Kickstarter_prediction_notebook.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7e08M1xyuUtM"
      },
      "source": [
        "### Description \n",
        "\n",
        "Using a dataset from [Kickstarter](https://www.kaggle.com/datasets/kemical/kickstarter-projects), the goal of this project is to be able to predict if a project will get sufficient funding from the backer's before deadline."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "k7PRm6ZGuUtQ"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import warnings\n",
        "\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "sns.set()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive/')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o1tyJ0La-cEh",
        "outputId": "50c245ba-b46f-4858-cd3d-a265ccb4951b"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive/; to attempt to forcibly remount, call drive.mount(\"/content/drive/\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('drive/MyDrive/ks-projects-201612.csv', encoding='cp1252')"
      ],
      "metadata": {
        "id": "-EW5OhHdTjrC"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(df.columns)\n",
        "print('Number of projects: {} | Number of parameters: {}'.format(df.shape[0], df.shape[1]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "alLCPkx2ZKm7",
        "outputId": "787d8dc8-6f46-4d11-ca4d-056ec00af148"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Index(['ID ', 'name ', 'category ', 'main_category ', 'currency ', 'deadline ',\n",
            "       'goal ', 'launched ', 'pledged ', 'state ', 'backers ', 'country ',\n",
            "       'usd pledged ', 'Unnamed: 13', 'Unnamed: 14', 'Unnamed: 15',\n",
            "       'Unnamed: 16'],\n",
            "      dtype='object')\n",
            "Number of projects: 323750 | Number of parameters: 17\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.rename(columns= lambda x: x.strip())\n",
        "print(df.columns)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g2ZlSqMS0q22",
        "outputId": "4dc75f90-cd80-45fd-be28-1fa1e4b5bb4c"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Index(['ID', 'name', 'category', 'main_category', 'currency', 'deadline',\n",
            "       'goal', 'launched', 'pledged', 'state', 'backers', 'country',\n",
            "       'usd pledged', 'Unnamed: 13', 'Unnamed: 14', 'Unnamed: 15',\n",
            "       'Unnamed: 16'],\n",
            "      dtype='object')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Overview of the dataset\n",
        "df.head(50)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "iJXpzLYFVsAi",
        "outputId": "c4357c92-e2e6-4932-dfc1-af131c76b3b7"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            ID                                               name  \\\n",
              "0   1000002330                    The Songs of Adelaide & Abullah   \n",
              "1   1000004038                                     Where is Hank?   \n",
              "2   1000007540  ToshiCapital Rekordz Needs Help to Complete Album   \n",
              "3   1000011046  Community Film Project: The Art of Neighborhoo...   \n",
              "4   1000014025                               Monarch Espresso Bar   \n",
              "5   1000023410  Support Solar Roasted Coffee & Green Energy!  ...   \n",
              "6   1000030581  Chaser Strips. Our Strips make Shots their B*tch!   \n",
              "7   1000034518  SPIN - Premium Retractable In-Ear Headphones w...   \n",
              "8    100004195  STUDIO IN THE SKY - A Documentary Feature Film...   \n",
              "9    100004721                                Of Jesus and Madmen   \n",
              "10   100005484                                   Lisa Lim New CD!   \n",
              "11  1000055792                                 The Cottage Market   \n",
              "12  1000056157  G-Spot Place for Gamers to connect with eachot...   \n",
              "13  1000064368                                     Survival Rings   \n",
              "14  1000064918                                          The Beard   \n",
              "15  1000068480                   Notes From London: Above & Below   \n",
              "16  1000070642                Mike Corey's Darkness & Light Album   \n",
              "17  1000071625                                           Boco Tea   \n",
              "18  1000072011              CMUK. Shoes: Take on Life Feet First.   \n",
              "19  1000082254                     Alice in Wonderland in G Minor   \n",
              "20  1000087442  Mountain brew: A quest for alcohol sustainability   \n",
              "21  1000091520                        The Book Zoo - A Mini-Comic   \n",
              "22  1000102741  Matt Cavenaugh & Jenny Powers make their 1st a...   \n",
              "23  1000103948                               Superhero Teddy Bear   \n",
              "24  1000104688                                Permaculture Skills   \n",
              "25  1000104953  Rebel Army Origins: The Heroic Story Of Major ...   \n",
              "26  1000115172                                  Daily Brew Coffee   \n",
              "27  1000117861                  Ledr workbook: one tough journal!   \n",
              "28  1000120151            Feather Cast Furled Fly Fishing Leaders   \n",
              "29  1000120287                                             BB130A   \n",
              "30   100012079            Chris Eger Band - New Nashville Record!   \n",
              "31  1000129669                                   Squatch Watchers   \n",
              "32  1000131947                         Arrows & Sound Debut Album   \n",
              "33  1000132945  Zen in America: a film on Zen Buddhism in Nort...   \n",
              "34  1000134913                         Galaxy: Winnie and Friends   \n",
              "35  1000146991             Help Scott Reynolds Make a New Record!   \n",
              "36  1000160286                          \"THE RETURN\" book project   \n",
              "37  1000171141             The Please, Please Me: Studio Premiere   \n",
              "38  1000182258            WE ARE ONE: STREET MUSIC OF NEW ORLEANS   \n",
              "39  1000183112                            Hot Chicken Takes Over.   \n",
              "40  1000184224                               Star and the Snowman   \n",
              "41  1000190427                                       Seas of Iron   \n",
              "42  1000197321                            (In)visible Empire Tees   \n",
              "43  1000201265  I'LL SEE YOU IN MY DREAMS - narrative feature ...   \n",
              "44  1000202062  SkateFrames-Photo frame made from recycled ska...   \n",
              "45  1000212914                       A Teacher's Travels in China   \n",
              "46  1000216800  Mothers Into Living Fit Yoga DVD for Moms and ...   \n",
              "47  1000217634                 Mobile barbecue & catering trailer   \n",
              "48  1000226576                       Following the Call - A Novel   \n",
              "49  1000227361                                         UNDERWATER   \n",
              "\n",
              "          category main_category currency             deadline    goal  \\\n",
              "0           Poetry    Publishing      GBP  2015-10-09 11:36:00    1000   \n",
              "1   Narrative Film  Film & Video      USD  2013-02-26 00:20:50   45000   \n",
              "2            Music         Music      USD  2012-04-16 04:24:11    5000   \n",
              "3     Film & Video  Film & Video      USD  2015-08-29 01:00:00   19500   \n",
              "4      Restaurants          Food      USD  2016-04-01 13:38:27   50000   \n",
              "5             Food          Food      USD  2014-12-21 18:30:44    1000   \n",
              "6           Drinks          Food      USD  2016-03-17 19:05:12   25000   \n",
              "7   Product Design        Design      USD  2014-05-29 18:14:43  125000   \n",
              "8      Documentary  Film & Video      USD  2014-08-10 21:55:48   65000   \n",
              "9       Nonfiction    Publishing      CAD  2013-10-09 18:19:37    2500   \n",
              "10      Indie Rock         Music      USD  2013-04-08 06:42:58   12500   \n",
              "11          Crafts        Crafts      USD  2014-10-02 17:11:50    5000   \n",
              "12           Games         Games      USD  2016-03-25 22:01:12  200000   \n",
              "13          Design        Design      USD  2015-02-28 02:10:53    2500   \n",
              "14     Comic Books        Comics      USD  2014-11-08 22:27:52    1500   \n",
              "15       Art Books    Publishing      USD  2015-05-10 21:20:54    3000   \n",
              "16           Music         Music      USD  2012-08-17 14:11:32     250   \n",
              "17            Food          Food      USD  2012-06-02 17:24:32    5000   \n",
              "18         Fashion       Fashion      USD  2013-12-30 07:06:11   20000   \n",
              "19         Theater       Theater      USD  2014-06-15 10:09:03    3500   \n",
              "20          Drinks          Food      NOK  2015-02-25 19:17:33     500   \n",
              "21          Comics        Comics      USD  2014-11-12 17:15:50     175   \n",
              "22           Music         Music      USD  2011-01-06 23:16:50   10000   \n",
              "23             DIY        Crafts      GBP  2016-01-05 20:09:06   12000   \n",
              "24       Webseries  Film & Video      CAD  2014-12-14 18:02:00   17757   \n",
              "25          Comics        Comics      GBP  2016-01-28 16:59:29     100   \n",
              "26     Food Trucks          Food      GBP  2015-03-31 18:06:32    3500   \n",
              "27  Product Design        Design      USD  2016-10-08 02:00:00    1000   \n",
              "28  Product Design        Design      AUD  2015-08-22 03:09:43    2000   \n",
              "29      Public Art           Art      USD  2013-03-24 00:07:28   25000   \n",
              "30           Music         Music      USD  2014-08-13 08:59:00   12000   \n",
              "31       Webseries  Film & Video      USD  2013-08-23 21:40:13   10000   \n",
              "32      Indie Rock         Music      USD  2012-05-19 01:04:31    4000   \n",
              "33     Documentary  Film & Video      USD  2013-10-21 23:00:54   10000   \n",
              "34    Illustration           Art      USD  2016-01-27 21:47:29    3000   \n",
              "35      Indie Rock         Music      USD  2012-09-02 18:43:16   15000   \n",
              "36     Photography   Photography      USD  2013-12-13 00:34:20   15000   \n",
              "37             Pop         Music      USD  2012-09-01 23:36:00   10000   \n",
              "38     Documentary  Film & Video      USD  2013-10-01 06:00:00    2500   \n",
              "39     Restaurants          Food      USD  2014-10-16 05:59:00   40000   \n",
              "40  Narrative Film  Film & Video      USD  2013-02-23 06:04:05    8000   \n",
              "41  Tabletop Games         Games      USD  2013-07-19 03:16:33    3000   \n",
              "42      Public Art           Art      USD  2016-01-02 00:00:00    1200   \n",
              "43  Narrative Film  Film & Video      USD  2014-02-05 00:57:14   60000   \n",
              "44             Art           Art      USD  2015-05-08 02:53:18    7500   \n",
              "45     Photography   Photography      USD  2012-05-13 23:34:56    4000   \n",
              "46          Family  Film & Video      USD  2014-06-19 17:18:29   11000   \n",
              "47     Food Trucks          Food      USD  2014-10-23 20:29:00   13750   \n",
              "48         Fiction    Publishing      USD  2016-02-01 08:06:07   13500   \n",
              "49    Film & Video  Film & Video      USD  2012-03-26 06:00:00    9500   \n",
              "\n",
              "               launched   pledged       state backers country     usd pledged  \\\n",
              "0   2015-08-11 12:12:28         0      failed       0      GB               0   \n",
              "1   2013-01-12 00:20:50       220      failed       3      US             220   \n",
              "2   2012-03-17 03:24:11         1      failed       1      US               1   \n",
              "3   2015-07-04 08:35:03      1283    canceled      14      US            1283   \n",
              "4   2016-02-26 13:38:27     52375  successful     224      US           52375   \n",
              "5   2014-12-01 18:30:44      1205  successful      16      US            1205   \n",
              "6   2016-02-01 20:05:12       453      failed      40      US             453   \n",
