Cookbook_Seaborn_regplot_and_lmplot_transparent.ipynb

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  "metadata": {
    "colab": {
      "name": "Seaborn regplot and lmplot transparent cookbook",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/RandomForestRanger/first/blob/master/Seaborn_regplot_and_lmplot_transparent_cookbook.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FdHuVZrD-9LB",
        "colab_type": "code",
        "outputId": "0557cfc0-5511-4ac3-f467-8c988f0846be",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        }
      },
      "source": [
        "# pip installing...\n",
        "\n",
        "!pip install --upgrade -q gspread\n",
        "!pip install gspread-dataframe"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: gspread-dataframe in /usr/local/lib/python3.6/dist-packages (3.0.2)\n",
            "Requirement already satisfied: pandas>=0.14.0 in /usr/local/lib/python3.6/dist-packages (from gspread-dataframe) (0.22.0)\n",
            "Requirement already satisfied: gspread>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from gspread-dataframe) (3.0.1)\n",
            "Requirement already satisfied: numpy>=1.9.0 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.14.0->gspread-dataframe) (1.14.6)\n",
            "Requirement already satisfied: pytz>=2011k in /usr/local/lib/python3.6/dist-packages (from pandas>=0.14.0->gspread-dataframe) (2018.7)\n",
            "Requirement already satisfied: python-dateutil>=2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.14.0->gspread-dataframe) (2.5.3)\n",
            "Requirement already satisfied: requests>=2.2.1 in /usr/local/lib/python3.6/dist-packages (from gspread>=3.0.0->gspread-dataframe) (2.18.4)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2->pandas>=0.14.0->gspread-dataframe) (1.11.0)\n",
            "Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests>=2.2.1->gspread>=3.0.0->gspread-dataframe) (3.0.4)\n",
            "Requirement already satisfied: urllib3<1.23,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests>=2.2.1->gspread>=3.0.0->gspread-dataframe) (1.22)\n",
            "Requirement already satisfied: idna<2.7,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests>=2.2.1->gspread>=3.0.0->gspread-dataframe) (2.6)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests>=2.2.1->gspread>=3.0.0->gspread-dataframe) (2018.10.15)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fC_0SaeQ_28l",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#import libraries\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import gspread\n",
        "from gspread_dataframe import get_as_dataframe, set_with_dataframe\n",
        "import seaborn as sns"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1zK0VVF75xPK",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#authorise node to access Gdrive via KDL\n",
        "from google.colab import auth\n",
        "auth.authenticate_user()\n",
        "from oauth2client.client import GoogleCredentials\n",
        "gc = gspread.authorize(GoogleCredentials.get_application_default())"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6N-SR1bJ6Tr2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#link to pre-opened csv file in my gdrive \n",
        "data1 = gc.open_by_url('')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "77NVIc3h9-4w",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#get the data as a worksheet  \n",
        "ws = data1.worksheet('woer')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-KYOnKml-6KD",
        "colab_type": "code",
        "outputId": "e75509bd-4348-422c-ac5d-284ef4bbcdde",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        }
      },
      "source": [
        "#convert the data to pandas dataframe (can include argument , header = None   if this is needed)\n",
        "Woer = get_as_dataframe(ws)\n",
        "#inspect data\n",
        "Woer.tail()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>data_id</th>\n",
              "      <th>event_id_cnty</th>\n",
              "      <th>event_id_no_cnty</th>\n",
              "      <th>event_date</th>\n",
              "      <th>year</th>\n",
              "      <th>time_precision</th>\n",
              "      <th>event_type</th>\n",
              "      <th>actor1</th>\n",
              "      <th>assoc_actor_1</th>\n",
              "      <th>inter1</th>\n",
              "      <th>...</th>\n",
              "      <th>longitude</th>\n",
              "      <th>geo_precision</th>\n",
              "      <th>source</th>\n",
              "      <th>source_scale</th>\n",
              "      <th>notes</th>\n",
              "      <th>fatalities</th>\n",
              "      <th>timestamp</th>\n",
              "      <th>iso3</th>\n",
              "      <th>Unnamed: 29</th>\n",
              "      <th>Unnamed: 30</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>10315</th>\n",
              "      <td>1576916.0</td>\n",
              "      <td>SAF3</td>\n",
              "      <td>3.0</td>\n",
              "      <td>14-Jan-97</td>\n",
              "      <td>1997</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Strategic development</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>...</td>\n",
              "      <td>30.8833</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Reuters News</td>\n",
              "      <td>International</td>\n",
              "      <td>Defusal: A group of unknown men place a bomb i...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.524054e+09</td>\n",
              "      <td>ZAF</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10316</th>\n",
              "      <td>1576955.0</td>\n",
              "      <td>SAF2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>09-Jan-97</td>\n",
              "      <td>1997</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Riots/Protests</td>\n",
              "      <td>Protesters (South Africa)</td>\n",
              "      <td>NUM: National Union of Mineworkers</td>\n",
              "      <td>6.0</td>\n",
              "      <td>...</td>\n",
              "      <td>27.2500</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Reuters News</td>\n",
              "      <td>International</td>\n",
              "      <td>The NUM, the mining union which the Rustenburg...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.524054e+09</td>\n",
              "      <td>ZAF</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10317</th>\n",
              "      <td>1977965.0</td>\n",
              "      <td>SAF1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>05-Jan-97</td>\n",
              "      <td>1997</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Remote violence</td>\n",
              "      <td>BAT: Boere Attack Troop</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>...</td>\n",
              "      <td>27.2500</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Reuters News</td>\n",
              "      <td>International</td>\n",
              "      <td>The Boere Attack Troop, a far right group, det...</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.542152e+09</td>\n",
              "      <td>ZAF</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10318</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10319</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 31 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         data_id event_id_cnty  event_id_no_cnty event_date  year  \\\n",
              "10315  1576916.0          SAF3               3.0  14-Jan-97  1997   \n",
              "10316  1576955.0          SAF2               2.0  09-Jan-97  1997   \n",
              "10317  1977965.0          SAF1               1.0  05-Jan-97  1997   \n",
