440 final project_1201.ipynb

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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>date</th>\n",
       "      <th>manner_of_death</th>\n",
       "      <th>armed</th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "      <th>race</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>signs_of_mental_illness</th>\n",
       "      <th>threat_level</th>\n",
       "      <th>flee</th>\n",
       "      <th>body_camera</th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>is_geocoding_exact</th>\n",
       "      <th>year</th>\n",
       "      <th>period</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Tim Elliot</td>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>53.0</td>\n",
       "      <td>M</td>\n",
       "      <td>A</td>\n",
       "      <td>Shelton</td>\n",
       "      <td>WA</td>\n",
       "      <td>True</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-123.122</td>\n",
       "      <td>47.247</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015-01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Lewis Lee Lembke</td>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>47.0</td>\n",
       "      <td>M</td>\n",
       "      <td>W</td>\n",
       "      <td>Aloha</td>\n",
       "      <td>OR</td>\n",
       "      <td>False</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-122.892</td>\n",
       "      <td>45.487</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015-01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>John Paul Quintero</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>shot and Tasered</td>\n",
       "      <td>unarmed</td>\n",
       "      <td>23.0</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>Wichita</td>\n",
       "      <td>KS</td>\n",
       "      <td>False</td>\n",
       "      <td>other</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-97.281</td>\n",
       "      <td>37.695</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015-01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>Matthew Hoffman</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>shot</td>\n",
       "      <td>toy weapon</td>\n",
       "      <td>32.0</td>\n",
       "      <td>M</td>\n",
       "      <td>W</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA</td>\n",
       "      <td>True</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-122.422</td>\n",
       "      <td>37.763</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015-01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>Michael Rodriguez</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>shot</td>\n",
       "      <td>nail gun</td>\n",
       "      <td>39.0</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>Evans</td>\n",
       "      <td>CO</td>\n",
       "      <td>False</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-104.692</td>\n",
       "      <td>40.384</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>2015-01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <td>5813</td>\n",
       "      <td>6341</td>\n",
       "      <td>Ellis A. Frye</td>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>62.0</td>\n",
       "      <td>M</td>\n",
       "      <td>B</td>\n",
       "      <td>Culpeper</td>\n",
       "      <td>VA</td>\n",
       "      <td>False</td>\n",
       "      <td>other</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-78.019</td>\n",
       "      <td>38.520</td>\n",
       "      <td>True</td>\n",
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       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5814</td>\n",
       "      <td>6342</td>\n",
       "      <td>Michael Anthony Pena</td>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>shot</td>\n",
       "      <td>undetermined</td>\n",
       "      <td>31.0</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>Lubbock</td>\n",
       "      <td>TX</td>\n",
       "      <td>False</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>-102.030</td>\n",
       "      <td>33.543</td>\n",
       "      <td>True</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020-11</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5815</td>\n",
       "      <td>6338</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-11-27</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>74.0</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Marinette County</td>\n",
       "      <td>WI</td>\n",
       "      <td>False</td>\n",
       "      <td>other</td>\n",
       "      <td>Car</td>\n",
       "      <td>False</td>\n",
       "      <td>-88.065</td>\n",
       "      <td>45.358</td>\n",
       "      <td>True</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020-11</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <td>5816</td>\n",
       "      <td>6340</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-11-27</td>\n",
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       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Wilsonville</td>\n",
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       "      <td>other</td>\n",
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       "      <td>False</td>\n",
       "      <td>-122.834</td>\n",
       "      <td>45.278</td>\n",
       "      <td>True</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020-11</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5817</td>\n",
       "      <td>6339</td>\n",
       "      <td>Cory Donell Truxillo</td>\n",
       "      <td>2020-11-29</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>43.0</td>\n",
       "      <td>M</td>\n",
       "      <td>B</td>\n",
       "      <td>Houma</td>\n",
       "      <td>LA</td>\n",
       "      <td>True</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-90.730</td>\n",
       "      <td>29.602</td>\n",
       "      <td>True</td>\n",
       "      <td>2020</td>\n",
       "      <td>2020-11</td>\n",
       "      <td>1</td>\n",
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       "<p>5818 rows × 20 columns</p>\n",
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      ],
      "text/plain": [
       "        id                  name       date   manner_of_death         armed  \\\n",
       "0        3            Tim Elliot 2015-01-02              shot           gun   \n",
       "1        4      Lewis Lee Lembke 2015-01-02              shot           gun   \n",
       "2        5    John Paul Quintero 2015-01-03  shot and Tasered       unarmed   \n",
       "3        8       Matthew Hoffman 2015-01-04              shot    toy weapon   \n",
       "4        9     Michael Rodriguez 2015-01-04              shot      nail gun   \n",
       "...    ...                   ...        ...               ...           ...   \n",
       "5813  6341         Ellis A. Frye 2020-11-26              shot           gun   \n",
       "5814  6342  Michael Anthony Pena 2020-11-26              shot  undetermined   \n",
       "5815  6338                   NaN 2020-11-27              shot           gun   \n",
       "5816  6340                   NaN 2020-11-27              shot           gun   \n",
       "5817  6339  Cory Donell Truxillo 2020-11-29              shot           gun   \n",
       "\n",
       "       age gender race              city state  signs_of_mental_illness  \\\n",
       "0     53.0      M    A           Shelton    WA                     True   \n",
       "1     47.0      M    W             Aloha    OR                    False   \n",
       "2     23.0      M    H           Wichita    KS                    False   \n",
       "3     32.0      M    W     San Francisco    CA                     True   \n",
       "4     39.0      M    H             Evans    CO                    False   \n",
       "...    ...    ...  ...               ...   ...                      ...   \n",
       "5813  62.0      M    B          Culpeper    VA                    False   \n",
       "5814  31.0      M    H           Lubbock    TX                    False   \n",
       "5815  74.0      M  NaN  Marinette County    WI                    False   \n",
       "5816   NaN      M  NaN       Wilsonville    OR                     True   \n",
       "5817  43.0      M    B             Houma    LA                     True   \n",
       "\n",
       "      threat_level         flee  body_camera  longitude  latitude  \\\n",
       "0           attack  Not fleeing        False   -123.122    47.247   \n",
       "1           attack  Not fleeing        False   -122.892    45.487   \n",
       "2            other  Not fleeing        False    -97.281    37.695   \n",
       "3           attack  Not fleeing        False   -122.422    37.763   \n",
       "4           attack  Not fleeing        False   -104.692    40.384   \n",
       "...            ...          ...          ...        ...       ...   \n",
       "5813         other  Not fleeing        False    -78.019    38.520   \n",
       "5814  undetermined          NaN        False   -102.030    33.543   \n",
       "5815         other          Car        False    -88.065    45.358   \n",
       "5816         other          NaN        False   -122.834    45.278   \n",
       "5817        attack  Not fleeing        False    -90.730    29.602   \n",
       "\n",
       "      is_geocoding_exact  year   period  count  \n",
       "0                   True  2015  2015-01      1  \n",
       "1                   True  2015  2015-01      1  \n",
       "2                   True  2015  2015-01      1  \n",
       "3                   True  2015  2015-01      1  \n",
       "4                   True  2015  2015-01      1  \n",
       "...                  ...   ...      ...    ...  \n",
       "5813                True  2020  2020-11      1  \n",
       "5814                True  2020  2020-11      1  \n",
       "5815                True  2020  2020-11      1  \n",
       "5816                True  2020  2020-11      1  \n",
       "5817                True  2020  2020-11      1  \n",
       "\n",
       "[5818 rows x 20 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#import dataset from WP, convert time format for statistic\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "ps = pd.read_csv(\"fatal-police-shootings-data.csv\")\n",
    "ps['date'] = pd.to_datetime(ps['date'])\n",
    "ps['year'] = ps['date'].dt.year\n",
    "ps['period'] = ps['date'].dt.to_period('M')\n",
    "ps['count'] = 1\n",
    "ps"
   ]
  },
  {
   "cell_type": "code",
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       "      <th>id</th>\n",
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       "      <th>latitude</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Tim Elliot</td>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
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       "      <td>WA</td>\n",
       "      <td>mental_illness_yes</td>\n",
       "      <td>attack</td>\n",
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       "      <td>body_camera_no</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Lewis Lee Lembke</td>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>47.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>White</td>\n",
       "      <td>Aloha</td>\n",
       "      <td>OR</td>\n",
       "      <td>mental_illness_no</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>body_camera_no</td>\n",
       "      <td>-122.892</td>\n",
       "      <td>45.487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>John Paul Quintero</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>shot and Tasered</td>\n",
       "      <td>unarmed</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>Wichita</td>\n",
       "      <td>KS</td>\n",
       "      <td>mental_illness_no</td>\n",
       "      <td>other</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>body_camera_no</td>\n",
       "      <td>-97.281</td>\n",
       "      <td>37.695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>Matthew Hoffman</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>shot</td>\n",
       "      <td>toy weapon</td>\n",
       "      <td>32.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>White</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA</td>\n",
       "      <td>mental_illness_yes</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>body_camera_no</td>\n",
       "      <td>-122.422</td>\n",
       "      <td>37.763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>Michael Rodriguez</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>shot</td>\n",
       "      <td>nail gun</td>\n",
       "      <td>39.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>Evans</td>\n",
       "      <td>CO</td>\n",
       "      <td>mental_illness_no</td>\n",
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       "      <td>5813</td>\n",
       "      <td>6341</td>\n",
       "      <td>Ellis A. Frye</td>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>62.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Black</td>\n",
       "      <td>Culpeper</td>\n",
       "      <td>VA</td>\n",
       "      <td>mental_illness_no</td>\n",
       "      <td>other</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>body_camera_no</td>\n",
       "      <td>-78.019</td>\n",
       "      <td>38.520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5814</td>\n",
       "      <td>6342</td>\n",
       "      <td>Michael Anthony Pena</td>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>shot</td>\n",
       "      <td>undetermined</td>\n",
       "      <td>31.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>Lubbock</td>\n",
       "      <td>TX</td>\n",
       "      <td>mental_illness_no</td>\n",
       "      <td>undetermined</td>\n",
       "      <td>NaN</td>\n",
       "      <td>body_camera_no</td>\n",
       "      <td>-102.030</td>\n",
       "      <td>33.543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5815</td>\n",
       "      <td>6338</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-11-27</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>74.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Marinette County</td>\n",
       "      <td>WI</td>\n",
       "      <td>mental_illness_no</td>\n",
       "      <td>other</td>\n",
       "      <td>Car</td>\n",
       "      <td>body_camera_no</td>\n",
       "      <td>-88.065</td>\n",
       "      <td>45.358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5816</td>\n",
       "      <td>6340</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-11-27</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Wilsonville</td>\n",
       "      <td>OR</td>\n",
       "      <td>mental_illness_yes</td>\n",
       "      <td>other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>body_camera_no</td>\n",
       "      <td>-122.834</td>\n",
       "      <td>45.278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5817</td>\n",
       "      <td>6339</td>\n",
       "      <td>Cory Donell Truxillo</td>\n",
       "      <td>2020-11-29</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>43.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>Black</td>\n",
       "      <td>Houma</td>\n",
       "      <td>LA</td>\n",
       "      <td>mental_illness_yes</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>body_camera_no</td>\n",
       "      <td>-90.730</td>\n",
       "      <td>29.602</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5818 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id                  name        date   manner_of_death         armed  \\\n",
       "0        3            Tim Elliot  2015-01-02              shot           gun   \n",
       "1        4      Lewis Lee Lembke  2015-01-02              shot           gun   \n",
       "2        5    John Paul Quintero  2015-01-03  shot and Tasered       unarmed   \n",
       "3        8       Matthew Hoffman  2015-01-04              shot    toy weapon   \n",
       "4        9     Michael Rodriguez  2015-01-04              shot      nail gun   \n",
       "...    ...                   ...         ...               ...           ...   \n",
       "5813  6341         Ellis A. Frye  2020-11-26              shot           gun   \n",
       "5814  6342  Michael Anthony Pena  2020-11-26              shot  undetermined   \n",
       "5815  6338                   NaN  2020-11-27              shot           gun   \n",
       "5816  6340                   NaN  2020-11-27              shot           gun   \n",
       "5817  6339  Cory Donell Truxillo  2020-11-29              shot           gun   \n",
       "\n",
       "       age gender      race              city state signs_of_mental_illness  \\\n",
       "0     53.0   Male     Asian           Shelton    WA      mental_illness_yes   \n",
       "1     47.0   Male     White             Aloha    OR       mental_illness_no   \n",
       "2     23.0   Male  Hispanic           Wichita    KS       mental_illness_no   \n",
       "3     32.0   Male     White     San Francisco    CA      mental_illness_yes   \n",
       "4     39.0   Male  Hispanic             Evans    CO       mental_illness_no   \n",
       "...    ...    ...       ...               ...   ...                     ...   \n",
       "5813  62.0   Male     Black          Culpeper    VA       mental_illness_no   \n",
       "5814  31.0   Male  Hispanic           Lubbock    TX       mental_illness_no   \n",
       "5815  74.0   Male       NaN  Marinette County    WI       mental_illness_no   \n",
       "5816   NaN   Male       NaN       Wilsonville    OR      mental_illness_yes   \n",
       "5817  43.0   Male     Black             Houma    LA      mental_illness_yes   \n",
       "\n",
       "      threat_level         flee     body_camera  longitude  latitude  \n",
       "0           attack  Not fleeing  body_camera_no   -123.122    47.247  \n",
       "1           attack  Not fleeing  body_camera_no   -122.892    45.487  \n",
       "2            other  Not fleeing  body_camera_no    -97.281    37.695  \n",
       "3           attack  Not fleeing  body_camera_no   -122.422    37.763  \n",
       "4           attack  Not fleeing  body_camera_no   -104.692    40.384  \n",
       "...            ...          ...             ...        ...       ...  \n",
       "5813         other  Not fleeing  body_camera_no    -78.019    38.520  \n",
       "5814  undetermined          NaN  body_camera_no   -102.030    33.543  \n",
       "5815         other          Car  body_camera_no    -88.065    45.358  \n",
       "5816         other          NaN  body_camera_no   -122.834    45.278  \n",
       "5817        attack  Not fleeing  body_camera_no    -90.730    29.602  \n",
       "\n",
       "[5818 rows x 16 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fp = pd.read_csv(\"fatal-police-shootings-data.csv\")\n",
    "fp.loc[fp['signs_of_mental_illness'] == False, 'signs_of_mental_illness'] = 'mental_illness_no'\n",
    "fp.loc[fp['signs_of_mental_illness'] == True, 'signs_of_mental_illness'] = 'mental_illness_yes'\n",
    "fp.loc[fp['race'] == 'A', 'race'] = 'Asian'\n",
    "fp.loc[fp['race'] == 'B', 'race'] = 'Black'\n",
    "fp.loc[fp['race'] == 'H', 'race'] = 'Hispanic'\n",
    "fp.loc[fp['race'] == 'N', 'race'] = 'Native'\n",
    "fp.loc[fp['race'] == 'W', 'race'] = 'White'\n",
    "fp.loc[fp['race'] == 'O', 'race'] = 'Other'\n",
    "fp.loc[fp['gender'] == 'M', 'gender'] = 'Male'\n",
    "fp.loc[fp['gender'] == 'F', 'gender'] = 'Female'\n",
    "fp.loc[fp['body_camera'] == False, 'body_camera'] = 'body_camera_no'\n",
    "fp.loc[fp['body_camera'] == True, 'body_camera'] = 'body_camera_yes'\n",
    "fp = fp.drop(columns=['is_geocoding_exact'])\n",
    "fp.to_csv('fp.csv')\n",
    "fp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Display frequent pattern by word cloud\n",
    "# importing the necessery modules \n",
    "from wordcloud import WordCloud \n",
    "import matplotlib.pyplot as plt \n",
    "import csv \n",
    "  \n",
    "# file object is created \n",
    "file_ob = open(r\"fp.csv\") \n",
    "  \n",
    "# reader object is created \n",
    "reader_ob = csv.reader(file_ob) \n",
    "  \n",
    "# contents of reader object is stored . \n",
    "# data is stored in list of list format. \n",
    "reader_contents = list(reader_ob) \n",
    "  \n",
    "# empty string is declare \n",
    "text = \"\" \n",
    "  \n",
    "# iterating through list of rows \n",
    "for row in reader_contents : \n",
    "      \n",
    "    # iterating through words in the row \n",
    "    for word in row : \n",
    "  \n",
    "        # concatenate the words \n",
    "        text = text + \" \" + word \n",
    "  \n",
    "wordcloud = WordCloud(background_color=\"white\", max_words=20, width=800, height=500,relative_scaling=0.5).generate(text) \n",
    "plt.figure(figsize = (16,9)) #increase the picture's resolution\n",
    "plt.imshow(wordcloud, interpolation=\"bilinear\") \n",
    "plt.axis(\"off\") \n",
    "plt.margins(x=0, y=0) \n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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G4WJmdtyrOKi1e3BICpIgUtBLJEt5IvOEupyucmSqF8M0+BfbHmerv3HFcxjKxvjutXf56ei5Ku+GQNmC67e5cEo2BKEclpAs5YkWMxhzhIOYmuUv+94kXszype7Dq1I8IsUMPx4+yz8MnqgSIgXK16XG7sYl2QGTgq4RV7OkSnl00yRZyvMPA8cRBYGcpi57kxMEAbds58Ote/ja5Vdnx7NakXejA/xWMUutw7PENyxNtlTkUmKMyXlK1KHaTbSswXp8OzFMg7OxYf6m/22OhvsX9S7IgohbtmOTZBRBQjN1CnqJTKlYJZQH7S4eb9y+7DlI0/d5IeFRpHxP/TYnLtmGIsqASVHXSKg5EmoObZ5HcTKf4i/7jlBn9/Bk0w5sKwirU3WNq+kIp2NDvDz6HpIo0uTw4lecZDWVyUKqwkLbl5riral+DNPklfGLjObi2EWZOocXn+JY8JhT05b5NlfNssKsCnqJF4ZO8xe9r5OYJ7AJCPhtznLehigjCiLF6fdMrJhDM68r65FihheHTpMtFfhi12G6ffXLvi5LES6m0UyDC4kx/uTyq5yJDVUoHHZRnl475TDUmXVTmjM3v83F3pq2ZZ9TEkQyWoGUWi3Aigh4lHKOkVO2YRPlWU9RXM2SUHNVCtF4Psmf975Og8PHo41b74oEUd00OBcfoWTqfL33COHida+TTZQI2T2zOVimWX5PRovZitA5KHulfjl2EY9s44tdh2l2BVY0j57UJN/oO8Lrkz1V3g0BgVq7B7/NiUOSMUyTvF4ioeYq9jHdNLmaifCNviOkSnk+3X7AUjzuQgREBET6Myd5M/wdfEodj9R/ngZH14ICuijINDq30ObaNTtmE100ObdimgZpLbpO81ycsXwPcXWMLb4HaXBsnp23gEi3535s4jfKoWBGtspDYnFr2PBKR1LN880rbxGZFrDr7F72h9rp8tbT7g7hUezYBIm0VmAin+RCYoyz8RFGc/HZ7yjoGu9GB2gaPs0/dz6GfwUu5HixbAl6efR8xYtaoJxrsNPfzFZfA01OPz7FCUI5PGGqkKI/HeZCYoye1MSs8qEaGs8PnUYWJf7Z1kcJ2FzLnktBL3E8co0fj5ytUjiCNhe7As3cE2yl3R0qz4VykvloLs6V9BRnY8OM55Pk9RL/OHgKj+JANW7s5ZhBESUebdzKt68enb0WBuasa//DrXuW/V3z6U+HuZIOV8zHLdvYX9O+JmXmdnIpOcFfXXmLd8L9VeFvkiDS6Q7R5q6h2RUgZHfjku3YRRnV0MiUCoSLGaLFDBP5JOP5JOlSkW2+Rrb6lq84Nzr87K/p4K2pK4znk9hEiTqHl1ZXkGZXkCanjwaHD7/NNZsQndNUxvNJelMTnIoNMZZLVITUxdQs3756lH01bTSuILfEwGQoG+X7AycoGTpPNG7nwbou6h1e4mqOI5N9HJnqm81JUg2NM9PhYBcSo9TaPTxQt5lDoU3UOTwk1By/mrjMO+FrpKeFOd00eDdylYfru5eldPx6soc/7329wkIsItDqDrIn2Eq3t55WVxC3bEcSBLJakalCmr7UFO8lRriajswK+BmtyK8megja3Xx+84PUOda+6YULGUayMb5x5QjnYiPopoksSGzx1dMxneMTsDnLBg8gq6mEi2mmCmnGcgnG80manH42e+qWfc4WV5B7a9p5N3KNqUIauyhT7/DS6g7S7CznFDU4ffiU8nlNTLJakbFcgp7pNTORT1YYXCLFDH/V/yb3htqXFZp3p1Mydd4KX+FY5OqswuGSbOwINLHD30Snp3bWKGaYJgk1x7VMhPPxES4mx0nNWW85XeXXE71s9zfx0da9yy4WMVVI8e3+o7wxT+EQENjqa2BnoImt3gbqHT48ih3dNEiXioznE/Slp7gQH2Mge92zHClm+P7ASWyizHOdhzasd9liYWRRYTR/kXOJV8jrKT7Y+Ps0ObciCguvNwmJWns7c9UAQRCQBBlJsKEbCxvR1pOpwgA6GnktydnEzxG5PnfdLCEgoJslMqWYpXTcJja80jHXgtTpqeW5joM807KLeke1JcYwTaLFDL8Yu8gLQ6e4PCfpOV0q8PbUFfbVtPN0085lbXqqofHm1BVeGb9ITL0u5EuCyMFQJx9p3cMH6rdQY/csaInPayrHItd4afQcr45dmhVOiobGi0NnaHfX8FznoWWFYsyEeL0yfpGhOXH+AI1OP8807+JjrXvp8tYtGBs8VUjz5mQvPxw6xeXkOMlSfkWueCiHWDU7AzxU38VLI+dnx5OlHEemenmyaceqEsoN0+RicozBbGVo1VZfI13e+ttSHWitTBXSfH/gBCejA1UKR6PTx/21mzlc183OQDMtrkBVoq1pmhimwWQhzdVMmCvTSaH31XauqIKVJIrsDjTzaMNWLicn2OZvZIe/iW2+Rjo9IdyKfVHLc7SY4fXJXr577RhXUlMVXo8LybJyX+vwoiyyaS1EspTnTGyYB+u6+Mq2x+nyloVhwzTp8tSR0YoVOT196UmEtIAkiDzeuI0vdh2m3VMzO+d2T4hIMcvp2NDsMZeTE6RLi7v1Z7iSnuIv+45UPAeSIHJvTTufaLuXww3d1NqrFV7TNEmVChyLXOXF4TMcC1+dvcfJUp7Xxi+zyVPLR1ruWZEnaCGGslH+fuA4R6f6KZk6jU4fjzZs4+H6LewKNC+o2OimQaSYoS81RX96ihq7e0XVq2RRZF9NO4fruhnMRqfXTDPbfA10eEK4ZNuiayZcSPOrict899oxrmUiFV6Pc/ERzsVH+ED9jRuF3ekYplkRildjc/Ohlt0807yL3cGWBauoqbo2HQp1ilfGL1YYscbzCU5Fh7ivdtOyPOBFvcRLI+d4c6qvwoMqCyKPNm7jo6338GBtV/lezQ+bMU2Sao43Jvv46eg53olcnVUQw8U0LwydpsUV5OnmnVZlq7sI04RT8Z+iGnkkQaZkFJc+QBCwCQsbRctL6tbXvSwaWTBNporXSJUizBe7vEoIu+je8EaNjcyGVzpmCNpc/F73w3ysbe+iL0JREKhzePlk+z68ip3/1vMrRnPX42xHcnFeG7/EgZqOZVnPr6Yj/GzsvSoh/2Cok9/f+gj7gm1LChVO2cZjjdvo9taDCT8be2/2bxmtyPcGjnNvTTvb/U03nEteL3EqOsSxyLWKcb/i5JnmXfyTTfcv6Zqvd3j5ePu9+G0u/qzn1/SlJheNp18Ku6TwoZY9vDJ2cdYrUdA1LiUn6E9PrSqhPK5muZycIDInfE5AmN6AVxZucCdgmAavT/RwNNxPRqt8sXd6Qny6/QAfab2H0CLKKsxYlCSaXQGaXQEequsmqxVXFWbW4g7yyfb9ZLQi23wN+JfpXQvZPXy8bR8iAv/v5dcqQt8M0+Tt8BUeadi64jK+IbuHZ1v2zCocUH52N3vr+ED9Fk7MSYSdWWN7Ai18sGlnhcIBsNPfzDZfI5eS47PHTOSTpEp5DNNY9F1R0jX+5srb9KWuC44iAjv8jXxl22PcV7tp0fkLQjns6vHGbdTY3aiGxjvhq7N/H8pGeX2id9ZTshb6UpNcSIyS10t0uEP89qb7+I22fUsmZUuCSIOj7MF6qK4LY4GiGzei0x3iM50HUQ2Nbb7GZVu96xxePtVxAAGBP7n8aoVgbZgmb0z28nB9910RYjWDR7bzyY57+fzmhwgtUSTEJsnsCjTjlG3kdJWXR9+b9SCawOXkOFfT4WUpHefjo7w0cr4q3Pfxxu18dfsTbPKEltwng3Y3H27dQ4cnhAkcDffP/n00l+BHw2fY7m+k01N74wtgsSHQzCK19naanVs5E/8Zx6I/xKfU0uDoXmStrE+Z/xuxlFSiiHZAoNO9j27PfQt6aSRBxiMvP4fN4uZy15gpnm7exYdadi9rs3LJdh6u38KzLXsqmguqhk5fapLziZElji6jGTpHw/1cSIxVhJa0uAI813mQe4Kty7ZitrqDfGXbY3S6Q7NjJiYj2Tg/GDy5YCWu+Uzkk5yIDlRZcPcEW3m2ZfeyYoElQeTRhq081bRjRSFmc5EFkV3+Zrb5KhWlaDHN65M9i1ZkWore1CT96amKcIwGp4/dgZZVz/N2MpZL8vpkT1V+So3NzW9vup9Pdxyg1rG4wrEQoiDgVRy45ZWXZbWJMjsDzdxXu2nZCscMkiDyVPPOaett5Qt+/rOxXEJ2D/fVdlaNO2Ub7e4ampz+inEB2BloZpu/ser5V0SJDk8NfuX6OtFMg2gxu2To4MXkOK9NVCayexQ7X+p6eEmFo/LcMrv8zXyk5R7q7Nc9Dibla3MqOoS2gvDFhUiWyn1C/IqTL3Q9yGc6Dq6oCpQoCKuqimSTZO4JtnIw1LniMBtZEHm2ZQ/b/U3I84SZc/GRu6ovkCJI7A918LlNDyypcMwgCAKd7hCPNmyrWuej+XI4nHGDIgElQ+NnY+8xnItVvG83e2r5cvfDdC6hcFTMXZTY6W/i85sfrJhLydS5lBzn1fFLq3q+Le5c9gc/zIHgxzhY8xvE1XGORX9IuhTBXEFhivVmqTdbyNaKKEiIgsxmz0G2eB+o+rfZc7CilK/FreWuUDqcksIn2/ejiPKyN1u/zckj9Vtpm1e1ZTyf5ExseLaB3mKM5hKci49U5U481riNvcHWFYf8dHpqea7zUMWYamgcDfczmFk6IcswTUZycc7FK5WloM3FwdpOur0Ny56HLEo83byLZldgVbZGQRDwyHY+1FJZki5dKnIyOki0kFnkyIXRDJ3LyXEG5l2De4PtdLhDG7K52PHoNfrT4YoNWwA+1LKbp5t2loXGDWTpnenFMl/hmZ/rsRwUQaLe4Z3tvzEfv81Jw7wkVqdso80dJGhbWKirsXlwSpXhQwk1t6jAb2Ly4vAZcpo6OyYisD/UweNN1fXkl8Ip29gVaK5K1J4qpLiUHFu0rPZKebJpB88078a2zB4ptxuPYueB2s1VZa5Hc/G7qhupR7Hz6Y4DK8rfkUSRTZ5ats3LzcqUCkSKGYo3iJXvT4c5Hx+pWL8An2zfT5e3bkXvTJskszvQzDPNuyrGY8UsxyMDS1aLs9h4KKIDSZDZ7X+SPYEn6c+c5ET8R6hG/o5SPBajxbUDv1LPUPYcU4WrmHP2H9M00QyVnGat2dvJxpPYFqDb20CHO7Qiy7AkiDS5/OwPdVSMZ7Qi1zJhYsWlheOLyTGupsMVlqSgzcWhUOeiAtNSCMAzzbuomSM4mUC8mKuIYV+IvK4ymI1WbQDt7hC7/M0rzqPo8ITY4q1fdd8LuyTzQO0mGubk1eimwUguzono4Iq+azKfoic1WRFX75QU9oXaqoTPjUBRL3EuPlLVQ6HJGeCZ5t0E7Rsz3nTLArk1OU1FM/QVbVY2SabB6Vv0GrhkW4XXAiBocy8ZiuZRytWb5pLX1UXLykYLGY6G+ytyVCRRLOdgrKKjeZPTz655IZIG5RysuQUtVotPcfKJ9ns3XJ+Lbf7GKu9YVlMrKmttZEQE2t0h7l+mZ2wuM40352JSzj3Ma0srHe+Er1X1kalzeDlc372q/Dev4uQDDVvxzfFoGZQNXWdjwyv+Pos7H7vk4mDNb7DJvZ/ziV/yXvJVTIxVRSrMUNRzRIrDTBb6CRcHyetpinqWcHGQiXw/keIQeT3NjawOS/3Vp9Rxb/DDqEaetyPf43T8ZXrTR+lJvc35xCu8Hfke/Znjq/4NFmvnrlA67q1pQ15Ft1Sf4uSeYEvVeKyYq8j1mI9hmgxmokwWKoX8rb5Gml3BVYUrCNNxtPtD7RXjeb3Eu5GBJQW3VKnAUCZalYPR6gqwyRNa5KjFEQWRXYEWPKsI1Zk5vt7p4+GGyoTQWDHLW1NXUPWFm4gtRE9qgr7UZMVYl7eOrb4GnPLGSyAfzycZycarkscfrOuaTRjfiNTaPVW5GwbmiqqfQTmkY6nmmIooVQlOPsWBV1k8zM4mSlXXtWjoi+YsXUqOE1crPZhu2c6hBUK+loNLttPkClR5gsbzScZugqV4Z6Cp7PXbYB2j6+yeqvuim8aK3g93MjZJ5t6atlWFPM6Uqp5PUddQF2nCCOV8scvJcVLzwmzvrWlfdWdzWRRpcvrZMU9xjhQzXHS3naIAACAASURBVEiMbQgLuMXK8Sl1PFT7mwRtTbwbfZ6r2VNr8kKGiwO8MfVt3pj6NqdiPyFaHCZeGud0/GXeCH+LN6a+xXD2PGtdTrv8j/FQ7WfRTJXTiZd5K/z3HI38A6fiP2U4d2FtX26xZu6KRPKuVXYTd0gKra5gucHgnAofyVKe8SWEgXSpXH53vvt6s7eO4Apj4uciCgL7azr45fil2THN1BnOxkioOYKLCGPpUqFKSZIFkXqHb1VeFyh7O5yyDW5QwGIx3LKdJxu389LIudlrm9dL9KQm6E+H2RG4cXJ8Yfrzw9lKa/D+UAft7poNFYI0w2AmWiXQAuwPtW/I/JQZ7JK84P1YaXiVLIh45cVzBERE5HnJgU5JwbWEBVcSxKq56Ut4YN5LjKEZlfNucQWWVIaWQhSu9zvJzikcECtm19SQcYa9wbZVVYW73TgkZcE1s5oCFnciiiCxw7/ywhlQVq4X8qqVDL1qbc4lVswxkU9WKSa7Ay1rqvLnlu3s8DdVFCrJaUVGcwkyWtEqn7vB2el7lAZHNz6ljrlZE43OLTxc9zkixSFsQnl/EhBpcW3n0bov0OraWfVdXqWWh+t+B49cWfDAIXlpcW5b8ul2L5LgbRfd7As8i2aq+JSlixfYJTd7A8/Q4Ogipo5S0LOICNgkFz6ljjp755LHW6wvG2+nWoDVNoebEQZq7R5G5oQ5pEuFKvf0XMKFNJFiturhaXL6V+0dgHJFpi0LNA3L6UWGc7FFlY5MqVCVlOyW7QTt7lV5XaDcv8G+ilCSGWRBZIu3gT2BFo5HB2bHJ/Mp3pzqW5bSMZKN05OaJK9fV+7qHF52B1oqwtA2EuXKSZVWSK/soMUVWFXozp2CINwcFVAUhCWFI0GgKoTIJspLXjtBEKpKJy4VJnApOVYRWiUg0OEOrUnJtYsyrnl5JXm9RE5TMU1zTWFRmzy1VYrYRkAQhKWzQjc4kijSsQpPM5TXnLTAmigHuCy+dkdysdmeNHPpdIdWXEVuLg5Jrsp/NIFEKcdkPmkpHRucLu8huji08N88B+nyHJz9bwGBBkcXDY6uBT/vkWs4WPOxqvFaexu19uU3IZ2LTXKyw/+BZX9eFm20unYuqBRZ3F42rpQzh5DdvWqBwCbK1NjdFUpHUS+RWaKOf6pUqLBYzlBjd1clrK4EARYsh1gyDMbzSe4JLvzAFg2topkUgFtZ2D2/XGrsrjVtUoIg4LM5ebp5V4XSUe7DMESkmFmwx8FcetOT9M4LrdodaGazZ+FeIxuBmJojP89D1uD04ZEdd1RXdcM0p5XvFOFCmmSpQE4rktdUioaGauhopo42bXlNlPJEF/DgrJSyRWpl91YSxJsaljaWq6wQZGLSk5rkP537yaq/czKfIjLPkKGbBkW9hGYaK+plMp8au3tBAfVWY5gGqek1M1XIkC7lyWkquek1U7bSl9dNyTBIqLkl37MbHUkQllWx6mYSK+YoLhCe1uD0rUkxtYlyRY7eDDlNJVLM0r3qb7awsHg/cVcoHa7pbrurQRbFKgtkydArwq3mU9BLVe5rRRBxSsqa46r9NicClaGTummQUBdv1KcZRlVyoV2UcYird6e7ZNuaBTmHpLCvpp02Vw3DuXIvE900GMzGOB0d4qnmxa0QqVKe3uRERXK8TZTYG2xbVp36O5VMqVCVzxGwrU3Bu1lohs5EPsXF5BiXk+OM5ZLE1SypUmFWcFR1jZKpoxsGujn339IW2GUjCMtYd5XnEQXhpilsJmVla/5v6U+XG+ndbFRDp2Toa7r/7gUavN0qNENnNJfgYnKMnuQE4/kkcTVHqpQnr5UoGqXymjEMNFPHMM2bv2buUASEVeVzrIWcVqzw0kH5vemQlDU9I5Ig4lGqf4tqaHe14mhhYXFz2fBKh4CAsoZ4ZkkQq+KhNdOoEgznUjRKVdYkmySvWUgXpgUumyhXnN80zSrr+Fx0U6+ajySIaxJkZKE6+XaliIJAvcPLBxq28J1rx2bHpwppjob7ebRxW1X1mhkGM1EupyYqShd3emrZ5m/EvYLuyXcaRUOrEgpcsnJbE8iN6cpib0z2cSI6wGCmXAltfuPCW4EAtzVX50aJujcb0zTXnIgrC9Itv2aGaTCYjfLGRC8nY0OzayanL/6eer8hUA5LupXkdBV9XvGGtSocUN6bZEHCJkoVxSE0Y+m90sLCwmIuG17pgLKQshZL3/xjTdNcsgGTNm3lnYsoiDdl2xdgwQ1iKaHCMKsTdtdq/RWmm4bN97qsFK/i4JGGLbw4fGY2JC2vq/Smyh3K51dEgXJoz5XUFL3JytCqvcE2NnvqNlRZ0PkYCwiZsnD7eiuousaJ6ADPD53mTGyIqWJ6ybUvImCXZJySDbskT+dTSLMlYFdarWp1rN+1KmilGzZfe79T1Eu8E77Ki8NnOBsfJlLILJn8LVLO03HKymz+jU2UMTAYzESrlPC7B2FZTfhuJqUFqrLdTIPG/D1l476JLSwsbgcbXukwMdFNfdXJmIZpVjUCvJGXQFpAoNcMfc3CykywwXzBTRCEJcvDSoKAIkqU9OvHGaaJsdbN/CYIX7Ig0uGu5d6a9op+I6O5BMfCVxdUOmLFDD2pCaLq9V4pQZuLXYHmFTXZuhMRBaFKgSytsJfFzaJk6BwN9/NXV97kQmKsymJpE8vJo1t9DbS5gtQ7vPhsTuyijCxKyNO5FJIgMp5P8v9c+iVT8woabDQWeoUIlKv/dHmrizysld3BllWV+75dqLrG65O9fKv/bS4lJ6q8QnZRLvf58TXQOr1mvIoDuyijTJcunvk3movzxxd+XtGDx2JtLFSpTTX0NQexmdNdGkrzKmdJorimgiMWFhbvL+6Kt8Va3LuGaVZtnLJYHXI1F7ukVL1o1emwGRNz9aEOZjm8Y77XQkJYsiqWND3fuaENmmlUbRArQTN0SubaNytBEKixu3myaQdvTV2ZjeGOqznOxIeJFjNVZX0HMhEuJccrlLjt/ia2+BruiNyHtVAW2MUKBbHcqO7WW3t7U5P8YPAk5+IjFdZmuyizr6aNJ5t2sNXXSMjuxqs4cMt2bKK8oAetLzV5C4WP9VPQnJKtyjotILCvpp3f3nTfTT+fV3GgbCCh7UJyjB8OnuS9xFjFmnWIMgdCnTzRtJ1ubz0hu2d6zdhQFlkznqR9wz/Pdxou2YY8b/0W9BLGGvcm04SSrle9pxRBwrWBw10tLCxuLRtnt1uCtFrAdK3uhVoyddJqZSLcQg3I5uKR7VUvWt00yWgFSrqObQ1xvJEFOqGLgohniZKEslA936Jeqig1u1IKemnJevArwSEp7PI3s9lbS386DJTDwQYyEc7GhnmiacfsZzVDpz8dpi91PWlXFkTuCbasqtHhnYZHcWATZfJzChXEi7lbmkcAkFLzvBPu53j0WoXC4ZRsfKh5F5/uOEC3tx7XMpOU75aAJEWU8CkOosV0xW8SoKpk6PuNhJrjrakrnIkNVwifLsnGb7Tt4+Nt+9jsrcMpKe+rNXMnEVBcVfuPbhqk1DyGaa66yplm6MRLuapxRZTL/ZwsLCwslsHG8esvwXg+terQpoJeIlysLGXplG0ElmjyF7S78S3QAXmqkF5TIqWJyVAmWjWuiBKtS1RsckhK1XwzWpGEWr1JLJeEmkczb058vigI1Du9PFK/tWJ8PJ/keHSgQoCZLKS4lBwnM6fWfJu7hu3+JtxLNI3bKITs7qpE+LHppO1bmUswmktwKjZEdl6BgkOhTj7TeZBdgRbcin3ZIYsFrYTBrfLWrF8kuSAItLqDFd4OE5PhXHyJo94fDGainI0NV73jDtd386mO/ewINC1bSQUrf2Y9aHD6FjSYjeYSVWHEK6FoaIzPa0AL5cpp9Rs85NXCwuLWcVcoHcO52Ko2L80wSKr5qnK0fsVJo8O/6HF1dg+1dg/zU8fHcwnSaygfaJhU9aUQEAjaXUuWifUqdpqdgYqxbKlIrJhd9UYznk9QXKJs8ErxK04eqNuMf46yltdU+lKTXEtHZscGMlEuJscqrKC7As1s8TbcUX0sVkuj04d3nsKa11WGs7Gber1vxGQhxZVUZQlYr+LgQG0H23yNK84zSGn5Wxgitr6C6lZfQ0XyrQn0JMfRbkmS/J3LaC7BQCZSMeZTnNxfu5kub92KE5aTpdxd0338TqHFFcCnOKvU8muZyJqUjoJeYigbqxiTBZFah4f6Bfp3WFhYWCzEXaF0XEiMrqoCSlYrciU1WSUs+RUnTc7FlQ6HpNDmriFor/QuXE5OLBgetVxMTI6G+yvGbKJEl7d+yRwTr+yg2VWpdBiYTBRSFX0uVsJQNlYRArRWJFGkzV3DodpNs2MmMJKLcyY+DJSTVK9lwlybI9h4FQc7/c1Vv2+j0umupcZe7UV7N3yNxC1MqM1MK6VzqXd4aXPVLLnWFuNaOrJgU7KNyIFQB8o8pSum5ricnLhNM7ozSJcKxOd5T5ucflpcgSU7wi/GlXR4TYKwRTUu2c5mT21V+O/J6OCSZddvRLpU4Nz0e3oGj+KgfY2dzi0sLN5f3BVKx6noEKpeWnEFoGQpz9n4SMWYgECtw0ure3EhVxAEtvobaHNVxnhfy0QYysZWJXyZZrnk6KXkeMW4Q1K4L9S55LE+m5NOd6jK8zKSjVcI8CvhbHxkTV6b+ZSvq4fHGrdWeCymCmkuJEYp6hqThRS9qUkKc67fFm8D2/2Nd83G1uQK0OYKVSVdH430M5ZL3BJvgWGa5V4zRqVS6ZEdCzYAu/H3GZyLD1eFaq0f6+vx2hdsqypuUDJ0fjRyZl3PeydjmCYFo7opqldx4FpFAzzDNDgdHbyl3r33A6IgsD/UQdBW2Qn9YnKM8UJyVe8X1dAYzEa5Om8vqbV72BVoXtN8LSws3l/cFUpHpJjhzakr6CtQOkqGzkAmwsnYYMV4yO5mxzLyB3b4muj21VeEFBQNjdfGLzG6ivhvE/jbq+9UVOISEGhw+vhAw9bFD6RcbajdE2KTp7Zi/FomzNnY8IotXEOZKH2pySW7sq8Gh6iUlQjf9TK5JUNnMBPlWibMaC5OzxxrsoBQDq3yNdzUedxOFFHi3lAbDc7KkIRYMcv3B08QKazeU7ZcBMqlNedXadJNY1Vhimdiw/SkJm95Mvx64ZbtPNG4vaIKkG4avDp+mYuJsds4s9vHYmvGMI1VleY+ER2kLz11F/fouH0cqu2kyRWoMELl9RIvDJ4mW1p5w89YMcuPh89WeKVkQWSTp5Z9NW03Zc4WFhbvD+4KpcPE5G/63yajFZbt7QgX0vx45GyVNb/ZFeDemvYb5g94FAf3126mc15FpaPhqxwN96/YS3AyOsDLo+crxpySwhNNOwgukdQO08mvrgB7520Aeb3Esci12fCl5WBi8uORswxnYzc92loQBBqdfh6u31IxPllIcTk5wVg+ycCcRPoWV4Ad/sYFk/Y3Mg/UdtHlra9YYybwq/HLvDh8mpS6vmFWglBu1jY/oT1WzBBdYXhgUs3x99feXTDJdP1Y3zwAQRB4rvMQ/nnPXbSY5v+++ArReWFp7wcEQcApKbikyjUTLqSrQq5uRLyY5W/7j64pFNVicYI2N483bCNor/R2/GzsPU7FBlcU0pbXVI6Gr1b0WAKoc3h5sL4L711Q3MPCwuLWcVcoHQB96Sn+6L2fUTS0GyoeCTXHi8NneH2ip2LcLdvYE2hhu7/xhucTBYEH67o4FOqsqBaS11W+eeUtfj3RQ26ZHoaLiTH+t3M/IaNdt0KJCHR4Qnymff+yqsE0OP3cV7upSkG5lBzj+aHT9M1LUF+Ml0fe4+djF0jdxNCqufhtTg6E2gnN2RAjhQwno4MMpCMVlXG2+RrZ4W++KxLI51Jjd/N0886qimQ5XeVb/Uf5i743mCqkVxwuqBk6o7k4Q9nqCmgLzWH++ScLaS4lx6tyPRYjoeb4/3pf5+1wP4W7xMsxQ7MrwBe7HqzwZOqmyanYEP/jqX+kPz21xNGLk1TzvD7Rw4+Gz6zKI3o7qXN4aXJV5rqN55NcTo6TXKaiHC9m+drl1zgeHbDyOdYJURD4cOsetvsbK7x1Ga3IH1/4OWdiw8sqh17UNd4O9/OnPb+qyO+ziRK7Ay080bh9VQ15LSws3r/cFX06oBz+8MrYBeLFLF/d/gR7gi1VnzFMg5FcnG/2v83PRt6rSpTe4m3gY617l93kzKc4+ET7fq5lohyLXJ0dnyyk+C8Xf8Gl5DjPdR6kzV2zYGWXVKnAC0On+O6141UCiEdx8C+3P0ndMiuDyILIvpo2Pti0k+8PnpgdVw2dX01cJlMq8PmuBzkQ6lgw6TNcSPPi8GleGDrDSC4+28TvZiMJIq3uIPfXbuan056dvK5yKTlGzZw4eqdkY4e/ifa7oDfHfERB4PHG7ZyPj/Kj4TMVymaylOf7gyd4N3KNj7Xu5eH6bto9oQXXj2maxNUcPakJzsVHOB0dIlLM8Fub7qPdvfR1a3T62epr5OKcHKLyM3SRJmeAT7Ttw2db2MOkGwan40N8u/8ox6MDZNZJQV2c9Rd0JEHkNzsOcSI6yBuTvbPjqqFxLHKNf/Pu93iyaTvPtOym21u/YM6RiUlBLzGaS3A5Oc7p2BAXEmNM5JMcqClXCdtItLqCbPbUVVTY00yDn4yco9Hp59mW3Yv2E9IMgxPRAb7Z/xZnYsNktZWH+Vgsnxqbmy93HWYkG2dwjhFiOBvjP5z+R36z4yCf6ThA0OaqUhwM02Qin+R7A8f50fBZIvNKym/y1PH5rger8kYs1hfTNAlnsrzVP8i7A6MMReOkCkVU7cZNfB/fuonP3b+P9prruar/849/ybvXRjBMk2d2buFLD+4n5Fk8qsI0TcaSab78Nz8EwGO38QcfPMzh7s6Kz12aCPM//PBlDMPgcHcH//HZx2fnfqRvgGMDIwzFEmRVFbsk0eT3sbe1kUe3bqKrtgZxhZUTLTYWG17pOBjqYKqQZjgbp2hoHItcpefdCTrcIfbVtBFyeHCICnE1S386zOnYMHE1W5WvUO/w8lTzTrb5G5dtvREEgW2+Bj636X6Sao7LqXI+gglEixl+MHiCV8YvssPfxBZvPbUOD5IgklDz5cZ48WFixWyF0AnlHI3Pb36A++s2LdvKPxO69ETjds7HR2bnAuVyh++Er3IpOc5WXwM7/E3UO3yIAqTUAlfSU1xOTTBVSJPXVAxMur311Du8nIuPVM1vrTQ4fByu7+YXYxemu7jD1UyEwTklGbu8dewMNqOssAznRsEl2fhy92GixQy/nuipyOXJaSo9yQmGszH++sqb1Dl81Du8BGzO2caCaS3PWC5JUs2jGhqqoVHUNTyKY1nJuc1OPwdDnbwx2UtMve7ZmCqk+Ive1zkWucrhum66ffV4FQeaoRNTc1xJTXEiOkBfapKYer0k8webdpJQs5yPj1b8lo2MR7HzP+35KP994e95L3k9l6Nk6gxmI3zn2rv8aPgMfpuLVlcQn82BXZQp6Bo5TSWmZgkX0hT0EiVDp2iUUHUdY1oZWS/Ffr1oc9dwINTBO+H+ikpr4/kkf3L5Vd6cusKDdZvp8pbXjKprxNQsfalJjkcH6E9PEStmZ/M4nm3Zw0Q+yfn4iJXbcZMRphPK/2n3w3zt8quzoWwmMJFP8ldX3uSHQyfZF2xjs7eWgM2NaZpEi1n605OcS4yRUvNVDWYbHT4+23mI3YGWu84DfSeTU0sc6RvgL986wUA0TlHTKOnLz8GLZHJoeuUzFk5nGYolMEyTaCa3rCIDJd1gKFYOpfU67OTU6r1G1TSGYglUTafR7yWWzfPe2CRff/M4PRNhCpqGphtlT74APZMRjl4d4vkzF/mtQ/fw8Xt24HNaYXt3Kxte6fhY6z42eUL8+9P/yFgugWYaRIoZYmqWC8kxREFAQMAwTTRTX9Cl71UcPN28i0+170deYZUkWZQ4XN+Nbhr8We+vK6yAeb1EPp8kUkhzNNw/3Q22PBfd1FEXmIssiHyx6yG+0PXQistQSoLIwVAH/2TT/fy3nl8xUUjN/q1k6kSKGeKRHKdiQ7OdaQ0TNFNHM65bS+rsXr66/XGSap4r6ambrnTYRJkubx27Ay2z+SYlQ6fE9euxzdfALn/zXeu+FwSBeoePf7vzaSRB5FcTlys8bwYmGa1IRisSLWbpTU3MrmUTc3oNrb7LgSSI3Fe3iWead/EPA8eZufsmZW/L21NXOBkdQBYkREHApOwp1AwD1dAqhMSH6rr4yrZHORkdpD8dpqiut9Jx64T1BqePPz74HP/LmRd4NzpQMYO8rpLXVSLFDAOZyLz7AwarS8y/U5EFkYfrt3AxMcaPhs/MWTNlj9uRyV6ORa4iC2LFmilNr5m5Qs0jDVv56vbHeX2ih57kBNoamqpaLIwiSny4dQ+aafCnPa9V5CJltSJZrUi4kEaeuF4gYOYZLy3QGLbO4eXL3Q/zsba9d001wY1AsaRx5MoA/9fPX2cylcEwTWpcDnY3N9Ic8FEyDPrDUXonI7NKgE2W2NfaxL62JloDPnY2NdDkv/VNHNP5Ij99r4e/P3GOa5EYumEiiQJumw0EyBZVSrpBSVfJRmJ8/chxbJLEJ/buxK5sePHUYgE29F11SAoHQh20uIL814PP8R9OP8/VdBiYLvG4DItvQHHx6Y79/G73w7hXUfoRwCbJPNq4jRq7hz/v/XVVvLJmGlVWhoWosbn5g13P8HTzzgW7yi4Hu6TwTMtuREHk631vVLjWoRxCoy8xlzZXkH+98ykequtmIBNZ9TyWQhAEWlxBDtd3L5jkXu/wsjPQvGRX+LsBcdo79R/3fIRtvkb+9uo7hOeFMkBZATFM86bK2oIg0ODw8dlNh8hqKj8dPVehSGimgbaMnKQPNe/mK9seo8MTAgScko04K0ssXjm3VhFtcQX4z4ee49v9R/lW/ztVpYZNytdrJfdHEWWUVfS2uJ0IgkCzy8/nNj9ATlf55filCkWiZOqUtBvnaXysdS//YtvjNLsCHKrdhE06UtXl3OLmYJcUPt62j0ann/968RdcTYcrGjLON/YshCgIdHvr+e+2P8lDdV2r6uNjsXoGYwn+7tgZJpJpRFHg4a4O/tUTD7E5FJwORTIpaQZv9g/y9SPHuTwZpqTpbG0I8dmD91DncSGJ4m3xTPVMRvjTXx8lVSiyKVTDcwf38HBXB0G3czZc6/nTF3jpvR4SuQJT6Sw/v9DHtoY69rU13fgEFhuODf322Btsxac4kASBHf4mvvHgF/lG3xF+MHACdQFLzVxkQWSHv4l/uuVhHq7fik2U1mRVV0SJvTWt/J/7P83Lo+f53sBxBjPRZXXcdUgKH2/by5e6DtPg9K/JijRTZebDrXvo9NTw7avv8MZk7w0b/dlEiScad/Cl7ofY4mtAESQ2eWpXVYN/OfgVJ/cEW2l0+pjIpyr+tsVb/75x34uCgFdx8DubH+DRhq08P3SKn4yeJ1bMrEjHEIBah5dnm/dwuL572efe5KnlX+98ki5fHd+79i5jy2wm2ewK8PlND/BMy25Cdg+iINDlraXO4WUin7xrOk0LQtlzEVBc/P7WR3mqeRd/d/UdfjF+ccWlqN2yjT3BVp5t2c3hui3UOjw3PugOQxREtvjq+cNdz9DlreeHgyeZLKRufCBlg8aXuh/mqaYd+G0uREFgi6+ekN1NUs3dJSvmzsMmyTxY18VfPPgFvjdwnO8PnKgIqVwMgbJ34zMdB/hk+35q7V5kK97+llLSdQaicU4OjWICXXUhPnffPnY31VfkPpiKyVM7uplIphk9kiJdKHJ+dIqReJKWwO3rGK/qOqW8wYH2Zv7dM4+wvaEOWZr2hJomAaeT9if8BFxO/vrtk+TUEmdGxrkSjrK3dfmh7hYbB+EGFXLuqH1ANw1Khj5b1UcUxAplwZwOoZospHll7ALHItfoT4WJqVl0U8cj22l2Bbkn2Moj9Vs5GOrALisLJumuFnM67CWnq5yMDvL2VD8Xk2OMZOPTFaFMXLJtOpG3gYOhTh5p2Irf5kQR1qb4VMwDE9M0KRoafakpXp/o4VRskIFMlOR0PLZfcdLhCbG/pp0nG3ewyVuHQ1IQmBa2po+fu0YUUUISxJsyz+FsjL/ofZ0Xhq83XbOJEp/b/AD/cvsTG84SvFZmQqayWpHTsSFORQe5nJxgOBcjruYo6BoCTJe7tdPo9NHmrmGrr4F9wXa2+uqxS8p0P4Xl35+ZNTtZSHEsco2j4X76UpPTOT6lWcWo0eljm6+RB+o2czDUSdDmqlgLJiaqrlWEFNnnrKfFzjvXKygIArIgLSrczIRJ6nOq74iCiCJW95CYYf57A8phkfIK17FplrMwNEMnUcrxTvgqp2JD9KYmmMilSJbKcdE2sVyOuMbmps0dZNN0KOGuQDNBmxtJEJEEYcXPkGEaqPN+B4BdkhFY+fethfK71mA8n+SdcD/HIlfpS00RKabJaSVkQcSrOGly+djua+LBus0cCHXiU5wVv93EpKhXvmMckrLhhA3dNFDnNYUVBAG7KK/qtyz0bEA5LFIWpVUZZGbuWVYr8ObkFd6JXOVycpyxXJKsXkQSRLyynRZXkB2BJu6v3cR9tZtxy/YVPysWN4dELs93jp/la68dBeCRLZ380ac+RNBVXeTDNE2OXBngT147yvmxSUJuF//+Q4/ysXu2L/jdX/nOi7zeew3DNPnUvl38mw8+RL13cUOIaZoMxpJ86Gt/DZRzOv6Pjz/FUzsrS+CfHRnn83/9fdRpr2d7TYCvPvoAH9u7fcF1a5omJ4fG+Nprb/PuQLlZ8z9/5D6+/NAB/FZux0Zl0ZfFhpLqJEFEkhZXEARBQEaixRngC10P8fnND1ZpTeWsivKmt5gwtBZmhCav4ODRhm080rB1VlhZeB7l/5859qbNY/o3GXWyPgAAIABJREFUOkSFPdMCz6LzEITZRlJz5zDTz2E9mJnL/ECvTnct9wRakYX3X8ywKAiIgoRfcS65dmaYvmMIAgvev+Uys2abp6tW/UbrPlggzflGz46AgH0F6+W6grH8ey0KAjZBXlGx7xu9N5bLzO9WRIk6u5ePtu7lIy33lBX8hT4//b8zz/ha3zeiIOK4Cb/jZiAIAoog0eYK0tpxgE+1H2C1a2a93jG3EkkQcc7re7MWVvNsLOc7FUHCr7j4cOs9PNuyZ8G1u957pMXyKekGqfz1nEqHoiwqiAuCgMduw20vr8OsqlLQbm9RDwHoCPl5bNviRXEEQaA14KvwyCTzRXJq6aYrHTPGjXS6wC9/dp6jR3oYGoxSLJbw+120tof+f/buPMzO6y7w/Pecd7t77YtKKu2LLdmSVzmxvMQkcZyks5MmgYQAIUCGARqGmR6GnummeZ6e6QG6oZul0wwkJKFDAgSHJLYTx05sx/smy9q3kqpU+3L35V3P/HGvyiqXliq5SlUlnY8fPZJvve99z3vve2+d33vO+f14+91bufOurbS2rbyR6JVgRQUdc3H2C9JAXOmp37PacbbTsdTtgKV/Pd5MAadKEzw9dnzG45sznexs7b2mf9Et1bUjGguh5bX70s/J2WtT1P9nSduy1PQ1s/JMf79c49fuSmBKOR1EAARhSM0PSNjnD9TdIMRtjDA4pom9xDcpko7NpvY2MrGLT9NOOPaMc3L9AD9c2Do+SimiSHHsyDD/8ff/maEzUziOSXtnhs6uDFOTZfa+0sfEeIHVq1t00LFIrrqgQ1sZJt0SL0z0zaiA3eYk2dHcQ2fsymfZ0DRN07TlJG5brGlpQop61suJUoXDI+Pc3Ltq1o25MIo4PZnjTK6+Lm9VJkVbYmmTsSRtm57mzCVvIso3TTeN1OJk/hsezPJ7/8c/UChUedueLfz8L72D9Rs7AfD9kP7TEwwP5th587oFP7ZWp4MO7YqLlKK/PDWj6BrUizPe2nr5H3YvCqiF/rJJU2pJg5i0MPTiS027bKqRiXA51X+JGdZlr9fQtLmKWSbbutrZvqqT/UOjHB2b4Bsv7aMznaQtmUBKAaq+puj1wVG+d/AY48UyUghuWtvDxo7WJW2/aUiSFxiVuZKUUrhuwJf/6kmy2TK337GJ3/m3HyYWf2MUybIMNm3uYtPmrhn7RaHC9+u1RaLo7HpigWkZWJYxa+puFClqNQ8QOI6JUgrPCwiD+mRyKQW2Y2Ga1+Y6KR10aFeUUoqcV+H5iZP0lSamH48bNtube9jWdPlVmn8wdJA/OfQYQ9XcQjT1LXtH1zZ+9br7uK5Jp/7TtMtVCT2+cOQJvnji6aVuyrRf3fYOPrNpz4Ku49C081nX2swnb9/JHzz6FPlKjW/vO8xrZ0Z428ZeepoyBI06HS+eHmS0UMKUkp1runnP9VvoWfDMVfO7oSeFwDKWx/rMyYkiP37iMOl0jM987t4ZAceFuDWfQwcGefzRAxzaf4bJyRJKKVpaktx82wbuf99ONm/txjTfOMdctsx//aNHkFLwiU/fychQju899BrHjozg+yEdnRl+4Zffwc23bsB2rr0u+LV3xtqSClTE/uwZHux/dcbjWzNd3NmxeUEXTmqapmnaSpZ0bN51/WbcIOSvnn6JwVyBvsksfZPZ6W0MKbCkQXM8xk29q/jsntu4de3qBW9L9TwVyFeCKFLsf62fMIxYv6GDzVvmdnNzfLzIY9/bz8svnqSru4nN21aBUpw6Ocb3vvsaI8M5PvOL97Lt+p5Z++ZzZb77rVc4cWyUVDrO2/dsoVCocurkGPGEjWFemzMgdNChXRFKKbwo5EBuiC+deJbhc+pBpEyH29vWcUtb7xK2UNM0TdOWn5Rjc+/W9QzlC3z52VdJOjbNiXpmJ0NKWhNxNnW0sWfzWm5bt4bmeWZ9muv4Ra5am2fLlwelFKdPTWAYkk1zDDgAulc188mf3cNHf2o36zZ0TE+lOnl8lC//1ZO8vrefo4eHzxt0HD0yQrFQ49OfvYfdb9uE7dSnmRUL1XrQsUwyEV5pOujQFoRSigjFpFvCFPU88vUcKfXc8JXAY39ukC+feJb9ucHp/Qwh2dmyhnf37HjLdTkSpsOqRNOyKSrYHku9pUKPmqbV00E323HWJFqWuinTMlb8mpyPrV15SinGS2W+8txevvr8XlY1pfm5O2/lozdtJ/4W1kvU6+UAql576FJLIRVwcnzqso+3lJSCUslFSEG6aXaNkwuxLIPVvbPXxazf2Mn1O1bz/DPHKBaqKKVmfR9Uqx73vms7u25eNx1wAKQzcz/+1UgHHdqCybpl/q9XH6QjliZpxbClQRhFTLgljhfGOF4am7HIWyBYm2zlvatvZHvz7DsF8/X2jo3sallDuEwWkjuGQdzQc7417a2IGRY/tWE3H+y9eambMi1p2jjXWPFSbWkEUcTrZ0b5+5f3I4XgbRt7+fgtO7DNt3b9JR0bU0rCKGSiVLlkitowinjh9Jm3dMyldHbRPdH8+gdBEFKpeFQrHr4fEoURSinKZRfDNIgihVKzM1DHYzbr1rdf80HGm+lvTW3BuGHA0+Mn5rStQNAZS/O+1Tt5T8+OBTm+Y1jzKk6nadryJ4QgaTokzYvn+te0q1HF8zk9laXseSQdG8c0qfkBUsrGaMXljbh1pJM4pokbhBwdnWC8WGZVU/q82RaVUpwYn+Lp46ff6uksCSGgqSmBUoqpqfKc9lFKUav5nDg2yovPneDYkWEK+Squ6+P7IcVCFc+98BqXdCaG4+j+yJvpoEO74ixh0JNo5v1rdvLTG3brDDCaNkdKBUTRFFGUQ6kaECEwESKOlC0I2dzohIhz9gkJ/EMoQgxjNYbRvmTt1zRtfgwpSdj1UYmy6/H0idO0pxLc0NNF0rbrd/AbzmaLilsWzYkYKce+YMr27as6aYrHKNRcJssV/nnfIdIxh7WtTViGgWjUBim7HiP5En/46FOUPe9KnfaCEkKwfmMHYRhx8vgovh9gWRfv/gZBxGuvnOavv/BDioUqN+zs5aZb1tPaliKesHnhueM8+tC+ix5TF+CcTQcd2oIxpKTNSVILA7wwIKRe4EdSz6wRNywydpwNqQ7et/pG3rnqehxDX4KaNhdRVML3D1CrfRfPfY4wnAT8RsDRRTx+P8nULwBvDOfXq/COMzn5MyhVIZX+ddLpX1uyc9A0bX6StsUNPV3s6OniwNAofRNZ/vixZ2ZtJwDLNGhJxNnU3srbN65lz+Z1bGhvIW7NvuN++/o1bOpoZaRQxA8jvvHS6xSqLu/evpmuTAopBDU/4MjIBA++dpBDI2Ns7Wzn9FSOmr98aubMhZSCbdevIp6wOX1qnMMHh7hhZ+9FR4myUyVefO4EE+NFPvDhW/jkZ+4iFqu/jmEYMXB6YtnUBFtJdI9PWzApK8bPbdrDcDXPRK1ENfTwohBbGmTsOL2JVm5sXs2u1l6abD3PUdPmKoqq1Grfo1j8E1RUwDQ3EIvfhCBOFE0SBKfw/P0kVPSmX6QRnvcSUTSOEGlc90lSqV9CCD1VSdOWO6UUXhASt0z2bFrLyYkpijX3/NsCXhAyWigxWijxXN8Az/X184t33c6ta1djmzOTmnSkknzk5h1MliscGh4niCK+u/8I391/hJRjI4Wg7PmEUYQhBJs72vidB+7l/37kCY6MTpy3DcuVEIL29gx33Xsdj39/P3/3laf55f/53XSvap6ulaGUIgwifD8kFrdw3YBCvkImE2PN2rbpgCOKFKPDOQZOT04X/NPmTgcd2oIQQpAyHX5u856lboqmXXU87wVKxT9FRUWSyZ8lkfwZpOxAiPrUiSAYAAKEeHMwH1CrPowQcWz7Vnz/IEFwHMtamHVUmqYtDqUUZc/nhb4B/mnvQV44dQbLkGxf1UnCtjCknJ5EqRrbB1FE2fUYLZbIV2o8faKflkScrnTqvNXJ333dJpRSfPPVA5wcnyJXrVHzA8quhyElMcukNRFnfVszv7DnNm5Zu5oN7S0rLugAMC2Dj/3UHZw4NsJrr5zmz//k+9z/3p10dTchDYnvB+RzFYIgYs8920gkbLq6m9j7ymmOHhlm45YuTNOgXKzx8gsnOXxoCNvWXej50q+YpmnaMhZFZaqVfyAMB0kmP0si+RkMo23GNqY5u8ZNfWpVHtd9BtPcQDzxMbzcy9Rqj+ugQ9OWOTcIeaFvgP/3+0/SP5VnbWsTH9h5Pfdt3cialgwxy5peMqBUPbtUyfUYyOZ55MBRHt5/lPFSmef6BnjX9ZtZ394yK528lJIHdmzlpt5VPN93hoPDY0wUy1R9n7ht0ZZMsHN1N3duWktLIk6oFHs2raPi+SRsi/ZUcla70zGHuzevxw9DOtMpOjOpS56rIesjKfdsWQ/Atu6O804JeyukFKxd387nf/1+vvaVpxk4Pcl/+aOHSSQcHMfEdQOCIOSmW9fztj1baGpOcMvtG9i/b4DnfnyME8dGSSYdyiWXZMrh+u2rUXp61bzNK+hQyifyD6Ki0fNvIGJIYz3SXLsQbZuzKBxDRWNI83qE0HURNE27egTBMYLgGNJoJxa/Hyln37E8P4XnvUgUZYknPopt70IIC8/9MUpPsdK0ZW28WOYfXz3AqckcLYk4771hG5+76/ZZ06TeYBC3LTrSSZriDoPZPI8dOclEqcJ4sYwfhjgXSLPbnUnzoV3X86Fd11+0TaYQfPzWG/n4rTdecJuN7a382Sc/ONfTBCBuWXzi9p184vad89pvvgxDcsOutfx2byvPP3OcE8dHKeQqRJEimXJo78iw48Y12LaJYUh23NjLZz//Ezz/zHHGx/IIBFu2reL2t23CcSzaHk+zZm3bjPXilm2y7foeMk1xmpsTi3o+K9H8RjpUGb/8BcLaIwjZAWLm7kJ2YSY+dcWDjrD2KKH3NE7zfwJ00KFp2tUjCE4QRXls+yakbJtHisyIavUhhLCIxe5DyjYs60b8RhBjWTcsars1Tbs8SimylSovna4X0u1MJ3nbht6LBBwztSYTZM6pSu4FIWGk1x9AfcSjrT3N+z546bo/Tszixl1ruXHX+fu0Gzd3znosnY7xiU/f+ZbbebW6vOlVIo2Z+ATC6HrT4wkM80oP2ytC7ylUlL3Cx9U0TVt8UZRFKRdpdM15dOLs1CrPfRop27GsmwCJ49yD5+2lVvuRDjo0bRlzg4B8tQaAbRo0nxNEXEqh5lL26jUkpBAkbAvL0DdktaV3GUGHQsgUZuz9SGvrpbeOSkThKVQ4iFJVhIgh5GqkuR4h07O3DyeJwpOocAyFjxAppLkBYfQixBv1HKJggCg8BdEkkfcqiDhB9UGgPg9QCBMz/gHg/DmqNU3TVgQVAgqBybn1Ny6lPrVqkkTiY0iZQqkQ294NKDz3GVTqFxFi7h0ZTdOuHLOxkLvmB1Q8n+FCkW3dHZfcr+b7vNo/xMnxSQDaUgnaUgnMC9Tr0LQr6TKCjrn/0lPhFIH7Q8LaI0TREDRKxQvZgxl7D4ZzH+KcBZFR0E9Q+y6h+yRKFRrbC6S5BTP+UaR923R2lig4Rlj7QT2giSZBOASVb3A2yBAihhn/F/M/PU3TtGVEyCRCWERRHtTc8+PXqt8BQKkq5fL/qP87ygGCIDiB7x/Fthd3DrWmafMnhCAdc9jc0cb+oVHGCiW+f/A4PU0Z1rU1z1qboZSi5geMFErsGxzmm68eoG8yixBw27p6xqnLrVyuaQtp0bJXKVUj9J4jKH8RIdNY8Y8iZBcqmiB0f4Rf+QoIEyP2AELEUFGRoPogQfVbGNYOpPNBhEijwn6C6nfwwy9gZZqQ5naEMJHWVoRsBuVSy/4y0liFnf5tmB4NkehRDk3TVjpD9iBEgiA4TqRKc1q1pqIcrvs0YOF5e/G8vWd/ghA2UVTEdZ/UQYemLVPtqQTv2b6Fvokpiq7HY4dPUKq53LpuNR2pJI5lIgA/iqh6PhOlMkdHJ3llYJDBXAGAbV3tPLBjK2tbmpf2ZDSt4bKCDhWVCGoPIryZi2iE7MBw7kLIJlQ4SuD+EPAxE5/GjL0HhAEqRBrr8Ep/TFB7HGndiDA3EQWHCd0nkGYvZupz9bUhQoLyQSTwS39B6P4IaawD0YQ01oCxBpSLEBaIFNK+RU8X0DTtqmJaW5FGF76/H98/hGn2nqcex0ye9wJRNIHj3EUs/v5zfqKIwlFKpb/Ec58jSn4WKXWhTk1bbjLxGPdv38KZbJ7Hj55kvFjm+4eO88OjJ2mOx0jYNoj6IvFSYw3H2QrZmZjDjp4uPnzTdt62oRfH0tURtOXhstZ0oEoE1e+eM6pQJ63rkfZOBE2oaITI3480NyDt2+oBB4AwENYOpHkdob+XKDiFNDcR+YdQ4RBG7NNIY3094AAQFobzDoLK1wndZzFjH0HIprd21pqmaSuEYfTgOHcS+IeoVr6GlBkc545G4FGfMqGUj1IeQiQQQlCtPgQIEsmfIT5jmqkiDIeo1R4jCPoIgqPY9q6lOC1N0y5CCkFvS4bP3X0769tbeLl/iIGpHBOlCoWax2S5ClAv4mcadGVStCUT9DSl2dbdwZ0b13Jddwdxe2HrXWjaW3F5azpkE1byZxHGqpk/Ec0I0QKAiioQTSHEDYg35ZUXsgUhWyDKQpRvbD+FUmWEbAcxM7exMLpBxFDhMODNv8mapmkrlBCSePwDBMEpatVHUMU/xff2Ypj15BoqqhJGY5jmBmKx+4miMq77NFJ2YNtvTt0oECKNE/sJKuW/wXWf0kGHpi1TUkrWtDTxM7t38Y6tGzk+PslooUShVsMLQpQCy5DELIumeIyuTJJ1rc10N6UvWJND05bSZV2VQsQx7LvnlL3q4uZazVHwxgJ2XQFS07QrQylFOZhiX+57C/acXbEtrE/djCHm/vVrmhtJJT+LITtwvWcpl7+KEHYjo1+EQpJMfop6QcAXiKJx4okPYxizCwkKkcBx7qRc+iKe+7yeYqVpy5xtmmxob2FDe8tSN0XT3pLLm141B0IkEbINpYqoaAphnLP+I8rVs6jIZmikzRWyFSGS9UxUqgLijXS6KhwBVUXILsB+05HOLhbXwYimaQuvGEzy4/GvLNjz3dTyPtYmb5xX0AFg2TfUE2b4dxEGfUSqQD2VbhxpdGBbOwETIVpIp38TJ3bXeZ9HCBPL2k46/RsImUR/d2qapmlXwqKNvwmjG2ndSOTvI/JeQcbePb2QPAoOEQVHkObm+sJwQFo7EMYaIu8llHM3QmxvLCQPCN2nUNEUZvyds2t7CANEol4cUAVM5+XVNE27yhhGG4ZxD3DPBbdxnN04zu6LPo+ULaTSv7zArdM0TdO0C1u0Oh3C6MJw7iMKjhBU/hYVTSCMLlQ0Seg+DsrFcN6BMHoBkOY2jNh9hNUH8ctfwnDuBJFGhQME1QcRZi9G7L4ZIyB1EmndROg+jl/5Koa1HaUiwMOM3T//09M0TdM0TdM0bUEt4vQqB8O5A1SFoPYQQfXvAAOIELIVM/HJetDRmEtcr3L+AQSC0H0Sv/xF6lOnQoTRixn/CNK8DnGeKQlW4tOgygTVbxK63wcshOzUQYemaZqmaZqmLQPzCzpEHDPxCQjfPXONxoU2ly0YsfsR5iZU2IdSFYSII4xepLllVupbafYi4v8Sae0iCocADyHSCHMT0tx4wRochn0LiN8gCvtAlQGzngVL0zRN0zRN07QlN6+gQwgH07l3XgcQMoVh7wLmlpZRGG0Yxp1zqrr7xk4mhr0LY47H0DRN0zRN0zTtypGX3kTTNE3TNE3TNO3y6aBD0zRN0zRN07RFpYMOTdM0TdM0TdMWlQ46NE3TNE3TNE1bVDro0DRN0zRN0zRtUS1aRXJteRqrvMjp0sNUg7EZj29t/hSd8duQ56mDshgi5TNR28ep4rdotq9jQ+aDWDJ10X1GK8/TX3qEajA+4/FtzZ+hI37zJdt+PPd1RqrPEqlg+jFD2Ozu/H0sI3n5J6NpmqZpmqZdlA46rjFCGAgEgarghTkqwSihqtGbeg9qjoUfF4IflZmsvcZA6VFqsSm64rtpcjZfdJ8LtX1d+n3MpWilFBaKCD8qUAsnqQQjGCJGRHDJfTVN0zRN07TLp4OOJaU4OPVXtMZuoCu+GyEWf7Zbs3MdCbObUNUo+QMcyn6RKff1RT/umxnCIWa0YssMMbMN22i+5D4tzvUkzR5CVaPo93Mo+9dk3QNzPubq1H10xG8lImCq9jovjf/+WzkFTdM0TdM0bY500LGESv4gfcUHkdKkK377FTmmJRNYMgGAQGLJpZlWZAiHnuQ7aHaux5YpHKPlkvtYMnlOewWWSMzrmI7RMn0cL8wBYp6t1jRN0zRN0y6HDjqW0ETtVdwwS6g8FNdWF1gIiWM048xhhEPTNE3TNE1b2XT2qiWjGKu+NGNRs6ZpmqZpmqZdjVbcSMerE39IyTvFrZ3/huHK0/QXH0ZgsKnpJ1md/AmKfh8Hpv4bZX+IJnsL21t/kZTVO+t5IhVSDs7QX3yEydo+vCiHIWJk7E2sTt5HR+xWDGnP2u94/hucLPwTW5s/RU/yHkYrzzBYfoKSfwaIiJvdrErcxerkvbOmDLlhjv7iw2S9wxS9UxS8PhQBx3NfZ6D4vRnbOkYz9/T8NwxhzXg8VD5Fr4/hyjPk3AONxdQelkySstaxKrGHrsQdl8wEtRQqwShHc19lpPLMjMc747exveWXiJltS9Syi8u6h3lx7Pdoi+1kV9tvkvMO0198mJx3jDCq4RgttMdvZk3ynWTsDRd8niCqMVZ9kaHyExT9k4TKxZYttMdvYm3qvSTNVRdd15N3T9Bfepgp9yBemAUkjtlC0uymPXYLnfHbiJud593XD0tM1PYyWHmCotdHEJWRwiFmtpGxNtAZv50WZzu2kX6rL9e0Vyf+gPHqS3TH7+SGtl89b3YxpSIK/kmeH/1dHKONHa2/Qnts54xtIhVQ8E4yUPo+U+4B/KiAIRI0O1tZk3wnbbEbkW/6nJyr4g8zVHmK8epLVIIRIuVjGWniRjstzg66EneQttZd9Dk0TdNWmnKQ5WTpRaa8wTltvya+g7XJXVjSWeSWadeqFRd0VIMxJmqvcar4bU4Vvk01HEOpiKLXR8xoY+/kH1Ly+gkai439qMCdq/4Icc6gThDVGKk+y4Gpv6h3QiIPISQKRdY9zGjledal38eWpk9iG5kZx3fDLAXvBJO1fUzVXmew/CP8qIgiQqmQvHucieor5N1jbGv5NAmze3pfL8wzVn1xuuNz0axJSs2abhWpgInqK7w09u/xVYlQuSil6m1XAVn3EKOVZ1mbfoBtzZ9ZdlOXDGGTNHtIWb317FPhKNVgjJTVS0S41M27oFC5FLyTSGHSV3iQY/mvUQsnUYSgIhQw5e5nqrZ/On3vm1WCMY7mvsJg+XHcMIdCIVAopZhyX2eo/AQ7W3+D9viu83Z+z5QeZ9/kf8ENJwmVhxAGqBDlgRQmo5Xn8Zp+mi3Nn5y1bzWY4EThHzhZ+CZBVEapEIRAqQjhCsbEC0y5B7iu+efpSuxesNet1dlBX+Fb9AX/zLaWn8WWzQgx86oOVI2R8tMUvJO0xpI0WRtn/NyPypwpP8aR7N9QDcaIVIAQAkU0fb1vzHyMDekPYRmzA+3J2uscyv41k7W9BKoKSoBQKC9CCIPhyjOU/H52tP7KnNYVaZqmrRRjtZO8nnuUsdqJue3QAqsT12Ohgw5tcay4oAMgIuBU4Tvc2PZrZKyNvDLx/zBZ28uLY79H2l7HHWv+A5VgkGdG/jcm3f0UvFM02fXOTKQCct5h9k38Z7yoQE/iXjZlPkbc7MKPCgyWf8jJwj/RV3gQS6bY3PQJpDBmHF+h6C89giWSrEnex9rUA8TMDmrhJCfy/8hQ5YecKv4zHfFbcBKt0yMmSWs1t3b8LooIgKeHf4usd4j1mQ+wpemTMwIjgUS86e0RGMTNTlpjN5AwV9EZv52U3YtAUvIH6Cs+yGDpcYbKT9Fsb2Nt+oHFfBvmzZZNrM98iLXpBwiiKgPl7/P65H9d6mbNWd47zpHc39Bkb+Lm9t8mY28kiCoMlZ/iZPEfGa08T9paS7O9GeucEQM/qnAi/w1OF7+DY7RwQ+vn6Uq8HVMkKPn9HM1/lYnqq+yb+hN2d/4eaWvDjM55ENU4MPXnlIMzrE9/gE2Zj+MYLShCasE4E+4+8u5ROuK3zWqzUiF57ygn8l/HlEm2tnySVcl7MEV8OgvYePUVHKOJtL1uQV+vnsS9HDT+klIwwGD5cTakPzprmyCqcKbyQ0yZpDv+dsxzEhtEyme8+jIHp75AGLmsS7+Pdel/Qcxoxw2n6C89Qn/pYY7nv44tM6xLv3/GSFEYeZwuPsRY9XnaYjvZlPk4Tc5WJAZelCfnHmW0+jzdiTsx55mUQNM0bbmbdPvJeoN4UXVO2weN9aWatlhWZNAB0BG/lY7YrThGM+vS7yfrHqQcDHJ7578jba0jbnbQ4mwn7x2l5J+eDjrcMMfJ/D9RCyfojt/JTe2/hSUzSCFRqouY0QFIDmX/kpHKc3TEb6XFuW7W8cOoysbmj7Cl6ZPEjHYEkoTZRay1jWo4ylj1RSZrr9MeuwlD1qcNSWHOmEJUn24iMGWCmNE+K7h5MyEEKWstt3b8LkIYGMJBUN8nYXYjhUUtmCDrHiLvzfHOxhUkhGxknEpgiPiynAJ2MZHySVm97Gr/LVJWbyMoVMTMdkJV43DuS+S9Por+AK3G9un9xqovMFJ5BoHJtubP0Jt6N4aIIYQgbnYQNzt5fvTfkHOPMFR+io2ZjhnTnCrBCNVwAlBsb/nF+uiZkKAgYa6i2bmOSAWYcnbHOVQu5WAELyrQ6tzAxsxHsWQahAClSFm9dMZvRyAwRGxBXy9TJlibvp/D2S9xsvAtNqR2MiWnAAAgAElEQVQ/wrnpEiIVUvJPk60dJGF2szp134xgq+wPcar4HbywQG/qPdzQ+j9hyRRCSBJmJzGzA6VCThT+npHqM7TGbpgxvc2NclSDUULl0pu8n+7EHgzhgICE6iZjbWR18icwpINET63SNO3q4UcuU+4ZKkFuqZuiadNW7ELyJnsjpowhhCRtrUUgMYRNi3M9ABKTuNGBUhFeWATqIxRelGOo8gSO0cKa1LuwZXOjsy8aGZVaaHGuJ2GuouT3k3OPnPf4aXs9HbFbiBsdSGEghEAIg4TZTcrqxRAxquEYoXIvchbzz1clhYFtZLBkEinMxnEFUpgkzR4y9iZC5eJHJSK1fKcsrUSO0Uxn4nbS1nqksBqvvcSWzaTtddhGE35UwIsK0/soIqZqr1P0++iI30KrcwOGiDfuyNfft7S1jlZnO4awGas+jx+VZhw3ZrTWp1MBA6XHAFH/TwikMDBlHNtInzdolcLGkU2AoBKOMVHbV29343qXwsKSSUyZWPA6MUII1qc/iJQxcu4RptyDM34eqhqD5ScQSFqc68hYbwQMCkUlHGWs+hwJcxU9ybuxZKbxOtQ/a3GjfmMhZrST905Q9E/NeH5bpjBkHICJ2mvUwnGEYPrcDelgG2kMYc+a9qVpmraS5bxhCsH4FS36q2mXsmKDDls2T9/lr9duEDiNAOJsB+Ls3HjVyBAVKZ+S348fFTFlkiZny6zOhhACW6aJGW14UZ5aMHHe4yfNHuJmx6yOWr0T2oQhrPqai8ZUqivBkLHp0YP6cfWXzUKyZJqMtfE877nAFAlMkSRSAZHyp3/mBlPTi/1TVi+O2Xqea06SsLqRwqHkDxApb9ZxN6Y/gsDkQPYveHzw5ziR/0fc8NJ3sAQGGXsjqxJ3U/BO8tL4v+fZkd9huPxjgqj8Fl6NuUmYq+iOvw2IOFX81jk/UYRRlcHy41hGitXJ+6YDK4AwqlH2z+BHZWyjibS9/ryfVcdowjGacYNJ3CA74+eGiLMqcRcpax39pUd4avjXeX3yz8i7x2e8R5qmaVebKe8MBX98qZuhaTOs2OlV51tsK8XsbFPAdKSvVDjdMSl4J3nszKc532iDIiJSPlLY9cWn52HKJIaIX6B1ovFHcfGO//yDAqUUbphluPIU47WXKXkDuGGWQFUII/cSIyvaWyGFhS0zF/x5vVM88z33ozJBYz7tkdxXOJb/H5zvmotUgCKoX3tvWlQvhGBH6y+RMLs5mP3/mHIPknOP8vrUn9KTvIdNmZ+kLXbjBduUttaxq+1fkTC76C8+wmD5MYYqT5K0VrM29R7Wph4gZa2Z9+sxF0JINmQ+wmD5R5wpPcqNbb+OLdP1pAi116gEI2SsjXQn7n7T6+HjhXkAJmp7eXTgk1zss2oIh1DVZp17b+rd2EaaI9kvM+m+zpHclzmW/zvaYjeyMfNRuhN7potlapqmXS2mvDMU/bGlboamzbBig47LK6Wnpkce6tOx4hedViGFjXmBwEIiEVewnJ9CEUUeI5VneG3yP1MJRpDCJm52kLBWYcs0CkHRP0XBO37F2nUtEY1pPfOhzglCDGEhZeyiV40l00jON03KYmPmo6xLv5cz5R9yqvBtJmt76S8+xGDpcdam38uutt/ElLOv17NrgW5q/1/Y0vQJ+kvf50zpBxS9Uxyc+u/0Fx9iW/NnWJt673nTRL9VXfHdZKz1FPw++osPsynzcULlMlB6FFPE6E7uOafSfJ0657MqMS75WTVE7LxrUqQw6I7fSWfsNiZqr3G69BAj5WcYr77MePVlOuK3clPb/0rGXr/g08s0TdOWQjUokHOHcaPKUjdF02ZYwUHH/AkM7EYa2SZ7E3u6/xPxc1LaLkWL5kxB0T/NqxN/gBcVWJN6Jztaf4WUuXZ6k1o4wZHcV3TQsYyYMoEh653h61p+js2Zn8K8rAX09TUcBgnWpd7PutT7KPr9HMt/jVOFb9FffBhHtnBD2+cvsC+gTFLWOra3fI6tzT/DePUVjuW/xnj1JY7l/w7baGJ18h1v4Wwv0HIh2dj0MfZO/AF9xQfZlPkYXlhkuPIUlkzTm3z3rICivtakPqrUHr+Z3Z2/10jyMO+j19e+4NAZ301nfDe1tkn6i49wPP93jFVf5ED2L7i5/V8TN9sX4Gw1TdOW1pQ3SN4fXepmaNos19StPSls0tY6TJnEjyrk/ZMA04uxL/Rn8TSeO7r0uo9QueS9Y1TDUVLWGq5v+Sxpa9057awvzPXPWcSsLb2Y0Ubc7EIKi5I/iBvV12Fc7jX3xjaSjL2eXW3/iq3NnyJQVUaqz3CxKXvnPr8lk/Qk72Zn66/RnXh7o1jliYvu/1asTT2AKZMUvFOM1/YyUnmaSPk02RtpjW2ftb0p4o2EDHG8qEDR7591Dpf3ugniRjvbmj/FDS2fJ260M1p5vrG+Ra+B0jRtZVMost4gBT21SluGrqmgo77wtIVVibuphROcKnwbLyrU59OrCKUUSoVEyieIqgRRDaUWbyG4baQRCEpBP5Hy68dvFIybfVw1vfhVIJCYKHV2rYoiVD557wQTtdcWrb3a/Elh0ObcSNpaz0jlWSZq+whUlUiF0+9zpELCyMOPytPXwblC5RFEFULln3OdNv4QTRe1O5sw4VxKRYSRSxDVGtf5G9eMUlF9CqFMThe3XCyWTLM29QBKBZwpP8pw5WlMGac39Z7zbi+EIGF20xW/g5I3wJnSo/hRcfocpl835ddfm8id9ZmJVEAQVQkjd/r1PnvukQqwjSaEMIkaa2k0TdNWOqUUU94gxQskwdG0pXRNTa8CcIwWNmU+zmRtHyOVp3lh7P9kQ/pDZOyNCCRumKXkn2G89jKO0cLW5k8RM1oXpS1tsZ2MVV/kTOmHdCf20BnfjUASERJE5Rk1B6SwSVprMESMSjDGqeJ32dT0kxjCxo/KjFVfoK/wLWrh5AWPV8+s5DVS6Sq8qDQdyISqgh8WCIVVL0wozEYq0YWJS+udRL/eqUYRqur0AutIBfhRES+McTYdqiHsRh2T87fdj0rTFd2DqIoXFuppbC/Q9lB5RMprdDwV/jmZm7yw0FifczaNrI1xnkQFczjJ886Y60q8jSn3AH2Fb7J/6s8oeMdZlbibuNlBENVwwyly3lFGKs+wrfnTdMRvw+CNtRWD5ccZKv+YzvittDZSxNbPqcZY9SWO5v8WU8QbxQFnNqAWTnK69BAVf4SuxG4y9kYskUKhqAZjnC49xGjlOVJWLyl7/az9F9KG9IfpKzzIWOUF3DCLLTP0JO+94PZJazXrMx8k6x6iv/Q93DDHuvT7SFn1IoZuOEXR72es+iJN9mY2Zj6KYzRN7z9Ve50z5cdxjGbaYzeRtHqQOEQE5L3jHM79DbVwko7YrY2ihDptrqZpK1vRnyDvjRDqDH3aMnTNBR1SmLQ613NL+79m/9SfM1Hdy1jl+UbGIDWj09qbun9RF4uvT3+IofITFLyTvDj270AYjRGMgJS9hvf0/sM57TZIW+vZkP4Qp0sPcTT/VU4W/hFTxPFVGYFBT/IeViXv4nD2S+c9Xs47ypnSoxS8UwRRGTfMUQmGATiS+zKniw9hyiSWTNIZv53e1P04jTUwb5UflThT/gEjlWcJogp+VKIa1Id/J2v7eH70d7FlBlMmSFtrWZO6n7bYDW+03T3MQOkHFP2zbc9TDoYAOJz7a04V//mctu9mbeo92MYbmaaGyj9iqPwkXpjHV2VqwSSgCJXLs6O/jSXTmCKBY7bSm3w3q5J75n+SF5jeY8kEW5t+GgH0l77P8fw3OJr7WxQhZ8etpLAwhNN47E0UjFdfZLD8GJEKkMJEYhCoGlKYmCJBR/wWtjX/7HmP74U5The/w8nCNwHVCOZU47lsHKOFden30h1/+/zPeY6EEDQ5m2iL72S8+jJS2KxJXPz6MoRFV/x2drb9OodzX2Sk8gyD5R9Nv0b1z2q9SGbSXDXrs6qoV5GfrL1GpIL6Ky3Mxi9jgSFs0tZarm/5+UW7saBpmnYl5fwhvZ5DW7ZWXNARM1pJmj31LD3n1ONIWj04spnpu5VC4BitJK2eWZlxDOnQnbiTJmcLZ0o/YLz2MhV/mIgAWzaRtHpoj91EZ3z39MLzs2yZIWWtxjFaZtyJn7GNkSFhriJmtDWqVp9f3Gzjzq4/4HjhG4zXXsUNpzCEjWO00ubsPM/27exo/TwtznWcKf+QajCKIqLZvI6e5D2sTt5HzjtKW+zlRmduZifMC3PkveMUvdPTjzlGCw716TlumMUNs41jdc6qF/FWhMqj5A3MKLYohUXSXA1AEFUIGpk2QuXREd4+Y383zJH3jlHyB6YfO7ejeG7bE2bXrLaX/SFy7mHCcx5/49hvjLpUw/FZ6WcNYZO0VhM3uzAukJbZkHHiZhemiJ83g1TMbGNH6+fpTuxhqPwEWfcQbpRFYuEYLWScTXTF76A9dtOsdNBdibezXZWZqO6l5A/gR0WUCjFlkrS9jq742+hNveu8Fckdo5m16fdjiDg59zCVYJRAVRGIRiHMbfQk30FbbNcFz22hCAzWpt7LePVlTBFn7QWmVp3LlAl6U/fTEtvOYOlxJmqvUglGAdX4rK6hI34LnfHbsM6p4g7Q7GxjS9NPk7E3UPBOUguzRJGHFDYJq4v22E2sTT1AwuzWmas0TVvxlFJkvSG9nkNbtsSb54+/iV5ZqWnaglAq5Fj+a7w2+ce0OTdw3+q/mncK4itNKcVI7Rhf6fuNBXvOm1rex31dn8OSs1P8apqmXS4/cvnx+Fd4afKbl1WJ/NbWD3Nnx08Tf9MNHE2bpwtOEVpxIx3alRUqrz4KdDnzQ4XAkikSZtfCN0xbNJEKqIWT+GHxsvY3pEPCXDVjJFAphR9VOF16qD51Mf3Asg84NE3TVpK8P0LeG7msgEPTrgQddGgXVfYHeXb0f6fsn5n3voaw6Um+g9s7/+0itExbLG44xYGpLzBQ+t5l7d/kbGFP1x/hNKa/CQGBqjJYfoyce4SU1cua1LsWssmapmnXvJw3Qs4fWepmaNoF6aBDuyhLpliVuAs3nJr3vlKYtDizazBoy5shYo11LZd3tyxhdmNIp7HovwpEZN0jHMj+BZZMsTnzL4kbuhCfpmnaQolURM4b1ovItWVNBx3aRcXNDna2/dpSN0O7gmwjw8bMR9iY+chbep5Xsv+R4cqPCVQFoQSO0cyq5D1szHx0gVqqaZqmAbhhiZw3jBuWlropmnZBOujQNG1RtMd2EioPP8pjyyY64rewPv1BDL2AWtM0bUHl/VFy/vBSN0PTLkoHHZqmLYpNTR9nU9PHl7oZmqZpV72cP0LW00GHtrzp5PSapmmapmkrVKgC8t4IRX98qZuiaRelgw5N0zRN07QVqhxkyXpDBMpd6qZo2kXpoEPTNE3TNG2FKvij5LyhpW6Gpl2SDjo0TdM0TdNWIKUUeW+UrA46tBVABx2apmmapmkrkK9ccv4IpWD+tbQ07UrTQYemaZqmadoKVPInyXqDKKKlboqmXZIOOjRN0zRN01aggj/GlDu41M3QtDnRQYemaZqmadoKE6mIQjCmiwJqK4YOOjRN0zRN01YYNyqT84aphcWlboqmzYmuSK5pK4BSEW5UoRaWqIVF/KiGr1yCyMWPXALlEqmQiAg1/Xd9jq9AIoVEIBHCwBAGprAxpY0pnMa/HRyZwDESODKJKWNIoe9JrFQKBUpRDYtUwzy1sIwXlXHDCr5yCSOfUHnT14lCNa4TY/qPIUws4WDJBLYRx5ZxYjJF3MxgiRhCiKU+Te0C/KhGLSxSDYt4UaX+vkdVfOURRh6B8lGN9z4imvEdUf9eOOc7QSZwjBRxI0PMSCGFsdSnpzUU/Qmm3DNL3QxNmzMddGjaMhOqgHKQpeRPUQomKAc5amGh0YEsUg0L+FEFL6oRKBcvrP8dqqDRiQinOxMAEokQEomBEBJDmNOdCks49b9lDEcmiRlJYkYKR6ZwjCQJo4mE2Tz9d8xIIoX+2liOgsinGIxR8Mcp+GOUginKfpZKmKUalnDDEm5Yng5WA+UTqbDe+UQhzw06MDCkhSViOEYCWyZxZIKYmSZpNJM0W0maLaTMNprsTpJmC4awlvoluCaFyqfsZykE45SCSUr+FJUgRyXMUQ0LuGGZWlTGmw44PYIZAWfUuCFR/444G3TM/E5IN74HmkmZraStdjJWJ2mrHVvGl/oluGYopQiURzXMUw6y9Jf3Me72LXWzNG3OdO9B05aYUhHlMEfWHSLrnaHgj1EMJin6k42gI0stLF12dpKIEFRIiA9qbvtIDGwjQdzIkGx0NhJmM0mzhbTZRtrqpKnR6TCFo+96LxE/cplyB5j0+pl0z5Dzhsn7oxT8MSpBrv7ez1FESKTCN66Rs5eb/+YtBbaMN4KOVpqsLlrsHlrs1bQ6a2i2V2HLGKCvicXihmWy3hBTXv09z3kjjUBzklIwiRfVmPOHHc4Z9QgIwgtXtZYYJMwm0lYHGauTZqubZruHNmcNrXYvcTOD0O/7gohUhBdVKAfZc/5Mzfj/nD9C3htbsGMOVQ/x/MQ3MIW9YM95JV3XdC+t9mo9GreM6aBD05aAQlHyJxmr9THhniLrDZL1hsh5w5SD7Lw6i4shIqQWFqmFRbLeG5lRJCZJs5mU1U7GbJ/ufLTYPbQ6a8hYnUhh6I7HRQjq01gunyLvjTFaO8ZI9Rhjbh9Tbj1YvTLXjcKLKnhehaw3yACvY4kYaauDFruHDmcd3fFtdMe3kDJbdQdggfiRS9YbYrR2nPFaH1PeAFl3iGIwQaC8K9KGiJBSMEUpmGK4eqQRhDTTaq+mzVlLR2wD3bHNtDq9egRkjhQKpSIqQZ5y47UtBVPTAUYlyFEOc9P/dqMK8wko52O4eoTh6pFFee4roTO2kRZ7FaC/c5YrHXRo2hXkhVUmvH6Gq0cYrR5vBBxDi/qLZCFFBBSDCYrBBPV8KYK4ka7f9bS7abZ6pjsg7bF1eu7/eRjCxLiMKWoKRdYdZKDyOmcqBxitnSDrDRKqWUMRV5yvakx5A0x5A5wu76XF7qEztpFV8W2sS95Es73qss5ZU1SCAiO1owxWDjFWO8GEe5qiP0lEsNSNawQh9dGVgcoBkmYzHc56umKbWZ3Yzqr4VhJmE3rU6w1B5NYDC3+SYjBFufH6lYM8lTBXnxoX5KmGBQJ14VEnTVuJ9G8BTbsC3LDCSO0op0t7Ga4dZaJ2ikqYvwoKOimqYYFqWGC0dhxDWI15/l202mvodDbQFd9Ch7MeQ1jXfAAiMTGEjZjnIv28P8ap0sucKr/KUOUwpWBy2V47gXIZd/sYd09xuryX0+VXWZ+8lY3p20mbbXrkYw4UikqQY6DyOv3lfYxUjzLlncGLqkvdtAtS5wQgZyoH6Cu/PB10rknsIGk2c20FH4paWJqeJlv/u/6nEuSphHmqQYFKmKcWFpft51nTFpIOOjRtEXlRleHqUfqKL3KmepAJ9zReVFnqZi2aUPnk/RHy/ggD5X2kzXaandW02avpjm9lTXwHLc7qpW7mkjGkiSnnvuDai2r0l/dytPgMA+V9FP2JJZ96N3eKUjDJseKzjNZOMlB5na2ZO9mQvA3biOspeBdQDQoMVPbTV3qRweohst7QshjNmg9f1RitHWfS7edM5QBrEjvYlNrN6sR2YkZqqZu3KGphiaw3VF+T509MJwGpBnkqjRsz1bBwVX//a9ql6KBD0xaBUhGT3hmOFp6mr/QS4+6pa+6XjUJRCMYpBOOcKe+jr/wKbfZaumOb6U3eyKr4NiwZW+pmXlH1qVVzW6SZ9QY5lH+CY8VnmXT7r9i8/cVQ8Ecp+uNMuKcZr53ixuZ3k7G6dFrmc/iRy1jtBEcKP+Z0eS9Zb3BFv+cAgfKYcE+R84YZrh5hffIWtmXupiO27qrLdjZYOci+3CNkveHpbIMrLVjUtMWmgw5NW2C1sMip0qscLjzJYOUg5TC71E1achFRI8vO8IypF/d0/jyWdJa6eVeMgXXJzDCRChmo7Gd/7lH6Si9TCfOshPU+l6KImHBPUQ6mmHT7ubn1A6xJbL/qOp/zpVR9ROho4WmOFp9mrHYSNyovdbMWVKBcRmvHyfujjNaOc13mHjan7yBhNi910xZMIRhjqHqYcqC/7zXtQnTQoWkLKOeNcDD/OIcLTzYW+S79Ys/lxo1KjFSP4cjkNTe/vz696sJBhx+5HC8+x2u5hxmuHMFXtSvYuiujGhY4XnyOYjDBHW0/ycbUHfOacnY1CSKP0dpx9mUf4XTlNQr+wqU/XY5qYZHT5b3k/RHG3T5ubL6fNmetTjKgadcI/UnXtAUQqZDR2nFeyz7MidKLlIOppW7SsmZIm62Zu665zoZsFGY8Hzcsc6jwBK9lH2LCPX1VB6wRIcPVI/x4/Ku4UYXrM/ddc4FHLSxxovQCr2UfZrR6/KoMMM9HEZH1htif+wFZb5CbWz5Ab3Jno7aLpmlXs2vrN76mLYJIhZypHODFyW8yUHn9mlu7cTlSZgub03csdTOuuPr0qtmdazcscyD/OK9OfZspb/CayWQz4Z7m2YmvE6mIG5rfdU0EoQpFOcjyevZ7HMg/TtYbRF0F0+fmy43KnCrvpRRk2eW/l+sydxM3M0vdLE3TFtHV/w2vaYvo7Pz75ye+wZnK/hW/8PNKkMJkY2r3VTWfe64MaWK8aXqVF1U5mP8Rr0x9u9EBvTYCjrNy3hDPTXydlNnKhtRtV/XicqUi8v4oL07+E0eLT1/zI6KRChirneCFyb+nEmTZ1fI+UlYL11ZqXU27dly93+6atsgiFTFYPcRzE1/XAcc8mMJmR9NPXJMpUw0xcyF5GPkcLz7H3ux3r8mA46y8P8ITY19itHYCpa7Ou/5KRUx5gzw19mUO5h+/5gOOc+X9UV7NPsRzk1+n4I9ftdeApl3rdNChaZdp0u3n1alv64BjHgSCnvh1tDvrl7opS8LgjTUdCsXp8mu8OvUdJt3+azbgOGvC7eOHI/+dWlRa6qYsuKiRQvvJsS9yvPjcVZedaiFUwiwHco/zzPjXdOChaVcpHXRo2mUo+OPsz/+Ak6UXdS72eZDCZEfzO6+5RcNnyXOyV43VTvJ6/vuM1I6toIJ/i2uoeogXJ/9hqZuxoJSKyPnDPDn61/SVXr5mFoxfDjcqcbjwJE9PfJViMKEDD027yug1HZo2T35U43R5Lwdyj+FF1aVuDgCWiGFKB0NYGMIABIqIUPmEUUCgvMZozNL+Ek+ZbWxK7V7SNiyl+vtjUQ6yHM4/QV/p5SsWtEoMTOlgShsTGyEkofIJIo9AuctitC4iZF/2e6xP3sLa5K6lbs5bppSi6E/w5NgXOVV+dVm8xhIDQ9qYwsGSNgJJELnT3xFLfRPFiyocLfwYA5M9nZ8maTZfk1MxNe1qpIMOTZunSXeA/blHqYS5K3ZMUzi0Ob0026tosrpIWx0kjCYSZjO2jCOFgUQCAiEav6BVfQqPIkKhCCKXalikGhaoBnmKwQR5f5SCN0bBH29Ma1m8oEQg2Za5G8dILtoxljsDE4nJqdIrHC48tSiZzhyZpCO2kQ5nHRmrg7TZQcpqw5EJhJAIBKIxyH32+vj/2bvP4Dyz68Dz//vENyfkHEiCOXYi2S21OqmlliVZsmRblmfG49HUrNc7ux/mi6t2tzZUjb07Na6Z8lbZa+/UzjjIQRp5bUlWstTqHNjsJpuhmcGARGS8OTxpPwBEN5uZvABeAPfnolUMOO8D9Bvuee655/iBR9UrUnBnyLsTTFeHmKpeZqY6sux35ktellcn/pRf7vndVT+xvuIXeHPqrxnMv7PsCYcpQjSGemiye0mYzfPPBbNpcT6OQCAWDu0HwcL7RODjBDUK7hR5Z4qcM8lsbYSJyiAFd3rZrr3mlzmVexlbj7K/8ZcJ6fFle+z7pWNiaRFcbfn+O3uBK/Vmki4MdGGt2iRvvc19Wo1U0qEo96DoznE+/zaj5dNL+jgCjSa7j87oDjrCW8nYXdhaePEgsiYMdGHMLx4WFpK3ExBAEODj4Qfzv7zAwQ2cxbvdhYVJ0VPVy0xVLzNdHaIqsb5eFwY7Us+u2g80Gap+kQuFQ1wqvCt1EFzG6qQ/9jAdke1krE4sLfyRna8Pnyu3cm3R6QXuwvOhihNUKbozjJbPcKnwHqPl08vWDnq8Msip7MvsSj+/LI+3FBy/wrHZH3Mq99KyJRwJs5ne6F46IztotLsJ6XFMLfSR54GJQPvwxsTHzJczBYvPg2uL2qpXJOdMMlY+xaXi0fmSwCWeI1PzS7w/+0OSVis7ks/UfQK6KXGQzsh2/GD5SiUvFt/j0NS3KXpypqBvSTzJnvQL2NrqvDEUN5vQ1LK2rqn/Oopy1wLmaiOcyb2yZCUIET3FxvgBNicOkrY6sLXo4qIBwX0v2AUChEBHm4/1MUEQkLE76QhvWSyzqHhFZqpDjJbPMFY+zWT10gMtOruju8hYHff99WvBWPkMk9XLOH75gQ+OW1qYjfH9DMQfp8nuvW6BeatF5a0IIRDoaELHxAY9BgQkzRaa7H62Jj7JVPUKp3OvciH/9pLv8rlBjXdn/p4tiU9i6eElfayl4AUulwtHODT97SUvwTSERVd0BwPxT9Ae3kzUSGNqYYzF58HdPxeu/XtDzJfgXRMYjfPvD5Gt7Eh9mtnaMOfzb3Gh8M6STlGv+kXenPxLUmYr3dHddT3HJazHCS/zjsx09YrUu/shPU7G7lr270NZP+r3FawodabsFRgunWSmNiI9tiXC7Eg/y/bksyTNFmw9ioZ+z4vH+yWEQMdA1w0sIgDEjYCM1UFvbC+OX6PsZblaPsvl0jGGiscpujP3tHDemfz0ut/+doMarvdgd71NLcRA/HF2pZ4nY3diazF0YSzBc0WgCR1bj2DpYSJGmtbQRocc4gsAACAASURBVLYkPsH7sz/kYvFdHH+pSq8CZmujnMz+jL2ZX1iix1gaQeAzUx3ixYn/h7KXW7LH0YRBV2Qne9Iv0BbeTFiPYwhrsWRKpg/fH2LYWpS42UhraIAdqU9zOvcyp7IvUViiFsAFd4YXx/+EL3b+jzRYnUvy/SmKsjxU0qEodynnTHAu/5b01qZt4QEONH6NjvA2bD162/KH5STEh3c8Q/r8FPG01cGmxEEcr8Jk9SIXC+8xWHyHbG38tj+XhNlEf/zhZbz6takrsov9jb9MS2gjIT22bM8VgUAXBmEjQXd0N412Dx9kf86R2e8v2Z1uN6jx/twP2ZX+TF3f4f6oIAio+WV+evWPmKtdXbLHabJ72Zf5In2xh4joqSVKOm/uWgISNhLYepSM1cFA/HGOzP4DZ3OvLUkp2Ux1iJ9d/SO+0PE7hPREXbw/Kopy71bHO7mirDAvcJmrjXG1fE5q3E3xAxxo/BpNoV40lm/hcD+E0DCFjYlNSIsTNTN0RnayP/gVxsvnuFA4xIX8IQru9PwZko/YlngGQ9grdOWrn61F2Zf5AjtSz5Iwm5d1F+x688lHzGhgX+bzpK023pr6G65Wzi/BYwVka+NcLh6lP7Y6EtYAj6Oz/8BI6QOWoimDLkwG4gd5qOEXabb776uUTqZrO2Ft4c0krVbaw5s5PPN3zNXGpD5OQMBQ8TjvzX6fxxq+et2ATUVRVg+VdCjKXah4ecbKZ/CRd3hyQ+xRDjb9Gk12P9oqKxm4vhwrTG/sIbqiu3ii6Z8wVDrOqezLDBbexQ0qCHR2pp7lXmrLlQ8lzVaebP4N+mIPY2nhuigvEUJgihAb4vsxNJvXJ/+SsSVoruAGVU5nX14VSUcQBMzURnh76ttLMnclrCd5KPNFdqWeJ2Ik66hUcb4ML6qn2ZX6DA12D29N/TWXi0elPoqPxzvTf0t/7GFaQ5vq4nWgKMq9UUmHotyFspdjrHxGWry01cFDDV9alQnHx10rvdGFgSlCbIofoD/2CEVvjrPZ1ym6MySs5pW+zFWp2e7jk82/SXd014rf1b4ZXRj0Rvfh+g5vTH2Ticqg1Phe4HK5eJSCM03MbJAaW7YAjxeXaKJ6zGjg0YavsDP1HJYWqbvnAXxYjtkV2YHd/Ju8OfXXnMu/icwdn5pf4sWrf8Iv9/xbDGGv6054irIare7VjqIsk4pXkLqg2pP6LG2hTXW5eHgQQgg0YWBqIZJGCw81fJFPtvxG3ZeO1aPW0Caebv1X9Mb21mXCcY0mdDbGH2Nn6tPEjSbp8Wt+iYvFI9LjynZi7qfS7+7DfBvcg02/xp70C3WbcHyUJnRaQhv4ZPM/Y2viSemJwUj5FO/NfA/UtHJFWXVU0qEod+AFLkV3lqpflBKvNTxAe2Tb/AJiDd+pE0J8OBugzhdK9