              "7   2014-04-24 18:14:43      8233    canceled      58      US            8233   \n",
              "8   2014-07-11 21:55:48   6240.57    canceled      43      US         6240.57   \n",
              "9   2013-09-09 18:19:37         0      failed       0      CA               0   \n",
              "10  2013-03-09 06:42:58     12700  successful     100      US           12700   \n",
              "11  2014-09-02 17:11:50         0      failed       0      US               0   \n",
              "12  2016-02-09 23:01:12         0      failed       0      US               0   \n",
              "13  2015-01-29 02:10:53       664      failed      11      US             664   \n",
              "14  2014-10-09 22:27:52       395      failed      16      US             395   \n",
              "15  2015-04-10 21:20:54       789      failed      20      US             789   \n",
              "16  2012-08-02 14:11:32       250  successful       7      US             250   \n",
              "17  2012-05-03 17:24:32      1781      failed      40      US            1781   \n",
              "18  2013-11-25 07:06:11     34268  successful     624      US           34268   \n",
              "19  2014-05-16 10:10:38       650      failed      12      US             650   \n",
              "20  2015-01-26 19:17:33        48      failed       3      NO      6.18000816   \n",
              "21  2014-10-23 17:15:50    701.66  successful      66      US          701.66   \n",
              "22  2010-12-07 23:16:50     15827  successful     147      US           15827   \n",
              "23  2015-12-06 20:09:06         0      failed       0      GB               0   \n",
              "24  2014-11-14 18:02:00     48905  successful     571      CA   43203.2511447   \n",
              "25  2015-12-29 16:59:29    112.38  successful      27      GB  167.7003057894   \n",
              "26  2015-03-01 18:06:32        21      failed       1      GB     32.41526106   \n",
              "27  2016-09-07 13:14:26     47266  successful     549      US           11253   \n",
              "28  2015-07-23 03:09:43      2000  successful      18      AU       1473.6189   \n",
              "29  2013-02-12 01:07:28      1395      failed      30      US            1395   \n",
              "30  2014-07-14 22:35:51     13260  successful      92      US           13260   \n",
              "31  2013-07-24 21:40:13   1373.37      failed      54      US         1373.37   \n",
              "32  2012-04-19 01:04:31   8641.34  successful     157      US         8641.34   \n",
              "33  2013-09-21 23:00:54     15663  successful     213      US           15663   \n",
              "34  2015-12-23 21:47:29        17      failed       2      US              17   \n",
              "35  2012-08-03 18:43:16  17499.99  successful     277      US        17499.99   \n",
              "36  2013-11-13 00:34:20     23907  successful     232      US           23907   \n",
              "37  2012-07-15 03:27:33     12656  successful     181      US           12656   \n",
              "38  2013-08-27 20:17:27         0      failed       0      US               0   \n",
              "39  2014-09-16 02:31:08     63401  successful     855      US           63401   \n",
              "40  2013-01-24 06:04:05      9401  successful     154      US            9401   \n",
              "41  2013-06-19 03:16:33      8105  successful     218      US            8105   \n",
              "42  2015-11-22 22:47:44        90      failed       4      US              90   \n",
              "43  2014-01-11 00:57:14  61365.16  successful     632      US        61365.16   \n",
              "44  2015-04-08 02:53:18         3      failed       3      US               3   \n",
              "45  2012-04-18 23:34:56   4866.17  successful      71      US         4866.17   \n",
              "46  2014-05-20 17:18:29     11055  successful      51      US           11055   \n",
              "47  2014-09-24 03:35:33         1      failed       1      US               1   \n",
              "48  2016-01-02 08:06:07         0      failed       0      US               0   \n",
              "49  2012-02-13 19:00:37      9660  successful     121      US            9660   \n",
              "\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>name</th>\n",
              "      <th>category</th>\n",
              "      <th>main_category</th>\n",
              "      <th>currency</th>\n",
              "      <th>deadline</th>\n",
              "      <th>goal</th>\n",
              "      <th>launched</th>\n",
              "      <th>pledged</th>\n",
              "      <th>state</th>\n",
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              "      <th>0</th>\n",
              "      <td>1000002330</td>\n",
              "      <td>The Songs of Adelaide &amp; Abullah</td>\n",
              "      <td>Poetry</td>\n",
              "      <td>Publishing</td>\n",
              "      <td>GBP</td>\n",
              "      <td>2015-10-09 11:36:00</td>\n",
              "      <td>1000</td>\n",
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              "      <td>1000004038</td>\n",
              "      <td>Where is Hank?</td>\n",
              "      <td>Narrative Film</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-02-26 00:20:50</td>\n",
              "      <td>45000</td>\n",
              "      <td>2013-01-12 00:20:50</td>\n",
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              "      <td>1000007540</td>\n",
              "      <td>ToshiCapital Rekordz Needs Help to Complete Album</td>\n",
              "      <td>Music</td>\n",
              "      <td>Music</td>\n",
              "      <td>USD</td>\n",
              "      <td>2012-04-16 04:24:11</td>\n",
              "      <td>5000</td>\n",
              "      <td>2012-03-17 03:24:11</td>\n",
              "      <td>1</td>\n",
              "      <td>failed</td>\n",
              "      <td>1</td>\n",
              "      <td>US</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1000011046</td>\n",
              "      <td>Community Film Project: The Art of Neighborhoo...</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2015-08-29 01:00:00</td>\n",
              "      <td>19500</td>\n",
              "      <td>2015-07-04 08:35:03</td>\n",
              "      <td>1283</td>\n",
              "      <td>canceled</td>\n",
              "      <td>14</td>\n",
              "      <td>US</td>\n",
              "      <td>1283</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1000014025</td>\n",
              "      <td>Monarch Espresso Bar</td>\n",
              "      <td>Restaurants</td>\n",
              "      <td>Food</td>\n",
              "      <td>USD</td>\n",
              "      <td>2016-04-01 13:38:27</td>\n",
              "      <td>50000</td>\n",
              "      <td>2016-02-26 13:38:27</td>\n",
              "      <td>52375</td>\n",
              "      <td>successful</td>\n",
              "      <td>224</td>\n",
              "      <td>US</td>\n",
              "      <td>52375</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1000023410</td>\n",
              "      <td>Support Solar Roasted Coffee &amp; Green Energy!  ...</td>\n",
              "      <td>Food</td>\n",
              "      <td>Food</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-12-21 18:30:44</td>\n",
              "      <td>1000</td>\n",
              "      <td>2014-12-01 18:30:44</td>\n",
              "      <td>1205</td>\n",
              "      <td>successful</td>\n",
              "      <td>16</td>\n",
              "      <td>US</td>\n",
              "      <td>1205</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1000030581</td>\n",
              "      <td>Chaser Strips. Our Strips make Shots their B*tch!</td>\n",
              "      <td>Drinks</td>\n",
              "      <td>Food</td>\n",
              "      <td>USD</td>\n",
              "      <td>2016-03-17 19:05:12</td>\n",
              "      <td>25000</td>\n",
              "      <td>2016-02-01 20:05:12</td>\n",
              "      <td>453</td>\n",
              "      <td>failed</td>\n",
              "      <td>40</td>\n",
              "      <td>US</td>\n",
              "      <td>453</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1000034518</td>\n",
              "      <td>SPIN - Premium Retractable In-Ear Headphones w...</td>\n",
              "      <td>Product Design</td>\n",
              "      <td>Design</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-05-29 18:14:43</td>\n",
              "      <td>125000</td>\n",
              "      <td>2014-04-24 18:14:43</td>\n",
              "      <td>8233</td>\n",
              "      <td>canceled</td>\n",
              "      <td>58</td>\n",
              "      <td>US</td>\n",
              "      <td>8233</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>100004195</td>\n",
              "      <td>STUDIO IN THE SKY - A Documentary Feature Film...</td>\n",
              "      <td>Documentary</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-08-10 21:55:48</td>\n",
              "      <td>65000</td>\n",
              "      <td>2014-07-11 21:55:48</td>\n",
              "      <td>6240.57</td>\n",
              "      <td>canceled</td>\n",
              "      <td>43</td>\n",
              "      <td>US</td>\n",
              "      <td>6240.57</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>100004721</td>\n",
              "      <td>Of Jesus and Madmen</td>\n",
              "      <td>Nonfiction</td>\n",
              "      <td>Publishing</td>\n",
              "      <td>CAD</td>\n",
              "      <td>2013-10-09 18:19:37</td>\n",
              "      <td>2500</td>\n",
              "      <td>2013-09-09 18:19:37</td>\n",
              "      <td>0</td>\n",
              "      <td>failed</td>\n",
              "      <td>0</td>\n",
              "      <td>CA</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>100005484</td>\n",
              "      <td>Lisa Lim New CD!</td>\n",
              "      <td>Indie Rock</td>\n",
              "      <td>Music</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-04-08 06:42:58</td>\n",
              "      <td>12500</td>\n",
              "      <td>2013-03-09 06:42:58</td>\n",
              "      <td>12700</td>\n",
              "      <td>successful</td>\n",
              "      <td>100</td>\n",
              "      <td>US</td>\n",
              "      <td>12700</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1000055792</td>\n",
              "      <td>The Cottage Market</td>\n",
              "      <td>Crafts</td>\n",
              "      <td>Crafts</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-10-02 17:11:50</td>\n",
              "      <td>5000</td>\n",
              "      <td>2014-09-02 17:11:50</td>\n",
              "      <td>0</td>\n",
              "      <td>failed</td>\n",
              "      <td>0</td>\n",
              "      <td>US</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>1000056157</td>\n",
              "      <td>G-Spot Place for Gamers to connect with eachot...</td>\n",
              "      <td>Games</td>\n",
              "      <td>Games</td>\n",
              "      <td>USD</td>\n",
              "      <td>2016-03-25 22:01:12</td>\n",
              "      <td>200000</td>\n",
              "      <td>2016-02-09 23:01:12</td>\n",
              "      <td>0</td>\n",
              "      <td>failed</td>\n",
              "      <td>0</td>\n",
              "      <td>US</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>1000064368</td>\n",
              "      <td>Survival Rings</td>\n",
              "      <td>Design</td>\n",
              "      <td>Design</td>\n",
              "      <td>USD</td>\n",
              "      <td>2015-02-28 02:10:53</td>\n",
              "      <td>2500</td>\n",
              "      <td>2015-01-29 02:10:53</td>\n",
              "      <td>664</td>\n",
              "      <td>failed</td>\n",
              "      <td>11</td>\n",
              "      <td>US</td>\n",
              "      <td>664</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1000064918</td>\n",
              "      <td>The Beard</td>\n",
              "      <td>Comic Books</td>\n",
              "      <td>Comics</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-11-08 22:27:52</td>\n",
              "      <td>1500</td>\n",
              "      <td>2014-10-09 22:27:52</td>\n",
              "      <td>395</td>\n",
              "      <td>failed</td>\n",
              "      <td>16</td>\n",
              "      <td>US</td>\n",