              "10318        NaN           NaN               NaN        NaN   NaN   \n",
              "10319        NaN           NaN               NaN        NaN   NaN   \n",
              "\n",
              "       time_precision             event_type  \\\n",
              "10315             1.0  Strategic development   \n",
              "10316             1.0         Riots/Protests   \n",
              "10317             1.0        Remote violence   \n",
              "10318             NaN                    NaN   \n",
              "10319             NaN                    NaN   \n",
              "\n",
              "                                        actor1  \\\n",
              "10315  Unidentified Armed Group (South Africa)   \n",
              "10316                Protesters (South Africa)   \n",
              "10317                  BAT: Boere Attack Troop   \n",
              "10318                                      NaN   \n",
              "10319                                      NaN   \n",
              "\n",
              "                            assoc_actor_1  inter1     ...     longitude  \\\n",
              "10315                                 NaN     3.0     ...       30.8833   \n",
              "10316  NUM: National Union of Mineworkers     6.0     ...       27.2500   \n",
              "10317                                 NaN     3.0     ...       27.2500   \n",
              "10318                                 NaN     NaN     ...           NaN   \n",
              "10319                                 NaN     NaN     ...           NaN   \n",
              "\n",
              "      geo_precision        source   source_scale  \\\n",
              "10315           1.0  Reuters News  International   \n",
              "10316           1.0  Reuters News  International   \n",
              "10317           1.0  Reuters News  International   \n",
              "10318           NaN           NaN            NaN   \n",
              "10319           NaN           NaN            NaN   \n",
              "\n",
              "                                                   notes fatalities  \\\n",
              "10315  Defusal: A group of unknown men place a bomb i...        0.0   \n",
              "10316  The NUM, the mining union which the Rustenburg...        0.0   \n",
              "10317  The Boere Attack Troop, a far right group, det...        4.0   \n",
              "10318                                                NaN        NaN   \n",
              "10319                                                NaN        NaN   \n",
              "\n",
              "          timestamp iso3 Unnamed: 29 Unnamed: 30  \n",
              "10315  1.524054e+09  ZAF         NaN         NaN  \n",
              "10316  1.524054e+09  ZAF         NaN         NaN  \n",
              "10317  1.542152e+09  ZAF         NaN         NaN  \n",
              "10318           NaN  NaN         NaN         NaN  \n",
              "10319           NaN  NaN         NaN         NaN  \n",
              "\n",
              "[5 rows x 31 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "agDus57n9-_S",
        "colab_type": "code",
        "outputId": "58f028fb-75e5-47ff-e512-1a460659d819",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 559
        }
      },
      "source": [
        "#since g-sheets brings along a lot of empty/Nan cellumns or rows, this chops them out. Can replace \"all\" with \"any\" if I want to discard any incomplete collumns or rows\n",
        "Woer.dropna(axis=1, how='all' ,inplace=True )\n",
        "Woer.dropna(axis=0, how='all', thresh=None, subset=None, inplace=True)\n",
        "Woer.tail()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>data_id</th>\n",
              "      <th>event_id_cnty</th>\n",
              "      <th>event_id_no_cnty</th>\n",
              "      <th>event_date</th>\n",
              "      <th>year</th>\n",
              "      <th>time_precision</th>\n",
              "      <th>event_type</th>\n",
              "      <th>actor1</th>\n",
              "      <th>assoc_actor_1</th>\n",
              "      <th>inter1</th>\n",
              "      <th>...</th>\n",
              "      <th>location</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>geo_precision</th>\n",
              "      <th>source</th>\n",
              "      <th>source_scale</th>\n",
              "      <th>notes</th>\n",
              "      <th>fatalities</th>\n",
              "      <th>timestamp</th>\n",
              "      <th>iso3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>10313</th>\n",
              "      <td>1576757.0</td>\n",
              "      <td>SAF6</td>\n",
              "      <td>6.0</td>\n",
              "      <td>06-Feb-97</td>\n",
              "      <td>1997</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Riots/Protests</td>\n",
              "      <td>Protesters (South Africa)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6.0</td>\n",
              "      <td>...</td>\n",
              "      <td>Soweto</td>\n",
              "      <td>-26.2667</td>\n",
              "      <td>27.8667</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Reuters News</td>\n",
              "      <td>International</td>\n",
              "      <td>A group of demonstrators blocked roadways in p...</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.524054e+09</td>\n",
              "      <td>ZAF</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10314</th>\n",
              "      <td>1576784.0</td>\n",
              "      <td>SAF4</td>\n",
              "      <td>4.0</td>\n",
              "      <td>01-Feb-97</td>\n",
              "      <td>1997</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Battle-No change of territory</td>\n",
              "      <td>Unidentified Armed Group (South Africa)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>...</td>\n",
              "      <td>Johannesburg</td>\n",
              "      <td>-26.2023</td>\n",
              "      <td>28.0436</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Reuters News</td>\n",
              "      <td>International</td>\n",
              "      <td>A group of robbers steal 50 guns from a police...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.524054e+09</td>\n",
              "      <td>ZAF</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10315</th>\n",
              "      <td>1576916.0</td>\n",
              "      <td>SAF3</td>\n",
              "      <td>3.0</td>\n",
              "      <td>14-Jan-97</td>\n",
              "      <td>1997</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Strategic development</td>\n",
              "      <td>Unidentified Armed Group (South Africa)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>...</td>\n",
              "      <td>Amanzimtoti</td>\n",
              "      <td>-30.0500</td>\n",
              "      <td>30.8833</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Reuters News</td>\n",
              "      <td>International</td>\n",
              "      <td>Defusal: A group of unknown men place a bomb i...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.524054e+09</td>\n",
              "      <td>ZAF</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10316</th>\n",
              "      <td>1576955.0</td>\n",
              "      <td>SAF2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>09-Jan-97</td>\n",
              "      <td>1997</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Riots/Protests</td>\n",
              "      <td>Protesters (South Africa)</td>\n",
              "      <td>NUM: National Union of Mineworkers</td>\n",
              "      <td>6.0</td>\n",
              "      <td>...</td>\n",
              "      <td>Rustenburg</td>\n",
