba', 'Africa Eastern and Southern', 'Afghanistan',\n",
       "       'Africa Western and Central', 'Angola', 'Albania', 'Andorra',\n",
       "       'Arab World', 'United Arab Emirates', 'Argentina', 'Armenia',\n",
       "       'American Samoa', 'Antigua and Barbuda', 'Australia', 'Austria',\n",
       "       'Azerbaijan', 'Burundi', 'Belgium', 'Benin', 'Burkina Faso',\n",
       "       'Bangladesh', 'Bulgaria', 'Bahrain', 'Bahamas, The',\n",
       "       'Bosnia and Herzegovina', 'Belarus', 'Belize', 'Bermuda',\n",
       "       'Bolivia', 'Brazil', 'Barbados', 'Brunei Darussalam', 'Bhutan',\n",
       "       'Botswana', 'Central African Republic', 'Canada',\n",
       "       'Central Europe and the Baltics', 'Switzerland', 'Channel Islands',\n",
       "       'Chile', 'China', \"Cote d'Ivoire\", 'Cameroon', 'Congo, Dem. Rep.',\n",
       "       'Congo, Rep.', 'Colombia', 'Comoros', 'Cabo Verde', 'Costa Rica',\n",
       "       'Caribbean small states', 'Cuba', 'Curacao', 'Cayman Islands',\n",
       "       'Cyprus', 'Czechia', 'Germany', 'Djibouti', 'Dominica', 'Denmark',\n",
       "       'Dominican Republic', 'Algeria',\n",
       "       'East Asia & Pacific (excluding high income)',\n",
       "       'Early-demographic dividend', 'East Asia & Pacific',\n",
       "       'Europe & Central Asia (excluding high income)',\n",
       "       'Europe & Central Asia', 'Ecuador', 'Egypt, Arab Rep.',\n",
       "       'Euro area', 'Eritrea', 'Spain', 'Estonia', 'Ethiopia',\n",
       "       'European Union', 'Fragile and conflict affected situations',\n",
       "       'Finland', 'Fiji', 'France', 'Faroe Islands',\n",
       "       'Micronesia, Fed. Sts.', 'Gabon', 'United Kingdom', 'Georgia',\n",
       "       'Ghana', 'Gibraltar', 'Guinea', 'Gambia, The', 'Guinea-Bissau',\n",
       "       'Equatorial Guinea', 'Greece', 'Grenada', 'Greenland', 'Guatemala',\n",
       "       'Guam', 'Guyana', 'High income', 'Hong Kong SAR, China',\n",
       "       'Honduras', 'Heavily indebted poor countries (HIPC)', 'Croatia',\n",
       "       'Haiti', 'Hungary', 'IBRD only', 'IDA & IBRD total', 'IDA total',\n",
       "       'IDA blend', 'Indonesia', 'IDA only', 'Isle of Man', 'India',\n",
       "       'Not classified', 'Ireland', 'Iran, Islamic Rep.', 'Iraq',\n",
       "       'Iceland', 'Israel', 'Italy', 'Jamaica', 'Jordan', 'Japan',\n",
       "       'Kazakhstan', 'Kenya', 'Kyrgyz Republic', 'Cambodia', 'Kiribati',\n",
       "       'St. Kitts and Nevis', 'Korea, Rep.', 'Kuwait',\n",
       "       'Latin America & Caribbean (excluding high income)', 'Lao PDR',\n",
       "       'Lebanon', 'Liberia', 'Libya', 'St. Lucia',\n",
       "       'Latin America & Caribbean',\n",
       "       'Least developed countries: UN classification', 'Low income',\n",
       "       'Liechtenstein', 'Sri Lanka', 'Lower middle income',\n",
       "       'Low & middle income', 'Lesotho', 'Late-demographic dividend',\n",
       "       'Lithuania', 'Luxembourg', 'Latvia', 'Macao SAR, China',\n",
       "       'St. Martin (French part)', 'Morocco', 'Monaco', 'Moldova',\n",
       "       'Madagascar', 'Maldives', 'Middle East & North Africa', 'Mexico',\n",
       "       'Marshall Islands', 'Middle income', 'North Macedonia', 'Mali',\n",
       "       'Malta', 'Myanmar',\n",
       "       'Middle East & North Africa (excluding high income)', 'Montenegro',\n",
       "       'Mongolia', 'Northern Mariana Islands', 'Mozambique', 'Mauritania',\n",
       "       'Mauritius', 'Malawi', 'Malaysia', 'North America', 'Namibia',\n",
       "       'New Caledonia', 'Niger', 'Nigeria', 'Nicaragua', 'Netherlands',\n",
       "       'Norway', 'Nepal', 'Nauru', 'New Zealand', 'OECD members', 'Oman',\n",
       "       'Other small states', 'Pakistan', 'Panama', 'Peru', 'Philippines',\n",
       "       'Palau', 'Papua New Guinea', 'Poland', 'Pre-demographic dividend',\n",
       "       'Puerto Rico', \"Korea, Dem. People's Rep.\", 'Portugal', 'Paraguay',\n",
       "       'West Bank and Gaza', 'Pacific island small states',\n",
       "       'Post-demographic dividend', 'French Polynesia', 'Qatar',\n",
       "       'Romania', 'Russian Federation', 'Rwanda', 'South Asia',\n",
       "       'Saudi Arabia', 'Sudan', 'Senegal', 'Singapore', 'Solomon Islands',\n",
       "       'Sierra Leone', 'El Salvador', 'San Marino', 'Somalia', 'Serbia',\n",
       "       'Sub-Saharan Africa (excluding high income)', 'South Sudan',\n",
       "       'Sub-Saharan Africa', 'Small states', 'Sao Tome and Principe',\n",
       "       'Suriname', 'Slovak Republic', 'Slovenia', 'Sweden', 'Eswatini',\n",
       "       'Sint Maarten (Dutch part)', 'Seychelles', 'Syrian Arab Republic',\n",
       "       'Turks and Caicos Islands', 'Chad',\n",
       "       'East Asia & Pacific (IDA & IBRD countries)',\n",
       "       'Europe & Central Asia (IDA & IBRD countries)', 'Togo', 'Thailand',\n",
       "       'Tajikistan', 'Turkmenistan',\n",
       "       'Latin America & the Caribbean (IDA & IBRD countries)',\n",
       "       'Timor-Leste', 'Middle East & North Africa (IDA & IBRD countries)',\n",
       "       'Tonga', 'South Asia (IDA & IBRD)',\n",
       "       'Sub-Saharan Africa (IDA & IBRD countries)', 'Trinidad and Tobago',\n",
       "       'Tunisia', 'Turkiye', 'Tuvalu', 'Tanzania', 'Uganda', 'Ukraine',\n",
       "       'Upper middle income', 'Uruguay', 'United States', 'Uzbekistan',\n",
       "       'St. Vincent and the Grenadines', 'Venezuela, RB',\n",
       "       'British Virgin Islands', 'Virgin Islands (U.S.)', 'Vietnam',\n",
       "       'Vanuatu', 'World', 'Samoa', 'Kosovo', 'Yemen, Rep.',\n",
       "       'South Africa', 'Zambia', 'Zimbabwe'], dtype=object)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Country Name'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "58e5113b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter a country name: chi\n",
      "Country \"chi\" not found in the dataset.\n",
      "Enter a country name: China\n"
     ]
    }
   ],
   "source": [
    "# input the value of as given above\n",
    "while True : \n",
    "    country_name = input('Enter a country name: ')\n",
    "\n",
    "    if country_name in df['Country Name'].unique():\n",
    "        break\n",
    "\n",
    "    print(f'Country \"{country_name}\" not found in the dataset.')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "33ebbd2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# run this to plot the graph of above mention country\n",
    "country_data = df[df['Country Name'] == country_name]\n",
    "years = country_data.columns[4:-1] \n",
    "emissions = country_data.iloc[:, 4:-1].values.squeeze() \n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(years, emissions, marker='o', linestyle='-')\n",
    "plt.title(f'CO2 Emissions for {country_name}')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('CO2 Emissions (kt)')\n",
    "plt.grid(True)\n",
    "plt.xticks(rotation= 90)\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "284eefac",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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2bHbt2lX0bqq934kUEZH65ZprruGDDz5gw4YN9O3bt9yxV111FRaLhc8//7zMJuZz587FxcWF4cOHFzv+/fffc88993DjjTcW7RpWW/Tp04c+ffrwwgsvMH/+fO644w4WLFhQ1KDdzc2NkSNHMnLkSGw2Gw8++CDvv/8+zzzzDK1atSpxvcKm1vv37+eyyy4r9tj+/fuLHq+syuYoT0REBDt37sRmsxWbHbVv375iz6EqIiIi2L9/f6mPFR6/mOufr6yG4S1btmT58uX079+/3EJaYY7o6GhatGhRdPz06dNVnpUFBbO6WrZsWawQXFbWr7/+Gg8PD5YsWYK7u3vR8Tlz5pQYW9o1goOD8fX1xWq1csUVV1wwm7e3N7fddhu33XYbubm53Hjjjbzwwgs89dRTJYqEIiIitUW9XqZ3IQ899BAbNmxgwYIF7Ny5k1tuuYXhw4cTHR0N/G/Hox9//JHIyEiaN2/OPffco5lRIiJSZU888QTe3t7cc889nDp1qsTjBw8eZNasWQCEh4dz9913s3z5cmbPnl1i7Hvvvcdvv/3GhAkTaNq0adHx1atXc/vttzNo0CC++OKLEku/nNWZM2dKzLwpnBFWuFQvKSmp2ONms7lolklZ/YB69uxJSEgI7733XrExv/zyC3v37i3aHa0yqpKjPFdffTUnT57kq6++KjqWn5/PW2+9hY+PD4MHD670Nc+/9saNG9m6dWux42fPnuWLL76ga9euhIaGVvn65/P29i669vluvfVWrFZrqcvk8vPzi8ZfccUVuLq68tZbbxX7szBz5swK3f+PP/4odRfIw4cPs2fPnmJLNcvKarFYMJlMWK3WomNxcXGltnvw9vYu9fybbrqJr7/+utRZkKdPny76/7/+OXJzc6NDhw4YhlFm3zQREZHaoF7PjCrPkSNHmDNnDkeOHKFx48YATJkyhcWLFzNnzhxefPFFDh06xOHDh1m4cCFz587FarXy6KOPcvPNN/Pbb785+BmIiEht1LJlS+bPn89tt91G+/btGTt2LFFRUeTm5rJ+/XoWLlzIuHHjisb/5z//Yd++fTz44IMsXry4aAbUkiVL+P777xk8eDBvvPFG0fjDhw9z7bXXYjKZuPnmm1m4cGGx+3fu3LmoaFKeAwcOMG/evBLHGzVqxNChQ6v47Mv32Wef8e6773LDDTfQsmVL0tLS+PDDD/Hz8yvqd1X4ptBll11G06ZNOXz4MG+99RZdu3YtWtb4V66urrzyyivcfffdDB48mFGjRnHq1ClmzZpF8+bNefTRRyudtSo5ynPffffx/vvvM27cOLZu3Urz5s1ZtGgR69atY+bMmRVuel+af/zjHyxcuJBBgwZx//33065dO06cOMGnn35KfHx8qTN+qqpHjx4APPzww1x55ZVYLBZuv/12Bg8ezP33389LL73Ejh07GDZsGK6urkRHR7Nw4UJmzZrFzTffTHBwMFOmTOGll17immuu4eqrr2b79u388ssvBAUFXfD+y5YtY+rUqVx77bX06dMHHx8fDh06xCeffEJOTg7Tpk27YNYRI0YwY8YMhg8fzujRo0lISOCdd96hVatWRctiz7/G8uXLmTFjBo0bNyYyMpLevXvz8ssvs2LFCnr37s29995Lhw4dSE5OZtu2bSxfvrzojc1hw4YRGhpK//79adSoEXv37uXtt99mxIgRF/Wai4iIOJzjNvJzLoDx7bffFn1euJ2zt7d3sQ8XFxfj1ltvNQzDMO69914DMPbv31903tatWw3A2LdvX00/BRERqUMOHDhg3HvvvUbz5s0NNzc3w9fX1+jfv7/x1ltvGdnZ2cXG5uTkGP/5z3+MHj16GN7e3oaXl5fRvXt3Y+bMmUZubm6xsStWrDCAMj+mTp16wWzlnT948OCicYMHDy51W/qIiAhjxIgRpV530qRJRZ/PmTPHAIzY2FjDMAxj27ZtxqhRo4xmzZoZ7u7uRkhIiHHNNdcYW7ZsKTpn0aJFxrBhw4yQkBDDzc3NaNasmXH//fcb8fHxJb4GK1asKHb/r776yujWrZvh7u5uBAYGGnfccYdx7NixYmPuuusuw9vbu0T2qVOnGuf/WFWRHGUp6+tz6tQp4+677zaCgoIMNzc3o1OnTsacOXOKjYmNjTUA47XXXrvgfc537Ngx45577jGaNGliuLi4GIGBgcY111xjbNy4scTYsl7Xu+66y4iIiCiR5fyM+fn5xt/+9jcjODjYMJlMxl9/FP3ggw+MHj16GJ6enoavr6/RqVMn44knnjBOnDhRNMZqtRrTp083wsLCDE9PT+PSSy81du3aZURERBh33XVXuc/z0KFDxrPPPmv06dPHCAkJMVxcXIzg4GBjxIgRxm+//VZsbHlZP/74Y6N169aGu7u70a5dO2POnDkl/gwYhmHs27fPGDRokOHp6WkAxfKdOnXKmDRpkhEeHm64uroaoaGhxuWXX2588MEHRWPef/99Y9CgQUbDhg0Nd3d3o2XLlsbjjz9upKSklPs8RUREnJ3JMKrYabKOMZlMfPvtt1x//fUAfPXVV9xxxx3s3r27RJNOHx8fQkNDmTp1Ki+++GKxadJZWVl4eXmxdOnSantnWERERERERESkttIyvTJ069YNq9VKQkICAwcOLHVM//79yc/P5+DBg7Rs2RIoWLYA9mv0KSIiIiIiIiJSl9TrmVHp6enExMQABcWnGTNmMGTIEAIDA2nWrBljxoxh3bp1vPHGG3Tr1o3Tp0/z66+/0rlzZ0aMGIHNZuOSSy7Bx8eHmTNnYrPZmDRpEn5+fixdutTBz05ERERERERExPnU62LUypUrGTJkSInjd911F59++il5eXk8//zzzJ07l+PHjxMUFESfPn2YPn06nTp1AuDEiRP87W9/Y+nSpXh7e3PVVVfxxhtvEBgYWNNPR0RERERERETE6dXrYpSIiIiIiIiIiNQss6MDiIiIiIiIiIhI/aFilIiIiIiIiIiI1Jh6t5uezWbjxIkT+Pr6YjKZHB1HRERERERERKTWMwyDtLQ0GjdujNlc/tyneleMOnHiBOHh4Y6OISIiIiIiIiJS5xw9epSmTZuWO6beFaN8fX2Bgi+On59fla6Rl5fH0qVLGTZsGK6urvaMpxy1PIczZFAO5XD2DMqhHM6eQTmUw9kzKIdyOHsG5VAOZ8+gHNWTIzU1lfDw8KK6S3nqXTGqcGmen5/fRRWjvLy88PPzc/gfFuVwrhzOkEE5lMPZMyiHcjh7BuVQDmfPoBzK4ewZlEM5nD2DclRvjoq0RFIDcxERERERERERqTEqRomIiIiIiIiISI1RMUpERERERERERGqMilEiIiIiIiIiIlJjVIwSEREREREREZEao2KUiIiIiIiIiIjUGBWjRERERERERESkxqgYJSIiIiIiIiIiNcahxahp06ZhMpmKfbRr167cc2bOnEnbtm3x9PQkPDycRx99lOzs7BpKLCIiIiIiIiIiF8PF0QE6duzI8uXLiz53cSk70vz58/nHP/7BJ598Qr9+/Thw4ADjxo3DZDIxY8aMmogrIiIiIiIiIiIXweHFKBcXF0JDQys0dv369fTv35/Ro0cD0Lx5c0aNGsWmTZuqM6KIiIiIiIiIiNiJw4tR0dHRNG7cGA8PD/r27ctLL71Es2bNSh3br18/5s2bx+bNm+nVqxeHDh3i559/5s477yzz+jk5OeTk5BR9npqaCkBeXh55eXlVylx4XlXPtxflcL4czpBBOZTD2TMoh3I4ewblUA5nz6AcyuHsGZRDOZw9g3JUT47KnGsyDMOo8p0u0i+//EJ6ejpt27YlPj6e6dOnc/z4cXbt2oWvr2+p57z55ptMmTIFwzDIz8/ngQceYPbs2WXeY9q0aUyfPr3E8fnz5+Pl5WW35yIiIiIiIiIiUl9lZmYyevRoUlJS8PPzK3esQ4tRf3X27FkiIiKYMWMGEyZMKPH4ypUruf3223n++efp3bs3MTExTJ48mXvvvZdnnnmm1GuWNjMqPDycxMTEC35xypKXl8eyZcsYOnQorq6uVbqGPSiH8+VwhgzKoRzOnkE5lMPZMyiHcjh7BuVQDmfPoBzK4ewZlKN6cqSmphIUFFShYpTDl+mdLyAggDZt2hATE1Pq48888wx33nkn99xzDwCdOnUiIyOD++67j3/961+YzSU3B3R3d8fd3b3EcVdX14t+oe1xDXtQDufL4QwZlEM5nD2Do3NYbQbbYpPZmmii4bE0+rYKwWI2OSRLIb0uzpVBOZTD2TMoh3I4ewblUA5nz6Ac9s1RmfOcqhiVnp7OwYMHy+wBlZmZWaLgZLFYAHCiCV4iIuLkFu+KZ/oPe4hPyQYszI3eQpi/B1NHdmB4VJij44mIiIiI1GklpxLVoClTprBq1Sri4uJYv349N9xwAxaLhVGjRgEwduxYnnrqqaLxI0eOZPbs2SxYsIDY2FiWLVvGM888w8iRI4uKUiIiIuVZvCueifO2nStE/c/JlGwmztvG4l3xDkomIiIiIlI/OHRm1LFjxxg1ahRJSUkEBwczYMAANm7cSHBwMABHjhwpNhPq6aefxmQy8fTTT3P8+HGCg4MZOXIkL7zwgqOegoiI1CJWm8H0H/ZQ2lxaAzAB03/Yw9AOoQ5fsiciIiIiUlc5tBi1YMGCch9fuXJlsc9dXFyYOnUqU6dOrcZUIiJSV22OTS4xI+p8BhCfks3m2GT6tmxYc8FEREREROoRhy7TExERqUkJaWUXos739bZj7D+Zhs2mfoQiIiIiIvbmVA3MRUREqlOIr0eFxi3aeoxFW48R6O3GJc0b0DuyIb1bBNI+1A+zlu+JiIiIiFwUFaNERKTe6BUZSKi/ByfLWarn6+5Cp6Z+bDtyluSMXJbsPsWS3acA8Pd05ZLmgfRpEUjvyIZ0aOyn3lJSbaw2g02xyWxNNNEwNpm+rUL0501ERETqBBWjRESk3rCYTQxpG8yXm4+WeKzwV/zXbunM8KgwcvNt/Hn8LBsPJRcUBOKSScnKY/neUyzfW1Cc8nV3oWfzBvRu0ZDekYFENfHH1aIV8HLxFu+KZ/oPe871OLMwN3oLYf4eTB3ZgeFRYY6OJyIiInJRVIwSEZF642hyJt/vOAGAn4cLqdn5RY+F/uUXfTcXMz0iAukREcikIZBvtbHrRCqbDiWxKTaZ32OTScvJZ8X+06zYfxoALzcLPSIa0Odccapz0wDcXMovTmn2i/zV4l3xTJy3rcSujydTspk4bxuzx3RXQUpERERqNRWjRESkXrDZDB5f9AeZuVZ6NQ/ki3t6s+nQaZau2cSwgb0vWARysZjpGh5A1/AA7h/cEqvNYG98KhvPFac2xxbMnFoTncia6EQAPFzNdG/2v55TXcMD8HC1FF1Ts1/kr6w2g+k/7ClRiIKC3R5NwPQf9jC0Q6iKliIiIlJrqRglIiL1wrxNh9l4KBlPVwuv3dIZVxczvSMDSdpr0DsysNK/2FvMJqKa+BPVxJ97BrbAZjPYfyqtaObU5thkkjJyWX8wifUHk4CC2VZdwwPoExmI2WRi1q/Rmv0i5FttxKdkczgpk5X7E84VJ0tnAPEp2WyOTaZvy4Y1F1JERETEjlSMEhGROu9wUgYv/bwPgKeubkdEQ2+738NsNtE+zI/2YX6M6x+JYRjEJKSzMTa5qEB1Oi2HzecKVWXR7BfHq46lk5m5+RxOyuRIciZHkjI5nJzB4aRMjiZncuxMFvm20uZClS0hreyCVV2lJa0iIiJ1h4pRIiJSp9lsBo8v3ElWnpU+LQIZ0zuiRu5rMplo3ciX1o18ubNPBIZhEJuYwabYZH784wTrzs2WKo1mvzhOVZdOGoZBYnouR84VmQoLTYeTC/4/MT2n3Pu6WcyEB3ri6+HCjqMpF8wZ4utR2adWq2lJq4iISN2iYpSIiNRpn66PY3NcMl5uFl67uQtmB82kMJlMtAj2oUWwD15ulnKLUYXq4+wXR7pQ4/C3RncjqrE/h5MzOZKUwZFzhaYjyQUfmbnWcq/v7+lKREMvmgV6EdHQi4hAb8LP/X+onwdmswmrzWDAK79xMiW71L5RAA28XOkVGWiX51wbqKG7iIhI3aNilIiI1FmHTqfz6pKC5Xn/vLo94YFeDk5UoKKzWurb7BdHulDjcICH5m8v9xomEzT29ywqNoWfV3RqFuiFv5frBXNYzCamjuzAxHnbMJ137/Odycxj3sbD3NWv+QWvV9upobuIiEjdpGKUiIjUSVabweOLdpKdZ2NAqyDu6N3M0ZGK9IoMJMzfo9zZL2H+HvVq9oujbY5NLrdxeCFXi4nIoILiUrNA74KZTudmOzVt4Im7i+WC17iQ4VFhzB7T/bxlaQXC/D1o08iXVQdOM/W/uzmVms3jV7bFZKq7RZgLvS5a0ioiIlI7qRglIiJ10px1sWw9fAYfdxdevqmTU/3CXpHZL/+4qp1metSgii6JfP3mLlzXrUk1pykoSA3tEMqGmASWrtnEsIG96dsqBLMJ3lkRw+tLD/DuyoOcSs3h5Zs64WoxV3smR6jo66IlrSIiIrVL3fzJRURE6rWYhHReW7IfgH+NaE/TBs6xPO98hbNfQv2LL8UrrD9tKmfHPbG/uMTMCo0L8au5pZMWs4nekYH0CDLoHRmIxWzCZDLx0GWtefWmzljMJr7edox7524hIye/xnLVJBdzxX5U1ZJWERGR2kXFKBERqVOsNoMpC/8gJ9/GwNZB3H5JuKMjlWl4VBhrn7yMeeN7Mra1lXnje/LZ3b0wmWD+piMs3hXv6Ih1XkZOPk8u2sl/lh8od5wJ51o6eesl4Xw4tgcermZW7j/N6A83knSBHftqmxX7E3j6uz/LHeNsr4uIiIhUjIpRIiJSp3y45hA7jp7F192FV27q7FTL80rz19kvA9sEc/+glgA8+fWfxKdkOThh3bXj6FlGvLmGr7YcxWSCYR0aYaKgwHG+ws+njuzgVEsnL2vXiC/v7UMDL1f+OJbCTbPXcySpYjO8nFme1cZLv+zl7jm/cyYzj6YBnkDJ16WQs70uIiIicmEqRomISJ0RfSqNGUsLZrg8M7IDjc/9ElvbPDa0DZ2b+pOSlccjC3ZgtZXV5lyqwmozeOvXaG6avZ64pEzC/D2Yf08fPhjbs9Slk6H+Hswe053hUWEOSly2bs0asGhiP5o28CQuKZMbZ69j1/EUR8eqsuNns7jt/Q28v+oQAHf1jWD53wfzXimvC8CVUY2c8nURERGR8qmBuYiI1An5VhtTFv5BrtXGkLbB3NKjqaMjVZmbi5k3b+/G1