              "      <td>395</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>1000068480</td>\n",
              "      <td>Notes From London: Above &amp; Below</td>\n",
              "      <td>Art Books</td>\n",
              "      <td>Publishing</td>\n",
              "      <td>USD</td>\n",
              "      <td>2015-05-10 21:20:54</td>\n",
              "      <td>3000</td>\n",
              "      <td>2015-04-10 21:20:54</td>\n",
              "      <td>789</td>\n",
              "      <td>failed</td>\n",
              "      <td>20</td>\n",
              "      <td>US</td>\n",
              "      <td>789</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1000070642</td>\n",
              "      <td>Mike Corey's Darkness &amp; Light Album</td>\n",
              "      <td>Music</td>\n",
              "      <td>Music</td>\n",
              "      <td>USD</td>\n",
              "      <td>2012-08-17 14:11:32</td>\n",
              "      <td>250</td>\n",
              "      <td>2012-08-02 14:11:32</td>\n",
              "      <td>250</td>\n",
              "      <td>successful</td>\n",
              "      <td>7</td>\n",
              "      <td>US</td>\n",
              "      <td>250</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>1000071625</td>\n",
              "      <td>Boco Tea</td>\n",
              "      <td>Food</td>\n",
              "      <td>Food</td>\n",
              "      <td>USD</td>\n",
              "      <td>2012-06-02 17:24:32</td>\n",
              "      <td>5000</td>\n",
              "      <td>2012-05-03 17:24:32</td>\n",
              "      <td>1781</td>\n",
              "      <td>failed</td>\n",
              "      <td>40</td>\n",
              "      <td>US</td>\n",
              "      <td>1781</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>1000072011</td>\n",
              "      <td>CMUK. Shoes: Take on Life Feet First.</td>\n",
              "      <td>Fashion</td>\n",
              "      <td>Fashion</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-12-30 07:06:11</td>\n",
              "      <td>20000</td>\n",
              "      <td>2013-11-25 07:06:11</td>\n",
              "      <td>34268</td>\n",
              "      <td>successful</td>\n",
              "      <td>624</td>\n",
              "      <td>US</td>\n",
              "      <td>34268</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1000082254</td>\n",
              "      <td>Alice in Wonderland in G Minor</td>\n",
              "      <td>Theater</td>\n",
              "      <td>Theater</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-06-15 10:09:03</td>\n",
              "      <td>3500</td>\n",
              "      <td>2014-05-16 10:10:38</td>\n",
              "      <td>650</td>\n",
              "      <td>failed</td>\n",
              "      <td>12</td>\n",
              "      <td>US</td>\n",
              "      <td>650</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>1000087442</td>\n",
              "      <td>Mountain brew: A quest for alcohol sustainability</td>\n",
              "      <td>Drinks</td>\n",
              "      <td>Food</td>\n",
              "      <td>NOK</td>\n",
              "      <td>2015-02-25 19:17:33</td>\n",
              "      <td>500</td>\n",
              "      <td>2015-01-26 19:17:33</td>\n",
              "      <td>48</td>\n",
              "      <td>failed</td>\n",
              "      <td>3</td>\n",
              "      <td>NO</td>\n",
              "      <td>6.18000816</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>1000091520</td>\n",
              "      <td>The Book Zoo - A Mini-Comic</td>\n",
              "      <td>Comics</td>\n",
              "      <td>Comics</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-11-12 17:15:50</td>\n",
              "      <td>175</td>\n",
              "      <td>2014-10-23 17:15:50</td>\n",
              "      <td>701.66</td>\n",
              "      <td>successful</td>\n",
              "      <td>66</td>\n",
              "      <td>US</td>\n",
              "      <td>701.66</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>1000102741</td>\n",
              "      <td>Matt Cavenaugh &amp; Jenny Powers make their 1st a...</td>\n",
              "      <td>Music</td>\n",
              "      <td>Music</td>\n",
              "      <td>USD</td>\n",
              "      <td>2011-01-06 23:16:50</td>\n",
              "      <td>10000</td>\n",
              "      <td>2010-12-07 23:16:50</td>\n",
              "      <td>15827</td>\n",
              "      <td>successful</td>\n",
              "      <td>147</td>\n",
              "      <td>US</td>\n",
              "      <td>15827</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>1000103948</td>\n",
              "      <td>Superhero Teddy Bear</td>\n",
              "      <td>DIY</td>\n",
              "      <td>Crafts</td>\n",
              "      <td>GBP</td>\n",
              "      <td>2016-01-05 20:09:06</td>\n",
              "      <td>12000</td>\n",
              "      <td>2015-12-06 20:09:06</td>\n",
              "      <td>0</td>\n",
              "      <td>failed</td>\n",
              "      <td>0</td>\n",
              "      <td>GB</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>1000104688</td>\n",
              "      <td>Permaculture Skills</td>\n",
              "      <td>Webseries</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>CAD</td>\n",
              "      <td>2014-12-14 18:02:00</td>\n",
              "      <td>17757</td>\n",
              "      <td>2014-11-14 18:02:00</td>\n",
              "      <td>48905</td>\n",
              "      <td>successful</td>\n",
              "      <td>571</td>\n",
              "      <td>CA</td>\n",
              "      <td>43203.2511447</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>1000104953</td>\n",
              "      <td>Rebel Army Origins: The Heroic Story Of Major ...</td>\n",
              "      <td>Comics</td>\n",
              "      <td>Comics</td>\n",
              "      <td>GBP</td>\n",
              "      <td>2016-01-28 16:59:29</td>\n",
              "      <td>100</td>\n",
              "      <td>2015-12-29 16:59:29</td>\n",
              "      <td>112.38</td>\n",
              "      <td>successful</td>\n",
              "      <td>27</td>\n",
              "      <td>GB</td>\n",
              "      <td>167.7003057894</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>1000115172</td>\n",
              "      <td>Daily Brew Coffee</td>\n",
              "      <td>Food Trucks</td>\n",
              "      <td>Food</td>\n",
              "      <td>GBP</td>\n",
              "      <td>2015-03-31 18:06:32</td>\n",
              "      <td>3500</td>\n",
              "      <td>2015-03-01 18:06:32</td>\n",
              "      <td>21</td>\n",
              "      <td>failed</td>\n",
              "      <td>1</td>\n",
              "      <td>GB</td>\n",
              "      <td>32.41526106</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>1000117861</td>\n",
              "      <td>Ledr workbook: one tough journal!</td>\n",
              "      <td>Product Design</td>\n",
              "      <td>Design</td>\n",
              "      <td>USD</td>\n",
              "      <td>2016-10-08 02:00:00</td>\n",
              "      <td>1000</td>\n",
              "      <td>2016-09-07 13:14:26</td>\n",
              "      <td>47266</td>\n",
              "      <td>successful</td>\n",
              "      <td>549</td>\n",
              "      <td>US</td>\n",
              "      <td>11253</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>1000120151</td>\n",
              "      <td>Feather Cast Furled Fly Fishing Leaders</td>\n",
              "      <td>Product Design</td>\n",
              "      <td>Design</td>\n",
              "      <td>AUD</td>\n",
              "      <td>2015-08-22 03:09:43</td>\n",
              "      <td>2000</td>\n",
              "      <td>2015-07-23 03:09:43</td>\n",
              "      <td>2000</td>\n",
              "      <td>successful</td>\n",
              "      <td>18</td>\n",
              "      <td>AU</td>\n",
              "      <td>1473.6189</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>1000120287</td>\n",
              "      <td>BB130A</td>\n",
              "      <td>Public Art</td>\n",
              "      <td>Art</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-03-24 00:07:28</td>\n",
              "      <td>25000</td>\n",
              "      <td>2013-02-12 01:07:28</td>\n",
              "      <td>1395</td>\n",
              "      <td>failed</td>\n",
              "      <td>30</td>\n",
              "      <td>US</td>\n",
              "      <td>1395</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>100012079</td>\n",
              "      <td>Chris Eger Band - New Nashville Record!</td>\n",
              "      <td>Music</td>\n",
              "      <td>Music</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-08-13 08:59:00</td>\n",
              "      <td>12000</td>\n",
              "      <td>2014-07-14 22:35:51</td>\n",
              "      <td>13260</td>\n",
              "      <td>successful</td>\n",
              "      <td>92</td>\n",
              "      <td>US</td>\n",
              "      <td>13260</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>1000129669</td>\n",
              "      <td>Squatch Watchers</td>\n",
              "      <td>Webseries</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-08-23 21:40:13</td>\n",
              "      <td>10000</td>\n",
              "      <td>2013-07-24 21:40:13</td>\n",
              "      <td>1373.37</td>\n",
              "      <td>failed</td>\n",
              "      <td>54</td>\n",
              "      <td>US</td>\n",
              "      <td>1373.37</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>1000131947</td>\n",
              "      <td>Arrows &amp; Sound Debut Album</td>\n",
              "      <td>Indie Rock</td>\n",
              "      <td>Music</td>\n",
              "      <td>USD</td>\n",
              "      <td>2012-05-19 01:04:31</td>\n",
              "      <td>4000</td>\n",
              "      <td>2012-04-19 01:04:31</td>\n",
              "      <td>8641.34</td>\n",
              "      <td>successful</td>\n",
              "      <td>157</td>\n",
              "      <td>US</td>\n",
              "      <td>8641.34</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>1000132945</td>\n",
              "      <td>Zen in America: a film on Zen Buddhism in Nort...</td>\n",
              "      <td>Documentary</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-10-21 23:00:54</td>\n",
              "      <td>10000</td>\n",
              "      <td>2013-09-21 23:00:54</td>\n",
              "      <td>15663</td>\n",
              "      <td>successful</td>\n",
              "      <td>213</td>\n",
              "      <td>US</td>\n",
              "      <td>15663</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>1000134913</td>\n",
              "      <td>Galaxy: Winnie and Friends</td>\n",
              "      <td>Illustration</td>\n",
              "      <td>Art</td>\n",
              "      <td>USD</td>\n",
              "      <td>2016-01-27 21:47:29</td>\n",
              "      <td>3000</td>\n",
              "      <td>2015-12-23 21:47:29</td>\n",
              "      <td>17</td>\n",
              "      <td>failed</td>\n",
              "      <td>2</td>\n",
              "      <td>US</td>\n",
              "      <td>17</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>1000146991</td>\n",
              "      <td>Help Scott Reynolds Make a New Record!</td>\n",
              "      <td>Indie Rock</td>\n",
              "      <td>Music</td>\n",
              "      <td>USD</td>\n",
              "      <td>2012-09-02 18:43:16</td>\n",
              "      <td>15000</td>\n",
              "      <td>2012-08-03 18:43:16</td>\n",
              "      <td>17499.99</td>\n",
              "      <td>successful</td>\n",
              "      <td>277</td>\n",
              "      <td>US</td>\n",
              "      <td>17499.99</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>1000160286</td>\n",
              "      <td>\"THE RETURN\" book project</td>\n",
              "      <td>Photography</td>\n",
              "      <td>Photography</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-12-13 00:34:20</td>\n",
              "      <td>15000</td>\n",
              "      <td>2013-11-13 00:34:20</td>\n",
              "      <td>23907</td>\n",
              "      <td>successful</td>\n",