SZtdXCw6et0RnbMz2Gp85+fJjR2Jj/Nhtgj0uvt3cBhqHhsYYZEfap6JV6d+DPpTSYiepJ9mc+zI/nsqnodCaGRsbp4tPEr9Mcekxw94I3JbzLrjNX1c0JRlBuppENR7sDxK2Rr49LidYa3kzCbVs0CQlleMaOBx5u+Tl9033x3qlWRmApMLcTO9PO0hgekRvYCh9HyabwlHkZ3v4Ig4Mjs9ylKnl1iaWF2pp5nd+qzqyrhuEYIQbPdzyMNv0hnZIfU2E5Q5c3Jv2IpDusrirJ0VNKhKHfg+jVy7qS0eI12NxEjKS2esnbowmRv+hfojz2Crq2uhaYQgrbwAH3RfYR1uc/vipfnauWs1JiyVPwC7818F5kLYIHGxth+9qY/N99GexU9Dz5KCEF3dDd70i9IHwx6KvsyU7UrUmMqirK0VNKhKHfg4+E8wCTujwrpccJG8qZTwZX1TSDYGH+MjfH9hPTYSl/OfdsYP0Cj3S01phc4Uhs5yBIEAUdn/oGSK3eXozW0kW3Jp9ZMA4aNsf1sjB/EFCFpMX083pz8a/xAfqcwpf44vkvBLZFzitf9qni1ui6z8wOfolsh5xSp+U5dX+tyUN2rFOUOgsDD8apSYllaBEMlHMpNpKw2tiWfpjHUs9KX8kCaQr20h7cwURmUdg7KCxymq/V3V7vs5Tg6+wOpLXLDeoKN8QP0xPZKi7nSLD3MtuSnmKpe5mLhnRvm+NyfgPP5N5moXJBe0qfUn9enjvHNyz9mtDyFHwT4C+enfrnrGb7a9TQJM7rCV3hzU9U5/t3pb3I8e4F/vemrPNP8MGFj/c6sUjsdinIHPj5OICfp0IWOUC875WM0dAbij9MR3rpKznDcXnd0FwlT3l16L3CZqQ7X3V3Ck9mfUZJ4lkOg0RXZydbkk6tmCvvdag71MxA/SMJskRbTC1zenv622u2oY9fu9E9UZm/4NVmZZao6x0wtR94p3XYnoCPcxOONuzjYsJNdqQ1EdHm7ZsryWVvvaoqyFIJA2p1M13fUB6Ryg+ZQPz3RPUSM1EpfihTt4S0kzWamqpek3NUO8Mm701T9Yt2Unnm+w+nsK/gSD7jHzSZ6Y/tIWW3SYtaT/tgjXC6+T86ZJJDwnhrgc7HwHllnnLTVLuEKFdmKboXvj77Of7n0Dzf8nY5GSLdpsBP0R9t5rGE7u1IbSVtx9I8Nv9wU72JTvGvx9//m6B9wIit3LpCy9NQtV0W5AyE0aW1AK34BJ6jU3R1bZeXowqAv9vCaKhGx9RhNoT5siQmCFzjMVIelxXtQY+UzzNSGJJUKze9ytIU30R97REq8ehQzM/THHiZltUqL6QU1Psj+HNXJqv7ZmkmTnaIt1EBbqIHmUJqYESLnlHhj+ji/f+av+NOLP2CsPKU+I9cotdOhKHcgkJd0OH6ZvDuNE1SxJB6qVFavRruXjsi2urmDL0tTqI+wnqDi5aXE8wOPnDtJO1ukxHsQQRBwKvcSbuBIi5kwm+iN7iVhyh+wWE/6YvsYLBxmrnZVym6HF3icyb3Gow1fxtTCEq5QWSpbEr38Zt/naAs3AvOlVwW3zGBhlJ9PvMfRubO8PHmU/lgHTe0ZbHX+cc1ROx2Kcge6MAjpcWnxJsoXKLoz0uIpq9f83e3NNNm9K30p0jXZvYQlvm58POldou5X2csxWHwXT1rSIWiwu+iO7JYUr35FjBSdke3EzQZJEQNyzjiXVsHU+vXOEDoxI0LSjJE0Y6StBF2RFp5s3suv9zzPjmQ/Vb/G5eIYs9XcSl+usgTUToei3IGumcSMtLR4I+VTzNXGSJotaB+rW1XWl6iRpi08QEzaAqx+JMxmqeVVflA/ScfF4ruUXXmLIluL0hzaSMpeH+cSuiI7OZd/g5wziYyyKNev8UH2JTbE9qMJdS91NWoNZ2i25z9nS16Vqi9vFzEIArzAJ+cWKbplqp6DF3gIITCETlgPkTSjRIzbVx/4gU/Jq5BzSlS8Ku7C+UxdaFiaSUQPETcjWNq97dDM1nJMVufwg4AmO0XGSqza2Tx3opIORbkDQ9jEzEZp8WZrI1wpvk9zqI+okYY10K1IuT8toY00h/rXRMeqjzO1EDEjgyEs3KD2wPH8wKPkZSVc2YMKuFQ4InGXA1JWK92RXWvyeXAzDXYnzaF+RsunqUmYgeTjMVI6ScmdI2ZmJFyhstxKbpXyQmv6qBHC1uWUNF9LOI7MneHwzGlO5S4xVp6m6JbRNZ2kGaU/1sGBhh08mtlGg33zwaYVr8ZweYIjs2d5b/Y0V4rj5JwiQgiiRojmUIYdiX6ea32U3ujdN4KYrmb52+GX+P7o62SsBF/vfZ6nmvehszZvSKqkQ1HuwBAWSbMZUwvh+BUpMU/nXqE1vIn+2KOY2vrt2b2eaeg02N2kzLV7dzthzL9uXO/Bk44An7K78klHza9wtXwWT1LXKoFGymqjbQ01ErgTITQ6I9sZLBxmqnpJSkzHrzJcOsGW5CelxFOW3rWEoORVOJEd5EppnLQZZ1Osi4wprzSz4lX5w3N/S8Etk7SitIcbMTQdL/DJO0XemznDqewlJiqzfK3nuRt2KqpejePZC3x76EVOZgeJGCHSZpzMQoLi+A7T1RwXCiPsd2+dRH/8lsJEZZbvDP+cn1x9m5ZQhn/W9wKPZbbf0LlrLVFJh6LcgRCCkB4jY3UyXjkvJWbWGefo7A8I60naw1sx7nE7Vln9IkaajNWJrUdW+lKWTNhISmvCEAQ+Nb8sJdaDGC9foOzlkNUtKaTHabJ7sfX6HG62VJpD/cTNRqaql5FSYhXUuFx6XyUddSznFPkgd5GJ6iwwn3SUvSrD5UmOzJ7B8V0+23aAfZnNWLqcz8T5z2+bz7UfpORV2ZncQE+0lYQRpexVOZW7yHeGX+Lo3Dnemj7Jk8176I1+eCPIDwIuFsf4/4Zf5kT2Al2RFh5v3MW+9AAtoQxBALNOnouFUaJGmK7wrefQCAQICAgYL8/wreEXeWniPTrDzfxG/+fYndyEoa3dhANU0qEodyWkJ2gNbZKWdABcLh7F0iKIjKAtvBlDk7M4U1aHjNVBxu5c6ctYUiE9hi6pA01AILVb1P0aLh3HlTQsFCBmpGkNbZIWb7WIm01krA6GtRNSdpC9wF0o16pgaaozYD06Vxji98/81Q1/bgidnmgrz7Q8zJNNe2mx5ZbI6ZrGL3U9dUP5YlyLsDe9GZ+A49lBSl6ZK8Xx65KOilflRHaQ9+fO0Rpq4EsdT/JMy8OY2ofL5+ZQms3x7jteh6kZCAQjpUm+NfQib0wdoz/azm/0fo4tiZ41n3CASjoU5a6E9Tht4c0cn/uJtEGBAOfyb+D4FfakP0dXdCchLYpQByHXhZTVRnqNDoG7JqTH0KRN1g6knqO4H37gMVz+ANd/8HKxeYKY0UBTqE9SvNVDIGgJbSSqH2LOH5MQMaDozDBRGaQzsk1CPEW2hBGlO9pCaOEGW8B8y+OSW6HqOxzPXiCi2zzasJ0mO40m6TD17c5KmZpBs50hYUYWSr2uv6EwXctyLj+EF/hsiffwWMP26xKOe2FrJmOVKf7r0M95Z+YDNsd7+Kd9n2VjrGNNl1R9lEo6FOUuGJpNo91DympjpiZ3QNml4nvknAl2pJ6jL/YQDVYXujDXbPcKZf6cUMJsIqzf/NDiWmFqIWkfpvMLlJVNOkpeltnaiLQbD4awSFqta7J72d1oCvURMVLMOTKSjvkSq+HSCZV01Kn+WDv/ov/ztIfmG7MEQMWvMV6e5vDsaV6ZPMKfXf4RObfEC20HSVvyznUEQcBsLc+Mk6PoVqj5Dq7v4eMzUZkFBMHCv/uovFtmojpDSLdoCWUe6JpmankOzXzAG1PHiBlhvtbzHBvWUcIBKulQlLsiEMTNRvpiDzEzI38q8kxtmNcn/4KR0gdsTjxBe3gLSasVTejrpqPNehIxUsTNpjXf3lPHQEgbBxXgBS4BwYq9JqarQzi+vNKqa2fF1utrPGW2ETGSCISUye5e4DBePifhypSloAudiB4iZn54ji1OhCY7RW+0DTfw+N7Ia7w+eYytiV7S1uYHfswgCKj48wfBj82d50JhhOlqDjdw8QOfAHB9l2ytQMZO3PD1ru9S8WrzLXGNB2v68uLEYWZqOWq+i+N7DJXG6Y92oOvaurnJqJIORblLESNFd2Q3p7OvUvTkD/fzAocLhbcZKX9Af+wR+mMP0xLaSMpqQ0NfN29K60HMaCBhrO3J08B8aZXE522ATxAEK/ZamKkOSd1tsfUoaatDWrzVxtYjJMxmDM2Wdq5jtjaK69fUGblVJmZG6Im0krLijFammKnJm4Pz2uT7/MXlHzFXKzAQ72ZLopu0GSds2FiaSdYp8P3R12/6tZrQ0Bc6XTn+g+1w5pwij2a2MecUODJ7lm9deZG4EeHRhm1Y62T6uko6FOUu6cKgKdRHf/wRjs/9BFndaz6u4uX5IPsiFwvv0hvbR09kDy3hDarsag2JGZl1UVKjCU3uXfxg8f+tiKnqFTyJQ8tCWoyMvX6TDoC01UFIi0lqRx5Q9vLk3SnS1tptRb1WiYX/8wP/hjKn+1V0y/zF5R8zUZljf+N2vt79PL3RtsVD2wEBFwuj/GjsrZt+fVi3SZlxLhZGmanlKHtVwvr97Xg83riLX+p8ipJX5c+1H/Lm1HH+5spPiRkRdiT718VB8rW9t68oksXNBjbG95M0b90WT5ayl+VU9ue8OP4nvD7x5xyd/QHDpZNUvMKSP7aytEJ6nIiRWunLWAZrJ0EOgoCZ2rC0nQ6BRlhPEDfkDR5djdJmu9R2wV7gLLThVVaTsldlrDJFzimSMmNE7zAd/G5N17JcrUxjaBqfbNrLxnjndYt7x3cZq0xRdG/ejjttxemNtuEFPoOFEc7mr+AH/n1dS1u4kbBu0xlp4iudT7ErtZGLxTG+NfQzLhXH8O4z7mqidjoU5R7owqQ1tIktiU/w7sx3pbbOvJWaX+R84W0uFt+lLbyZrshOWsObabJ7SZrNqtvVKqOhE9bj2Nranc+xFlX9AgVnWuIhcpOokVn3ZUAJswlTC0uL5wUO09UrbIofkBZTkcMPfKq+Q2VxWGiA63tkF+Z3HJ45Tckrsy89QFtITjJuaSa60PCDgJHSJCW3QsQI4QcBebfEqexFfjx2CO8WOysJI8r2RB9vRZoYLI7y/dE3qPkO3ZFWokaYIAio+jXmnAIlt0JHuOmWU80/alO8i690Pk3RrfD+3Dm+M/xz/mnvZ2kJNUjr2lWPVNKhKPcoZqQZSDzOeOU8l4pHWa5yDy9wGS6dZLh0kozVSWdkO23hAZpCfTRY3etuuNhqZWlhwnoCbR11LFkLss4EjsSbDIZmEzPlziNYjaJmBkvIm6sxn3QMSYunyDNemeHHY2+RMOc/qwICHN9lqpblTO4KVyvT9EXbeaJpN23hD5OOmWqOodI4ebeEE7g4vstsLQ/AYGGElyeOEDMjmELH1Ax2pzZiaxZCCBrsJDuTG3h/7hw/m3gHH4+UGccNPKar8+1w3cCjJ9pK/ibTxA1NZ3Oim8+07ud7o6/z9vQJRsuTbIx1kjJjBAQUvQpT1SxBEPClzifvKukA2J3eyFfcp/izSz/k1cn3SZoxfrX7WZJmbM2WUaukQ1HukRAajXYPu1LPk3dnmF6BrfyZ2jAztWHO5F6nLbyJ1vBmWkIbaLL7SFktEmcjKLLZeoywcWOXFKW+FZwp/MCVFs/UbGLG2j/Xcye2FsXWowg0Ah68vMQLXHK1cQlXpsg2Wpni70dfve7PBIKQbpGxEhxo3MkTjbvYl95MSP9wB3CwOMp3R15luDxBzXeo+Q6FhXKo9+fOc64whKWZi7/+9x3foMme/3pTGPxaz6eJm1HO5q/wt8MvEwQBpqaTsZLsTG3gkcxWjs6e49Wp92963RkrwVPNDxHWQxyeOcXl0lVemTxK1auhCYGtWyTNGNsSfcSMu9+1Ewj2N+6g4JX55qUf86OrbxE3Iny581OEdGtNJh5qZaIo98HUQnRH95B3pzg8/Xfk3akVuY6qX+BS8QiXi8dIW220hDbRGt5Ac2gDjXYPUSPFWqqrXwssLYytxVb6MpR7VHTnpCYdhrCJGWqnQxPaQpmZjePfvK7+XgT4lP286mBVJyzNYHuyj1/r/vRN/14TgpBu02in6I+20x5uvGH4XoOVYG96gA2xu2u6EPrIQW8hBLuSG2m0UpzMXWSulqfqO4R0i9ZQhi3xHhJmjKgepsFOsiF+88dosJM82/II25N9XCyMMl3LUfGqaEIjpFukrThdkRY6wtd3JYwYYZ5teYSdyQ1sinXdcFhcFxpPNe8jCHwmqnNEjNAKtspYeirpUJT7FDGSDMQ/QdnNczz7jxRd+W1071aAt7j7caHwNo12D82hDTSH+mi2N9Bgd6ryqzphajaWxBp2ZXmUvDn8QM55Dpgvr4oaaWnxVrOokcIQFg4PnnQAuIFD2csR19b3If16YOsWu1Ib2ZXaeN8x+mLt9MXuvxuZEIKOSBMdkVu3Kd+Z2sDO1IbbxrF1k95oG73Rtrt+7JgR5jNt+2/7byzN5DNt6+MMkko6FOUBJMwmdqWfRwjBybmfkXMnV/qSqPklRsunGCufIWKkaLJ7abJ7aQ5toCW8gZTZjqGtj57g9cgQNqYmr4ZdWR5Fd07aIXKYb8Ed0tWOF8wPSdQlzinwA5eiO0vcVEmHotQTlXQoygMQQpC0Wtmd/iy2FuVE9qdMVa+wkrMErgnwKbozFN0ZhkrHiBvNNIXmd0BaQ5toCW0gamTWZN1oPTM0SyUdq1DJncOTuNOhCwNLdTAD5s916BLPofmBR9GbkxZPURQ5VNKhKA9IIEiYzexIPUfMbOTE3D8yXDq5LO1075YXuMw5o8w5o1wuvk/aaqfJ7qUltJH2yFYa7C5V8rNM1E7H6lSSfKZDw8DSVdIBYOkR6UlHyZmVFk9RFDlU0qEokkSMJJvi+0mYzZzOvcy53Jvk66Dc6uNqfonxynkmKoNcKr5HJt9NS3gDneHttEU2EzXScqdIK9fRhYEhsZREWR5VvyiluxLMDwY0tZDUhfZqZmtRqR33fDwqvhqiqij1Rr3jKYpEphaiI7yFuNFAs93HqdwrjJZO4QSVlb60GwT4FNwZCu4MY5UzXCq8R3Ooj/bwVroiO0lb7ejq7Id0mtDUjI5Vxg88qaVVmtCxtLBK7hdYWhhd4msiCAIcv352mhVFmaeSDkWRTAiNpNXCFv1JGu1eBgvvcCb/GjPVYWl3SmVz/DKT1YtMV68wVDrB+fzbdES20hd7iEa7F1Oz7xxEuSsCDYGaIr+aeIEDEl+7AqES+o8whCn5NREs/DdTFKWeqKRDUZaIpYdpi2wmabXQHt7ChcIhzuffXpjpsfIHzW/GxyPnTJBzJhmvnONi8T3aw1vojz1Ma2gAW9WgPzAhdLXTscp4gUsg8TUr0NBQz4FrhDCkJh0BPm5QkxZPURQ5VNKhKEtIIIgaaXpj+2iwu+mO7uZC/m0GC4cp1XV3lYCSl6VUyjJVucSV4vu0h7ewKX6Q9vAWLF0dOr9f2sKSU1k9vKAmNelACHWe4yM0oYHELnoBAZ6vdjoUpd6odz1FWQaa0ElaLcSMDM2hfvrjjywkH+9S9rIrfXm3VfWLjFfOM1sbYaT8AR3h7WxOPEFbeEB1YbofQpv/pawaru8SBDJ3OoTa7foIDUPq+ZYgCNROh6LUIZV0KMoy0jWTtNVO3GiiJbSRTfGDXCi8w2DhEEV3jnotuwKo+WUmKoPM1a4yUjpJT2wP25PP0GB3q7u290As/FJWj/nzASrpWCq60CUfqldnOhSlHqmVgqKsAGMh+UgsJB9bEk9wsfAu5/JvkXMm6vbAOcy33J2oDpJzJhgpnWIg/jhbk58iZqQR6g6+otyd+r2/oCiKsiRU0qEoK0jXTJJWC3GzkSa7jy2JT3KldIyzuTeYqFzAR16bTtkqfoHR8mmyzlUul46yN/0L9ET3qE5Xypozv5Mn98xBPb+2l5uPJ/fMDOrMjKLUI/WqVB6Y7we8deLSPX1NOh5ha1/L0lzQKqQJnZjZQNTIkLY72RB7jPHKec7l3+RS4QhOUF7pS7yFgKI7y+XCEWZrowzED7Iv8wXiRoPa9VDWDF2Y0st/fIlzP1a7+Z+F3PI1XQ3gVJS6o5IO5YG5ns+/+4sXr/szIebf+P2PHb4UAmzT4BN7Nqik4yaEEIT1OGE9TspqpSuyg2xmgsHCO5zNv8FcbXSlL/GmfDzmaqO8P/sjrpbP8XjT12mPbFV3G5U1wdBMhMzuSoFKOj7KD+TudAghMIQlLZ6iKHKoFYHywAxd43/5xmcWf+95PicHx/jBm6f44id20NeewTQMZnIl3j83wpXxWQ7s6FnBK14dTC1E0molbjbRaPewI/UcY6XTnM2/waXiEbw67M5S9QsMl07wo7E/4NGGL7M9+SyGGoKmrHK6sOR2V1I7Hdfx8KR2B1PlVYpSn9SrUnlgQsDuje2Lv58rlPn2i0f51Wf38txjmwlZBkIIXNdnU1cjP3rrNO+dGWbflq4VvOrVQxM6ESNJxEiSNJvpie0l70xysXCYc/k3maxeWulLvI6Px2xtmFcn/ozZ2ihPNP06uiZ30aYoy2m+VEdm0uHjoborXeP7rtTmGWriu6LUJ5V0KA9MCHHdXCfX8zl3ZZJf+/Q+YuEPDxXrlkZDMkosbPPBxasrcKWrn6mFMIRNzGigwe5mR+o5pqqXOZt7g4vFwxTd2ZW+xEUlb46jsz/A8Ss81fKN+bvFEktUFGW5CMnD/PzAo+ZXpMVb7Wp+GT9wpcVTZzoUpT6ppEORThMC09R5++Rldm5sR1tYaAZBwEyuxMmLV4mGVL3t/RJCIBCE9Bi2FiVuNtIe3spj3lcZKp3gbO51hkvH62I4Vs0vcWLup/iBx3Ntv41AzSZQVh+BwNajCDQpd+QDfJyFhbamyoCo+SU8ieVmQmjYWkxaPEVR5FDvdop00bDF5w5u489+8A5Hzo6wubuZkGUwlS3yweBVDEPnt778+Epf5poghEDHJGIkCesJEmYzm+L7ydaucjb/BufybzJbG1nRa3SCCiezL5KwWjjQ+Csrei2Kcr8iegpdGNKSeS9wqfllQnpcSrzVrOoX8SUO89OEQcRISounKIocKulQpAtZBr/45E46m5P8+K0zHD49RLnqkEmEeWRbN8/v38KmrqaVvsw1RwiBKWwMYREOJ2i0e9mb/gVGyqc4OfdThlZw98MNqhya+jYNVicDCZVwKqtP1EjPTxGXdN7ZD1yqXkklHcjf6dDQieopafEURZFDJR2KdEII4hGbT+zZwGPbe/D8gCAI0DSBoetYpo6u3XyGQ65W4ZuDb/MXg2/fMv6XevbyS917+ebgISaref7bzZ9ic/LD9rs/Gz3NH519mf9+69Psb+rD0tbX03y+/ErH0sOYWoiYmaE/9hAz1WFOZn/OufwbFNzpZb+ulffq2wAAIABJREFUql/k5+P/idbQAAlLJZ3K6hI10mgSywO9wKXqF6XFW82qXknqmY755hsq6VCUerO+VmPKshFCYBo6pnFvH9Ihw+Dxlg002FEAjs+N8tbkIA9lutnX0A3AxkQzzeE4T7UO8B9PvcjrE+dpCydIWGFytTJ/dfEQA4lmBhItmGJ9nyG4Vn6laQat4c00h/p5uOEXOZN7jZNzP2O6dmVZryfnTPCz8T/iS13/MzK7ASnKUosaKannL9ygRsmdkxZvNSu6s7hBVVo8lXQoSn1aV0lH2a3x47Hj/B8n/wFbM/hUyxb+t91fXrLH++nYSf7fC69Q9hz+zdbP8GhDP5a+fn7klarDu2eGuTAyhaFpvHBwG7GITbnqYJsGlnljQmAKnR2pdrYl51vwhgyTM9mr7G3o5ss9+wDQFgYP7m/u58DUJX40cpLdmU72Zbr5m0uHmaoW+Ndbn6IpFFPdkhZcO3yuCZuU2cYjDV9mR/JZBgvvcHT2HxivnJc6nOtWAnwuF49yNveGKrNSVpXF8ipJXL9KwZ2RFm81K7ozOL680k9T2NhaVFo8RVHkqMsVsB/4+AvrH31h0Xgvi8drQ4a8hf8VAnShLfyZT8VzCIKAmr+0w5m+N3yEM7mreIHPD0aPsTnRRtM6qN/1fZ/B0Rl+97/8hNOXJ4GA3rYGPrFnA7P5Mn/xo8Ns6Wnmq8/sueFrP1wcz/9eQwMh0ITA+FhJlgb8cu9DnJgd4ftDx8nVKvxw+ARf6NpNX7wJTd1Jv6n53Q+DqJFmZ+o5NiUOMJh/h/dmvsfVynkClvZ1UfMrvD75l/TFHsLUQkv6WIoiS8xolNo21/GrK1LmWG8cv0LZy+Mjp7xKQydqpNUNJ0WpQ3WZdPzeie/z3eEjOL7HHzzy6xxs2nTPy8eCW+VT//h7BEHA1mQb33zit5bkWm/n2pueYP4O/oO8BfpBQM13EQgsTa/rN9R8qcqf/N2bhCyL//w/fY2q4/J7f/pTICAZC9HemOD05YkHfhyBoCOS4gvdu/nP597gtfHzbEg08XTbFuKGXdc/o3ow//MRhLQ425JP0x9/hDO51zgy8z2mqkNLmHwEzDmjnMy+yO70Z9XQQGVVSFttmMK+8z+8S25QpeConY6CO4MjcWaJLkzSdoe0eIqiyHPz07wrrMGOEdYtfAKmqgVq/r3fAZmpFfACH00ImsMr0zrv85172ZpsZ0uynS907iVpRe4rThAEXCxM8sKLv89vvvmfqHryDtwtharjcX5okn/+C4+yuaf5unMdlqETDVnki3I+ZIQQPN++ja5omquVHJ/v2kVbOKESjnswP9xRENYT7Em/wJe7/lceafgSMSOzZAmB69c4PvcTfIkdaxRlKRmaTcpuk3au49pOx7Wd+fWq4E7jBBKTDs2kweqSFk9RFHnqcqejwY4RNizmnBJT1TxVzyGk3/100QCYrOQA0IRGW2hlko5nWrfxTOu2B47jBB6XilPM1Iq0hVfD4bgAmO9W9dEP1ABwXI9SpUbIljMtNggCzucmma4WsTSDw9OXeaihm5aQSjzuV9Jq4ZPNv0FXZDeHpr/FaOkUnqTSh2sCfGZro1wpHKUv/rDU2IqyVBqsbq6IY9QkdFoK8Cl5WQruFHFz/XZzm62OUfXkdfHShUmD3S0tnqIo8tTlTkejHSOiz0+snqrkqd7jTkdAwEQlD8yfCWldFQv1Wyu7Nd6fWd4uQw/CMg02dDbyvddOMpUtUqrU8P2AUrnGxbFpPrg0zra+ljsHugsVz+Fblw/THknxTzY8xjuTlzg+O7Lk53XWOk3obIg/zPNt/wNbkk9iaWHpj+H6Vc4XDq37O73K6tFgd6MLOTdMAKpekZnaqLR4q01AwGxthIrEpMMQJhm7U1o8RVHkqdOdjjhhYz7pmKzmqXj3Nqk0CGByIenQhEbrCpVXyRAEASWvxvtzqyfpiIUtfuXZvfzun/6U/+7ff4fGZJSpbJE//NvXmc4W2dDRyKcf3fzAj+MHPj8bO8253ATf2PQEjzb2cqkwzd9cPMyGeBO9sUY0tdvxQDJ2B082/3NMLcSp7EtS5wq4gcOV0jHcoIop1IFypf412j0YwpIWr+oVmK2O0BPdLS3mauIHPnPOGDW/JCWeQBDWk8SMjJR4iqLIVZdJx3U7HdXCfZxhCJisXtvp0Gi9RXmVYH5R7wU+Ja9GxXNwfY8A0BCYmk7YsAjrJpq4/aZQ1XPJOiVqt7jWhBUmZth3jHOtq1bVd3B8j6rvcj4/zunsGAA132WkPIt9k4F3hqaTMMNEjNt/KAYLh9JLXo2a5+IGPgCaENiaQcSwsTTjvhfshq6zZ6CT//O3P893XznB6SsTtDcl0DWNL35yB59+dAup+IPfOb9azvHDkZPsSneyPdVOwgrzld59/N6xH/HS1bN8tTdOTB0of2Axs4EDjb+K61c5k3sVR1o//YCKl2OiMkhH5MHLEBVlqWWsDkyJu34Vv8hMbZggCNbl+1TemaDkZgnwpcTThEmjKq1SlLpVl0lHxo4uLpzny6vucacDGF8406ELQctNdzoEQmiUvRrn8uP8ZOwEh6cvMlaeo+K5xI0QvbFGHm8e4MnmzXRGMti3mbFxJjfGv//ghxybG7rp3//2wDP8Su9jJMzbf2D5BLwzPcgbk+cYLExyqTDFeCW7OEHhXH6cX3rl/7rp126INfPfDDzNc23bbxnf8T2mqwXenbnEqxNnOZUdZbKSww8CUlaELck2nmzZwsOZPlrDSQyh3deHoaFrbOpq4t98/al7/tq7UfNcvjt0jJxT4Z+1b6UlnADgYFM/jzb28reXj7KvoZud6Q4erG+YAhA3G3m44UsU3GmuFI/hS+ps5fo1rlbOq6RDWRUsPUJzqI+scxUvuLfPpZup+WVma6PU/BK2vv7mSkxVL1P2stLiGcKkLfzgu+iKoiyNukw6QrpF0oxgajrT1cLiXI1ri1/X9xkpzeAsdL5pD6cJ6+bi3wcEiwfJbc2g0b7xzVwXAj/w+cexk/zxuZ9ztZzF1g0MoWNqOjmnzLszlzgyc5k3J87xjU1P8lCmF0O7+XAoWzdoDSeZqRXxAh8/8Mk55flrv4fv3fN9Xho/zUvjpxa+F0iYEbLO/PazITSSZoSb5QFpK3LTHZBrap7LyewIf37xdd6YPE/Vc7A0A1Mz0AXM1oq8PH6al8dPc6BpI/9y45PsSHVi3ke3liAI8PyAmuPi+cHCd/IhQ9cJ38Vh8rhp0x1Jk7SuT9auVnIMFWd4rn0Lm+LNi7symtD41b6HGS3P8d70FTbEm4ibqnRHhuZQP9uST5N1xpmVVIfuBQ6TlYtSYinKcuiO7OZi4V0pSQcEFNxpJiqDdEV3Soi3egRBwHjlPEV3VlpMUwvRGdkhLZ6iKHLVZdIB0Biab5ubc8pknTJu4GMuTIO9Wpnjtw79KaPlOQD+40O/xhPNAxgLf3/tTIeGoCmUQL/JFFmfgPP5cY7NDZF3KmxPdbAp3kKjHafquwwWJjiVHWO6WuDwzCXSV6K0hBL0xm7eZWRDrJnf2f455mpl8k6ZnFPmW1cOcWhq8J4Owuuaxuc6drMv07PwvQQMl2b5o3MvAtAaTvIvN34K8ybJT9wMsSneetO4XuBzIjvMH5/7OYemLhLSTfpjzQwkWumIpBEIRsoznM1dZag4wxuT58k7FX5n+y+wJdGGrt19zwE/CCiUqpwbmmRwdJp8qfrxnIOulhTP3cW5jidbB3iydeCGP++OZvi3+37xpl+zOdnKHx/49bu+XuXubYof4FLxXXLOpJRFlx94ZJ1xCVemKMujK7oDSwtLO99UdGcZr5xfd0mHE5SZql6m4uWlxBMIYkYDDbZql6so9ap+kw47Tlg3yTllJit5ar67uNA+MnOFsuegIfAJeHt6kP1NGzHQF89oTFcLaELcssVsxXM4lx+nwY7xlZ5H+FrvfppDicW/zzllfjDyPv/lwmtcrWR5f3aIIzNX6Ik23rTcyNB0MnaMjB1b/LO3pi9wZObyvSUdQmNvpoe9zCcdfuDzQXZ0MelImhGeb9tJyLi3DirjlRx/N/Qeh6cvYesGT7Zs5p/0Pc7mROt1uzcn50b4v8++yKHpQY7PDfNfr7zDbw88Q4Mdu+syq2rN5YdvnuLPf3iYeMTG0G9MWPYOdN5V0qHUF1uP0ht9mJHSabLO1QeO5+NRdGfwAw/tJjcHFKXeZOxOEmYzBXdGylmEspdlojKI69cwNHmH1OvdZOUSOWeS4J5qAW5NFyZdkR3qfURR6ljdJh1Ndpzw4mHyPFXPJWrYBEHA0ZnLlL0areEU45Ush6cvUvPcxdKivFOm4jtYmn7bzlUh3eRA40b+xcZPEjOuL8FJmGE+1bKVwcIk37p8iMlKjqHSDI7vYd3mbEc98gKfQ1ODHJ6+iBf4PJTq5Wu9B9ieunFq6/ZUB/+0/3FGyrMMFib5x7GTfKFzL2krin6XSUepUuN7r53kyX0b+PqnHyIZC99QDnYvOydKfemMbCduNkpJOmB+SFrFKxAxVm+XOWX9EGh0RXcyXrmAK6Gpghe4zNZGmapeoTW8UcIV1r8g8BktnyHvTEmLqQtz3e0WzR9XlHlmMbihKkFRZKrblV+jHSO8MBBwamGnA6Dk1TidG6PquXy2YydRw+ZCfpKJSm7xtTJxbTAgtx8M2GTHea5t+w0JxzXNoTj9sWZMoeMTMFcrknPL8r7JZZJzynyQHWGsPIcpdPY3bWAgfus5GXsyPXRGMhhCo+BWODpzhbJXu+vH8/yAUqXGpx/bTHtTkmjYIhK6/pdtra7ETflQ0mombjRKm8wMAY4vbyKxoiy13uheTE3eWbGsM85Q6RhBIKeLU70re3lGS6elnucI6XHaw1ukxVsd7q/Ry634gYfKOpSlVMdJR5zQwk7HdLWwmHSczV1ltlbE0DSebN5CSzhBQMA7M4P4C2/Yi0nHbcqrAJJWhB2pWw8R0oRGxLAWZ4bUfI+at/qGzo2V5xgtzREAjaE4XZHM4vd0M6am0xlJYy8kfefyV++pRMzQNdoaEgyPZ3G99fEhup4INBJmM5ak2RoBAa6UQ7mKsjzaw1tJW20ISR+hRXeW0dIpyl5OSrx6N1o+zUxtSF6rXAw6I9uJGKt7EPC90tDQJRasuIEjrdxNUW6mbm83f7Rt7nTtw6Tj6OwVim6VzkiGllCCHclOLhemeGvqAl/uehhdaIvtcrXbTCPXECSMEGnr9m0KdQT6wmyNIAikvUkup+lqgelaAZjv2nWxMMWrE2du+zUzteLipOhrHbnulm3qbOtr5buvniASNmlMxjB07bpN4FjEprN5fX1ArCUhPSZ1MrO6u6asJoZmsTnxCSYqF6WUWAX4TNeGGC6dZCBxELklM/XF8asMlY6Tk9hAwtRstiSelBZvtdCELnHHGWpeaVWucZTVo26TjohhkzQjGEJnplrE8T28wOf47BAlr8ZT6S5s3WRnqpMfjx7n2OwQRbeKaRmMV+b7fuu3mUauaxpR014XE6vLnkPZnS+PGi7N8odnf3aPX19b3EW6G74fMJsvMTaV5T/81cu0NSQIh0w+mnZs62/lG1/Yf0/XodQPTejctG/zfRAIDGFLiaUoy2VT/ADvTv8dOXdSSrxsbZxLxSN0R3cT0mN3/oJVaqIyyGjpNFVJU8hBkLLa6F5v5zmQn3SUvLmFEitFWRp1m3TAtba5JlmnjON7TFZyXC5O4/geezM9hHSTPZluQrrJTK3I6dwYjzVsYKIy34IvatgkbjGjQUMstthd6/zAx1/YtbA1g6QZuafD8E12fHG3524ITdCUivG5x289pLCzSR0aXs1cv0Yg7cNJYGoq6VBWl5TVRmdkB6dzr0gZlukEFUZLpxgunWBD/DHEGtztqPkVLhQOMV27Ii2mLgwGEgelnrFZLTRhYGjydpwLC50EFWWp1HXS0WTHCekmk9U8Za/G8blhCm6FmGGzOd6GpRn0RBvpjGSYq5V4c+o8jzT0M1HJIRC0hBJo97BYXqsszcBaaIvbGk7xTOs2eqINd/31aStK9BaH7W8mFrb5V186eM/XqaweFT+PF9z9OZ/b0YS2LhcMyuq3PfU0FwpvS7trP1MbYbDwDu3hrWuym9tE5TxDxePSZnMA2FqUgfjj0uKtJqZmY2vyJtnnnSlqfvm6YcyKIlN9Jx2h+aQDIOfMd1EqulUG4q2krchCaZTgscZ+TudGOTR1EXeTx0QlhyYE7RF1ZgDm2/8mFiZ6h3SDhxt6Odi0acWup1x1KJSqNKXXbgnBWuYHHnlnCkdCLTsILC0i9W6doiyXzshOWkMDXCm9L+UArhtUGSqe5FLkCJsTT6BLLJ1ZaSU3y9n8m0xVL0mLKdDoju5etwMBLRGWWornBlVma6NkrA7JZ/YUZV5dbwNc2+kAmK7mOZkdoew57M30XNd9aX/jRgyhM5ifYLySY7paQABtobWQdIjrzkIEBHj3eNCrNZxcPFA/Xs4xVs7i+CuzhRoEAcMTc/zjodsfZFfqV8GdIe9O40vY6dCFQcpsldYFSFGWk6nZ7Gv4otSdutnaMKdzrzBdHZIWc6V5gcPF4rtczB+WNskd5hta7Mt8nrV88P52TD0sdacDYKx8Gje4+xb5inIv6vqTvjH04YDAC/kJxspzBEHAznTXYjICsCXZRqMdxwk83pw6T8mrIYSgLZJeqUuXRgCmZiyeqXB8j9navb1pN9lxNsVbSJhh5pwS785cZKg0vdidajn5QcDoZJZ3Tq2dD9T1Zqx8mpI7JyWWJnRSVpuUWIqyEvqi++gI3/r82r3y8RgpneR07hVKblZa3JUTMFW9zOnsK8zUhiXGFfRG963D2RwfsrUIYSMhNeZQ6TiOX1mR9YGy9tX13m2DHSdszCcXJ+aGKbhVmkMJuiMZzI8cAo8aNnsy3YyUZ3l5/DQwf1D8djM6VgshBCHdpMmOc7WSJeuUOTQ1SHNnAku7u/98tm7ycKaPd6cv8ebUed6avECjHeOF9t30xpquS+BgfoL5XK3EWHmOkltjR6qDiHHrg76+H3D07DCmabBzQxtVx+W90zf/cPF8nxODciZZK8vP8StcKR6XNtRLFyYZ+9azchSl3hmaxcMNv8hw+YS0IZdlL8f5/JtkrA4GEo9jaWEpcVdCzpnk5NyLjJQ/kNqONaRH2Zf5wnwnvXXK0kJE9RS6MPEkzTqaqFxkpjZMxEghWL8/W2Vp1HXSEdUtEmYEQ2hcKk5R9VwONG4kZoZuOOR0sGkTPxo9xom5EWB+sd5+i3a5sjm+R9VzqPouju9RW/jf2VoRb+FuwWS1wKXCFCkrgqnpmJqBJXQihoUubj9VNGpYPNa0gb8feo+ZapHvXDlMzXdpD6cxNR038Kh6LrZusjnRSnPoxjsfA4kWPtu+i4lKjvP5cf5+6AhXijPsSnXRFIpj6yZBEFD1HHJOhbHyHBeLk4R1i67oZ++QdPh877UPiIYtdm5oo1Cq8offeZ1UPIyuXf99+UHA1FyRlkz8Pn/ay+faXJb1/KH2caPlM4yUP6Am6eCsIUyaQxukxFKUldId2UVPdA/n829JizldvcL7cz8ibCTpje5ZlTX2JTfLqezLnM2/JvXwOEB/7BHawgNSY642mjCIGGkieoq8pNbNblDlTO41WkIbsXW5pVuKUtdJhxCCJnt+QVx05w+t7kl3E9FvnKa9L9ND1LCZrc0vhgyh0XSTxfdSOJMb4+2pC0xVC4vJR813OZUdWxxqeGjqAhOVHFHdwtINLM3A1gyebdvO9lQH+m1qUmNmiBfad3FqbpSz+at8kB3lSmma1lASSzNwAo+yW6MrmuGfb/jkTZMOWzd5onkAD5+/u/IuH+RGeWn8NK9PniNuhgjrFkEQUPZq5J0K7sJcjgONG+/4/QtN8Mi2LkxjfnHuej6jU1me37+ZkH39B6Xv+Zy5MslMTlaP9qXjBlWuls9R8rI0h/pJmi3rOgHJO1Ocyv6cudqolHgCjbjRRMZSOx3K6qZrJo9kvsxY+SxFd0ZKzICAsdIZjs58H0sL0x7esqoOlle8POfyb3Ai+1NyjpwF8TUxI8NDmS+qs2BA1EgRNxulJR0A5/Jvsj35NK3hgXX9mafIV/fvYE12nJBmUqRKWDfZkmxbPOdx3b8LxdmcaOPtqQsEQMqMLE40X2pnclf5zpV3GS3fuuTkUnGKS8WpG/68I5JmW7L9tufgLM1gZ6qLb2x6kp+MnuBc/iqTlTyD+QmEENi6SdwIzX/PN/nZXJO0wjzbup2WUILXJ89xOjvGcGmGuVqJbK0MQEgzaLLjNIcSdEUbeKxxA/E7tMvVNY0XDm5b/L0QgpZMnK8+vQfbuv4p5vk+rxwd5LuvnLhtzHrg+FUuFd/jTO412sKbaQsP0BoaoMHuxtYjK315y6riFTiVe4mLhfeo+WUpMXVh0B7ZqmZ0KGtCR2Qbe1Iv8MbUX0orI/JxuVI8hiZ0Hsp8kfbwVgxteT7XHkTJzXIu/wZHZr7PdFXeTA6YHya6O/0CLaGN6/X8+HWiRoak2cxo+ZS0mAV3mqOzP+Apu5OQFlPtcxVp6j7peLSxH1PTKbpVwoZFf6wZXbvx7oZA8PW+A+zL9BAAjVbshuFKhqazLdnBb216Gl3T6Is23fHxBxKt/Eb/E1Q8h02JFuLmjbW125Lt/HrfAfLOvdfz7kh13NVU9Ihh8VTLVjbFWziTG2OqkqfiuQgxv4uRMMN0RtJ0RTN3jPNY4wYGEq1cLkwxVJolWytR8efrQUPafKzmcILuaAPNdhxDu7c7HbGwxdeffwjLvPHppQlBczrGlt7me4q5UrzAZaY2vNg/vyW0kdbwJlpCG2my+0hazauy7OFelL08Z3Kvcnz2J+TdGxPn+2VoNv2xh6XFU5SVJNDYlf4MQ6VjXCkdkxbXCSpcLLyLG9TYl/4CXdFdWHU816bgTHM69yrvz/1QesIB822Kd6WeX+jrqBbDcaOBtNWJhi5lSOU1Z/Nv0B7Zys7Uc+is7c84ZfnUfdKxPdXB9lTHXf3bTzRv5hPNm2/596amszXZztZk+10//qZEK5sSrbf9N/ca836Zmk5frIm+2J2TpTtJW1HSmSh7Mj0Srux6kZDF5x7fdtO/E0LQ05Imvn+r9MddWgFlL8el4nsMl06QtFppsntpCv3/7N1pdFznnd/5713q1r5hBwgSBPedojZKsmxJXiTLltvtPe5kcibppDNzOjlZZk5ezMyLeZNMZ+bMOXmRPidLz/Sa7ky33XZbbq+yLUuyLIkSKe6bSAIgdtQC1H7rLs+8KBAiuEAEWGCBxP8j1QFRqKr7oFB16/7u8/yfZ5Du4FY6Q4NEzbYHbjHKgjPNubnXOTn7E3L1MWjCWgTQOEBrtzbRu45nnhEPFk3TiJppDnd8jczYCBWvOTO8AbiqznDpOI5Xo+hm2Bo7TCzQtqYOuj3lkrVHODP3KhcKv2LWac4wzOuFjQSH279K1GyTs+/zAkaYtuAGYmYbhSYOsar7Fd7NfoeokWZr/HEZZiWaYs2HDvHgiUWCxCL375AaV9XJ2iNk7REul96lzdpAe3CAjuAmOoIDdAQHiAXa76vx1zdyfJuJ6nnOF17ng+LbTR0vDGBqFrsSHyckhYriAaKh0R/Zz8H0i7yd+cumnnn2cRmtnqbk5cjVR9mdeIbO4OCaGG5V84oMl49zdu4XjFSau+L4hzT2p55nY3T/mgpbraahkQr00Rbc1NTQAZCrj/LrzF+g8Nkef3I+6MlzL1bu/j0qEmuW5/kMT+Z59+xVZstVPM+/6QT5QG96UR3I/aruV5isXWSy9gEhI0Yy0E0q0EtbsJ/O4ADtwU0krW4Cevi++KB0fZsZe5ih0ntcKR9lunapaTUcH9JIWN1sTzzV5McVorU0TcPE4kDqBWadCc7Ovdr0bczWJziZ/wmZ2hCDsUcYjD5GOtjXkpMcda/KZO0Cl0pHGC4dI2MPNzVoXW9r7DEOpl/E1Czp5bhB2uqjK7SFkfJxfO5+0dbrTdYu8quZP6fs5tmTfE5mtBJ3RUKHaLpyrc6f/OAI+VKV7rbY/JCjxamjUnvQdlyKmlek5hWZqn2AVQ4TNztJWJ3EzU7SVh9pawNtwX6SgS5MPbhmQoivfCruLFO1i4xVzjJRPc+0fYWqtzoLkxlagAOp50kEOlbl8YVoJU3TiAc6eKztyxSdDKOV5k+aYftlhsrHyNgjjJRPsSl6gI2RfbQHN636xAxKKWp+kcnqRa5WTjJSPknGHmraNNq30h3ayuPtXyMZ6EZ7wIawNkPIiNET2k7K6mnyAowNM/Zl3sr+JRl7mJ2Jp9kQ2Xtf9+SL1pFXjWi6uuNyfmSaLz97gEd3b8Q0bv6QuHEq3QdN3a+SrY+QrY+goRMy4sTMNmJmO1EzTTzQQTLQTTLQTcLqIma237MzeEop6n6FOWeKXH2MTG2YXP0q+foYs/UJ7FU8eNDQ6A3vZE/yOaSbXjyodM2gM7SZwx1fpzKZn6+Har6Sm6VUyjFVu8il0tt0BjfTG95JV3ALSaunafsUpXxsv0zWHmWq9gET1fNk7avk6+PYfqkJv8ntxc0ODrd/nd7wTqkruA1N0+gJb6MnvGNVQgdA0ZnhxOxPmKpdYkNkNxsj++kN7yJq3qtFmBWOb1PzSvOXIlWvsHBJWb1sjT1OYA1PsiAkdIhVEAlZfO6p3QxP5ohHgsSjwZtmHEvHI3SmYi1q4b2l8Kl6c1S9OWbsK4BGUI8QNhKEzQRhI0HIiBE2kkTNNFEjRTSQJqTHCRoRLD1KUI8Q0IN3OKZWoZTCUTa2V17YQVe8WYpOtnGg4mQpe3nKbp6Sk6Xml2lWkfhSLCPKY+1fImqmV31bQrSSrplsiuzn8fav8svpP6TqFVZpS6rxnnazjFfOcaV0lESgg5h722jRAAAgAElEQVTZQTrYRzrQRzTQRtRIETFTBPXobYOIQqGUT9UrUHFnKbuzFJ1M44SEM0HJzVKoT1N0s01dXfx2LD3Mo+1fZjD2qJxZ/wjxQCf94T1cLR+n6GZXZRueqjNePctM7QrDpfdJBzcs1DQmA90kAh2EjMQd9bYpFL7y8Pw6jl+jrmqNr34V269Q9yrYfgV7PmTYfpm6X5m/TeO2jl+lPn+f7fGnGIgeIoCEjrVM3sWi6ZRS5ItVXnnnAueHp0lEw+g3rEy+e3M3Owfuj2lzm09h+2Vsv8ysM7FwralZWHoYS49gGRECWhBTtzA0C1OzCMz/29BMdM1Ax0DXjPmo4Dd24MrDVTaeX8dVLq6q4/o2jprfmXtlbK+Mo2zuRci4nobOw+kvsDl66J5uV4hW0NAwtSDbE09R9Qq8lflLbL+8qtt0lU2ufpVc/epCD2vESGAZ0fl9S5iAHsLULEw9gIGFrul48/sKTzm4fn3+YK6K7VexvRIVb25Vh0/diqEFOJR+id3JZ7D0sNRxfARDM9kUPcjVyknOFV5DreL+3VE1pu3LTNtXCOoRomaasJEgeMPrTNdMdBq9U2r+M8pXLh4unu/gKqfxvXLxlLNwcedfh56q4/j2wufYUvVCnnJA3dvPNLF8EjpE01Vtl7dODfP5p/dyaMeGWw6vSsXX1+J6d8JVdVyvTsWbA+fWt9Ex0DQdDR1da8xT39jNNno3FD6e8lCrVMx5N7bFn+BQ+vPS/S3WDU3TCOkx9iY/hasc3sl+C8df/npOK3F9D+sNrUJHb5y40Aw0NHzl4+PhK++e9GB8FF0zeSj9OQ6mXyRipCRw3KGk1cNg7DEmax+QX6UhfYvNn0CrLw7TjRNi5g2fUY1hegofHx+lvFUNRmJtktAhms4KGBzc1ktnKsbB7RuIhq07WgBRfDQfD9R8oLiP9tfdoa18rOPvEgu0t7opQtxTmqYTNdPsTz2Pwufd7Hfvea/BYmohYKzFfYihmRxMv8ih9EskAl0P3NpHq8nQTAaiDzFRPUfRyeAquyXtWMuvL9FaEjpE0/m+YiJb5NiFMd44fpmAqd8UOvYM9vDbv/FEi1oo7qXO4CDPdf9jOkObW90UIVpC03RiZjsHUp/F0EyOZP+amre6Bdj3I1OzOJR+iYPpz5GyeqRwfAViZpo9yefI1ccYLr+PHPmLtURCh2g6K2DwxL7NVG0HdZsxlhu779WMF6KV2oMDfLLnd+iP7ENmqxLrma7pxM129idfIKCFOJL9a4puptXNWjNCRoyH07/BvtRnSAQ6JXCskKbpdIe2sS/5KUpulqw90uomCbFAQodoupAV4MUndy15G9OQD5QH3YbIXp7u/O/oj+xFQ5dx2WLduzbUam/yU4SMOO9kv03GHmp1s1ouEejisfYvszP+NBEzLUOq7pKpW2yNP07RzXIs97KEW7FmSOgQTadQeL5PKh6RWo51anfiOR5r/xKdocH54nd5HQgB88XlRpwdiY8RMVMczX2PK6V3121R7YbwHh5p/yKbo4cI6jHZVzRJyIixP/UZHL/GidkfUXbzrW6SEBI6RPMVyzb/9399lc8c3smzD29rdXPEPRTUozzS9kX2Jj9J0uqVM5ZC3IKmaVhamE2RA0SNFGmrj1Ozr6z6lLprSUALsjPxCQ6kP0t3aAumFpTA0VQaETPFofTn8ZXLydmfNGZGFKKFJHSIpqu7LqevTPKVTx5sdVPEPdQf3stj7V9mQ2QvYSOOJoFDiCWZukVnaJDHza/RGRzkaP5lpmuXWt2sVdce3MhD6ZfYFjtMLNAuC/+tEg2NqNnGo+1fImTEOZb/PgVnutXNEuuYvNNF0+maRizy0SuSrnUBPUhPaDttVj+5+mirm7NmRYwkh9IvsTPxcVJWL4YWkDOWQtwhXTOImW3sSn6CjuAAp+d+xrnCL6l6xVY3remCepQdiY+xL/UZuoJbZNG/e0DTGj0eB9MvEjfbeTv7V8zYw8isVqIVJHSIpgsHLZ57ZDuvvvcBB7f3Yej35xlvUwuyJfYY7cGNXC69y+m5n5Gxh1vdrDUjZMTYGf8E+1KfpD24iaAeld4NIVbg2nCrnvB2klYPA9FDHM//gJHKicZKy/c5QzPpj+zjofTn5ntCE9K7cQ9paISMGNsTT5EO9vNe7m/4oPhWi9eLEeuRvOtF05mmzkB3iu9fGudf/4eX2b+lh2h4cc9Hb0eCpw9uaVEL74ymaVhGmA59gESgm23xJxirnOZ88Q1GK2dw/Gqrm9gSIT3B9vgT7Et9hvbgRkJGTGanEqIJdM0gYiTZEnuUntA2RirHOZ7/MRPV8/i4rW7esumaSV94JwdSn2VT5AARMyU9oS0U0EN0h7byye7fYSD6EO/l/oZMbaix6KwQ94CEDtF0xbLNf/jWG1RqDr7vc/bK1E2zWD22d9OaDx3XaJpO0Ihg6SESgS62xp9grj7J5dIRLpXeIWMPPxBnI5eiodMZGmRn/Gm2xh8jEejC0iMSNoRoMk3TMDWLeKCTXYlPsCn6EKOVU5yafYWx6hkcv9bqJn4kS4+wMbKPvalPsyG8m7ARx9As2VesAbpmEDGT7Ep8goHoQS4W3uL92b8lZ4+i8FvdPPGAk9Ahmi6dCPMH/8s3lryNFbj/XnqaphPQgpiaRTgcpyM0wKG2lyg6M1ytnGK4/D4T1fNUvUKrm9oUGjppq5dN0YfYGnuMztCWhYOHRoiUAwghVksjfASJax3siD/NYOwRpmtXuFB4g0vFdyi4M6ylcfk6Bmmrj+3xp9gaf5y24EYsLYSumRI21qCAHsTUOjmQfoEdiae4XHqXc4VfMlo5fV+dRAsbCTpDgwxED2DqVqubIz7C/XfkJ9Y8Q9fpSMVa3YxVo2kaGgaWFiaghQgbSTqCmzmQ+iy2XyZvjzFZu9i4VC9SdGbum+7rkB6nMzTIpsh+BmKHSFsbCOghDM2U9TaEaIFG+AhgYLIxso/e8E6e6PgGE9VzfFB8h5HKcYpOpiVnqQ0tQJu1kcHYwwzGHqEzuJmAHm7sLzQdOTGxtmmatnAibW/yU+xKfJw5Z5qLxTe5VHyH6dqlNfXZZWgB0lYf3aFt9IZ20BPZQTLQjalZGFoAQwu0uoniI2hKLXmmZO2cRhHiPqCUQuHjKx+Fh688ql6BvD1Gtj5Gvj5Krj5Kvj5Oyc3jt+iMkoZGUI+SsnppD25q7MTDO0hZfQT0IDpG4wwl2roOGtf+nvUm1u8YWgBznQw18ZWH69ebduCiocuMR3z4uvSUi6vqZO0RxipnGK+eY6J2gbKTW5UQEtBCtAc30hPeQV94J73hXcTNDnTNQNcMGW75AFCq8bry8ai6c4xWznK1coLJ2kVy9lVcVV/1NphakESgkzarn3SwnzZrA+3BfpKBXiw9PP9609Ew1v1n1Bp12z+IhA6xamq2w3vnR7k0lsHUdT731B5ikSBV2yEYMLECRqubeA8olGJ+tWEfhZo/YFD4yqXiFSg7WUpujpKbo+zmsb0itl/B9qvYXhnbL1P3KnjKWfgw8NX8Zf5gztCMhTM9hmZiaAEsPUrETBA2koSNBBEzScxsJxXoIWX1EjYT6OiAjq5paDTOTMoOXIj7R+MzXOHjo1RjH1NxZ8nNn+CYc6YoONOU3Tw1r0jNK+H4tca+RLkoGkOjTD1AQAsRNKKEjBgRM0XM7CAR6CRl9dBmbSQZ6MLQTDRNbwQMCRkPtGvhtvG68vHwmK1PkLWHma1PUZ7/3Kq4eSreHHW/huc7859VDj4KUzMxNAtTtzDnvwa0IEEjStRMNy5GmqjZRtRMEwu0EzXTjRMzaPOvtcZ/oM3/L6+5NU5Ch7h3fN/n8niOf/tHP+HccGPc8ebedv7d734B1/P5sx+9y66BLr72qYda3dSWWvzeU/NvtsVvObXkW/DGn938Pl+8c772nbZwc9l5C/HguRZErt+n3LwvWXr/8eG+YfF+Q0LG+qRQ171kPuq19eHPbnf8ueRnE/I6u8/d9o8nNR2i6YoVm//83V8Tsiz+8H/7Jrbj8n/88SuAIhkL0deR4NywrIq6eKcqh/9CiObQ5id6kH2KaBZtvpfhuu+EWDZZyUs0ne14fHB1hn/w0uPsHOgiYH44jMoyDaIhi2J57U/7KIQQQgghmkNCh1gFja59XdcWDSFSgON6VGp1QkGZZUIIIYQQYr2Q0CGazgqYbO3v4OU3TpOZK1Op1fF9RaVa58pEljNDU+wZ7G51M4UQQgghxD0iheSi6VzP4/0LY/zbP36FgGnQkYxybniavVt6yM6V2bqhg3/xjU/Qloy2uqlCCCGEEKJ5ZPYqcW+5ns+V8Szfe+0U50amqdUdOpIxntw/wPOP7yIVD7e6iUIIIYQQorkkdAghhBBCCCFW1W1Dh9R0iKZTSvERYVYIIYQQQqwjEjpE07mezwejGRzXu+lnnueTL1aZzhdb0DIhhBBCCNEKEjpE0+UKFf7lv/8u+WL1pp+Va3V+duQCf/y3R1rQMiGEEEII0QoSOsQ9pWvaQm+HEEIIIYRYH8xWN0A8GJRSVGoOmbky2bkynuczNj1L1XauvxG5QoXhyRyRkCwOKIQQQgixXkjoEE2hFIxnCrz8+imm80VKVZs/+9G7BC1z0W3K1Tp11+U3n9nfwtYKIYQQQoh7SUKHaApNg650jIM7+jhxcZyAaRCLhAgHzetuo7GxO8XeLb08sXegha0VQgghhBD3koQO0RSappGMhfjUozs4uH0D54an+KdffZrOdKzVTRNCCCGEEC0mheSi6cJWgOcP71o0tEoIIYQQQqxfsiK5EEIIIYQQohluuyK5nIoWq8b1fLJzZYrlGpqusbErhWkYeL6PrmsYunS0CSGEEEKsBxI6RNMppShWbN4+Pcz7F8eYzpVIxcP84y8+iWUanLkySUc6xo6Nna1uqhBCCCGEuAckdIimsx2PXx67xHd+cZyutjiaBqcuTWDXHRzX5c2TQySiQQkdQgghhBDrhIxvEU1XqdX5/hunObhjA//ym8/y9z/32MLPouEgnakYV6fnWthCIYQQQghxL0noEE3neh7TuSIff2gr3W3xRbUbuqZhGjqO47awhUIIIYQQ4l6S0CGaTtd0YpEgwxM5PN9fuF4BparNRLZAZ0rW7xBCCCGEWC+kpkM0XTgY4GMHB/nBr89Qdz0c16Ncq/P26WGyc2XGM3N85dkDrW6mEEIIIYS4RyR0iKYLBU1efHI3pUqdn797kartUKnV+ek752lLRPj4wS08tLO/1c0UQgghhBD3iCwOKFaF7ytyhTKnL08ynS/heh6RcJDNPWl2bOoiHAy0uolCCCGEEKK5brs4oIQOIYQQt1Sq13lr8ipvT1xtdVNWJGiYPNG7kac3DLS6KUIIsV7IiuRi9fi+4syVyWXdJx4NMtDTtkotEkI0Q8V1eGtihP9y8t1WN2VF4gELyzAkdAghxBogoUPcNc/3+f1vvfHhFdqHMfemjjQNLNPgkd0b+fsvSugQQgghhFgPJHSIu6ZrGs8+um3he99TDE1keevUMB87sIXejjimYVCs1PhgNMPMbIm+jmQLWyyEEEIIIe4lCR3irum6xleePbjwfbFS4z99501eenovX3h6L6lYGF3XqdUdLo9lefXoB8wWqy1ssRBCCCGEuJdkcUBx17T5VcavXVzX59j5MR7e2U9Pe4JQMIAVMEhEQwz2tdGWiHD8g7FWN1sIIYQQQtwjEjpE82ngK8WFkRn864o6lFIUKzZDEzkMXV56QgghhBDrhQyvEk0XDgb4+MFB/vrVE1ydnmWgJ41lGsyWapwbmiIzW+Jrnz7U6mYKIYQQQoh7REKHaLpwMMCXnj1AMhbm6PlRLoxM47ge4WCAnrY4f+f5h3l8j0xhKYQQQgixXkjoEE1n6DobOlP85jP7eXL/IFW7jucrLNMgEQvRlYoRkhXJhRBCCCHWDQkdD4iz2Wn+6Mwxhguzq76tf/rQEzzRuxFziboMXddIxsIkY+FVb8/dUkqRqVb4569+H//GdUVWwWPdG/j6zv1sjMu0wUIIIcRaN1S+wqvTPydTz2DqJk+0PckT7U+1uln3HQkdD4hC3eb4zARnczOrvq3DPf082r1hydDhK0WpYnN1Kk+xWr9plcBUPMKuga7Vbuod8ZXifD7Dr8ZH7sn24pZF1XXuybaEEEIIcXfKbonL5cuM18awdIttse2tbtJ9SUKHWLZT2Sk85d/2547r8f7FMf7gb94iVyjjegpYHDoe3b2J//W//8wqt/TOuMrndHaq1c0QQgghhHhgSegQy3Y6O43r3z50lGt1/ttPjmIaOv/kNz9GKh5G0xbfZi0Nu/J8n1MZCR1C3CgWsHhu4xZCRoC5eo2CXWOublOo1yjY9sK/bdflHoxMFEIAuXqWd3JvM14d55H0oxxMPdT0bZyeO8UbmddoC3bwpb4vY+pyuCjunryKxLJNV0pMV0rErSD6jWkCcByPoYkc//zvPMPhvQOYxs3DsDRuvl+reEpxSno6hLhJyDR5pGsDe9u6cJXC83081bi4vmr82/epeS6Fus2cXZu/NMLI3LXr6tddb9coOjaekpgixEpk7AzH8kfJOzkGIptXZRvH597n5NwJ+iMbUdz+JKMQyyGhQyybpxRncjMMJttuGTrQwAqYRMMWwcDafokppcjXaowU5lrdFCHWHF3TCJkmIXPp97GvGgHEvxZE1LVAct33fuOrr3xc36fo1CnYNWYXQkkjoExVSrx8+dw9+g2FuL8opZh18ozVRrG0IP4qBAJfeVwsncf2bTzlSS+maJq1fUQo1qyTmSle3Lzjlj8LWQEe27OJH7xxlp2buoiFg/e4dXfOV4pzuWncJWpUhBBL0zUNXTPg9nNLLKKUwkfNh5RGEGkEFSWhQ4gllL0yk7VJal4Ny1ydz9bx6jhz9TmUxA3RZBI6xIqcykzOF5MbN/1M18A0dN48dYXT/3aSLX3txCIW2nW9Itv6O/jaJ5s/DnW5fKU4kZlsdTOEWFc0TcNAwzDg+hV7lFLYntuydgmx1s05c4xVR1d1GxdLF6j7MsOiaD4JHWJFrhWTK6UWhQmAuutxfniavo4EANm5MrlCedFtEpHQPWvrUqSeQwghxP3AVz65epbRyuqFDle5nC+ew1USOkTzSegQK1Ko2wwXZtnbfvNaG8lomN/73S8sef9bFZe3gq8UpzLTrW6GEEKI+5jjO1wpX+Z88RwjlWFm7GnKbhmFIqiHSFpJ+kIb2Jfcz97EPgJ6YMnH85VP2S1xpXyFseooY9VRxmtjZOwMVa8KQNEt8N2xb/O3E9+77ePsjO3i871fYFN04Kafub7LWHWUq5URxmpjjFVHmahNUHQKuKrR4zhcHuJfn/hXt338sBHh013P86nuT3/kc+Qpj6yd5VzxLJfLl5isjTPnzOH4DqZmEjPjdIW62Bbbzr7EfjqCnejayo8VsnaGk4UTXCxeZNqepOxWqPk1LC1AxIzSYXXSH+lna2wbW6PbCBnNPRk6UZvgO6Pf4oPSRXx8AprFFzd8iUfTjzV9W/cLCR1ixU5kJtnd3olxw0xUuq4Rj6zdOo5rlFKMlQpkquWPvrEQQghxg6yd4e3cW7yV/TW5ehZXufjKR83/d820PcWl0ge8mX2D7mAPv7Xp77E9fuu6SIC6X+f92WP8xdX/iq/8Wz6mQmH7NrZv3/Zxql4VD++WP5upz/BnI3/CaOUqPv58rdXi+kYfn5Jbuu3je8qn7tdv+/NrbThfPMvrM6/xQekidb+Oz4e/0zXZepaRyjDH8kf5UeCHPNv5SZ7ueJpEILnk498oV8/xg4mXeTd/BNu7Vgy/+LnT6llGK1c5Mfc+hmawNbqN/3Hb7xI2Isva1u1MVMf59thfcWruJK5ysXSLz/d9gYdShwjqa//4aLVI6BArdiozxdd37OfG2W9rtsNr719a8r4dqRgP7+xfxdZ9NF8pTmYmpVROCCHEilwpX+ZXmdeZspcepqtQeMrDUx6j1av8x0u/zz/b/i/YHB285e01NAK6RcJcfMBt+zYlt4hCoaERMSJLHignrRQB7da9KgY6USNGMpBadP2sM7swvMrUTJKB1G2nuQ8ZYaLm0gfqc84s7+aOcGLu+JLF6deCwbVhZC+PfxdfeTzb9UliZmzJbVxzsXSePx76I2bsaTx167B147ZMzaQ33EdIb876YdcCx8m5E3jKI6SH+HL/Vznc9iQRI3LTkPT1REKHWLETmUmUUjfVdRTKNf73P/jxLe+jlCJkmTx/eFfLQ4cCjksRuRBCiBXalzzA65nXyNQzxMw4exJ72BXfzcbwJlJWGkMzmHPmOFc8y48nf0i2nkGhKLgFvj36V/zLHf/zLYcQWbrF422HeTT92KLrj8+9z58M/SFlr0zcTPDZnhf5ZNfthzZpmoZ+m2nlOoNd/LPt/xx1w5o5/9f53+Ny+RIKRX9kI//Tjn992+CiadpHrrvVYXWyJ7GPY7NH0dDZFBlgX3Ifg9EtdAa7CBkhbM9mpDLMr7Kvc7ZwBtu3cZTDG5nXGIxuYU9i75IH60oprlZH+C+X/jM5J7twfUAL8FDqEDvju+gIdhI2wtS8GjP1aYZKVzhfOoeGzqHUobsOA0opJmrj/PXYtxYCR9iI8JX+r3O47TAhPbSuAwdI6BB34Wx2hprnEtOtRdd3pGL86N//k0XXuZ7PZLbAG8cvc2k0yzc+feheNvUmSqnGzFUzEy1thxBCiPtXUA/yQs+LfLr7ebbGthG+xdnyiBGhN9TLI+lH+b1z/4YZexqFYqgyxERtgg3hDTfd59rB/I2B5MYAoWn6ilcLb8wiZ9w0WkGj0dNyrTfF0Iy7WpHc0Ax2xHfy24O/Q0+ol55Qz01BJWpEabPa2JXYzcvjf8MvZ17F9mtk6hmuVkcYjG0hskSPju3b/OnwH5N3cvO/g8b22A7+weA/osPquMU99vJMx3M4yiFfz9MRvNVt7pxSirHqGH899i1OzZ3AxydhJvhK/9d4JP0YQT247gMH3PGs6kLczFU+Z3MzN12v6xqJaGjRpS0RYc9gD1965gBbNrTz3ddOtqDFi9V9j7PZm9svhBBC3AlN09iT2Mv+5IGFoTO3uyQDST7X8/mF+/rKY7h8pYWtvzc0TaMj2MHD6UfoC/eha/ptn6OwEeaR9KMMRD4sfJ+qTVJ2l669fCf3FlO1qYXhW1uiW/ln2/8FHVbHkn8TS7foDnVjaDdP/3/b3wcd/brlAnzlM1q9ynfGv83JueP4+KQCKb7a/w0eTT9OyJAejmskdIi7cmJmecOTQpZJLGwxmS2sUovu3IV8hqqsCSCEEOIe2RnfvfBvpdSSRdrrVU+ol5SVXvi+4lVxl1g3xFc+b+feojY/q5eBwW9t+nurNpwpoJsE5nt+fOUzVh3lb8a/w4nZ9wFotzr4av/XebTtUYLG+i0avxUZXiXuyomZRiH29W9r31eUazfPpqEUjGcKXBzNkIo3Z4aIu7HcwCSEEELcjaT1YWH4tdmnxGIhI4R13bBt13fwbphV63p5J0/GzizMvLUjvpPuUM+q9S4YmompBeYDx1VenvgeJ2aPA406mS/2/SYPpx8hcMPQcyGhQ9ylk/PF5NxQSP5v/ugni26nAMf1mc4VsQIG//Clw/e4pYsp4LiEDiGEEE2ilMJVDu78LFWNKWEbU9E2Bv2om6aXvbGI+0GnVGMWL1e588+Rh4+af44UzM8oVb8ujCkUS00zOVq5inNdT8j2+I5lDZdaLlMzMTWDqdokP5r8Ie/nj+Hj0xPq4Yt9X+ah1KGPXIdlvZLQsc5pgKHpeMpf0dSxI8U5Zu0a7eEPey40DazAzS+tWNhgz+ZuDu8d4OD2mwvn7iU1P13uSunzRXbr6+NCCCHEjTzlUfUqFJwiV8qXGateZao2TdEtUPbK2J6N4zu4yqG+xDChB5k/v55HyS0yWZtkqHyFydoEOSdP2S1R86rUfQfHd3CUs+R0tzcqukX869Yi6Qp2o3/EjFp3w9AMim6Rn02/wtH8e/j46Og8mn6cPYm9EjiWIKFjnYsGLAaTacZLRbK1yrLv7ymfU9kpnun/cK7xZCzMv/kfPr/EvVqvWLe5Usiv6L6xgEVHOEK2VqVYl65xIYRYr2pejeHKEG9kXuP47PtUvA8/Rw3NwNAMdBqF04ZmEDaMRbdZD1zfJVPP8P7se7yZfZOJ6vjCKTsdvfEcafr8RSOoWdT9+sKq6B+l5tUW9RiFjNCi0RfN5vh13sm9RcbO4MyvZ+Ljc2z2KBsjmziQPCjB4zYkdKxzYTPAN3ce5IdD53l9bHhFj3FiZnJR6LgfnMpO4/m3HyO6lO3pdn5jy26+e+mMDNESQoh1qu7bvJN7i7+d+D7ZegaAkB4iakaJGFHag+0kzCQRM4ylBwnM1wF8Z/zbLW75veMpj6vVEX4w8X3enz2GQmFqJhEjStSMkgwkSVtpomaMkB4ioAfQ0Tmaf48rlcutbv4t5Z08eSePpVu0Bdqo+3XKXpmx6ii/mP4ZUSPKttj2u5pm+EElz8g6V3Ec0qEQneEoAV3HWeaB+P1aG3FihSuRa0BbMMKGWALblZmvhBBivTpbOMtPpn68EDhSgRSPph/jkfRjDEQ2E9ADNxUzF53Cugod+XqOX868yrHZo0AjlG2Pbedw+5PsjO8mFUjd9BzZvs1EbfyOQ0fYCKNdt55J2S3N15o27/e4UcyMsz9xgCfan2S4MsTPp19h1pnlXPEscTNB1IzSF96wqrUl9yMJHetczXPwfMVgso2EFVrREKszuWlc38PU75831/EVLgoYNE16Y3FiAQvbu/Mxp0IIIR4cru9yJP8OGbsROCw9yBf6vsjhticbw3tu49pwnPXAVz7j1XHenw8chmawN7mPL234Cj2h3iXu1yjCv1OpQBLjuug/h14AACAASURBVNAxXh1fmMlqNRiaweG2J/hC3xeJmTE2RjZR8Sq8PvNLyl6Z9/JHiAfifKb7edqtjluuOL9eyTOxznlKUfMcBuJJksGVzSc9XSkzUb5/5hp3fZ/T2ekV3TdlhdiabMNVPras8SGEEOvSrDNL1s7gzoeIzZHN7I7vWTJwAAsh5W58uJq3YslpnVa8gQ+7CO5mdi3bt5m2pxfWIkkGkuyK714ycACUnBLV+TU37kRfuJ+Q/uHzfqF0nrpvr9rMYIZmEA/EiZkxABKBBJ/oeIZD6YcJ6iF8fN7MvMHb2bcoucV1N0PZUiR0CCqOy8Z4iqS19M7ydhR3NxPUvTZVKTG1wpCUDM6HDl9ChxBCrFc1r7qo0DltpTE/onjYVz4n507c1XZ1TceYrxVwlIvt15s+j2JA+/D3KHuNlcBXsg1PeQsL9gGE9DCJQGLJ+yilGK2Okqtn73g7aStNb7hvYSjTUHmIC8UL+I3JeJfd7pXoCnXzTOdz7E7sJqAFqPk1fjHzc47NHqXqVWWuy3kSOgQVt05PNE5bKLKiIZBKKU7cR6HjZGaSlU0QDKlgiMFkej50yPAqIYRYjywjuGi8/qwzS92v3/astq98RirDvJV98+62q1tEjMYU9bZXI2dnqbp33itwJxKBxMKQoHw9T76eW1GHiqHpWNetyF3zaxSc4m2HTimlyNWzHJ87xpQ9taxtPdH2FFGj0fOg8Pne+HcZKl/B9d0lexqUUri+u6yeldsZjG7h2c7nGIwOYmgGc84sr0z9lLPFMzetz7JeSegQVF2HkGmwIZ4gbC5/mjdfKU7OLG8H0UonZiZX1N1pajqdkSi9sTieDK8SQoh1K2kmSZhJDBrB42rlKh+ULlBwC/OLAjY+Y1zfJV/Pca5wlv/v6l8w587dVXFxzIzTFewGGtO0Xilf5tjsUWbrszi+g698XN/F9mxKbomKW1nWmhcAA5HNmFqjN8VVDq9M/ZQpe5KaV8NXPr7ycXyHqluh6BQXLeR3PUsL0hZoI6g3gkfRKXCxdIGJ2kQjoM0/R57yKLklhitD/HTqJ5ycO4GnvOuGkX20/ckD7IrvWmj3aPUqfz7ypxydfY+x6ij5eq7xfHgVSm6JfD3PZG2CS+VLHJ89xum5k8t6jm5nT2Ifn+h8jt5QHzo6E7Vxfjb1U66ULuOu0zVarieF5IKK6+D4PluTbSSCQSru8t4YCrg4m6XqOisKLffaicwU/gpCR8yy2JxIY2o6ru/jrnDKXSGEEPe3oBFkV2IXQ+XL5JwcFa/MDya+z4w9w8bwJkJGCIWi6BQZrgxxNP8ec84sO+I7mXVmmaytbDKTNquN7fFtnCuexfZrjFav8uPJHzJWHaUv3EdQD+Epl6pXo+KW6Qx1sjO+m2Qgecfb2Jfcx+uZXzJZm0SheC3zKiW3yPbYDuKBBGp+ZfWKW8ZVLnsSe9kcvXnafEM36A51szW2jTOF0zjK4fTcSXzlsS+5n4SZRNd0al6VydokpwunGakMkbbaSAXSTNtTd9wDETSCvNT3G5TcEhdK53GVy3BlmD+88gdsj+9gQ2gD8UACUzNxlEPZLZOrZ5mojpOr59ib3M+jbY/f8XN0O7qm83D6EUpukVemfkKmnuFC6TyvzvyciBlhQ7h/Xc9oJaFDUHVd3GuhwwoxuYJ6h4JdY2guz+72rlVoYfNUXYcL+cyKBlclrCDbUu14SmF7nozQFEKIdexQ6hHGq+O8m3+Hklti2p7mbydeRkcnZITxlIft14DGsKhdid18ZcPXeSPz2opDR9SMsiexjyvlIU7PnaTm1xivjTFeG7vl7R9vO0x/eNOyQkdfuJ+PdXyCX0y/QraexVMeR/LvcCT/zk23jZlx2qy2W4YOgK5gF093fJzZeiNolb0y7+aP8F7+XQK6haEZ1H0bT3kYmkFPqJdPdn0KXyl+Pv3KMgvKN/Cl/q/w48kfcrF0kTlnFle5nC2c4WzhzG3vF9ACTQ0Clm7xZPtTlNwSr828SsEtcDT/HvFAgue7X1jXM1pJ6BBUXQfH99iSaiNprWwGK08pTmSm1nzoGCrkKdRrK7pvwgqxLSVF5EIIIRoFzM93v0DEjHC+cJZsPUt5/ux/zasS0AOkAmnSVpqByGY+1fVpukM9bIlu4RczP1vxdjeE+3mh50XiZozL5cvM1vNU5wvbNRorn1u6RdiI0Ga1Y61gdexPdn0KQ9M5MXucmfkZqOp+HR+FoRkENJOQEaIj2Lkwi9OtBI0Q+xL7AXgr+2smaxMU3SK2Z+P4dZRmEjYiJMwEveFeHksfZm9yL1O1KRJmggnGl9XuwegWvrHxm7yTe5tzxbPk6jkKTgHbr+H6Lj4+OjoBPUDICBMzY7Rb7eyI71z2c7SUqBnj4x3PUHSLvJN7m6pX4c3MG8TNOM92PkfcTNy0Psl6IKFDUHUdXN+nP5akMxLF1PVlDx3yleJUZopv7Ny/Sq1sjlOZKTx/+X0UGpAOhRmIp/CUT12KyIUQYt3rCnXzUu8X2JfYz1D5Ctl6lppfw5jv7UhbbWyKbGJLdOtCvcHW2DaebH8KQzPZGNm47G0amsFgdJDOYCfD5SGuVkaYdfLYfh0NDUu3iJpR0oE0GyMDxM2lZ4y6FUu3+HT38+xJ7OVS6QOm7SnKbgVP+Vh6gJAeIhFI0BXqYlNkYMnHipjRhQUTPyh9wFRtkpJbxEdh6dZ84Ohjc3SQdCCNrul0BDt5KH2ItmAbG8MDRMzIHbc9bbXxQs+LPJp+nJHKEBO1CYpOAdu3cZWHqZmEjRCJQIquYCcbwv10Bpc+YZoMpHkodYgBZwBTM+kPf/TfrT3YznOdnyRqRMk7OaBR/G/7deJ3/Ns8WCR0iPmeDh9T1xlMpIkFLGbt5fUGeMrndHYKpdSaTu8rrecImQH6YwkSwRCFek16OoQQQgCNhQF3xHfe8dnyrlA3vz34O3e1TQ2NuBlnX3I/+5Krc7JPQ2NDuJ8N4f67fixDM+gO9dAd6rmj28fMGJ/pfuGuttkebKc92M6hu3qUhv5IP/2Rr67gfhvpX0GwfFCtz0FlYpGq4+D6jTP329PtxFcwxEoBw8VZ5uq3nsViLVBKcTozhbeMlU6viVsW29PtAHi+kp4OIYQQQohlkNAhqHouzvxwqm2pduKBldV1VF2Hi/m7X211tczZNYaLcysqAI9bQban5kOH8rF96ekQQgghhLhTEjoEtfnZqwAG4ilSodCKFgn0fMWp7Npdr+PCbIbaMqcDviYRaMxcBfM9Ha70dAghhBBC3CkJHWJR6IgHQ/THkoSM5Zf7uMrndGa62c1rmpOZqRWtrWHqOt3RGF2RxgwdrpLVyIUQQgghlkMKyQVVz1k4GNeA7ak2opZFtbq8IUSe73M2N4Pn+xj62suzp7PTuCuo54iaFluTbZjzv5Pn+9SlkHxFlFL4SpG3q8zaNUp1m7LjUHbrlB2nMamB5+GqxuKLnu/jz09OoGsahqZj6I2vpq4TMkzCZoCw2fgaCQSIW0FSwTBxyyKgr99FmIS433m+z5xdI1urMlevUazbFOs2Ndel5rnYXuOEmacUSikMXSegN/YNAd0goOuEzAAJK0jSCpEMBklYIRLBIMEVnFgTQtwdedeJRk/HdQfj29IdxAIWmWplWY+jgMlykelqmd7o2poQzvN9zmSn8VbQ0xGzLHakOz58LKWwfenpuBMVp85EucRkuUimWiZbq5KvVcnWKuTtKiWnTrlep+w6lJ06Vceh7nvzBxKN4HEtdBjXQoemYeg3ho7AQuhIWEFSwRDpUJhUMERbKExXJEZfNE5PNE7IMNf0DGtCrFelus1YqchYqcBEucB0pUy2ViFbqzBr3xw6aq6Lp3w8X+GjMLXrQodhENANQqbZCBxWkESwETzaQxF6onE2RBP0xRL0RGPErSC67BeEWFUSOsT88KoPD6K3p9qJrbCYvO57nMvNrLnQMVUpMV0pr6iIPBaw2L4odMg6HbeTr1UZKc4yWiowXiowUS4yUS4xVSmSq1bI1WoU6rVl/x2u9ZA43HloNDSNaMAiHQzTGYnQE2mEjr5YnI3xFNtSbfTHkgQMY0U1TEKIu6OUIlOtcHE2ywezWYYKea4W55goF5ksl8jVKnjLmOLcVT6u54MHLFG+Z2o6qVCI3mic3micvmiCTYkku9o62Z5qpyMcWbcrRguxmiR0CBzfw/H9hTU2uiMxuiIRzJy+7OFIznyPwnMbt6xSa1fmbG6G+gp6J3Q00sHGooDXNIZXSegAcDyP0VKBS3NZLs3mGSrkGS3OMVlpHDQUWjiFsqcUhbpNoW4zXJwFGsMHU8EwvdE4A4kUW1Nt7Eh3sLutk8FkWoZjCXEPFOs2F/IZjs9Mci4/w6XZHMOF2WWHjJVylU+mWiFTrXAyM4WORioUYjCZZmuynZ1tHexr72ZnuoNUKCwnJYRoEgkdAgXUPQ9PKUxNwzIMtiTbODI1RrFeX9Zjub7H6ezaKyY/nZ1e1Jtzp4KmyaZEiphlLVznKbWiAPOgqHseQ4U8pzNTnM3PMFyYZbQ4x2ipwJy9/F6Me0kBebtK3q5yJjdNyDDZEEuwOZlmX3s3j/f0c6irl4gZkCFYQjSRAqYrJd6bGuPI1BhnstN8kM+Ss6srWrC1mXwUuVqVXK3KsekJ0sEwW5Jp9rZ380TvRh7t3kBHOCL7BCHukoQOAUDNbRSTXyuW3pHuJGpaKwgdPhdns9Q9F2sNFeqdzk4trEWyHNFAgJ3XDa2Ca8Or1lchueN7jBbnOJmZ4lRmiovzQyHGSoX7eiavmudyaS7Hpbkc70xc5bWxIfa2d/Gx3k08u3GQsIQPIe7KtVq/X4+P8Ob4CCcykwwXZqmt0X2or9RCHcnJzBRvTYxwoLOXJ/s28VTvRroiMan9uAN1x+XM5SneOjXEge19PHVgsNVNuqfmSjV+fuQChXKNzxzeSV9nstVNWhPWzlGhaCnb8xat1L0j3U40YC1xj1tTNMb1j5YKbEm2NbGFK1dzXT6Yza6siDxgsautc9F162lF8lm7xqnMJG9PjnI2O82VQp6xUpHqCtc7WcuKTp1j0+OczExyZHKUNydGeGnLTh7v2SgHGUKsQL5W5a2Jq/xs5BLvTY8xWizcV73ENc/lXD7Dpbk8706N8auxYV4c3MHhnn7i1srqHu8Xb7x/iTdPDPHkgUGeOrB50YyUnu9zcWSGv/nlKXZt7uKLz+y/6f6O53N5PMuPf32OcDCw7kJHpVbn1yeHyM2VeWzPJgkd8yR0CKCxc73+oHxLso2EFUSDZQ+XqXseZ3MzayZ0jBRnVzzsJxqw2J5uX3Sdr9SKek3uF67vc7U4xzuTo7w3Pca53AxDc3kKdXtND51qFtf3OZ/PNIaQZad5pn8zf3fXQ3RGoq1umhD3hbrncTo7xfcvn+f1saE13bNxJxzf4/JcjrFSgbO5aZ7t38IXtu5iW6rtga0DOzc8zcuvn6YtGeHJfQOLVnVTvmJsZo7vvXaKUnX7LUNH0DR4ZFc/qViIgd61cSxwLyVjIb726YdwHE8Cx3UkdAjg5mlz41aQjfEkZ3LTyx4+4/geZ7LTfH5wZ7ObuSJncjMr6pkI6Dp90Tjtocii6z3l31dn6+6U7bmcz2V4dfQyR6cnuDSbZbJSWje9OjeyPY+j0+NcnstxaTbHP9j3CA939bW6WUKsadOVMj8dvsjLl89xOjvd0skkms32XE5npxkvFTmZmeQ3t+3hU5u2kgqGWt20Ncc0DQZ629Zl4ACIhCwe27Op1c1YcyR0CADqnrto1hBd09iR7uC1saFlh46673EmO9PsJq7Y2ew09RX0TITNADvSHQt1Ltd4SuE8QAfiZafOqcwUP796maPT41yazZKv1fDXRb/GR5u1a/xw6AITlSLf3HmAL23bK8OthLiB5/ucyU3zVxdO8fOrlxkrFVpeIL5a8naVN8aHGS3NcWUuzzd3HaA3Gpf9ghAfQUKHAOZrOvzFHxA70x1EzACzdm1Zj+X6PsOFPOV6nai1/LqQZjuTm15RSIiYAXbeUM8B4D9APR2XZnN8++IpXhsbYqQwy9wDdFaymRzf593JMfK1Krbn8Xd2HpADDCHmVV2HN8dH+NMzx3hvevyB6t24HV8pLs/l+fNzx7lanOUf7X+UXW2dD+xwqztxrdbj//3e2wvXRYIBnjywmRee3H3b+1Vqdc5emeLo+VEmMgUcxyMcDNDbkWDPlh72bOkhHmnU0IxM5vnWz46zd2sPe7f0cOTMCKcvTVKzHTrbYnz84BYObO/DND/8OyilKJRrvHvmKmeHppjOl3Bcj0jIYrCvjSf2DbBt44ef9aWqzZsnhjh3ZYrPHN6J43n86v3LTGQKaJpGf1eKJw9sZtfmbkzjw5OSdt3lO6+e4Oi50YXrutIxvvrph9j8ET0+I5N53jo5xKWxLMVyDdMwSMZCbO1v5xMPb6MtEVny/vcLCR0CaAyJ8m9Yk2NnWyeRQGBFj1dy6lwp5NnX0d2M5q3YnF1jtDi37PVGACKBALvaOm663lMPTiG5p3yGC7OczEy1uilrngIuzeb5zyeO4Pk+v7Xr4KLiSiHWo1m7yo+GLvInZ45xMZ99YE7I3KlsrcKPhy8yUS7yuw89weGejYTM9XlopaERsgL0tMeZK9W4Mp5lfGaOnvbbLxZcrtb50a/P8vJrp6jZDvFoCAUUyjXeOjXE6PQs3W3xhdBRKNc4cmaEqWyBnx+5yFSuSMDQqTse7569ypHTI/z2F5/g44e2YBqN4OH7ip8ducBf/Pgodt0lEQsTChjki1V+feIKxy+M8Q9/4wl2DzaOVxzXY2g8yy/eu8hcqcpEtkCpYhMMBMgXyo2gc3mSb77wMIf3DSz8Lrqu0ZaI0JGKkp0rc+LiOPFIkOef2LXk8/ba0Uv81Svvc2UiSzRkkYqHcRyfY+dLvHv2Kp94eNtd/mXWjvX5zhA3sefX6bhebzRORzjKlbn8shdssj2XM7nploeOS7NZSs7ypv2F6xcFTN/0M89XOA/IB2t/LMmBzh5+MXqF8gqep/VGoRguzPKHp48SDVh8efveVjdJiJaZqZT56w9O81/PHedqYW7dDsmsui7vTo3x7468zr965Cme7tu8LoOHpkFfZ4K/97lHKZZtfnbkAn/502NL3mdoPMtrxy5hGDq/9eKj7NjUCWjYjsNkpkg03DgIv9F7566yf2sff/9zj9HbkUChOHlxnP/0nV/zB9/9NXu39NKZjqJpGpqmsX1TFy88sYt9W3uJR0OYhk52rsx3Xz3Ju2eusrHn/ELouGYmV+L9C2M8sX+ATz++k0jQYq5c5Ye/Osur733A4IY2dg50LbTPNHSe3L+Zg9v7mMgUyReqzBYrS/7+F0Zm+OPvv8Pl8Sy/9cLDPLpnE9GwhecpipUaU7kiiciDM1Pa+ntXiFtq1HQs7g2wDINtqXZOzExSWeYUqddmsGq1syssIg+aBltTbQRv8cHhK/+Bmb0qbJoc6upjf0c3b01cbXVz7gs+iqFCnv/n1HsMJFI80r2h1U0S4p6bLBf583PH+W/nTzJVKbW6OS3nKcWZ7DT/55HX8R5RPNM/+EAEj++/fpp3z1xdtF6RUorZYvWm22qahhUw6UrHiYaDpOIfPSSoVK1TLNdoT0bZvbmb7Zs+HOa0a7MLCgLmzT3Kdt3jC8/s42MHB7FMA03T2NSd5uj5UX51/ApHzgzz2Sd3YxgamgY7B7rY2JUiEQstDI11XA8UvPH+ZS4M37yocd316O1I8rVPHWKgN42maXieT7Fsc+bKFFenZpmZLS2EDk3TiEdDxKMhfAVB66P//j988wwfjGZ46em9/OazB+hINYKSmj/RW6u7i4aK3e9kbIAArg2vuvks1e62TsLm8odY2Z7LuTUSOuwVTNUYNgPsauviVqP2faVwH5DQoWkau9s6eaJnI0HjwdmxrTZPKS7kM/z++28zUSq2ujlC3FOT5SJ/evZ9/uzscQkc11E09gu/d+SX/PzqJWz3/p0m+Jqq7TBXbJyxv3aZK1ap1JrTM97XkaC/K8WJixP8+Y/e462TQ5QqjZqgYMAkaJnotxjG2tuRYKAnvRA4AGKRII/s3oih65y4OL5wTKNpGpZpkIqHF9XimYZOd3uccDBA1Xbwb/hcj4QstvV3sLE7tbANw9DpSEVpT0ao1upUaytfs8p1PY6dG6XuuHz2qd20JT9c9f5aD004uLIh7mvV/R/DRVM4/v/P3n0HSXreB37/vqlzmg6TZ8Nsms0BkQEACZAiqIMYTpGSKFEnS/ZZvtKpznZJdtm+ss9Xda6TdD6zdKGkoyTqKIkURZEiKUokCIAASKTFAptm0+QcOse33+Q/enaxYWZ3u/ed/Hyqpnamd/rpd3qm335/z/P8fj972aBjoC2Fv4XZGstxmC0XSVcrJPzrkwDlAJdaXOnwqxoHl0kih+t9OrbG9ipoNEA81dHNQDzFuwuz6304m0bdtnhzbpIvXDzNbz/ylEgsF7aFhUqZv7h8jv86+C5Z/c7Z7u3OAYbzWf6fN1+mzevnkc4e1E2cXP6RRw/wyaeO3FLF0bRtTg9O8Pkvv/LA43cmI3z6w8eomxavXxjj3atT7Ohs4/Eju3jy1B46ExFk+c5zayziR7sp4Liua+n75zKlG6sF0EhyP3t1mtODE0zM5SiUa+h1k1JFp1IzcBy4/RLI71WJR/0oyq1Bj6LIqIqMYS1/3XS/ihWdQlkn4PPQEd8ene5F0CEAjaBjubyNVjuTA1QMg2u59LoFHXPlIgvVctP5KNCoXHV7J/LrbJyWuptvVJIkcSzZySOdvZxfnGvp+XpQmiwT8/qI+wLEfQFiPh9+RcWjqHgUBVWSMR0bw7KomgZ5vUa6VmW+UiJdq6zbdrdiXef58WGe7tvD411963IMgrBWcnqVrw8N8icX316XgCOgaqT8QVL+AKlACL+q4VUUvIqCLMnULRPdsqhZJplahflKmYVKmXy9teawD2K0kOVfvf4iv/+hH2dvLLFpLyjbIn76uxO3bPExTYuJuZwr42uqwuH+Tn7z557i0ugcr7wzzOlLk1wam+eF01f5zMdO8fjRXfg8t874y1Jj29TtFFlGghvv0Y7jYJgWf/BXr/KDt4eQZIn9O1L0dsQIeDVKlToj05llj02WZbRldgC49Zs0LRvHcVAVGVmW7gigtiIRdAgAGNby26tCHi87IjGG89mmZ/drlslgZoHH1uli7Ep2kWoLy9uqLNMbji7b8On61qqtli4Z9fp4uL2Hl2OjXM4urtrjSEB3KMKBtiQ7IjF2hmPsjMToDIbxLgUXqtz4kCUJicaJWKIxg+g4DrbjYC3l1Zi2RV7XGS/mGMwscGZ+hsHM2jUkc4CJYp4/G3yH46nOlrYiCsJmUDEMXpoY5T+dfYNMbfUDDgnYFW3jRKqLgbYU++NJupbOE5oso8oKytI54voFvUPj/HD9PG3YNnXLJFOrciW7yGBmgbOLs1zJLq76RIUDDGbm+T9fe4Hfe+rjpPzBbXFR2QqPptKZCBOPBji6t5v5TJHvvXGZ771xhT//+zOkYiEO7+m65T7lah3LuvOdOFeqYjsOkeB779+vnx/jGz84TyoW5H/91R+joy2MpinIksTYbIa/feX8yge3ir+yoN+LosgUqzp63cJxnC3/NyKCDgFYeXuVLEkMtCV5bXq86aBDt0yurOIF7L1cyi5SayGfw6eoHIynlp2ZchxnXVYCVpssSZzq6Oah9m6uZBddC6qUpSaTx5NdHE62cyjRTsofwLu0guFRVDxy4yKi1ZOt5dgcSrTzob7dVAyDxWqFN2Yn+bvRK1xIz7UUeDZDt0zeWZjh+fEhnuu/e2lEQdiMTNvmQnqO/++dHzFfLa/qY+2NxXm6r58Pdu9iRyRGyOPBp6j4FBW1hfPE9XP2sVQnNdOkbNSZKOZ5dXqM708Mczm7uGpNDC3H4bWZCf7Nmz/gX33go2JS4i4kSWrkcMRU2iJ+upMRFnNlXj4zzELuzr+5yfkcxYqO7Ti3vFcPjsxhWjZ7e5PIkoTjwMWROWq6wfuO7eZwf+eNUuemaVGpGuj19cm98XlVdna2MbOY5/SlCVJtA3i0rX1ZvrV/OuG+WbZ9y/7Hmx2Mt+NTNYpNllTVLYsrSyf09VhavpxZaCmRz6eqHEqsvLVqqySR3y7pD/BwZy+vTo8zVmx96TzhC/BQRzePd/XxcEcPKX/wpm0Qquu9LRRJRlFlfKpKzOunIxhiTyzOP+o/wJn5af780lnenJui2mQFtmbMVUp8e/QKz+7af0cHe0HYzBzHYaKY5/8980OG8stvQ3lQiiTxaGcf/3jfIR7u6CHhCxBQtZaCjNtJkoQqSaiyh6DmIe7z0x0KczTZwU/tP8Kbs1N85co53p6fXpUJJcO2+ObwZR7t7OMn9x0W54fbTM3nqNQMejtiN5KmFVlGN0wquoGqysu+Z5Srdb72wlna20K0x0NIksSl0TlefmcIWZL44Il+ZEUGByJB742KW9fHsm2H6cU8f/EPb9+Ry7FWZEni2fcf5Oy1af7kb99gR2eMo3u7bxyj4zjMLBaIhv0EfevfaNkNIugQADCdlROiDiXa8SnN/6nYjkO6VmW6VKA3HH3QQ2yKaVtcy2VaqlzlU1QOxduX/T/H4Y4KF1uFIsk82tnLifaupoOOdn+QD/Ts5Om+fo6nuggvzU56VRWZtd2rqkgyQc1DQNV4ZsceHuns5fmxIf7w/Ftcy6VXZWtc3bK4nFnkrblJHu/asQqPIAjrY7FW4b9cOM1rMxOrsiJwONHO5w6f4gPdO0n4AngUZVUnqRpBiELEqxDyeOkOhnlfVx/fHb/Gnw2+y/AqBFY1y+T33n6FRzt72RWJbdktNKWqztmr0xRKNbLFKmcuT6IbFhdG5vjq998lvxlqNAAAIABJREFU6POQiAXp70mQiAYBOHtthi9++01UWaanPUY05KNaNxiaWGR8Nsszj+5nV/ed3bx398R5a3CcoX+/wO6eJODwzpVpZheL/MonHm1UnAKQ4P3H+vmjr7/OS29f43/7D9+mryPGQq7E4OgcXk1ld8/du4Xfr7GZDCPTGUoVndl0kdnFAoVyjeffvMLIdJqAz0NfR4zd3Ykb5XSfOLmHS2PzfPX5d/jtz3+TQ7s76UpGqNbqTC8WmM+U+N3f+hS7l3kONiMRdAhAY4uKs8LlWF84SpvPz2Qp3/QFW9U0uJpLr3nQMVrIkdebTx6UgJjXx87InU0BYSmnYwtur7quOxjm4Y4eXpuZuGcpzIjHy5O9u3h2535OtHcR9XjxqSqafGdFkfUgSRJeRSXpU/jU3kMcT3Xy+2//kJcmR1radncvs+Ui3xm9KoIOYcuoGHWeHxviy5fPuZ4DEdY8/OLBE/zU/iP0haJ4lLU/b8iShE/V6A1H+fmB4zzU3sMfXTjNd0auuN5Zfa5c4v96/QX+80c+tZSLsvXMpYv82z97gVyhgu00+mAYpsXblyY4f20GSYL+3iS//NwjPHFiDwB7ehI8NNDH6cEJ3hocp25aeDWV7lSUf/KJx3nm0f10pyJ3PFZ7W5hPPnWUH747zOnBCYrVOp3xML/1Cx/i2fcN4PWoN/pd9LRH+de/8Rx/8q03OH1pgtfPj9ERD/HEqT08dXIPX/7uGUZnsg/88z//5lX+6vl3lsrvOuiGieM4fO2FsyhKY9Xu6Uf28eufeh/t8UaXdp9H5Z/8xGMc6e/k269e5NLoHGcuTeLxqCQiAd5/bBfxyJ3NETcrEXQIQKPL9kqzWIosM9CW5EoLORJV0+BydpEP9/W7cZj3rZFE3vx2Gq+icjDefpctQA6OszVXOqDxu368q48fTI7y3fFrd/y/LEkcSXTwXP8Bntmxl85AEG+Le63XiiRJ+FSVA/Ek//cHPsrvv/0qXx8abKlT/d2UjDpnF+eYK5foCIZcHVsQ1prtOEyUCnz+3ddcD9IPtCX5jROP8+He3YQ83nWv7CRLEn5V42iyg//lkafYEY7ypcF3ybhYocsBXpoY4ctXzvGZA8dYtvTSBvKLzz7MTz19Ap9HXbZk7BMn+vnWv/t1tJuqWu3sivOF//0zd10RU2T5lkpUe3qT/Pc//UEM08K2HRrPlIQiNxoNaqqybMlc23bYtyPF+4/twjAtHAdkWcLnUW8ppStJEooMpwZ6ObS7Y2kreeN7PZqCpir8j599GsuybzxONOjnsz/+CD/70ZPLNvg7sKuDf/0bz+EA/pv+/zMfO8U//vCxFSdwATyqckfvjaDfwwdP9PPo4R1LFa0at8uyhKYq+O6jyeBmsXV+EuGB2I694r5GicYWq++MXW36zadmmlxZhyaBrVau8igKhxLLNwWExunQ2nK1q261Jxbn4Y4e3pybJKfXgMbqz9N9e/iZ/Uc4GE8R0DyNQAM2bLBxO1mSSfoD/M6jT2E7Nt8YvkTZcDfPI10t887CDB8L7nN1XEFYazm9xh9fOM1kMe/quI939fLPT32Ahzt6UKWNNVmhyDKdwRD/3bFHCWke/uj8WyxUK66Nbzo2//7Mj3iuf4CIx+vauKvB59XwrdCY7nrn8duTnlVFJhpqblZeUWT8itxSEzxZkgjcR66DJEmoikQosPxzfvsYstxoyrfSMamKvOxYd7vPvWiqcksAt1WJoEMAYKmi9Yr/fzDRjldRgeZKkeqWyVA+i2FZy9a7Xi2XsotUrdZWOg4nl8/ngPdKtm5liiTzvu4+Xp4aZaKY4xN7DvLJPYfYEYk2tk6xeQKN20mSREjz8NuPfoisXuP7E8MtNY9cSaZW5fTcFB/bJYIOYfMyLIt3Fqb5ypXzrk6xPN3Xz2+eej9Hkx3IkrwhtxhdP0f80qGTOI7DH50/zWLNvcBjrlLiC+dP85un3u/amIKwWYigQwAaF9N3e3M5FE/hayFocGg0UBvOZzkQT7Z8fM2oGAZj+WxLF5M+ReHwCknk28nhRAf/5omP4VVU4j7/je0PmzXYuJkkSUQ9Xv7nR55grJDjUmbBtQurYl3nfHqOUr1OyLM1qo0I24vjOCzWKvzbN19xNY/jgz07+R9OPM7xZOeGP49IkkRA1fjsoZNk9Cp/NviOa6W3bcfhCxdP85mB47QHgq6MKQibhajdJgCNE+HdLrzCHi+7onFUqfk/mYppcDW3dv06ruQWqbSQz6FKMv3ReMsd2LcSRZLoCUVI+gONDq/S1uqWKkkS/ZE4v3b0YVff+B0a21KG8mnXxhSEteI4DlXT5GtXL3IhM+/auMeSHfz60Uc41d69ac4jN1Y8Dp7kIzv2oLh43AVd5/Pv/GjFMvXCymRJwruUi7FMqoewwYmgQ7gvkiRxONHe0hapqmlwNbt2F2FXs60FHZqicCTVsWneFFfT9SBjKz8XkiTxif6DHE50oLlYO79Y1xnJP3glFEFYD1m9yp9dese18ToDIT578CQf7N656c4nkiSxIxLjJ/cd4XDCvRVwy3H42rWLzJSLro25XRzq7+SP/+Uv8O/+xafpaY+t9+EITRJBh3DfDic68MjNBx0Vw+BKbnHNZnUuZ9NUW0gQ9sgKRxOdq3BEwkalKQqfPXSChC/g2pglo85oQQQdwubiOA66ZfHN4UtMlQqujOmRFT659yAf2bnH9aaga+mD3Tt5omc3YReTv2umyVevXRCrHcK2snnPAsKaO5xox9vCSkfdtpgs5l0vUboc23G4lmutcpVXUTic7FiFoxI2sid7drE7Gndt+0SpXmeskBMXE8Kmk9OrfHHQnVUOCXhf9w5+fNcB4i4G9etBUxQ+sWeAk6ku15LfDdvi69cGqblYyEIQNjoRdAj3bWckRszrb+mkWzaMNdnnnq5WmK+UMZvspSEBCX+AvjVuYiisP1VW+Pju/YRcmsWs2xYL1UpLW/wEYb0Yts03hy8z4VKJ3LgvwNN9/RzdIhM5B+IpHunsIeb1uTKeA0yXCrw4MezKeIKwGYigQ7hvqixzMJFCbWGZvGzU1ySv40pukXILKyqarHA00bEhSzgKq++p3t1ENBe3TlgmmZp7jcUEYTU5jkPZqPOlS++6Mp4sSby/ewdP9Ozc1NuqbibROE/sb3OvCqNuWXzt2kWsLdxwVhButjXOBsKaOZLsQGslr8M0uJpb/aDjWjbdUsM3VZY5mhL5HNvVzkiMvkjUtS1WuimCDmHzsHF4Z2GGoXzGlfHa/UHe372D/ljClfE2iiOJDg4l2vGrrTWAu53p2Lw9P81CpezKeIKw0YmgQ2jKkURHSysdFcNgOJfBcrHu++0c4GouTcVsZaVD5sgW2QYgNE8CHu7oWWqA+eB0yySni6BD2Pgcx8G0bb527aIr40nAsVQnD7V3b7mVY0WWOdXeQ3cw7NqYNdPg1ekx18YThI1MBB1CUwbiqZZmeUzHZq5SJu1iZ9fbGZbFSD7bUhJ5QPNwILY2zQuFjWkgnsTTQqGE5YigQ9hMsrUqL7iUWxD2eDme7GTPFlvluO5EqpOecMS1gEq3LF6dHheFJ4RtQQQdQlPiPj994eiNDtXNKBt1rq3iFqupUp6MXsVu8uStSBL7YgmCooP0trYvlmxp6+ByTNt2rYOxIKwmB/je2BCFuu7KePtiCU52dLe0Ir4Z9EVi9Efj+FzaYmXYFmfmZyiuQXVHQVhvW/OsIKyqo8mOljqTl4w613Lu7BlezrVcpqUkckWSOSbyOba9vnDUtZUO23EwRClMYROwbJtvDF9yZSxZkuiPxV1Ntt5oJBqBVdznd2U8h0ap4ncXZlwZTxA2MhF0CE07luxsqSJJ2agztKpBR5pyvfmgQ5VljidF0LHd+VWNiMfryrYJy3Go2yLoEDa+TK3KmYVpV8aKeX3sb0uS8gddGW+j2tfmXtABULcszi7MujaeIGxUIugQmtaoYNVCMrlpMFrIUrfc33biOA7D+QylFpLIPaIpoLAk6Q+2tHXwdo2VDlEGU9j4Xp+doO7SqtyOcIyDbSlXxtrI+iNtrvXrgEbQcSm76Np4grBRiaBDaNquFk+4tuOQqVWZLhddP6ayYTBZLKA3uY9eAjoCIbpcrEYibF5Rj9e9oEOsdAibwMtT7lVO6g6G2R1tc228jSruD9Dm9btWYtuwLYZyadeCP0HYqETQITTNoygcTLS3dHFWMnSGV2GL1VgxS75eo9n6H7IkcSzV6cqFprD5eRUVyYUNVg5O0wUNBGGt1S2LN2YnXBnLIyt0hyJ0BEOujLeRKZJMRzBMwKVkcodGBbHpcsGV8QRhoxJBh9CS48nOlmZ5ivW6aw2objaUy1BsofqKLMmcSHW5fjzC5uRVFbZccwFBWMFoIctkMe/KWAl/gJ2RmGsV4Da6rmCIgOZexcO6ZXE1u/oNdAVhPYmgQ2jJ0WQncosVrIbzWddrkg/lMxRbSCJXJInjonKVsESVFBFzCNvG67OTuJV5lPAH6A1HXBpt40v6g/hVd5qJAtRti7FCzrXxBGEjEkGH0JJDiXZ8LXRvrpkGk8U8ZcNw7Vgs22Ykn22pXG7E42VPdGs2sRIEQbib84uzrk0AtXl9dAa2T25cxOPF4+KqjmXbzFVKro0nCBuRCDqEliT9AfpamNVq1CSvMVF0b0Ynq1eZq5SaLlEqAQfiKQKaO/tyBUEQNpPBzELTeXAriXn9dAS2fj7HdVGPD08LE28rMR2bhUrZtfEEYSMSQYfQsuOpLuQWNqMU6zojhaxrxzGSz1LQW8nnkDgp8jkEQdiGykadcZe286iSTJvXR9TFMrIbXcjjaal0/EpM22a+KlY6hK1NBB1Cy46nOmml6FOxrjOcdy/oGM5nKNRrTd9PkiROtIugQxCE7We8mKdsurPN1a+qxHx+VBcvwjc6r6K01CR3JdZSSXlDlM0VtrDtc4YQXHc81dVSqdmioTOSz7pWUnQ4n6XQQuUqj6xwRDQFFARhG7qcWXAtn8Ovaa42y9sMNFlxvdR6zTQpGs2/lwnCZiGCDqFluyIxYl5/0/fTLYvZSpFcrfrAx6BbJuPFXEtJ5L3hKCl/8IGPQRAEYbO5mktju5TQEVA1op7tFXSosux60GE7DqUW3ssEYbNwLwtK2HZ8qsbBeIqFqeaT3/J6jbFijrg/8EDHMFcpsVitYLUwY3dCNAXcNGzHwbRt6pZJ3baoWzambWHaduPDse/43Lr99hW/tm58fnZxFtN2q4ioIGxck8UCjktp5MV6nRcmh5kuF10ZbzOoGHWmSu4287NxRFdyYUsTQYfwQE6kuvjB1GjT9yvojS1WJ9u7H+jxG0nkLeRzAKce8LGFB+M4DpbjkNNr5PUaZaNOyajf8m/FNBqBhmU1PmzrxufGLUHEewGIdV+Bxs1f33xf0UVc2B7mKiXXtlelaxW+OXyZb3LZlfG2K8dx0C1zvQ9DEFaNCDqEB3KivQsJmp4vy9drrlSwGs1nybeQzwFwQgQda8aybRarFWYqRTLVCplalXSt8W9Or1HQa5RNoxFoGPUbn1dNk7plYtq2a6U9BUGA+UpJvKY2GAfQTbHSIWxdIugQHsiRZAearDTdI6Nk1Jko5DAsC01pvcHSaKG1lY42n5+dkVjLjyvcXdmoM1HMM10qMFUqMFUuMFcus1AtkdNrN1Y3inVdXPgIwhqrWxZZ/cFz6gR32Y5D3RYrHcLWJYIO4YEkfAF6w1GG85mm7mfaNgvVCgvVMt2h5psMApTqOtPlIlWz+ZN0qx3VheXZjsNsuci1XIaruUWGchlmykUWqmXmK2XS1QqmI3IlBGEjyOk1kTuwATk41C1xnhS2LnHVJTwQWZI4nupsOuiAxhvfWCHXctAxWSqQrlZoZePNyVRXC20NhZs5wEypwLsLs5xfnGOkkG2sajzA70UQhNU3Xym5VrJccJGD+L0IW5oIOoQHdiLVxdeuXWz6fnm9xmghx/u6d7T0uGOFHPkWmgICD5zAvp0V9BoX0/O8NT/NxfQ813JpJop5Ki41GhMEYXXl9JqYEhAEYc2JoEN4IBJwssWu3rl6jbEHSCYfLWTJtZDPockyhxPtLT/udrVYLfP6zCSvTI1yKbvAaCFHTq+JmTlB2GSqpkHz5T8EQRAejAg6hAe2K9JG1ONtuopUeanOedU08KtaU/e1HYexYo58C0HHrkgbbb7mmxpuV3OVEq9OjfHy1CjnFueYKOapibKOgrBp6ZaJmCsQBGGtiaBDeCCSJOFXNQ7EU7wxO9nUfW3HYbFWYaZcpD8ab+q+2VqV+XIJvYVkyBOpLmRJQhKNAe+qbNT50fQ43xq5zJn5GabKBZF8KghbQCvnTUEQhAclgg7hgcmSxIlUV9NBB0CuVmO8kGs66Jgo5snUWiv5eLK9G1mkka/IdmwuZRb5+tAgL02OMJLPipUNQdhC6pYpNlcJgrDmRNAhPDBJguOpzpbum9OrjBXzTd9vrJAj28LWKoDj7Z1ilWMFxbrO98aH+OrVC5xbnCUvEk4FYctpTCKIV7YgCGtLBB3CA5OROJroRJakppOKs3pjpaNZ48UcuRaaWyX9AXpDUbHOsYzpUoG/unqBr127yEQxh2GLevGCsBXVLUuEHIIgrDkRdAiuSPgD9IWjjDUZQNRMg9lykbxeI+r13dd9DNtiopSnoDeXuA5wONGOT1HESsdNHOBCeo4/vXCG5yeGSFcrW/KCRAI8soJXVfEqKj5Vxac0PveqCj5F5dziHIUmCyIIgiAIgnBvIugQHpgkSaiyzNFkR9NBhwOka1WmS4X7DjrmKmUWKuWWOlwfT3YhS3LT99uqHMfhnYVZ/vO5N/nB5Aglo77eh7QsWZIIaR7iPj8xr4+wx0dA1QhoGkFVw6958N8URDQCCg2fqjS+VlQ8ioIiyyiShCxJyNJ7nytLX/+zF/6WwfSCaGwobGkeRRGrvYIgrDkRdAiuUJY6k39z+HLT983WKkwU8xy8z94ZE8Uc2RaTyI+nOlHEKgfQCDjOLMzwH999g5enRte9uZ8qyXSGwuwIR+kKhukOhukMhukIhIh5ffhUFU1WUGUZVZJvBBCKJKPI7wUS7wURt31w74plXkVtLImImEPYwnyKCiLsEARhjYmgQ3CFLEscTbbWJDCjVxlvIpl8vJAj00I+h0dWOBhvRxZBBwDnFuf4j+++wQ8mR6iucXUqCYh6fRxLdnIo0c7eWLzR78Xru7Eq4VFUvIqCR26sUIjfmyC4w6uoroYce6JxnujZhSqLVeQHEfF46QtH1/swBGHViKBDcIWMxN5onKCmUTaamzHP1WpMlPLYjnNfF5bjLZbL3deWIOzxNH2/rWi8kOMrV87z0uTImpbD3d+W5MmeXTzU0c2eaIKQx4Nf1fCrS9ufxNY3QVh1PtXdt/7+aJxfOXKKiMfr6rjbjYxEUBPvUcLWJYIOwRWNJoEqA/EUp+emm7pv3baYr5RIVyukAsG7fm/FNJguFym1kOx7NNmJKosk8pxe4+9Gr/D1ocE1CTiS/iDP7T7AMzv72R2JE9I8BDQNj/hdCMK68Coqbr70ZEkioHqI+wLuDSoIwpYjgg7BNYosczTR2XTQAZCuVpkqFe4ZdEyXCi1XVzqW7Nz2y/+mbfPazDh/evEM+XprfU7u195YnJ/ef5SP7txLwucnqHnQZGVVH1MQhHtrrHS4F3UYtoUuGogKgnAPIugQXKNKjQpWrcgsJZOfaL97XshkMU+mVmnpMY6lOlDl7T2zPpzP8DfXBpkqFVbtMRI+P7986BSf3neIhC9AQNUAxKqGIGwQca8fN6dfTNsWQYcgCPckgg7BNYosc6zFzuTpWoXJ0r2TySdKedLV5oOOjkCQzmAYaRtXbCkbdV6bmeCFyeFVK870od7d/IuHPsieWLwRbEjb+RkXhI2pPRhydRKgbltUTRF0CIJwdyLoEFwjAQlfgJ5QpOmZ9JxeY6pUwLQt1LtswZksFlpKIj+c6MC7zXMIrmQX+asr56mtwsWBKsv802OP8QsHj9MeCN5XeVpBENZHm9ePX9Vc68tTNQ0Kq7xdUxCEzW97b3AXXCVJEpqicCTR/BYr23FYqJaZq5RW/J5srcpsudhS8vOxVAeqsn3zCUp1nTPzM5xLz7k+tkdW+J1HnuRXjzxEZyCEIski4BCEDUyWJDoCQddWISuGQa7F3kmCIGwfIugQXKXJred1LFYrTBZXXiGZKhVYbGFrFcCRRCfaNk4inygV+P7EMLbj7sYqWZL47Uee5Kf3HyXm9W36YEP0BBS2i65Q2LXXa8U0yOpipUMQhLvbvldhwqpQZZmjyRbzOqoVJu+yLWuylCfdQhK5V1E40JZE3aY9IAzL4mpukddmJlwf+5cOnuS5PQNEPN5NH3AA6KaB43JgJggbUVcg4vJKR00E7YIg3NX2vAoTVo0qyexrS9yoWNSMxkpHftmLPsdxmCwWWGhhpeNgPEVAa/54tor5aokfTo1j2Jar4z7W2ccvHjxBuz+4JQIOgJpliQsnYVvYEY66VlijWNeZr5ZEwC4Iwl2JoENwlSRJ+BSVA23Jpu9bNHRmVsjZsB2HqVKBbAsrHYcTHdu2EZ3jOKSrVd5dnHV1XL+q8suHTrIjEt0yz6vjONRF2U9hmziYaEd26bVrOjaL1UrL5cwFQdgeRNAhuE5TFA63nNdRZnqZLVbz1RLz1RJWCzNpR5IdeLZpErntOMxXSlzNpl0d99md+zma7MCrbJ0CeGXTaOnvSxA2o8OJdhQX89yyepXpUtG18QRB2Hq2zhWDsGF4ZIUjifaW7rtQrTBVKrInlrjl9ulSsaUkchmJQ/H2bdsJO1+vcT497+rWKq+i8JGde+gMhl0bcyOYr5SwbHu9D0MQ1kSbz09PKMK1nDsTEtlalZlyseVeTULrLMfGsE3qtoXl2DcKhkg0in0okowmq3hkBXmF3MaiUaVuW6xcTkMi7tk6W2kfhO3Y1CwD3TKRJPArHjyyKp6b+yCCDsF1miLfWLpvtlrSQrW8bI+PyVKBhUq56WPpCoVJBYKuzuhtJsV6nSGXLiquO9Xew55YYsutHs2WSpiOCDqE7eNoooOhXNqVPKb5SpnRQhbHccTF1xpxHAfdNhkpzfPqwhXeyowwXl4kX69gOw5+VSPmCbIzmOSxxF6e7jxEuy+67Fj/8uxXeXXhCoaz/ASVT9F45aP/x2r+OJvGQq3Il8df4xuTbxNQvXyu/wk+3n0Cn7J9c0fvlwg6BNcpkky7P0hnIMR0ubnl9kytwnS5gO04N/YbO47DdIvlco8k2vFusYvjZlRNg6lyc40a7+Whjm5S/oCrY24E0+WCWOkQtpWjyQ6+PjzoSgJ4plZlOJ+lYhoENY8LRyfcS8Wq8w8z5/iT4R8wUblzcqlumOSNKmPlRVRJ4ZFE/4pBR1D1Etb86LaB7TjYjo1hW9iitMYdrhZn+eHCFTL1Epl6iTfSQ5xo28XuUGq9D23DE0GHsCo8isrhREfTQUfVNJkrlyjoOjGfDwDdspgtl1rqeHs4sbXyDprhOA4V03B1n7UmywzEU0S9PtfG3ChGClkMEXQI28iJ9q6WVqSX49Ao9jGSz3KkxZw+4f5Zjs1b6WG+NPoqE5U0EhBQvIQ1Hz7FgyRJWI6NaVsYtsmRWC9J78pbYj/V9zDH23aSNyoU6lUKRpUz2TEmKmkcEXjcwquoBFUviiSjSBIh1YdH3p7XGc0Sz5KwKryKwuFEiu+OX2v6vvPVMtPlwo2gY7ZcZK5Saum0dzCR2r5BB1A26szfpct7s7qDEdr9wS2XI+M4DoOZ+aU9zYKwPRxLdpLwBZhz6RwxVSpwNZfmcKJdbLFaZbl6hTPZUYZL8wC0eYI8232cT/Q8xI5gEo+iULdNsnqZ8XKa3kCcsOZfcbxT8d2ciu++5bbfvfgtvjL++opbrrar/ZEunu0+jiIpxDwBPtp1hC7/8itIwq2259WYsOq8isLBeIvJ5JUyM+Uih5aS0afLBRaqzb8phjQP/ZH4tu1Ebto2eb3makWmrmB4S26dKJt1RvJZTLHSIWwjmqLwZM8uvnL1vCvjTZcKDGbm+fiu/fhUcXmxmuZqeYaLjYBDAt6X2sfP7/oAXf7Yje/xyhqd/hidN90mPLioFuCndjzGT+14bL0PZdPZnldjwqrTZIX+aLylJoEL1dItZXOny0XmW0giP9CWJKBp23bGzXJsqqa7fSfag8Et2Wjx4uI8JaO+3ochCGvu6R39ro1Vs0wuZRZdq4glrKxoVFnUG1tnPbLGzkCSTjHbLmxwIugQVoUkSYQ8HvbG4k3fN1OrMlspYdo2lmMz02K53EOJ9m0922Y5DlXTcHXMqMe3JbervTI9RsVw97kShM3gsc4+wh73Vi+v5dK8uzDrSp6IsDLDNqlZjYkSv6oRUL2udZgXhNUigg5h1XgVlYMt9OswbJu5col0rUKpXme2UqLSwsXzwXj7ti5hZ9s2ussdtr2KirLFVo5qpsHrM5OuB2iCsBnEvD4e7uh1bbyZUpF3F2ZItzBRJNwfx3EwHRtjqcS3jLxi/w1B2Ei23pSlsGH4VJWD8dZKyM1VSsyWi3gVtaUkR01W2NeW2Nblch1wPUfBoygoW+zN7Xx6nvFiTnQjF7YlSZJ4bvcBXpwYcaVKkY3DmYUZ3pid5OO7998ofS60pmYZzNcK1G2Dum1Rt010y2AwP03NakyUGI7FWHmB1xeXL9yS9IbpCcTXfRLuel+RXL1M3qhQMeuYjoWEhCYrBFUvbZ4QUc2P2kKxEsdxyBsVsvXKUrNDE9txUGUZr6wR9fhJeML41ftf2SsslRyumPqK39Plb6PbH2vqmC8VpinUqzg4HIn1EViqOFY2dRb1Ivl6BcM2sZaO36doRLUASW+k6d0Ghm01nhe9TNnSMZael/u1aW8DAAAgAElEQVRxINJNzONeiXwRdAirxquo7I8lUSQZq8mma/OVMjPlEj5Faan6Uk8oQtIf2LZNAaFxMeF2lSnbcbZU+UTTtvnW8GXyLZRjFoStQAI+1NdPdyi8bGPWVgznMvxwZpxHOntoD4RcGXO7mqpk+MOhF1jUS+TrZXJGhaJRo26/t4pdNKr85dhr/OXYa8uO8RM9p/jVPR+iL5hYq8O+g2GbzNXynMtN8nZ6hEuFaWZqOcqmjixJRDQ/vYEEx2M7OBXfxUCkm5gneN9Ba9GoMVKa5430EOdyEwyV5sjXK+i2SUD1kPSGORDu4pHEHo7G+tgVSt3XBNq14iy/O/gtLhVmVvyez/U/ya/seYpQE++3f3Dlu7y+eA3TsfnDx36NI7E+psoZ3kgP8UZ6iMuFafJGhZrZOP52X4SBSDfvbz/A8diOWwoGrMReCsIu5qd4Kz3M2dw4U5UMeaOKYZv39U7++Yc/x/tS++7757oXEXQIq0aVZTqDYdoDQWaa7NcxX72+0qEwV24+6DgYT+FvIYl9K5ElyfWVnrplbakVgfFijldFPoewjUmSRNTr5RP9A/yHs2+4Mqbp2LwxO8HrM708u3v/liuxvZbyRpW30iO3BBkeWUWWJHTLxMFBWrpNW6FXhE/R1nXFqWYZDOan+PrkaX4wP0jeqC77PfO1Am9nRvje7Dme6znFs93H6fLH7hkcpPUi35+7wFfGXmektHBLQ0OJRkDSCEoWeH72Ao8l9/Dzuz7AqfiuFZ+z6/yKh95AgopVx7AtDNtCtwyqVh2zycnUlYxXFpEliS+N/pAX5wYxl0oUSzR2LBTNGsVSjaHSPC/OD/KJ3of4xV0fuGtVMsdxSOtF/m7mXb42/ibjlTQyEgHVS5sniESjuWTZ1G+ZFA4oHiKan4Dqxa94CGvu9uQSQYewqvyqyoF4sumgI6fXuJpLo8oymdqdJ6h7ORhPtVQ5aytRJMn1pO+yUcewtkbNdsO2+Pq1QWbLrfWAEYStQpFkntszwJ9deodi3Z0qbkO5DN8dH+JQooM9LRQUERpS3jCf6nsY67ZeGRPlDG+mhyiaNbyKxvHYDgai3cuOcTDSQ1Bdn4auddvkYn6KPx5+iR8tXAVpabuXv42oJ4BXVrFxKJs6c9U8M7UcE5UMXxx5hbJZ42d2Pk6nL7ZiFcqCUeVvJk7zpdFXyRkVPLLKjkCClC9CQPGgyDK61djSNV5Jk62X+eHCVeZqBf75wLM8mth714CsJxDnZ3c+znytQNnUqVg6E0srEst1gW/F25lRvj31Lu9kRwmpPnYEk7R5gngVFdO2ydXLjFUWSeslyqbO306eJqBo/NreZ1YM6Mumzkvzg3xp5FUW9CJh1cf+SBeHoz10+mPISMzrRS7lp7iQnyJvNHKwegMJnuk8zL5wJwlviN2h1lofrEQEHcKq8qsaA20pXpwYaep+tuPwytQYEjTdsE0CBuKpbV25ChoXEm731EjXKtRcTk5fL5cyC/z92NWWOt0LwlYiSxL9kTjv79rJ349ddWVMy3F4dXqMQ4l2UoHjRDxeV8bdbvqCCX5j/0fvuP2luUEuF2YomjUCipenOg7xszsfX4cjXJnjOExXsvz1xJu8unAFTVbYG+rkI11HeDyxl75ggoDiwXJs0vUS57Lj/P3MuRvB1DenztATiPPx7hME1Tv/fmzH5oW5i/zl+GvkjAph1ceT7QM803mEQ9EeEt4QEhI122CstMAPFi7z7al3mKikGSnN84Whl9gRTNLtb1vxZ4ho/juaJg7mp5ir5V0LOr4/e4GqVWdHMMmPdR3jyfYD7A6145M1TMdmopzmhfmLfG38TWZqOUqmzvOzF/lY13H2hDuWHXOsvMg/zJxjQS/ilVUeSfTzuT1PMRDpvrFy5DgOI+UF/nT4ZZ6fvUDF0rEci2OxHTyc6F+V1bHtfVUmrDq/qjIQT7Z039FCtqX7xbw+esMRPNt8SV+VZaJeH5osY7iUUD5XKVHeAluRinWdv7h8jvFiXqxyCAKNIhE/s/8IL0+NtlQtcDmL1QrfGb3C3licJ3t24dmC5baFlVWsOqczI7w4dxGAHYEkn+3/IE93HL5lhl6VFDp8UTq6jtITiKPbJq8tXiVTL/Pi3CBHY30ciNy5ijNdyfLX42+Q1UtIwEe6jvJP9z1D3BO6ZWXEr3gYiPbQH+6gTQvy+5e+jW6bXCnO8r2Z8/xS/xOr/lzcTcWqE9MCfK7/ST7efeKW50aTFPrD7XQFYkgO/MHV7+IAeaPCm+nhZYMO07YYKy9yMT8FNBLdn+k8wuHorVXqJEmiP9TOR7uOMlSa42J+ipHSAiPleY7G+ppKuL9f2zfLVlgTHkVlV6SN4BpuddrXliSkebdtU8DrZEkioGrEvH7Xxpws5snr1U1dg9+0bZ4fH+bFiWHKoiGgIACN7ZiPdvbyRM9OV8c9uzDLV66cZzCzgOVyNT1hY5ur5Xl5/jJVq45f8fBwop8nUgfumuNzINLFQ/FdRLTG+9a53ATj5fSyfzsvzl9iqprFxqHdF+Vndj7eyFdY4b1fkxSe7jzMrlCjqmbZ1Hll4fKNKmDr6foKzUrPjU/WeKbzCFGtUUmqZhmMlheW/d6qVWe2lqe61Melyx9bcUUEYG+4gy5fIz/EprE6VTJXZweACDqEVSVLElGPj13RlZcv3TYQT27Jrtmt8Koq7YGga+Pl9Brjxdym7mnx7sIMXxw8w2wLBQoEYauSJImA5uGXDp2kzcWJCstxeGlylL+4fI6xQg5nE09YCPfPdhzmawXO5ccBSHpDHIx0E1hmm9TNZEmmL5Ag4W1UPSuZNaarWSrWrSVrTdvirfQQRaNxcXy8bSft3vBd+5VIkoRP0TgU6QHAcmwWagXmqrmWf043SEg8230c712S2iVJIqT56Ak08qMsxyZXX74XTt22KN8UNPgVD+G75PSEVR8+5b1VjbKpYzS5rf1+ibVOYdUFNI39bUkupOfX5PEOtIkk8usCqkZvKOrac+8AZ+ZneKq33/V8kbUwnM/wJxfPcDE971rlEUHYKlRZ5niqi2d37ePPL591bdyqafCd0SuENA+/MHCcHZGY6N+xxdWXSuRevzDWbZNz+QnKd+l3cd1oeYGS8d73pfUSVcsgrL0XDGfqZeZq+RuVnnL1Ml+fPI1Xvvt7v+GYTFWzN31tMa8X2BlqraeYG6Ka/75K+MqSRGgpeLAdB91efvJPvq1cvuXYGM7KQYRhW7cUKlBlZdV2ioigQ1h1AVVjoK21vI5m+RSV/mgcn9g7DEBI89AfdbdyzFtzU0yW8vSGIpuqD8pYIcefXjzDS5Mjru1ZF4StJqBq/MyBo7w0Ncq0S307ADK1Kl+9egHLsfmFgePsirZtuUaj96NmGsyWS2u6+r8ealad+Vr+xtfztQJfHW+tJHPNqmPeNvM+W8tRu6mM8PX+Fs2yHfu+AqHV1OGLokn3d6H/XrDurLhq6Fc8pLwRVEnBdCyy9TKz1Rx9geX7tMxUc2Tq5Rtft/siyybuu2H7veKFNedXNfa1JVHWYGarNxwl4fNvqovh1RT2eNgbi+PmMz9RzPPazAQ5ffNUfRov5Pji4Dt8Y2hwUx23IKw1RZbZH0vyc/uPul6MI12r8NWrF/jD86c5vziHvkUq4d2P2XKR748P8Z/OvcmXXFxF2qjMZS7mFUlGbeHDgTsKfpRNHeumQERGamlsRZLXPUcxpHldXfnzyip9gQQ7l5pBjpfTvLZ4jUX9ztYF+XqFHy5eZbTUyA/p8EXYE+pYtaBDTAcLq06VZToCIVL+ILMtdBdvxv625Kbc9rNavIpKTyhCwh9gsbr8/s9mOcDfjVzhsc4+Huvq3dCNvxzH4VJ2gS9fPs83hgdJt9DzRRC2m4Cm8cm9B3l3cZbnx5ufPb6bnF7jb65dZL5S4if3HeYD3TuJetenh8RqK9XrDOXTDKYXOLs4yzsLM1zOLnI4sXJS75bh3BoodPiifCC1n3ZfpOmhDkS672hSd/ss/+PJfRyMdjf9fhRUvexex61V0NjOhItTg5IksTuU4sMdh5mt5ckZZb43ex7LsTka6yPuaeTL5I0Kl/LTPD93gQW9gE/R+FBHo0fHaq1CiqBDWHWNBCgPe2OJVQ86BkTQcQtJkkj6gxxNdvBCk71S7uZaLs1fX7tAXzjKjnB0Q1YKq1sWb89P8xeXz/L9iWHyYoVDEO6LLEl0ByN87tAphnMZRlosX76Simnw/PgQs+UiQ7kMH925l/5o25YoqVs1DYbzWS5lFricWeBydpEL6XkWq+VtVZ5bkWUCNyUnJ71hnu0+zkO39bxoVUD13nJhfKJtJz+3632rNkO/2SS8YT7SdYQFvcBLc4NMVjL81fgbvDJ/mfhS/5KcUWammqNs6kQ1Px9IHeC5npO0+6Krdlyb/xUubApBzcP+tiSvTI+t2mNISOxrSxAUlatukQoEeLijx9WgwwG+O3aNvlCUzx46ScLn31CBx3ylxIuTI/zNtUHOzE+LHA5BaJJHUTjZ3sUvHjzB751+hbLLryEHOJ+eZ7pc5OziLB/u6+fJnl10BcObanusA2RrFUbzOYbyaa7lMlzNprmSW2S6VMDaptW6vLJGwhu+8XXZrLFQcy9HKOWN4Lmp2tNkJX1H3sd2JksSu4Mpfmbn45i2xXdnz1Oz6oxX0owvNTX0KRoJT4iH4rs50baTD6YOsDOYRF3F158IOoQ1EVyqYLWakv4AXcHwht7usx7CmpdD8XaSvgCLNXe2WAEU6jp/eeUcHlXhZ/cfJeELrHvgUTUNLqTn+c7oFb47NsREMbdt3/QF4UGFNA8f372fwcw8f331IvYqzNVnalX+Yewag5kFXp+Z4JHOXh7u6KE/GsejbMxzeamuM1MuMlbMMZzLMpLPMFbMMV7IM1sputaMdTPzKipd/hhRzU/eqJLWSwwV5zBta2k70YNJecO0+6KMlhcwHZuzuQlKZo2ItrEmwNaT6Vik9SLpegmPrHA01sejiT34l1agvIpKzBOkLxCnN5BYk1UiEXQIa8KrquyMRAmo2qrNOu+NxQl7RFPA2ymyzM5IG4919fKtkSuujj1TLvLFi++Qr9X4zMAxdoRj6zJLWbcsrmQXeXFyhFemRrmQnqdQX9+KJIKw2UmSRHsgyGcPniRdq/LCxPCqPdZEMc9kMc8bs5MMxFMcTXZwKNHOQDxFbyi6qrOvd1O3LLJ6lZlSkclSgfFijqlintlKiZlykalSgYKur0pAtpkpkkynL8rhaC8/XLxKydQ5l5vgcmGGw7Heew9wDx5F5aH4bi7mJ8kZFSYraV6Zv8wn+x7Gp4jdDg4Ow6UF/nLsNd5MD3Mo2sNnd3+QRxJ71vX5EUGHsCYUSabN62dHOMql7OKqPMa+tiRhTeznXE5XMMxTvbt5cXLU9S7cM+Uif3H5LOPFHP9o9wBP9e0ivEYd4fN6jYvped6YneT0/DTnF+dIP8BqTtIXwHYcsnpVXEIIAqDJCgcTKX71yEMU6zpvzU2t2mM5wHS5yHS5yJuzk/Qs5YztjrTRH43TG47SG4rQFQrjcbGXgO041EyDrF4jV6uSrlWZr5SYrZSYr5RI16pkahUWKmXmq2WKdX3dKx5tBh2+KE+2D/BOdoyKVedSYYa/nngTn6LRH25HukvytO3YzNUKSEDcG7plK9V1H+44xAtzFyjkq5iOzZfHX6fNG+RDHYfQZGXF8R3HQbdNpioZ2n2RW/p/bBWGbXGlMMPbmVEsx2ZvqIOH4rvXPSATQYewZkIeL/vakqsWdOyPJQh5RBL5cvyqypFkByfbu3hlyv28mnxd5+/HrjGUz/Ly9Cgf7N7Jwx29dAZDrpYCdByHolFnKJfmYnqB8+k5LmUWGMlnyT1goJDyB/hnJ97HeDHPFwfPoFtif7DbLNumZpnUTHPpX+Omz01qlsFcpXzvge6TYdtcyS7y96NX8akqPkVt/Kuq+BTtvdsUFU1RRMO6FXgVlYfae/jVIw9RNuoMZhZW/TGLRp1LmQUuZRbwKSrtgSBxX4CEz0/CHyDhDxLz+m58BFUPqiyjKQqarKBIEpbjYNk2lmNj2jaGbVE1TSpmnbJhUDEMSoZOvq5T0GuUjTql67fpNXJ6jWK9jiUaibYkqHp5NLmXD+cm+M7MuxTNKi/OXaRgVHksuYeBSDdJbxivomE5NhVTJ1svM13NMlpaZKQ8z/uT+3m68/CyQUdfMMFP7niMhavfZa5WYLS8wH8ZeolLhRlOte1iRzBBSPUhSRK6ZVAwqizoBcbLaUZK81SsOr+658NbMuiwlkoWV63GJON0NcfF/BT7I10Eb0vCX0si6BDWTEjzsK9t+eY0DyqgauyIxERTwBVIksSOcIyP7dzHuYVZ8quw9ch2HK5kFxnJZ3h7bppdkTb2tyU50JZkTyxOTyhCm+/+T+6O41C3LTLVKlPlApPFPOOFHKOFHJOlPFOlIgvVkivBQUDV+G+OPMyn9x5ipJDlLy+fFUHHbSzbRrdMqrcFCVXzveChusLt1/+vbpkYlk3dtjBufNgY1tK/SxeFbqlbFj+cHudaLo0mK2g3Lkrl976WGxepmqLcFpTcFpyoKn5Fxbt0m/+WIEa78flWDVwCmsYTPbso1ut8/p0fMV7M3/tOLqlZJuPF/I3HlGj0fwpoGgFVI6B58MoKiiyhLPVekCUJ23GwcbAdB8uxsWwHw7bQLZO6ZaFb1tLftLFt8zCKRpVrxTnyRoWaZaBbJjXboGYZnM9P3gi4TNvmC8Mv4ZW1xmtC1vCqjc9T3ggHIl13jC1JEt3+GD+54zEqVp1X5i+TMyq8PH+JwcIUXb4YYc2HKivYjkPdNimbOrl6mbReomzq7A62rxj0yZLEhzsOkTcq/NeRV1nUC1wtzjJdzfL64jUSnhBeRUOSGsdfteoUl/JLMvUSKV9kxa7elmMzXyswVJpDtxrPh26b6JbBZCXNxFIyNsDZ3Dh/Pvojwpqv8bwoGj5ZxatoDES6iXtDLvymmqNJKilfmLgnRKZe4mJ+ks9f+Qc6fTG8inrLKpAqyfhVD0lvmH3hLg5Fe4iuUm6MuEIT1kxQ87A3mkDizkY/D6ovHCXuC2yqqidrLaR5eF/XDp7s3c3fDl9atccxbJuruTRXc2lem5kgFQiS8geIeX20+fzEvQHCHi9Bj4ZHVlBkGcdpLAfXLYu6ZVI06uRqVQp1nZJRJ6fXyOlVsku3uZkcrskKv3ToJJ/ee7ixGhdLEPcFKLq8DW0j0i2T4XyWiWKemmlQNd8LFq4HF9Wl23XrvSDBvClIMGwb07716/e+56avbWvNk/ptHNK1yn1tuZNo9BRSl4IR9abARL0pQGnc3gheVOm9IOb6998cuPiXgpH3/m0EKAl/gMOJdvzq5tp7HtI8/NjOveiWyR+ee4uxYm5djsOhUXZXVKV7cBOVDF8ceYWpaubG69h0Gq/dslm7katiOhZfGv0hqrT0GpAUVFnBK2scb9vB/3TouWXH12SVgUgXv7LnKbr9bXx/9gIztRwz1cbH3UQ0P22eIJq0cuJ5WPPxXM9J4p4g35g8zbvZccqmzqXC9F3HViSZdm+EoLL8lmzDNnk3O8afDr+M4ViYtoXpWJi2Tc02qJjvvT9cyE0xUlponC+WnhdVakxm/NbAx9cl6FBlmaOxPn6i5yRfn3qbXL3MudwE55i443tlJDRZIaj6aPdFOBzt5dN9D7Mv3OlK0v8tx+XqaIJwF9r1JoGBIPMubqEA2NeWICK2Vt2VJEnsiET5+O79nFucY9Tl2vvLKRo6xbzOcD4DXJ9RacwWe2Tlxoykg4PlONiOjWk7jdk206S+yiUQFUniMwPH+PmB4yQDAWRJIqB5OJRsZ7KU3/KVrwp1nW8OX+K7Y9dubD9pBAiNz82bPt/qz4UDNwKkB2khqUjSLcGJuvT5zV8fjKf4nUef2nRBhyRJxLw+nusfQJYk/uj86RuvbWFzKps6Q6U5Jiv3/j1m63e+b6uSTNwTvOv9vIrGQLib5K4wJ9t2cS4/wWB+islK5sYKi4xEQPUQ94bo8cfZE+7gQLiTI7G+e+YhtHmCPNN5hF3BFBfyk5zNjXOtOMeCXqRi6pi2hUdWiXr8dPii7AylOBDuYiDSTWqFZoW245Cpl7lcnLnn86LbBnp9+QC4YKxPQ9pcvcK53ATDpXlq1t0n0GwaOS56vbECNF5eJFcv89/ue4b+ULurKx4i6BDWjCRJRLxe+qNx14OOvbEEYY9IIr8Xr6LyWGcvn957iD88/ybF+trO5puOTdGob4hVBFmS+Kl9R/ilgyfpDUVu2eP6aEcvz48NYTlbe4uVYVlMlgpcXqU8q+3Ichwsy4S7/Ol4FYW65d42srUkSRJtS4GHX9X4woXTnFucW+/D2nYOR3v5ncOfoGrV8cgqu1rsqr033MFvH/4EVbO1c7IsSbTdI+iARhXFDn+UuDfE0bY+0nqRglFDtwxMx0Jamm33KR7Cmo82T5Co5kdbJpdjOT5F43Csl92hdh5P7iVbL1M26xi2iY2DIsn4ZJWA6iXmCdDmCd21RKxHVvn/2Xvv8Dyu+97zc6a+Db0ThWgE2EWRlEiJlCWquchSHJdI7pYd35td+zrJOptbnmRvbm422Zs8u6mOU+zETmzHTbIs23LUeyFFSmLvHQRBgCDq26acs3/MoJEAAYJg1Xwe6QHx4rxzzsw775nzPb92W2U71RdZKG9Zcf2kr3+h5Q4+XH8TUilK7RRJY/pN06Rh88XWDXy4/iY0IUYri5/NicwZHjm2iRe799CTG6QmVsxNZc3UJkqJ69YEF1CpFDnfpdcZZnv/MfYMdJLxHV47vZ8bSxupjBWdUw3+YohER8RlpcCyaS0u5Y2T55r4ZosAWopKSUWZq2ZEaSzBB5vbOT40wKMHdr4rs7DoQvCxtqU8vGQVTUUl57jlra6qRdcEvDvdvCMizosQgiI7xr3zWymwLL69821e6zwWpY29jJTHCiiPFUzfcBpKrCS3lC+YgxHNDFPTKbcLKLcvfuyTkTAsGoxyGpIXVxfM0HTqE2XUJy5NHOoNJfMv+D2WZkz7vj4nzTNdO/hpxxYG3SyrSpv4VNN6WguqSJkxDKFPyOmlAF/5ZH2XU9klfOPg87zWs4+s77Ct/xjrK9oj0RFx7VIQxnXMJVWJFJWJFGYUzzEjNCGYX1jMg+3L6Mmmeanj8LtqqWBoGg+2LeOzi1fSUlw6af7/BSVllNoJTnhzV0E3IuJ6QhBsIt1W20iJHac6meKJw/uiOIuIiCvIyWwfL5zaRb+boTpWxB1Vi7i5vGXS7F9jmCSNGKVWiqVFdWzvP06fk6Y7Nzia/WquiERHxGUlbprMLywhphvk5si9oLm4lGI7FhUFvABMTWd5eRVfWLoKVwYZft4NJAyTTy1awUPty5lfWDxlwbG4YbK8opqT6aFo9zYi4jzEDZMVFTWUxRM0FBTzw33b6RiOxHpExJWg38lwcLgbCOqbNKUqpxEcY2hCYOnmqKuxhjhvLZXZEImOiMuKLjRKYjHqC4rY3987/RtmQGtRGYVRPMcFEzNMbq6uC9JKSsUbXXPn8nY1Uh5L8PDSVXyoZRE1yYJpM53dVF3H00cPvCvdzyIiLgRT12ksLOFTi1awoKSM7+7Zyhudx/Gi+hYREZcVP0w9DCAQF5TC2wkLJg6Fwe8ldhJrjssQRP4oEZedQitGS3HpnB2vpbiUQmvufA7fTcQNk7U19fzWylu5u6EF4woVDLrULCwp57/cfDsfb1/OvFThjFIr31xVe93WXIiImGs0ISiLJ9hQ38zv3byB//2GNdSlJs8M9G7H0q/PeTbiyhPTDYrNILD/VG6APYMnkTMQ/670efrkdjb3HiIfipZFRXUzShJwIUSWjojLTqFtz5noSBom9QVFJMxrK/Xk1UTcMFlZNY+v2uspjyf42aG9pK+C7FJzgalp3NXQwmcW38iKihoShjljN7y2knKKY3G6M8OXeJQREdcPccOkrbSMquQqVlXX8si+HbzQcZjBS1CQ9FqjsbCY+5sXcl9T+5UeSsR1SrldyPKSep7t2skZZ5ifdWwB4K6qJVTHiydspCml6HPS7B3s5MXuPbxx+gAns0Eq/cWFtdxYPJ/UeTJ8zYZIdERcdgotm5aiuREdDYXFlMTi0Y70RWLrBm0l5fzmjbfSVlLOd3dv5eA1nn+/LlXIJxbewAea2qhNFWHpF1bkyDYMbqyo5smjBy7RCCMirk90oVEai3NrTQMLS8q5t3EBP9q3nU1dJ8i+ywLNTU3j5up6HmhZyOqqWspjCQrtyDIfcWmojZfwvpob2DPQyYlsH0fSp/nWwRf56fHNlNhJCs0EutBwpMugk2XIy5Hx8gy6WbK+i0IxP1nOJ5vW01ZYgzbH3g+R6Ii47FiaTlUiRXk8wens9JWCz0dLGEQecfEYmkZNsoAH25axpKyK7+x+h+eOH7rmrB5J0+SehlYeWricJWVVpExr1qL05uo6njp6IAolj4iYBZYezPX3NLSyqnIeb3V38uj+nWzs6mD4GptXLgQNWFRWyZ0NzWyoa6YmWUCxHSduGFHCk4hLiqnprClv5TcXvp9/PfwyO/o76Hcz9LsZjqZPB0HiApQCqeSERCkJ3WJdRTsfabiJJUV1xKcpyjgbItERcdkJqtrGaSwsuWjR0VxUSlEUzzFnCCFIWTarqubRUlzK+5va+N6erWw+dYKcd3UXM4sbBrfUNPBQ+3JurJxHSSyGqV2YdeNs1tQ0IAgqpkdERFw4QghihkFNsoB7GlpZU13P3r4enjxygKeOHuBUZui6+HbpQrCwpIJb5tWzob6ZxsISCu0YScNEEyISGxGXBSEECd1ifUUbCwqq2N5/nE29B9k/2MWp/CBpL4dUCkszSBoJyu0C6hNlLC6qZW33m38AACAASURBVEXJfGoTpRSacQyhXZJ7NhIdEVeEQsumuaiEzadOzPoYmhA0FZZQaEeZq+YaU9MpjyW4u6GFm6pq2djVwU8P7OKNruOXvYr5dFTEk9xR18QHmxeypKySItvG1PQ5mTDbS8optmOcyWfnYKQREe9ehBDYhkGFYVAci7GsvJqHl67kza4TPHV0P5u6Oq65uI9iO8YNFdXcOm8+a2vqqU6kSJgWccO4ZIu2iIjpEEJg6yZ1iTKqYkWsr2jHVT6+HLNsiLCdLjQMoWNpBrZuBGlyL+F9G4mOiCtCkR2j+SLjOqoTKSoSyes249KVJpi4DCriSd47v5Xbahs5NtjPM8cO8vTR/RzoP4Mj/SsytrJYgtVVtdzZ0MzqqloqE6lL8qA3NY0bq+bx7LGDc3bMiIh3O6amU2TrFFg2tclC3tu4gDO5DFtOdfJq5xE2nTxBV2YI/ypKVy2AykSKpWVVrKis5sbKeTQVlpCyLGzdwNL0yKIRcVWhheLDvgRuUrNFqPN/qa+eb3zEeXGlT8Z18eTs8qLrmkbSNC/aHWWmSKXI+x4Zd/ZBhbomSBoW5gUGCF8MSinyvn9RcQ6WrhM3zCkL013N+Eri+D6O79MxPMimruO81nmMHae7OXWJFgm6EJTHkywurWBZeTWrqubRXlpBgWlh6QaGpl2yRAJKKYZdB8e/MHGlhS4lcePqmewnw1eSrOuSv8Dzi7g4DE0jZVozSt38bkEqhSclrvRxpc+xoQG2dp9ke+8p9vT2sL+/97JVO08YJrWpQlqKy2gvKWNBSTkLisuoiCexdB1T0zA0HT0SGRERkzHllyISHREREbNiZJHgSYmvJGdyWfb1neZgfy+d6SG60sOcygxzJpch4wUL27zn4UofTQh0TcPUdGK6QYFlUWDZFNtxKuIJqhIp5qUKaSosoaGwiNJYkHFD1wJzcPSwj4i4vpFK4Ydzix/ONSfTQxwZ7OP44AAnM0N0Z9L0ZNIMODmGHIdhN0/e9/GkP7oBZ2j6qFAwNZ2EYVJoB3NNiR2jOBajLJagJlnAvFQRtalCSu1YICq0oLiaLgSa0EZdUiIiIs5LJDoiIt4tKJXFyf6S4YH/fN52uj6PWOo3iCU+Pkf9qqC6OQqlQI37OdZm4nvGP78FAiFCX9PQr1QI0BAgxBSzmMLJv0Ru+Ov43iFM6zZiqS9imAtnfR6eu4fB3k+g1NCUbYSIYcd/hWTRH826H+l3kxn+S/KZH563nWEuI1n0PzDMZbPuKyLiWkepYCYJfirkyNwS/Dc6z0y2pDlbJ4yfaxj997j5hkhcRERcBFN+eaKYjoiI6xCFD+r8wc9KZUHNXUYqEe4IXj5nN/C9DpzM47j5VwFFPvtjNKMF3WhEiNlmNZOgcue9foGgulhXDwXKnfZzCsYyO7fJiIjrBTGy8RCJgYiIa5ZIdEREnEVg/ZME+2cCIS7nMnou0NH0Wkz7dpQ8g5RnUHIQpRzAA64f/30lB5GynzGjrI9SfSiVmbXoEKIQ074d6Z9Ayj6UPINSeYJrN4dpg0UM3ViEad0afkZnUCodihmXyNAcEREREXE9EYmOiIhzyOM6b+K729G0euzE/Vd6QBeEEBaWfSuWfevoa0p5SP8I2eFvkM985wqObm4RWjGaXkZQjkuBsNG0KoRIzfqYulFHQenXR39XSqHUEE72x6QH/q+LH3SIphURTz1MPPXwuL7yeM4WMoN/iudunrO+IiIiIiIirjSR6IiIOAsl+8kNfR3XeRXDXn/NiY7JEMJAiAKESFzpocwpulGLHX8A6Xfh+0ex7LuxYncjhDVnfQS+3QmEKJqzY07dl43QCkFc3VmvIiIiIiIiLpRIdEREjEMphZLDeO7WKz2UiBli2usx7fVXehgRERERERER5yFKEh4RMQEH39uDUgNXeiAREREREREREdcNkeiIiBiHUjlc580rPYyIiIiIiIiIiOuKSHRERIQEAcNpXCcK4I2IiIiIiIiImEuimI5rFCXT+H4HEGTB0fRqlJIoNYyS/SiVRwgdIVIIrXhcYK1CqVyQZlSmUSiEsBBaURhofGHpYZXKoeQQSmUAD6U8QAuOI2JB/yI54+MqlUX6p1EqTZD6tRxNKwn/JkFlkWoorF3gBuNHA2EiRDwIwsWetrBTkBbXRakcqDxK5YO+vb347u7Ra4VM47l7znssIWw0rRyhFczwHIM6EEplgloZuOF1UwTXTgOs8HwKwn+/23PTK6QcRPonp2mnoemVaFrxZRnV1UwQn9SLlKcJUj/H0Y2G0b+BG35308G/lc9oiuhZfHcnH4MTpAGWacAJ73PCY1rB8bUCwJj1PT72XR5GyUzYj0+Q9lqE3yczmANFPEymYM6qv2COTYNKB3OfGp+CWht3XrGgHxEL+786kLIP6fcAEiEsNL0RIbTwGvphau1hxu6HIAkF2AgtOatnxAhBHzmUTIfPi8nuueS4e+7dPudFRFx/RKLjGsVz32Gw9+OAjh3/EMniP0P6XeSzP8fJPob0jyG0FKZ1K1bio5jmSoSWQMpB3PzL5DOP4LlvoVQeXa/Hir8XK/YAutGEmEHmHKXySP8UnvsWbv41POdtpOxByUEQFppWgm60Ylg3Y9nr0YzGcCF4/geJ7+4lM/T/4uafR4gi4gW/Qzz1OZTK4XvH8JxNOPmXkN4+pN8TiqsYml6DYS7GtO/CsFag6fPCh+XU/bm5F/H9/fjeIXzvIL53GCVPj2sh8dzNDPTcfd4x68YiEgVfxYq/b9prpmQ/UvbgOTvw3Lfx3b1I2TFWR0PYaCKFptejm22Y9nswzCVoei2zXShdHyjc3FMM9//2eVsJUUCi6L8TSzx0mcZ1NSPJpb9FdvgvAA3DXElRxU+ChbM8jedux8m9gOduQfldSDkYbFRopehGK6a1BtN+D5rRhKYVcCGLQKVclOzFc3fhOm/gOZvxvQ6UOgNKoGkFaEYDhrkSy74D3WwDrTK8v2faT1CgUfpd+O5eXOc1PHc70u9AyjOgHBAaQqTQtAp0Yz66sTCcH5rQ9OpQWM2kP4WU/UjvWHg+b+J7h5B+dyjaJIg4mlaMptehGy0Y5g3o5lJ0vRKhVV4V4sPJ/ITM0J+i1DCaXk9x5XMoFUOpfnx3F07ueVznDZR/MtiYElp4Tk2Y1mpM+050s2VGc/kYCiWzSNmF52wNrp+7HemfRKlBBCZCKw6umbUa016PbrQgRNE1WCMpIiLifESi45rHRcpepHeYXPYRcsPfAHIAKH+QfPbH+N4hKPgtDGs1TvYxssP/gPSPjh7B93aTHdqD73WQKPjNcPdr6geKkkO4zuvkhr+J67zGOUXMlIP0h5H+cdz8C+TT/4qdeAg78VE0vW4GD9/geEoNolQvUvbh5jeSS38Dz9nC2QXalMrjewP43h7y2ccwY3cTT/1vGOYN50mdqhju/3K4YLj0KOXhOptxso/i5l5Aym4mLf6mPKRKI+UpPHcz+cz3MKxbSKT+E4a9FqXexcJDmCCSYRV1P/w/KqA3MyS+7ETJYXy/i1zmX8hn/i2wGI5DKVB+Bul34OZfRMs+Qiz5Wez4A2ha2Yx6UiqL52wjn/k+Tu6pSZMySJlFOt14zmZy6X/Fjt9PLPUFdKMd0GdwjwcWW8/ZTDb9LdzcC0B+smYodQZfnsH39gJPAQa6uYREwW9j2huA6Ra2Ct/rIJ/9Abn091HyFJN/d4fDea8Dz3mDPN9FiFLsxK+SKPw9rjZvZul3htbWfvLp75BN/yOozMRGCqSfRfon8ZzXyGV/RCzxKWKJh9D0qmn7CKxtfbjOS+TT38N1tnD256TIo8Lr5uZfJJf+DrHER7HiH0Y3mme0CRYREXFtEImO6wAlz5DP/gQn+xhCK0CI6tCl4Qzg47lv42SfQPqnyGceQcpuNG0eCAsl+1BqCJA4ucex7PVYsWoQ8Un7knIIJ/sYmcE/Ram+8FUdoZUEZnEMFH7odtUP5JCyk2z67/D9wyQKfgvdaGZmu2QK6Z0gn3mUfOYH+N5uwEJo5aGLhAHI8Fz7Cao4S9zcUyjZT7Lof6IbC6fcLdPNpaGZf3yXWXzvwNjvIoVuNJ13lLrRHLp1ne9UMjjZx8lnHmPsoWuMuhMgLILFj3/W+YDnvM7wQAepkr/FMG/g3el2IND1Juz4RwMxKgfD6t3BgkjJ7is9wKsflcN1XieffQwn+ziBO1BBeO9aBPdVDikHQKUJvn8HyA3/HSifWOITCO38dV6UzOA6L5Md+is8dzuBi9NIPwVhPwpwUHIgFP1Z8tkf4nl7SBb9IYa5avpTUS6es4n0wB+GYgICsVKI0JJBP0KA8kP3yUzYV1hVPrROzGQnXfo9ZIf+jHzul6CywYsiEe7E2wihj3PxygbuSaGYG3GhvDoXzj6esxUn99RowdDA3a0IsAnuh5HPaQgA5Z8kl/4mSuVIpL6E0M5XhFOhZA/5zA/JZf4V6Z8IXzfC51QKMIHA3VSqQVBZlDxFdvhr+N5+4qmvoJtLrtLrFxERcaFEouM6wPcOIdUQmlaOFb8f3WjFd/eSz/4E39sDKDz3TTxvK9I/jWVvwIzdjaaV4uZfIZ/9WbB7pxxc53UMay26VndOP0q5OLlfkBn8E5QaBEBoZRjGUszYreh6K0JLBZYHvwPfeRPX2YL0j4PK4OaeIitiJAr/y4x3TV3nTVxnI9LvQGhVGOZyTGt14PIhClDk8b0DuPlX8Zy3w11VhedsIp99jHjqSwgxmX+/IFXyt6Dk+DPE9/YwdOYz4e86hrmUVPFfn3eMQpjTPHxBaIWY9jo8Z0so+ipDN4w2dLMZTatAiBhKZfG9w8H5uG+hZB+gkP5xssN/TUHJ36LU9DEr1x8Cw7qBlHXD6CtK+UjZS274r8ilv3XlhnaNoOQw2eG/x3M2gYhjGO0Y1k0Y5lKEVoZAw5ddeM4W3PxrSP8Y4CP9Ezi5JzDMpZj22qmPrzxcZxOZob/CD+vcCFGAbizAsNdgGEvQtDIUEilP47vv4OY34nv7ARff3UZm4H+QKv06un7u/DOuJ6TfRW74X8YEh0himMsxrJsxzLYwDswIRKnswfcO43v7kV4HUvYGc5zRPpOrRj7zCE7+hVHBoelNmPZaDHNF6KKVQOGh5AC+dyzs5yBS9gICK371FhfNpf8RN/8qYKAbbZjWanTrxiBGTRhI/zSe+w5u/hV87yDgoeQZ3Ny/41orsWL3THlsKYfIZ39CLv0tpOwCRp4XizCs1ehmG0KUAC7S78Rz38Fz3sb3DgNOaCXzSBT+fmjxiFytIiKudSLRcR2g1CBClRNLfR478auAQNm3gjDJDv05Sg2GDwyBFXsf8YLfwjAXA2CYK5D+SZzcvxNYRUZqVJz70Pe9PWSHvja66yW0UmLJh4knf33SRbeKfxQn90uyw38RxEuoNG7uBRxzGXbiU+dxsxpbUEv/CACa3kgs+Wns+K+i6ZVntb8bK/4hckN/RT772KggcrI/IxZ/ECWKzlmkCyHQz3IPUMpHyZ6zhmKjGzVTjPPCMK1bkPEjKCSWfXtghdEmtyjZiQfJDn+NfPrbYWAnuLlnkf5JNL1xTsZzrSOEjiYSQOxKD+UawcFzNoKIY8XuJp76Moa5ZEILE1Cx+3Dyz5Ad+kt8bx8AvrsH19mIYa0OY6XORfod5DP/hu/uAgLBYcU/SCz5xdBH/+xF40dwnTfJDP5J6DYZWGVzw98gUfj7Uy4ylVJIeQrXeWV01KZ1M4nC/45htk559kFc2EHc/EZ0c0EYJ3V+lMrj5l9CyYHwnIpIFP6XsOq9PeX4lOrFzb+B7x3GtG6etp8rhZt/GdAw7VuIF/wupnXjOW0s9QFcZyPZwT8JrVfg+ydwcs9h2hsmvR+U8vGcjeSzj40THJXEEh/DTnwS3ajnbIutUg/h5l8hN/z1MINgHjf/HPlMK/GCrwDnzuNzTXowy8kjPei6Rk1jBbHk5J/xXCN9SW9XP11HepjXUkVZdZQII+L65OpyMo2YJQLdaMG0b2NkIhcijmEuRDfGHsJCpDDtdehG2+hrml6ObrQiRJB5SfpdYUaliSjlkhv+Z6TfSeAeIbDjv0Y89eXQnWGSUWkJrNh7iSV/ncBcD1J2BztYZy/uJ/Y28TiiOIwJeXASwRGg69XEUr8enq8WnksHvn+UETel6bm0DzRNryBe8GUSBb+JYd04peAA0LRC4qkvhbuxI19TH89555KOMeJ6x8AwlpMo+K/nCI4RhJbEtG/Hjn+EwB2KcOPicOj2dy5KeTi5p0Px4AIC076deOo3MMwFUwoI07qJRMHvIMZZPvOZR5BhZr7J8VB+72g8lhCpwMpxHsERtIthmEuIpz6PZd82pXiacF5yAKn6GMlQpRsLMKyVUwqOoB+BppVjxz9IouA/nbft1YCmN5Is/KNJBQcE2flMczWx5MOMzOOoTGBhn2IeV7IXJ/8ivrszPEgcO/4r2MnPhhnUzp1rhTCwYncQL/gtdKOFkXkvn/kevruXsSxhl46OA118638+yvf+7Od0nzhzyfsbwcm7bPz3rfzfD/89bz2/67L1GxFxuYlEx3WBhabXoOkVE14VWgWaXj36u2bUo+n15zxshV45KhyU7Ad17iLd947gOq8zEo+g6TXEkl8giEOYerEeLGDWo48uCHx87yjeBRTgM6xVWPbt06ZB1Y1mdHMxiLGdb987OOn5XDk0ZipuNK0wEJLjFi3SP04UPB0xW4RIYScfGk2dOxWaVoxuLpkwfwTpd09N2l7KICh85O9CK8WK/wqaPvkCczymfQuGdQMjAd1KDeDkfjnNiYx9jxQuUp5ByeHzv2dWaIx/TEo1EKYkl1O/5Rojlvw0mtF83jZCS6CbyybcN0oNTSkOPXcXnvMWQUwPGEY7ZuxOdH3etOMx7bVYsTvCmA9Qaph89vFJN8MiIiKuLSLRcR0gRGLSGAkh4kGQckhQS6LknHbaaFA2gBNkB1ITF7au82qQDjfEtDeg6aUzMHcLhCjAMFeOvqJkP95oLYzJ3zOGiWEuC4PPp0c35odB5gFS9qFmvEN29S3mdaMRMS67jgxd2yIiLhyBppdi2Rtm1lorQhu3SAySQ2Qmbeu7u0KrYvAdMszlwb07owBggWmtYyyLlMLNv3Ge9gaaVo2mhVZPNYznvI6T+wW+dww1h5sMQitG12sZsfhI7yD5zI/w3a1hvYmrb864IEQcK/aBmTUVcTRj/tgLykHJc+cjpXx8/xDSOzj6mm6uwBhnYZ+mJ6zYexHjNpnc/POgMtf+9Y6IeJcTxXRcBwTF/SYrTGcEaUZH2xVMWJBPaDeqP1WQfQqFGLf495ztKDWW6tC0VjJ9qsmRju0J/tNKDeP7x2b0Vk0rRTPqp3ThOqcrkZo4LpXlahQTM0YkmCDCriqrTcS1hY5mNKPp5TNqLYR51nzhAs6kbX3vaFh0LuzJWDBa1HNGIzPmB9YLBSMJHaYel4amV2HF3ksu8z3Aw/cOkhn8M8zYXZj2rUH/ei2aVsjFuE0KYWLF3ofn7gytjJJc+pv47m7M2F1BDR1jPppWFcaoXVsJHnSjGU2vmmGshDFqfQgIMoOdjVJDSK9zXDpyO9gM0mZ23wXjWoymlYxadgNX2S4MrZwZP3cuAiFg4PQQ208PMXB6CKEJymqKqWutJlkYP+d6nTk1QOehbgZOD+H7kmRBjNrWKipqS9GNieNVUnH8QBedh7rJZx3iSZuymuKg05E2StHfM8TON/ZTPq+EhavP3XTr7ujl4NZjlNeV0rKsHk2b3R6y7/mcOtbLqeO9pAcySF9i2gYFJSkaF9eOnq9SisEzw3QdOU3/6SHyWQcBJIsT1DRWUD2/HCEEUkp6T/ZzdE8ndQuqOXm4h3wmz7zmSkoqizi27yQDp4eorCulbkENscRYWvtsOkfXkdN0d/SSzzqYlkFZTQm1LVUkCmITrntPxxkObDvGopuaMSyDY3s66eseRPqSeMqmbVUzBcWJsbH3DnPySA8DvcPB2AWkihLUNFVS1VA2q3gh6UuO7D5B19HTNC+tp3r+uff4/neOcOp4L4tWN1NaXTzaz1BfmuP7u+jrHsBzfWIJm6qGMuoXVKPp2oTxSF/SdfQ0J4/0kB3OIaXCjlsUlaWoaiinpHKa7JlXEZHouB4QBmLSFLdnFdoS1hR1K84uyHXuIl16hxi/4PDcfSgeDaqBT0MQwLl33Cth9WDlT+HrPda/0EovaPHC2ZVslWTmouPyLRiU8oJ0xbJvLFWkcsJdWo8gjWQQWKtmHJMSEXE+DHR9/vTNRhGhG1OIUudYQEeQftdosHXwewdO7skJltbz4Xv7gvS2I++X/SjlTmkpEVoZduJBfP8EnrMRpYaRsot85rs4uV9imCsxrNUY5iJ0owlNr5lijpweK3YvvncgCIr2TwA+rvMyrvMqurkIw1qDaa5AM5qDvrSiWfVzJdD1maYvH2k2fr5XTDa3BgVQx4qsCq04TKk+c7EgtDhCrwTXYCQVuvQPg7mIyyE6+nqGeOXxLZw83ENf9wDZdJ6KeSXc+WtrWfO+GygsHRNfJw6e4vkfb2TrS3tID2VBgW5oLLixkXs/sY7WG+ZjmGNj3r/1KI9+7SkObDuGnbBIJGNUN5aTLBwT+Eopuo+f5tt/9BMa2ufx23/zOVJFY3938i6bn9nBD/78Cd77qdtoXlI3K78V1/HY/upeXvzJmxzd3YnnBt9BJRWxlM1v/sVnRhf7SsFrv3iblx/bTGYoh+f6SF8iBCxes4AHvngn9W3VSF+y/+0jfPMPfswdH1nDns2HOHXsNIvXtrL4phY2PbWdjoOnqGup4iNfvpclaxcAMNSf5q3nd/Hqz9/i1NHT+K6PAkqrirj1gyu55QM3UFRWMLoY3/PWYf7x937Ar//hr9HXPcDWl/dy5tQA+UweJSX/9Z9+g4KiBIhg0f7qz9/i5Z9uITs8buyaYOktC7j/CxuoW1A91WWaEqUUW1/azeP/+Dz3f/FO7nv4duz4OBE1nOOxrz/Dns2H+MpffoaSqiAZQu/Jfl58dBObn9vBUF8a6Qffo3lNldz7qXWsvGPxqPCQvuTAtmP84p9e4OieTgA810NoGiUVhbz307ex7oOTx2NdjUSi47pAY2YTsc5sZial/DCj1Zgfcy799xd8nIkHdQjiQyazvIw9BAMXsdktFmYxqEveg5T9+N4BfPcgvn8A6R1HylNhLvwgpz/KDYSGCmsKXMuWmoirB6FN6l55sSglw13tsV1vJ/cETu6JiziqH1gppxIdwkA3F5Mo+F3y2R/i5l/H9w+HdR7O4Oafwc2/gKbXBlWurVUY5vLA0jNdTZ2z+9IKiKX+A5peHQTLu9vDGkgS392J7+4kLxIY5kpM62YMawW6uQhdn5usd5eSmaYuvxCUyo3VMyGs/TGLOVzTSkAYo9ZdKfu5XHPh0d0niCdtlq1ro6K2lO6OXl55fAuP/cOzFJUXsHLDEgxTZ3ggwy++9SKvP/EOy25dwJI1C7DjJsf3dfHCjzdypmuA3/jjB6lsKEfTBNl0ju/+r5+x+80D3PfwHbSumM9wf4Ydr+3j9SfGkoRomkZ5bSkr7ljE1pf2sO+tw6zcMJb44UzXAPvfOUpxRSHtq5rOsabMlP1vH+G7/+tnZIZzrL57KS3LGjAtg77uAU4c6qa4vGDcjrsiO5RjXnMVTUvqKCpP4WRdtr26l5d+solY0uILf/DR0WP3dQ9ydPcJbvnACva9dYSN/76N/u5BlqxdQG1rFa/94m22vryHRTe3oKRi28t7+fk3nidVnODuh26lpKKQ/tODvP7EO/z0754hkbJZ+/4VExb1AC8+uglNEyy6qZnq+RU4eZdje05QVl00upRQKhAAda1VNC2uo7AsRT7rsO2Vvbz46JvEkzaf+/0PX/D10w2d9lXNVD65jb1bDrP6rqU0tI997w/v7OD4/i4W3tRMZV0ZmqbhOh7PfP81nvn+6yxf386dH2smnozRdaSHp//tNf75Dx+luqF8VAR5rsfj//AsG5/axke//F7qWqsDa1LXAH2nBkikru5EFWcTiY7rAhHu8M+g3ax2812U8qZvdkGoYGdz2pAQg+vhNlXKx/f24eaew8m/gOfugEnjM0wQJgIzLNDohilzI+ERcbGIKSydF4tHsBs9l/eoYrpsRUKYGNZiNOP/wLTfwM2/gufuwPcOhaLAQ/pHcbJHcXNPY5grMGMbMO33oBtNF3QtNK2EWPIzGNYq3PyLuM5b+O7e0P3HB5XBc17Bc15F11swY3dg2hswrdUzdg29IlySzFreBOusEPqEuLSZM1KwMkBdRlfZeCrG+gdWsuFjazEtA9fxMG2TR7/2FDvfOMCCFY2UVBayd8thNj+zgwXLG3jwtz/AvKZKhBB4rodu6DzyN0+y5bmd3PPJdVi2ycFtx9jy/E7W37+ST/7u/RiWgZSKpbcs4OieTro7xjJmFZakWHnHEjY9uZ0tz+3khtsWohtBIcrOw93sf+cITUvqaFlWP6tz9D2fZ3/wOp1HuvnE79zPXQ+uJVEQn/D38W4+Qgje95n3YNkGhhU8k5VStK1sZOsre9m18eCEmBvTMmhaWs99D99BWc1WNj65lcLSAh744p0c2tnB3i2H6e8ZwnM8Bs+kefPp7SgUv/If7+aG29pH+y2pLOJf/vgx3np+F+2rms9xYTq4/Thf+f8+zbJ1bZjjxjUyZggsT+//7O1YMQPDDNtIxYIV89n26l52bwrGPhsXq/mLallww3zefGYHR3efoG5BFZqmoaRix+v7Gegd4gPrbqekItjs6DzYzYuPvknL8no+/tX7KKsZc7lSCv7ljx9j45PbqG2pQugC6SuO7u0kWRjnnk+so7SqaPQcpa+uuaQW1/5qLuIyoE10swAMa82MXScmwzCXMrPb79rzkz4Xc1tZggAAIABJREFUhe9uJ5v+Z9zcM6HVCBAJdL0OTa9FaKUIkQotO7FR4eF5u3Cyv2T8LnJExOy5FLlDJmZ4AtCNdjS9Ztb9BYJgZkHomlaEFbsXw7oF392J62zBd3fge/uD2DGVRalBXOclPG87nruNWOKTQdrqC1p0CwxzKYa5BNM9hOduwXPewff24nv7Q6Gj8P0D+OlDuM4bxBKfwIp/6IKtK5eNKWslXQwGYtzcrpREMZuF0UQhe2kE8+TUNFVQt6BmdBFrWgZtK+ZTWVfKsb2dDJwepKSykD2bDzHQM8TqLy+jbJy/vmEarL9/JT//p+fZ9PR27vjoGizbZMdr+0EpbvnAitGFu6YJiisKWba+nWe///roGEzboL6tmob2Gva9dYRTx3qZ11xJLp3n6O5O0oNZWm+YT1H5ZPGc0zPQO8yhnR2UVRez4j0LJwgOYFLriRUzAnF0/AzDAxlcx2Wwdxjp+WSGsig59nnZCYvymmKEJoglLEqqiiipLCSeimHHTOJJG9fxcPMeJw51c/xAF27eZfurezm658TocU539uHkXE4c6iY9cG4ii8U3N9O4uHb0swImFQ+mbXB0dyfdx3sZHszi5l36Tw/he5LMcA4lFUK/8LVGsjBO+6omtjy3kwNbj7J8fTtF5QUM9A6z750jFJamaFxUix3GruzefJCB00M4uXKe//FGrNjYPHfq+GmkUux7+8iocNIMjeXr2nnqu6/y2N89zZK1bTS011BZPxIvdG3lg4pER8S0CGGFAaWCkYdALPFpdLONMUEw8rcxU+zkrwVtA5P7VA/8K7Wrf2nEje+fIpf9IW7uydFCf7rRhmnfjmGtQjda0LRKhFYU+j2PjSOXeSQUKpHoiLg6EcII5weTkZo4ZuxurNj7AgEdtGLy+WH8v8f/1C7QJUegaYVo9i0Y1mqk34Xnbh2rch0WPVWyDyf7c1A54uIrGNZSLvx7LzDMFgyzBRm7D9/dMdqP574dxn0ErlfZob8GYRFLPDiLfq5NhIhNTECgMhPcrWaKkgMT4nw0UczlWmAlCmIkUhOLjhaVFxBPxRjsGyaXDeIbz5wawMm7lM8rnrB4BKhqKMMwDbqO9CD9QHT1nOgDoLJ+olubrmuU15ybEr6ksojVdy/lp3/3LO+8tJt5zZX0dPaxZ/NBKutKWbS6edYFE/tODZDPOMxrqcSKTy/onLzLs99/nc3P7sBzfOy4iaZr5LMu2eEciYL4hJAvTdOwYsFxhSawYiamHSw5hRAITQt265ViqG+Yob406YEMW57biW5M/JxLq4uoa6065xoDVNaXTxAcZ6OUIp91ePYHr7PluZ0Txp7LOGSHcxSWpqYKV5sRbTc20ri4lj1bDtFx4BRF5QXsf+cwnQe7ueG2hZTXlox+TqdP9OHkXY7v66KvexBNm/j5ta9spKKudDSxgGHqvO/Tt5EdzrP52Z1seW4XrcsbWHRTM4tubqWhveaSF82cSyLRETEjdL0W393DaDC5sNGNthkV2LpwrtQX6NKIHc/ZjJffOCo4NL2OWPIzQR0DrZjznm8kNiKuATStDKGlUDJYVAlMdL0BTZ/7mIHpEMJEN+rRjXos+3Y8dxdO/jmc3JNI7wDg4uZfxrBuDNL6Tpr5b2ZoWhLNXoNpr8H3juHmX8HJ/RI3/wIQVE7Pp78T1Bm6BmI85gIhiiYUe5SqP0wMMFXikHNRKoeU3YwVdhVoRh2XI4h8KjRdQ2jirPh5FczeYhLX5VGXmbHnSmD1YTRweKxtcPyzSaRitN3YSKIwzo7X9nHbh1Zz8nAPh3d2sOL2RdS3z/6ekkqhCFx0ZrLi3vn6Af71T35KTVMl9z18O/OaK0kUxBnuz/A3Xz19TvtAWJz72uSDAZSifVUzdz24llTxuV4UiVQsyPJ1FnbMDD6X87Dt1b185/95nNqWKj7wudupaaogURhnsHeYrx09d+wXSkVtKW03NvLEt17iyK4OmpfWsXPjQbLpHAtvaqaobGyOGbEGrbt/JUtvbZtUMBWUJEfFiKZp1C2o5rO/9yG2vbKXvVsOcWDbcba/to8laxdw/69voO3Gxos+h8tFJDouMztOnmJXdzf3LWonaV0+c/HFYpjLcfOvoFQgOjx3C1bsris8qrlmspiXixcivrc/3P0MMO11QZ2TGQT1Stl1AXVGIiKuDJrRiKZV4Ieiw/f2I2XfFREd4xFaAaa9Bt1oRYgCculvoWQXSg3jubuRshv9IkTHeHSjAU1/CN1ciPR78L0dgMT3O/Dc7VjvFtGhFaLpdQiRCjZaVBbpH0fJfsQM7wffO4j0A3e14JjlaHodl8vSkR3Ok03nJrw23Jcmn3ZIFSdHg5lLK4swbYMzXf24eXdCkHNPxxl81w8CiEO3nRF//O7jvSxZ2zraVvqSgd5zi1sKTVBZX8by9W1se3kv21/dx/F9JwFYuCoIQJ4tRWUFWLZJ9/EgPe10MQ0bn9zKUF+az//Be7jrwVuAQFCdOtZLeihLsnD2CV+SxQmShQlM26ChrYb6trn7riip2Pjv2xgeyPL+z76HO39tbfC6UnQe6iYzlKOwLDXNUc6PpmssXtPKxjCgvLalisM7O5jXVElda9UEYVFSXYRpGdgJi4WrmiZkJZsKIQRFZQWsf2AVN92zjIPbjvHGL7fy7A9fJ5a0rynRcW05g10HbDvZxffe2kbGubbSoBr2rRNytDu5Z5Gy5xIVa7pyQdMT/YZlmDnlYgK1FEoOotSYL6quN80oi5BSeTznnag2R8RVj2EsRNPrGRHtrvM2vndwdJPiSqPpZaH4GKt3oGT/nFcxF0LDMJdgxe4Ye1F5SL9rTvu5mhFCD1IHj7vWnrsd3zswwyMo3NxzE1Iwm9baMObt8ljBu4700HGgC88JEqj4vuTg9uP0dJ6hfkE1ReEideFNLRRXFPL2C7s5c2pg9Hnoez5vPLmVXCbPjXcsGl10Lrq5FQFsfnYHTi6Y15VSpAez7N44+fUpKk2x7NY2XMfjpZ+8yf53jlI9v4KFN82sYO5UlFQWUtdaTe/JPnZtPEAuPdGqLn2J78vRc3LzLkKICW5gbt5j16aD9HUPcDHMa6qgbkEVR3Z2cGDbMZz8xGeek3NxHW9CzMiF4OZdNE1QVj02difnsvvNQxc99hEa2ufRuryBo3s7eeXxLfScOMOSWxZQUVs6od3C1U0UlRew5dmd9HScGXW9GyGbzuN5PkqpwP1MytFYFiEEsYTN4ptbufNja9ANnY7919bcElk6ImaEYSzCsFbi5J4GHKR3gNzwt0kUfAVFcsYPg2ACkxeUs/1yIRBhxqgYkAMUSg3h+6cuMv3lRAtKUItjOutF8OD13B0E2YEiIq5eNKMew1qJ576Dkr0o2YmTfQzdmI9uLLgAt5oga9X53DZnPYcoyYQNBGGF2fHONx6fIL7kQhe7477fQgMx+x3paxHDXIRprcJ3dwMuvrsbN/9yWIyw4rzv9dxdOLnnUKPZ/Sys+P2XMXU6ZIZzbHxyG07WpbK+jL7uAV54ZFOw4FvbSkFYp6N9ZSOr7l7Kpie38dN/eJYla1qxYiadh7p55nuv0rysnpvuWTYaNN6+qolFN7ew+dkd/OTrT9O0pA4377FnyyF6T02++DUsg7rWahra57Htlb2UVBZx873LqKy7OCuiaRnc8dE1HNl9gie+/RL9p4dpaK/BjlmkhzKcONjNHR++iaqw6N/iNQt48ruv8tyPNgaFCAUc23uSl3+6eULdktlQVlPCTfcs5+juTp767qsM92eoaaxAhfEeJw52c+OGxbSvbDpv/MakCMHiNa0896M3eP7HG4OaI8CxPZ28/PgWCkrnJrtcPGmzeE0r21/bx5bnd5IoiNO6rOEcS0ZD+zxu+5VV/PLbL/HI155i5YbFFFcU4uRcBk4PcXRPJx/+0j2jAsnJuXz7jx9j/sJ5lFYVE0taZIdy7H7zEEoqmpbWzcn4LxeR6IiYEUJLEEt+Cs/dgfSPAYp85nsIoWHFH8Aw25nK3zao89Ef1KbwDqHpZVixe87X26U4hekRAoSFbjSOVkSWfjdO9hfEkp++wEw3owdF08sRWuGov7vnvo307kGYxZMuZpTK4+ZfJDv892FGnIiIqxshbKzY3XjO27j5FwEXJ/8cQljY8Q9jWKvC1LGTf7elTCP9o/juLpTKEEt+Zsq+lBrCzb8EKo9uLkM3GsYFrE/6Dny/G9d5Fd87OPqqrteiTVMl23PewvcOoBuN6GY7QhSHlccn70cpietswck9P/qqIIZhLDxvP9cbQqvAtG/Hc7bgudtQapB89mcIrRA7/gCaXsU594KSeO52sulv4Hm7GNlsMWMbMK1VzCyb2cWj6RrLbm2jtqmS13/5DrmMQ2YwQ6Igzvs/9x4W3dQyuvBNFSd5/6dvwzQNdry+j92bDo6mzG1or+XeT62jpqlytFp4qijBJ3/3fh75m6d48ruvUFiaCmIVqou5+6FbePRrT086prJ5JSy/rZ1NT22lfF4Ji9e2Tig4OFuWr2vjY195Ly8/tplXHt+CbmgYpoFSCk0TrH3/DaNtV25YzF0P3sKujQfoPt6LaRmYtsHC1c1U1ZdxYNuxWY/DMHVWvGchvuvxys/e4rkfvRHE0IR/t+IWi9e0zOrYQsDqu5ay4WNr2bnxAF1HT2NaBlbMZNFNzVTWlXB0z8lZj3087auaqG2u5NCO46x/oIWa5opzYnUs2+SeT6zDtAw2P7uTn3/zhQnB5PGzEhhIqTi0o4NdGw+g6zqGbaBpQSrd2z60mnseunVOxn65uGpEx0sHj9CXzbJ2fj1VBYFq3nHyFO90nmRDazO1RYU8un0X1akU/bkc+3pO40lJY0kx97S3UmjbQaXHdIaXDh3haF8/OdejOB5jVf08bqoP1KBUimN9Azyz7wD3trfy2pFjHOsfoDgW49amBuqLi9jV1U3n4BDDeQddE7SUlXK0r5+hvMNtTfNZWBXs1JwcHGLjsQ4Onj6DrgnaKsq4uaGeskR8VE1vPXGSjcc6GMhmqSsupi+bm+oSXPUY1s3Ekp8nO/TnKNWPUv1k0/+M5+5CNxej6w1B9Vlhg/JQ5JB+H1J2I/1OpN+Bkr2Y9p3TiI4r6V6VxIxtwB8ORIeSZ8hnvgcqg27egKaXAlrgNqLSSDmM0OIYxiI0vXLSY+rGEnS9AW9EdDibyab/GSv2XgyzNfB9xkfJAaR/FM95Byf/PL67B91sx3f3cnHWDhVUQFcZxleVRymUyoX5762r0vo0NSoUs2edEwpkDiUzIOw5OKcwD7rKhtdprBtwkDKNEPYcJVSQKOUGYx+3U67ww8KRecA8z6L3yqIbbdiJB5HyFL67E1SafPYX+N5hDGukMF95mNlIopQT3PPydDg/dOJ7h9H0eecVHagMbv553PxGdKMV3ZiPps9H06vRtNLg+EIH5SDlANLvwHO34eZfRckeADS9HsNcgdBKp+4H8L3d5NLfQWhJNL0R3WhE02vDbHOpQOyE96GUPfje3qBQobc3PIIVZqhbMDcX+RpBCA3DWo0V/xBS9iL9E0j/ILn0t/G9AxjWSnS9HiEKwrmvF9/dj+u8hutsApUGQDcWEk9+IUwpfuk3oyrrSvnA526nuKKA0qpiDu04Tu/JfjRdUN1QTsvyBgpKJu6M17fV8MAX72TpLQvoOXEG35MUlCRoXFxHXWv1OeJg+fogPe3R3SfIpvMki+I0La6jtKqIguIk7SsbzxlXPGFTVV+GnbCpaaygbcW5bWaDHbdYd/8q6ttq6NjfxVBfBqUkdtyitLqYqvqycfUyCvn4V+9j7+ZDDPVnMEydirpSWpbV09Nxho6DpxCaQCiNxiV1fOL//CCtN8wHoLalio986V6qGgLrTNm8Et73mduw49ZoHExhaYpb7ruRhvZ5HN/fxXB/GqEJ4skY5fNKaFxcizEujW/z0jo+9Z8fYP6iWuxJslqNIETgVvXxr97H3i2HGQ7HXllfRvPSOk4d76XrSM+0wegzoaSikOLKQuy4xaLVTZTPm3x+qagt5f2fu5321c2cOnqabDqPaRkkCmJUza+YEHhux0w++98+RM+JM6QHg7TEdsKiuKKQpiW1F23xutxcNaJja+dJjvcP0FZRPio6Dp3p46m9B1hWU0VtUSEvHzxCbyZDY2kJ5ckEvlT84J0dQUGZpYuxdJ2c57HtZBfFsRgp26JjYJAtHSeoSCZpLC0JAp+Ghvj25rdJuy4CiBsGvlLkXI+M4/LakePs6e6hqbSEI319bD7eSU1hiiNn+pFSUldcRM51+emO3RzrG6AilUQpxVN7D3A6neG+Re2UJRMc6OnlXza/jRCC+uJCugYHebuzi5x7bbrLCGFjJz4CuOTS30T6J0GlcfPP4eZfC3b0RSqoIqx8gkXZcOibmw2PUcDFxUhcWoRIYMXeh5N7BuntBzx87wDZ9DdCUVUIiMBFSuVRKoNutqMlvzil6DCs5Rj2enz/GEr2odQgTu5n+O5ONL0mdBsIqjpL2Y3vHQGVxjBvJJb6EpnBPwyLkE0vxqQcwMk+gVJ9KJlDkQ3HmUfJIXxv91hb1Y+T/Vm4QDIDsShi4SI6hm4swLBWok2zMLvUSL8nrDjdASqHIhf8VA5KZfDdHaNtlcqRzz6G520nEFJ2KD5iCBFD0xsx7VvCrGHnks/+IhDHKhv2kQsrLDtBxetRXNz8ZjKDvw9YIKygD+ywnyoMaw26MXnhLs/dg+dsRMrB0X4gOCfpn8b3xvqS/gmyw38fuqVY4z6n4LMyrNUY5rLLWsdgMoQwMe33AHlyw/+E524HcnjuW3ju9kAQaIVhQToVbEyoNFIOTCiUqenV03emHKR/BOkfwc2b4bFLEFoBAjsUHe6oGJB+DyPiVGhlgXXWXoOYouL5uI6CBbG3C3gTIQoRWlm4uRIP3x+KdzmA9E+MZqkDHcO6gVjq8wjt8rkGXS1oWjFW/D6UypLPfB/pH0f6R8lnunDzr6DpFQgSoageQvqdoTU4eD7o5jLiqf8Y1lO5PFaOksoi1r5vbHe/sm5mc19ZTfGkmZUmQ9MEbTc2Thr8+/7PvmfS9+QyebqP95JIxWhf1XTRgc/jMS2DlmUNtCxrOG87IQQ1jRXUNJ7rHldSWUTbyqaRlsxrqmRe09jzsKK2lNs/fPPo78XlBROu8wixhE3L8gZalp9/LAC1zVXUNldN2w6CgPyzxzR+7AtXXVx8zAj9p4fo6x5kXnMljYtriSWmnpNTRQmWr2uHde3nPaZu6Cxb1zYn47sauGpEx0zpHk7z6VUrWFk3D09KuoeHef7AYT6wqB1L1ylNxPnVpYupKSzANnQO9fbx3554mu0nT9FYOha86/g+Uko+vHwJRTEb15fYhkHacch5HoUxmw8tXcSj23dxvH+Ae9paefXwUU4ODdOfy7Gz6xT7e3q5raWR9U3zUUrx4207efnQUZbXVFOWTPD8gYOcyWT5/M2rWFpTyUA2x67uHtQ1XF1a04qxE59A06rIZx/Hzb9CIChySL9jmnebaHo9ujHdF+jK5ZwWwsAwFhFPfZlc+h/DBa1EyTN4U7g6Ca3gvHU0NK0EO/4RUDny2ceD3VaVwfd2hBluzsbEtO8mlvwspr2OfPYRpN/JTKwdSvaTS38LKU+Giy6HIO3kJEJPZcMF4VvhCwaB+Aiqoluxe9D1+XDFRccp8tlH8Ny3w3NyCc5psrgYD8/djOduDn/Xw0KLFggT01oXuAJOJToyj+C574Tixg2D+Ce77j7SP0w+MyIONIJq8laYsrWNhF41pejw3V1kh/8JJc+gcMJ+Jq/qrWQ/bv6Z8DcBGOPOySCe+g+B+84VFh0QpJC17HsRouT/b+/eYuvI7wKOf/+XmTn3c+wT3504Tpx11kk3m2zSENJsQtmgarvqsu2yrKBCIECF14LEC0hIICReQLwg8cADVFQCCSq6CBVCW1Z0s+0u7WY3TdrcyGU3G3ttJ46v5zJnhocZO3Fi+9hO7Pjy+0iR4uMz859zfM7M/C+/349K6d+olL5LGKc+DYIBCAYW3F7pLVj3QJ1WHLRpB5JE557F7RsMxu7CTb6Ml3wJrevHaWndgtIFCAaJBgZGCWujdUOylMriJE6SSL2GdfbXbWejMqYDL/UaWjdSnvoGfvUDCEsEtRvxMt2HKZXD8Y7hpV7F8Y7WWTq38YVhyMCHw7xz6ixNnUX2/1zfrFmf0mSZd0/9mB9+Z65rydxe+OUj9B7csfT4iA3Mr/hc+uAG//G1/1n0NvuO7ebIi8+SSHlxBfKLXD13k+c+20dnT+u6qp+xWtbdJ+6ppiJ721ooplMzP5+6eIVgunojioHxcd68cpWRUompqs9ktcrw5OxKlmnX5dmONroaZt98TFQqOFqzJZ2mu9hAMZ1kolJhR7GBcwOfMDgxSdn3uTQ4zNn+AcYqZb5/LTp5fnR3lMtDt7kzNUUYhpwfGKSzkOeppiKNqRSNqRR7W1sYGHu8GVNWm9Y53ORLGLsLP3ESv/oeNf8iNf8jCCfiJS8mGgnUBbRpxZhoTbSxvXH8xxqmkriJz6FNkWr5LfzKj6KLZDACYQXiYmhKF9C6LRo5NwuPuFjbg0r/BsbZTbV8mlr1PEGtf2ZUNHqvmjB2J453GMc9inGejkaPnX1US99hcUus/Cir2LJiQXzAj0f5o+Jc4RoIYg+pEgS3l/maatHyF0rRawpvE4bzv6YoCHqIpc/GBUA5nlWK9xPOv5QyDCcJg0HCcHSJ7YQQd4ZCJuO/0xhPcknig5RO4XhHMXYbjnsMv3qGmv8Tav716DMVL52Jio7mUKYZEw9GGGc31nm6zv6zuMlX0GYrfvU8Qe0qQa2fILgT7Xsm45yD0hm0bkLb7VhnD9bZj3X2xql8698QWPcAqewf4Fffn0l9HdQGCcLR6FxAlehcl0DpBrRpx9jdWHc/1tmHdXay2ZNEGtOGSr6Msb34lXeoVs9Qq14iDIaia4WyKJXBmPbo+uAejJZf2R1PfPbuSQnDkNHhcd7/3oW4SvdF+q8NcvJXjtLZ8/BMYBiGS8rstHbOFmtHCNGS46VkyApDrp2/ydDHdxgZHOWtN35EOpdg/4m+ZVeK3+jWdKfDr9VmOhPTiqkUVt87iTva4N+Xcuwf3nuf09c+5NiOLrYXGyj7Pmdu3iJ44B4imhWZOz+y1gqFQqvon9Uaq+8FNQVhyHilQtp16G3aQlMmmursa23hF3qhZ0u0xm6y6tOcyWDuO958IvFQBcrlMPYpMoW/AkKUSmOchwMVo1mJ13Hcw9HPtmvOwEnrPkc6/4cz6SON8zT1LshKOVh3L8Z5Cqd2NL7RHYlH/KtEuaAcUCmUzqJ1MVrPrReeFta2i2Tmd/CSr0TtmC0Y27PgNvdz3COk838yUwHX2J2zq+MuglJRxXTHPYa1e6glPoyXRU0R3Zib6GKoEiiVR5umugGpKB2vB2/BcT8d3yRN37iE8Qh5Bm22oM3WuGJ79Llxk59H220Q+vF7Mf/fRulm0vk/hQVueBdLm/Z4RPnJMqaLVPb3HktQvTbNCy7fSWa/GrfzaJdlpXNYZ8+8v3e8o6QLf/5Y0iEbpzdesvQgjZt88V6aWGUxduEb+llbm06S6a/gJb4Qba6LGGdx0/xK2ShtqtmK4x0mqA0QBLej2JiZGJx4YEJl0LoBZZqjwnJ1RgeVcrG2F2O7cWqDcQdvjDCYjGeNakTfKYPCjWIvdBFtWuL9L74ToE0zbuKFqMr5zDluIu5Q+lFbSgPTAxF5tG6J21p7l1fHO07aNM187qK/5+LeD60ao6Km3gkg6vwZ27e4bXUO7R2KrxcvENQG4wGXCtPnU6UK8fezLZ7F29yjxMP9I3zjr09RnirjJlyOvXyQ41889NDshOs5PPv8bnbtq78kaVp+S3ZWfIQAaw3bn+7g9a++uOhtUtkk3/vmD/nPr79FeapCY3OeF3/9eXqf68bI+zunNXNWtMZQC0Nq4b3eweDE5EPxD0arBc9F/3jmLMd3dvOFvt3kEh7Dk5P8zel353yuXmBH6sEf7nuuArKeR2MqxZHt29jfMXua3jUGpRSFRIKRUolK7d5c/PDkJLVl5pqedeymCS/1yoLPUTqF4+4Hd+Hp/enqvcuhlBulxaRrWds/SOsGtHd02dsb242x3fWfuAhKGZRpqpvicWn7TGLsToxdfCaOpbwmrbN4ycWfNNcDbRpxzYlVactNHF+Vdh7n53Q+Sims04d1Fndj+CCt82jvyCMeg0WZlrozgcvYMQoPYzuBFU4ZqTTaNMZJJNY34+zEOMvMAqRTOO5BcA8us3WF1oUonmqOQbLNzA9qnBu5xd9dfnvmsbGRCc5/ZoLeTAtfOXSS3LY874Q3Gbp8gde7D5EwUZyLNppcY+aR09ZudkorkpnEQ9mjFhKGIc98ppeG5hxKKxpb8nT0tD5SocSNbs10OlqzGd6+doP3P+4n53ncGh3jnRsfMVqef638XMIQJitVlIKP747xL2fPMVGJR5MfowMdbZy5eYv/vnyVXMKjIZnkztQUk5Uqu5qKNCSTHNrWwT+dOcvpqzc43NXJwNg4//vhTcr+k1+yIoQQQognLwhD+qfu8oOhq3x5x2EKXgqa4Od37aEtWWBf6y6GSuNcvHKO6xPD/NL25570IQuigZ2tj7mC+ka3Zjodn97Wyf8N3+bUhct8++IViukUO4oNS8709Fs/c5B//uDH/P43v0XG8+hqyHNwa8djP95PtbXypWf28OaVq/zlm6cJwpCk43Boa8dMnMiJnm6u3x7hjfM/5d9/coGOQp597W28fX35+ayFEEIIsfGkrcfJ9j46UvmZx/QaTZEtxHKoMFxwBmDV4o1qQcDA2Di3xsYo+zUyrktjKslIqcS2QoFcwuOnA4M4xrC1kMeN18t9NHKXT8YneKa9FauKloJHAAADKElEQVQ1Y6Uyl4aGmaxW8aylLZeh7NfwjKWzkCMMQ+6WylweGqa3eQtZb/Za6LLv8/FolL6xq5Dn5ugYpapPd7GBT8bHmahU6chlSbkuE5UKt0bHGJ6YxA+i7FfNmTSt2QyujQrs9I+Nc/PuKGXfJ59M0JhMMjA+wZ6W5pnXIMRa51cvUp78OjX/0oq3pU0HifRvrv2EA0IsQxCMUil9i8rUv65Ke17qy7iJE6ta0VssTaXm893+C/zF+f/ib3/21+hMNzz0nKHSOH9/5ftcnxjmzw78Imm7nGK1QqyKeWMX1sxMh9Ga9nyO9nxu1uOd3OvxTxflm/X7Qp7Owr3nZBMeBzrnD35VSlFIJuad/fCspfu+1Lpb79t3e272saVdl54txZnA8bnaastlacvNzmLw4GsUYq0Lw1H8yv3pdVeOsT2EqVdXvB0hnoiwSuBfjSu3rzzHOx4HvK9Kc+IR1MKQO5UJvOl4DaVIGoeU3ZxZvMTGs2Y6HUIIIYQQm9VQaYw/eu8NXB2tgsg5CT7XsZdXt9erXSPE+iCdDiFEXcbuIpX/YwiWWldiGVQKa2VpldiYlM7ipV6bSWW+0oztgU1eYG+9KLgpfnf38zR50eoIq/XM/4XYCKTTIYSoS6kc1tnH6oR5KdQmL6gmNjIHbbrQZnlpypdOo2Rt1brgGUtfvp3OVKH+k4VYh6TTIYSoKyrYJokPhHhU0XdJsdkrlYu5RWXBpJMoNibpdAghhBBCrAMlv0r/1CjJONjcKE3GSZCWYHOxDkinQwghhBBiHXh3+Dq/ffpr6HjJXFMiy6/uOMxLWz/1hI9MiPrWTJ0OIYQQQojNJgxDSrUqo9USRS+N1Q8vZa2FARPVMmN+edbjRmmyjid1O8RaMu/6QOl0CCGEEEIIIR6HeTsdEskmhBBCCCGEWFHS6RBCCCGEEEKsKOl0CCGEEEIIIVaUdDqEEEIIIYQQK6peylypUCOEEEIIIYR4JDLTIYQQQgghhFhR0ukQQgghhBBCrCjpdAghhBBCCCFWlHQ6hBBCCCGEECtKOh1CCCGEEEKIFSWdDiGEEEIIIcSK+n9bYcIjStF2EgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# importing the necessery modules \n",
    "from wordcloud import WordCloud \n",
    "import matplotlib.pyplot as plt \n",
    "import csv \n",
    "  \n",
    "# file object is created \n",
    "file_ob = open(r\"fp.csv\") \n",
    "  \n",
    "# reader object is created \n",
    "reader_ob = csv.reader(file_ob) \n",
    "  \n",
    "# contents of reader object is stored . \n",
    "# data is stored in list of list format. \n",
    "reader_contents = list(reader_ob) \n",
    "  \n",
    "# empty string is declare \n",
    "text = \"\" \n",
    "  \n",
    "# iterating through list of rows \n",
    "for row in reader_contents : \n",
    "      \n",
    "    # iterating through words in the row \n",
    "    for word in row : \n",
    "  \n",
    "        # concatenate the words \n",
    "        text = text + \" \" + word \n",
    "  \n",
    "wordcloud = WordCloud(background_color=\"white\", max_words=20, width=800, height=500,relative_scaling=0.5, collocations=False).generate(text) \n",
    "plt.figure(figsize = (16,9)) #increase the picture's resolution\n",
    "plt.imshow(wordcloud, interpolation=\"bilinear\") \n",
    "plt.axis(\"off\") \n",
    "plt.margins(x=0, y=0) \n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[({'gun'}, 3322), ({'gun', 'body_camera_no'}, 2955), ({'gun', 'body_camera_no', 'shot'}, 2920), ({'gun', 'Male'}, 3209), ({'gun', 'Male', 'shot'}, 3166), ({'gun', 'shot'}, 3279), ({'Not fleeing'}, 3609), ({'Not fleeing', 'body_camera_no'}, 3155), ({'shot', 'Not fleeing', 'body_camera_no'}, 2982), ({'Not fleeing', 'body_camera_no', 'Male'}, 3001), ({'shot', 'Not fleeing'}, 3399), ({'shot', 'Not fleeing', 'Male'}, 3228), ({'Not fleeing', 'Male'}, 3431), ({'attack'}, 3762), ({'mental_illness_no', 'attack'}, 2923), ({'body_camera_no', 'attack'}, 3334), ({'body_camera_no', 'attack', 'Male'}, 3198), ({'shot', 'body_camera_no', 'attack', 'Male'}, 3073), ({'shot', 'body_camera_no', 'attack'}, 3208), ({'shot', 'attack'}, 3614), ({'attack', 'Male'}, 3614), ({'shot', 'attack', 'Male'}, 3467), ({'mental_illness_no'}, 4469), ({'mental_illness_no', 'body_camera_no'}, 3959), ({'shot', 'mental_illness_no', 'body_camera_no'}, 3797), ({'shot', 'mental_illness_no', 'body_camera_no', 'Male'}, 3645), ({'mental_illness_no', 'body_camera_no', 'Male'}, 3804), ({'shot', 'mental_illness_no'}, 4274), ({'shot', 'mental_illness_no', 'Male'}, 4109), ({'mental_illness_no', 'Male'}, 4301), ({'body_camera_no'}, 5099), ({'shot', 'body_camera_no'}, 4856), ({'shot', 'body_camera_no', 'Male'}, 4639), ({'body_camera_no', 'Male'}, 4875), ({'shot'}, 5525), ({'shot', 'Male'}, 5278), ({'Male'}, 5563)]\n",
      "The executing time of the FP-Growth algorithm is 1.9134907722473145 seconds.\n"
     ]
    }
   ],
   "source": [
    "# Frequent pattern mining\n",
    "#  \n",
    "import operator\n",
    "import time\n",
    "\n",
    "class Conditional_FP_Tree:\n",
    "    def __init__(self, item, support, parentNode):\n",
    "        self.name = item\n",
    "        self.count = support\n",
    "        self.nodeLink = None\n",
    "        self.parent = parentNode\n",
    "        self.children = {}\n",
    "\n",
    "    def support_count(self, support):\n",
    "        self.count += support\n",
    "'''\n",
    "    def display(self, depth = 1):\n",
    "        print(' '*depth, self.name, ' ', self.count)\n",
    "        for child in self.children.values():\n",
    "            child.display(depth + 1)\n",
    "'''\n",
    "\n",
    "'''\n",
    "def find_frequent_items(D, min_sup:int):\n",
    "    item_count = defaultdict(int)\n",
    "    for row in D:\n",
    "        for item in row:\n",
    "            item_count[item] += 1\n",
    "    items = dict()\n",
    "    for item, count in item_count.items():\n",
    "        if count >= min_sup:\n",
    "            items.update({item: count})\n",
    "    F = sorted(items.items(), key=operator.itemgetter(1), reverse=True)\n",
    "    return F\n",
    "'''\n",
    "\n",
    "def create_FP_Tree(D, min_sup:int):\n",
    "    # To create FP Tree, create headertable first.\n",
    "    headertable = {}\n",
    "    for row in D:\n",
    "        for item in row:\n",
    "            headertable[item] = headertable.get(item, 0) + D[row]\n",
    "    # The headertable include item name and support count.\n",
    "    remove = []\n",
    "    for key in headertable.keys():\n",
    "        if headertable[key] < min_sup:\n",
    "            remove.append(key)\n",
    "    for item in remove:\n",
    "        headertable.pop(item)\n",
    "    # If item is not frequent, then remove from headertable.\n",
    "    ### frequent_itemset = find_frequent_items(D, min_sup)\n",
    "    frequent_itemset = sorted(headertable.items(), key=operator.itemgetter(1), reverse=True)\n",
    "    if len(frequent_itemset) != 0:\n",
    "        for item in headertable:\n",
    "            headertable[item] = [headertable[item], None]\n",
    "            # create node link.\n",
    "            # Now headertable contains itemname, support count, and node link for each item.\n",
    "        FPTree = Conditional_FP_Tree('Null', 1, None)\n",
    "        # root node: item = Null, support = 1, Parent = None\n",
    "        for transaction, support in D.items():\n",
    "            treegrowth = {}\n",
    "            for item in transaction:\n",
    "                if item in set(headertable.keys()):\n",
    "                    treegrowth[item] = headertable[item][0]\n",
    "                    # only need frequency here\n",
    "                    # treegrowth contains all unique frequent items in each transaction in turn\n",
    "            if len(treegrowth) > 0:\n",
    "                sortgrowth = sorted(treegrowth.items(), key=operator.itemgetter(1), reverse=True)\n",
    "                # To build the tree, sort by support count. Highest comes first.\n",
    "                nextitemset = []\n",
    "                for item in sortgrowth:\n",
    "                    nextitemset.append(item[0])\n",
    "                # THIS IS SOMETHING NEW TO ME: orderedItems = [v[0] for v in st]\n",
    "                # MORE EFFICIENT CODING THIS WAY.\n",
    "                updateFPTree(nextitemset, FPTree, headertable, support)\n",
    "                # Update tree for each transaction in turn to construct the whole tree.\n",
    "        return FPTree, headertable\n",
    "    else:\n",
    "        return None, None\n",
    "\n",
    "'''\n",
    "============ Insert Tree =============\n",
    "'''\n",
    "\n",
    "def updateFPTree(itemset, tobeupdateTree, headertable, support):\n",
    "    # Update tree for item in the chosen itemset one by one.\n",
    "    # Finish by recursion\n",
    "    if itemset[0] in tobeupdateTree.children:\n",
    "        # If the item is already one child of the current tree, then update the support count.\n",
    "        tobeupdateTree.children[itemset[0]].support_count(support)\n",
    "    else:\n",
    "        # Call to build a new branch of the conditional tree and update the headertable.\n",
    "        tobeupdateTree.children[itemset[0]] = Conditional_FP_Tree(itemset[0], support, tobeupdateTree)\n",
    "        if headertable[itemset[0]][1] == None:\n",
    "            # If there is no nodeLink, then create one.\n",
    "            headertable[itemset[0]][1] = tobeupdateTree.children[itemset[0]]\n",
    "        else:\n",
    "            # If there is a nodeLink, then update it.\n",
    "            updatenodeLink(headertable[itemset[0]][1], tobeupdateTree.children[itemset[0]])\n",
    "    # Recursion\n",
    "    if len(itemset) > 1:\n",
    "        new_itemset = itemset[1::]\n",
    "        updateFPTree(new_itemset, tobeupdateTree.children[itemset[0]], headertable, support)\n",
    "\n",
    "def updatenodeLink(new_node, target_node):\n",
    "    # Based on Figure 6.7, all linked nodes are as nodes in linked list.\n",
    "    # When there is a nodeLink, then find the end node and add the new link.\n",
    "    while new_node.nodeLink != None:\n",
    "        new_node = new_node.nodeLink\n",
    "    new_node.nodeLink = target_node\n",
    "\n",
    "'''\n",
    "============== Top-down finished. Now starts bottom-up. ==============\n",
    "'''\n",
    "\n",
    "def bottom_up_Tree(leafnode, path):\n",
    "    # Recursion again\n",
    "    if leafnode.parent != None:\n",
    "        # We have not reached the root node yet.\n",
    "        path.append(leafnode.name) # grow up\n",
    "        bottom_up_Tree(leafnode.parent, path)\n",
    "    return path\n",
    "\n",
    "def find_path(node):\n",
    "    # Recursion again...\n",
    "    conditional_pattern_base = {}\n",
    "    while node != None:\n",
    "        path = []\n",
    "        updatepath = bottom_up_Tree(node, path)\n",
    "        if len(updatepath) > 1:\n",
    "            conditional_pattern_base[frozenset(updatepath[1:])] = node.count\n",
    "            # node is the leafnode for this certain path,\n",
    "            # so its support count should be the minimum support count of all nodes in the path\n",
    "            # Use the minimun support count of all nodes in the path as the support count of the path.\n",
    "            # conditional pattern base stored all paths and their support counts.\n",
    "        node = node.nodeLink\n",
    "        # Start from the bottom and move to the parent to find all paths.\n",
    "    return conditional_pattern_base\n",
    "\n",
    "'''\n",
    "============== Mine Frequent Patterns ==============\n",
    "'''\n",
    "\n",
    "def FP_Growth(headertable, prefix_path, min_sup:int, frequent_itemset):\n",
    "    # beta = [alpha[0] for alpha in sorted(headertable.items(), key=operator.itemgetter(1))] why bug?\n",
    "    beta = [alpha[0] for alpha in sorted(headertable.items(), key=lambda p: p[1][0])]\n",
    "    # Start from the bottom frequent_1_itemset: leafnode\n",
    "    # Use each one of the frequent_1_item as the leafnode, updating path with len(path) increase by 1 each time.\n",
    "    for base_node in beta:\n",
    "        newfreqitemset = prefix_path.copy()\n",
    "        newfreqitemset.add(base_node)\n",
    "        frequent_itemset.append((newfreqitemset, headertable[base_node][0]))\n",
    "        conditional_pattern_base = find_path(headertable[base_node][1])\n",
    "        conditional_FPTree, conditional_headertable = create_FP_Tree(conditional_pattern_base, min_sup)\n",
    "        if conditional_headertable != None:\n",
    "            # As long as there is frequent itemset, recurse.\n",
    "            FP_Growth(conditional_headertable, newfreqitemset, min_sup, frequent_itemset)\n",
    "    return frequent_itemset\n",
    "\n",
    "######################################################################################################################\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    start_time = time.time()\n",
    "    with open('fp.csv') as file:\n",
    "        ds = file.readlines()\n",
    "    transactions = []\n",
    "    for i in range(len(ds)):\n",
    "        transactions.append(ds[i].strip().split(','))\n",
    "    Dataset = {}\n",
    "    for transaction in transactions:\n",
    "        Dataset[frozenset(transaction)] = 1\n",
    "    Frequent_Itemset = []\n",
    "    Prefix_Path = set([])\n",
    "    min_sup = len(transactions) * 0.5\n",
    "    FPTree, HeaderTable = create_FP_Tree(Dataset, min_sup)\n",
    "    FrequentItemset = FP_Growth(HeaderTable, Prefix_Path, min_sup, Frequent_Itemset)\n",
    "    print(FrequentItemset)\n",
    "    # print(len(FrequentItemset))\n",
    "    print(\"The executing time of the FP-Growth algorithm is %s seconds.\" % (time.time() - start_time))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2015</td>\n",
       "      <td>994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2016</td>\n",
       "      <td>961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2017</td>\n",
       "      <td>986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2018</td>\n",
       "      <td>990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2019</td>\n",
       "      <td>999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020</td>\n",
       "      <td>888</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      count\n",
       "year       \n",
       "2015    994\n",
       "2016    961\n",
       "2017    986\n",
       "2018    990\n",
       "2019    999\n",
       "2020    888"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Bar plot police shooting total count of each year according to WP data (12/01/2020)\n",
    "#In order to match WP chart, it does not exlude \"unknow\" race data\n",
    "table_1 = pd.pivot_table(ps, values=['count'], index=['year'], aggfunc=np.sum)\n",
    "table_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Total Police Shooting Number per Year')"
      ]
     },
     "execution_count": 4,
     "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": [
    "table_1.plot.bar()\n",
    "plt.title('Total Police Shooting Number per Year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x960 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "table_2 = pd.pivot_table(ps, values=['count'], index=['period'], columns= ['year'], aggfunc=np.sum)\n",
    "table_2.plot.line(figsize = (20,40/3))\n",
    "\n",
    "plt.title('Total Police Shooting Number per month')\n",
    "table_2.to_excel('table_2.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>id</th>\n",
       "      <th>name</th>\n",
       "      <th>date</th>\n",
       "      <th>manner_of_death</th>\n",
       "      <th>armed</th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "      <th>race</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>signs_of_mental_illness</th>\n",
       "      <th>threat_level</th>\n",
       "      <th>flee</th>\n",
       "      <th>body_camera</th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>is_geocoding_exact</th>\n",
       "      <th>year</th>\n",
       "      <th>count</th>\n",
       "      <th>place</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Tim Elliot</td>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>53.0</td>\n",
       "      <td>M</td>\n",
       "      <td>A</td>\n",
       "      <td>Shelton</td>\n",
       "      <td>WA</td>\n",
       "      <td>True</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-123.122</td>\n",
       "      <td>47.247</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>WA-Shelton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Lewis Lee Lembke</td>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>47.0</td>\n",
       "      <td>M</td>\n",
       "      <td>W</td>\n",
       "      <td>Aloha</td>\n",
       "      <td>OR</td>\n",
       "      <td>False</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-122.892</td>\n",
       "      <td>45.487</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>OR-Aloha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>John Paul Quintero</td>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>shot and Tasered</td>\n",
       "      <td>unarmed</td>\n",
       "      <td>23.0</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>Wichita</td>\n",
       "      <td>KS</td>\n",
       "      <td>False</td>\n",
       "      <td>other</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-97.281</td>\n",
       "      <td>37.695</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>KS-Wichita</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>Matthew Hoffman</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>shot</td>\n",
       "      <td>toy weapon</td>\n",
       "      <td>32.0</td>\n",
       "      <td>M</td>\n",
       "      <td>W</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA</td>\n",
       "      <td>True</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-122.422</td>\n",
       "      <td>37.763</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>CA-San Francisco</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>Michael Rodriguez</td>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>shot</td>\n",
       "      <td>nail gun</td>\n",
       "      <td>39.0</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>Evans</td>\n",
       "      <td>CO</td>\n",
       "      <td>False</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-104.692</td>\n",
       "      <td>40.384</td>\n",
       "      <td>True</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>CO-Evans</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>5813</td>\n",
       "      <td>6341</td>\n",
       "      <td>Ellis A. Frye</td>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>62.0</td>\n",
       "      <td>M</td>\n",
       "      <td>B</td>\n",
       "      <td>Culpeper</td>\n",
       "      <td>VA</td>\n",
       "      <td>False</td>\n",
       "      <td>other</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-78.019</td>\n",
       "      <td>38.520</td>\n",
       "      <td>True</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>VA-Culpeper</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5814</td>\n",
       "      <td>6342</td>\n",
       "      <td>Michael Anthony Pena</td>\n",
       "      <td>2020-11-26</td>\n",
       "      <td>shot</td>\n",
       "      <td>undetermined</td>\n",
       "      <td>31.0</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>Lubbock</td>\n",
       "      <td>TX</td>\n",
       "      <td>False</td>\n",
       "      <td>undetermined</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>-102.030</td>\n",
       "      <td>33.543</td>\n",
       "      <td>True</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>TX-Lubbock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5815</td>\n",
       "      <td>6338</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-11-27</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>74.0</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Marinette County</td>\n",
       "      <td>WI</td>\n",
       "      <td>False</td>\n",
       "      <td>other</td>\n",
       "      <td>Car</td>\n",
       "      <td>False</td>\n",
       "      <td>-88.065</td>\n",
       "      <td>45.358</td>\n",
       "      <td>True</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>WI-Marinette County</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5816</td>\n",
       "      <td>6340</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-11-27</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Wilsonville</td>\n",
       "      <td>OR</td>\n",
       "      <td>True</td>\n",
       "      <td>other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>-122.834</td>\n",
       "      <td>45.278</td>\n",
       "      <td>True</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>OR-Wilsonville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5817</td>\n",
       "      <td>6339</td>\n",
       "      <td>Cory Donell Truxillo</td>\n",
       "      <td>2020-11-29</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>43.0</td>\n",
       "      <td>M</td>\n",
       "      <td>B</td>\n",
       "      <td>Houma</td>\n",
       "      <td>LA</td>\n",
       "      <td>True</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "      <td>-90.730</td>\n",
       "      <td>29.602</td>\n",
       "      <td>True</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>LA-Houma</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5818 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id                  name       date   manner_of_death         armed  \\\n",
       "0        3            Tim Elliot 2015-01-02              shot           gun   \n",
       "1        4      Lewis Lee Lembke 2015-01-02              shot           gun   \n",
       "2        5    John Paul Quintero 2015-01-03  shot and Tasered       unarmed   \n",
       "3        8       Matthew Hoffman 2015-01-04              shot    toy weapon   \n",
       "4        9     Michael Rodriguez 2015-01-04              shot      nail gun   \n",
       "...    ...                   ...        ...               ...           ...   \n",
       "5813  6341         Ellis A. Frye 2020-11-26              shot           gun   \n",
       "5814  6342  Michael Anthony Pena 2020-11-26              shot  undetermined   \n",
       "5815  6338                   NaN 2020-11-27              shot           gun   \n",
       "5816  6340                   NaN 2020-11-27              shot           gun   \n",
       "5817  6339  Cory Donell Truxillo 2020-11-29              shot           gun   \n",
       "\n",
       "       age gender race              city state  signs_of_mental_illness  \\\n",
       "0     53.0      M    A           Shelton    WA                     True   \n",
       "1     47.0      M    W             Aloha    OR                    False   \n",
       "2     23.0      M    H           Wichita    KS                    False   \n",
       "3     32.0      M    W     San Francisco    CA                     True   \n",
       "4     39.0      M    H             Evans    CO                    False   \n",
       "...    ...    ...  ...               ...   ...                      ...   \n",
       "5813  62.0      M    B          Culpeper    VA                    False   \n",
       "5814  31.0      M    H           Lubbock    TX                    False   \n",
       "5815  74.0      M  NaN  Marinette County    WI                    False   \n",
       "5816   NaN      M  NaN       Wilsonville    OR                     True   \n",
       "5817  43.0      M    B             Houma    LA                     True   \n",
       "\n",
       "      threat_level         flee  body_camera  longitude  latitude  \\\n",
       "0           attack  Not fleeing        False   -123.122    47.247   \n",
       "1           attack  Not fleeing        False   -122.892    45.487   \n",
       "2            other  Not fleeing        False    -97.281    37.695   \n",
       "3           attack  Not fleeing        False   -122.422    37.763   \n",
       "4           attack  Not fleeing        False   -104.692    40.384   \n",
       "...            ...          ...          ...        ...       ...   \n",
       "5813         other  Not fleeing        False    -78.019    38.520   \n",
       "5814  undetermined          NaN        False   -102.030    33.543   \n",
       "5815         other          Car        False    -88.065    45.358   \n",
       "5816         other          NaN        False   -122.834    45.278   \n",
       "5817        attack  Not fleeing        False    -90.730    29.602   \n",
       "\n",
       "      is_geocoding_exact  year  count                place  \n",
       "0                   True  2015      1           WA-Shelton  \n",
       "1                   True  2015      1             OR-Aloha  \n",
       "2                   True  2015      1           KS-Wichita  \n",
       "3                   True  2015      1     CA-San Francisco  \n",
       "4                   True  2015      1             CO-Evans  \n",
       "...                  ...   ...    ...                  ...  \n",
       "5813                True  2020      1          VA-Culpeper  \n",
       "5814                True  2020      1           TX-Lubbock  \n",
       "5815                True  2020      1  WI-Marinette County  \n",
       "5816                True  2020      1       OR-Wilsonville  \n",
       "5817                True  2020      1             LA-Houma  \n",
       "\n",
       "[5818 rows x 20 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ps[\"place\"] = ps[\"state\"] + \"-\" + ps[\"city\"]\n",
    "ps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "state = pd.pivot_table(ps, values=['count'], index=['state'], columns=['year'], aggfunc=np.sum)\n",
    "state.to_excel('state.xlsx')"
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   "source": [
    "#Display polices shooting rate on map\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "import pandas as pd\n",
    "df = pd.read_excel('state1.xlsx')\n",
    "\n",
    "fig = go.Figure(data=go.Choropleth(\n",
    "    locations=df['state'], # Spatial coordinates\n",
    "    z = df['police shooting per 1m'].astype(float), # Data to be color-coded\n",
    "    locationmode = 'USA-states', # set of locations match entries in `locations`\n",
    "    colorscale = 'Reds',\n",
    "    colorbar_title = \"police shooting per 1m\",\n",
    "))\n",
    "\n",
    "fig.update_layout(\n",
    "    title_text = 'Yearly average fatal police shooting per 1m by State',\n",
    "    geo_scope='usa', # limite map scope to USA\n",
    ")\n",
    "\n",
    "fig.show()"
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  {
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   ],
   "source": [
    "#Display polices shooting number on map\n",
    "df = pd.read_excel('state1.xlsx')\n",
    "\n",
    "fig = go.Figure(data=go.Choropleth(\n",
    "    locations=df['state'], # Spatial coordinates\n",
    "    z = df['average police shooting by year'].astype(float), # Data to be color-coded\n",
    "    locationmode = 'USA-states', # set of locations match entries in `locations`\n",
    "    colorscale = 'Reds',\n",
    "    colorbar_title = \"Average police shooting by year\",\n",
    "))\n",
    "\n",
    "fig.update_layout(\n",
    "    title_text = 'Yearly average fatal police shooting by state',\n",
    "    geo_scope='usa', # limite map scope to USA\n",
    ")\n",
    "\n",
    "fig.show()"
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  },
  {
   "cell_type": "code",
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   "metadata": {},
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   ],
   "source": [
    "#Display polices shooting number on map\n",
    "df = pd.read_excel('state_all.xlsx')\n",
    "\n",
    "fig = go.Figure(data=go.Choropleth(\n",
    "    locations=df['Acronym'], # Spatial coordinates\n",
    "    z = df['Gun Ownership rate'].astype(float), # Data to be color-coded\n",
    "    locationmode = 'USA-states', # set of locations match entries in `locations`\n",
    "    colorscale = 'blues',\n",
    "    colorbar_title = \"Gun Ownership rate\",\n",
    "))\n",
    "\n",
    "fig.update_layout(\n",
    "    title_text = 'Gun Ownership rate',\n",
    "    geo_scope='usa', # limite map scope to USA\n",
    ")\n",
    "\n",
    "fig.show()"
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  {
   "cell_type": "code",
   "execution_count": 32,
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     },
     "metadata": {},
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   ],
   "source": [
    "#Display U.S. history of territory expansion\n",
    "\n",
    "df = pd.read_excel('state_all.xlsx')\n",
    "\n",
    "fig = go.Figure(data=go.Choropleth(\n",
    "    locations=df['Acronym'], # Spatial coordinates\n",
    "    z = df['State year'].astype(float), # Data to be color-coded\n",
    "    locationmode = 'USA-states', # set of locations match entries in `locations`\n",
    "    colorscale = 'blues',\n",
    "    colorbar_title = \"State year\",\n",
    "))\n",
    "\n",
    "\n",
    "\n",
    "fig.update_layout(\n",
    "    title_text = 'U.S. history of territory expansion',\n",
    "    geo_scope='usa', # limite map scope to USA\n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
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   ],
   "source": [
    "#Display police basic training \n",
    "\n",
    "df = pd.read_excel('state_all.xlsx')\n",
    "\n",
    "fig = go.Figure(data=go.Choropleth(\n",
    "    locations=df['Acronym'], # Spatial coordinates\n",
    "    z = df['Police Basic Training hours'].astype(float), # Data to be color-coded\n",
    "    locationmode = 'USA-states', # set of locations match entries in `locations`\n",
    "    colorscale = 'blues',\n",
    "    colorbar_title = \"Police Basic Training hours\",\n",
    "))\n",
    "\n",
    "\n",
    "\n",
    "fig.update_layout(\n",
    "    title_text = 'Police Basic Training hours by state',\n",
    "    geo_scope='usa', # limite map scope to USA\n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
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\"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Average shooting per 1,000,000\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('9f33958d-1af0-4807-9923-f2c03fb78e46');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.express as px\n",
    "df2 =  pd.read_excel('state_all.xlsx')\n",
    "fig2 = px.scatter_geo(df2, locations=\"Acronym\",\n",
    "                     hover_name=\"State\", size=\"Average shooting per 1,000,000\",\n",
    "                     locationmode = 'USA-states')\n",
    "\n",
    "fig2.update_layout(\n",
    "        title = 'Average shooting per 1,000,000',\n",
    "        geo_scope='usa',\n",
    "    )\n",
    "fig2.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "            background-color:  #536edd;\n",
       "            color:  #000000;\n",
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       "            background-color:  #4c66d6;\n",
       "            color:  #000000;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
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       "            background-color:  #ee8468;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f7b599;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col7 {\n",
       "            background-color:  #a7c5fe;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f18d6f;\n",
       "            color:  #000000;\n",
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       "            background-color:  #aac7fd;\n",
       "            color:  #000000;\n",
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       "            background-color:  #89acfd;\n",
       "            color:  #000000;\n",
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       "            background-color:  #6a8bef;\n",
       "            color:  #000000;\n",
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       "            background-color:  #efcfbf;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col13 {\n",
       "            background-color:  #e4d9d2;\n",
       "            color:  #000000;\n",
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       "            background-color:  #5d7ce6;\n",
       "            color:  #000000;\n",
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       "            background-color:  #8caffe;\n",
       "            color:  #000000;\n",
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       "            background-color:  #8caffe;\n",
       "            color:  #000000;\n",
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       "            background-color:  #9ebeff;\n",
       "            color:  #000000;\n",
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       "            background-color:  #88abfd;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f3c7b1;\n",
       "            color:  #000000;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #c9d7f0;\n",
       "            color:  #000000;\n",
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       "            background-color:  #d5dbe5;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f7a688;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col8 {\n",
       "            background-color:  #f1cdba;\n",
       "            color:  #000000;\n",
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       "            background-color:  #efcebd;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f7ba9f;\n",
       "            color:  #000000;\n",
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       "            background-color:  #cbd8ee;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f6bea4;\n",
       "            color:  #000000;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #92b4fe;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col15 {\n",
       "            background-color:  #5977e3;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col0 {\n",
       "            background-color:  #7396f5;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col1 {\n",
       "            background-color:  #4c66d6;\n",
       "            color:  #000000;\n",
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       "            background-color:  #516ddb;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col3 {\n",
       "            background-color:  #f39475;\n",
       "            color:  #000000;\n",
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       "            background-color:  #779af7;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col5 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col6 {\n",
       "            background-color:  #f6bea4;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col7 {\n",
       "            background-color:  #8badfd;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col8 {\n",
       "            background-color:  #f6a385;\n",
       "            color:  #000000;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #7ea1fa;\n",
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       "            background-color:  #93b5fe;\n",
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       "            background-color:  #779af7;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #6485ec;\n",
       "            color:  #000000;\n",
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       "            background-color:  #b3cdfb;\n",
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       "            background-color:  #aac7fd;\n",
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       "            background-color:  #abc8fd;\n",
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       "            background-color:  #f7ad90;\n",
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       "            background-color:  #c3d5f4;\n",
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       "            background-color:  #f6a586;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #97b8ff;\n",
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       "            background-color:  #f6bfa6;\n",
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       "            background-color:  #a5c3fe;\n",
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       "            background-color:  #7da0f9;\n",
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       "            background-color:  #93b5fe;\n",
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       "            background-color:  #a9c6fd;\n",
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       "            background-color:  #c3d5f4;\n",
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       "            background-color:  #6c8ff1;\n",
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       "            background-color:  #80a3fa;\n",
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       "            background-color:  #6180e9;\n",
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       "            background-color:  #6c8ff1;\n",
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       "            background-color:  #799cf8;\n",
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       "            background-color:  #f0cdbb;\n",
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       "            background-color:  #82a6fb;\n",
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       "            background-color:  #4e68d8;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #a5c3fe;\n",
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       "            background-color:  #f7b497;\n",