              "      <td>-25.6667</td>\n",
              "      <td>27.2500</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Reuters News</td>\n",
              "      <td>International</td>\n",
              "      <td>The NUM, the mining union which the Rustenburg...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.524054e+09</td>\n",
              "      <td>ZAF</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10317</th>\n",
              "      <td>1977965.0</td>\n",
              "      <td>SAF1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>05-Jan-97</td>\n",
              "      <td>1997</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Remote violence</td>\n",
              "      <td>BAT: Boere Attack Troop</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>...</td>\n",
              "      <td>Rustenburg</td>\n",
              "      <td>-25.6667</td>\n",
              "      <td>27.2500</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Reuters News</td>\n",
              "      <td>International</td>\n",
              "      <td>The Boere Attack Troop, a far right group, det...</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.542152e+09</td>\n",
              "      <td>ZAF</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 29 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         data_id event_id_cnty  event_id_no_cnty event_date  year  \\\n",
              "10313  1576757.0          SAF6               6.0  06-Feb-97  1997   \n",
              "10314  1576784.0          SAF4               4.0  01-Feb-97  1997   \n",
              "10315  1576916.0          SAF3               3.0  14-Jan-97  1997   \n",
              "10316  1576955.0          SAF2               2.0  09-Jan-97  1997   \n",
              "10317  1977965.0          SAF1               1.0  05-Jan-97  1997   \n",
              "\n",
              "       time_precision                     event_type  \\\n",
              "10313             1.0                 Riots/Protests   \n",
              "10314             2.0  Battle-No change of territory   \n",
              "10315             1.0          Strategic development   \n",
              "10316             1.0                 Riots/Protests   \n",
              "10317             1.0                Remote violence   \n",
              "\n",
              "                                        actor1  \\\n",
              "10313                Protesters (South Africa)   \n",
              "10314  Unidentified Armed Group (South Africa)   \n",
              "10315  Unidentified Armed Group (South Africa)   \n",
              "10316                Protesters (South Africa)   \n",
              "10317                  BAT: Boere Attack Troop   \n",
              "\n",
              "                            assoc_actor_1  inter1 ...       location latitude  \\\n",
              "10313                                 NaN     6.0 ...         Soweto -26.2667   \n",
              "10314                                 NaN     3.0 ...   Johannesburg -26.2023   \n",
              "10315                                 NaN     3.0 ...    Amanzimtoti -30.0500   \n",
              "10316  NUM: National Union of Mineworkers     6.0 ...     Rustenburg -25.6667   \n",
              "10317                                 NaN     3.0 ...     Rustenburg -25.6667   \n",
              "\n",
              "       longitude  geo_precision        source   source_scale  \\\n",
              "10313    27.8667            1.0  Reuters News  International   \n",
              "10314    28.0436            1.0  Reuters News  International   \n",
              "10315    30.8833            1.0  Reuters News  International   \n",
              "10316    27.2500            1.0  Reuters News  International   \n",
              "10317    27.2500            1.0  Reuters News  International   \n",
              "\n",
              "                                                   notes fatalities  \\\n",
              "10313  A group of demonstrators blocked roadways in p...        4.0   \n",
              "10314  A group of robbers steal 50 guns from a police...        0.0   \n",
              "10315  Defusal: A group of unknown men place a bomb i...        0.0   \n",
              "10316  The NUM, the mining union which the Rustenburg...        0.0   \n",
              "10317  The Boere Attack Troop, a far right group, det...        4.0   \n",
              "\n",
              "          timestamp iso3  \n",
              "10313  1.524054e+09  ZAF  \n",
              "10314  1.524054e+09  ZAF  \n",
              "10315  1.524054e+09  ZAF  \n",
              "10316  1.524054e+09  ZAF  \n",
              "10317  1.542152e+09  ZAF  \n",
              "\n",
              "[5 rows x 29 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XP7Il_lAFnQx",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "sns.set_style(\"whitegrid\", {'axes.grid' : False})"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Dfw-ez-AXMz",
        "colab_type": "code",
        "outputId": "cd889aa1-dc22-4aa9-a29a-2db97d649d8b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1770
        }
      },
      "source": [
        "sns.lmplot(x='longitude', y='latitude', data = Woer, scatter_kws={'alpha':0.20}, fit_reg = False, size = 24, hue= \"event_type\", palette= 'Set1', aspect = 1)\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f5173faaf60>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        },
        {
          "output_type": "display_data",
          "data": {
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9BaoictlG27IX\nSh9iyecGq24PBCOX/JjaglpEpP7Mei9ARERERERkphltKzi5fPaePWQfe7y07ajr4vT1kX3scew9\ne+q9NJkGVm7YNK76pcg8/DCZB7bjnD1b+h48e5bMA9vJPPxwxXnBO7cSX3ol/oKLr1iaw+orejSl\nHaKhBs7srJ7tOBbRYO05oCPVL1f29+9l/qlBAgUXA1jQs6TmeQt6llA0YTBicdw+Te6ppym8dhD7\nrbcQfs+7MRsbwTQxGxsJve2tbAotY9HpLgy3iAcYbpFFp7vYFFpW8/ojdYGJiExnQ1vzjlRvXrii\n5u0j1UVEZGZQB6uIiIiIiMg4XWwrOLk89q7dI9bVxSpX/dp7gdLM1WwuRzgUYuWGTeX6RMg/9sSI\n9eFdrLFt2wDwffmXzB9wwLQgGMSMhYFL3/5xbdsbKmawDq9PBuf5F4nmHKIZByh1rNbizwfh3I6/\n6QYfXjZHYf8BCqtX0/i+9+G+610VW1ZGfnSEzU4Eho9nTcwnXKz9ef+hbi8RmZtm6viFi23ZOzRn\ntbfrMHY+QyAYoXnhikuavyoiItOHAlYREREREZFxuthWcCOZqW8cTjWnxizH0eoy91z1a++d0ED1\nQk5f35jrsW3bCH3/6+Rz1dv3Xur2j0NzVvcfeY7BfJpoMMbatjdc8vxVN5lkz39+D6eyJ8n5DUIF\njyWJlVz3nR+UTihWzostBPM1Q9ZCMA+lRl0sB3CLuINp/GYpdb1wy8qVG7fyyvM/rLrOiuvfUnOd\nI3WBicjsN9PHL1xsy96mBa0KVEVEZhkFrCIiIiIiIuNktbRUvAk4vD6Smf7G4VSyGhtrBllWY2Md\nViNzkRWPl7YHrlGvpeXm2zn++A9q1i/VmmvefMmB6nBuMsmeD/wGr7unwW8A0J3w0RE/xS8+chsr\n3/4bNCwI0tLlgVPqYO1uPskVJ6u3ruyef5LEuZ3Qm3tzePEcbncPwUd3kI0dwN/ejq+trXx+25vf\nCcDhvT9nMJsiGm5gxbo30fbmd+oDJzPEk/d9mL3J18gEPCK2wbrEat786a/We1kyC402fkG/G0RE\nZDpSwCoiIiIiIjJOF9sKrha9cTh2gY0byD5WPbsysHFDHVYjc1HwjtvIPLC9Zr2Wpb9/LwBndj5e\n3v6x5ebby/V6cs6c4VT+VDlcTcUsuhaUOk6TziCD2QHObGyFZw/Tci5T/tTXfsZ//dBbWdC7BH8+\nSCGYp3v+STYf3A0uhHMOS9J+fH2DtLSvwjlzhkOvvoz93I+JrGxn4RveQmLVNUApZB0KWoe7WLeX\n1N+T932YZ9Id4Ac8SPu90vF9H1bIKhNupDELJ776JXoP7cUu5gn4grRsehPL/vSzU7w6ERGRagpY\nRURERERELsF4wwHNbR27oTmr9q7dOAMDWI2NBDZu0PxVmTJDc1bzjz2B09eHFY8TvOO2ivmrF1r6\n+/dOi0D1Ql4+T+5cuArQF/eXvy5YpX8jb93KqeJjtDxxGAoF8Pn49DNdNH/29ygcPMiJv/0qA2dP\nUDA9/EWPRl8D89rXEVh1PemQyemuQ+VrZo8f5XjoaYByyCoz097ka6VwtUb98nurJ5Y6ome+WuMX\nTv7dX3Pyl8+DWfodli9kOb7jYfgzFLKKiEjdKWAVERERERGZApc6t3WuCqxfr0BV6irytreNGqjO\nFEYwSKjgkT0XstqB82Gr3xl23h1vYsG9X8XL589/8MMwMGMxlt/35xiNDRXXzT31NNaihZzteKGi\n7tml+/Yc3DOtA9a9H7qb4yf3k/N5hIoGS5esZd3XvlvvZU0rmYBXnrlbVZ9GtAX/7FBr/ELPgZfA\nqD73zPM/Z9kUrUtERGQkZr0XICIiIiIiMheMNJ91tLmtIiKXy2ppYXFw8fmCB9mIj3TMhxmJkaOA\nZ9uEcm7pQyCehxEIYAQC+JYuJXjTTVXhKoC1eBEAdjFbUTcCpQ+N5DPpyXtSl2nvh+7mte59ZH0u\nHh5Zn8tr3fvY+6G76720aSVi10i2RqnXy2hb8MvMYSYS+FpbMUIhMAyMUIiCVwSj+vvNLmr3DxER\nqT8FrCIiIiIiIlOg1huHvtZWddeIyKQyEwnWf/P7rPQtBtPAX/AwXI+EGyJ+080MkCObTbF84VVV\n9x2aEV3rd1dwQ2