              "      <td>232</td>\n",
              "      <td>US</td>\n",
              "      <td>23907</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>1000171141</td>\n",
              "      <td>The Please, Please Me: Studio Premiere</td>\n",
              "      <td>Pop</td>\n",
              "      <td>Music</td>\n",
              "      <td>USD</td>\n",
              "      <td>2012-09-01 23:36:00</td>\n",
              "      <td>10000</td>\n",
              "      <td>2012-07-15 03:27:33</td>\n",
              "      <td>12656</td>\n",
              "      <td>successful</td>\n",
              "      <td>181</td>\n",
              "      <td>US</td>\n",
              "      <td>12656</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>1000182258</td>\n",
              "      <td>WE ARE ONE: STREET MUSIC OF NEW ORLEANS</td>\n",
              "      <td>Documentary</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-10-01 06:00:00</td>\n",
              "      <td>2500</td>\n",
              "      <td>2013-08-27 20:17:27</td>\n",
              "      <td>0</td>\n",
              "      <td>failed</td>\n",
              "      <td>0</td>\n",
              "      <td>US</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>1000183112</td>\n",
              "      <td>Hot Chicken Takes Over.</td>\n",
              "      <td>Restaurants</td>\n",
              "      <td>Food</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-10-16 05:59:00</td>\n",
              "      <td>40000</td>\n",
              "      <td>2014-09-16 02:31:08</td>\n",
              "      <td>63401</td>\n",
              "      <td>successful</td>\n",
              "      <td>855</td>\n",
              "      <td>US</td>\n",
              "      <td>63401</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>1000184224</td>\n",
              "      <td>Star and the Snowman</td>\n",
              "      <td>Narrative Film</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-02-23 06:04:05</td>\n",
              "      <td>8000</td>\n",
              "      <td>2013-01-24 06:04:05</td>\n",
              "      <td>9401</td>\n",
              "      <td>successful</td>\n",
              "      <td>154</td>\n",
              "      <td>US</td>\n",
              "      <td>9401</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>1000190427</td>\n",
              "      <td>Seas of Iron</td>\n",
              "      <td>Tabletop Games</td>\n",
              "      <td>Games</td>\n",
              "      <td>USD</td>\n",
              "      <td>2013-07-19 03:16:33</td>\n",
              "      <td>3000</td>\n",
              "      <td>2013-06-19 03:16:33</td>\n",
              "      <td>8105</td>\n",
              "      <td>successful</td>\n",
              "      <td>218</td>\n",
              "      <td>US</td>\n",
              "      <td>8105</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>1000197321</td>\n",
              "      <td>(In)visible Empire Tees</td>\n",
              "      <td>Public Art</td>\n",
              "      <td>Art</td>\n",
              "      <td>USD</td>\n",
              "      <td>2016-01-02 00:00:00</td>\n",
              "      <td>1200</td>\n",
              "      <td>2015-11-22 22:47:44</td>\n",
              "      <td>90</td>\n",
              "      <td>failed</td>\n",
              "      <td>4</td>\n",
              "      <td>US</td>\n",
              "      <td>90</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>1000201265</td>\n",
              "      <td>I'LL SEE YOU IN MY DREAMS - narrative feature ...</td>\n",
              "      <td>Narrative Film</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-02-05 00:57:14</td>\n",
              "      <td>60000</td>\n",
              "      <td>2014-01-11 00:57:14</td>\n",
              "      <td>61365.16</td>\n",
              "      <td>successful</td>\n",
              "      <td>632</td>\n",
              "      <td>US</td>\n",
              "      <td>61365.16</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>1000202062</td>\n",
              "      <td>SkateFrames-Photo frame made from recycled ska...</td>\n",
              "      <td>Art</td>\n",
              "      <td>Art</td>\n",
              "      <td>USD</td>\n",
              "      <td>2015-05-08 02:53:18</td>\n",
              "      <td>7500</td>\n",
              "      <td>2015-04-08 02:53:18</td>\n",
              "      <td>3</td>\n",
              "      <td>failed</td>\n",
              "      <td>3</td>\n",
              "      <td>US</td>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>1000212914</td>\n",
              "      <td>A Teacher's Travels in China</td>\n",
              "      <td>Photography</td>\n",
              "      <td>Photography</td>\n",
              "      <td>USD</td>\n",
              "      <td>2012-05-13 23:34:56</td>\n",
              "      <td>4000</td>\n",
              "      <td>2012-04-18 23:34:56</td>\n",
              "      <td>4866.17</td>\n",
              "      <td>successful</td>\n",
              "      <td>71</td>\n",
              "      <td>US</td>\n",
              "      <td>4866.17</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>1000216800</td>\n",
              "      <td>Mothers Into Living Fit Yoga DVD for Moms and ...</td>\n",
              "      <td>Family</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-06-19 17:18:29</td>\n",
              "      <td>11000</td>\n",
              "      <td>2014-05-20 17:18:29</td>\n",
              "      <td>11055</td>\n",
              "      <td>successful</td>\n",
              "      <td>51</td>\n",
              "      <td>US</td>\n",
              "      <td>11055</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>1000217634</td>\n",
              "      <td>Mobile barbecue &amp; catering trailer</td>\n",
              "      <td>Food Trucks</td>\n",
              "      <td>Food</td>\n",
              "      <td>USD</td>\n",
              "      <td>2014-10-23 20:29:00</td>\n",
              "      <td>13750</td>\n",
              "      <td>2014-09-24 03:35:33</td>\n",
              "      <td>1</td>\n",
              "      <td>failed</td>\n",
              "      <td>1</td>\n",
              "      <td>US</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>1000226576</td>\n",
              "      <td>Following the Call - A Novel</td>\n",
              "      <td>Fiction</td>\n",
              "      <td>Publishing</td>\n",
              "      <td>USD</td>\n",
              "      <td>2016-02-01 08:06:07</td>\n",
              "      <td>13500</td>\n",
              "      <td>2016-01-02 08:06:07</td>\n",
              "      <td>0</td>\n",
              "      <td>failed</td>\n",
              "      <td>0</td>\n",
              "      <td>US</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>1000227361</td>\n",
              "      <td>UNDERWATER</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>Film &amp; Video</td>\n",
              "      <td>USD</td>\n",
              "      <td>2012-03-26 06:00:00</td>\n",
              "      <td>9500</td>\n",
              "      <td>2012-02-13 19:00:37</td>\n",
              "      <td>9660</td>\n",
              "      <td>successful</td>\n",
              "      <td>121</td>\n",
              "      <td>US</td>\n",
              "      <td>9660</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9a1e308d-3c55-4914-a4f0-cbc4fafb8b2b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9a1e308d-3c55-4914-a4f0-cbc4fafb8b2b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        " # Converting datetime data\n",
        "df['deadline'] = pd.to_datetime(df['deadline'], errors='coerce', infer_datetime_format=True)\n",
        "df['launched'] = pd.to_datetime(df['launched'], errors='coerce', infer_datetime_format=True)\n",
        "\n",
        "# Connverting numerical data\n",
        "for num_column in ['goal', 'backers', 'pledged', 'usd pledged']:\n",
        "    df[num_column] = pd.to_numeric(df[num_column], errors='coerce')"
      ],
      "metadata": {
        "id": "O72Jid3JN-0j"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Getting rid of the undefined columns\n",
        "df.drop(columns=['Unnamed: 13', 'Unnamed: 14', 'Unnamed: 15', 'Unnamed: 16'], inplace=True)\n",
        "\n",
        "# New feature to count the number of characters in the project name\n",
        "df['count_chars'] = df['name'].apply(lambda x: len(str(x).replace(' ', '')))\n",
        "\n",
        "df.drop(columns=['ID', 'name'], inplace=True)"
      ],
      "metadata": {
        "id": "mIcNBuJbvtR3"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['state'].unique()[:10])\n",
        "print('-----------------------------------------------------------')\n",
        "print('\\nNumber of different states: ', len(df['state'].unique()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qcxzPkH9VsPH",
        "outputId": "702b3fbd-5ed8-4e78-bd62-31851f286f4b"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['failed' 'canceled' 'successful' 'live' 'undefined' 'suspended' '4262'\n",
            " '3984' '525' '0']\n",
            "-----------------------------------------------------------\n",
            "\n",
            "Number of different states:  410\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['category'].unique()[:10])\n",
        "print('-----------------------------------------------------------')\n",
        "print('\\nNumber of categories: ', len(df['category'].unique()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Op8tfxGfBBl3",
        "outputId": "eef9fa86-9df0-4d02-cd46-06d41ea54bf4"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['Poetry' 'Narrative Film' 'Music' 'Film & Video' 'Restaurants' 'Food'\n",
            " 'Drinks' 'Product Design' 'Documentary' 'Nonfiction']\n",
            "-----------------------------------------------------------\n",
            "\n",
            "Number of categories:  771\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['main_category'].unique()[:10])\n",
        "print('-----------------------------------------------------------')\n",
        "print('\\nNumber of main categories: ', len(df['main_category'].unique()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YhdUIy0lBjBj",
        "outputId": "f37077b9-80da-4329-866d-0e06e0ea368c"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['Publishing' 'Film & Video' 'Music' 'Food' 'Design' 'Crafts' 'Games'\n",
            " 'Comics' 'Fashion' 'Theater']\n",
            "-----------------------------------------------------------\n",
            "\n",
            "Number of main categories:  120\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['currency'].unique())\n",
        "print('-----------------------------------------------------------')\n",
        "print('\\nNumber of differnt currencies: ', len(df['currency'].unique()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "53FRgVsBBBvM",
        "outputId": "0589a618-74f1-41c0-834d-4fbddd642757"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['GBP' 'USD' 'CAD' 'NOK' 'AUD' 'EUR' 'MXN' 'SEK' 'NZD' 'CHF' 'DKK' 'HKD'\n",
            " 'Music' 'Food' 'Theater' 'Technology' 'Film & Video' 'SGD' 'Games' 'Art'\n",
            " 'Publishing' 'Design' 'Rock' 'Comics' 'Crafts' 'Photography' 'Journalism'\n",
            " 'Fashion' 'Software' 'Dance' ' Be active!' 'Nonfiction'\n",
            " ' clothing company' 'Painting' ' tango and culture' ' Religion '\n",
            " 'Apparel']\n",
            "-----------------------------------------------------------\n",
            "\n",
            "Number of differnt currencies:  37\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['country'].unique())\n",
        "print('-----------------------------------------------------------')\n",
        "print('\\nNumber of differnt countries: ', len(df['country'].unique()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YbPthnurDKVs",
        "outputId": "cd0e2dce-b625-46e5-8c83-82ced2f71394"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['GB' 'US' 'CA' 'NO' 'AU' 'IT' 'DE' 'IE' 'ES' 'N,\"0' 'MX' 'SE' 'FR' 'NL'\n",
            " 'NZ' 'CH' 'AT' 'BE' 'DK' 'HK' 'LU' '14' '46' '10' '0' '42' 'SG' '35'\n",
            " '780' '122' '213' '2' '3' '126' '73' '19' '1' '142' 'failed' '140' '38'\n",
            " '24' '60' '37' '29' '167' '45' '23' '4' '85' '9' '248' '111' '18' '13'\n",
            " '28' '40' '54' '17' '20' '195' '25' '72' '22' '12' '158' '62' '307' '31'\n",
            " '107' '7' '110' '6' '69' '68' '84' '75' '119' '78' '150' '77' '83' '89'\n",
            " '16' '154' '92' '11' '116' '56' '136' '58' '27' '26' '582' '43' '5' '41'\n",