W+uYVNsMrNXxvDQZa0dHatOOJqcyaNf7WDL4TMAXNM5jBeu74S/lytQduNwZ5550zLYh28m9mPcnN/ZE5/Kbe9v4L07ezCwdbCjo1XK0t0neXzRTlKy8vD1cOHVmzpzVaeCQtNfX5cG4W2Y9dtBlu9JYP/JNNqG+jo4vYiIiFSGZkaJiEid8P7qQ/xxLAU/DxdeutH5l+ddSPMgb/59XRQA/1kezbYjZxycqPb7bvtxrp61hi3ndlmccWsX3hrVragQVai0xuHOLsTPg6/u70O/lg3JyLVy95zf+W77cUfHqpDcfBvTf9jNfZ9vJSUrjy5N/fn54YFFhahC578uDw1pydAOjci3Gfzz2z+xafagiIhIraJilIiI1Hr7TqYy81wD6qkjO5a6nKc2uql7E67t0hirzWDygu2kZuc5OlKtlJKVx8NfbueRr3aQlpNPj4gG/DJ5IDd2b1rri5bn8/VwZc7dlzCyS2PybQaPfLWDD1cfcnSsch1JyuTm99YzZ10cAPcMiGThA/0ID7zwDpjTr+2It5uFrYfPMH/zkWpOKiIiIvakYpSIiNRqeeeW5+VZDa5oH8KN3Zs4OpLdmEwmnr8hiqYNPDmanMWz3+1ydKRaZ9OhJK6etYb//nECi9nEY0Pb8NV9fSpU7KiN3F0szLqtKxMGRALwws97ee7HPU45c+innfGMeHMNO4+lEODlykdje/L0NR1wc6nYj6eNAzyZcmVbAF5ZvI+E1OzqjCsiIiJ2pGKUiIjUarNXHmTX8VT8PV158YZOdWqmC4Cfhyuzbu+GxWziux0n+GbbMUdHqhVy8228sngft3+4keNns4ho6MWiB/ry8OWtcbHU7R9/zGYTz1zTgX9d3R6Aj9fGMvmrHeTkWx2crEB2npWnv/uTSfO3kZaTT8+IBvz88ECu6NCo0tca27c5XZr6k5adz/Qf9lRDWhEREakOdfunMRERqdP2nEjlzV+jAfj3dR0J8asby/P+qkdEAx65vKCB+TPf7SIuMcPBiZzbwdPp3DR7PbNXHsQw4NaeTfnp4YF0a9bA0dFq1L2DWjDztq64Wkz88McJ7p7zO2kOXup56HQ6N7y7nnkbC5bVPXhpS768r0+Vd760mE28eGMnLGYTP/0Zz2/7TtkzroiIiFQTFaNERKRWys0vWJ6XbzO4smMjru3S2NGRqtWDQ1rRKzKQjFwrkxdsJ89qc3Qkp2MYBvM3HeGaN9fy5/EU/D1dmX1Hd169uQs+7vVzA+HruzXhk3GX4O1mYf3BJG59f6PDlrN9t/0417y1lr3xqTT0duOz8b14Yng7XC9yplrHxv5FyxKf+W43GTn59ogrIiIi1UjFKBERqZXeWRHDnvhUGni58vz1dW953l9ZzCZm3tYVPw8X/jiWwoxlBxwdyakkpedw3+db+ee3f5KVZ6V/q4YseWRQiR3Z6qOBrYP56v6+BPm4sTc+lRtnr+fg6fQau39WrpUnF+3kka92kJlrpU+LQH6ePJDBbYLtdo9HrmhNkwBPjp/N4j/6uyEiIuL0VIwSEZFaZ9fxFN5ZEQPAv6+LItjX3cGJakbjAE9euakzAO+tOsj6mEQHJ3IOK/cnMHzWGpbtOYWbxcy/rm7P5+N715ldFe0hqok/30zsT/OGXhw7k8XNs9ez/ciZar/vgVNpXPv2Wr7achSTCSZf3pov7ulDIzsvqfVyc+H5G6IA+GRdLLuOp9j1+iIiImJfKkaJiEitkpNvLVqed3WnUK7pXL9mvlzVKYxRvcIxDHj0/3aQnJHr6EgOk51nZdp/dzNuzu+cTsuhdYgP303qz72DWmA21+2ZclXRrKEXiyb2o0tTf85k5jHqw43V1mPJMAz+b8tRrn17LdEJ6QT7uvPFhN48OrQNlmp6bYa0DeGazmHYDHjqmz/J11JWERERp6VilIiI1Cpv/RrDvpNpNPR247nrour88rzSPHNNB1oGe3MqNYcnFu3EMAxHR6pxe+NTufbttXy6Pg6Au/pG8MPfBtChsZ9jgzm5IB935t/bh8FtgsnOs3Hv3K383+9H7XqP9Jx8Hvu/P3hi0U6y82wMbB3EL5MH0q9VkF3vU5pnR3bAz8OFP4+n8NmGw9V+PxEREakaFaNERKTW2HnsLLNXHQTg+eujaOhTP5bn/ZWXmwtvjuqGm8XM8r2nmLfpiKMj1RibzeCjNYe47u11HDiVTpCPO3PuvoTp10Xh4WpxdLxawdvdhY/u6slN3ZtitRk88fVO3vo12i5FzT0nUrn2rbV8u/04FrOJx69sy2d39yKohv6uhvh68I+r2gPwxtL9HD+bVSP3FRERkcpRMUpERGqFnHwrf/+/P7DaDK7pHFbvG1N3bOzPk1e1A+D5H/ew/2SagxNVv1Op2dw1ZzPP/7SXXKuNK9qHsPiRgQxpG+LoaLWOq8XM67d05sFLWwLwxrIDPPP9Lqy2qhWkDMNg3sbDXP/uOg4lZhDq58GC+/owaUirGl8yefsl4fSMaEBmrpVnv9tVL2cOioiIODsVo0REpFaYuTya6IR0gnzc+Pd1UY6O4xTu7tecwW2Cycm38fCX28nOszo6UrVZvOskV85czZroRDxczTx/fRQfju1ZYzNu6iKTycQTw9sx/dqOmEwwb+MRJn2xrdJ/jlKz83joy+08/d0ucvNtXNYuhJ8nD+SS5oHVlLx8ZrOJl27shKvFxK/7Evhl10mH5BAREZGyqRglIiJOb/uRM7xftDyvE4Hebg5O5BzMZhOv39KFIB939p9K46Wf9zo60kWx2gw2xSazNdHEpthkrDaDjJx8nly0kwfmbeVsZh5RTfz48W8DGdMnol72C6sOd/Vrzjuju+NmMbN490nu/HgTKZl5FTp357GzXPPmWn7aGY+L2cTTI9rz8V09Hf53tHUjXyYOLpj1Ne2/u0nNrtjzERERkZrh4ugAIiIi5cnOK9g9z2bA9V0bMzwq1NGRnEqwrzuv39KZcXN+57MNhxnYOpgrOjRydKxKW7wrnuk/7CE+JRuwMDd6Cw293TCb4HR6LiYT3D+oJY8NbYObi95Ls7erO4XRwMuN+z7fwu9xZ7jl/fV8encvGgd4FisSNoxNpm+rEMwmmLMujpd+2Uue1aBJgCdvj+5Gt2YNHP1Uijw4pBU/7oznUGIGry7ex/PXd3J0JBERETlHxSgREXFqM5Yd4ODpDIJ93Zl2bUdHx3FKl7YNYcKASD5eG8vji/5g8SODaOTn4ehYFbZ4VzwT523jr519kjJyAQjwcmX2HT3o27JhzYerR/q2bMjCB/py1yebOXAqnRvfXc99g1rw4ZpDxYqEjfzcaeTnwc5jKQAM7xjKKzd1xt/L1bFP4C88XC08f0MUoz/cxBebjnBDt6b0iHCeYpmIiEh9prcWRUTEaW09nMyHaw4B8NINnQjw0vK8sjwxvC0dwvw4k5nH3//vD2xVbERd06w2g+k/7ClRiDqfu4uZXpGO6T9U37QL9eObB/vTMtibk6nZ/PvHwtlq/3MqNYedx1JwMZuYfm1HZo/p7nSFqEL9WgZxc4+mGAb885s/ybPaHB1JREREUDFKREScVFaulSkLd2IYcGP3JrVy6VlNcnex8Oaobni6Wlgbk1hUxHN2m2OTSxQ7/upUag6bY5NrKJE0CfDkq/v64mopvydXgJdrrejd9a+r2xPo7cb+U2l8sLp2/L0QERGp61SMEhERp/T60v3EJmbQyM+dqddoeV5FtArxYerIDgC8tmQ/O4+ddWygCkhILb8QVTQurWLjxD6iE9LJs5Y/uy4xPbdWFAkbeLvx9Ij2ALz5azSHkzIcnEhERERUjBIREaezOTaZT9bFAvDyjc7Xi8aZ3XZJOFdFhZJvM3j4y+2k5+Q7OlKZ9p1M5b3VBys0NsS39vTAqgsqWvyrLUXCG7o1oX+rhuTk2/jXt7swjNqxjFVERKSuUjFKREScSmZuPo8v+gPDgFt7NmVIuxBHR6pVTCYTL9/Ymcb+HsQlZTLtv7sdHamElMw8pv13NyPeXMve+LRyx5qAMH8P9YyqYRUt/tWWIqHJZOKF6zvh7mJmbUwi3+047uhIIiIi9ZqKUSIi4lReXbyfw0mZhPl78PQ1HRwdp1by93Jl5u3dMJtg0dZj/PePE46OBIDNZrBg8xGGvLGST9fHYbUZXBUVygvXR2GioPB0vsLPp47sgMXs3H2J6ppekYGE+XuUeE0K1cYiYfMgbx6+vDUAz/24lzPndmsUERGRmqdilIiIOI2Nh5L4dH0cAC/f1Bk/Dy3Pq6pekYE8NKQVAP/65k+OJmc6NM/2I2e4/t11/OObP0nOyKVViA/zJvRm9pge3NEngtljuhPqX3yWTai/B7PHdGd4VJiDUtdfFrOpqP9YXSoS3juwBW0a+ZCckcuLP+91dBwREZF6S8UoERFxChk5BcvzAEb1Cmdwm2AHJ6r9Hr68Nd2bBZCWk8/kBdvJd8C29qfTcpiy8A9ueHc9O4+l4OvuwtMj2vPL5IEMaB1UNG54VBhrn7yMeeN7Mra1lXnje7L2yctUiHKg4VFhda5I6OZi5qUbOwGwcOsxNhxMcnAiERGR+snF0QFEREQAXv5lH0eTs2gS4Mk/r27v6Dh1govFzKzbu3H1rDVsO3KWN3+N5rFhbWvk3nlWG5+tj2PW8mjSzjVRv7lHU54c3o5gX/dSz7GYTfSODCRpr0HvyMBaN+umLhoeFcbQDqFsiElg6ZpNDBvYm76tQmr1a9MjIpA7ejfji01H+Ne3f/Lz5IF4uFocHUtERKRe0cwoERFxuHUxiXy+8TAAr9zUGV8tz7Ob8EAvXjg3E+TtFTFsOlT9M0HWRidy1aw1PP/TXtJy8unc1J9vHuzH67d0KbMQJc6rsEjYI6juFAmfOFcUPZSYwbsrK7ajo4iIiNiPilEiIuJQ6Tn5PLFoJwBj+jQrtnRL7OPaLo25qXtTbAY8+tUOUjLzquU+R5MzeeDzrYz5eBMxCek09HbjlZs68d2D/enerEG13FOkKvw9XZk2siMAs1fGEJNQ/q6OIiIiYl8qRomIiEO9+PNejp/NomkDT566Ssvzqsv06zrSvKEXJ1KyeerbnRiGYbdrZ+dZmbn8AFfMWMXi3SexmE2M69ec36Zcym2XNMNcB2bSSN1zdadQLmsXQp7V4J/f7MJms9/fCRERESmfilEiIlKjrDaDTbHJbE008eHaWOZvOgLAqzd3xttdrQyri4+7C2+O6oaL2cTPf57kq9+PXvQ1DcNg8a6TXDFjFTOXR5OTb6NPi0B+engA067tiL+nlluK8zKZTPz7uo54ulrYHJfM/225+L8TIiIiUjH6qV9ERGrM4l3xTP9hD/Ep2YAFoqMBuLRNMP1aanledevcNIApV7bl5V/2Mf2HPfRsHkirEJ8qXSsmIY1p/93D2phEAML8PfjXiPaM6BSGyaSZUFI7NG3gxd+HteH5n/by4s97ubx9I/U1ExERqQGaGSUiIjVi8a54Js7bdq4QVdyqA6dZvCveAanqn/sGtqB/q4Zk5Vl5+Mvt5ORbK3V+WnYez/+4h+Ez17A2JhE3i5mHhrTi178P5prOjVWIklpnXL/mRDXxIzU7n+d+3OPoOCIiIvWCQ4tR06ZNw2QyFfto165dueecPXuWSZMmERYWhru7O23atOHnn3+uocQiIlIVVpvB9B/2UF5Hluk/7MGqni3Vzmw2MePWrjTwcmVPfCqvLt5fofNsNoNFW48x5PVVfLQ2lnybwRXtQ1j22CCmXNkWLzdNtpbaycVi5qUbOmM2wX//OMHK/QmOjiQiIlLnOfwnx44dO7J8+fKiz11cyo6Um5vL0KFDCQkJYdGiRTRp0oTDhw8TEBBQA0lFRKSiDMPg+NksohPSiTmVzrqY06XOiCoaD8SnZLM5Npm+LRvWXNB6qpGfB6/d3IV75m7h47WxDGwdxMDWwUW9vBrGJtO3VQiWc43H/zyWwrP/3cX2I2cBaBHkzTMjOzCkbYgDn4WI/XRq6s+4fpF8si6WZ77fxdJHBuPpZnF0LBERkTrL4cUoFxcXQkNDKzT2k08+ITk5mfXr1+PqWtAUtXnz5tWYTkSk7ji/cfhfiw1VZbMVFp3SiD6VzoFT6cQkpBGTkE5GbuWWfwEkpJVdsBL7uqJDI8b2jWDuhsP87cvteLpaSEjLASzMjd5CmL8Hjw1tw7YjZ1jw+1EMA7zdLPzt8taM7x+Jm4tW+kvd8vdhbViy+yRHk7OY+esB7e4pIiJSjRxejIqOjqZx48Z4eHjQt29fXnrpJZo1a1bq2P/+97/07duXSZMm8f333xMcHMzo0aN58sknsVhKf/cqJyeHnJycos9TU1MByMvLIy8vr0qZC8+r6vn2ohzOl8MZMiiHcpRmye5TPP/zPk6m/q/YEOrnztNXt+PKjo0ueL7VZnDsbBYxp9KJOZ1BTELBfw+eTicrz1bqOS5mE80betE6xAcPVzPf7rhwT6iGXi41+vWp7382Hh/aimW7TxGfmk1adn6xx+JTsnl80c6iz6/tHMYTV7amkZ8HGFby8ipfbKyI+v6aKIfjcriZ4dlr2nH/vO18tCaWER0b0T7Mt0YzVIZyKIczZ1AO5XD2DMpRPTkqc67JMAyHNej45ZdfSE9Pp23btsTHxzN9+nSOHz/Orl278PUt+Y9/u3btiIuL44477uDBBx8kJiaGBx98kIcffpipU6eWeo9p06Yxffr0Esfnz5+Pl5eX3Z+TiIiz+SPJxCcHCmexnD8TquDb//g2Nro0LPh/mwGJ2XAyy8TJzML/mkjIgjyj9FlUFpNBiCeEehoFH14F/x/sAZZzt7UZMH2bhbO5f83wvywBbjC1u5WLnKwllWAz4NmtFtLyoPTXpeD1ndjeSmv/Go0m4jBz9pvZkWymmbfBo530PUlERKSiMjMzGT16NCkpKfj5+ZU71qHFqL86e/YsERERzJgxgwkTJpR4vE2bNmRnZxMbG1s0E2rGjBm89tprxMeX/o57aTOjwsPDSUxMvOAXpyx5eXksW7aMoUOHFi0XdATlcL4czpBBOZTjfFabwaVvrD43I6p0Pu4WBrUO4tDpDA4lZZKbX/pMJzcXMy2CvGkd4k2rYB9anftvs0BPXCwXXrK1ZPcp/rbgD4BijcwLf8976/YuFZqlZU/1+c8GwKbYZMZ8suWC4+aN70nvyMAaSKTXRDkcn+NUajbD31xPek4+z4xox9g+xWfs16evhXLUzhzOkEE5lMPZMyhH9eRITU0lKCioQsUohy/TO19AQABt2rQhJiam1MfDwsJwdXUttiSvffv2nDx5ktzcXNzc3Eqc4+7ujru7e4njrq6uF/1C2+Ma9qAczpfDGTIoh3IAbDmYVG4hCiA9x8rPu04Vfe7haqZViA+tQ3xpFeJDm0a+tA7xITzQ66J6TF3TtSkuLham/7CnWDPzUH8Ppo7swPCosCpf+2LVxz8bAEmZ+RcedG5cTX996utrohyOz9G0oStPXtWOZ77bxYxl0VzduTFh/p41mqEylEM5nDmDciiHs2dQDvvmqMx5TlWMSk9P5+DBg9x5552lPt6/f3/mz5+PzWbDbC54F/7AgQOEhYWVWogSEanvElIr1hD82i6Nua5rY1qH+NK0gSfmalqXMjwqjKEdQtkQk8DSNZsYNrC3XRqpS9WE+HrYdZxIXXFHr2Z8u+0Y246cZer3u/lgbE9HRxIREalTHLoVzpQpU1i1ahVxcXGsX7+eG264AYvFwqhRowAYO3YsTz31VNH4iRMnkpyczOTJkzlw4AA//fQTL774IpMmTXLUUxARcUqZufnM33SE15fur9D4Ub2acXn7RjRr6FVthahCFrOJ3pGB9Agy6B0ZqEKUA/WKDCTM36OMblEFSyjD/D3oVUNL9ESchdls4qUbO+NiNrF0zymW7D7p6EgiIiJ1ikNnRh07doxRo0aRlJREcHAwAwYMYOPGjQQHBwNw5MiRohlQAOHh4SxZsoRHH32Uzp0706RJEyZPnsyTTz7pqKcgIuJU4hIz+HzjYf5vy9ESu6OVxkTBMjkVG+oni9nE1JEdmDhvGyZK7+U1dWQHFQylXmob6st9g1rw7sqDTP1+N/1aNsTXw/HLJ0REROoChxajFixYUO7jK1euLHGsb9++bNy4sZoSiYjUPjabwcoDCczdcJiV+08XHY9o6MWdfSJo4OXGlIVlNw5XsaF+Gx4Vxuwx3Z2yl5eIoz18eWt++jOew0mZvLH0ANOu7ejoSCIiInWCU/WMEhGRijubmcvCLcf4fONhjiRnAmAywZC2IYztG8Gg1sFFS+683Z2zcbg4B/XyEimdh6uFF67vxJiPN/HZhjiu79aEjqHejo4lIiJS66kYJSJSy+w5kcrcDXF8t+M42Xk2APw8XLjtknDG9IkgomHJX5RUbJALKezllbRXvbxEzjegdRA3dGvCt9uP84+vd/KPK1uzNdFEw9hkfR8VERGpIhWjRERqgdx8G0t2n2Tuhjh+jztTdLx9mB939Y3guq5N8HSzlHsNFRtERKrm6RHtWbL7JPtOpjHus22AhbnRWwjTDFMREZEqUTFKRMSJJaRmM3/zEeZvOkJCWg4ALmYTw6NCuatfc3pGNMBkUlFJRKQ6/R6XTGautcTxkynZTJy3jdljuqsgJSIiUgkqRomIOBnDMNhy+AyfrY9j8a6T5NsK2o4H+7ozulczRvduRiM/DwenFBGpH6w2g+k/7Cn1MYOCzSCm/7CHoR1CNeNURESkglSMEhGpAVabwabY5HL7jGTlWvl+x3E+23CYvfGpRccvad6AsX2bc2XHUNxczDUdXUSkXtscm1xs84e/MoD4lGw2xybTt2XDmgsmIiJSi6kYJSJSzRbvij9vJ7uSfUYOJ2Uwb+Nhvvr9KKnZ+QB4uJq5vmsT7uwbQcfG/o59AiIi9VhCWtmFqKqMExERERWjRESq1eJd8Uyctw3jL8dPpmTzwLxtRDXxY/eJVIxzA5oFenFnnwhu6dmUAC+3Gs8rIiLFhfhWbFl0RceJiIiIilEiItWmsM/IXwtRQNGxXccLluMNbhPMXf0iGNxG24SLiDiTXpGBhPl7cDIlu9Tv5yYg1N+DXpGBNR1NRESk1lLzERGRanKhPiOF/nNrFz4b34vL2jVSIUpExMlYzCamjuwAFBSeSjN1ZAd9/xYREakEFaNERKpJRfuHmPULjIiIUxseFcbsMd0J9S++FM/NYmL2mO4MjwpzUDIREZHaScv0RESqifqMiIjUHcOjwhjaIZQNMQl8/esmvj1swWozGNA62NHRREREah3NjBIRqSaFfUbKYgLC1GdERKTWsJhN9I4M5NLGBs0CPbEasOFgkqNjiYiI1DoqRomIVJPz+4z8VeHCPPUZERGpnQa2CgJg9YHTDk4iIiJS+6gYJSJSjZoEeJV6PNTfQ31GRERqsYGtGwKwOlrFKBERkcpSzygRkWr0+cY4AK7rEsYtPZqwdM0mhg3sTd9WIZoRJSJSi/WJDMTVYuJwUiZxiRk0D/J2dCQREZFaQzOjRESqSUpmHt/vOAHA2H7N6R0ZSI8gg96RgSpEiYjUct7uLvSIaABodpSIiEhlqRglIlJNFm49Sk6+jQ5hfnRv1sDRcURExM4GtSnYSU99o0RERCpHxSgRkWpgsxl8sekIAHf2jcBk0kwoEZG6ZvC5YtT6g0nk5tscnEZERKT2UDFKRKQarI1JJDYxA193F67r2tjRcUREpBq0D/UjyMedzFwrWw4nOzqOiIhIraFilIhINfh842EAburRFC837RUhIlIXmc0mBrUOAmD1gUQHpxEREak9VIwSEbGz42ez+HXvKQDG9IlwcBoREalOg9sWLNVbpb5RIiIiFaZilIiInX256Qg2A/q1bEirEB9HxxERkWo0oFUQJhPsjU8lIS3b0XFERERqBRWjRETsKDffxoLfCxqXj+2rWVEiInVdQx93ohr7A7BGS/VEREQqRMUoERE7+mVXPInpuTTyc+eK9o0cHUdERGpA4a56q6O1VE9ERKQiVIwSEbGjeecal4/uFYGLRd9iRUTqg0HnilFrohOx2QwHpxEREXF++k1JRMRO9san8nvcGVzMJm7vFe7oOCIiUkO6NQvAx92F5Ixcdp1IcXQcERERp6dilIiInRTOirqyYyiN/DwcnEZERGqKq8VMv5YNAVitXfVEREQuSMUoERE7SMvO49vtxwG4U43LRUTqncFtC5bqrVIxSkRE5IJUjBIRsYNvth0nM9dK6xAfekcGOjqOiIjUsEGtC4pR246cJTU7z8FpREREnJuKUSIiF8kwDD4/t0Tvzr4RmEwmBycSEZGaFh7oRYsgb6w2g/UxSY6OIyIi4tRUjBIRuUgbDyUTk5COl5uFG7o1cXQcERFxkMJd9VZHa6meiIhIeVSMEhG5SIWNy2/o1gRfD1cHpxEREUcZfK4YtWr/aQzDcHAaERER56VilIjIRTiVms2S3ScBNS4XEanvercIxM1i5vjZLA4lZjg6joiIiNNSMUpE5CJ8ufkI+TaDXs0DaRfq5+g4IiLiQF5uLlwS2QCA1dpVT0REpEwqRomIVFGe1caXm48AMEazokREhPOW6qkYJSIiUiYVo0REqmj5nlOcSs0hyMeN4R1DHR1HREScQGET842HksjOszo4jYiIiHNSMUpEpIo+P9e4/PZLmuHmom+nIiICbRv50sjPnew8G1vizjg6joiIiFPSb08iIlUQk5DG+oNJmE0wqnczR8cREREnYTKZGNS6cKlegoPTiIiIOCcVo0REqmDexoJeUVe0b0STAE8HpxEREWdSuFRv9YFEBycRERFxTipGiYhUUkZOPl9vPQbAnWpcLiIifzGgVRAmE+w/lcbJlGxHxxEREXE6KkaJiFTS9ztOkJaTT2SQN/1bBjk6joiIOJkG3m50aRoAwOpo7aonIiLyVypGiYhUgmEYzN0QB8AdvZthNpscG0hERJxS4VK9VQdUjBIREfkrFaNERCph25Ez7DuZhoermVt6hDs6joiIOKnBbQpmzq6NTsRqMxycRkRExLmoGCUiUglzNxwG4LouTfD3cnVwGhERcVZdmgbg6+FCSlYeO4+ddXQcERERp6JilIhIBSWm5/Dzn/GAGpeLiEj5XCxmBrYumB2lpXoiIiLFqRglIlJBX/1+lDyrQdfwAKKa+Ds6joiIOLlBrQv6Rq1WMUpERKQYFaNERCrAajOYv+kIAHf20awoERG5sMIm5juOniUlM8/BaURERJyHilEiIhWwYl8Cx89mEeDlyojOYY6OIyIitUDjAE9ah/hgM2BtTKKj44iIiDgNhxajpk2bhslkKvbRrl27Cp27YMECTCYT119/ffWGFBEBPt9Y0Lj8tp7heLhaHJxGRERqi8LZUVqqJyIi8j8OnxnVsWNH4uPjiz7Wrl17wXPi4uKYMmUKAwcOrIGEIlLfxSVmsOrAaUwmuKO3luiJiEjFFRWjok9jGIaD04iIiDgHhxejXFxcCA0NLfoICgoqd7zVauWOO+5g+vTptGjRooZSikh99sWmgllRl7YJpllDLwenERGR2qR3ZCDuLmbiU7KJSUh3dBy7stoMNsUmszXRxKbYZKw2FdtERKRiHF6Mio6OpnHjxrRo0YI77riDI0eOlDv+3//+NyEhIUyYMKGGEopIfZadZ+X/thwD4M6+mhUlIiKV4+FqoXeLhgCsqkNL9RbvimfAK78x5pMtzI22MOaTLQx45TcW74p3dDQREakFXBx58969e/Ppp5/Stm1b4uPjmT59OgMHDmTXrl34+vqWGL927Vo+/vhjduzYUeF75OTkkJOTU/R5amoqAHl5eeTlVW1Xk8Lzqnq+vSiH8+VwhgzKYd8c3207TkpWHk0DPOgX2eCinoszfD2cIYNyKIezZ1AO5bB3hgEtA1l94DQr9ydwV59wh+WwlyW7T/G3BX/w13lQJ1OymThvG2/d3oUrOzaq0UzO8GfDWXI4QwblUA5nz6Ac1ZOjMueaDCdavH727FkiIiKYMWNGiZlPaWlpdO7cmXfffZerrroKgHHjxnH27Fm+++67Mq85bdo0pk+fXuL4/Pnz8fLSchsRKd8bOy0cyTAxspmVK5o4zbdLERGpRU5mwkt/uOBqMnjxEitutXgfDJsB07dZOJsLYCplhEGAG0ztbsVc2sMiIlJnZWZmMnr0aFJSUvDz8yt3rENnRv1VQEAAbdq0ISYmpsRjBw8eJC4ujpEjRxYds9lsQEHfqf3799OyZcsS5z311FM89thjRZ+npqYSHh7OsGHDLvjFKUteXh7Lli1j6NChuLq6Vuka9qAczpfDGTIoh/1y7DyWwpENm3BzMfP06EsJ9HZzSA57coYMyqEczp5BOZTD3hkMw+DTuDXEp2QT2K4Xg1qX3yO1unLYw6bYZM5u3FLOCBNncyG4Qx96RwbWWC5n+LPhLDmcIYNyKIezZ1CO6slRuBKtIpyqGJWens7Bgwe58847SzzWrl07/vzzz2LHnn76adLS0pg1axbh4aVPeXZ3d8fd3b3EcVdX14t+oe1xDXtQDufL4QwZlOPic3y55TgA13QKo1GAt8NyVAdnyKAcyuHsGZRDOeyZYXCbYBb8fpR1B89weYcwh+W4WEmZ+RUe54jXyBn+bDhLDmfIoBzK4ewZlMO+OSpznkOLUVOmTGHkyJFERERw4sQJpk6disViYdSoUQCMHTuWJk2a8NJLL+Hh4UFUVFSx8wMCAgBKHBcRuVhnMnL54Y8TAIxR43IREblIg84Vo1ZH1+4m5iG+HnYdJyIi9ZNDi1HHjh1j1KhRJCUlERwczIABA9i4cSPBwcEAHDlyBLPZ4Rv+iUg9tGjrMXLybXRs7Ee38ABHxxERkVquf6sgLGYTMQnpHD+bRZMAT0dHqpJekYGE+XsQn5Jd6uMmINTfg141uERPRERqH4cWoxYsWFDu4ytXriz38U8//dR+YUREzrHZDOZtOgzAnX0iMJnUgVVERC6Ov6crXcMD2Hr4DKsPnGZUr2aOjlQlFrOJqSM78MC8bWWOmTqyAxZ1LxcRkXJo2pGIyF+sjj7N4aRMfD1cuLZrY0fHERGROmJQ64LZ/6sP1O6lemH+Zc/qGt27GcOj7NcTS0RE6iYVo0RE/mLexoJZUbf0CMfLzan2eRARkVpsUJuCXfTWxiSSb7U5OE3VvbuyYOfrG7o1Zt74noxtbeWOXgWbCa3Yl0BOvtWR8UREpBZQMUpE5DxHkzP5dV8CAHf0qZ1LKERExDl1bhpAgJcradn57Dh61tFxqiT6VBpLdp/CZIJJQ1rROzKQHkEGTw1vQ6ifBydSsvnq96OOjikiIk5OxSgRkfN8ufkIhgEDWgXRMtjH0XFERKQOsZhNDGhVMDuqti7Vm73qIADDOjSiVYhv0XF3VwuTLmsFwNu/xZCdp9lRIiJSNhWjRETOycm3Fr2bO6ZPhIPTiIhIXTSoTUHfqFXRiQ5OUnlHkzP5fscJAB68tFWJx2/rGU6TAE8S0nKKlryLiIiURsUoEZFzfvnzJEkZuYT5e3BF+xBHxxERkTpo8Lli1M5jZ0nOyHVwmsr5YPUhrDaDga2D6BIeUOJxNxczD19eUKSavfIgGTn5NZxQRERqCxWjRETO+fzcu7ijezXDxaJvjyIiYn+N/DxoF+qLYRQ0Mq8tEtKy+WpLwezhiZe2LHPcjd2bEtHQi6SMXD7bEFdD6UREpLbRb1siIsDuEylsPXwGF7OJ287tCCQiIlIdCpfq1aa+UZ+sjSM330a3ZgH0bdGwzHGuFjOTL28NFMykSsvOq6mIIiJSi6gYJSICzNt4BIDhUaGE+Ho4OI2IiNRlg1r/rxhlGIaD01xYSlZeUQ+oBy9thclkKnf8dV2b0DLYm7OZeXyyNq4GEoqISG2jYpSI1Hup2Xl8t/04AHeqcbmIiFSzns0b4OlqISEth30n0xwd54I+3xBHek4+bRv5cnm7C/dUtJhNPDq0DQAfrT1ESqZmR4mISHEqRolIvff11mNk5Vlp08iHXpGBjo4jIiJ1nIerhT4tCv69cfalelm5Vj5ZFwcU9Ioym8ufFVXo6qgw2oX6kpadz4drDlVjQhERqY1UjBKRes0wjKLG5Xf2bX7BpQciIiL2UNQ3Ktq5i1ELfj9CckYu4YGeXNM5rMLnmc+bHfXJuliS0nOqK6KIiNRCKkaJSL224WASh05n4O1m4YZuTRwdR0RE6onB54pRv8eeITM338FpSpebb+OD1QWzmh4Y3LLSO80O69CITk38ycy18v5qzY4SEZH/UTFKROq1wllRN3Zvio+7i4PTiIhIfREZ5E3TBp7kWm1sPJTk6Dil+m7HceJTsgn2deem7k0rfb7JZOKxc7Oj5m6IIyEt294RRUSkllIxSkTqrZMp2SzdcwqAMWpcLiIiNchkMv1vqd6BRAenKclqM3hv5UEA7h0YiYerpUrXubRtMN2aBZCdZ+PdFQftGVFERGoxFaNEpN6av/kIVptBr8hA2ob6OjqOiIjUM4VL9VY5YRPzJbtPcigxA39PV0b3rvobNiaTib8PbQvA/E1HiE/JsldEERGpxVSMEpF6Kc9q48vNRwC4U7OiRETEAfq1bIiL2URsYgZHkzMdHaeIYRi8syIGgLv6Nb/oZez9WzWkd2QguVYbb/8WY4+IIiJSy6kYJSL10tLdpzidlkOwrztXdgx1dBwREamHfD1c6d6sAeBcs6NWHTjN7hOpeLlZuLtf84u+nslk4u/DCmZH/d+Wo05VeBMREcdQMUpE6qXPN8YBMOqScNxc9K1QREQcY1CbIABWO1Ex6t1zvaJG9WpGA283u1yzV2QgA1sHkWc1eOu3aLtcU0REai/9BiYi9U70qTQ2HkrGYjYxqnczR8cREZF6bHCbEADWH0wiz2pzcBrYEpfM5thkXC0m7h3Ywq7XLtxZ7+ttx4lNzLDrtUVEpHZRMUpE6p3PNx4G4Ir2IYT5ezo4jYiI1GcdG/vR0NuN9Jx8th0+4+g4RbOiburelFB/D7teu1uzBlzWLgSrzWDW8gN2vbaIiNQuKkaJSL2SnpPPN9uOA3Bnn+aODSMiIvWe2WxiQOtzS/WiHbtUb/eJFH7bl4DZBPcPblkt9yicHfX9HyeIPpVWLfcQERHnp2KUiNQr320/TnpOPi2CvenfqqGj44iIiDC4TTDg+Cbms8/Nirq6UxiRQd7Vco+oJv5c2bERhgEzl6t3lIhIfaVilIjUG4ZhMO/cEr0xvSMwmUwOTiQiIgIDWxcUo3YdTyUxPcchGWITM/j5z3gAHry0VbXe69GhbTCZ4Kc/49lzIrVa7yUiIs5JxSgRqTe2HjnLvpNpeLiaualHU0fHERERASDY150OYX4ArI1OdEiG91cdxGbAZe1C6NDYr1rv1S7Uj2s6NwbgP+odJSJSL6kYJSL1xrxNRwG4vmsT/D1dHZxGRETkfwadW6q32gFL9U6mZPP1tmMAPHhp9fSK+qtHrmiN2QTL9pxi57GzNXJPERFxHipGiUi9kJoLS/ecAmBMnwgHpxERESmusG/U6ujT2GxGjd77wzWHyLMa9IoMpGfzwBq5Z8tgH67v1gSAN5ZqdpSISH2jYpSI1GlWm8Gm2GS+jjWTZzXoFu5PVBN/R8cSEREppkdEA7zdLCSm57Invub6KCVn5DJ/0xGg5mZFFZp8eWssZhOrDpxm6+HkGr23iIg4lopRIlJnLd4Vz4BXfmPMJ1vYkVzw7e5QYiaLd8U7OJmIiEhxbi5m+rYs2OV1dXTNLdX7dH0cWXlWOjb2K5qdVVMiGnpzy7kejpodJSJSv6gYJSJ10uJd8Uyct434lOxix1Oz8pg4b5sKUiIi4nQKi0Gr9tdMMSo9J59P18UCBTvoOWKX2Ycua4WrxcT6g0lsOJhU4/cXERHHUDFKROocq81g+g97KK3jRuGx6T/swVrDPTlERETKU9jEfOvhM6Tn5Ff7/eZvOkxqdj4tgrwZHhVa7fcrTdMGXozq1QyAGcv2Yxj6t1lEpD5QMUpE6pzNscklZkSdzwDiU7LZHKv+FCIi4jwiGnoT0dCLfJtR7bOEsvOsfLimYFbUA5e2xGKu+VlRhSYNaYW7i5nf486wJjrRYTlERKTmqBglInVOQlrZhaiqjBMREakpRUv1DiRU632+3naM02k5hPl7cH3XJtV6rwtp5OdRtNPtG8sOaHaUiEg9oGKUiNQ5Ib4edh0nIiJSUwa1LihGrT5QfTOE8q023lt1EID7BrXAzcXxvxJMvLQlnq4W/jh6ll/3Vm8hTkREHM/x//KIiNhZr8hAGni5lvm4CQjz96BXZGDNhRIREamAvi0b4moxcSQ5k7jEjGq5x4874zmanEWgtxu3X9KsWu5RWUE+7tzVrzkAM5YdwKa+jiIidZqKUSJS5yRl5JBnLf2H2MKOGFNHdnBofwwREZHSeLu70COiAQCro+2/q57NZjB7ZcGsqPH9m+PpZrH7Parq/kEt8HF3YU98Kkt2n3R0HBERqUYXVYzKycmxVw4REbuw2QymLNxJek4+TQI8CfVzL/Z4qL8Hs8d0Z3hUmIMSioiIlG9wmxAAVu23fzHq130J7D+Vho+7C3f2bW7361+MBt5ujO/fHID/LD+gXW9FROqwShWjfvnlF+666y5atGiBq6srXl5e+Pn5MXjwYF544QVOnDhRXTlFRCpkzvo4Vh84jbuLmU/vvoR1/7iceeN7Mra1lXnje7L2yctUiBIREac2qE0QABsOJZGbb7PbdQ3D4J0VMQCM6ROBv2fZS9odZcLAFvh5uHDgVDo/7tTvFiIidVWFilHffvstbdq0Yfz48bi4uPDkk0/yzTffsGTJEj766CMGDx7M8uXLadGiBQ888ACnT9v/XRwRkQvZfSKFV37ZB8DT13SgdSNfLGYTvSMD6RFk0DsyUEvzRETE6bUP9SPIx53MXCtbDifb7bobDiWx4+hZ3F3MTBgQabfr2pO/pyv3DWoBwKzl0eRb7VeMExER5+FSkUGvvvoq//nPf7jqqqswm0vWr2699VYAjh8/zltvvcW8efN49NFH7ZtURKQcWblWJi/YQa7VxhXtGzGmt3M0ZBUREakss9nEoDZBfLPtOKsOnKZfyyC7XPfdFQW9om7tGU6wr/sFRjvOuP6RfLw2lkOJGXy34wQ392jq6EgiImJnFZoZtWHDBkaMGFFqIep8TZo04eWXX1YhSkRq3As/7yEmIZ1gX3deuakTJpNmQImISO01uE0wAKsPJNrlen8cPcvamEQsZlPRzCNn5ePuwgODWwIw69cD5Gl2lIhInVPpBub//ve/yczMLHE8KyuLf//733YJJSJSGcv2nGLexiMAzLi1Cw19nPfdXhERkYoY0CoIkwn2xqeSkJp90dd7d2VBr6jrujQmPNDroq9X3cb2bU6QjztHk7NYuOWYo+OIiIidVboYNX36dNLT00scz8zMZPr06XYJJSJSUQmp2Tz59U4A7h0YycDWwQ5OJCIicvEa+rgT1dgfgNXRFzc7KvpUGkt2nwJg4qUtLzpbTfB0s/Dguaxv/xZNTr7VwYlERMSeKl2MMgyj1OUvf/zxB4GBgXYJJSJSETabwd8X/kFyRi4dwvyYcmVbR0cSERGxm/8t1bu4zYFmryroFXVlx0a0buR70blqyujezQj18+BESjYLNh91dBwREbGjChejGjRoQGBgICaTiTZt2hAYGFj04e/vz9ChQ4samYuI1ISP18ayJjoRD1czb47qhruLxdGRRERE7GbQuWLU2phEbDajStc4mpzJ9ztOAPDgpa3slq0meLhaeOiygszvrIghO0+zo0RE6ooK7aYHMHPmTAzDYPz48UyfPh1/f/+ix9zc3GjevDl9+/atlpAiIn+163gKry7ZB8Az13SgVYiPgxOJiIjYV7dmAfi4u5CckcuuEyl0bhpQ6Wt8uOYQVpvBgFZBdAmv/PmOdmvPcN5bdZBjZ7KYt/Ew9wx07ubrIiJSMRUuRt11110ANG/enP79++Pq6lpiTFZWFp6envZLJyJSiqxcK5MXbCfPajC0QyNG92rm6EgiIiJ252ox079VQ5bsPsWq/acrXYw6nZbDV78XLG97sJb0ivorNxczD1/Wmie+3snslQcZ1asZ3u4V/hVGREScVKV7Rn3zzTelFqIyMjK4+uqr7RJKRKQ8z/20h4OnM2jk584rN3UutY+diIhIXVC4VG91dOX7Rn2yLpacfBtdwwPo27KhvaPVmBu7N6F5Qy+SMnL5bEOco+OIiIgdVLoY9dNPPzF16tRixzIyMhg+fDj5+fl2CyYiUpolu08yf9MRTCaYcWtXAr3dHB1JRESk2gw6t0vstiNnSc3Oq/B5KVl5fL7hMACThrSq1W/cuFjMTL6iNQDvrzpUqa+DiIg4p0oXo5YuXcqHH37IzJkzAUhLS2Po0KGYTCYWL15s73wiIkVOpmTz5Nc7AbhvYAv6twpycCIREZHqFR7oRYtgb6w2g/UxiRU+7/MNcaTn5NOmkQ+XtwupxoQ149ouTWgV4kNKVh6frI11dBwREblIlS5GtWzZksWLF/Pcc8/x5ptvMmzYMNzc3Pjll1/w9vau1LWmTZuGyWQq9tGuXbsyx3/44YcMHDiQBg0a0KBBA6644go2b95c2acgIrWQzWbw94U7OJuZR1QTP/4+rK2jI4mIiNSIwtlRqw5UrBiVlWvlk3VxQMEOemZz7Z0VVchiNvHIudlRH6+J5WxmroMTiYjIxah0MQqgc+fO/Pjjj/zzn//Ey8urSoWoQh07diQ+Pr7oY+3atWWOXblyJaNGjWLFihVs2LCB8PBwhg0bxvHjx6t0bxGpPT5cc4h1MUl4ulqYdXs33Fyq9O1LRESk1hlc2DfqwGkMw7jg+AW/HyE5I5fwQE+u6RxW3fFqzNVRYbQL9SUtJ58P1xxydBwREbkIFdqKolu3bqWuM3d3d+fEiRP079+/6Ni2bdsqF8DFhdDQ0AqN/eKLL4p9/tFHH/H111/z66+/Mnbs2ErdV0Rqj13HU3h96X4Apo7sQMtgHwcnEhERqTm9WwTiZjFz/GwWhxIzyv13MDffxoerCwo19w9qiYul7rx5YzabeGxoG+77fCtz1sUxvn8kDX3cHR1LRESqoELFqOuvv77aAkRHR9O4cWM8PDzo27cvL730Es2aVWyb9szMTPLy8ggMDCxzTE5ODjk5OUWfp6amApCXl0deXtWaHxaeV9Xz7UU5nC+HM2Soazkyc/P52/xt5FkNhnUI4cauoZW+Xl36etSFDMqhHM6eQTmUw9kyuJqgZ/MA1h9M5re9J2kWEFFmjq+3HedESjbBPm5c37lRtees6a/Hpa0D6dTEjz+Pp/Luimj+MbytQ3KUxRlyOEMG5VAOZ8+gHNWTozLnmoyKzPWtJr/88gvp6em0bduW+Ph4pk+fzvHjx9m1axe+vr4XPP/BBx9kyZIl7N69Gw8Pj1LHTJs2jenTp5c4Pn/+fLy8vC76OYhI9Vpw0MyGBDP+bgZPdrbi7eroRCIiIjXvtxMmvj9soX2AjQfa20odYzPgpR0WErJNXNvMyuVNHPZjfrXac8bE+/ssuJoNnulmxV8b64qIOIXMzExGjx5NSkoKfn5+5Y6tUDHKMIwa2Q727NmzREREMGPGDCZMmFDu2JdffplXX32VlStX0rlz5zLHlTYzKjw8nMTExAt+ccqSl5fHsmXLGDp0KK6ujvvNWDmcL4czZKhLOZbsPsVDC/7AZIK543rSp0XZsyCrM4e9OEMOZ8igHMrh7BmUQzmcMcP+k2lc884GPFzNbHlqCGZsJXL8suskD3+1Ez8PF1ZNGYSPe4UWQVwUR3w9DMPgtg83s/1oCnf2acazI9o5xZ8NqN9/RpVDOWpTBuWonhypqakEBQVVqBhVoX+hOnbsyLPPPsuNN96Im1vZbz1ER0czY8YMIiIi+Mc//lG51EBAQABt2rQhJiam3HGvv/46L7/8MsuXLy+3EAUFfa3c3UuuJXd1db3oF9oe17AH5XC+HM6QobbniE/J4l/f7wEKel4MbNvIITmqgzPkcIYMyqEczp5BOZTDmTJ0bNqARn7unErNYfvxNPo0DyiWwzAM3l8TB8C4fs1p4ONZY9nOz1FTplzZjjs+2sRXvx9j4qWtCD43ddoZ/mw4Sw5nyKAcyuHsGZTDvjkqc16FOhq+9dZbvP7664SGhnLbbbfx2muv8cUXX/D111/z0Ucf8dhjj9GrVy+6du2Kn58fEydOrFLw9PR0Dh48SFhY2bt+vPrqqzz33HMsXryYnj17Vuk+IuLcrDaDx776g5SsPDo39eexoW0cHUlERMShTCYTg1r/b1e9v1odncjuE6l4uloY1z+ypuPVuH4tG9I7MpBcq403f4tmU2wyWxNNbIpNxmqrm8sTRUTqkgrNjLr88svZsmULa9eu5auvvuKLL77g8OHDZGVlERQURLdu3Rg7dix33HEHDRo0qPDNp0yZwsiRI4mIiODEiRNMnToVi8XCqFGjABg7dixNmjThpZdeAuCVV17h2WefZf78+TRv3pyTJ08C4OPjg4+PdtcSqSs+WH2IDYeS8HKzMOv2bri51J2dgERERKpqUJtgFm49xuoDiTwxrHWxx95ZUbCyYFSvZgR61/0mSiaTib8Pa8ut729gweajLNh8FLAwN3oLYf4eTB3ZgeFRZb/BLSIijlWpheQDBgxgwIABdrv5sWPHGDVqFElJSQQHBzNgwAA2btxIcHDBuz5HjhzBbP7fL6GzZ88mNzeXm2++udh1pk6dyrRp0+yWS0QcZ+exs7yxdD8A00Z2JDLI28GJREREnMOAVkGYTLD/VBrxKdlFx7fEJbM5NhlXi4l7B9X9WVGFkjNySj1+MiWbifO2MXtMdxWkREScVPV3NSzHggULyn185cqVxT6Pi4urvjAi4nAZOflMXrCDfJvB1Z1CuaVnU0dHEhERcRoNvN3o0jSAHUfPsjYmicK3a95deRCAm7o3Jcy/ZntFOYrVZjD9hz2lPmYAJmD6D3sY2iEUi7n6N2ISEZHK0doXEXEa//5hD7GJGYT5e/DSDZ1rZBdPERGR2mRQm4IVBGtjEgHYG5/Gb/sSMJvg/sEtHRmtRm2OTS42O+yvDCA+JZvNsck1F0pERCpMxSgRcQo//xnPV1uOYjLBf27rir+X43eSEBERcTaD2wQBsOrAabacNvHiL/sAuLpTWL1a2p6QVnYhqirjRESkZjl0mZ6ICMCJs1n84+udADx4aUv6tGjo4EQiIiLO6WRKNiYgI9fG5zEW4AwAnZv6OzRXTQvx9bDrOBERqVmaGSUiDmW1GTz61Q5Ss/PpEh7AI1e0cXQkERERp7R4VzwPzd+OUcpjL/28j8W74ms8k6P0igwkzN+Dshb0m4Awfw96RQbWZCwREamgShejtm3bxp9//ln0+ffff8/111/PP//5T3Jzc+0aTkTqvvdWHWRTbDLebhZm3dYVV4tq5CIiIn9V2LC7tEJUoek/7MFqK29E3WExm5g6sgNAmQWpqSM7qHm5iIiTqvRvfffffz8HDhwA4NChQ9x+++14eXmxcOFCnnjiCbsHFJG664+jZ/nPsoLvJ9Ou7UjzetTrQkREpDLUsLuk4VFhzB7TnVD/kkvxHr+yLcOjwhyQSkREKqLSxagDBw7QtWtXABYuXMigQYOYP38+n376KV9//bW984lIHZWek8/kBdvJtxmM6BzGzT2aOjqSiIiI01LD7tINjwpj7ZOXMW98T8a2tjKodUGD9w2HkhycTEREylPpYpRhGNhsNgCWL1/O1VdfDUB4eDiJiYn2TScidda0/+4mLimTJgGevHh9J0wmTaMXEREpixp2l81iNtE7MpAeQQbTR7bH1WJiTXQiG1WQEhFxWpUuRvXs2ZPnn3+ezz//nFWrVjFixAgAYmNjadSokd0Dikjd8+POEyzaegyzCf5zW1f8vVwdHUlERMSpqWF3xTRt4Mltl4QDMGPpAQyjfvTQEhGpbSpdjJo5cybbtm3joYce4l//+hetWrUCYNGiRfTr18/uAUWkbjl+NounvinYBGHSkFb1/odmERGRiiivYXfh52rYXeChIa1xczGzOS6ZNdFauSEi4oxcKntC586di+2mV+i1117DYrHYJZSI1E1Wm8GjC3aQlp1P1/AAHr68taMjiYiI1BqFDbun/7CnWDPzUH8Ppo7soIbd54T6e3Bnnwg+XhvLG8sOMLB1kNoBiIg4mUoXowrl5uaSkJBQ1D+qULNmzS46lIjUTbNXxrA5LhlvNwuzbu+Kq6XSkzNFRETqteFRYQztEMqGmASWrtnEsIG96dsqRDOi/mLipS2Zv+kIfxw9y697E7iig9qJiIg4kyrtpjdw4EA8PT2JiIggMjKSyMhImjdvTmRkZHVkFJE6YPuRM/xneTQA/74uioiG3g5OJCIiUjud37C7d2SgClGlCPJxZ1z/5gC8sewANpt6R4mIOJNKz4y6++67cXFx4ccffyQsLExTXkWkVFabwabYZLYmmvDcf5rnftqH1WZwbZfG3Ni9iaPjiYiISB13/6AWzNtwmL3xqfyy6yQjOmsZo4iIs6h0MWrHjh1s3bqVdu3aVUceEakDFu+KP6+fhYW50dsBCPRy4/kbolTEFhERkWoX4OXGhIGRzFwezX+WH2B4VKhmkYmIOIlKL9Pr0KEDiYnalUJESrd4VzwT520r1li1UHJmLutj9P1DREREasb4AZH4e7oSk5DOf/847ug4IiJyTqWLUa+88gpPPPEEK1euJCkpidTU1GIfIlJ/WW0G03/YQ1ldGUzA9B/2YFXfBhEREakBfh6u3D+4BQAzl0eTZ7Vd4Ayxh/PbNWyKTdbPfiJSQqWX6V1xxRUAXH755cWOG4aByWTCarXaJ5mI1DqbY5NLnRFVyADiU7LZHJtM35YNay6YiIiI1Fvj+jXnk7WxHE7K5Outx7i9l3b/rk4l2zVsIczfg6kjOzA8Sn27RKRApYtRK1asqI4cIlIHxKdkVWhcQlrZBSsRERERe/Jyc2Hipa147sc9vPVbDDd0b4K7i8XRseqkwnYNf50HdTIlm4nztjF7THcVpEQEqEIxavDgwdWRQ0RqsdTsPBZsPsL7qw5WaHyIr0c1JxIRERH5nzt6N+OD1Qc5fjaLr34/yti+zR0dqc4pr12Dwf/aNQztoEbyIlKFYhTA2bNn+fjjj9m7dy8AHTt2ZPz48fj7+9s1nIg4t2NnMpmzLo6vfj9Kek4+AGYTlNUWwASE+nvQKzKw5kKKiIhIvefhauGhy1rzzHe7eOu3GG7pEY6nm2ZH2YNhGCRn5PLTn/Fq1yAiFVbpYtSWLVu48sor8fT0pFevXgDMmDGDF154gaVLl9K9e3e7hxQR57Lj6Fk+XHOIxbtOFjWkbB3iwz0DI/F0tTB5wQ6AYu+MFb7/NXVkB70bJiIiIjXutp7hvLeyYHbUvI2HuXdQC0dHsrvzG4c3jE2mb6sQu/zclWe1ceJsFoeTMjmSXPBxOCmDI8lZHE3OLHpTsiLUrkFEoArFqEcffZRrr72WDz/8EBeXgtPz8/O55557eOSRR1i9erXdQ4qI41ltBsv3nuKjNYf4Pe5M0fH+rRpyz8AWDG4djPncDztuLubzGlcWCFXjShEREXEgNxczk69ozROLdjJ71UFG926Gt3uVFoo4pYttHJ6anceRpMJCU2HRKYMjyZmcOJtd7o54JhMEermSlJF3wfuoXYOIQBVnRp1fiAJwcXHhiSeeoGfPnnYNJyKOl5mbz9dbj/Hx2ljikjIBcDGbuLZLYyYMjKRj45LLc4dHhTG0QygbYhJYumYTwwb2tts7cyIiIiJVdWO3JsxeeZDYxAw+XR/HpCGtHB3JLirSOHxYh1BOpmZzOCmTo8mZHE4umNl0JKmg4HQms/xCkoermWaBXuc+vGkW6ElEQ2+aNfSiSYAnrhYzA175jZMp2aX2jQJo5Oeudg0iAlShGOXn58eRI0do165dseNHjx7F19fXbsFExLESUrP5bEMcX2w6wtlzP5z4ebhwR58I7urbnFD/8t/VsphN9I4MJGmvQe/IQBWiRERExOFcLGYeuaI1kxfs4P1VBxnTJwJ/T1dHx7ooF2ocDjBp/nbMQF45s5sAgnzc/ldwauhNRKAXzRp6ERHoRbCvOyZT+T/PTR3ZgYnztmGCUvN4ulrIyrPiU4dmpIlI1VT6u8Btt93GhAkTeP311+nXrx8A69at4/HHH2fUqFF2DygiNWvfyVQ+WhPLf3ecINdqAyA80JMJ/SO5pWd4nZrOLiIiIvXPNZ0b886KGA6cSufjtbE8NrSNoyNdlM2xyeU2DoeCgpWVgtntTRt40qzhuZlNgQUzmwoLUBf7c97wqDBmj+leol1DsI87Gbn5xCVlMv7T3/ns7l5qIC9Sz1X6u83rr7+OyWRi7Nix5OcXNKpzdXVl4sSJvPzyy3YPKCLVzzAM1kQn8uGaQ6yJTiw63r1ZAPcObMGwjtqCV0REROoGi9nEo1e0YeIX2/hkbSzj+jUn0NvN0bGqrKINwade04Gx/ZpX+890ZbVr2H0ihTs+3MTm2GTu+3wLH47tiYerClIi9VWli1Fubm7MmjWLl156iYMHDwLQsmVLvLy87B5ORKpXTr6V/+44wcdrY9l3Mg0Aswmu7BjKPQNb0COigYMTioiIiNjflR1D6djYj90nUnl/9UGeuqq9oyNVWUUbgrcL86uxNxdLa9fQuWkAn46/hDs/3sya6EQemr+N2WN64Gox10gmEXEuVf6b7+XlRadOnejUqZMKUSJO5PwtfTfFJpe688mZjFzeWRHDgFdW8Piinew7mYaXm4Vx/ZqzcsoQZo/poUKUiIiI1Flms4m/DytYnvfZ+rgKzy5yRr0iA2lYzswuExDm7+EUjcN7RATy0dieuLuYWb43gUcW7CD/XFsIEalfKjQz6sYbb+TTTz/Fz8+PG2+8sdyx33zzjV2CiUjlXWhL37jEDD5eG8uircfIyrMCBbuajOsXyehezfD3qt0NPEVEREQqakjbELo1C2D7kbPMXnmQqSM7OjpSlZxKzS7q8/lXhfOgpo7s4DQtF/q1CuK9O3tw39wt/PRnPO6uZl6/uQtmJ8knIjWjQsUof3//op0T/P1LbuMuIo5X3pa+D8zbRpem/uw8noJxbkD7MD/uHRjJNZ0b4+ai6dEiIiJSv5hMJv4+tC1jPt7EFxuPcO/AFjQO8HR0rErJyrVy3+dbSMvOp0mAB/k2g1OpOUWPh573pqQzGdI2hLdGdWfS/G18s+04Hq4WXrg+6oK79YlI3VGhYtScOXNK/X8RcQ4V2dL3j2MpAAxpG8w9A1vQr2VD/YMvIiIi9Vr/Vg3pHRnIpthk3l4Rw4s3dHJ0pAozDIMpi/5g1/FUAr3dWHBfXxoHeJZoHO4sM6L+anhUKDNu7cIjX+1g/qYjeLhYeOaa9vr5VKSeqPR0iKysLDIzM4s+P3z4MDNnzmTp0qV2DSYiFVeRLX0BXr+5M3Pu7kX/VkH6h15ERETqPZPJxN+HtQXg/34/ypGkzAuc4Tze/i2Gn3bG42I28d6YHoQHehU1Du8R9L/G4c7suq5NeOXGzgB8si6WN5YecHAiEakplS5GXXfddcydOxeAs2fP0qtXL9544w2uu+46Zs+ebfeAInJhFW266arleCIiIiLF9IoMZGDrIPJtBm/+Fu3oOBWyeNdJ3lhWULh57voop2hOXlW3XhLOv68r6Nf19ooY3q4lr4GIXJxK/2a6bds2Bg4cCMCiRYsIDQ3l8OHDzJ07lzfffNPuAUXkwgK9yt5B5XwV3fpXREREpD4pnB31zbZjHDyd7uA05dsbn8pj/7cDgHH9mjOqVzPHBrKDsX2b88+r2wHw+tIDfLTmkIMTiUh1q3QxKjMzE19fXwCWLl3KjTfeiNlspk+fPhw+fNjuAUWkfNuPnOG5H/eUO8aZtvQVERERcTZdwwO4on0jbAbMXO68M3OS0nO457MtZOZaGdAqiKdHtHd0JLu5b1BLHr2iDQDP/7SXeRv1u6VIXVbpYlSrVq347rvvOHr0KEuWLGHYsGEAJCQk4OfnZ/eAIlK6jJx8pv+wmxtnr+dAQjo+7gX7Efy1M4AzbukrIiIi4mweG1pQCPnhjxPsO5nq4DQl5ebbmDhvG8fPZtG8oRdvj+6Gi6VutWB4+PJWPDC4JQBPf7eLRVuPOTiRiFSXSn/3evbZZ5kyZQrNmzend+/e9O3bFyiYJdWtWze7BxSRklbsT2DYf1YzZ10chgE3dmvC6ieG8N6Y7oT6F1+KF+rvwewx3Z1uS18RERERZ9KhsR8jOhX8vPSfZc7VSNswDKb+dxeb45LxdXfho7t6ElDBNg21iclk4snhbRnXrzkATyz6gx93nnBsKBGpFi6VPeHmm29mwIABxMfH06VLl6Ljl19+OTfccINdw4lIcUnpOfz7xz18v6PgH+WmDTx54YZODG4TDMDwqDCGdgitNVv6ioiIiDiTR4e25pdd8SzZfYo/j6XQqam/oyMBMHfDYb7cfBSTCd4c1Y1WIb6OjlRtTCYTz17Tgew8Kwt+P8ojC3bg4WLhig6NHB1NROyoSvM6Q0ND6datG2azmdTUVL777jt8fX1p166dvfOJCAXvhn2z7RhXzFjF9ztOYDbBPQMiWfrooKJCVKHatqWviIiIiLNoFeLL9V2bAPDGsv0OTlNgXUwi/z7XH/Qfw9sxpF2IgxNVP7PZxAs3dOK6ro3Jtxk8+MU21kSfdnQsEbGjShejbr31Vt5++20AsrKy6NmzJ7feeiudO3fm66+/tntAkfruaHImYz/ZzGP/9wdnMvNoF+rLtw/25+lrOuDlVunJjSIiIiJSjslXtMZiNrFy/2m2Hk52aJa4xAwe/GIbVpvBjd2acN+gFg7NU5MsZhNv3NKF4R1DybXauHfuFjYdSnJ0LBGxk0oXo1avXs3AgQMB+PbbbzEMg7Nnz/Lmm2/y/PPP2z2gSH2Vb7Xx0ZpDDPvPatZEJ+LmYuaJ4W354W8D6BIe4Oh4IiIiInVSRENvbunRFIA3ljqud1Rqdh73zN1CSlYeXcMDePHGTphM9WvGu4vFzJujujGkbTDZeTbGf/o724+ccXQsEbGDShejUlJSCAws2B5+8eLF3HTTTXh5eTFixAiio513G1SR2mT3iRRueHc9z/+0l6w8K31aBLLkkUE8eGkrXOvYrikiIiIizuZvl7fGzWJm/cEk1sck1vj9rTaDyV9uJyYhnVA/Dz64swcerpYaz+EM3FzMzB7Tg34tG5KRa+WuTzaz63iKo2OJyEWq9G+14eHhbNiwgYyMDBYvXsywYcMAOHPmDB4eHhc4W0TKk51n5ZXF+7j27XX8eTwFXw8XXrmpE1/e24fIIG9HxxMRERGpF5oEeDKqVzgAbyw7gGEYNXr/V5fsY8X+07i7mPlgbA9C/Or371kerhY+HNuTnhENSM3OZ+wnmzlwKs3RsUTkIlS6GPXII49wxx130LRpUxo3bsyll14KFCzf69Spk73zidQb6w8mMnzmamavPIjVZnB1p1B+fWwwt13SrN5NyRYRERFxtElDWuHuYmbr4TOsPFBzzbO/2XaM91cdAuC1W7rQuWlAjd3bmXm7u/DJ3ZfQuak/yRm53PHRJmITMxwdS0SqqNLFqAcffJANGzbwySefsHbtWszmgku0aNFCPaNEqiAlM48nF+1k9IebiEvKpJGfOx/c2YN379C7YCIiIiKOEuLnwdi+EQDMWFozs6O2HznDP775E4BJQ1pybZfG1X7P2sTPw5W543vRLtSX02k53PHhRo4mZzo6lohUQZWaz/Ts2ZMbbrgBHx+fomMjRoygf//+dgsmUtcZhsHPf8Zz+YxVfLXlKABj+jRj2WODGdYx1MHpREREROSBwS3xcrPw5/EUlu45Va33OpmSzf2fbyU338bQDo34+9C21Xq/2irAy4159/SmZbA3J1KyueOjTZxMyXZ0LBGppArtC//YY4/x3HPP4e3tzWOPPVbu2BkzZtglmEhdFp+SxTPf7Wb53oIfaloGe/PyTZ25pHmgg5OJiIiISKGGPu6M7x/J2ytimLH0AEPbN8Jstn/7hOw8K/d9voWEtBzaNvLlP7d1rZb71BVBPu58cU8fbn1/A0eSMxn90Ua+uq8vwb7ujo4mIhVUoWLU9u3bycvLK/r/sqivjUj5bDaDLzYd5pXF+0nPycfVYmLipa2YNKQl7i71c4cUEREREWd278AWfLYhjv2n0vjxz3i7L50zDIMnFu1k57EUGni58tFdPfFxr9CvafVaqL8HX9zTm9ve38Ch0xnc+fEmFtzXhwAvN0dHE5EKqNAyvRUrVhAQEFD0/2V9/Pbbb5W6+bRp0zCZTMU+2rVrV+45CxcupF27dnh4eNCpUyd+/vnnSt1TxFFiEtK49f0NPPP9btJz8unWLIAf/zaQx4a2USFKRERExEn5e7ly78AWAMxcfoB8q82u13935UH++8cJXMwm3r2jB+GBXna9fl0WHujFF/f2IdjXnX0n0xj7yWZSs/McHUtEKqBKPaPsqWPHjsTHxxd9rF27tsyx69evZ9SoUUyYMIHt27dz/fXXc/3117Nr164aTCxSOqvNYFNsMlsTTWyKTcZqK2hymZtvY9byaK6etZYth8/g7WZh+rUdWfRAP9qG+jo4tYiIiIhcyN39m9PAy5VDpzP4bscJu1132Z5TvL50PwDTru1I35YN7Xbt+iIyyJv59/Qm0NuNncdSuHvO72Tk5Ds6lohcQKXnf2ZnZ/PWW2+xYsUKEhISsNmKvzOwbdu2ygVwcSE0tGLNmmfNmsXw4cN5/PHHAXjuuedYtmwZb7/9Nu+9916l7itiT4t3xTP9hz3Ep2QDFuZGbyHM34MxfSL4fsdxDpxKB+CydiE8d30UTQI8HRtYRERERCrM18OV+we35OVf9jHr1wNc26Uxbi4X977+/pNpPLJgO4YBd/aJYEyfCDulrX9aN/Jl7vhejP5wI1sPn+HeuVv4ZNwluFrMRW8WN4xNpm+rECzqxSXiFCpdjJowYQJLly7l5ptvplevXhfdJyo6OprGjRvj4eFB3759eemll2jWrFmpYzds2FCigfqVV17Jd999d1EZRC7G4l3xTJy3jb9u9hufks1rSwre6Wro7ca0aztyTecw9VYTERERqYXG9o3gozWxHE3OYuHWo9zRu+rFo+SMXO6Z+zsZuVb6tmjIsyM72DFp/RTVxJ/PxvdizEebWH8wiZtmrycpPYeTqTmc/2bx1JEdGB4V5ui4IvVepYtRP/74Iz///DP9+/e/6Jv37t2bTz/9lLZt2xIfH8/06dMZOHAgu3btwte35PKlkydP0qhRo2LHGjVqxMmTJ8u8R05ODjk5OUWfp6amApCXl1fUlL2yCs+r6vn2ohyOz2G1GUz77+4Shajzebqa+fGhvgT5uJOfXzNThuvza6Iczp9BOZTD2TMoh3I4ewblcEwOVxM8MKg5z/+8n7d+jea6To1wdy3e97MiOfKsNibO28rR5CzCG3gy67ZOYLOSZ7PaJWd9ek3+KirMhw/u7Ma4T7ey+0RqicdPpmQzcd423rq9C1d2bFTKFapPfX5dnDGDclRPjsqcazIMo7zfo0vo0KEDCxYsoHPnzpUOdiFnz54lIiKCGTNmMGHChBKPu7m58dlnnzFq1KiiY++++y7Tp0/n1KlTpV5z2rRpTJ8+vcTx+fPn4+Wl5oBycaJTTLy958LNxx/qYKW1f6X+qomIiIiIk8mzwfPbLZzNNXFjcyuDwyr/893/HTKz7pQZd4vBo1FWwvQriV3ZDHh6i4WMfIDSViQYBLjB1O5WtGJPxL4yMzMZPXo0KSkp+Pn5lTu20jOj3njjDZ588knee+89IiLsu645ICCANm3aEBMTU+rjoaGhJYpOp06dKrfn1FNPPVVsaV9qairh4eEMGzbsgl+csuTl5bFs2TKGDh2Kq6trla5hD8rh+Bw/7IyHPX9ecFyLjl25unPNTQeuz6+Jcjh/BuVQDmfPoBzK4ewZlMOxOTIbHeXZ/+5ldaIn0+4ciKfb/96YvFCOLzYfZd2GvZhMMOv2blzeLsTu+erja3K+TbHJZGzcUs4IE2dzIbhDH3pHBtZYrvr+ujhbBuWonhyFK9EqotLFqJ49e5KdnU2LFi3w8vIqETI5ObmylyySnp7OwYMHufPOO0t9vG/fvvz666888sgjRceWLVtG3759y7ymu7s77u7uJY67urpe9Attj2vYg3I4LkdYgHeFxznia1MfXxPlqD0ZlEM5nD2DciiHs2dQDsfkuL1Xcz5cG8fR5Cy+3HKc+we3rFCO9QcTef6nfQA8fmVbhndqUq0569Nrcr6kzIq1xUjKzNfP5w7IYbUZbCtsKn8szSmaytf318SeOSpzXqWLUaNGjeL48eO8+OKLNGrU6KKaMU+ZMoWRI0cSERHBiRMnmDp1KhaLpWgZ3tixY2nSpAkvvfQSAJMnT2bw4MG88cYbjBgxggULFrBlyxY++OCDKmcQuRi9IgPxcXchvYztY01AqL8HvWrwXRcRERERqT5uLmYmX96GKQv/4L1VBxnduxm+HuX/AnYkKZMHv9hGvs3g+q6NmVhKAUvsI8TXw67jxH7K2oFcTeXrp0oXo9avX8+GDRvo0qXLRd/82LFjjBo1iqSkJIKDgxkwYAAbN24kODgYgCNHjmA2/2/L1H79+jF//nyefvpp/vnPf9K6dWu+++47oqKiLjqLSFXMWRdbbiEKYOrIDg6v9ouIiIiI/VzftTHvrozh0OkM5qyL4+HLW5c5Ni07j3vm/s7ZzDy6NPXn5Zs6a3flatQrMpAwfw9OpmSXuclQkI+b3iyuYWXtQF7YVH72mO4qSNUzlS5GtWvXjqysLLvcfMGCBeU+vnLlyhLHbrnlFm655Ra73F/kYny+IY7nf9oLwDWdw9h6+My5Kn+BUFX5RUREROokF4uZR65ow8NfbufDNYe4q29z/L1Kzo6y2Qwe/WoHB06lE+Lrzvt39sTD9cKb30jVWcwmpo7swMR52zBBqQWp1Ox8Vu5P4PL2NbujXn1ltRlM/2FPqa+FQcGb+NN/2MPQDqF6E78eMV94SHEvv/wyf//731m5ciVJSUmkpqYW+xCpD/7v96M88/1uAB68tCVvjerG2icvY974noxtbWXe+J6sffIyFaJERERE6qhrOoXRtpEvadn5fLjmUKljXl+6n+V7E3BzMfPB2J6E+mtpWE0YHhXG7DHdS3y9G/m50y7Ul9x8G/fO3cJn6+McE7Ce2RybXOxN+78ygPiUbDbHVr3/tNQ+lZ4ZNXz4cAAuv/zyYscNw8BkMmG1Wu2TTMRJfbf9OE9+sxOACQMiefzKtphMJiwm6B0ZSNJeg96Rgarqi4iIiNRhZrOJx4a14f7Pt/LJulju7t8cP/f/vdf//Y7jvLvyIACv3tSZruEBDkpaPw2PCmNoh1A2xCSwdM0mhg3sTd9WIdgMg6e/3cVXW44y9b+7OZyUyb9GtNfP7tUoIa3sQlRVxkndUOli1IoVK6ojh0it8NPOeB77vx0YBozp04ynR7TXmn8RERGRempYh0Z0auLPn8dTeHdlDEPaBLE10cTZzUd54eeCnfMeGNyS67tV7855UjqL2VTizWILJl6+qRPNg7x5ZfE+PlkXy5HkTN4c1RUvt0r/eiwVoKbyUppK/20bPHhwdeQQcXrL9pxi8oLt2Ay4tWdT/n1tlApRIiIiIvWYyVQwO+ruOb/z8do4Pl4bB1gguqCvaKcmfjx+ZVuHZpSSTCYTEy9tSbNALx79vx0s33uKW9/fwMd3XUIjPxVE7K2wqXx5S/XCtAN5vVPhnlGvvvpqscbl69atIycnp+jztLQ0HnzwQfumE3ESK/cnMOncdrzXdW3MSzd2xqypvCIiIiL1XnZu2W1Kdh1PZdmekzWYRipjROcwvry3D4Hebuw6nsoN76xjb7z6INubxWxieFT5zeLv7t9cSyXrmQoXo5566inS0tKKPr/qqqs4fvx40eeZmZm8//779k0n4gTWxyRy/+dbybXauCoqlDdu6aJvlCIiIiKC1Wbw7x/3lDtm+g97sNpK20dMnEGPiAZ892B/WgZ7cyIlm1ve28DK/QmOjlWnHEnKZOGWgtqBj3vxxVnuLgUlif/bcoyscgq7UvdUuBhlGEa5n4vURb/HJTPhsy3k5Nu4on0Is27vhoul0ptQioiIiEgdpF3C6oZmDb34ZmJ/+rZoSHpOPhM+28IXmw47OladkGe18fCC7aTn5HNJ8wZsffqKEjuQB/u6E5OQzku/7HV0XKlB+q1apAzbj5zh7jm/k5VnZVCbYN65oztuLvorI//f3n1HR1mnfRj/TjoJkITQQu81BEKRvrLSUVwBKQIKiAUWpa2LDQUUXRVF3deCC4rrKsoq2FYsuOqiIFJD6E06gQCBJEBC2v3+gRkTaoBpkOtzjufIZJK5Mpl5MnPneX4PAADAaZwl7NoRHhqof955nW5tVkk5uaZHP16npxdsVC57tV2Rv/93q+L3HFOJkAC92L+JggP91bJ6KTUrfXpR+TIlgvVC38aSpHd+3qX/bjzo5WJ4Cu+sgXNYty9Fd7y1TMdPZat1jSi9MbiZggP8vZ0FAAAAH8JZwq4tQQF+mnZrrB7oUkeS9I9Fv+rP763i8LHLtPTXI3rl+22SpKd7NVKlyNBzXu8PdcpoeLvqkqQJHyXoUNqpc14P15ZLOpverFmzVLx4cUlSdna23n77bZUuXVqSCqwnBVzNNh1I1e1v/qK0jGw1rxqpWUOaq1gQgygAAAAUlHeWsAMpGTrX/jMOSeU5S9hVxeFw6L4baqtyqVD99cMEfbX+gBL/8bNmDmnOUPESpJzM0ri58TKTbm1WST0bV7jg9f/ata4WbzusTQfS9NeP1mj20BacufwaV+hhVJUqVTRz5kznv8uXL69//etfZ10HuJptSzquwbN+0dGTWWpcOUKzh7VQWPAlzWwBAABQRPj7OTSpZwONfHeVHFKBgVTe2+hJPRtw8pur0J+aVFSFiGK6550VWrM3Rb1eXaLZw1qoTrkS3k7zeWamhz9OUGJKhqpFhWryzQ0v+jkhgf56eUCcer7yk37YfEjv/LxLQ9pUc38svKbQh+nt3LlTO3bsuOh/wNVq5+ETGjhzqQ4fz1SD6JJ6Z9h1KhES6O0sAAAA+LBuMdF6fXBTlQ8vuNdM+fAQvT64qbrFRHupDFeqRbVSmv/ntqpeOkz7jqWrz2tL9NPWw97O8nkfrtirBWsPKMDPoZcHxJ11Br3zqVu+hB7pXk+S9PSCjdpykKOvrmWsGQVI2nv0pAbN+kVJaadUp1xxvXtXS4WHMogCAADAxXWLidZPD95w1lnCGERd/aqXDtP8kW10XbVSSjuVraGzl2nu8t3ezvJZ2w8d16TP1kuS/tKlrhpXjrikzx/Sppqur1NGp7JzNfr91TqVzXpd1yqGUSjyDqRkaODMX7TvWLpqlAnTe3e1UqmwIG9nAQAA4Cri7+cocJYwDs27dkSGBelfd12nW5pUUHau6cF5a/XsV5s4094ZMrNzNfaDeKVn5ah1jSjd+4cal/w1HA6HpvWNVVRYkDYdSNO0rza7oRS+gGEUirSktAwNnLlUu5NPqkqpUM25q5XKlAj2dhYAAAAAHxIc4K8X+zfRmI61JUmv/7Bd97+/WhlZ7LmT54WFm7V2X4oiQgM1vX9j+V3mQLZsiRA9d2usJGnWTzv049ZDrsyEj2AYhSIr+USmBs/6Rb8ePqGKEcU05+6WZx3rDwAAAADS6b12xnWuo+n9GivQ36Ev1ibqtplLdfj4KW+ned1PWw/rjf/9Kkl6pnesosOLXdHX61i/nAa3On2CtL/8e42ST2RecSN8C8MoFEkpJ7M0eNYv2nLwuMqVDNacu1uqUmSot7MAAAAA+LjeTSvpX8NbKrxYoFbvPqZery3WtqSiu9h28olMjf93vCRpYMsq6hZT3iVf99EeDVSzTJiS0k7poXkJMuOwyGsJwygUOWkZWbrjrV+0ITFVpYsHa87drVQ1KszbWQAAAACuEq1qRGn+n9uoSqlQ7UlOV+/XlmjJ9qJ3pj0z04SPEpSUdko1y4TpsRsbuOxrFwvy18sD4hTo79A3Gw5q7vI9Lvva8L5CD6OysrI0YcIE1apVS9ddd53eeuutAh8/ePCg/P39XR4IuNKJU9kaNnu51uxNUWRooN67q6Vqlinu7SwAAAAAV5maZYrr4z+3UbOqkUrNyNaQt5bpo5V7vZ3lUe/9slvfbjyoIH8//f22OBULcu1MIKZiuP7ata4kacrnG/TroeMu/frwnkIPo5566im98847GjFihLp06aLx48fr3nvvLXAddpuDL0vPzNHwfy7Xil1HVTIkQP8a3lJ1y5fwdhYAAACAq1RU8WC9d1dL3RQbrawc0wMfrtH0bzYXiffGWw+m6cn/bJAkTehWVw0rhLvldu5qV0NtakYpPStHYz6IV2Z2rltuB55V6GHUe++9p1mzZumBBx7Q1KlTtWLFCn333XcaNmyY84nmcHD6UvimjKwc3fOvFVr6a7KKBwfon3dep5iK7tlYAgAAACg6QgL99fcBcbrvj7UkSX//bpvGzo13nmkvJ9f0y45krTzs0C87kpWTe/UPqjKycnT/+6t1KjtXf6hTRne2re622/Lzc2h6vyYKLxaotftS9NK3W9x2W/CcQg+j9u3bp5iYGOe/a9WqpR9++EFLlizR7bffrpwcTmkJ35SZnav75qzSj1sPq1igv2YPa6G4KpHezgIAAABwjfDzc+iBrnX13K2xCvBz6NP4/br9zV/04Yo9avfsdxr81gq9s9Vfg99aoXbPfqev1iV6O/mKPPvVJm06kKaosCA93zdWfn7u3TGlfHiInundSJL0+v+2a+mvR9x6e3C/Qg+jypcvr+3btxe4rGLFivr++++1fPlyDR061NVtwBXLzsnVmA9W69uNSQoO8NObQ5qrRbVS3s4CAAAAcA3q17yy3rnzOpUICdDynUf1148SlJiSUeA6B1IyNPLdVVftQOr7zUmavXinJGla31iVLRHikdvt3iha/ZpXkpk0fm68Uk5meeR24R6FHkbdcMMNmjNnzlmXV6hQQd9995127Njh0jDgSuXkmv7y4Rp9ue6Agvz99MbtzdSmVmlvZwEAAAC4hrWpVVofjWgt//PsLJR3kN6UzzdcdYfsHUo7pb9+uEaSNLRNNd1Qr5xHb39Sz4aqFhWq/SkZevSTtUViba5rVaGHUY899pj69et3zo9VrFhR//vf/846wx7gLbm5pofmJejT+P0K8HPo1UFN1aFuWW9nAQAAACgCkk9kKecCcxKTlJiSoWU7kj3WdKVyc08v0H74eKbqliuhh7rX83hDWHCAXhoQJ38/h/6TkKiPV+/zeANco9DDqKpVq6pr167n/XiFChU0ZMgQl0QBlyr/ooBLfz2iRz9Zqw9X7pWfQ/r7bXHq3MCzE3sAAAAARVdSWsbFr3QJ1/MFby/Zqf9tOaTgAD/9/bY4hQT6e6WjSeUIjetUW5L0+KfrtfvISa904MoEXOonfPjhh3r//fe1ZcvpFezr1KmjgQMH6tZbb3V5HFAYX61L1JTPN/x2LLa/3tm60vmx6f2aqEejaO/FAQAAAChyCruOkqfWW7pSGxNT9cyXmyRJE2+sr7rlS3i1Z2SHWvrflkNavvOoxs5drX/f21oB/oXe1wY+oNA/rdzcXPXv31/9+/fXhg0bVKtWLdWqVUvr169X//79NWDAAI7XhMd9tS5RI99dddaigHlCAtkgAQAAAPCs66qXUnR4iC50jrmQAD9VLx3msabLlZ6Zo9Hvr1ZmTq461S+rwa2qejtJ/n4Ovdi/iUoEB2jV7mN65ftt3k7CJSr0O/WXX35Z3377rT777DNt2rRJn3zyiT755BNt3rxZH3/8sRYuXKiXX37Zna1AATm5pimfb9D5RqAOXZ2LAgIAAAC4uvn7OTSpZwNJOu9AKiM7V91fXqT/JOz3XNhleGrBBm1NOq4yJYL1bJ9YORwXGrF5TqXIUE3tFSNJ+vt/t2rlrqtn/S1cwjBq9uzZmjZtmm666aazPnbzzTfrueeeYwFzeNSyHcnn3SNKujoXBQQAAABwbegWE63XBzdV+fCCh+JFh4fokR71VD+6pI6ezNJ9c1Zr1HurdOT4KS+Vnt836w/o3aW7JUnT+zVWVPFgLxcV9KcmFXVLkwrKNWns3HilZWR5OwmFVOhh1NatW9WpU6fzfrxTp07aunWrS6KAwkhKvfYWBQQAAABw7egWE62fHrxB797ZXHfUztG7dzbXTw/eoHv+UFOfjmqr0R1ry9/PoS/WJqrLi4v05dpEbyc7HUzN0IPzEiRJ9/yhhtrXLuPlonN74pYYVYwopj3J6Zr82QZv56CQCj2MKlasmI4dO3bej6empiok5OpYfA1Xv8SUdP3z552Fuu7VsiggAAAAgGuPv59DLauXUrPSppbVS8nf7/RhbkEBfhrfuY4+HdVW9cqX0JETmRr53ird//5qHT2R6dXm3FzT+H/H6+jJLDWsUFIPdKnr1Z4LKRkSqJcGNJGfQ5q3aq8+X+Pbhz3itEIPo1q3bq3XX3/9vB9/9dVX1bp1a5dEAeeTm2t675dd6jJ9kVbtPnbB6zp0ehfY66qX8kgbAAAAAFyqmIrh+vS+trrvj7Xk7+fQ52v2q/OLi/TN+gNea5r5469avO2IigX66++3xSkowLdPDNWiWind98dakqRHP16rfcfSvVyEiyn0I+rRRx/Vm2++qX79+mnZsmVKTU1VSkqKli5dqr59++qtt97So48+6s5WFHG/HjquATOX6tGP1yntVLaaVI7QYzc1kENnLwqY9+9JPRs4//IAAAAAAL4oOMBfD3Stq/kj26h22eI6fPyU7vnXSo2bG69jJz27l9TavSma9vVmSaffT9UsU9yjt3+57u9YW00qRyg1I1vj58ZzIisfV+hhVJs2bTR37lx9//33at26tSIjI1WqVCm1bdtW33//vd5//321bdvWna0oorJycvXaD9vU7eUftWxHsooF+uuxmxpo3sg2Gt6u+jkXBSwfHqLXBzdVt5hoL1UDAAAAwKVpXDlCn9/fTiOuryk/h/Tx6n3q8uIi/XfjQY/c/olT2Rr9wWpl55q6x5RX/xaVPXK7rhDo76eX+jdRaJC/ftmRrDcWbfd2Ei4g4FKu3KtXL3Xt2lVff/21c7HyOnXqqEuXLgoNDXVLIIq2tXtT9OC8BG1ITJUkta9dWk/3aqTKpX5/vHWLiVbnBuX187YkffPjL+rSvqVa1yrLHlEAAAAArjohgf56qHs9dW1YTn/5cI1+PXRCw/+5Qn2aVtLjPRsovFig2277ic83aMfhE4oOD9HfejeSw3F1vaeqVjpMk29uqAkfJWj6N1vUrlZpxVaK8HYWzuGShlGSFBoaql69ermjBZcgJ9f0y45krTzsUNSO5Gtu+JKemaOXvt2iWT/tUE6uKSI0UI/d2EC9m1Y85wYxb1HAIxsLLgoIAAAAAFejuCqRWjC6vaYv3KKZP/6qeav2avG2w/pbn0b6Y92yLr+9LxISNXfFHjkc0ov9mygiNMjlt+EJfZtV0g+bk7Rg7QGN/SBe/xndTqFBlzz6gJsV+jC97777Tg0aNFBqaupZH0tJSVHDhg31448/ujQO5/bVukS1e/Y7DX5rhd7Z6q/Bb61Qu2e/01frfOc0oFdiyfbD6vbyIr2x6Ffl5Jpuio3WwnHXq0+zSlfdZB4AAAAALldIoL8e6VFfH41oreqlw3QgNUPDZi/Xgx8lKDUjy2W3s+9Yuh6enyBJ+nOHmmpVI8plX9vTHA6Hnu7VSOVLhujXwyf05H82ejsJ51DoYdRLL72ku+++WyVLljzrY+Hh4br33ns1ffp0l8bhbF+tS9TId1cpMSWjwOUHUjI08t1VV/VAKiU9Sw/NS9DAmb9o15GTKl8yRDPvaK5XBjZVmRLB3s4DAAAAAK9oVrWUFoxurzvbVpfDIc1dsUddX1ykRVsOXfHXzsk1jZsbr9SMbDWuHKGxneq4oNi7IkKDNL1/Yzkc0vvLdutrL56ZEOdW6GHUmjVr1K1bt/N+vEuXLlq5cqVLonBuObmmKZ9v0LnOCZB32ZTPN1yVZw34at0BdZ7+P32wfI8kaVDLKvpm/B/UuUE5L5cBAAAAgPcVC/LX4z0baO49rVU1KlSJKRm6461lenj+Wh0/lX3ZX/f1H7Zp2Y5khQX56+8DmijQv9BjAp/WpmZp3fOHGpKkh+Yl6GBqxkU+A55U6EfZwYMHFRh4/oXSAgICdOjQlU9lcX7LdiSftUdUfiYpMSVDy3Ykey7qCiWlZWjkuys14t2VSko7pRqlwzT3nlZ6qlcjlQxx38J8AAAAAHA1uq56KX05pr2Gtqkm6fSeP11fXKTF2w5f8tdatfuoXvz29MnJnrwlRlWjwlyZ6nV/6VxXMRVL6ujJLD3w4RrlXoU7blyrCj2MqlixotatW3fejyckJCg6OtolUTi3pLTCTXInfrJW/1yyU0k+PPk1M/17+R51euF/+nLdAfn7OfTnDjW1YEx7tbyKj08GAAAAAHcLDQrQ5Jsb6v27W6lSZDHtO5auQbN+0cRP1upEIfeSSsvI0pgPVisn13Rz4wrqFVfRzdWeFxTgp5f6xykk0E8/bj2stxbv8HYSflPoYVSPHj302GOPKSPj7AFHenq6Jk2apJtuusmlcSiobImQQl1v+6ETmvTZerX823/Vb8bPmr14hw5cYI8qT9t95KQGv/mLJsxLUGpGtmIqltRn97XVhG71FBLo7+08AAAAALgqtK4Zpa/H/kG3t6oqSXp36W51e3mRft5+5KKfO+nT9dqTnK5KkcU0tVfMNXuyqFpli2vijQ0kSc99tVkb9p99UjZ4XqHPbzhx4kTNnz9fderU0X333ae6detKkjZt2qRXX31VOTk5evTRR90WitO7Y0aHh+hASsY5141ySCpTIlh3ta+uL9cd0Ordx7RsZ7KW7UzWlM83qHnVSHVvFK0ejcorOryYp/OVnZOr2Yt36oWFm5WRlavgAD+N71xHw9tVV8A1clwyAAAAAHhSWHCAnrwlRt1iymvCRwnak5yu22Yu1dA21TShW12FBp1+25+Ta/plR7JWHnZo48Ktmr96n/wc0ssDmlzzS6QMallFP2xO0rcbkzR27mp9dl87sRuEdxV6GFWuXDktWbJEI0eO1MMPPyyz0+MQh8Ohrl276tVXX1W5ciw27U7+fg5N6tlAI99dJYdUYCCVN8N+4k8N1S0mWvf8oab2H0vXl+sOaMHaRK3cdVQrfvvvyf9sUNMqEerRKFrdG0WrYoT7B1MbE1P14LwEJexNkSS1rhGlv/VupGqlr61jkgEAAADAG9rWKq2vxrbX0ws26f1lu/X2kp36fnOSpt3aWMknTmnK5xt+W4PYX9p6+nC1Ho2i1axqKe+Ge4DD4dCzfWLV9aUfteXgcT29YKO61C+jlYcditqRrNa1ysrf79rcM8xXFXoYJUlVq1bVggULdPToUW3btk1mptq1aysyMtJdfThDt5hovT64ab4NyWnlw0M0qWcDdYv5fd2uChHFNLxddQ1vV10HUjL05bpELVibqBW7jmrV7mNatfuYpn6xUY0rR+jGRuXVPSZalUuFurQ3IytH//fdVr3xv1+VnWsqERKgiTfWV7/mla/Z3UABAAAAwBtKhATqb70bqXtMeT04L0G7jpxUvzd+Pu/1v0hI1E2xiQXeR16roooH6/m+sRo6e7ne+XmX3vl5lyR/vbN1haLP8X4a7nVJw6g8kZGRatGihatbUEjdYqLVuUF5/bwtSd/8+Iu6tG950Ulu+fAQDWtbXcPaVtfB1Ax9te6AvlibqOU7k7VmzzGt2XNMTy/YpNhK4erRKFo9YqJVJerKBlPLdybrwXkJ+vXQidPdDcvriT81VNmShVv7CgAAAABw6f5Qp4y+HvcHPfH5en20ct8Frzvl8w3q3KB8kdgzKCMr55yXH0jJ0Mh3V+n1wU0ZSHnIZQ2j4H3+fg61rF5KRzaaWlYvdUkbjnIlQzSkTTUNaVNNSWkZ+vq3wdSyHclK2JuihL0peubLTYqpWNI5mDrf4XT5jzvO273xZGa2nvtqs/61dJek0+tYPfnb4YMAAAAAAPcrGRKoPk0rX3AYZZISUzK0bEeyWte8ts9qnpNrmvL5hnN+zHR66ZuiNJjzNoZRRVzZEiG6vXU13d66mg6lndLX60+vMbX01yNaty9V6/al6rmvNqtBdEndGBut7jHlVaNMcUnSV+sSCxx3/M7WFYoMDZRJOnYyS5LUv3llPdKjvsJDr+0F8QAAAADA1ySlFe6s6oW93tVs2Y7kAkvdnKkoDeZ8gc+cwuyZZ56Rw+HQ2LFjL3i9l156SXXr1lWxYsVUuXJljRs3ThkZ1/4TxxPKlAjW4FZVNefuVlr+aCc93auR2tUqLX8/hzYkpmra15t1wwv/U7eXFmn0nFUa8e6qs57MR09m6djJLJUuHqQ5d7XUs7fGMogCAAAAAC8oW6JwS6QU9npXMwZzvsUn9oxavny53njjDcXGxl7wenPmzNFDDz2kt956S23atNGWLVs0dOhQORwOTZ8+3UO1RUNU8WANbFlFA1tWUfKJTH2z/vShfEu2H9GmA2nadCDtgp8f4OenljWYJgMAAACAt1xXvZSiw0N0ICWjwNnY8zh0en3h66pf+2fUYzDnW7y+Z9Tx48c1aNAgzZw586Jn5VuyZInatm2rgQMHqlq1aurSpYtuu+02LVu2zEO1RVOpsCANuK6K/jW8pVY82kn3/qHGRT/nQOrp3RsBAAAAAN7h7+fQpJ4NJJ0ePOWX9+9JPRsUiTWS8gZz5/tOHZKii8hgzhd4fRg1atQo3XjjjerUqdNFr9umTRutXLnSOXz69ddftWDBAvXo0cPdmfhNZFiQGlQoWajrsnsjAAAAAHhXt5hovT64qcqHF9zjp3x4SJE6e9yFBnN5ispgzhd49TC9Dz74QKtWrdLy5csLdf2BAwfq8OHDateuncxM2dnZGjFihB555JHzfs6pU6d06tQp579TU1MlSVlZWcrKyrqs7rzPu9zPdxVvdUSFFu5hExUa4NE2X/i5+EIDHXT4egMddPh6Ax10+HoDHXT4egMdvtfRsW5pdajdXku3H9J3P6/UDa2bqVXNMvL3c3i8yZv3Rce6pfV/Axpr6oJNOpD6+5wgvFiAnvpTQ3WsW7pI3R+u7riUz3WY2bkOHXW7PXv2qHnz5lq4cKFzragOHTqoSZMmeumll875OT/88IMGDBigqVOnqmXLltq2bZvGjBmju+++W4899tg5P2fy5MmaMmXKWZfPmTNHoaGhLvt+ipJck6as8texTOncM2VTRJA0qWmOGCoDAAAAAHxJrknbUx36Yb9D6475qWWZXA2slevtrKveyZMnNXDgQKWkpKhkyQsfUeW1YdQnn3yiXr16yd/f33lZTk6OHA6H/Pz8dOrUqQIfk6T27durVatWmjZtmvOyd999V/fcc4+OHz8uP7+zjzo8155RlStX1uHDhy9655xPVlaWFi5cqM6dOysw0HtnivNmx9frD+r+D9ZIUoGF8PJmT/83oLG6Nizn0SZf+Ln4QgMddPh6Ax10+HoDHXT4egMddPh6Ax10+HpDXseLc7/VzM3+qlUmTF+Obuu1Dl+5P660IzU1VaVLly7UMMprh+l17NhRa9euLXDZsGHDVK9ePT344INnDaKk01O2MwdOedc730wtODhYwcHBZ10eGBh4xT9oV3wNV/BGx01NKikgwF9TPt+gxJTf14YqHx6iST0bePW4Y1/4ufhCAx10+HoDHXT4egMddPh6Ax10+HoDHXT4ekO1EqfnCNsOndDJLCk81Hs9vnB/XGnHpXye14ZRJUqUUExMTIHLwsLCFBUV5bz8jjvuUMWKFfW3v/1NktSzZ09Nnz5dcXFxzsP0HnvsMfXs2fOcwyu4V7eYaHVuUF4/b0vSNz/+oi7tW6p1rbIs+AYAAAAA8HnFA6VqUaHaeeSkVu05qj/WLevtpCLDqwuYX8zu3bsL7Ak1ceJEORwOTZw4Ufv27VOZMmXUs2dPPfXUU16sLNr8/RxqWb2Ujmw0taxeikEUAAAAAOCqEVclQjuPnNTqXQyjPMmnhlE//PDDBf8dEBCgSZMmadKkSZ6LAgAAAAAA16SmlSP08er9Wrn7qLdTipSzV/wGAAAAAAAoAuIqh0uS4ncfU06uV87vViQxjAIAAAAAAEVSrbLFVSI4QCcyc7T5QJq3c4oMhlEAAAAAAKBI8vdzqEmVCEniUD0PYhgFAAAAAACKrKZVIiVJq3YxjPIUhlEAAAAAAKDIalb1t2EUe0Z5DMMoAAAAAABQZDWpEiGHQ9p15KQOpZ3ydk6RwDAKAAAAAAAUWSVDAlWnbAlJ7B3lKQyjAAAAAABAkdaUQ/U8imEUAAAAAAAo0pr+dkY9FjH3DIZRAAAAAACgSMtbxDxhb4oys3O9XHPtYxgFAAAAAACKtOqlwxQZGqhT2bnakJjq7ZxrHsMoAAAAAABQpDkcDjWtcnrvqJUcqud2DKMAAAAAAECRxyLmnsMwCgA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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# or explictly mention the name \n",
    "country_name = 'United States' # here , change the name of the country \n",
    "country_data = df[df['Country Name'] == country_name]\n",
    "years = country_data.columns[4:-1] \n",
    "emissions = country_data.iloc[:, 4:-1].values.squeeze()  \n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(years, emissions, marker='o', linestyle='-')\n",
    "plt.title(f'CO2 Emissions for {country_name}')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('CO2 Emissions (kt)')\n",
    "plt.grid(True)\n",
    "plt.xticks(rotation=45)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "mlp",
   "language": "python",
   "name": "mlp"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}