kmcsAXrriP1dwMQDASm/wnd4mOn9w/rvpctS6xelz1etEW/LOHmUjgb28nsG5d\n6d9AuOZ5AZ92/xARkfrTFsEiIiIiIjJtpOwUyVySgmvjNwMkQgkaAtWdUzPVeOe2iohMBDOR4Prt\njzBv4BjX9vVwev+LnOo6SG5wkHAsweKFy7hi6dqq+w0FVLV+dw0dN2eSHOr8BYNhEy/eiL/RIobN\n0lWXt8V3f3cnvV2HsfMZAsEIzQtX0LSg9bKuOSTnq73F7Uj1uerNn/4q3Pdh9iZfIxPwiNgG6xKr\nS/VzpsPsU23BP3u1bHpTaeZqjbqIiEi9KWAVEREREZFpIWWn6MqcLh/bbr58PJtCVhGResn39eB0\nddEyr5WWecPCykKh5vkXC6h8bW3ElryHyKut2J2vUchlMUIh/K2r8S279AmJ/d2dnDz6yvl15wbL\nxxMRsoaKBtkaYWqoOL22vh3JVIaab/70V3nzKOuYDrNPa83uHKrLzLbsTz8Lf1aauWoX8wR8QVo2\nvalUFxERqTMFrCIiIiIiMi0kc8kR6wpYJ0/xyBEKHR246UHMWJTjp1/j2IlXyObShEMxVlz/Fla+\n/T31XqaITACrP02xRt1v1H57aCwBVTKXpLF1JY2tK6vql/q7u7fr8Ij1iQhYly5Zy2vd+2rWp7vp\nEmrC6LNPp3ItZiKB79zj1rOTVibHsj/9LJf+cQ0REZHJo4BVRERERESmhYJrj6sul6945Aj5XbvK\nx0eff5Rde59j0GjEJYBJH6df+VsAhawis0CTE6Sbwap6ItyMr7W1IqDas/1rvHriZTJmgYjrZ03b\nJjZ84nNV952M3912PjOu+nit+9p34UN3c/zkfnI+j1DRYOmStaX6NDddQk2YXrNPtQW/iIiITDUF\nrCIiIiIiMi34zQC2W/2mrN8M1GE1c0Oho6Pi+JVdzzEQnE9f3KC/2aLo8+ErRkh+/6t8WAHrnJB5\n+GHyjz2B09eHFY8TvOM2Im97W72XJROkMZKAQY8+J0XBK+I3fMStBhojiYqAavf/+CN2nXoBzNL9\n0qbNi8eehv/xR1Uh62T87g4EI+Rz1UFwIBi55GteaN3Xvsu6Cbva1JlOoaZmn4qIiMhcpoBVRERE\nRESmhUQoUTGDdXhdJoebHiRNnj4yFHA4nmgiHTZIzrfK5xR8cLithcf+3Zu443s/r+NqZbJlHn6Y\nzAPby8fO2bPlY4Wss4PV0kJDLkeDFamqD3fgyPPlcBUAD3A99h/cybqOjortVyfjd3fzwhUVM1iH\n1+e6C0PN3M6dFF54ETeTwde6bEo/FKHZpyIiIjKXKWAVEREREZG6S9kpkrkkmUKGbDFH2BcmHoyT\nCCU0f3USZaIW3enU+YIXoLfFwjDBcM6XraKfVxsGuWPqlyhTKP/YEyPWFbCe5yaTM3bW41hnVWbM\nwvkDD3BLvxAyVvXMz6Hf0clckoJr4zcDl/27e2jOam/XYex8hkAwQvPCFRMyf3Umc5NJ3IEBiseO\nYfgDFA6+Rn7nswAYkfCUfyhCs09FRERkLlPAKiIiIiIidZWyU+Xup4g/QsRf6qxSuDqxaoVC6eUt\nsO9U+Zym/jyOL4oJWI5XrgfsAoNRq8ZVZTZx+vrGVZ+L3GSyomPvwrBxJhjLrMqI6ydtnpuh6p7/\nXRBxzv8eGD7zsyHQMOG/r5sWtM75QHW4oe89IxDAt2AhTjKJvfMZcFyMhhiG//yWzFP5oQjNPhUR\nEZG5yrz4KSIiIiIiIpMnmUuOqy7jN/TGvJfLgeeVQ6FiJEhg7VrMaAQMkyWmSzTllgMVy4VwxiNq\nJ4kOOhd5FJnprHh8XPW5yDlzZlz1mWpN26ZhR275q6ua15a/rsfMz7ls+PeY0diAb/kyPNMCv78i\nXAV9KEJERERkKihgFRERERGRuiq49rjqMn4jhT9WfxpryWKCmzcTvv0tXPl3f8Wqo8eJDhZo6vOI\npW2ixTNYDHJVKjq1i5YpF7zjtnHV56KRQsXZFjZu+MTnuHHZLcTcAAYmUcfPhvh61r/nd8vnGMFg\nHVc499T6HrNiMXDd6ro+FCEiIiIy6bRFsIiIiIiI1JXfDGC71W8c+81AjbPlUowU/jQ5QS7sE37z\n1/6RRb//nzgaHGQwahEddLgqFeWO7/188hcqdTW0pWj+sSdw+vqw4nGCd9ym+avDGMFgqRO8Rn0m\neXb7V9hzeAdpN0vMDLN+xRY2b/tIxTkbPvE5NlC9LfIQq6VlilY7veV27CD/9A6cvn6seBPBW7YQ\n2rJlwh+n1veef9ONOI//v6pz9aEIERERkclneJ7nXfy06WXXrl1s3Lix3ssQEREREZEJMHwG63AL\nI4s0g3WCFDo6aodCoRC5tsUkc0kKro3fDGj2rcgoRgobfa2tM2YO5bPbv8KOg49W1bes2loVsg6p\nNcN5pjzfyZTbsYPMD35UVY/c9c4JD1lH+t6zX3uNwnMv6EMRIiIiIlNMHawiIiIiIlJXQ2GeQr7J\nY7W0jNiB1hBo0GstMkZmIoEPpnXY+L/vuY2Xl3tkQybhnMt1Rw1+54tPlG/fc3hHzfvtObyDzdQO\nWM1EYlo9x+ki/3Tt1zL/9I4JD1hH+t4LrF8P27ZN6GOJiIiIyMUpYBURERERkbpTyDe5LiUUUsea\nSG31DBsv9nP5v++5jWfXGIABQDZs8uwa4J7byiFr2s3WvPZIdRmZ09c/rvrlUtAtIiIiMn0oYBUR\nEREREZkDxvPG/IVbUXq5HMXOTnznriMiU28sP5cvL/cYCleHK9VLYmaYlFMdpsbM8KiPb+/Zg71r\nN87AAFa/gBlPAAAgAElEQVRjI4GNG0rdk3OYFW/COXvhJOtSXURERERmN7PeCxAREREREZHpxTlz\nZlx1EZl8Y/m5zIZqv80zvL5+Re2ta0eqA/S+9CwHf/4DDmWOccIaoH/gDNnHHsfes2csS5+1grfU\nfs1GqouITLXikSNkH3mEwX95kOwjj1A8cqTeSxIRmTUUsIqIiIiIiEgFL58fV11EJt9Yfi7DObfm\nOcPrm7d9hC2rttJghTEMaLDCbFm1lc3bas9fTdkpTux9Bttw8QDbcDnjy5I2C9i7dl/6E5oFQlu2\nELnrnVjzEmCaWPMSRO5654TPXxURuRTFI0fI79qFm0qB5+KmUuR37VLIKiIyQbRFsIiIiIiIiFQw\ngkG8XK5mXUTqYyw/l9cdNUozVy9w3dHKbYM3b/sIm6kdqF4omUviDqar6v1WntjAwJiuMZuFtmxR\noCoi01Kho2PEuq+tbWoXIyIyC6mDVURERERERCpYLS3jqovI5BvLz+XvfPEJNh/wCGdd8CCcddl8\nwON3vvjEyBfOnIXuX8LJ3aV/M2crbi64NmY0VnW3guFiNTZe2pMREZFJ56YHx1UXEZHxUQeriIiI\niIiIVDATCXyUZjt6+TxGMIjV0oKZSNR7aSJz1lh/LkcNUy+UOcvLv30nJ30D5IImobzLkmIj1/3t\nIxCZB4DfDOBfu4b88y9U3NXvmQQ2brjcpyUiIpPEjEVL2wPXqIuIyOWb0oC1WCzyyU9+kmPHjuE4\nDvfeey833ngjqVSKj33sY/T397Nw4UK++MUvEggEpnJpIiIiIiJTzk0mFWDJtGUmEvp+lDmtv7uT\n3q7D2PkMgWCE5oUraFrQWtc1mYkEg1EfyVySgmvjN1MkbB8NgYZLut5LH/wVDsfSDG1wlg2aHAqm\ncT/4K9zwnecBSIQS2KtX0fnP3yLd24lnguHCFbHlBD5832U9H/0dFBGZPP72dvK7dtWsi4jI5ZvS\nLYIfeughwuEw3/ve9/jMZz7DX/zFXwDwN3/zN9xyyy088MADrFmzhgMHDkzlskREREREppybTFLs\n7CzN0/M8vFyOYmcnbjJZ76WJiMx5/d2dnDz6CvncIJ7nkc8NcvLoK/R3d9Z1XSk7RVfmNLabx8PD\ndvN0ZU6Tsqs7lMbilL/vovWGQAPJL3yBTN9xPJ+JZRgEXeg/e5RX/vh3L+lxQX8HRUQmm6+tjeDG\njZgNDWCYmA0NBDdu1PxVEZEJMqUdrHfddRfvfOc7AZg3bx59faX/wf7EE0/w7W9/G4APf/jDU7kk\nEREREZG6cM6cGbGu7h0Rkfrq7To8Yr2eXazJXO3wMZlLXlIX62DAwsKrWR8udXg/EdODC87tPrZv\n3I85RH8HRUQmn6+tTYGqiMgkmdKA1e/3l7/+x3/8x3LY2tPTw/e+9z127tzJqlWruO+++7RFsIiI\niIjMal4+P666iIhMHTufGVd9qhRc+6L14pEjFDo6cNODmLEo/vZ2skuah20rHCARSpQC2UELYsXq\nCw5WBqxFy7kwWz1fv0T6Ozh26e3byT/yKE5fH1Y8TvDOrcS2bav3skaUslO1v99EREREZpFJC1gf\neOABHnjggYraRz7yEW699Va+853vsG/fPr72ta8BkM/n2bJlCx/+8Ie57777eOCBB/jN3/zNyVqa\niIiIiEjdGcFgaVvEGnUREamvQDBCPjdYsz7ZRptLevLj95DsOULRAJ8HsUVtLPvvX8Bvlj6kXjxy\npGLenptK0btrJ32ZpVhLFgOUtxUGuCLfwmvhXsJmAcvwcDyDrOtndboJe+9ejGCQTDxMLuijYLpY\nnoe/4OE/l8n6nMogdjz0d3Bs0tu3k7n/++Vj5+zZ8vF0DFmHtrEeMvz7TSGriIiIzCaTFrC++93v\n5t3vfndV/YEHHuDxxx/nr//6r8sdrYsXL+aGG24AYMuWLTz33HOTtSwRERERkWnBammh2Fk9y89q\naanDakREZLjmhSs4efSVmvXJNDSXdMjQXFIfcOi334/d00GxqfReStGAvq7D8Icf56avfAeAQkdH\n1TWTubNk/nUX5HO4uTxWczPBTTeR3BDk5n9+An79Ng77k/SHTSIZh9WZBm789P8Cz2Ng8Czd/UnC\ni9oodL+OYxg4AQM8F3/Rozm+jEJHR0UIPFb6Ozg2+UceHbE+HQPWid7GWkRERGS6mtItgjs7O7n/\n/vv59re/TXDYJxLf8IY38Oyzz7J582b27dvHihWT+/+wiIiIiIjUm5lI4IMRu5RERKR+huas9nYd\nxs5nCAQjNC9cMenzV0ebS9p/7FXCpgsUGIz6KPoMfEUP/4GD5eDKTVd23XqZDIOv7sM5dgzzXHDp\ndHWRffRxwIC3LOPmf36Cm8+dX+joqOgq7XNSALRu+/ccf+h7DJw4iGe4OJbJ0uhy1v72H1SEwOP5\nG6a/g6N3Kw9x+vpq3neker2NZRtrERERkdlgSgPWBx54gL6+Pn77t3+7XPvGN77BRz/6UT7xiU/w\n5S9/mfnz5/O7v/u7U7ksEREREZG6MBOJOfVGsojITNK0oHXSA9ULjTaXtGCWhqCGcy7h3PmwysAo\nf23GoripUiiaHkzSc+Igp3uP4EVcGskTIXj+cV7aA2+p7IC88PELXmkvYK9g0/Z7fwhA8egxsG1W\nBq+oONc5c2bcf9Pm8t/B0bqVh78mVjyOc/Zs1f2teHwqljlufjOA7VZ/Hw9tYy0iIiIyW0xpwHrP\nPfdwzz33VNXnzZvHN7/5zalcioiIiIiIiIjItDLaXFK/a2CfC1mH87vnA1Z/ezv5XbtIDyY5lTqJ\nW8wSHcjTNz9C0syDSylkdR1ivbUfZ/jj+w0ftlfE8J8Px7yCTcCofjtppHBYahutW3l4wBq8c2vF\nDNbh9ekoEUpUzGAdXpeZrb+7c8q7+kVERKazKQ1YRURERERERETmot6XnuXMnufJZwYIRhppWb+J\n5hs2V5wz2lzSpmVXceb4/qrbmpZdVf7a19YGQOeTPwDTwAhHicSaMYougxYMGgWanBBNRT9NC5pr\nPs7wx49bDXQXkxWBn+EPEHejVfc1ho2CkosbrVt5uKE5q/lHHsXp68OKxwneuXVazl8FyttVJ3NJ\nCq6N3wyQCCVm9PzVsWzlPNv1d3dWzKXO5wbLxwpZRURkrjI8z6v++OM0t2vXLjZu3FjvZYiIiIiI\niMgl0JvVMtf0vvQsnTsfqaq33nxnVcg62s/HM+9/F6/bx8mETCI5l5WBpbzxH35Ydd0DL/4Uz/Pw\nBgfJ736JwquvAmAAK5x5GLEYubVt9Gd6yaUHCMUamb92A4mVa3F6evDSacxoFLOlhUw8TH/IK4dl\nTTmD8Olk1WP6Wlv1czwOF867HWKEQvjb2+uwIqnlwq2ch8y17/fX9/6cfG6wqh4MRVm57k11WJGI\niEj9qYNVREREREREpsxY5w6KzCZn9jxf/rrjyf9HV7iZoj9I8Lk9rE1lue3BH5dvH2ku6an0KXJ/\n/jGWDKvlztUXxxZXnBsIRsjnBjGiUYIbbgDLh3P4dfx5B9+SpQwuitPVdQjPtiFvk+k5w5FX91O4\n4RZa3vgWiMWAc52ziQRNwy/eCK4/pg9JXKbRupVl+hjrVs6znZ3PjKsuIiIyFyhgFRERERERkSmj\nN6tlLspnBoBSuHq88XxEmguE6IgE4NfeURGy1nIsdWzE+lDA2vPRj5J/4kmKXo7kgjC+q9fS8O9/\ni9DNm+HmzSxZfi1NC1o5+aU/xbNtvGwWAC9vQ8HmzPNP0RSZhxmPY85LjPhzOVIILGNnJhL4QEH1\nNDfWrZxnu6EPbdSqi4iIzFUKWEVERERERGTK6M1qmYuCkUZy6T66wpVzT61zQ5uOWRefX5ot1u4U\nG6r3fPSj5H/8EwCiAF0ZBrIvkwLCH3gfyc99ggGrH7/lkjEszF4/gTW3AOAVbLAL2EYBt78fIxLG\nOX0aDEPb1U4iBdXTnxEM1t7KeY7NHG5euKJiBuvwuoiIyFylgFVERERERESmjN6slrmoZf0mOnc+\nQtFf+X1uFUoJay4Yuug1wr4ImWJ1B1nYV+ogyz/xZEU9mvOI5goMPr+fnlN/QDjSB4CDQTEC/kAe\n+8DTpZDVcQEIWEG8YrF8DS+drrjmQ395L3v6T5AzDEKex/qmK/g3f/D5i65dZKbSVs4lTQtaAejt\nOoydzxAIRmheuKJcFxERmYsUsIqIiIiIiMiU0ZvVMhdFMw7zjp4laOfIBUJYXilc9TulgDWUr/7Q\nwYWWNSzjQHJ/VX2p20ShowMGB8HzwDBK/3fOgL+I6e8rH2dDBieWBBlo8JFd7+No7hBXD+S5PttI\nPNGK4Tv/VpEZjZa/fugv7+W5gZPla2cNo3T8l/cqZJVZS1s5n9e0oFWBqoiIyDAKWEVERERERmHv\n2YO9azfOwABWYyOBjRsIrF9f72WJzFh6s1rmmtyOHWR+8CNiRpi1nV10LKkOKJY5F98ie2jO6rHU\nMbLFDGFfhKVuEy29Nh5AIAD5fClkhXIQWoiGsPylWjZk0Lk0xEDchwsEXYeBJj+7r7VoeClFe0ML\nht+HEQhiJRKYwz74sKf/REVwO7z+b8b3klTp7+5UZ5xMW9rKWURERGpRwCoiIiIiMgJ7zx6yjz1e\nPnb6+srHCllFLp3erJaZxE0mL+sDAfmnd5S/vm7TLfD80xxrbiEXDBHK51jm5LntwR+XzykeOUKh\nowM3PYgZi+Jvb8fX1gaUQtahoBWg0NHBuTgV/40bKOx4pnQwFLJ6HqErV5NPnsbyewxGLdIxCwDT\nBduz8Bc9MKCj1cdd7e2Y8QS+5cuAUmf50PPPDbss5UeFHNWh63j0d3dWzHbM5wbLxwpZRURERGS6\nMuu9ABERERGR6cretXtcdZGp5iaTFDo6sPfuLQUyyWS9lyQyq7jJJMXOztLcYM/Dy+UodnaO62fN\n6euvOL5u0y2868qraGg8yS/f0Me/3JblD//ydr7/l/+J4pEj5Hftwk2lwHNxUynyu3ZRPHKk5rW9\n/PnO1/gnPoF/yxshGCwloZ4HiQRNA0Xc/kBpLZaB6ysFooYHp81w6TqWwWDYpHi0k9zOZyr+zg09\n/5DjAi54RYYHrCHHuazfPb1dh8dVFxERERGZDtTBKiIiIiIyAmdgYFx1kak0FPwMGQp+fKDu0Avs\n//S9HN3/LFkKhPGzfO1m1t6nmZFycc6ZMyPWx/pzZsWbcM5WBpA/HXiGne1AqZmUwSD8nMO4f3sP\n79r4m1XXKHR0lLtYhzOCwVL4e078E5/AG0gx+NBDFPbtA8PEly6wKL6BnlO78JoMzCJkTB/dZphe\nK1K6jusRzboY8yL44k0YjQ0UXnsNp7cXq7kZgGv8CV5wzj0PD4YaV6/xJ8b1egC8/Mcf5+jBV8kZ\nHpmowYKW+az49fdUnGPnM2O+3mi01b+IiIiITAZ1sIqIiIiIjMBqbBxXfbZSl+T0NFrwI+ft//S9\n7N//JBnyeLhkyLN//5Ps//S99V6azADDO0THUq8leMuWqtrLrW7NeaYvNZ4tf/3QP3+GT+3/Iv/f\n0S/z357/M777vpuqzreGzUgF8AZSFLtOU3ztNby8jdvXh3v6FJETPSwPXctKbmWgsJr9vuZyuAoQ\nzLus6yy9RWQ2nf8bV3ztYPnrd/76h7gxFyRc9DANj4jjcpPZxDt//UPjej1e/uOPc+DgAbJ4eB44\nHnSe6eHwP/9TxXmBYGSEK4zd0Fb/Tl8fuG55q397z57LvraIiIiIzG3qYBURERERGUFg44aKGazD\n63OFuiSnr4kIfuaCo/ufHbG+dorXMh1c7jzRuebCDtHh9bEKbSkFrPmnd+D09WPFm8gELDCrA9ZM\nsFR76J8/w85NDeX6YNTHzht88L6buPtbL5TrZiKBDygcOoRz+jTOyVMYjY24Aym8wcHyeV4+D/0e\n8zstfuuzX+OfvvIhDob6Kfgg3uew6RC88aZ/y6m4j2Iog588cSKEi8WK9b39Lb/Or9h5jECwPKd1\nvK/H0YOvVhwH8h7FkEHXmTOsGFZvXriCyzXaVv/qYhURERGRy6GAVURERERkBENvvs7lrQUnYntM\nmRwTEfzMBVkK46rPZvrAxPhZLS0Vr9nw+niEtmwpB60Akb/8KYNW9XkRu/Tvy9eEa17n5fYAd9eo\nG4EAvmXLOP6FzzGQ6qbgM/AXXRozHg2NC8B1S+f5/SyOLeajf/RQxf3PPPwDTqdPlY9tHLpJsWBR\nnBDwwy/8F/a2FhmM+Ihmiqzr9PGuj/+v8vnjeT1yhjd8hCuBIpDzsAMGhmEQCEZoXriCpgWtY77m\nSLTVv4iIiIhMFgWsIiIiIiKjCKxfP6cC1QupS3L6mqjgZ7bK7dhB/ukdhNI5sn7AssB3PtEK46/f\n4upEH5gYv6EO0fF2/Xb89Ae8/osXyGSzRMJhVl5/E+2/clf59o2s4Ofu6+C5Ffe7ob+Z4MaNZI7W\nfrsmE6mup/7uG+R//hR9h/bR02iCr9QFa/tNepqgkOzDKkZwTQ/zzDHs3/oAC+79aMXftvTyFth3\nquramavbePp/fJhn1sDQW0jpqK90/MX/wl1//I2K1+Ox//B+jmXAtkIEnBzLInDHP/5DxTVDnkF2\neMJKKWRtKsKaG3+l5vO+VFZjY2l74Bp1EZk+tLuCiIjMRJrBKiIiIiIiIxqpG1JdkvVnJhL4Wlsx\nQiEwDIxQCF9rq96QpBSuZn7wI5yzSa4wm8HzoFiEolM+Z/nazXVcYX3oAxOXxkwk8Le3E1i3Dn97\n+5jC1VeeeZJMNgN4ZLIZXnnmSTp++oPyOXfd/AFu/kWeaMbB8CCacbj5+RS37fewX32VSKZY89oX\n1ge+9S2yP/ox7sAAA8OaXnubYry6opW9q9bw4rpr6WqO4+HhmAH69x6h+1P/vWIOqbuohcDatZjR\nCBgmZjRCYO1a3EUt7F1cey17W52K1+Ox//B+DubD2FYYMLCtMAfzYR77D++vuN/yVVfVvN5I9csx\n0pb+c2mrf5Hpbmh3BS+XA88r767gJpP1XpqIiMio1MEqIiIiIiIjUpfk9GYmEpcUqM72TpH80zvK\nXy9tvwk6XuCE20vOcAn7Iixfu5m1932+jiusD20rPTVe/8ULI9aHuljzT+/g9sNBbtufA4aC/yBe\nMEn+sSe47rTNzht8uAY4loFnGrjA6tdsDrz40/I2uvZPHwHTxCsWKfhLn6HvbYpxcuECAM7OX8qV\nuRwD8yOcsgxei5n82x92kP7l6wT+/DOEtt6Bf0Ub5rIGrCWLsZYsrliz3wwwGK6xlzFU1Y9lgBqn\nHstUHl/32S/AH3+cowdfJWd4hDyD5auuKtUnmLb6F5n+tLuCiIjMVApYRURERERkRJe6PaZMX3Nh\nDqfT119xvLT9JpYCmCbzPveZuqxpOtAHJqZGJpu9aN3p68fLV4fdXiGP09fH3d96gfz7N/LStVGK\nPhN/3mXJyTwrWtpJHthL/KprOXn0FQLpXkJnz0J/P/5ms7Qt8LzSz3H34iVc358qXzvqwnXpAv/y\nrna2PXQA90w3xQMHwHOJpBrpcwtVAWsilCCadUhHqpPTaPZ8R7ibTGJbIUrDVY2K80r1Std99gtc\nV/NVmnhzfat/kelOuyuIiMhMpYBVRERERERGdaldkjI9zYVOESvehHO2emtBK95Uh9VMH/rAxNSI\nhMPntgeurg+x4k0YwVBVR7HhD2LF4wC84bp3cl2qDzLQ5fRRiJa26u0/1kHT0hW4AymSmR4W9/WB\n59E44NLTHKDgL80XXp1xS1nn0LjTc/+uzriYnoPhD+Blsjinu4i1tGB29pFd2kbBten8+pfp2/cL\n9hYKNDXZnG2MEiiWLmD7wA5aLDyd5yfvWM+SeBtr//DTBIpZbF942AOWgtaAUx0ki4gM0e4KIiIy\nUylgFRERERERmUPmQqdI8JYtZH7wo5r1uU4fmJh8LfObeXn/UVzPxTRMwr4wwVCMldffVD4neMsW\n7Jdfpnjo9Yr7Gs0JgnfcRvdPH+L1V56mSBEfPjLxEKFYKXjN93ST/dmjePkchUKuNF/YsojmgV6b\ncM5mIBYi7BbxDDC8cx2l5/4Ju0WCQQ8jEcdznXInbWTQoaVxGfs/fS9n9z9XXtPyfh+F41nONgfI\nhkw802DloQxXHsuRDcChzBG8T91Lq5XgEGEutCwygS+uiMw62l1BRERmKgWsIiIiIjKjFY8codDR\ngZsexIxF8be342trq/eyRKatudApEtpSClLzT+/A6evHijcRvGVLuS4yWXpfehYrP8DiWJQz6RS2\n51IoDtLeurY8fxUgcPXVhO+6i8yDD+Ic6wTTxFy0kOCNN3L2uac4eXgvnlvEszwKFEjnCgAEzSBW\nfxrPKP0M+10D/H5wS92q0YLJ8mNn2N9+BVnTR8Qt4JmlkNUzPMAj7TeIrlmB2diEYVoYwdIWvmYs\nCsDR/c9WPa9VPSbhbqA/STYwFNie+9fzOJU5wR1/8Xn4zOfodALYvjCBYoZlUYPr/vNv8csv/Sm5\n9AChWCMLbryV+bdunZz/ACIy42h3BRERmakUsIqIiIjIjFU8coT8rl3lYzeVKh8rZBWpba50ioS2\nKFCVqXdmz/MALF6wmMULzs8zDfnN8tdDc5ADV68lcPVaAJyTpyh2d2FGo/T83+9BsUisaJAMuBiW\nQaQAaWuQQLFAgz9Wuk46TbzPLnWmWhZEo5iRCBErzZKubnYvXcwN/YDhUjQ9OLeEfXGHt6VL22Ub\nkTDWooUA+NvbAchSqH5inkfOyYHfGLblsAemAYZBLlAqvumTf1S+ixEK0d91jGNP/LBcy6X6yscK\nWUVkiHZXEBGRmUgBq4iIiIjMWIWOjhHrClhFalOniMjkyWcGLlqvNQe5eOwonl2AaBS7kAUg6otC\nNkXa7+DlHawsNKeL+DJnIXOYeMoh6vqBQinstG08v59C1KQl3szbzwzwr1cEuLrfIuI4ZCyLXzY5\nfOSRTrwrV+K7chXW4kX4V7RV7P4Qxk+GC7YMd1xCjgkFj6zfOF/3PDAMQnb1c7ZaWuj+8Xcqal1n\ne+i2B9l9/9+w7LFHuXLjG7nyXf/moq+riIiIiMh0o4BVRERERGYsNz04rrqIlKhTRGRyBCON5NJ9\nNetDas07djNZhlpDA/4wtp3FK9iEbZdoMI5r2/iOn2Lxkf7zdzJNiERK/2fb4PdhBIOEV67EmdeI\n5zq864UDeIVSR2rANXlrcBHGFVdgRqIk/tt/rfkclq/dzP79T15Q9ViauBInf5rXOVt1nyWJFRih\nUNWHNnLp88Fy19kejhXS52bBFhnMDrLn6UcBFLKKiIiIyIyjgFVEREREZiwzFsVNpWrWRUREplrL\n+k107nykZn1IrTnIZiRc6mAF5i+7ir8OPUEiDBHHJWMlSWbh/bvTlRd1XchkIB4n9I5fxbd8OZgm\nSzdczZF//TYAXrFYPr2RMHguAE5fKQQ+vf27dO98nPzgAMFoIwtuvp21930ePn0vR375DDkvT8j1\ncUXwCtre9A7MaBT+/succnvJ+Q1CtseSBau57h/+pebrEYo1kkuVHqvbHjwXroI17O2oQ7ueUcB6\nGdxkUjsSiIiIiNSBAlYRERERmbH87e0VM1iH10VERKZa8w2bgdIs1nxmgGCkkZb1m8p1qJ6D7Jw8\nhdN7Fqe7G7enh69bj7M04IFTuj3quDRYFt/+92u4dleRUN5myemzLD7TXwpZHQfn5Enc3rP4r2pn\n/q1bKZw4Qc8rL1L0+fDlHRoJ0+RvAKM0iNWKxzm9/bsce+R8MJpL95WPr/ovf8SVF6zR3r8fgNX/\n8fdYfa4e3Lhx1C35F9x4a3nmas7wyvWo7/wHoTLZzFhfXrnA0DzfIV4uR7GzEx8oZBURERGZZApY\nRURERGTGGnpTt9DRgZsexIxFK+bIiUy2lJ0imUtScG38ZoBEKEFDoKHeyxKROjr1f75B55FfkLMc\nQo5F8eW9FQHr0BzkwqFDFPbspfD66xhNTfiWtZJ7/kUa3miAcz6MNB2LQD7AAr+DB2SDAQ4tXwRQ\nClmDQfBK4ZqbSmPv2cPCt91F89U3kG1eSe6RR88vLuAHIHjnVk7s/EnN9XfvfJzmdTdW1KwliwkA\nzqlTYJhj/ns7/9atpWu++BSh0yYFwyTqixIKNZXPiYQjF3lFZSS15vkO1RWwioiIiEwuBawiIiIi\nMqP52toUqEpdpOwUXZnTZAoZBvIDFL0ivgEfV8ZXsTi2uN7LE5E6eOWeD9LRuQus0nHWckrH93yQ\na7/49YpzjUAAr1jAbG4GwN63j+LBg4Q3GRXn+exSKBpyHdIxP8G8i7/gcXLRPBaf6ccIh8F18C1b\nhrVoIfau3QTWr8cHRN7xDjAM7OdfxM3l8LW0ELxzK7Ft28j/7J9qPof84EDNObHWksVYVywhsG7d\nuF6T+bduZf6tWwn+8CF2/98f4vS45J0UWCZWo8mVt2wd1/XkvFr/nUarTwfa0lhERERmCwWsIiIi\nIiIilyCZS5IpZOjN9ZZrBa/Aof6DxAIxdbKKzEGdR35RDlcvrF877Hio89DNZM/XDh6CTIas1UDE\ncct10ysFrjnTwm8ZFCMW0YyDQQAWLyJ0663nL5zL4QwMlO6XSGAmEjSNsG1+MNpILt1Xs15rTiyU\n5sdeqvnhBEtTIbqKg+SAUNFjYSrE/LDCtUs1Gf+dJtN02NJYAe+l0esmIiJSzaz3AkRERERERGai\ngmszkB+oqhfdAslcsg4rEpF6y1nOmOpDHYZmJHy+lsuC55Dq9yrOdc/NLu1yAuVaPmgSAkJveEPl\nuelBrMbGMa11wc23j1i3Wlpq3jZSfSz6n3qRBc0trFvUxk2LVrBuURsLmlvof+rFS77mXDcZ/50m\n02hbGk+FoYDXy+XA88oBr5vU3+zR6HUTERGpTR2sIiIiIiIil8BvBih6xaq6z/RTcO06rEjk4vq+\n9DH5aUAAACAASURBVCXyP3kYN5XCbGgg+Pa3Ef/Yx+q9rBmr56lH6X7xKXLpAUKxkYPNkFPZ1jrU\neehbthx7/34Auvpz9CTa2PRokD1vNAjPS+L3ZxkIOSQzjSztOBfSmhbFgI+l0QRuXz9W7Hy3vOcU\nCWzcMKa1L9p2N1CauZofHCAYbWTBzbeX6z6Y0I61Qv/guOpycUPzfGdKZ2G9tzTWzNpLo9dNRESk\nNgWsIiIiIiIilyARSuAb8FHwChX1hkADfjMwwr1E6qfvS18ie//3y8duf3/5WCHr+PU89SjHnvhh\n+TiX6iMYaqC/0E/QqdwwrLXt+opjq6WFYmcn1pLFBIBX/+CTnFiwsnz7+mcA5hFyOwkXu+htHKRn\nXoJCMIjfMliUyXHlTdfjnO7CbGjAHUxjRmP4r1tHYP36MT+HRdvuLgeqFxraYvhCl7pVqL8pSqEv\nVbMul26k/07TUb23NK53wDtT6XUTERGpTQGriIiIiIjIJWgINHBlfBWH+g9SdAv4TD8NgQai/iiJ\n0Mx4s1vGJr19O/lHHsXp68OKxwneuZXYtm31Xta45X/y8Mj1GRqwdnzso3S9sh/bdQmYJguvXUv7\nl/5qSh67+8WnqmqLVl+P/+BeiukUOcsh5Fi0tl3PtV/8esV5wzsPrSuW0NOwoOZj5KwFROaHmO96\ntOQK4JqYgQCLV5RCVP+VKwhu3lw+39faOnFPsIbLmaHZdOuN9PzwiZp1mRuGPlhQqz4V6h3wzlR6\n3URERGpTwCoiIiIiInKJFscWEwvESOaSFFwbvxkgEUrQEGi4+J1lRkhv305mWNenc/Zs+Ximhaxu\nqrp7cLT6dNfxsY/S+fK+8rHtuKXjj310SkLWXLp6BjNA8+rr2PAnX7ro/Yd3Hub9IwQVnp8ly66m\n9/hBbDtDEB/zWlcxb8Nm3MFB/K2tYBgTtjXsqw/ez+u7nyebyxEOhVi5YRNX/dp7y7dfzlahTVvf\nBJRmsRb6B/E3RWm69cZyXWa/em9pXO+Ad6bS6yYiIlKbAlYREREREZHL0BBoUKA6i+UfeXTE+kwL\nWM2GBtz+/pr1majrlf0j1tun4PFDsUZyqb6a9fEKFvLk/eGa9XjbGuJta3AH0xgFB880SvNzN27E\n19Z2KUuv6dUH7+eVnU+WjzO5bPl4KGS93K1Cm7a+aVoGqsUjRyh0dOCmBzFjUfzt7RP62sp59dzS\nuN4B70yl101ERKQ2BawiIiIiIiIiI3D6qgO00erTWfDtb6uYwTq8PhPZrjtq/cB3/57XX3qBbD5H\nOBhi5Q03sebu/zhhj7/gxlsrZrAOr4/XfLuPEzUC1vmp7vLXZixW2gLYMAnfeee4H+NiXt/9fM36\ncy/8jH2ZV0jbKSJ5j6vmX8NV7W+sOGcsW4Xae/Zg79qNMzCA1dhIYOOGcc2LnSzFI0fI79pVPnZT\nqfKxQtbZZybNrJ1O9LqJiIhUU8AqIiIiIiIiMgIrHsc5e7ZmfaaJn5uzmv/Jw7ipVKkL8u1vK9dn\nmoBpYjvVIWvANDnw3b/nlWfOz0jN5HLl44kKWeffuhUozWLNpQcIxRpZcOOt5fp4XP/iTrjxZnoC\ncfL+