            " '30' '177' '36' '15' '49' '51' '9854' '168' '8' '57' '283' '61' '33' '74'\n",
            " '157' '405' '91' '174' '813' '66' '52' '114' '288' '109' '21' '32' '169'\n",
            " '50' '98' '483' '289' '88' '124' '159' '222' '65' '631' '59' '53' '117'\n",
            " '197' 'successful' '70' '55' '108' '63' '732' '93' '162'\n",
            " '2015-09-10 18:15:45' '39' '34' '284' '170' '238' '246' '2001' '608'\n",
            " '144' '99' '71' '229' '338' '81' '176']\n",
            "-----------------------------------------------------------\n",
            "\n",
            "Number of differnt countries:  162\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LRB1RQSDawAb",
        "outputId": "e45c94e4-c110-4316-f69a-8c3c49446cb0"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "category                 object\n",
              "main_category            object\n",
              "currency                 object\n",
              "deadline         datetime64[ns]\n",
              "goal                    float64\n",
              "launched         datetime64[ns]\n",
              "pledged                 float64\n",
              "state                    object\n",
              "backers                 float64\n",
              "country                  object\n",
              "usd pledged             float64\n",
              "count_chars               int64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def verify_value(df, column, possible_values):\n",
        "    \"\"\" Convert values that are not in the defined list of possible values to nan \"\"\"\n",
        "    df[column] = df[column].apply(lambda x: np.nan if x not in possible_values else x)"
      ],
      "metadata": {
        "id": "jErUcvkocYaq"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# List of the accepted values for different features (delete errors)\n",
        "list_states = ['failed', 'canceled', 'successful', 'live', 'undefined', 'suspended']\n",
        "list_countries = ['GB', 'US', 'CA', 'NO', 'AU', 'IT', 'DE', 'IE', 'ES', 'MX',\n",
        "                  'SE', 'FR', 'NL', 'NZ', 'CH', 'AT', 'BE', 'DK', 'HK', 'LU', 'SG']\n",
        "list_currencies = ['GBP', 'USD', 'CAD', 'NOK', 'AUD', 'EUR', 'MXN', 'SEK', 'NZD',\n",
        "                   'CHF', 'DKK', 'HKD', 'SGD']\n",
        "\n",
        "\n",
        "verify_value(df, 'state', list_states)\n",
        "verify_value(df, 'currency', list_currencies)\n",
        "verify_value(df, 'country', list_countries)"
      ],
      "metadata": {
        "id": "i0qKektg6M0d"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Testing the function 'verify values' on countries\n",
        "df['country'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0iOsDtqbeHqA",
        "outputId": "3c28c30d-21b1-4e66-c914-e53fe5bb07c4"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['GB', 'US', 'CA', 'NO', 'AU', 'IT', 'DE', 'IE', 'ES', nan, 'MX',\n",
              "       'SE', 'FR', 'NL', 'NZ', 'CH', 'AT', 'BE', 'DK', 'HK', 'LU', 'SG'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# We Consider 'canceled' and 'suspended' as 'failed' by meaning\n",
        "df= df.replace({'state': {'canceled': 'failed', 'suspended': 'failed'}})\n",
        "\n",
        "# checking the data\n",
        "df['state'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MG-wnazWfb94",
        "outputId": "b3bd6b1f-94cd-4a07-aced-de9467d78efb"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "failed        202054\n",
              "successful    113081\n",
              "live            4428\n",
              "undefined       3555\n",
              "Name: state, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Delete live and undefined states\n",
        "df = df[df.state.isin(['failed', 'successful'])]\n",
        "\n",
        "# Check the data\n",
        "df['state'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D-72Q2G3sKhz",
        "outputId": "c02b32d0-a586-4e25-c73e-49391b2f2d2c"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "failed        202054\n",
              "successful    113081\n",
              "Name: state, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# USD Pledged == Pledged (when Pledged is expressed in USD)\n",
        "df['usd pledged'].iloc[np.where(df['currency']=='USD')[0]] = df['pledged'].iloc[np.where(df['currency']=='USD')[0]]"
      ],
      "metadata": {
        "id": "xAr1-VouNbor"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(20, 10))\n",
        "df.isnull().mean(axis=0).plot.barh()\n",
        "plt.title(\"Percentage of NaN in each column\", size=30)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 623
        },
        "id": "kfgGNzZFxNxQ",
        "outputId": "cc08bc38-7905-4001-aa99-eb7a10b33bd4"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.dropna(axis=0, how='any', inplace=True)\n",
        "df.reset_index(drop=True, inplace=True)\n",
        "print(df.isnull().sum(axis=0))\n",
        "\n",
        "print('\\nNumber of duplicates: ', df.duplicated().sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L2wFqKP_A1Ji",
        "outputId": "6255834e-a6fa-4d67-8ab4-7241b5edee29"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "category         0\n",
            "main_category    0\n",
            "currency         0\n",
            "deadline         0\n",
            "goal             0\n",
            "launched         0\n",
            "pledged          0\n",
            "state            0\n",
            "backers          0\n",
            "country          0\n",
            "usd pledged      0\n",
            "count_chars      0\n",
            "dtype: int64\n",
            "\n",
            "Number of duplicates:  0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_without_pledged = df.iloc[np.where((df['usd pledged'] < 1) | (df['pledged'] < 1))[0]]\n",
        "print('Number of projects without the pledged amount in USD:',\n",
        "      len(np.where(df_without_pledged['currency'] != 'USD')[0]))\n",
        "\n",
        "df.drop(np.where(df_without_pledged['currency'] != 'USD')[0], inplace=True)\n",
        "df.reset_index(drop=True, inplace=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9DPgibEmHUA6",
        "outputId": "85913fd0-1ca4-4665-966f-1a7fe09de5f9"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of projects without the pledged amount in USD: 12917\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Get a conversion factor for each campaign so we can make the currency conversion\n",
        "\n",
        "factors = []\n",
        "\n",
        "for idx, currency, pledged, usd_pledged in zip(df.index, df['currency'],\n",
        "                                               df['pledged'], df['usd pledged']):\n",
        "    if (usd_pledged > 0) & (pledged > 0):\n",
        "        if currency != 'USD': \n",
        "            factors.append(pledged/usd_pledged)\n",
        "        else:\n",
        "            factors.append(1)\n",
        "\n",
        "    elif pledged > 0:\n",
        "        df['usd pledged'][idx] = pledged\n",
        "        factors.append(1)\n",
        "    \n",
        "    elif usd_pledged > 0:\n",
        "        df['pledged'][idx] = usd_pledged\n",
        "        factors.append(1)\n",
        "    \n",
        "    else:\n",
        "        factors.append(1)\n",
        "\n",
        "# Generate new features \n",
        "df['usd_goal'] = df['goal']*factors\n",
        "df['year_launched'] = df['launched'].dt.year\n",
        "df['month_launched'] = df['launched'].dt.month\n",
        "df['duration'] = (df['deadline'] - df['launched']).dt.days"
      ],
      "metadata": {
        "id": "kKECej8_5wdN"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['year_launched'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cmijTz4Aop-e",
        "outputId": "9967b1f8-c5b1-4859-af72-f5d73fea1640"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2015    71739\n",
              "2014    64043\n",
              "2016    47398\n",
              "2013    42939\n",
              "2012    39372\n",
              "2011    25119\n",
              "2010    10108\n",
              "2009     1261\n",
              "1970        5\n",
              "Name: year_launched, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Delete data from the year 1970 (errors)\n",
        "df = df[df['year_launched'] != 1970]"
      ],
      "metadata": {
        "id": "rL9JCzbio17Y"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Count the number of campaigns launched during the past seven days\n",
        "launched = pd.Series(df.index, index=df.launched, name=\"count_projects_7_days\").sort_index()\n",
        "count_projects_7_days = launched.rolling('7d').count() - 1\n",
        "\n",
        "plt.figure(figsize=(10, 10))\n",
        "plt.plot(count_projects_7_days)\n",
        "plt.title(\"Number of projects launched over periods of 7 days\", size=20)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 615
        },
        "id": "b-3v_q8MKvwl",
        "outputId": "5ded94ce-38dd-468c-dd60-1669403fa27b"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Create the new feature and make it compatible with our indexes\n",
        "count_projects_7_days.index = launched.values\n",
        "count_7_days = count_projects_7_days.reindex(df.index)\n",
        "\n",
        "df['count_projects_7_days'] = count_projects_7_days"
      ],
      "metadata": {
        "id": "QfvMj_I6Kv3p"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Delete unwanted features for prediction\n",
        "df.drop(['deadline', 'launched', 'currency', 'backers', 'goal', 'pledged', \n",
        "         'usd pledged'], axis=1, inplace=True)"
      ],
      "metadata": {
        "id": "3-ZH-rfKCJ6v"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(20)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "5OEBbUIyILWe",
        "outputId": "7d8760ad-fc9c-484f-e795-f55148b611f4"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          category main_category       state country  count_chars  \\\n",
              "0            Music         Music      failed      US           43   \n",
              "1     Film & Video  Film & Video      failed      US           51   \n",
              "2             Food          Food  successful      US           52   \n",
              "3           Drinks          Food      failed      US           42   \n",
              "4       Nonfiction    Publishing      failed      CA           16   \n",
              "5       Indie Rock         Music  successful      US           13   \n",
              "6           Crafts        Crafts      failed      US           16   \n",
              "7            Games         Games      failed      US           49   \n",
              "8           Design        Design      failed      US           13   \n",
              "9      Comic Books        Comics      failed      US            8   \n",
              "10       Art Books    Publishing      failed      US           27   \n",
              "11           Music         Music  successful      US           30   \n",
              "12         Theater       Theater      failed      US           25   \n",
              "13          Drinks          Food      failed      NO           43   \n",
              "14          Comics        Comics  successful      US           22   \n",
              "15           Music         Music  successful      US           43   \n",
              "16             DIY        Crafts      failed      GB           18   \n",
              "17          Comics        Comics  successful      GB           44   \n",
              "18     Food Trucks          Food      failed      GB           15   \n",
              "19  Product Design        Design  successful      US           29   \n",
              "\n",
              "         usd_goal  year_launched  month_launched  duration  \\\n",
              "0     5000.000000           2012               3        30   \n",
              "1    19500.000000           2015               7        55   \n",
              "2     1000.000000           2014              12        20   \n",
              "3    25000.000000           2016               2        44   \n",
              "4     2500.000000           2013               9        30   \n",
              "5    12500.000000           2013               3        30   \n",
              "6     5000.000000           2014               9        30   \n",
              "7   200000.000000           2016               2        44   \n",
              "8     2500.000000           2015               1        30   \n",
              "9     1500.000000           2014              10        30   \n",