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       "            background-color:  #f08a6c;\n",
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       "            background-color:  #c5d6f2;\n",
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       "            background-color:  #f0cdbb;\n",
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       "            background-color:  #d3dbe7;\n",
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       "            background-color:  #4a63d3;\n",
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       "            background-color:  #4b64d5;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #f59f80;\n",
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       "            background-color:  #c1d4f4;\n",
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       "            background-color:  #f7a688;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #5f7fe8;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #d6dce4;\n",
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       "            background-color:  #f2cbb7;\n",
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       "            background-color:  #a6c4fe;\n",
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       "            background-color:  #c5d6f2;\n",
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       "            background-color:  #e9d5cb;\n",
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       "            background-color:  #c6d6f1;\n",
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       "            background-color:  #b40426;\n",
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       "            background-color:  #f4c6af;\n",
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       "            background-color:  #a9c6fd;\n",
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       "            background-color:  #f7b599;\n",
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       "            background-color:  #f2cbb7;\n",
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       "            background-color:  #bed2f6;\n",
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       "            background-color:  #7396f5;\n",
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       "            background-color:  #7396f5;\n",
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       "            background-color:  #9fbfff;\n",
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       "            background-color:  #4e68d8;\n",
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       "            background-color:  #a3c2fe;\n",
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       "            background-color:  #84a7fc;\n",
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       "            background-color:  #97b8ff;\n",
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       "            background-color:  #bbd1f8;\n",
       "            color:  #000000;\n",
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       "            background-color:  #84a7fc;\n",
       "            color:  #000000;\n",
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       "            background-color:  #d5dbe5;\n",
       "            color:  #000000;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col14 {\n",
       "            background-color:  #7b9ff9;\n",
       "            color:  #000000;\n",
       "        }    #T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col15 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Total  shooting</th>        <th class=\"col_heading level0 col1\" >Violent crime</th>        <th class=\"col_heading level0 col2\" >Population</th>        <th class=\"col_heading level0 col3\" >Average shooting per 1,000,000</th>        <th class=\"col_heading level0 col4\" >Violent rate per 1,000</th>        <th class=\"col_heading level0 col5\" >State year</th>        <th class=\"col_heading level0 col6\" >Land area(sqmi)</th>        <th class=\"col_heading level0 col7\" >Populatiion per sqmi</th>        <th class=\"col_heading level0 col8\" >Gun Ownership rate</th>        <th class=\"col_heading level0 col9\" >Unemployment rate</th>        <th class=\"col_heading level0 col10\" >Percent black</th>        <th class=\"col_heading level0 col11\" >Bachelor's degree or higher</th>        <th class=\"col_heading level0 col12\" >Poverty Rate</th>        <th class=\"col_heading level0 col13\" >Violent rate</th>        <th class=\"col_heading level0 col14\" >Police Basic Training hours</th>        <th class=\"col_heading level0 col15\" >Month before work</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row0\" class=\"row_heading level0 row0\" >Total  shooting</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col1\" class=\"data row0 col1\" >0.92</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col2\" class=\"data row0 col2\" >0.89</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col3\" class=\"data row0 col3\" >0.13</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col4\" class=\"data row0 col4\" >0.13</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col5\" class=\"data row0 col5\" >0.046</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col6\" class=\"data row0 col6\" >0.26</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col7\" class=\"data row0 col7\" >-0.11</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col8\" class=\"data row0 col8\" >-0.093</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col9\" class=\"data row0 col9\" >0.22</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col10\" class=\"data row0 col10\" >0.05</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col11\" class=\"data row0 col11\" >-0.088</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col12\" class=\"data row0 col12\" >0.16</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col13\" class=\"data row0 col13\" >0.13</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col14\" class=\"data row0 col14\" >-0.008</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row0_col15\" class=\"data row0 col15\" >-0.16</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row1\" class=\"row_heading level0 row1\" >Violent crime</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col0\" class=\"data row1 col0\" >0.92</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col1\" class=\"data row1 col1\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col2\" class=\"data row1 col2\" >0.98</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col3\" class=\"data row1 col3\" >-0.11</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col4\" class=\"data row1 col4\" >0.15</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col5\" class=\"data row1 col5\" >-0.14</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col6\" class=\"data row1 col6\" >0.19</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col7\" class=\"data row1 col7\" >-0.061</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col8\" class=\"data row1 col8\" >-0.21</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col9\" class=\"data row1 col9\" >0.27</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col10\" class=\"data row1 col10\" >0.16</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col11\" class=\"data row1 col11\" >-0.01</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col12\" class=\"data row1 col12\" >0.14</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col13\" class=\"data row1 col13\" >0.15</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col14\" class=\"data row1 col14\" >0.036</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row1_col15\" class=\"data row1 col15\" >-0.13</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row2\" class=\"row_heading level0 row2\" >Population</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col0\" class=\"data row2 col0\" >0.89</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col1\" class=\"data row2 col1\" >0.98</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col2\" class=\"data row2 col2\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col3\" class=\"data row2 col3\" >-0.2</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col4\" class=\"data row2 col4\" >0.02</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col5\" class=\"data row2 col5\" >-0.19</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col6\" class=\"data row2 col6\" >0.15</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col7\" class=\"data row2 col7\" >-0.081</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col8\" class=\"data row2 col8\" >-0.28</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col9\" class=\"data row2 col9\" >0.23</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col10\" class=\"data row2 col10\" >0.14</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col11\" class=\"data row2 col11\" >0.038</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col12\" class=\"data row2 col12\" >0.061</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col13\" class=\"data row2 col13\" >0.02</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col14\" class=\"data row2 col14\" >0.094</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row2_col15\" class=\"data row2 col15\" >-0.12</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row3\" class=\"row_heading level0 row3\" >Average shooting per 1,000,000</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col0\" class=\"data row3 col0\" >0.13</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col1\" class=\"data row3 col1\" >-0.11</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col2\" class=\"data row3 col2\" >-0.2</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col3\" class=\"data row3 col3\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col4\" class=\"data row3 col4\" >0.48</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col5\" class=\"data row3 col5\" >0.68</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col6\" class=\"data row3 col6\" >0.59</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col7\" class=\"data row3 col7\" >-0.093</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col8\" class=\"data row3 col8\" >0.64</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col9\" class=\"data row3 col9\" >0.29</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col10\" class=\"data row3 col10\" >-0.2</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col11\" class=\"data row3 col11\" >-0.36</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col12\" class=\"data row3 col12\" >0.37</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col13\" class=\"data row3 col13\" >0.48</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col14\" class=\"data row3 col14\" >-0.2</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row3_col15\" class=\"data row3 col15\" >0.069</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row4\" class=\"row_heading level0 row4\" >Violent rate per 1,000</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col0\" class=\"data row4 col0\" >0.13</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col1\" class=\"data row4 col1\" >0.15</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col2\" class=\"data row4 col2\" >0.02</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col3\" class=\"data row4 col3\" >0.48</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col4\" class=\"data row4 col4\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col5\" class=\"data row4 col5\" >0.095</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col6\" class=\"data row4 col6\" >0.34</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col7\" class=\"data row4 col7\" >0.54</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col8\" class=\"data row4 col8\" >0.34</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col9\" class=\"data row4 col9\" >0.55</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col10\" class=\"data row4 col10\" >0.46</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col11\" class=\"data row4 col11\" >0.1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col12\" class=\"data row4 col12\" >0.47</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col13\" class=\"data row4 col13\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col14\" class=\"data row4 col14\" >0.0093</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row4_col15\" class=\"data row4 col15\" >-0.12</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row5\" class=\"row_heading level0 row5\" >State year</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col0\" class=\"data row5 col0\" >0.046</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col1\" class=\"data row5 col1\" >-0.14</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col2\" class=\"data row5 col2\" >-0.19</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col3\" class=\"data row5 col3\" >0.68</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col4\" class=\"data row5 col4\" >0.095</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col5\" class=\"data row5 col5\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col6\" class=\"data row5 col6\" >0.56</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col7\" class=\"data row5 col7\" >-0.23</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col8\" class=\"data row5 col8\" >0.55</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col9\" class=\"data row5 col9\" >-0.071</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col10\" class=\"data row5 col10\" >-0.58</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col11\" class=\"data row5 col11\" >-0.26</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col12\" class=\"data row5 col12\" >-0.1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col13\" class=\"data row5 col13\" >0.095</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col14\" class=\"data row5 col14\" >-0.35</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row5_col15\" class=\"data row5 col15\" >-0.072</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row6\" class=\"row_heading level0 row6\" >Land area(sqmi)</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col0\" class=\"data row6 col0\" >0.26</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col1\" class=\"data row6 col1\" >0.19</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col2\" class=\"data row6 col2\" >0.15</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col3\" class=\"data row6 col3\" >0.59</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col4\" class=\"data row6 col4\" >0.34</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col5\" class=\"data row6 col5\" >0.56</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col6\" class=\"data row6 col6\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col7\" class=\"data row6 col7\" >-0.17</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col8\" class=\"data row6 col8\" >0.42</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col9\" class=\"data row6 col9\" >0.27</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col10\" class=\"data row6 col10\" >-0.25</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col11\" class=\"data row6 col11\" >-0.17</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col12\" class=\"data row6 col12\" >-0.0091</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col13\" class=\"data row6 col13\" >0.34</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col14\" class=\"data row6 col14\" >-0.13</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row6_col15\" class=\"data row6 col15\" >0.027</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row7\" class=\"row_heading level0 row7\" >Populatiion per sqmi</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col0\" class=\"data row7 col0\" >-0.11</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col1\" class=\"data row7 col1\" >-0.061</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col2\" class=\"data row7 col2\" >-0.081</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col3\" class=\"data row7 col3\" >-0.093</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col4\" class=\"data row7 col4\" >0.54</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col5\" class=\"data row7 col5\" >-0.23</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col6\" class=\"data row7 col6\" >-0.17</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col7\" class=\"data row7 col7\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col8\" class=\"data row7 col8\" >-0.62</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col9\" class=\"data row7 col9\" >0.27</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col10\" class=\"data row7 col10\" >0.49</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col11\" class=\"data row7 col11\" >0.66</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col12\" class=\"data row7 col12\" >0.12</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col13\" class=\"data row7 col13\" >0.54</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col14\" class=\"data row7 col14\" >0.28</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row7_col15\" class=\"data row7 col15\" >-0.17</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row8\" class=\"row_heading level0 row8\" >Gun Ownership rate</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col0\" class=\"data row8 col0\" >-0.093</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col1\" class=\"data row8 col1\" >-0.21</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col2\" class=\"data row8 col2\" >-0.28</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col3\" class=\"data row8 col3\" >0.64</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col4\" class=\"data row8 col4\" >0.34</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col5\" class=\"data row8 col5\" >0.55</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col6\" class=\"data row8 col6\" >0.42</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col7\" class=\"data row8 col7\" >-0.62</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col8\" class=\"data row8 col8\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col9\" class=\"data row8 col9\" >0.055</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col10\" class=\"data row8 col10\" >-0.12</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col11\" class=\"data row8 col11\" >-0.6</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col12\" class=\"data row8 col12\" >0.38</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col13\" class=\"data row8 col13\" >0.34</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col14\" class=\"data row8 col14\" >-0.35</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row8_col15\" class=\"data row8 col15\" >0.19</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row9\" class=\"row_heading level0 row9\" >Unemployment rate</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col0\" class=\"data row9 col0\" >0.22</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col1\" class=\"data row9 col1\" >0.27</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col2\" class=\"data row9 col2\" >0.23</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col3\" class=\"data row9 col3\" >0.29</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col4\" class=\"data row9 col4\" >0.55</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col5\" class=\"data row9 col5\" >-0.071</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col6\" class=\"data row9 col6\" >0.27</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col7\" class=\"data row9 col7\" >0.27</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col8\" class=\"data row9 col8\" >0.055</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col9\" class=\"data row9 col9\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col10\" class=\"data row9 col10\" >0.4</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col11\" class=\"data row9 col11\" >-0.068</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col12\" class=\"data row9 col12\" >0.51</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col13\" class=\"data row9 col13\" >0.55</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col14\" class=\"data row9 col14\" >0.18</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row9_col15\" class=\"data row9 col15\" >-0.02</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row10\" class=\"row_heading level0 row10\" >Percent black</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col0\" class=\"data row10 col0\" >0.05</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col1\" class=\"data row10 col1\" >0.16</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col2\" class=\"data row10 col2\" >0.14</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col3\" class=\"data row10 col3\" >-0.2</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col4\" class=\"data row10 col4\" >0.46</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col5\" class=\"data row10 col5\" >-0.58</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col6\" class=\"data row10 col6\" >-0.25</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col7\" class=\"data row10 col7\" >0.49</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col8\" class=\"data row10 col8\" >-0.12</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col9\" class=\"data row10 col9\" >0.4</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col10\" class=\"data row10 col10\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col11\" class=\"data row10 col11\" >0.18</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col12\" class=\"data row10 col12\" >0.44</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col13\" class=\"data row10 col13\" >0.46</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col14\" class=\"data row10 col14\" >0.021</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row10_col15\" class=\"data row10 col15\" >0.029</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row11\" class=\"row_heading level0 row11\" >Bachelor's degree or higher</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col0\" class=\"data row11 col0\" >-0.088</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col1\" class=\"data row11 col1\" >-0.01</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col2\" class=\"data row11 col2\" >0.038</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col3\" class=\"data row11 col3\" >-0.36</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col4\" class=\"data row11 col4\" >0.1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col5\" class=\"data row11 col5\" >-0.26</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col6\" class=\"data row11 col6\" >-0.17</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col7\" class=\"data row11 col7\" >0.66</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col8\" class=\"data row11 col8\" >-0.6</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col9\" class=\"data row11 col9\" >-0.068</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col10\" class=\"data row11 col10\" >0.18</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col11\" class=\"data row11 col11\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col12\" class=\"data row11 col12\" >-0.5</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col13\" class=\"data row11 col13\" >0.1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col14\" class=\"data row11 col14\" >0.38</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row11_col15\" class=\"data row11 col15\" >-0.24</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row12\" class=\"row_heading level0 row12\" >Poverty Rate</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col0\" class=\"data row12 col0\" >0.16</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col1\" class=\"data row12 col1\" >0.14</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col2\" class=\"data row12 col2\" >0.061</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col3\" class=\"data row12 col3\" >0.37</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col4\" class=\"data row12 col4\" >0.47</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col5\" class=\"data row12 col5\" >-0.1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col6\" class=\"data row12 col6\" >-0.0091</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col7\" class=\"data row12 col7\" >0.12</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col8\" class=\"data row12 col8\" >0.38</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col9\" class=\"data row12 col9\" >0.51</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col10\" class=\"data row12 col10\" >0.44</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col11\" class=\"data row12 col11\" >-0.5</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col12\" class=\"data row12 col12\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col13\" class=\"data row12 col13\" >0.47</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col14\" class=\"data row12 col14\" >-0.037</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row12_col15\" class=\"data row12 col15\" >0.2</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row13\" class=\"row_heading level0 row13\" >Violent rate</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col0\" class=\"data row13 col0\" >0.13</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col1\" class=\"data row13 col1\" >0.15</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col2\" class=\"data row13 col2\" >0.02</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col3\" class=\"data row13 col3\" >0.48</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col4\" class=\"data row13 col4\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col5\" class=\"data row13 col5\" >0.095</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col6\" class=\"data row13 col6\" >0.34</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col7\" class=\"data row13 col7\" >0.54</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col8\" class=\"data row13 col8\" >0.34</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col9\" class=\"data row13 col9\" >0.55</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col10\" class=\"data row13 col10\" >0.46</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col11\" class=\"data row13 col11\" >0.1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col12\" class=\"data row13 col12\" >0.47</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col13\" class=\"data row13 col13\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col14\" class=\"data row13 col14\" >0.0093</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row13_col15\" class=\"data row13 col15\" >-0.12</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row14\" class=\"row_heading level0 row14\" >Police Basic Training hours</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col0\" class=\"data row14 col0\" >-0.008</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col1\" class=\"data row14 col1\" >0.036</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col2\" class=\"data row14 col2\" >0.094</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col3\" class=\"data row14 col3\" >-0.2</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col4\" class=\"data row14 col4\" >0.0093</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col5\" class=\"data row14 col5\" >-0.35</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col6\" class=\"data row14 col6\" >-0.13</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col7\" class=\"data row14 col7\" >0.28</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col8\" class=\"data row14 col8\" >-0.35</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col9\" class=\"data row14 col9\" >0.18</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col10\" class=\"data row14 col10\" >0.021</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col11\" class=\"data row14 col11\" >0.38</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col12\" class=\"data row14 col12\" >-0.037</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col13\" class=\"data row14 col13\" >0.0093</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col14\" class=\"data row14 col14\" >1</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row14_col15\" class=\"data row14 col15\" >-0.076</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2level0_row15\" class=\"row_heading level0 row15\" >Month before work</th>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col0\" class=\"data row15 col0\" >-0.16</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col1\" class=\"data row15 col1\" >-0.13</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col2\" class=\"data row15 col2\" >-0.12</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col3\" class=\"data row15 col3\" >0.069</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col4\" class=\"data row15 col4\" >-0.12</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col5\" class=\"data row15 col5\" >-0.072</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col6\" class=\"data row15 col6\" >0.027</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col7\" class=\"data row15 col7\" >-0.17</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col8\" class=\"data row15 col8\" >0.19</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col9\" class=\"data row15 col9\" >-0.02</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col10\" class=\"data row15 col10\" >0.029</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col11\" class=\"data row15 col11\" >-0.24</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col12\" class=\"data row15 col12\" >0.2</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col13\" class=\"data row15 col13\" >-0.12</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col14\" class=\"data row15 col14\" >-0.076</td>\n",
       "                        <td id=\"T_2bcb32dc_357d_11eb_a136_8c859016bec2row15_col15\" class=\"data row15 col15\" >1</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fb30cef2ed0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Analyze correlation between polices shooting and other variables\n",
    "state_all = pd.read_excel('state_all.xlsx')\n",
    "corr = state_all.corr()\n",
    "corr.style.background_gradient(cmap='coolwarm').set_precision(2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "            background-color:  #cbd8ee;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col9 {\n",