IMFCnvnpblbc/eu4Pb14ThEjFMJrbsZauPCS1nvyW1/nzM7HyWdSBCMNtNx8O0ve98Hy7dka\nMxaTZDht5WnNl7ZDTpsFXjz5LEBFyHqxrULtPXvIPvZ4+djp6ysf1ztkLXR0jFgfS8CaPLiPnoN7\nyGfSBCMx5q9aT2LVNRO8ShERERGZbhSwioiIiIiIiIwgeOfWihmsw+szUfxjH4MZGqheaOG1aytm\nsA6vH3zphZr3ef2lFya0i3X+rVsvKVCt5foXdwLgJpMUOzspvPYa+edfLN9uBAI4Pb0Errtu3Nc+\n+a2vc/xn/1o+zg8OlI+HQtZwKEQml624X2/AxjTPHxs+P4Tg1Z59XHXVzWPeKtTetXvEer0DVjc9\nOK76cMmD+zj+8tPl49zgQPlYIauIiIjI7GZe/BQRERERERGRuSm2bRuR9/4G1rx5YJpY8+YRee9v\nzLj5q7NR+5f+itbrriFgmWBAwDJpve4a2r/0V2Tz1d2YwIj1erL37CH99/9A///8Mum//weKnZ24\nqRT2cy/gnDhO8cgRPDuP1TyfwNq1GKHQuB/jzM7HL1pfuWFT1e0FyyMWrfxsvuHzkwkaBNatw9/e\nPqZtQ52BgfLXaTtFZ/o4h1KHOXJyH/3dnWN9GpPCjEXHVR+u5+CecdVFREREZPZQB6uIiIiIiIjI\nKGLbtilQnYbsPXtYsv56FratrJrpGQ6GyNTY8jYcHH84OZlqbZ2b/s53MTDwTAPriqXl24z587CW\nLMbL58f9OPlMatR6yk4RvuNm5rlnOb3vAEamQJM/zKJGG/+86qAxFmgY1+NbjY2l52an6Mr3lOuF\noJ+TR18BoGlB67iuOVH87e0VM1iH1y8mn0mPqy4iIiIis4cCVhERERERERGZUS4203PlDTdVzGAd\nsvKGm6ZsjWNRa+vc4sGDeIMZzHgcTBMzHsdoaKC4/1UCq1djBIPjfpxgpIH84EDNespO0ZU5DUDr\nHW+l9Y63ArAwsojOXzzFC6/8tOp+a1bfPK7HD2zcQPaxx0na/RV1a8VyAHq7DtctYB2as1ro6MBN\nD2LGovjb28c0fzUYiZGr+brGJniVIiIiIjLdKGAVERERERERkRnlYjM9h+asvv7SC2TzOcLBECtv\nuGlC569OhOFb53Y9+E8MZHoo+Az8BZfGngjxFWtxzpzBAlzTAMBqaRn347TcfHvFDNbh9WQuWfM+\nyVySqzf9KgAHXttJ2k4RCzSwZvXN5fpYDXUWF392P2SKGOEI1orl+JctA8DOZ8Z1vYnma2sbU6B6\nofmr1lfMYB1eFxEREZHZTQGriIiIiIiIiMwow4PJkeqLt24lsO5K7HyGQDBC88IVU7W8MRvaOrfr\nwX+ix+4FXylEtf0mPeRg/y9oXNwGjkNw+TJ8ra3lmaf93Z30dh2ueH4jdYEued8HgdLM1XwmRTDS\nQMvNt7PkfR/kUN/BmvcpuDYAV2/61XEHqrUE1q+n0egjnxusvi0Yuezr10Ni1TVAaeZqPpMmGIkx\nf9X6cl1EREREZi8FrCIiIiIiIiIyowwFk7XqUAofh2Z7AuRzg3Wf9VnL0Na5A7mzYFbfPhB0aPL5\n8HJZ/NdfVxGujvf5LXnfB8tB63B+M4DtVs919ZuBS3lKo2peuKJi3cPrM1Vi1TUKVEVERETmoBr/\n811ERERERERmEzeZpNDRgb13b2nOYLL2lqAiM0Vg44ZR671dh2vePlK9XgLr1xO+43YKplfz9oLf\nhEAA34oVGIZRrk/k80uEEuOqX46mBa0sWX4twVAUwzAIhqIsWX7ttAq9RURERETGQh2sIiIiIiIi\ns5ibTFLs7Cwfe7kcxc5OfFDuhhOZaYZmetq7duMMDGA1NhLYuOF8fYSZnvWe9VlLYP16/FjYpgue\nB8OyVn/Rw79mDf4Vbbjp81vrTuTzawg0AKWZqwXXxm8GSIQS5fpEa1rQqkBVRERERGY8BawiIiIi\nIiKzmHPmzIh1BawykwXWry8HqlW3BSMzatZnfOXVdB95BQyjFLKe0+hvwr+iDbNlPmYsWq5P9PNr\nCDRMWqAqIiIiIjIbKWAVERERERGZxbx89WzF0eoiM1Xq2d0MPLcHOzVIIeCSWRogsnpZxTnTddbn\nqu9uh7u30ff6LykYLn4HGpsWccWHfq98jr+9/f9n796C2zrve+//sHBYIAlAhCXokIgyZSuMHdmM\nI9puLFnxju0dT7az00N2pns6e3Kx3xw8zTTpxR63mR6uMpO2s9+L5m0zTtJmptnTJK3j7DZx4jqx\n5Pgg27FNJaasyKFtiSYcWxQtAwRAcK0FYK33giFEigBFUCAWDt/PFZ+fQPChKtANf3ief/Xjbpxl\nivbjTEzUPSUOAADQ6yhYAQAAAKCLBUxTnmXVzIFukX/muN768bHqOmJJ0VNZVcJRhfbuUMTs19Yd\ne9v6atp933qg+nF5ampxXnJhXkZsQOGREYWGh6t/vvR9nJ85I8cudsT3h87iTExo4cjR6rqSzVbX\nlKwAAAAUrAAAAEDPczMZVWZn5dm2AqapYCrF1bFdJJhKrZjBujwHukXuZxMXFrYjd2FB0UpF4RfP\na/edH+2In2kvnXxMp6Z+pnm7oAEzpmuHf0vX7P9Q3cczyxSbyRk/XjenYAUAAKBgBQAAAHqam8ms\nKN88y1I5nVZI6ohCApdmJJMKSZTo6GpO/jfzSG1HbqFQzUtzhY74mfbSycf07Es/qa6nnvyRTjz5\nf7XrrK3dM452Ja7UDd/5oY87RK+p5HIN5QAAAL2GghUAAADoYZXZ2bp5O5cRaIyRTPJ/T3S1SHxA\nzlxe7sLCijw0EJVU/2da+qXnNHX6eRWtgvqjMQ1fdaOGrrmpJXte7tTUz6ofn3/+SWVCjqSAzm2P\naOvbJZ1emJb++92UrGiZYCKhSjZbMwcAAAAFKwAAANDTPNtuKAf8wDXWuJTEb40uzmCtVFbksf1X\nSVr9M83NZPTa+KM6deZnkhGU0denec/VyZOLMyZbXbLO2xdO3eZlSwpIkuyIUc3fzL2mG1q6K/Sy\nyNiBFTNYl+edypmYkDN+XJVcTsFEQpGxA1x3DAAANoyCFQAAAOhhAdOUZ1k1c7SPXi4YucYa6xF/\n/2Lpk3nopyrNFRQaiCq2/yrFrxuRtPJn2tK/qdfSL0qepEpFbqEgQzHJjGjq9PMtL1gHzJjy1uLV\nq5VQoJqbjlv92AoHVn0esFmWisduKSSdiYkVhXElm62uO/V7AgAA/qJgBQAAAHpYMJVaUV4tz9Ee\ner1g5BprrFf8/Qc08O69l/yZtvRvaqFcXPEYd2FBhhlR0Sqo1a4d/q3qDNZg2VP5NyVratapPiZa\n8hp+3l5+cwYuX2R0tGvKR2f8eN28W75HAADQWhSsAAAAQA8zkkmFJH4B38Z6vWDkGms0Yj0/05b+\n7fSF+lUszV/4ZHfxeuH+aKyVW5YkXbP/NkmLs1jjnqmiYyk162jb+VL1MbsSVzb0nL3+5gxguUou\n11AOAABwKRSsAAAAQI8zkkl+2d7GOrFgbOapOa6xRqMu9TNt6d/Unp3v1kvpZafajKAkafiqGzd7\nizVds/82XbP/Nk29mdSL//c7eiu+RdlYWYn8nPb179AN3/mhJCnv5JWxMiq5jsJGRMloUvFIfNXz\n9fqbMzrBa88/qqlTT6to5dQfTWj42lt05Y0f9HtbXSmYSKiSzco9O6PyG2/Isy0FzKjC7x7xe2sA\nAKBDGX5vAAAAAABQX70isV0LxqVTc55lSZ5XPTXnZjIber5611VzjTU2aunfzu53Xqtrhg6oPzyg\nQCCgWHK79u+/veXzV5eb+oeva+roY4pt2aVhI6WrvF3aFrtGg3f+jqTFcnWmeFaOa8uTJ8e1NVM8\nq7yTX/VcnfjmjF7y2vOP6uTx/9D8wpw8z9P8wpxOHv8Pvfb8o35vrStFxg7IPTuj0unTv/nv0+Kp\nbjdfkDMx4ff2AABAB+IEKwAAAAC0sU6bk9vsU3NcY41mW/5vavfu92jo6ve1zb+pN59+tm4+/MlP\nKWPVfqNCxsqsOsXK6e/2NnXq6br5xadYzz7wLZ176qjs+ZzMgYS2H7xdOz/2B63YZteIjI5q/vs/\nUKCvr3p6Nbhrl4I7dzCHFQAAbAgFKwAAAICulHnlpN56ZUJ2sSCzP6Zt+0aV3Lff7201rNMKxs04\nNcc11mi2dv03ZdcoRJfnJdep+ee1cj/enFGemlLh29+Wc/wX8hxHoXfuUt9v/7b677pr075mpypa\ntWd/XpyffeBbmv7x96prq5CtrilZG2PE44q874ZVOXNYAQDARlCwAgAAAOg6mVdO6vUXnqyurflc\ndd2pJWs7lkG1cGoO2DgzGpW9sFAzl6SwEZHjrn6zQtiIrFhPfu1/a+qFJ1QsFdTnhbVn+L3a9/H/\nZ1PfnFGemlL+G9+Q89z4hezMa5r/5v+RJErWi/RHE5pfmKuZL3fuqaM1P//cU0cpWBu0NIe1Vg4A\nANAoZrACAAAA6DpvvVJ7nlq9HM3DzFRg43bdcvOaeTK6WI5W3nhT9jPPaOHoT2U/84zi5y7MYJ38\n2v/WL8cfUrFckALSglHSr6af15mffn9T36hRmpxU6dRLq3I3X5B9hLmiFxu+9pZ15fZ87dOV9XLU\nFxk70FAOAACwFk6wAgAAAOg6drHQUI7m6bQrjYF2cfyzn9Trr7+muXBUbiCsuFPSrm07teuWmzX8\nyU9JkuKRuMrT0zp3alKeKoooqMH5oCIvvKRyaECh4WFNvfBEzeefeuEJjeh/bdr+3cK8vOL86j8o\nl2qeGux1S3NWp049raKVU380oeFrb1k1f9UcSMgqrP77Mwc4ddmopTmrzvhxVXI5BRMJRcYOMH8V\nAABsCAUrAAAAgK5j9sdk1TjdY/bHfNhN7+mkK42BdnD8s5/Uy2+mpaChiOtIclQKSmbUq5arS6Kn\nf63dWv36Kk1OKjQ8rGK5WPNr1MubxYgNKNA/IK9wUckaCis4OLipX7tTXXnjB1cVqhfbfvD2FTNY\nl+doXGR0lEIVAAA0BQUrAAAA0OGsY8dkP3lMleycgoNbZN56SNFDh/zelq+27RtdMYN1eQ4A7eb1\n11+TgqunOL3++mu6+PJS9+IC86K8P9S/eD3wRfpD/Ze9z7WER0YUvvaaFTNYJcmIx2TesXaJiPqW\n5qyee+qo7PmczIGEth+8nfmrAAAAPqNgBQAAADqYdeyYit9/sLquvJ2prnu5ZE3u2y9pceaqXSzI\n7I9p277Rag4A7cSqUa7Wy43YgNx8vmYuScPvPaxfjj+06s+H33v4Mne5ttDwsOL/83+q0Ncn5/gv\n5DmOQu/cpb7f/m3133XXpn7tbrfzY39AoQoAANBmKFgBAACADmY/eaxu3kjBmnfyylgZlVxHYSOi\nZDSpeCTerG36IrlvP4UqgI4QrbhaqFGmRivuqiw8MiJ7fLxmLkkjn/5f0tcWZ64Wy0X1h/o1/N7D\ni/kmCw0Pa/ALX9j0rwMAAAD4jYIVAAAA6GCV7FxDeS15J6+Z4tnq2nHt6rrTS1YA6AS7d1+5OIO1\nRn6x0PCwpMWZq25hXkZsQOGRkWouLZasI9r8QhUAAADoVRSsAAAAQAcLDm5R5e1MzXy9Mtbqz1/K\nKVgBYPMd+Pt/kD77Sb3++muygoaiFVe7d1+5mNcQGh5eUagCwEa5mYwqs7PybFsB01QwlZKRTPq9\nLQAA2h4FKwAAANDBzFsPrZjBujxfr5LrNJQDAJrvwN//gw74vQkAPcXNZFROXzg971mWyum0QhIl\nKwAAl0DBCgAAAHSwpTmr9pPHVMnOKTi4Reathxqavxo2InJcu2YOAACA7lSZna2bU7ACALA2ClYA\nAACgw0UPNVaoXiwZTa6Ywbo8BwCgHTkTE3LGj6uSy6l8+rQqZ2ckScHBQZkfulOxj33M5x0C7c+z\nV7/Bbq0cAABcQMEKAAAA9LilOasZK6OS6yhsRJSMJpm/CgBoS87EhBaOHJUklU7+UqUTJyRJgWRS\ncl0Vv/OvkkTJClxCwDTlWVbNHAAArI2CFQAAAIDikTiFKgB0gMnfu1u5119RyfAUdgNK7N6nke/9\n0O9ttZQzfrz6ceWVV6ofe4WCFF/8b5n940coWIFLCKZSK2awLs8BAMDaDL83AAAAAAAAgEub/L27\n9dYbL8sxPHmSHMPTW2+8rMnfu9vvrbVUJZerfuwuv8q0VLrwmGy2lVsCOpKRTCo0NKRANCoFAgpE\nowoNDTF/FQCAdeAEKwAAAAB0AevYMdlPHlMlO6fg4BaZt17ebF4A/jr7wLd07qmjsudzMgcS2n7w\nduVef6XmW+Vzr7+yOuxiwUSiWqAapil3YWHxD8LhC48ZHPRja0DHMZJJClUAADaAE6wAAAAA0OGs\nY8dU/P6DqrydkVxXlbczKn7/QVnHjvm9NQB15J28pnPTejX7iqZz08o7+eqfnX3gW5r+8fdkFbLy\nPFdWIavpH39Puf5AzecqGV6rtt0WImMHqh8H9+2rfhyIxaofmx+6s6V7AgAAQG/hBCsAAAAAdDj7\nydpFqv3kMU6xAm0o7+Q1UzxbXTuuXV3HI3Gde+pozc+zTUNRy12Vh93axWu3ioyOSvrNLNbrr1Ng\noF+VszOSFk+umh+6k/mrAAAA2FQUrAAAAADQ4SrZuYZyAP7KWJlV2cy3vqlXf/6cBmeLmg7n5BmG\nQkZIIc9QPNivgdgVMhWWVF71uYnd+1Zl3S4yOlotWgEAAIBWo2AFAAAAgA4XHNyyeD1wjRzw08k/\n/UNNv3pcVqCsqBfSnqsPaP9ffcXvbfmu5Dor1jPf+qbOPf+YAp4Uriwov8VQOSjFF0qSQspU8lJB\n2nbdTYqeeVO5119RyfAUdgNK7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TweDwAdO3b0r0J78uRJ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\nMgK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VoWQFAPomOegBAAAAAAD2Y2Nl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\nk9n1folsdgC/CwCAyaRgZaIlstloVSodcwAAABgl4/hDxNtX+2y8eD4azz8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P3vBY3qAAAAAICNR8AKtJl4LKXCwnzd+lZZaw+p2x74KQJVAOgSi31WM25GpcBX\n1LSVjqXpvwpgVbZjCBgZHNyUQPVqVipV3Rlcpw4AAAAA2BocEYyulPNzOps9qx/NndLZ7Fnl/JX9\nkNrV4B33NFXfDI16RW1GDykAQPtK2kndnLpZ7+s/oJtTNxOuAli1RmEfIeD62SOHmqoDAAAAADYe\nO1jRdXJ+btmRhn7g1cZrvTHsj4/LHzuuSjYrK5WSPXJo0442u+XD90uq9mItulnFYykN3nFPrb4V\nokND8sbG6tYBAACwtXJ+ruN2k9sjh7Tw7LG6dazP4veQrfp+AgAAAABYiYAVXSfjZhrW13Ijyh8f\nX3ZzqDI3Vxtvxk2MFx/5lE6Xz6kYMxR3Q/VF9umWf/KFDX+fa9nKHlIAAABobDMWD24FQsDNZQ8P\n87cEAAAAgBYiYEXXKQV+U/Xr8ceON6xv9E2NFx/5lF6NnJcihiSpEDP0qs5Lj3xK9z72jQ19r+vZ\nqh5SAAAAaGyjFw9uJUJAAAAAAEC3ogcruk7UtJuqX08lm22qvh6ny+eaqgMAAKC7bfTiQQAAAAAA\nsH7sYEXXScfSy45RW1pfCyuVUmVurm59oxVjRlN1AAAASOXJya5tbRA1bfmBV7cOAAAAAABag4AV\nXWfxqLSMm1Ep8BU1baVj6TUfoWaPHFrWg3VpfaPF3VCFOmFq3A03/L0AAAC6QXlyUt7YWG0c5HK1\ncTeErPUWDx775/+NztwSl++YShTLuutEVg9//bUWzRAAAAAAgO2HgBVdKWknN6wn1WLfKH/suCrZ\nrKxUSvbIoU3pJ3VrZF+152qdOgAAAFYqTUw0rHdDwHr14sG//81f0Ot3JmUF1Z/nExG9dO8O6dMf\nJGQFAAAAAGCLELACq7CwN63ZD98m3yvKduLauSetzTiU7d7HviE98imdLp9TMWYo7oa6NbKvWgcA\nAMAKQb7QVL0TLV08+J9v6amFq0udPJjSw9d5nSCTUWVmRqHnyXAcWQMDMtNra6MBAAAAAMB2RsAK\nXMf8xSmdO/Nqbey5hdq4b/f+DX+/ex/7hu7d8FcFAADoTmZvQkEuV7fejQrx+l/hGtUXBZmMylNT\ntXHouipPTSkiXTNk7eb+tgAAAAAArBUBK9pWu6ywn50+3bC+2oCVG1Ptyx0dlffCqCpz87L6++Qc\nOazY4cOtnhYAAFil6NDQsh6sS+vdKFEsK59Y+TUuUSxr/ktfkvfNpxVkszJTKTmffFB9jz4qSarM\nzKx4zle/+Gs6MWSrGI8oXizr4KlAn/vzl2o/7/b+tgAAAAAArJXZ6gkA9SyusA9dVwrD2gr7IJPZ\n8rn4XrGp+tUWb0wFuZwUBrUbU+XJyQ2cJdbCHR1V8YknVbmckYJAlcsZFZ94Uu7oaKunBgAAViky\nOChnZERmMikZpsxkUs7ISNcGgHedyDasL3zlLxXMzUlBoGBuTgtf+UvNf+lLkqTQ85Zd/9Uv/ppe\nvDuuQiKi0JAKiYhePGjry79yT+2aa/W3BQAAAABgO2MHK9pSvRX2i/Vr7WLN+Tll3IxKga+oaSsd\nS+urv/EJnbjdVrEnovhCWQff9PWr/+m7q56L7cTluSt7eNlOfFXPv9aNqW698dcpvBfqB6neC6Ps\nYgUAoINEBge3zeeqD/38Lyt//M914aaYXNuSsobu/H5BHzOHFGhuxfXeN59W8Eu/pMr58wryeRlR\nW1Y6rRNDdt3XP3HA1Ofee7wd+tsCAAAAALAWBKxoS1evsL9eXaqGq9PFC7WxH3j6T7/zkF47lJAZ\nhpKkYjyil+6OSP/0x1cdsu7cc2ut52ohd1nzuUsqVTzdsOeA5i9OXfeYYG5Mta/K3HxTdQAA6mmX\ntgbofj/6sz/Q1IkndIu1Q7ecv1Lf//O/oOCxp+s+p/LeyTBGIiHlcgp9T+XpCyo26NlajEeUOfWa\nLp0aV/7UK7IrhtI7b1Tfzn21a7q1vy0AAAAAAKtFwIq2ZDhO9XjgOvVGMu7K44MnbokqMCWzsrx+\n4vb6K/brWQxQJ9/6nmbn3lXUsrUrfaNsu6cWvF4dsi690RrOz0sRS0Z8+Y5Xbky1ntXfVz0euE69\nWfRyBYDtabGtwaLFtgYRiZC1Tfjj4/LHjquSzcpKpWSPHJI9PNzqaa3J9A+PNawfSKWqxwNfxYzF\nqv+dTEqSgssZhSVf8WJZhTq9XG2vondOvCBJsnbskHfunC5cOCVJtZC1W/vbAgAAAACwWvRgRVuy\nBgaaqktSKfBX1NweU6Gx8tpiT3NrC3+lS6cAACAASURBVPp271cytUs3779LN+y7XZJ0/tybOjt1\nUuPff1LzF6/cWL26f6x1ww2qXJpVWFzes5UbU63nHKkfgDaqN0IvVwDYvq7V1gCt54+Pa+HZY6q8\n15e0MjenhWePyR8fb/XU1sQv5xvWnU8+WPdn9j0/LkkKs7lauGpEbR18o/7JMAfOlmuPjXS/Ivv2\nSY6jzOV3u76/LQAAAAAAq8UOVrQlM51WRGrquL2oacsPlt8oii0E8hxTRslWpJyQQksyKoqWs03P\naewbf6ofLZxVzg4kU7pRO3Xb0EdUcHPLdrJefUPV2neDbEmV8+clw5TZm1B0aIgbU21gcYfpenee\n0ssVALavtbQ1wNbxx443rHfiLlY70iu/tDJktSO96nv0UUnv9VzNZmWmUnI++aDiDzyg3P/zp/JG\nRxUuuDJ6YrKHD+ozv/Rvpcd/VycORFSMRxQvlnXwVKDhn/01hWFQe20j3a9oul+hYarn6NGt+lUB\nAAAAAGhrBKxoW2Y63dTReulYelkPVkkaOlPSD29JKlpKXimGlganEro0O6tdO3eu6rVf+MP/Ra95\nk/IjgQq2VIkYyoUz8o5/S8Mf+bQkaXb6tPp27697Q9Xad4OsG/fJvuuuVf8+2Bqxw+s/ypdergCw\nfa2lrQG2TiVbf1Fdo3orraaX754fe0BTJ55Y8dw9P/aAJKnv0UdVfughlSYmlM3P6mJcyj3+Jwpe\neUF9lbISQaiwUJT30ksykr36xS/8Z33uqlNV3nrqK3ILK/8+Trx3A39bAAAAAAA6GwErukbSroao\nGTejUuArknf1sd67NffO27q4Wwoiphy3rNveKeu+f/q/afrixVUHrCenfyDTLsuPG6pEqidrB4ah\nqT5fd06ckvYNyfeqRwBzo3X72chergCAzmINDCzrwbq0jtazUqnq8cB16u1ktb183/ern5f+rNpz\n1S/nZUd6tefHHqjWJb37x3+ki//wtOZNV4W+mFL7BhU9/qoCK9SlHVHpckkJ35BMU99/4wW9/aUf\nqRixlDAs3XHLHbrvN/6ldh0YrvVgXWrXgc7b8QsAAAAAwGYhYEVXSdpJJe2kypOTeuP/+AOdnX1d\n+xI3aN/ce/1ZDVM37b9TkuR7K3u2NlKwygrCQHbJUCliqBIxZIZSKMk/OylJsp149S1sW6U3J2r9\nrax0WkYqyY3WLuYcOaziE0/WrQMAutta2hpg69gjh7Tw7LG69XZyrV6+V/+z9L5f/bzep8+vuPbC\n41/WO889KVXKyqcMlcuuZs++odRCTrGKJUVMzfeaSlwO9epOU+M39cswDRkKVQjL+v7kSek//jvd\n9xv/UpJ06dS4vGJeTrxXuw4MK33ggxv/iwMAAAAA0KEIWNF1gkxG/slXNTXzlmRKkbCkchCVTEMK\nQ1169y3dIMl27FW/ZqISUTbiK1IJlVgI5EcNSZLjhyqVFiRJO/fcqiCTqfa82pFWcDmjsOSrksnI\nvulGbrR2sY3q5QoA6EzNtjXA1lnss+qPHVclm5WVSskeOdR2/Vc3opfvxRePSUFZklS2rtTzTqhY\nviKFpsoRQ2Euq1MH90thqHDBVT4WkxuLK5Clp8++oeD3f0c/+dv/nkAVAAAAAIBrIGBF16nMzCgs\n+XKtihRKMT+vvJOWAklmKC+s3njas3v3dV+rPDmp0sSE7ijt0nT0rAJLilQCSdUbVDfMVhS3Etp3\ny53q271fpYkJSZKZTMpMXun7Gvqr3y2LzrQRvVwBAMDGs4eH2y5QvdpGtJjwClnJjEiVsiIVqfze\nN71CTFLJV9kqqcetaEfoaiFWXWhYcBwtxKqfWQ1JlYij70+/Jb0XsgIAAAAAgPoIWNF1Qs+TEbUV\nq1haMMvqKbuSMnLtXpXlqEfSzTfvX9Z/9eTIoOb2WyrFDEXdUP1TFd3x+N/LGxuTJP2jw7+owtf/\ng8Z3L8iNGUrmKxq8KL2vskM3/dTPqG/3/tp7N5oTAAAAulvm1GtrOlp3I3r5OomUXNdVWMir1w01\n12towc1rwTHkeJYUhnK8QJd22oqUSypFbbmxRO35XsSU74SaS1s6U3lDmX/13+qzv/sXq35/AAAA\nAAC2EyMMw7DVk2jW2NiYRkZGWj0NbDF/fFzut19Q5cK0jJij6PBd6jlyZMWRfKWJCQUXZ/TW//sf\nNTE3seQnhnJxySlV/xPzQ93o7JYx8Zpm3r9yrcHAW2Xd9OlflbV3T+3m1qWX/kGXpyZUciJy4kkN\n3PuA9j3y3y1777q7D2IxRYeGNuYPcQ2LO26DfEFmb0LRoSFFBgc3/X2Bq81fnNLs9Gn5XlG2E9fO\nPbfWFiIAALCR2uXzT+bUa3rnxAsr6jcdPLKqkDXIZNbVy/fC41/W2Wf+WvJ8ha6rhUhZZ8x52eVQ\nCd9UbzFQ7HJeknR2b5/e2bdbM+m9MvReuBozVbYKMiLVk1d6/Qs6XNhHyAoAAAAAQB3sYEVHOP2r\nn1Xh7AkFkYrMsqmwFJP3rZhK/3dETrJfAx8+or0//48Vep7c731fpePHtcd1VJ6P6XyPK9csyzMq\nCj1TdjFQaJpaiFg6Vbmg2AdsxSrBivec22/pxgVX5dNnJFV3EOy65ye06977lfj5z9ad50bsPlir\n8uRkbcetJAW5XG1MyIqtNH9xSufOvFobe26hNiZkBQBspHb6/HPp1HjD+moC1ka9fFe7aGnvw5+T\nVO3F6hWy2pFIKfjhccXKqvZmLZdr1+6ey+m5Hx9QtNyjiG8rMMvyInmZkZIkQ0ZYkiSdsN5V/U+9\nAAAAAABsbwSsaHtn/sdfVvb8K1IkkBc1ZN1T1O2ld2UpUCm09Iq9W38/U9T+L31PN8T3Kn/+rGJh\nRP1WQqk9+7X79DmF+YLG94Wy/YqyvZbm+qMqxSKKlkOl7KgGp1Ye4VuKGbXHlQvTtZDU7E2suHaR\nmU4rIq1r98FaLfZ/rVcnYMVWmp0+3bBOwAoA2Ejt9PnHK+abqq9Gs4uW9j78uVrQKknHP3O/3CCv\niFVW1CrIdCpaiFj6+k/erEIqpUhpXrFiXJIUCaJyDVsR01e0XJ1zwTHXPHcAAAAAALoZASvaXu6t\nlyWF1XD1wwv6YGm29rOoEegflc4rnizpu8FuhRd+pJ6iLTe1Syob8p0e9RfnlPACuRFD2bili7tt\nSVLZDFVMmlpI9ajHDdU/X5LjXzkxO+peeRx6V479vd5Rv/V2H3z9wbv12u0pFeMRxYtlffDNrD79\n9A/W82dZIcgXmqpjc633mL9O5nvFpuoAAKxVO33+ceK9cgvZuvW1Wu+ipYGP/qTOf/trciKu5AVS\naMhLGErEIyoGngpRyY0XZbuOzMBSJIiqHL0oyyipUpH6CitPeQEAAAAAABJLktH2AqN6VNlCj6Xb\nS5mrfhrKkPSB0qzKtqlcOqJEWJCVmVbWm5dcV1m7LAUVxcqGZnbZWohHNNcX0Vx/VJ5tqlwwle+1\ntNBjybOv7Frtn6rIUCizJyZDhsJsTkZvUqHvK8hcPY/Gvv7g3fru3TuUj0cUSMrHI/ru3Tv09Qfv\n3og/T02jnbXX2nGLzRFkMipPTVX78YahQtdVeWqqqX9uOpntxJuqAwCwVu30+WfXgeGm6qux3kVL\n+3/n3+im4WFFI44MmYoGUtyXFFrqC6oLCMvRkorJvPJ983LjRRlWSaEpVSLSwcqNa547AAAAAADd\njIAVbc+sWJJCVSxD1YjyisU4NKLqblP/vYA0ZngqhxXlz5zS+f5QZ1MllSolTe+xdTkd0exOR/NJ\nS/keQ85CVO5CVAsRS5d32irYlnrfCbTnth9X+eJFmX19Ul+fKtl5VSbPqHT6dFNh2Wu3p5qqr1Wj\nnbXX23GLjVeZmWmq3m127rm1qToAAGvVTp9/0gc+qJsOHlEskZJhmIolUrrp4JFV9V9tZCMWLQ18\n8qf1/v/hf9Wtn/is9qT2K1GJSkZFdlhZcW1gVSRD6lmo6K7pXn32d/9izXMHAAAAAKCbcUQw2lp5\nclLx1C3KZd+SVQlVllkLWUNdCVjLMhT1A9nvHfFrGaEqC3nN9UUVKYcKJc2nIvKjpjzHlO8YsiqG\ngkqoYkyy3ah6LlRfd+d0qLJla372nFKVParkC9VdEEGooFhQ8MPXJUlGLLaqI1+L8fr/N2tUX6vF\nPmOliQkF7805OjRE/9UWCL2VPX2vVe82i0cWzv7/7d15mJ11mSf871mqTqUqqaQglWCQfVEWQYmo\nyOKLcgF2j2M7Lm3TSreOjI5to7bdCE670pe2MDq24zWN+l52j9oqit0Or74ji/COiIIQZFWIkS2s\nqSQVktpO1VneP4oUqaQKT0KSqko+n7/queucOndV6knyPN/z+91PPpDR6lDaK53Zd+kh5q8CsNPN\ntv//9Bx+zHMKVLe279JDJs1g3bLesnkLkqGN6TjxZUmS+ddfk/kbNmX9on23eWhlcENO/dWGHPzQ\nULo7azvcNwAAAOzpBKzMamMrV2bpH787ufzLqW1clfvaenLM2Lqn16sWkqc/Wtm2TwqNQspj9Ty1\nXzkd7cUUC20ZaxQytKGRJ3vbcvuLuzPYUUqzmHRUG1k4Opbu5lja59dy0KPDGe4qZV1nR9YtLKa9\n2simJ9bmpb3HprhgftJsTuqr/uDDKS9b1tL30DlUy8AUYWrn0M6/aVU++GCB6ixQqFTGtweeor63\nWLjkAIEqc9Idf/rv81j/AxlpL6RjtJllPYfk+H+5cqbbAp7Fnvz/n53xpqXS81+Yjff+NJvqg6m9\n+OBkvz/Km35xS75cGEqztyuFRjmNUv3pcHVt9nuimo6RRroffWwXfVcAAAAw9wlYmdUaA4NJkqV/\n/O4sTbL2pp/ml13fz4tH+9JWaGS0Wcyq9p7c89S+ed6mkZQrSWVRMSP1clJIyoVmCktKWd3WluFK\nKYVikkbSVqqnu1hNZayZ0lgz5dQz1lvMvMFaGhlf5frQQfOy9Dc35dAXHZvm2NjkvkaGWg7Ljrlv\nY25+yT5T1tkzlXp7U1u9eso6MHvd8af/Pr8bfCBpT5Jmhtszfvyn/17ICsyY5/qmpcF9e7P2+Qel\n+MQDKYwOpnnQIRlbuCzvv3tNanesztqb/r9sXFBOtVJMpdpI96ZaujfW0jVUz+hdd6VQqaTU29vS\nzi0AAACwtxCwMqsV53elsWlTkuTxf7g4I4X1WVQp5uHq0nTMPzDLzv9oyn93Xl66aENK5Ub6D+rM\n0EglxUYx6UgKzVLGih1Z2mjPIwPdGWhrS6U+P73VTUmxmlr60z28MYPzSpk30si8RjUbMi9JUq4n\nj3eO5oju7tTWrZvcV0dny2HZ6676VXLWS3LPC7oz1FlO51Atx9y3cbzOHqnY05NyxmeuNqtVNyZh\njnisf3O4um39+N3fDrATNPr79/p/j/tH+pPe56fR+/yJWluS+kuq2X+oPW0/uCrPe2KKMQaFQtJs\npjkyktrq1Skne93PDgAAAKYjYGVWazvyyFRXrMjj/3BxBjvWT9TrlWRw7OE88dH3JIuS0Wo5qSaj\npXJKxUZSamSsWEmp2ZEUi6mknvpYd/bZuDj1Ui1dzWoKjfY0i/PzVPmxLBl7Is0kzcIzr90xXMtI\npZh0dY6HZRs3plmrpVAup3LSy7frBtPrrvpVXrfzfiy71Oidd2Z0xW2pb9yYUnd32pefkPbjjpvp\ntuacYk+Pm5Awx4y0P7P1/LZ1YK5p9PdP2lFibw0KxxqjU9Zr8zuy5t0fmP6JBx2YxqZNaazvT3Ns\nNPUnnkjlxBP3qp8dAAAATGe3Bqzr1q3Lhz/84VSr1YyNjeWiiy7K8cc/sybkO9/5Tr7yla/kuuuu\n251tMYttnqc1Ulg/5efr+46kXC1nrDx+87vWKCRthbSnllK9/enZqc0MFsppH1uUYq2UykhHah1P\npVJvpDxaTqNwcB7Zt5jFT61NaWws5Xqy8qCOPPb8jtTairnmkS/m+LuH88bCCSktWpThYw/Lk4/d\nk+qqm1PpnJ/Fhx+XnsOP2T0/kF1s9M47M/yTZ86/+oYNE8dCVmBP1zE6vi3wVHVg7qn39U1b35tC\nwrZie0Yb265QbSu2J3ffM+3z9r3ks6k/8cTEcWNgYK8MqAEAAGAqxd35YldeeWVe//rX5xvf+Eb+\n6q/+Kv/wD/8w8bl169blmmuu2Z3tMEeUDz44jenGnXY00zVYmzgcHRy/CV5OI+VaUmw201ZtZnVb\nZ4q1Usq1tqSRDNYWpDzWljQKKdaLGW2fn1qpO2PDXXng+e15+LDO1CrFlGvNDM8r5aYT5+f7pdsz\nOL+cx+64MYO/+22azUZGBjfmkTt+lv5V09+cmktGV9y2XXX2XrUHH8zw1Vdn8F//LcNXX53agw/O\ndEvwnC3rOWTbYjN5XnOR3/OdrNHfn7GVKzN6110ZW7kyjf7+mW6JPVCzOsW2t89S31P1dEwdhvZ0\n9CT1+rTPa6yffF4W2sbfgTJdcA0AAAB7k90asL7jHe/I6143vlHq448/nqVLl0587tJLL83555+/\nO9thDimOTrM940ghC448NoueGktbrZn2jY2Mrm+kMVJIqdFIfbSUTRsqeWDhvDTK9RQahaSYjNW6\ns76xKGMpp1FqplqoZH1zXlYu2y+rjpifRiEpjzZTaj6zaumOF1ayfmD8hlL9sccntbF21Z277Hvf\nneobN25Xnb1T7cEHU12xYnw+crORxqZNqa5YIXxizjv+X67MYV2HZN5oUmgm80abOXR0UY541wf8\nnu9Em7dtbY6MTJrvKGRlZytUpn6H3nT1PdWC9gVZ2rlf2ouVFFJIe7GSpZ37ZUH7gqRUmvpJpVKa\nY5O3Fi49vWp1bwuoAQAAYCq7fQZrX19f3vOe92RwcDD/83/+zyTJzTffnEqlMmm7YNhSR9cBGRx7\neJt6aV0lWZzMP/SFmT86ljQGU69WUltwSAqbxjIyWsjPX9RIyoUMLdiUeQPzUy+PpTzaluHMy3Bj\nXkY6N6VZLOSAxnC6B5JCxm+sb224o5Sx+vgNpWZ1ZNLnqkMDu+Lb3u1K3d2pb9gwZZ25a+iqq1L9\nyfWpb9iQ0qJFqbzm9HSeddYOf72xlSunrW/e1hvmquP/5cocn2T46qvH30SwFb/nz51tW9ldSr29\nk2awblnf2yxoXzAeqG7t2GOS2+/Ytn7UC1OcPz+NgYEU2tpT6ulJoXv8+XtbQA0AAABT2WUB6/e+\n971873vfm1T7y7/8y5x66qn5/ve/n//zf/5PLrroolx22WX54he/mP/xP/7HrmqFOWrT6Kb0j/Rn\nrDGa9m9/K8N/dk4K/avTaG+mWE06mouy8OQzUl/zUApj61Oa15FSqZiHGiMZfuS3KTeLmVfpyXD3\nghTrydCCTRkrj2Zh/74p1cppFhsZ7RhKozyc/QfW5cD2gXRkNO1rGrm/u5InK20pjT2TtM4bqaet\nVMlovZpCpWNSr5XO+ZOOG/39qff1p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            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f5175761710>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "edP3GFnVAXPb",
        "colab_type": "code",
        "outputId": "f039784d-c2be-428b-d590-459a6fff78b6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 378
        }
      },
      "source": [
        "sns.regplot(x='longitude', y='latitude', data = Woer, scatter_kws={'alpha':0.15}, fit_reg = False, )"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f517593a6a0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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5xnLZbvR7D6nUo3X7AagyyYxyCTDUzXk0xkeyXLhaoj+bYkfeplBxcIKArKmy\nfzTLUN5saazT3mTnrSza3RBCLhAI7mjah4iMDWUZG8piGkrLmMybQfOmwVAVbM+n7vmkIBHz7CaS\nwpprxduP96J5HClEddkLxTqmoZDSVcIgZGa5hmX7SJKErsooqowiSyyt1GFF4tC+AUo1B1WNzO8g\nBM8P0CRwG/1i5aa+N0f3d09M+9aJa7x+cYmy5ZIzNR44NMQj9+9KprCdnFhmeCDNzuEsw3kDVVHw\nG61i47ryuuPhegEh3LHNYu6sqxUIBAJaLdKzV4qUqzZuEJLSFIbzJsP9Zs/s5xuhedOwb2eWcw1R\nd3wflUjIH7preFPrNw0Vy/aQJDrmcHebvtat1anvB1h2SLnqoCly0o/dDwJsN0QNQ/J9BnXXR2uI\nt9M0rSUW7dGRDAuFKpoSbVIMVeHo/v6u3ee+deIa3zzZlCNgucnjWMw1VaZiuVyZq7BQtKjVXYIQ\nRvIp9uzIslK1WShamLqK5weYhpqU2d1JYn7nXKlAIBDQapFOz1dYKNZw/RBNlam7PlcXI7HdM5pd\n6zTX+d6rm4OjByLBvjxbwfH9jqz1jawfIGNqZMyo+UyzeHWzvEtVh7rjdcwUVxQZ3w+YK9QYHkiT\nny9T8G1sLyovMxQJw9CQZZnRgagNq67KbWIeqfnBsTy/8/PvWPdevH5xqefxR+7fFV1bSmNmscpS\n0cLzfFRFJggCZpeqzBejoS3plMKekSy6lkkG1UQd5+4cebtzrlQgEAhoHb5xdaFMNq1TKNv4foAi\nR1bxYsniPfftvOH36ohFK1JLPPfogWGOHhjelBu/1/CQ9k5nvZ7negErtRpzyzVsJ8DQo45vmiKz\nvGJjOz6ZlIbrh+QIifPUVEXmbfv6OTCW59J8hV1DGSbnVkvN4rj8RjwKEFng3Yhj7RBZ1eWaQ8pQ\nuTq/wkzBolb3CELImyr7duXx/JCJ2Wgdo4NREpyp31nSdmddrUAguONp7nBWs/2k93nVcpAkCU2R\nyKX1JE57vXSbR55La8wvWx3JaHE70m6u8HbLsr1DG8DEtRKTsyuAlLSVjRu5tFOuOlxbqiWPbSfg\n6lyF0YE0siThNFzUMiG2FxCE0JfReOS+XeweyTI6mGZgII3k+yDBfCMpbjBntHgULNvjO6dmOH25\nELVezWg8dNdIsmHJmRply6Vuu9RsD6+RJDeUN1vW6wdwdX6FywtVwiDEdX0CYHHFI2VojA6lAZhZ\nrjE6mEnq5O8khJALBIJtz0YEMEZVJJZX6iyXbSo1By8IMXWVsaEs6ZRGuVan7nh847VrmIbC+Ej2\nukS92zzykf40SqM/eTzQIz4MqE8JAAAgAElEQVR/L1c4tMZ72+d8T1wrcWpyGVmK3MlxW9lDu/rY\nu7Ov5XkTM2Wm5lfQNYWBbIrhfhNZAlmWqdguO4fSWLaHLYOmq6RSEjlT5+CuHOMj2UQgD+8ZIJ9S\ned/De7peu2V7fPPEDK+cX63nLlQc/uX1awAcu2eUBw4N8Y8vTbHSVLfvBVFN+uTMStKy1TQULs9V\nCBpj0Vad+RJL5Xoi5HHWfdzs5k5CCLlAINjWNAtgqWpTKNu4bsBAzmB8JNPRGMX1AuaWo9nZw3mT\n89NF5osWaV1FVcH14a5dfY1z+02laZsT816100N9Jm/bn+44vlGXeXu71YmZFYAkCS3m6kI1EfJY\n7AEIo43AQskiYyrsHMxSqjrYbsBgTqU/p+P5PtUg6qo2kDMwDT1573a6ZZ7fvXega7tbL4CTl5Y4\nds8oj9y/i1OTy9izZRw/QFdkxobS7NuZZ2KmlAj5+EgWq6kkTyYSc6XR593QFFwvQNdkFEVm56B5\nR8XHQQi5QCDY5sQCWKrazDcEOnrs4Lg+y9k6GVNPLPWK5ZJJqdSdKAM7pSkEQYgfBHjOapeyZqYX\nKpsW8s3OI+/mMofOGun2dqt1x8fQotapEJVjWbZPEIYsFq2oN/lMGVkCTVHQdSXqkgbMLNXYOZhF\nkUDVZFw/oD+boj+bwnF9PD8knVIJwqAjmQ56Z54XqzbVemc9fBiGLTHwuNSvnVpTUuDYUIZ8xmCl\nZhOGoGkKvh8iKxKqLGOoMqoic+++fvbvzN1xIg5CyAUCwTYnFsBC2W45brseQRDi+AEZU09c1eWq\ng64p6JrC7HKNkYFV6zjeFBQqdkuM+XpK0TY7j7zdZR7TTfibxby5t7jnB1QaSWSpRl26ZXvYjodp\nRO+bSykUqpGQO170frqmsGPQxHVD3IaLWtcUBnIquqbQl+4UceideX5+qkQmpXaIuSRJZFPN3gWl\nax/7tNG6kXrHkRFePDOfPHYdH9v1GRs2GRkwOTCWb5medqchhFwgEGxrYgGMBSjGcUM0haQmGmCh\nWOP81SJBCEEQMrtci1yyskRfWk9KqprLqmBVFJuJJ4XFfdCbxaRQrrNQcbi2UCEIQ/oyOoN9qTVj\n970mlHUT/uZwwoGxvshF7frUm1zQo4MZSlWbIIgmfymKjKrKZNLRBqVc91HlKAZ9eHee/qzB1YUK\nSFGNuK5KmIZG2lBJm93X3Cvz3HECjh4YaomRQ5TMdt/BoeTxgbE8Jyc6x4seGItGlMbDW4oVl5Wq\nRbkaNX5RZNi7I8N//LcP3pEWeDviDggEgm1NLICaJreIeezajmPHJy8tcWpiiZrt4vsBmqJiux5+\nqGE23M1pQ22IWKtbPM4qj5mcWWkRoGrdTx7nszrTC1Xy/Wl0TaFSc5i4VmZ5pU7WjCzbjKl1JOVt\ndEJZ/JyYA7si0ZuYWaFUdehLa4wOZhjIGgSN2zGUNyhVGzXWDTHPpOHhu0da2s/uHslueDMBq5nn\nHcczGu+9fwxFhtOXC1iOTz7dmrUOJBuf5tGp8YaoeXjLhasFalaALIOiRCGC+ZLN89+4yM/9yJGu\na7uTEEIuEAi2NbHQjeRNri1Vo+xtXUWRPfwgZDBnMD1f4cTEEp4XoKkqrudQthw0VcFxfHbkUxi6\niqRIjA6kSekykkRLVnkzEzOr07xmlyrMFWrYXsjpySVGB1LYXkgoSTi2T8aUGenPsliycb2QL784\nyfRiDa+RqPXQ4SF+8UfvTa6lWbhnlqqcmljCsv2WDPp2F/yBXXkO7MpzebZMJqUmlnjMntE8uwOf\nK3MVQqSuk9Sa7+VGNhMADxwaaomRNx83jSirvVdme0w8OrWd5mS5haIFEkgh+D4oUogkhbx8bkEI\nOULIBQLBWwDTUDk0nmewz2CxVMdxfXQ9cpX3ZQxOTy7jNdzlqgxhACDh+wG5jIGuKUiShCLJHLtn\nx7qJbXFcd3apwpWmXueLK3VmlmsMZFOMDqd5OZlwthrfNbQo5q0qMrbr8+LpeVRF7hCk5r7s0JpB\nr6lyIuYrVZvlRqa+H/iEYdAi4gCDOYO+jM7BXf2MDnZmzLffy426q+MObK9fXKJS98im1KRf+o3w\nO09+naWV1vi6KkdZ7wB1J0CSwPUcCuXOka2bpbl8MVQU6ra3rVz222elAoFAsA4DuVTLj3r8A205\nUXlSGIQEQVQa5ofRsI+0rtKXMRjuSzHUn9pQdnqcpHXhWolqzcVvjNcMwpCUrrJSs5k4We76WtsN\nEzGPee3CYoeQtw9zaT5+9MAQparDStVOSukA+tIGjuvjBwGKIqOpSiLi0Dtj/kZ45P5dNyzczXQT\ncVgV8ZgwjP772svT3H9oCNvxMXSF6YUykzPlpBzuvoNDa3bNa6/fd/2ga/3+7cz2WKVAINi2rNWs\n5VuvTfNPL02xUrVJ6Rpv29/Pe46O3bQf0Ni6HB1IQRiwUKpjOS51x6NWdwlDCYmQMAxRFZkj+7pP\n6VqdVx65uHNpnYvTC5SrLmEYEhKJiutCEHhsVi6tLvPDm/uyN1N3/OT+XJ2PNguKLJHSlSQbPwsM\n95sdr90OjVK6iXgv0ik4c3mZu/dEn9uJC4u8caVA2ohKCMuWy7dPRa7/XmK+0fr925ntsUqBQLAt\nWatb2amJJb57ZoGqFT2u2S7fP7uAH4S89/5dN/VH9MBYftUd3hBkSYrEL0RierFKPmN0ddF2c3ED\nVGrRpDDbix7LhARAsIFKtXjASBhG87o1RWaxZLUlvyldxTzOoDcNlZSudgxAAZAkyGf0Dce6txMS\nUdZ6xpTpz5q4QVOXu0bPddsNWnoBxE1ourHR+v3bme3/qQoEgtuWtaydk5eW8PxOoTp7pcRDd41s\nWHS+f2aOk5eW1nSlNmdHvyZBOqWiKhJzBRuqkQV4bWma//byNE/87IMYejQOtO74fP3VacqWi67K\nDORS9Dfqy1+fKG74PrQThAGe2xByGfYPZplZrFK1PXRFJpfRyaV1LNvqeG1zBr2hK9hdatx1TdlU\nrPtmEHteLs+WubZYwfNC+nP6Ta3xvrfNY1K2XPLppolvTvRZ+kGrCJeqLoslq8UrBNH3MOo/ECYb\no5jt1K9dCLlAILhlrGXtlC2Xbn+1HG/D1tD3z8wlrlNgTVdqnB39yrlFypbD5bkq3fiTL77GB47t\n5qvfv9rxt10DKVYsl0qXJiabwW7e3wRwarLEqcnXeceRYQihL6szNphmz44c3z45w6WZFRw3oD+r\n4wd+EscfzqeYXui8juH8jSV/rcXMUpVz11aYW6gkmfT9WYNS1WF6ocK5qdUNTrHscLIeleVtVMyH\n+tSu7nVTjUIDtuvhB5FVbmoy40MZCmUbWY56CtRtH0mKrPKoilBCUxU8P8R2fF6aWOLidJG67dPf\nZ3BwrI+dg5mO3vjbIQwR072HoEAguGOxbI/FksXsco3FktXS53qzqF2smoVijTcmlyjXXEplB9tt\nPb+pqxu2hk5e6t5ZrNdxgME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h0fSyUsVONnlVy6ViObh+SNZUKZRXM6zb7+3RA0McGu9H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cWfvvfVmBzxlvWy2zTA4z2/vh8Cx4ChzUewW2ALya/lkAx0QiOsfRV7DaLpBnweDqL0/7d379Fx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\nXVXQ0zAwl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            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f51759ac940>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wbC3w2SeCaU3",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}