       "            background-color:  #f6bea4;\n",
       "            color:  #000000;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #92b4fe;\n",
       "            color:  #000000;\n",
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       "            background-color:  #5977e3;\n",
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       "            background-color:  #f39475;\n",
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       "            background-color:  #779af7;\n",
       "            color:  #000000;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col3 {\n",
       "            background-color:  #f6bea4;\n",
       "            color:  #000000;\n",
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       "            background-color:  #8badfd;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f6a385;\n",
       "            color:  #000000;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col8 {\n",
       "            background-color:  #7ea1fa;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col9 {\n",
       "            background-color:  #93b5fe;\n",
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       "            background-color:  #779af7;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #6485ec;\n",
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       "            background-color:  #f7ad90;\n",
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       "            background-color:  #c3d5f4;\n",
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       "            background-color:  #f6a586;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #97b8ff;\n",
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       "            background-color:  #f6bfa6;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col6 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col7 {\n",
       "            background-color:  #7da0f9;\n",
       "            color:  #000000;\n",
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       "            background-color:  #93b5fe;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col9 {\n",
       "            background-color:  #a9c6fd;\n",
       "            color:  #000000;\n",
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       "            background-color:  #c3d5f4;\n",
       "            color:  #000000;\n",
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       "            background-color:  #6c8ff1;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col12 {\n",
       "            background-color:  #80a3fa;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col0 {\n",
       "            background-color:  #799cf8;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col1 {\n",
       "            background-color:  #f0cdbb;\n",
       "            color:  #000000;\n",
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       "            background-color:  #82a6fb;\n",
       "            color:  #000000;\n",
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       "            background-color:  #4e68d8;\n",
       "            color:  #000000;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col5 {\n",
       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col6 {\n",
       "            background-color:  #a5c3fe;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col7 {\n",
       "            background-color:  #f7b497;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f08a6c;\n",
       "            color:  #000000;\n",
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       "            background-color:  #c5d6f2;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f0cdbb;\n",
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       "            background-color:  #d3dbe7;\n",
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       "            background-color:  #4a63d3;\n",
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       "            background-color:  #f59f80;\n",
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       "            background-color:  #c1d4f4;\n",
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       "            background-color:  #e5d8d1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col6 {\n",
       "            background-color:  #5f7fe8;\n",
       "            color:  #000000;\n",
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       "            background-color:  #9abbff;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #f1cdba;\n",
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       "            background-color:  #c1d4f4;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #adc9fd;\n",
       "            color:  #000000;\n",
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       "            background-color:  #d6dce4;\n",
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       "            background-color:  #f2cbb7;\n",
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       "            background-color:  #a6c4fe;\n",
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       "            background-color:  #c5d6f2;\n",
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       "            background-color:  #e9d5cb;\n",
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       "            background-color:  #c6d6f1;\n",
       "            color:  #000000;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col7 {\n",
       "            background-color:  #f4c6af;\n",
       "            color:  #000000;\n",
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       "            background-color:  #a9c6fd;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col9 {\n",
       "            background-color:  #f7b599;\n",
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       "            background-color:  #f2cbb7;\n",
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       "            background-color:  #bed2f6;\n",
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       "            background-color:  #7396f5;\n",
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       "            background-color:  #5e7de7;\n",
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       "            background-color:  #e0dbd8;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #f7b194;\n",
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       "            background-color:  #a2c1ff;\n",
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       "            background-color:  #ccd9ed;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col8 {\n",
       "            background-color:  #d8dce2;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col9 {\n",
       "            background-color:  #f5c2aa;\n",
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       "            background-color:  #e0dbd8;\n",
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       "            background-color:  #94b6ff;\n",
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       "            background-color:  #81a4fb;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #7a9df8;\n",
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       "            background-color:  #7a9df8;\n",
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       "            background-color:  #4e68d8;\n",
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       "            background-color:  #ef886b;\n",
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       "            background-color:  #3f53c6;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #3b4cc0;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #d7dce3;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col9 {\n",
       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #7a9df8;\n",
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       "            background-color:  #3b4cc0;\n",
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       "            background-color:  #e5d8d1;\n",
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       "            background-color:  #e2dad5;\n",
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       "            background-color:  #9ebeff;\n",
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       "            background-color:  #799cf8;\n",
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       "            background-color:  #d2dbe8;\n",
       "            color:  #000000;\n",
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       "            background-color:  #f4c6af;\n",
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       "            background-color:  #e7d7ce;\n",
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       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col7 {\n",
       "            background-color:  #f6bea4;\n",
       "            color:  #000000;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col8 {\n",
       "            background-color:  #4b64d5;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col9 {\n",
       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #e2dad5;\n",
       "            color:  #000000;\n",
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       "            background-color:  #85a8fc;\n",
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       "            background-color:  #b2ccfb;\n",
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       "            background-color:  #f3c7b1;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
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       "            background-color:  #c9d7f0;\n",
       "            color:  #000000;\n",
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       "            background-color:  #d5dbe5;\n",
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       "            background-color:  #b40426;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Average shooting per 1,000,000</th>        <th class=\"col_heading level0 col1\" >Violent rate per 1,000</th>        <th class=\"col_heading level0 col2\" >State year</th>        <th class=\"col_heading level0 col3\" >Land area(sqmi)</th>        <th class=\"col_heading level0 col4\" >Populatiion per sqmi</th>        <th class=\"col_heading level0 col5\" >Gun Ownership rate</th>        <th class=\"col_heading level0 col6\" >Unemployment rate</th>        <th class=\"col_heading level0 col7\" >Percent black</th>        <th class=\"col_heading level0 col8\" >Bachelor's degree or higher</th>        <th class=\"col_heading level0 col9\" >Poverty Rate</th>        <th class=\"col_heading level0 col10\" >Violent rate</th>        <th class=\"col_heading level0 col11\" >Police Basic Training hours</th>        <th class=\"col_heading level0 col12\" >Month before work</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row0\" class=\"row_heading level0 row0\" >Average shooting per 1,000,000</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col1\" class=\"data row0 col1\" >0.48</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col2\" class=\"data row0 col2\" >0.68</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col3\" class=\"data row0 col3\" >0.59</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col4\" class=\"data row0 col4\" >-0.093</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col5\" class=\"data row0 col5\" >0.64</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col6\" class=\"data row0 col6\" >0.29</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col7\" class=\"data row0 col7\" >-0.2</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col8\" class=\"data row0 col8\" >-0.36</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col9\" class=\"data row0 col9\" >0.37</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col10\" class=\"data row0 col10\" >0.48</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col11\" class=\"data row0 col11\" >-0.2</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row0_col12\" class=\"data row0 col12\" >0.069</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row1\" class=\"row_heading level0 row1\" >Violent rate per 1,000</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col0\" class=\"data row1 col0\" >0.48</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col1\" class=\"data row1 col1\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col2\" class=\"data row1 col2\" >0.095</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col3\" class=\"data row1 col3\" >0.34</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col4\" class=\"data row1 col4\" >0.54</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col5\" class=\"data row1 col5\" >0.34</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col6\" class=\"data row1 col6\" >0.55</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col7\" class=\"data row1 col7\" >0.46</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col8\" class=\"data row1 col8\" >0.1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col9\" class=\"data row1 col9\" >0.47</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col10\" class=\"data row1 col10\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col11\" class=\"data row1 col11\" >0.0093</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row1_col12\" class=\"data row1 col12\" >-0.12</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row2\" class=\"row_heading level0 row2\" >State year</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col0\" class=\"data row2 col0\" >0.68</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col1\" class=\"data row2 col1\" >0.095</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col2\" class=\"data row2 col2\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col3\" class=\"data row2 col3\" >0.56</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col4\" class=\"data row2 col4\" >-0.23</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col5\" class=\"data row2 col5\" >0.55</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col6\" class=\"data row2 col6\" >-0.071</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col7\" class=\"data row2 col7\" >-0.58</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col8\" class=\"data row2 col8\" >-0.26</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col9\" class=\"data row2 col9\" >-0.1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col10\" class=\"data row2 col10\" >0.095</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col11\" class=\"data row2 col11\" >-0.35</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row2_col12\" class=\"data row2 col12\" >-0.072</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row3\" class=\"row_heading level0 row3\" >Land area(sqmi)</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col0\" class=\"data row3 col0\" >0.59</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col1\" class=\"data row3 col1\" >0.34</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col2\" class=\"data row3 col2\" >0.56</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col3\" class=\"data row3 col3\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col4\" class=\"data row3 col4\" >-0.17</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col5\" class=\"data row3 col5\" >0.42</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col6\" class=\"data row3 col6\" >0.27</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col7\" class=\"data row3 col7\" >-0.25</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col8\" class=\"data row3 col8\" >-0.17</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col9\" class=\"data row3 col9\" >-0.0091</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col10\" class=\"data row3 col10\" >0.34</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col11\" class=\"data row3 col11\" >-0.13</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row3_col12\" class=\"data row3 col12\" >0.027</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row4\" class=\"row_heading level0 row4\" >Populatiion per sqmi</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col0\" class=\"data row4 col0\" >-0.093</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col1\" class=\"data row4 col1\" >0.54</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col2\" class=\"data row4 col2\" >-0.23</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col3\" class=\"data row4 col3\" >-0.17</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col4\" class=\"data row4 col4\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col5\" class=\"data row4 col5\" >-0.62</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col6\" class=\"data row4 col6\" >0.27</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col7\" class=\"data row4 col7\" >0.49</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col8\" class=\"data row4 col8\" >0.66</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col9\" class=\"data row4 col9\" >0.12</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col10\" class=\"data row4 col10\" >0.54</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col11\" class=\"data row4 col11\" >0.28</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row4_col12\" class=\"data row4 col12\" >-0.17</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row5\" class=\"row_heading level0 row5\" >Gun Ownership rate</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col0\" class=\"data row5 col0\" >0.64</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col1\" class=\"data row5 col1\" >0.34</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col2\" class=\"data row5 col2\" >0.55</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col3\" class=\"data row5 col3\" >0.42</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col4\" class=\"data row5 col4\" >-0.62</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col5\" class=\"data row5 col5\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col6\" class=\"data row5 col6\" >0.055</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col7\" class=\"data row5 col7\" >-0.12</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col8\" class=\"data row5 col8\" >-0.6</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col9\" class=\"data row5 col9\" >0.38</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col10\" class=\"data row5 col10\" >0.34</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col11\" class=\"data row5 col11\" >-0.35</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row5_col12\" class=\"data row5 col12\" >0.19</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row6\" class=\"row_heading level0 row6\" >Unemployment rate</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col0\" class=\"data row6 col0\" >0.29</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col1\" class=\"data row6 col1\" >0.55</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col2\" class=\"data row6 col2\" >-0.071</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col3\" class=\"data row6 col3\" >0.27</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col4\" class=\"data row6 col4\" >0.27</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col5\" class=\"data row6 col5\" >0.055</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col6\" class=\"data row6 col6\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col7\" class=\"data row6 col7\" >0.4</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col8\" class=\"data row6 col8\" >-0.068</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col9\" class=\"data row6 col9\" >0.51</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col10\" class=\"data row6 col10\" >0.55</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col11\" class=\"data row6 col11\" >0.18</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row6_col12\" class=\"data row6 col12\" >-0.02</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row7\" class=\"row_heading level0 row7\" >Percent black</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col0\" class=\"data row7 col0\" >-0.2</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col1\" class=\"data row7 col1\" >0.46</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col2\" class=\"data row7 col2\" >-0.58</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col3\" class=\"data row7 col3\" >-0.25</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col4\" class=\"data row7 col4\" >0.49</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col5\" class=\"data row7 col5\" >-0.12</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col6\" class=\"data row7 col6\" >0.4</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col7\" class=\"data row7 col7\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col8\" class=\"data row7 col8\" >0.18</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col9\" class=\"data row7 col9\" >0.44</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col10\" class=\"data row7 col10\" >0.46</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col11\" class=\"data row7 col11\" >0.021</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row7_col12\" class=\"data row7 col12\" >0.029</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row8\" class=\"row_heading level0 row8\" >Bachelor's degree or higher</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col0\" class=\"data row8 col0\" >-0.36</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col1\" class=\"data row8 col1\" >0.1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col2\" class=\"data row8 col2\" >-0.26</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col3\" class=\"data row8 col3\" >-0.17</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col4\" class=\"data row8 col4\" >0.66</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col5\" class=\"data row8 col5\" >-0.6</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col6\" class=\"data row8 col6\" >-0.068</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col7\" class=\"data row8 col7\" >0.18</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col8\" class=\"data row8 col8\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col9\" class=\"data row8 col9\" >-0.5</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col10\" class=\"data row8 col10\" >0.1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col11\" class=\"data row8 col11\" >0.38</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row8_col12\" class=\"data row8 col12\" >-0.24</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row9\" class=\"row_heading level0 row9\" >Poverty Rate</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col0\" class=\"data row9 col0\" >0.37</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col1\" class=\"data row9 col1\" >0.47</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col2\" class=\"data row9 col2\" >-0.1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col3\" class=\"data row9 col3\" >-0.0091</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col4\" class=\"data row9 col4\" >0.12</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col5\" class=\"data row9 col5\" >0.38</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col6\" class=\"data row9 col6\" >0.51</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col7\" class=\"data row9 col7\" >0.44</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col8\" class=\"data row9 col8\" >-0.5</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col9\" class=\"data row9 col9\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col10\" class=\"data row9 col10\" >0.47</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col11\" class=\"data row9 col11\" >-0.037</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row9_col12\" class=\"data row9 col12\" >0.2</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row10\" class=\"row_heading level0 row10\" >Violent rate</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col0\" class=\"data row10 col0\" >0.48</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col1\" class=\"data row10 col1\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col2\" class=\"data row10 col2\" >0.095</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col3\" class=\"data row10 col3\" >0.34</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col4\" class=\"data row10 col4\" >0.54</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col5\" class=\"data row10 col5\" >0.34</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col6\" class=\"data row10 col6\" >0.55</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col7\" class=\"data row10 col7\" >0.46</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col8\" class=\"data row10 col8\" >0.1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col9\" class=\"data row10 col9\" >0.47</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col10\" class=\"data row10 col10\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col11\" class=\"data row10 col11\" >0.0093</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row10_col12\" class=\"data row10 col12\" >-0.12</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row11\" class=\"row_heading level0 row11\" >Police Basic Training hours</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col0\" class=\"data row11 col0\" >-0.2</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col1\" class=\"data row11 col1\" >0.0093</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col2\" class=\"data row11 col2\" >-0.35</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col3\" class=\"data row11 col3\" >-0.13</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col4\" class=\"data row11 col4\" >0.28</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col5\" class=\"data row11 col5\" >-0.35</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col6\" class=\"data row11 col6\" >0.18</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col7\" class=\"data row11 col7\" >0.021</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col8\" class=\"data row11 col8\" >0.38</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col9\" class=\"data row11 col9\" >-0.037</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col10\" class=\"data row11 col10\" >0.0093</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col11\" class=\"data row11 col11\" >1</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row11_col12\" class=\"data row11 col12\" >-0.076</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2level0_row12\" class=\"row_heading level0 row12\" >Month before work</th>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col0\" class=\"data row12 col0\" >0.069</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col1\" class=\"data row12 col1\" >-0.12</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col2\" class=\"data row12 col2\" >-0.072</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col3\" class=\"data row12 col3\" >0.027</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col4\" class=\"data row12 col4\" >-0.17</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col5\" class=\"data row12 col5\" >0.19</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col6\" class=\"data row12 col6\" >-0.02</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col7\" class=\"data row12 col7\" >0.029</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col8\" class=\"data row12 col8\" >-0.24</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col9\" class=\"data row12 col9\" >0.2</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col10\" class=\"data row12 col10\" >-0.12</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col11\" class=\"data row12 col11\" >-0.076</td>\n",
       "                        <td id=\"T_24657eb8_382e_11eb_8e12_8c859016bec2row12_col12\" class=\"data row12 col12\" >1</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fa752e10190>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Analyze correlation between polices shooting and other variables\n",
    "state_all = pd.read_excel('state_all1.xlsx')\n",
    "corr = state_all.corr()\n",
    "corr.style.background_gradient(cmap='coolwarm').set_precision(2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.425396041156865"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import math\n",
    "0.68*math.sqrt(48/(1-0.68*0.68))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "state_all = pd.read_excel(\"state_all.xlsx\")\n",
    "ax = sns.boxplot(x='Marijuana Legality', y='Average shooting per 1,000,000', data=state_all)\n",
    "ax = sns.swarmplot(x='Marijuana Legality', y='Average shooting per 1,000,000', data=state_all, color='0.25')\n",
    "# Select which box to change color    \n",
    "fl = ax.artists[0]\n",
    "ml = ax.artists[1]\n",
    "fi = ax.artists[2]\n",
    "\n",
    "# Change the appearance of that box\n",
    "fl.set_facecolor('tab:blue')\n",
    "ml.set_facecolor('tab:gray')\n",
    "fi.set_facecolor('tab:red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ANOVA test is done by R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.boxplot(x='Governor Party', y='Average shooting per 1,000,000', data=state_all)\n",
    "ax = sns.swarmplot(x='Governor Party', y='Average shooting per 1,000,000', data=state_all, color='0.25')\n",
    "\n",
    "# Select which box to change color    \n",
    "Republican = ax.artists[0]\n",
    "Democrat = ax.artists[1]\n",
    "\n",
    "# Change the appearance of that box\n",
    "Republican.set_facecolor('tab:red')\n",
    "Democrat.set_facecolor('tab:blue')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=-0.9935600797734223, pvalue=0.32539634692674047)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# t test \n",
    "from scipy import stats\n",
    "\n",
    "de = state_all.loc[state_all['Governor Party'] == 'Democrat', 'Average shooting per 1,000,000']\n",
    "re = state_all.loc[state_all['Governor Party'] == 'Republican', 'Average shooting per 1,000,000']\n",
    "\n",
    "stats.ttest_ind(de,re, equal_var = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=0.9256428704805298, pvalue=0.36215753167284326)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# t test \n",
    "import pandas as pd\n",
    "from scipy import stats\n",
    "state1 = pd.read_excel('state1.xlsx')\n",
    "\n",
    "de = state1.loc[state_all['Governor Party'] == 'Democrat', 'Total shooting']\n",
    "re = state1.loc[state_all['Governor Party'] == 'Republican', 'Total shooting']\n",
    "\n",
    "stats.ttest_ind(de,re, equal_var = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}