              "10    3000.000000           2015               4        30   \n",
              "11     250.000000           2012               8        15   \n",
              "12    3500.000000           2014               5        29   \n",
              "13    3883.490018           2015               1        30   \n",
              "14     175.000000           2014              10        20   \n",
              "15   10000.000000           2010              12        30   \n",
              "16   12000.000000           2015              12        30   \n",
              "17      67.012400           2015              12        30   \n",
              "18    2267.450503           2015               3        30   \n",
              "19    1000.000000           2016               9        30   \n",
              "\n",
              "    count_projects_7_days  \n",
              "0                   871.0  \n",
              "1                  1336.0  \n",
              "2                  1051.0  \n",
              "3                  1297.0  \n",
              "4                   880.0  \n",
              "5                   837.0  \n",
              "6                  1306.0  \n",
              "7                  1177.0  \n",
              "8                  1778.0  \n",
              "9                  1446.0  \n",
              "10                 1602.0  \n",
              "11                  837.0  \n",
              "12                  984.0  \n",
              "13                 1671.0  \n",
              "14                 1474.0  \n",
              "15                  332.0  \n",
              "16                 1144.0  \n",
              "17                  485.0  \n",
              "18                 1816.0  \n",
              "19                  969.0  "
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              "      <th></th>\n",
              "      <th>category</th>\n",
              "      <th>main_category</th>\n",
              "      <th>state</th>\n",
              "      <th>country</th>\n",
              "      <th>count_chars</th>\n",
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              "      <td>1336.0</td>\n",
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              "    <tr>\n",
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              "      <td>20</td>\n",
              "      <td>1051.0</td>\n",
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              "      <td>Drinks</td>\n",
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              "      <td>failed</td>\n",
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              "      <td>42</td>\n",
              "      <td>25000.000000</td>\n",
              "      <td>2016</td>\n",
              "      <td>2</td>\n",
              "      <td>44</td>\n",
              "      <td>1297.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Nonfiction</td>\n",
              "      <td>Publishing</td>\n",
              "      <td>failed</td>\n",
              "      <td>CA</td>\n",
              "      <td>16</td>\n",
              "      <td>2500.000000</td>\n",
              "      <td>2013</td>\n",
              "      <td>9</td>\n",
              "      <td>30</td>\n",
              "      <td>880.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Indie Rock</td>\n",
              "      <td>Music</td>\n",
              "      <td>successful</td>\n",
              "      <td>US</td>\n",
              "      <td>13</td>\n",
              "      <td>12500.000000</td>\n",
              "      <td>2013</td>\n",
              "      <td>3</td>\n",
              "      <td>30</td>\n",
              "      <td>837.0</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Crafts</td>\n",
              "      <td>Crafts</td>\n",
              "      <td>failed</td>\n",
              "      <td>US</td>\n",
              "      <td>16</td>\n",
              "      <td>5000.000000</td>\n",
              "      <td>2014</td>\n",
              "      <td>9</td>\n",
              "      <td>30</td>\n",
              "      <td>1306.0</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Games</td>\n",
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              "      <td>US</td>\n",
              "      <td>49</td>\n",
              "      <td>200000.000000</td>\n",
              "      <td>2016</td>\n",
              "      <td>2</td>\n",
              "      <td>44</td>\n",
              "      <td>1177.0</td>\n",
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              "      <th>8</th>\n",
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              "      <td>13</td>\n",
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              "      <td>2015</td>\n",
              "      <td>1</td>\n",
              "      <td>30</td>\n",
              "      <td>1778.0</td>\n",
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              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Comic Books</td>\n",
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              "      <td>US</td>\n",
              "      <td>8</td>\n",
              "      <td>1500.000000</td>\n",
              "      <td>2014</td>\n",
              "      <td>10</td>\n",
              "      <td>30</td>\n",
              "      <td>1446.0</td>\n",
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              "      <td>27</td>\n",
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              "      <td>4</td>\n",
              "      <td>30</td>\n",
              "      <td>1602.0</td>\n",
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              "    <tr>\n",
              "      <th>11</th>\n",
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              "      <td>837.0</td>\n",
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              "      <td>25</td>\n",
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              "      <td>3883.490018</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1671.0</td>\n",
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              "      <td>2014</td>\n",
              "      <td>10</td>\n",
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              "      <td>successful</td>\n",
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              "      <td>43</td>\n",
              "      <td>10000.000000</td>\n",
              "      <td>2010</td>\n",
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              "      <td>30</td>\n",
              "      <td>332.0</td>\n",
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              "    <tr>\n",
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              "      <td>18</td>\n",
              "      <td>12000.000000</td>\n",
              "      <td>2015</td>\n",
              "      <td>12</td>\n",
              "      <td>30</td>\n",
              "      <td>1144.0</td>\n",
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              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Comics</td>\n",
              "      <td>Comics</td>\n",
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              "      <td>67.012400</td>\n",
              "      <td>2015</td>\n",
              "      <td>12</td>\n",
              "      <td>30</td>\n",
              "      <td>485.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
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              "      <td>15</td>\n",
              "      <td>2267.450503</td>\n",
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              "      <td>3</td>\n",
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              "      <td>1816.0</td>\n",
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              "      <td>29</td>\n",
              "      <td>1000.000000</td>\n",
              "      <td>2016</td>\n",
              "      <td>9</td>\n",
              "      <td>30</td>\n",
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          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(20, 10))\n",
        "ax = sns.countplot(x='main_category', data=df, hue='state', hue_order=['successful', 'failed'])\n",
        "plt.title('State of the campaign depending on the main category', size=30)\n",
        "\n",
        "total = len(df)\n",
        "for p in ax.patches:\n",
        "    percentage = f'{100 * p.get_height() / total:.1f}%\\n'\n",
        "    x = p.get_x() + p.get_width() / 2\n",
        "    y = p.get_height()\n",
        "    ax.annotate(percentage, (x, y), ha='center', va='center')\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 720
        },
        "id": "xs5e-PkkaePG",
        "outputId": "e4bef149-266e-48e0-d8f7-85f37940d46f"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from itertools import product\n",
        "\n",
        "# State of the campaign depending on the subacategory of a main category\n",
        "\n",
        "cols = ['Publishing', 'Food',  'Fashion', 'Technology']\n",
        "indices = product([0, 1], [0, 1])\n",
        "fig, axes = plt.subplots(2, 2, figsize=(20, 20), sharex=True, facecolor='lightgray')\n",
        "\n",
        "for idx, var in zip(indices, cols):\n",
        "    var_data = df.query('main_category==@var')\n",
        "    sns.countplot(y='category', data=var_data, hue='state', \n",
        "                  hue_order=['successful', 'failed'], ax=axes[idx[0], idx[1]])\n",
        "    axes[idx[0], idx[1]].set_title(f\"{var}'s Category\\n\", fontsize=20)\n",
        "    axes[idx[0], idx[1]].tick_params(axis='y', labelsize=10)\n",
        "\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "NXq9P9pElNfj",
        "outputId": "e5d86589-543c-4560-b18a-d5e32983e713"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x1440 with 4 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gb_failed = df[df['state']=='failed'].groupby('count_chars')['state'].count()\n",
        "gb_successful = df[df['state']=='successful'].groupby('count_chars')['state'].count()\n",
        "\n",
        "plt.figure(figsize=(10, 10))\n",
        "plt.plot(gb_successful, label='successful')\n",
        "plt.plot(gb_failed, label='failed')\n",
        "\n",
        "plt.legend(loc='best')\n",
        "plt.title('Number of Successful and Failed projects depending on \\nthe number of characters in the project name',\n",
        "          size=15)\n",
        "plt.xlabel('Number of Characters') \n",
        "plt.ylabel('Number of campaigns')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 646
        },
        "id": "p3CQSVbmVJ0O",
        "outputId": "b187d7e3-ff04-4de7-d81a-da1ce7cbd8f5"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ],
            "image/png": 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WuiUlv8l8DvxYKVUYV706uakVWmAB5ubrVNw2eW4Ti5NTWPczYLJS6rq4373TMTlGi34/RctJIica8ximB9gkTFuOmHcxd/1TlVL3YdqBJXZUSIfjlVJ3uPs+HdOT8tS416/BdGywMT2jtmHa4pyIGdagpR017sfcMb+nlLobc4d7F+bH7ZUWbutI4E6l1FOYH14b8zn+FngzrrH265jhDZ5QZiiSfTEN2utorbVS6i/AfUqpvphG8z2BM7TWZ7sdVGKlEH/DNPx33Bhe0Fp/gbnI/hd4Syk1FVMaNhDzmT6ttX5fKfUaJmn/EnN8z8D8PnwIoJSahSnVW+hu/yLMgMiNXvzdThBfALcppaowydh1tPAOXWu9RSn1Oaa0cKv7ef4W0zi+ewu3FVVK3QP8XpnR8D/C9LLbsyXbSWI6cKVS6gFMQj0J08i9pe5315uplPozJgnqh+lBPcvtdPM2pvr7ZaXUbzAJ7i2kXrW6EXMu3IRJjO7GtH1rbgiWpzGl9O8opW7EDE9xE+Z8eizZCu75eTWm8X93zM1ZLaZa/zTMeVzlxv858KH7u7IZ833Y7HZciXV2+JlS6u9AldZ6QUvPyxYc/+nAe5he63djhvnoDowD8rXW8W2Id2I+z3sxpYr3YtqLxRLJZzC/ke+7N8jLMSVVBwAbYh0LUvQA5gbrTaXU/Zj2sdeSWklsk7TWm5VSjwO3KKXCwNeY6t/uNH/DdDvmt+N1pdQjmKYkd2OGgpnd5JqizaSNnEjK/XFt8AOjtY51Lx+ESUTOx3QzT7efYkoYXqe+Wi2+Ee4sTG+rPsCzmIvnNZg77lTaxO1Ca70R0w6pGpMMPYT5kT8mri1Jqj7DNKY+EzOky+vu37dj2j/F9rkQk7hNxFSnHYb54Ux0KeZCdz7mIv4AZqy42HaexxyTUZik9hn3743u699g2uhUYYZceMfdXg2mswnAJ5gL6/Nu7PtheuvGShVmY4Yl+AemN2sxphdsrNStMedgOs88hxnG4VbqL8otcS7mAvgM8EdMcv1MK7YD5vP7Hebi+gomab+mldsCQJuxxX6DOQ6xY3lSkysl384mzLFagvn+TcOUjvTADMcTa4B+CqbEaaq73IOYY5SKTzDn9wOYYX4WkkIVojZjmR3txvYkZiiL1ZienYnJuRO33ouYm7BxmO/Dq5hzei5uSZvWWmMaxW/CNAF4DXMzscp9fRVmCJLTMaWOsdLn1pyXzR5/9zM+HfP5XolJ6h7DfFcTS5j+jhkf7Ul32+9geprHtlWN+W2ZjvneTcOcwyNoYU9NtxbkBPd9voL5HM8n7vegja7BJOw3Y34Hv8O8r8ba6MbiWoTpTd0Xc3xvd9eXKcIywHKcltZMCCGEyEWqnefgdKu8twLnuqWHHZpKYYDnXKfMUClBrfVhXscikpOqVSGEEG2mzJiH/4MpjZvrcTiiFZRSR2CGSpqLGQHgLMz80D9saj3hLUnkhBBCpMOdmHZfv3arSkXu2Y6pZr8W035yKXCB1jrZDA0iS0jVqhBCCCFEjpLODkIIIYQQOUoSOSGEEEKIHCVt5ETWU0qdCRRqrZ9OeP592rEHXjZQSl2AmUe1W8J8jlnBHUz2z5iBg/O01olztKa6nZXkQO8/dz7Pc4EH3FkFvIrjcMyQF2PcYWzasq0O+f1qr+9OY5+XEF6REjmRC87EjBUlss9jmLkTj8OMsdXRjcQMgtvT4zjmYj7vZWnYVkf9fr2F+YzSNcZaTEf9vESOkhI5ITopd/qdvEamRErVKOAvWusPml3SI0qpgiamu/JUa2Nz5939tB1CymotOWfdQb5TmfBdiJwmiZzIau7UVT9w/451sb5Fa31z3DLnYmYM6IsZ9f2i+JHd3UnXb8XMMtAXMzL9te5o/I3tdyhmQu/YOEpnY6YBe9Ldvx0X32it9f5J1j1Za/1mXOxXYWbEuAAz1tZdWuvfK6V+hCnl6Y076n2SC9We7pQ8+2Nmr/iN1vq1hJhPBW4ARmNKyZ7BTFcWdl+/GfglZniBPwBjMTNoPNvIZ3AkZkiJfTDTYb0CXKO13h5XtQfwR6XUH4G/aq0vaGRbBZhR7c8C+gPrgL8nTHWEUupXmDkuu2BG0/95rApTKdUFM+3PMcBgzKjzb2OO5da4bTjuNkow825uAYYrpU7EjNK/D2ZohcXAjVrraQkxjAXuAA7B/EYuBq7HzDkcm1FghVIKYJXWeqi7XglmFoZj3e1/BFweG4oj7rw4H1OCeQpmPs6jlVKnYM6BUZjZDr5xP+ukCXKyqlX3fV+JmdLrIsw59jJwlTsrQ7LtPI2336/zMDMCnIaZZuohrfUtccvdTCPnrFvFeQOmlLQMc77fpLWOuOteQELVaqqxKqUuAi7HzL6wBXMsf4KZkaHJzythO80eE6XUAMz5djhmiq81mFkqbo3NKhP3eZ2DOXd+gBl4+bda6+fcafquxIz9NtV9T3ZcHKMx351D3afeBS7TWm9IFrfILVK1KrLdbZgL1peYapKJmCl8Yg7E/NBfDVyMmdbrLwnb+AcmefodZgLoz4E3lFLjUtj/PZixlc7ATDN1I62fduZqzHRA52CmwrrXnffxAsxF4zrMhe3KJOu+iJk663TM/K8vK6X2ib3oXtRexUz5cwomaboYk4jFK8RMrfQE8H0amSJIKbU35sc+NiXbTZi2YbHxpGJVewD3uX/f1si2LDf2SzBTQ53gbq84YdEzMUnzxZjprk7CHLP42P2YpOp4zEX8SMyFMdGvMRfFKZjPFsy8wP9yn/sBZqqqd9x2frFYR2GSlQGYKZwmY6aLGuy+51gbvtPd9zzZXa83Zuom5a53JiYZ/bebxMb7Peam4IfA75RSwzCf60zM+Xke8CYmsW+pqzHzb56PmfPzZ8AVTSzv9ffrXkzV5xnA48BNSqlfJCzT4JxVSh2L+U7MxUz/9WfMsXmwmf01G6tS6v8wTQY+wCSQl2CSua40/3kl09wxKcbMP3yV+/7uxUzV9+ck27obWI85fz8C/urOTXsAZrq/BzDTbJ0Z936GY87pfDeGC4C9gX+5302R46RETmQ1rfUypVQ54NNaJ6tK6g6cqLWuAFBK9Qf+EKuyUkodBZyImQ8yVroxzW20fj3Nj1j+odb6avfv6Uqp72Mu4i+14u0s1Vr/zI3z3+6+LwKGxEqU3JKWycBdCes+obX+vbvMe5hSomuBs90f43uBZ7TWl8ZWUErVAA8ppe7UWm92ny7AlAb8s5lYb8DMc3mK1jrqbq8ceFEpNdGdCPtTt1RqZSPHJuZYTCnaqfHz5dJwrtQwcFpcicpemJLQS6GuquySuPcXwJRSzFJKlWitV8dta73W+qy4x2itH4xb14e5IO+NKWn52H3pJsxF+5C4Ks/pcevFBrr9Umu9Mm7zv8IkbuNi844qpT4GVmIusA/FLfup1rouWVFKnQFs01r/Om6ZRkuzmrEyrlT0PTdJPR1zQ9JAFny/FsW+E268fYHrlFKPxJUoNThnlVJ/Bd7XWv/Ifepd91y8Uyl1e7K5VlOJVSnVE3ND9YDW+qq41V+N205Tn1cyTR4TrfUC6m8QYufNDmCqUuqyhLmeZ2qtr3OX+wyTAJ8CjHK/p++6JfOTMXPAgjmnN2DmoI2V8M3HlEaegGlLKHKYJHIi130eu8i4Frv/D8RMCH805kfsY/fCHzOD1BosT0t4vBhTZdcaM2J/aK1tpdQKoCq+WhAT86Qk69ZVo7rr/pP6i+RIN6aXEt7jTMxd+GhM6QKYqp13Uoj1AEwv0mjcc68AEczk5qlO0A6m1Kw8IYlL5j+xJM61GOirlArGVQ9PwZRcjMAkTjEjMRO4xzRIhJRSgzBVWEdjStxipREfxy12JPBcK9qtHY1J+LbGHYNtwBxMdXi8xAvnAqCHm5z8DfhYa72jhfuPSXa+Ju6/Jdr7+/VawuNXMVWng6g/nrucs0opP6ZkMLHk+kVMidVEkpfSphLrREzi+FQKsaeqyWPi3ohdgSnx3B3znY0pwXzO8bECpp2kUmoj8EHC9/Rbdv2NOhpTomnHve8VmJuM/ZFELudJ1arIdYlDQMTuXmM/hsWYNlnhhH83Y6rLWrP9/GQLtnJbqW6/LMnjAe7fsSrKt9n1Pa5wn49/nxUJd/iNGYBpg1bHvVhspuVVfkWY6qDmJPssLCAPQCk1GVOKNxuTxE7Ardqk4We2S+xuCdwbmCT5RuAI4HuYBCF+3VRjTVSMaf+XeJ4dQcPzLPFz1ZjqwT0wx3CTUup5pVSfVsSRzvO1se1B+r5fyc5rqD+3oeE5W4xpC7bL5xj3uLHzM5VYi9z/W3MONKa5Y3Ilprr9Ncx5cAAQK7FNPHat+Q0pxjRVSHzfe5DaMRJZTkrkREdXDqzFtHVpD9VAKOG5Xu2wn76YJCr+cexiU+7+fzGm7U6iFXF/pzon33p3H3XckpCiuP2lajO7Xphb64fAZwnVx4c1smzi+xwO7IupXno3bv3E9mutjbUckygmaye4rZnY0Fq/BbyllOqBqf57ANNG6uxWxJJJbf1+9W3kcXwilfh5bcIkIonr9ouLKZlUYo19xwa4+8mEH2JKv6+PPeE2K0iXckySmKwtX6beo2hHksiJXNCWUoUZmMbG27XWS9IXUp1SYKhSKj+up+mx7bCfycDXUFe6dCr1HRU05gI1VGv9eJr29xkwWSl1XVy1zemY34xZLdzWDOAapdRJsV68rVQAJPa+PK8F6xK/vlJqCHAQMD9uuRnAmUqp6xsZ4iKxRGqX9TBtvlo91InWegvwvJugZmpcPi+/X5OBR+Ien45J4hq0cYvRWkeVUnMwCVD8umcCNo1X+6cS62xM79kfEdduLUFbSzkTteW8TsUMTFvQOVprmVy9A5JETuSCJcCpSqnTMD/w67TW61JcdzpmGIvpSqm7gUWYBtzjgPzE4S9a4XXMcAZPuEM57Itp3J5uP1VK1QILMW2IhmN6v8bazF2NGZKhO6a6sBZTdXIacIbWuqWDot6OKd17XSn1CKbN0t3Ae25Hh5aIHYPnlVK3YnoaDgAOjWvonup2HlJKXY9JNE/A9HJNxRLMuXOfUuoGoBumZ+/ahOVuwfRk/NDtDbgZc0w3a62nYpJmgJ8ppf6OaeO4ALgf0yNwplLqz+52+wGHAbO01i80FphS6meYpO1dzLAsIzBJSmJnkPbi5fdrb6XUY5j2l4diOp5cET90RiNuwnQceArTqH8MpjT08WQdHVKNVWtdqZS6DbhDKRXCVHXnYUpJb9Far6Vtn1djcV3udl5Yhknihrdhe4luxtz0vaWUmoophRuI6YD0tNb6/TTuS3hA2siJXPAwpsHwVMxF9uJUV3TvQE93170S80P+GObC2dKSpWTbX4hJ3CZiqtYOwwwdkG5nY0ovXseMg3aW1rquGlVr/SKmlG4cpqH3q5jennOpL0VKmdZ6EWaIj77utm4HXqAVQ6+4x2AyZtiKKzGJ5u20vFrnMcxQJ1e4MQ3BDImSSgw1mPMgghmC4jbM0CwfJCynMZ05NmGqol7DvOdV7uurMCU1p2M6SfzLfX4Tps3eEsx4Z9MwvRJ7sGuJXzLzgT6YZHAa8H+YoTh+k8p7SwMvv1/XYJKpVzDDctxG80OIoM3Yf2djGuv/y933fZihUhI5LYlVa30npnf00Zhhcx7DzOQRqyJv9efViFsx363Yd6yW+iFz2kxr/Q3m3KzCfAffwdyw1LBrRwqRoyzHkZJWIYQQmaOSDJrdDvu4DLhXa53OalAhso5UrQohhOgw3E45h2IGfp7jcThCtDupWhVCCNGRdMNUm/pJXtUqRIciVatCCCGEEDmqs1at5mEGA10PRJtZVgghhBDCS35Mb//PSRiuprMmct/DTDgshBBCCJErDiGhR3hnTeTWA1RU7MC22161XFTUlc2bt7d5O8Ibcvxylxy73CbHL3fJscssn8+iV68ukGT6uM6ayEUBbNtJSyIX25bIXXL8cpccu9wmxy93ybHzRIPmYNJrVQghhBAiR0kiJ4QQQgiRozpr1aoQQgghEjiOw/btW9i5czu23figDmVlPmy7uSlxRUsFAiF69eqD3596eiaJnBBCCCEAqKjYiGVZ9O7dD7RbYTMAACAASURBVL8/gGVZSZcLBHxEIpLIpZPjOOzYsZWKio0UFw9IeT2pWhVCCCEEALW11fTsWUQgEGw0iRPtw7IsunTpTiRS26L1JJETQgghhMvBsiQ18Eprkmc5WkIIIYQQOUoSOSGEEEKINlqzZjUXXnguF154LtOmvdPksmeccTLLl3+blv1KZwchhBBCiDb64IOZjB69D1df/ZuM7lcSOSGEEEJkperqam6//SZWrlyO3x+gpGQIEycexCeffMTtt98DwNtv/2uXx88++xTTp7+LZfkoKCjg4YefwOfz8eab/+Tll/8OQDAY5J57/kDv3kXMnj2LZ56ZSk1NLcFgkMsuu4rRo8ewevVK7rjjFqqrq7HtKMcffzLnnjuFjz56n8cffwSfz080GuFXv7qGTZs28tJLL2DbNgsWfMUdd9zDFVdcwj33/IE99hgOmFK4+MfpIomcEEIIIZL6eMF6Zs1vML0nlgVOG2foOnjsAA4a0/QwG599Npuqqh0899zLAGzdupVZsz5odPl33nmTWbM+5NFHp1JY2IUtWyrx+XzMnfsFzz77FA8//ARFRcVUVVXh9/tZu7aUp59+kvvv/zNdunRl+fJl/O//Xs6rr77Fq6/+g4MPPpQpUy6s2zfAE088xjXXXM/o0WOJRqNUV+9k/Pj9WbNmNTt37uSXv7yybR9MC0kiJ4QQQoisNHz4CFauXMF9993Nvvvux6RJBze5/Mcff8Rpp/2AwsIuAPTo0ROA2bM/5vvfP5GiomIACgsLAZMorl1byi9+cXHdNqLRKOXlmxk3bl8efvhPVFdXM378/owfvz8A++23P3/60/0cfviRTJgwKe0lbC0liZwQQgghkjpoTPJSs0wNCDxw4CCee+4lvvjicz799GP+8peHuPDCi7Dt+uLA2tqaVm/fcRwOPHAiN9xwa4PXDj/8KEaPHst///spzz33NG+99QY33ngbl19+NcuWfcucOZ9zww2/5ayzzuOUUyY3WN/v9yfE2bLx4VIlvVaFEEIIkZXKyr7D5/Nz6KGHc/nlV1NZWcFuuw1k2bKl1NbWEg6H+c9/ZtYtf9BBh/D6669QVbUDgC1bKgGYOPEg3n33LcrLNwNQVVVFTU0NBxwwgc8+m83y5cvqtvH114sAKC1dQ+/eRZxwwslceOFFLF5snl+9eiXDhg3nzDPP4dhjj+frrxcnjX3gwMEsWWLW+eKL/9btO92kRE4IIYQQWWnZsm959NEHAbDtKOeffwFjxuzD/vsfwJQpZ1Jc3Ifhw0ewefMmAL7//RPZuLGMiy++kEAgQEFBAQ899Djjx+/PlCkXcOWVl2JZPkKhIHff/QcGDy7hxhtv4667bqOmpoZIJMyYMfuw5557M3PmdKZNe5dg0ExVdsUVVwPwyCMPUlq6Gr8/QNeuXbn22huTxn7RRT/njjtu5h//eIn99tuffv36t8tnZDltba2Ym4YCKzZv3r5LsWdr9enTjY0bt7V5O8Ibcvxylxy73CbHL/ts2LCK/v2HNLuczLXafpIdA5/PoqioK8DuwMpdXstYZEIIIYQQIq0kkRNCCCGEyFGSyAkhhBBC5ChJ5IQQQgghcpQkcqLDiVasw6mt8joMIYQQot1JIic6lGjlOqpeuZGqt+/DsaVHlRBCiI5NEjnRYTiOTfUHU8ECu2wZ4YXveR2SEEII0a4yNiCwUmolUO3+A/iN1vo9pdQE4DGgADM2yvla6zJ3nVa9Jjqn8KKZ2N99S/7hPyWyYg41n79KoGRffD3bZxBGIYQQ7e/DD9/nscceJBQKccstv6OkZGiDZZYsWcyLLz7PTTfdzvr16/jpT6fw1lszWrSf1q7ntUyXyJ2htR7n/ntPKeUDngN+obUeCXwI3AXQ2tdE52Rv20TNf1/GP2g0gREHkXfIjyAQovqDJ6WKVQghctg///kqP/nJz3nqqeeTJnEAo0btxU033Z7ZwLKE11N07QdUa61nuY8fxZSu/bgNr4lOxnEcqmf9FYD8Qy7Asiyswp7kTzyX6vcfJ7zo34TGHOtxlEIIkXvC33xMWH/Y4HnLsmjrzFBBdSjBkQc1ucyf/nQf8+d/yerVq3jttZcpLu7D6tWrCIdrGThwMNdeeyPdu3dn7twveOihP/Lkk8822MaiRQt59NE/s2OHmX/1pz/9OZMmHQzAK6+8xEsvPU+XLl2YOPHgNr0fr2Q6kfubUsoCZgHXASXAqtiLWutNSimfUqp3a1/TWpenGow73UVa9OnTLW3bEi2zbcH7bF+zgKJjf0KPPXave94pPo7vSuey8/N/0HfcJIK9BzS6DTl+uUuOXW6T45ddysp8BAL1lXVRn4VlWUmXbez5VPl81i77Suaqq37N0qXfcN55Uzj44EOprKygZ89eADz66EO88MIz/OIXl+P3+7AsM3WY3+8DzLa3bdvGfffdyf33/4ni4j5s2rSRCy+cwvPPv8yGDet59tmp/PWvL1BUVMQ999xZt56XfD5fi74XmUzkDtFar1FK5QEPAA8Cr2Vw/w3IXKu5z965lR3vTcXXbzg1JQc1OA7WgefjrL6Oda//mYKTfoNlNfyCyvHLXXLscpscv+xj2/Yuc6j6h0+iYPikBsula67VVLbhOA7RqEMkYvPmm/9i2rR3iUTC7NxZzeDBJUQiNtGojeNQ9zeY5efN+5J169Zy5ZWX1W3PsixWrVrFggXzmTjxYHr06EUkYnPyyacxY8Y0z+eQtW27wfcibq7VBjKWyGmt17j/1yilHgbeAP4I1M0Mq5QqBmytdblSanVrXsvMuxHZoubj5yBcQ/6hP8byNUzSfF16mSrWD54kvGgmodFHexClEEKItvrqqy95/fVXeOSRqfTq1Ytp097ljTdebXIdx4Fhw0bw0EOPN3htwYL57RVqRmWk/FAp1UUp1cP92wLOBuYBc4ACpVSsYvrnwMvu3619TXQCjuNQu3gmkeX/JTT+FPy9dmt02cDIg/EPHkvNf1/C3i65vhBC5KJt27bRpUtXevToQW1tLW+99Uaz64wePZbS0tXMnftF3XNff70Ix3HYd9/9mD37YyoqzHXhzTf/2W6xt6dMVQT3A95XSs0HFgIjgUu11jYwBXhEKbUUOAz4LUBrXxMdn1O9neoZD1Mz6xn8u+1JaJ8TmlzesizyD54C0Si1X72VoSiFEEKk04QJkxg4cBDnnHM6v/zlxSilml2ne/fu3HXX/Uyd+hd+9KNzOO+8M5g69S84jsPw4SOYMuVCLrnkJ/z4x+fTtWtutte02trrJEcNBVZIG7ncEyldSPX7T+BUbyO0/+mExh6ftEo1meoPnyL8zcd0OedefF161T0vxy93ybHLbXL8ss+GDavo339Is8ulq42caCjZMYhrI7c7ZpSO+tcyFpkQbeBEaqn+5Hl2vv17rFAhhafdQN64E1NO4gBC+54EjkPtvDfbMVIhhBAic7weR06IZjmRWqr+eTv25tUE9z6KvAPPwgqEWrwdX7c+BNXBhL/+gNC4k3YplRNCCCFykZTIiawXWf459ubV5B/5M/IPmtKqJC5GSuWEEKJpnbTJVVZozWcviZzIerWLZ+Lr0Z/AsAlt3lZ8qZy9oyIN0QkhRMfh9wcIh2u9DqPTikYj+Hz+Fq0jiZzIatFNq7DLlhHc68g2jyIeI6VyQgiRXNeuPams3EhtbY2UzGWY49hs21ZBQUHLZp2SNnIiq4UXzwR/qNn5+Foisa0cMkWQEEIAUFDQBYAtWzYRjUYaXc7n82Hb0ms1vSxCoXy6du3RorUkkRNZy6nZQfjb2QRHTMDK65LWbYf2PYmwnmVK5YZemtZtCyFELiso6FKX0DVGho7JHlK1KrJWeOknEKkluNeRad92fKlcZOtmAJxIDfaWDUTWfU1k1TycaDjt+xUiGad2p9chCCFylJTIiazkOA7hxTPx9d0Df/HQdtlHrFRu7dRriIZrobZql9d9/YZTcMxl+ApbVswtREtEN6+m6vVbCapDyTtoStraggohOgdJ5ERWiq5fgl25nvzDf9pu+/B160PehDPxb15GONANq0svfF16YXXphbN9M9WznqXqtVsoOO4K/MXNj3QuREs5jkPNp38H23bbgwbJm3C2JHNCiJRJIieyUnjRDMjrQmCPA9p1P6ExxzXa1sNXNJid7/2JqjfuIP+Iiwnuvn+7xiI6n+iar4iuXUzepPOwt5YRXvAelj9I3gFneB2aECJHSBs5kXXsHRVEVn5JUB3SpsF/28pfPJTCyTfi6z2Y6ukPUjP3n9IdX6SNY0ep+fQlrB79CO55BHkTzyU46jBq571Jzdw3vA5PCJEjpEROZJ3wkg/BiRLa8wivQ8FX2JPCk35D9Ud/pfaL14isno+/qASrWxG+rsX4uhVjdSvGV9jT61BFjgkv+QC7ch35x16G5Tc/xXmH/AgnGqb2i1exAkFCY4/3OEohRLaTRE5kFceOEl7yPv5Bo/H16Od1OABYgRD5h/+UcJ+hhL+ZRWT55zg123dZJv+wnxBUh3gUocg1Tu1Oar94Df8ARWDI+LrnLctH/mE/oToaoebTF8EfIrT3UR5GKoTIdpLIiawSWTkXZ0cFwYOmeB3KLizLIjT6GEKjjwHACVdjb9uMs30j1bOeJbxijiRyImW1897Eqd6WtGOD5fOTf+TF7KzZQc1nL6Z1VhMhRMcjiZzICtGKddTOe4vIt59idetDoGQfr0NqkhXMx997IPQeSGDwV4S/nY1jR7B88pUSTbO3baJ2wXsEhk/E32f3pMtYvgCBkrFE1y6Cmh2Q37Ipe4QQnYdcdYSnomXLTQK3ci4EggT3PorQPsdjtXDSYC/5B+1N+Ov/EC1bTqD/SK/DEVmu5vNXAKvZnqmW2+7SrtqCXxI5IUQjJJETnnDC1ez890NE1yyAUCGh8ScTHH0Mvvzcm/c0sNueYFlESxdJIieaFC1bTuTb2YTGnYSva1GTy1oFZiBqp6oSeg/MRHhCiBwkiZzwRGTVPKJrFhAafyqhsd/HChV4HVKrWXld8BXvTmTtIvL2n+x1OCKL1c5/Byu/G6FxJza7bKwntFNV2d5hCSFymIwjJzwRXb8EggWExp+a00lcTGDQ3thly3ESpvkSIl508xr8A1RK57zlTg3n7NzS3mEJIXKYJHLCE9F1S/APGInl6xinoH/g3uDYRNYt8ToUkaWcaARnaxm+ngNSWyGYD4EQdpUkckKIxnWMq6jIKXZVJfaWDQQGjPI6lLTx9xsOgRDR0kVehyKylL21DBw75UTOsiyswp5StSqEaJIkciLjous1AP7dOk4iZ/kD+AeMIrJWEjmRnF25DgBfz91SXsdX2BNHSuSEEE2QRE5kXHTdEgjm4ysq8TqUtAoM3Btnywbs7Zu9DkVkIbtyPQC+nv1TXscq6C4lckKIJkkiJzIuun4J/v4jc2qsuFT4B+0NINWrIim7Yh1Wl95YwfyU17EKe0obOSFEkySRExllV23BrlxPoANVq8b4eg3EKugh1asiKXvLhtQ7Oriswp4Q3okTqWmnqIQQuU4SOZFRde3jOlBHhxjLsvAP3Ivo2sU4ju11OCKLOI6DXbm+xYmcLzYEiZTKCSEaIYmcyCgzflw+vuIhXofSLgKDRuNUb8PevMbrUEQWcXZUQLgaX6/UOzpA/VhyUr0qhGiMJHIiozpq+7gY/8C9AMxk50K46js6tKJqFZndQQjROEnkRMbYO7diV6zDP0B5HUq78XXpha/XQCLS4UHEqR96pIWJXIFUrQohmiaJnMiY6Hoz60FH7OgQzz9wL6IbvsGJ1HodisgSduV6CBXUJWapsgq6geWTEjkhRKMkkRMZE12nO3T7uJjAoL0hGib63bdehyKyRKyjg2VZLVrPsnxmLDmZb1UI0QhJ5ETGRNcvwd9vOJYv4HUo7co/YBT4/ERLF3odisgSJpFrWUeHGKuwh3R2EEI0ShI5kRGmfdzaDjUtV2OsYD7+fsNlPDkBgFNbhVNV2eL2cTEy36oQoimSyImMiI0fF+iA48cl4x88FnvTKmrmvoHjOF6HIzzU2h6rMb7CHtLZQQjRqI5dxyWyRnT9EgiE8PUZ6nUoGREacxx2eSm1X7yKU1VJ3qTzsXxy39QZxRI5f2urVgt64FRvxbFtOYeEEA1IIicyIrpOu+PHdY5TzvIHyD/iImoKexKe/w5O1Rbyj/wZViDkdWgiw+zK9eDzY3Xv06r1rcKe4Dg41VvrxpUTQogYub0T7c6u3oZdUdqhx49LxrJ85E84i7yJ5xJZOZedb/8ep2aH12GJDLMr1uHr0a/Vg2DXDwos1atCiIYkkRPtrrO1j0sUGnMs+UddQrRsOVVv3IG9fbPXIYkMsivX4+vRuvZxED/fqnR4EEI0JImcaHfRdbH2cbt7HYpngsMOoOCEq7G3V1D1+m1EN630OiSRAU40gr21rNUdHSB+vlVJ5IQQDUkiJ9pd9LulZvw4f+doH9eYwG57Unjq9eDzU/XGnURWzfM6JNHO7K1l4Nj4erWuowPINF1CiKZJIifalWPb2BVr8RWVeB1KVvD3HkThaTfg6zmAndP+SO3C6V6HJNpRW4ceAUwHmVChJHJCiKQkkRPtytlaBtEI/l4DvQ4la/gKe1J48rUESsZR88nfqP7kbzi27XVYoh3YlesA8PXo36bt+GRQYCFEIySRE+0qWlEKgK/3II8jyS5WMI/8Yy4jOOY4wgunUz39zzh2xOuwRJrZleuxuvTGChW0aTtWYQ9smW9VCJGEJHKiXdnlawGr1fNMdmSWz0f+xHPIm3AWkVVfEln1ldchiTQzc6y2vlo1xpLZHYQQjZBETrQru6IUq3sfrGCe16FkreDoY7EKuhNZ+onXoYg0chwnjYmcqVqV6d6EEIkkkRPtyi5fK+3jmmH5/ASGTSCy+isZMLgDcaoqIVydlkTOV9gDomGorUpDZEKIjkQSOdFunGgYe8sGaR+XguCISWBHCC//3OtQRJrYFW5Hh3SUyLlDkEg7OSFEIknkRLuxt2xwx9CSErnm+IqH4OvRn8i3s70ORaRJ3dAjbRhDLkam6RJCNEYSOdFuTEcH6bGaCsuyCIyYRHS9lim8Ogi7ch0EC+pK09qiPpGTIUiEELuSRE60G7u8FCx/m8fQ6iyCwycAEJZSuQ7BrlyPr9cALMtq87bq51uVEjkhxK4kkRPtxq5Yi69n/04/NVeqfN374u83gsjS2dI7sQNIV49VAEKF4A/IfKtCiAYkkRPtJlpeKu3jWigwYiJ2xVrs8jVehyLawKmtwqmqTFsiZ1mWOwSJlMgJIXYliZxoF064BmfbRmkf10LBPQ4Ay09YxpTLafVzrKZvIGyroAeO9FoVQiSQRE60C7si1tFBSuRawsrvSqBkLJFvP5X5V3NY9LtvAfAXD0nbNmW+VSFEMpLIiXYRS+RkMOCWCwyfiFNVSXT9Eq9DEa0UXbcEq3tffF2L0rZNq7AHtlStCiESSCIn2kW0vBT8Qaxufb0OJecEhoyDYD7hpdJ7NRc5jk1kwzcEBoxK63atwh5QswMnGk7rdoUQuU0SOdEu7Iq1+HrthuWTU6ylrECIwO7fI7Lic5xIrdfhiBayN6+Bmh34d0t3IieDAgshGpKrrGgXdnkpvl7S0aG1giMmQriayKp5XociWihWJe4foNK63fqx5KSdnBCiniRyIu2cmh04VZX4paNDq/kHjMIq7Ent/HdxIjVehyNaILpeY3Xrk9b2cQBWgSmRk/lWhRDxJJETaReN9ViVErlWs3w+8iaeg71pBTvffUCSuRzhODaR9ZpAmqtVwW0jh1StCiF2JYmcSDu7vBSQoUfaKjjsQPIPv4jouiWSzOUIu7zUtI9Lc0cHAKugO2BJ1aoQYheSyIm0s8vXmsnCu/T2OpScFxwxifwjJJnLFdF1bvu49iiR8/mxCrpJiZwQYheSyIm0sytK8fUemJbJwoUkc7kkun5Ju7SPizFjyUmJnBCiniRyIq0cx8EuX4tf2selVXDEJPIP/2lcMifDkmSb9mwfFyPzrQohEkkiJ9LK2bkFp2a7tI9rB8GRB5F/2I+Jrvta5mLNQu3ZPi5G5lsVQiSSRE6klV0em2NVSuTaQ2DkwVhdi4iu/srrUESC9mwfF2PmW92K48g8vEIIQxI5kVZ2hdtjVeZYbReWZREo2YfI2kVSvZpl2rt9HLhDkDhRnOrt7bYPIURukUROpJVdvhYrvxu+gu5eh9JhBUrGQaS2bgYB4b1MtI+D+LHkpMODEMKQRE6kVbSiVKpV25l/t1HgDxGR6tWskYn2cSDzrQohGpJETqSN4zjYFeukWrWdWYEQ/oF7EVn9FY7jeB2OIDPt48C0kQMpkRNC1JNETqSNs30zhKulRC4DAiX74GzbhF25zutQBJlpHwem1yqALSVyQgiXJHIibWIdHfxSItfuAiX7ABBZJdWrXstU+zgAK5gH/hBO9bZ235cQIjdIIifSJhobeqTXbh5H0vH5uvbGVzSY6BpJ5LyWqfZxMVYwD6THshDCJYmcSBu7Yi1Wl15YeV28DqVTCJSMI7phKU7NDq9D6dQy1T6uTiAkQ88IIepIIifSRjo6ZFagZB9wbCJrFngdSqeWqfZxMVYgD2S+XSGESxI5kRaOY2NXSiKXSb4+e2Dld5NhSDxkV1USWbOAwOAxmdtpME9K5IQQdSSRE2nhbNsEkVppH5dBls+Hf/BYImvm49gyZZMXar96B+woobHfz9g+rUBISuSEEHUkkRNpYVeYjg7SYzWzAiX7QM0OomXLvA6l07F3biW8+D8Ehk/A171v5nYsbeSEEHEkkRNpEa0w45lJiVxmBQbtDZafqFSvZlx4/rsQDZO378kZ3a+0kRNCxJNETqRFXY/VUKHXoXQqVl4X/ANGElk9z+tQOhW7ehu1i2YQGHYgvp4DMrvzQAgnLImcEMKQRE6khV2xVjo6eCRQMha7vBR7+2avQ+k0wgumQaSGUIZL4yBWIidVq0IIQxI50WaOY2NXrJdEziOBknEA0ns1Q5yaHdQunE5g9/3x9/bgnA+EcKRqVQjhkkROtJmzbRNEpceqV6we/bG69yWySqpXM6F24XQIVxMaf4on+4/N7OA4jif7F0JkF0nkRJtJj1VvWZZFcI8DiK5ZQKR0odfhdGhObRW1C6YRGDoef1GJN0EEQub/qFSvCiEkkRNpEK2QOVa9Fhp/Mr5eA6j+z1+wqyq9DqfDql34b6itIrSvN6Vx4LaRAxmCRAgBSCIn0sAuX4vVpbf0WPWQFcgj/6hf4NRWU/2fv8gAwe3Aqd1J7YL38Jfsg7/PUO8CiZXISc9VIQSSyIk0MHOsSmmc1/y9B5J30HlE1y6mdt6bXofT4YS/mQU1O8jzqG1cjJTICSHiSSIn2sSxZY7VbBJUhxIYNoHaOa8RWa+9DqdDCS+dja+oBH/fYZ7GEUvkZAgSIQRAINM7VErdBNwMjNFaL1RKTQAeAwqAlcD5Wusyd9lWvSYyx9m+CaJhKZHLEpZlkX/Ij9ixcTnVMx+jyw9uxcrv6nVYOc/e8h32xuXkHXim16HUVa3KECRCCMhwiZxSajwwAVjlPvYBzwG/0FqPBD4E7mrLayKz7HLpsZptrFABBUdfirNzKzvff1yGqUiD8LJPAQgMO9DjSNzhR0Cm6RJCABlM5JRSecBDwCVxT+8HVGutZ7mPHwXObONrIoPqe6xKIpdN/MVDyZtwFtHVX1H1+m3UzPkn0bLl0gmiFRzHIfLtp/gHKHxdi7wOp75ETjo7CCHIbNXqrcBzWuuVSqnYcyW4pXMAWutNSimfUqp3a1/TWpenGlBRUfqqnPr06Za2beWSsp1lRLsV0XdgX69DaZOOePycwyezpSDAjq8/oWbO69TOeQ1fQTcK9tiHrqMm0WWU96VL6dDex65mwwq2V66neOIpdM+C8yTs700V0K3QR7csiKetOuJ3r7OQY5cdMpLIKaUmAvsDv83E/lK1efN2bLvt1U59+nRj48ZtaYgo91StX4XVY0BOv/8OffyGHUFo2BEEqrcRLV1EZM0CqpbPZ8eiWeQdeiGhUYd5HWGbZOLYVX8+Ayw/1X3GUJMF54m9IwzA1vItVGdBPG3Rob97HZwcu8zy+axGC58yVbV6GLAnsEIptRIYBLwHDAeGxBZSShUDtluqtrqVr4kMkR6rucOX343g8AkUHHERXc77A/5Bo6mZ9Yz0bG2G49hEln2Gf/DorOk0Ut9GTnqtCiEylMhpre/SWu+mtR6qtR4KlALHAfcCBUqpg91Ffw687P49p5WviQxxtm2EaFg6OuQYy+en4KhLsLr1oXr6g9jbNnodUtaKbliKs6Oc4PCJXodST3qtCiHieDqOnNbaBqYAjyillmJK7n7bltdE5sjUXLnLyutC4XFX4thRdr73R5xwddLloptWUTPvLRw7kuEIs0Pk29kQCBEYsq/XodSxfAHw+aVETggBeDCOHIBbKhf7+xNgTCPLteo1kRl2xTpAeqzmKl/P/hQcfSk737mP6pmPkX/sZViWubezt2yg5vNXiSz/LwD+3oMJlIz1MtyMc6IRwss/JzB0fH11ZrYIhKTXqhACkJkdRBvYFbE5Vgu8DkW0UmDQaPImnENk1ZfUfvEa9vZyqj98ih0vXUdk9TxC+5wAlkW07FuvQ824aOlCqNlBcPgEr0NpwArkSYmcEALwqEROdAx2xVqpVu0AgqOPwa4opfbLf1E7/x1wHIJ7HUlo35PxFfYgUrqQ6HfLvA4z48LffoqV1xX/oNFeh9JQIE/mWhVCAJLIiVYyPVbXE9xtT69DEW1kWRZ5B/0PTm01BPLI2+8UfN361L3u7zec8NJPcGwby9c5CvGdcDWRVXMJjjjItEnLMlYgJDM7CCEASeREK0mP1Y7F8gcoOPrSpK/5+w4jvHgmduVa/L0HZzgy//mSuwAAIABJREFUb0RWfQmRWgJZWK0KQFBK5IQQRue4vRZpV9djtbckch2dv99wgE5VvRr+9lOsLr3x9x/hdShJWYGQDD8ihAAkkROtZMcSuZ7SRq6js7r3xcrvRvS7ztHhwd5RQXTNQoLDJ9T14s02prODJHJCCEnkRCtJj9XOw7IsfH2HYXeSRC68aAZgE9zzCK9DaVwghBOWqlUhhCRyopXsinVSrdqJ+PsNx96yAad6u9ehtCsnUkPt1/8hMGQ8vu59ml/BI1IiJ4SIkUROtJgTjcgcq52Mv98wAKJlHbudXHjpbDN23JhjvQ6ladJGTgjhkkROtJhdvgaiEfx99vA6FJEh/j57gOXr0O3kHMchvGAavuIh+PuP9DqcJllBGRBYCGFIIidaLFq2HAB/3909jkRkihXMw9d7cIcukYuuXYRduY7Q6GOxLMvrcJoWCIEd7bRz4Aoh6kkiJ1osunE5VkF3rK7FXociMsjfbxjRsuU4tu11KO2idsE0rIIeBIYd6HUozbICIfOHlMoJ0elJIidazC5bjq/P7tlfaiHSyt9vOISr64ae6UiiFeuIrplPcO+jsPw5ME56IA9ABgUWQkgiJ1rGqa3CrlyPv+8wr0MRGVY/MHDHaycXXjgd/AGCex7udSgpsdxEjrB0eBCis5NETrRItGwFAP6+0tGhs7G69TEDA5d1rETOqd5O+JuPCQ6fhK+gu9fhpMatWpUSOSGEJHKiRaIb3Y4OfaSjQ2cTGxi4o03VVbvkA4jWEhxzjNehpKyuRE6GIBGi05NETrSIXbYcq0d/rLwuXociPODvNxynAw0M7NgRwotm4B+4F/7eg70OJ3VBaSMnhDAkkRMpcxyHaNlyKY3rxOoHBu4Y1auRFXNwdpQTGp3lAwAnqOu1Km3khOj0JJETKXN2lOPs3CIdHTqx+oGBO0b1anjpJ1hdi/CXjPU6lJap67UqiZwQnZ0kciJl9QMBS0eHzqpuYOAO0HPVCdcQXbuYwNDxWFZu/RRadZ0dJJETorPLrV8v4alo2XLwBfAV5VBbIpF2/n7DiG5ckfMDA0fWLoRomMCQfb0OpeWCsc4O0kZOiM5OEjmRMnvjcnxFJVj+oNehCA/VDwxc6nUobRJZ+SWECvEPyO55VZOxZPgRIYRLEjmREse2iW5cKfOrig4xMLBj20RXf0WgZCyWLwdmckgUu5mSqlUhOj1J5ERK7Mq1EKmRjg6ibmDgyIo52FvLvA6nVaJly3Cqt+VmtSqYNn2BkJTICSHIwVtR4YW6jg59pKNDZ2dZFoERkwgveI8df78Gq3s/AoNHExg8Bv+APbFi7beyWGTlXPD5CQwe43UorWYF8mT4ESGEJHIiNXbZcggVYvXo53UoIgvkTzyH0F5HElmzgEjpAsL6I8KLZkAgROGJ19RVv2ar6Kov8Q8YhRUq9DqU1pMSOSEEksiJFEU3Lsffdw8sy/I6FJElfD36EerRj9Doo3EitUQ3LKV6xiPULphGQRYncnbleuwtG8gbfbTXobSJFciTNnJCCGkjJ5rnhGuwy0tl/DjRKCsQIjBobwIjJhJZOTerp/CKrPoSIGfbx9UJ5kmJnBBCEjnRvOimleA40j5ONCs48mCwI4SXfeZ1KI2KrJqHr6gEX9cir0NpEysQkhI5IYQkcqJ59kbT0cEnJXKiGf7iIfiKBhP+ZpbXoSRl79xK9LuluV8aBxCQEjkhhCRyIgXRsuVY3YrxFXT3OhSRA4IjD8HeuIJoefYNGBxd/RU4DoGhuZ/ISYmcEAIkkRMpiJYtl2pVkbLA8Alg+bOyVC6yah5Wl974ioZ4HUrbBfJwZPgRITo9SeREk+yqLTjbN0tHB5EyX0F3AkPGEVn6CY4dSbqM4ziEv5mFvW1TxuJyIrVEShcQGDKuQ/S+NiVyUrUqRGcniZxokrSPE60RHHkwzs6tRNcsSPp6+Ov/UP3+E9TOezNjMUXXLYZIbcdoHwfuOHJSIidEZyeJnGhSdONKsCz8xR2gKkpkjL9kDFZBd8K6YfVqdNNKaj55HoBI6aKMxRRZ+SUE8/HvNipj+2xPVjAPIrU4juN1KEIID0kiJ5rk7CjHKuhhBh8VIkWWL0Bg+EQiq+Zh79xa97xTs4Od0x/CKuhOaPypONs2ZmS+VsexiayaR2DwGKzYhPO5LhAy/0elelWIzkwSOdEku2oLVmFPr8MQOSioDgYnSuTbTwHTLq76gydxtpdTcNQlBIYfCGSmVC48/12cnVsI7P69dt9XpsRurmQIEiE6N0nkRJOcqgpJ5ESr+HsPxlc8tK73anjBNCIr5/4/e3ceJ9d91vn+c07t1a3ulnrRvlmyjm3ZlizvJN6yk0BICIEESJiwTGBIgLkMw3Dnhjsw984EhoEZGJYQEsYJEMhCEjsxcZzEq7wntmzJ0rH2pVtS72tVL1XnN39UVatXdbW61nO+79fLL7XOqa76tUpWP/38fs/zELv9/YTWXY3dvB6rYQ3ZzvIGcplzB5l4/kuEr7qV8FX+CeSmM3KqXBUJNAVycllmbBC7QYGcXJnIrjfi9Z1h8rXvMfHcFwlv20fkhrcDYFkW4U27yXQdxnheWV7fG+4m/d2/xF69kfg9v+iLatUCZeREBBTIyWWYbAYzPoKVXF3tpUidiuy8A+wwE099DqtxDfF7fmFWMBXauBsmxvB6T5X8tc3UOOlv/ykAibf9Wq44wEemz62qclUk0BTIyaJMeggAK9lc5ZVIvbLijYS37QM7TOKtv4oVa5h1P7TxOiC3/VlKxhjGH/sbvIFOEm/+FeymjpI+f02IKCMnIhCu9gKkdpnUIIC2VmVF4vf8PObW92E3r513z040YbduzZ2T2/fuZT1vpvM1zj/yMJlEG6ENDqF1Dnb+h47JA98kc/JFYrf/JOFN15fk66g1VuGMnDJyIoGmQE4W5Y3lAjltrcpKWJE4VnN80fvhTbuZfPVhzNQ4VmTxxxUYY5g6+G0mnv0nQg3NZMePMPXadwGwW9Zjt20jc+xZwjtuJ3LjD5fs66g5hTNyKnYQCTQFcrIokxoAUNWqlFVo42448BDZ80cIb9l72ceazCTjT91P5vX9hLftY9NP/F/0Do7j9Z4m0+WSPX+EzOmXsdu2EL/7531V3DDXpYyctlZFgkyBnCzKpIbAsrESq6q9FPGx0LqrIRQhc+7QZQM5b7Sf9CN/htdzkujN7yG6793YsQSWnSHUsYNQxw7Y+87pCljL9vkR4HwgpzFdIsGmQE4W5Y0NYiWbsSyff0OUqrLCUULrdl22n1z2wlHSj/wZJjNJ/G0fJ7Lt5sWfz+8BXN50Fa4yciKBFox/8eSKqBmwVEp40268gS68sYF597yhC6T+5b9DJE7yxz5x2SAuUJSRExEUyMllmNQgtgI5qYDQxt0A87JyJjNJ+jt/AXaI5I/8NqE1G6uxvJpk2WGwQ8rIiQScAjlZlNGcVakQu3UzVnzVvLmrE8/+I17fGRL3/hJ2Y2uVVlfDwlFVrYoEnAI5WZDJTuWmOqiHnFSAZdmENu4m23kIYwwAU8efY+q17xG58R2Et16+mjWorHBMGTmRgFMgJwsyqcJUBwVyUhnhTbsx6WG8/nN4QxcYf+JvsTt2ELvtJ6q9tNoVjmmyg0jAqWpVFjQ91UHNgKVCQvkJDJnTL5E5+SLYIRJv+Te5s2CyICsS1WQHkYDTv5CyoEL1oOasSqXYDauxWzYw+f2vg8mSePuv61zcUpSREwk8ba3Kgqa3VhuUkZPKCW3aDSabPxd3U7WXU/OscFTtR0QCThk5WZBJDYIVwoo3VnspEiDR3W/GiiaI7nt3tZdSF6xwDDM+Uu1liEgVKZCTBXmpAU11kIqzm9cRu+XHq72M+hGOYqa0tSoSZPouLQsyY4NqPSJS43LtR7S1KhJkCuRkQSY1pKkOIrVOZ+REAk+BnCzI05xVkZpnRdQQWCToFMjJPCYzCRNjCuREal04Cl4W42WqvRIRqRIFcjJPofWIrdYjIjXNCsdyHygrJxJYCuRknsJUBzUDFqlx4SiAmgKLBJgCOZnHmw7klJETqWXTGbkpFTyIBJUCOZlnOiOn9iMitU0ZOZHAUyAn85ixAbBDWDFNdRCpZZfOyCkjJxJUCuRkHi81hJVswbKsai9FRC4nkgvklJETCS4FcjKPSQ2q9YhIHbDyW6s6IycSXArkZB6TGtBUB5F6EC5k5BTIiQSVAjmZx9OcVZG6YE0XOyiQEwkqBXIyi8lMwmRKW6si9SCihsAiQadATmYptB7R1qpI7bPUfkQk8BTIySzTzYA1nkuk9oXyxQ7aWhUJLAVyMosZK0x1UEZOpNZZlgXhqDJyIgGmQE5m0daqSH2xwjG1HxEJsHAxD3Ic5z7glOu6Jx3HWQ98EvCA33Fd90I5FyiVZVKDYIch1lDtpYhIMZSREwm0YjNyfwFk8x//dyBCLpD763IsSqrHGxvAatBUB5F6YYVjOiMnEmBFZeSAja7rnnEcJwy8HdgKTAJdZVuZVIWmOojUmUhMGTmRACs2IzfsOM5a4B7gNdd1R/PXI+VZllSLSQ3pfJxIHbHCUWXkRAKs2IzcnwEvAFHgN/LX3gAcKceipHq81AChjddVexkiUqxwDDM+Uu1ViEiVFJWRc133D4C3AG9wXfcf85c7gV8s18Kk8szUBEymNZ5LpI4oIycSbMVm5HBd93UAx3EKwd+xsqxIquZS6xE1AxapG+FY7ocwEQmkYtuP7AP+HLgRiOcvW4ABQuVZmlTa9FQHnZETqRu5jJyKHUSCqtiM3P3Ag8DPA6nyLUeqySiQE6k/kRhGW6sigVVsILcV+I+u65pyLkaqqzCey9YZOZG6UcjIGWPU/1EkgIptP/JV4G3lXIhUn5cagFAEoslqL0VEihWO5X7NantVJIiKzcjFga86jvMUMGskl+u6Hy75qqQqTGoIK6mpDiL1xApHATCZydyUBxEJlGIDudfy/4mPmdSgmgGL1Jt8IMfUBMRXVXctIlJxRQVyruv+XrkXItVnxgawWzdXexkisgyFLJzGdIkEU7HtR960yK0J4JzruqdLtySpFi81SGjzDdVehogsw/R2qipXRQKp2K3VzwAb8h/3Aa35j7uBdY7jvAJ8wHXdo4s9geM4XwO2Ax4wCnzcdd2XHcfZRa69SWv+uT9ceJ4rvSfLZ6YmYGocS82ARepLRBk5kSArtmr1M8CfAi2u624AWoD/AfxV/uMXgL9Y4jl+znXdPa7r3gT8EfDZ/PW/Av7cdd1d5JoOf2rG51zpPVkmkx4CwE42VXklIrIchWIHZeREgqnYQO7Xgd9xXTcNkP/1/wF+w3XdMeA3gVsu9wSu6w7N+G0z4DmO0wHsA76Qv/4FYJ/jOO1Xeq/Ir0fmMOlhAKy4AjmRulI4I6cxXSKBVOzW6hhwK/DMjGs3c2nKg1fMkziO8zfk+tFZwDuAzUCn67pZANd1s47jdOWvW1d4r6fIr4nW1sZiH7qk9vb6rhYbG8iQAtasX0uszr+WK1Hv71+QBf29mwqtJgWsStqsqsM/i6C/f/VM711tKDaQ+13g247jPACcBTYBPwp8PH//zcCXl3oS13V/EcBxnA8B/w34xHIXXEp9faN43sqHVbS3r6KnZ6QEK6qeyYsXARicCGPX+deyXH54/4JK7x14qQwAw/1DjNfZn4Xev/ql966ybNtaNPlU1Naq67qfA24HjpDbFn0duDN/Hdd1v+G67i8VuyDXdT8P3AecAzY6jhMCyP+6gVywePYK78kVMOnc/5CW+lCJ1JVLZ+RU7CASRMVm5HBd94qbAjuO0wisdl33bP73Pwr0k6t6fRn4IPB3+V9fcl23J/+4K7ony2fGRyASv/RNQUTqw/RkB52REwmiRQM5x3H+2nXdf53/+PPAgnuQRY7oagC+5DhOA5AlF8T9qOu6xnGcXwbudxznd4EBYObzXek9WSaTHlY2TqQOWXYY7JAyciIBdbmM3MkZHx9byYu4rnsRuGORe0fIbduW7J4snxkfwUookBOpS+GoqlZFAmrRQM513f8642ON6PI5kx7GalAzYJF6ZIVjysiJBFTRZ+Qcx4kCDtBGrv0HAK7rfq8M65IKM+Mj2K1bq70MkcDpHx7nE595js3tjbzp5k3s29VOOFRsi8+8cEyTHUQCqthZq28EvgTEgCZgGFhFrkr0qrKtTirCGINJj2Bra1Wk4p585TzjE1n6Ryb4q68forkxyn17N3LP3g00N8aKeg4rEtVkB5GAKvbHvj8B/tB13TXASP7X/8zSY7mkHkylwcvojJxIhWU9jycOdLF7+xo++dE7+fWfuJHNHY187amT/Lu/eJovPlrk8WRl5EQCq9it1V3A/5xz7ZPkCiL+qKQrkoq71ENO47lEKunV4/0MjEzw02/ZhW1b7NnZxp6dbVzsT/GF7x7lW8+d4T1v3E40Errs81jhmNqPiARUsRm5IXJbqgDnHce5DlgNlG7GlVTN9JxVZeREKurxlztpboyyZ2frrOtr1yS5/bq1APQOjS/5PFZYW6siQVVsIPfPwDvzH38WeBT4PkWM5ZLa543nM3IJZeREKqV/eJxXTvRx143rFyxuaG9JANAzmF76ycIxzJS2VkWCqKitVdd1f2PGx3/kOM6z5IodHi7XwqRypjNyaggsUjFPHOgCA3fv2bDg/Y5lBHLKyIkEV9HtRwAcx9lIbqbpSdd1O8uzJKk0M645qyKVVChyuP6qVtqaEws+ZlUyQiwSomdw6a1VwlGdkRMJqKK2Vh3H2eI4zpPAaeCbwGnHcZ50HEeNx3zApIc1Z1Wkgl453sfg6CT37F04GwdgWRbtLfHiMnIRNQQWCapiz8jdT+5MXLPruh1AC/Bi/rrUOTM+omycSAU9/nIXLQsUOczV3pIo8oxcFLwsxsuUaIUiUi+KDeRuBn7Ldd0xANd1R4Hfzl+XOmfSIyp0EKmQ3qE0rx7v464bNxCyL/9PcCGQM8Zc9nFWON84WFk5kcApNpB7FrhtzrVbgGdKuxypBjM+rIycSIU8eeA8AHftWb/kY9tbEkxmPIbHlgjQ8scizJTOyYkETbHFDseBhxzH+Sa5sVybybUj+QfHcX6/8CDXdX+39EuUcjPpEUJt26u9DBHfy3oeT77SxQ07Fi9ymOlSC5Lxy47rupSRUyAnEjTFZuTi5HrJTQAd+V+/CiTIBXWbgU3lWKCUlzEmd0ZOzYBFyu7AsXyRwyItR+Zqb4kDRbQgieQep4ycSPAU20fuI+VeiFTJZAq8rMZziVTAYy930tIY5cYlihwK2prjWCwdyFmRXEZO81ZFgqfoPnKO4ySBncwZy+W67tOlXpRUzvScVWXkRMqqezDNoRP9/Ogbti1Z5FAQCYdoWRVbOiNX2FqdKqLnnIj4SlGBnOM4Hwb+FzAJzPwXxQBbyrAuqRBPzYBFKuLxlzqxLIt79m5c1ue1tyToLjojp61VkaApNiP3h8D7XNd9pJyLkcqbHs+l9iMiZTOV8XjylfPsvbqN1asWL1pYSHtLnEMn+y/7mOliB52REwmcYosdJoHHyrgOqRKN5xIpvxfdbkbTU9x30/KycZDLyA2OTjI5lV38QcrIiQRWsYHcJ4A/dhynrZyLkcq7lJFTICdSLo++1ElHS4Jrt61e9ud25FuQ9A4tfv5NGTmR4Cp2a/V14PeBf+M4TuGaBRjXdUPlWJhUhhkfgUgCKxSp9lJEfOlc9yjHzg3xk/ftxLasZX/+pV5yaTa0NSz8oHwgZ1TsIBI4xQZynwc+B/wTs4sdpM6Z9LDOx4mU0aMvdxIO2bzxxqUnOSxkZiC3GMu2IRTR1qpIABUbyLUCv+u67uUH/kndUTNgkfIZn8zwzMEL3HpNB42JK8t6r0pGiEVC9AxePttmReKatSoSQMWekftb4EPlXIhUh0mPYKvQQaQsnj10kfHJLPftW36RQ4FlWbS3xIvoJRfV1qpIABWbkbsN+JjjOP8RuDjzhuu6d5d8VVIxJj2M1aE5qyKlZozh0Zc62dzRyI4NKzu+0N6SoHtgqV5ycRU7iARQsYHcp/P/iY8Y42HGRzWeS6QMjncNc7Z7lA+/3cG6giKHmdpbEhw62Y8xZvHnCsd0Rk4kgIqdtXp/uRciVTCRApPVGTmRMnj0B53EoiFuv27tip+rvSXBZMZjeGyS5saFGwpbkZgyciIBtJxZq2vJbbG2kWs9AoDrup8tw7qkAtQMWKQ8RtNTvHCkm7tuXE8iVvQ/s4u6VLk6vmggRziGmRhb8WuJSH0pqtjBcZz3AMfJ9ZL7FPDx/K8qgKhjnsZz1YSBkQm+/Nhx0hOZai9FSuT5wxfJZD3u2buhJM/X3hIHlmhBEtHWqkgQFVu1+v8BH3Fd9yZgLP/rvwa+X7aVSdkpI1cb/vmJ4zz07Gm+8vjxai9FSuT51y6yoa2BzR2NJXm+tuY4FksEcmFtrYoEUbGB3BbXdb8059r9wIdLvB6pIKOMXNX1DqZ55uBFGhMRHv1BJ8c6h6q9JFmh/uFxjp4b4rZrO1Zc5FAQCYdoWRWj+3ItSCIxjAI5kcApNpDrzp+RAzjlOM6dwA5A47nqmDJy1ffQs6exbfidn93H6qYY93/rCJmsV+1lyQq8eKQbA9x27cqLHGbqaEksnZHLTGCM+raLBEmxgdyngTfmP/4T4FHgAPAX5ViUVIZJD0M0iRVa+WFsWb7+4XGeevU8b7xhPetbG/jZtzp09ozxrefOVHtpsgLPHe5my9pG1q1JlvR525cI5IjEwHiQnSrp64pIbSsqkHNd9w9c1/1K/uPPAbuAm13X/UQ5FyflZdIaz1VN33ruDMbAO+/YCsDeq9u45ZoOHth/iov9qSqvTq5E92Cak+eHub3E2TjIFTwMjk4yOZVd8L4VyRVEaEyXSLAUW7W613GczYXfu657Bhh1HGdP2VYmZWfGR7StWiVDoxM8fqCLO3evoy3fWgLgp99yNZGwzf3fOqItsjr0wuHc4Jtbr+ko+XMXWpD0Di0yhiscBdCYLpGAKXZr9e+AuROfo8DnS7scqSSTHsFWoUNVPPzCWTJZj3fduXXW9ZbGGO+/bwdHzgyy/9ULVVqdXKnnXutmx8amWcF5qVzqJbfw9qoVzvWXUwsSkWBZTtXqiZkXXNc9Dmwr+YqkYsz4sDJyVTCSmuTRH3Ry+7VrWbvAOaq792xg56Zm/ul7RxlOaZusXnT1jnGuZ7TkRQ4FSwZyha1VVa6KBEqxp9zPOY6zz3XdHxQuOI6zD+gqz7Kk3KbnrCojtyK9g2n+5EsH6B+ZIGRZhEIWtm0Rti2aGqK8ad8mbr9uLeHQpZ+ZHnnxLBNTWd71Q9sWfE7bsvi5d1zDf/rs8/zZV17hx+/ewTVbWkrWykLK4/nDF7Eoz7YqwKpkhFgktHgLkogyciJBVGwg9yfA1x3H+UNyEx52AP8O+P/LtTAps4kUGE8ZuRVIT2T4n19+haHRSe7ZswHPM2Sn//M4dWGEz3zzMF978iTvuH0Ld924nkzW47vfP8fNTjsb2xoWfe6NbQ185J3X8MXvHeO/feEltq5bxTtu28It17QTsotNpEulGGN4/nA3zpYWWhYbobVClmXR3pKgd3DhM3CFrVVl5ESCpahAznXdTzuOMwj8ArAZOAv8puu6Xy7n4qR8NJ5rZTzP8KkHDnG+L8W//ak97N62Zt5jjDEcON7HN585xd8/8joP7j/J5o5G0hNZfnSRbNxMP3T9em69poOnD17gW8+f5VMPHOIrj8d56y2b2berndbmeOm/MLkiZ7tHudCf4m23bV76wSvQ3hKne0AZORG5pOgGYvnJDnOnO0idUjPglfnio8d45XgfH3q7s2AQB7kMyt6dbezZ0crrZwf55jOnOXiyn70729iytrg/90g4xD17N3LXng0cONrLvzx/hi989yhf+O5R2prjOJtb2LW5BWdLC+0tCW2/Vslzhy9iWxY372ov6+u0tyQ4dLIfY8y893q62EFVqyKBok6wAaXxXFfuiQNdfPuFs7z55k3cd9PGJR9vWRbOltU4W1ZzoT9Fc0N02a9pWxY37Wrnpl3tnOsZ5fDpAV4/M8iB433sP5irbnU2t/BbH7wJ21YwV0nGGJ5/rZvrtq9mVXL57+1ytLckmMx4DI9N0jxnC1d95ESCSYFcQE1n5NQQeFmOnB7g8w+7XL99DR94885lf34puv1vam9kU3sjb71lM8YYunrHeO5wN994+hT7Xz3PXXs2rPg1Sunh58/w0tFe/r1Pg8wTXcP0DY/znru2l/21LlWujs8L5C71kdPWqkiQKJALqOmMXLyxyiupPRf7Uzz6UicA8WiIeDRMIhYiHLL5x+8epWN1gl/+setroujAsiw2tjfy3rYGDp/q56tPnuC269YSi9TGGGTPGB558Sz9wxO8fKyXfWXeeqw0zxj2v3qecMjipqvL/7W1t+Sybj2DaXZuap59MxQBywJtrYoEyqKBnOM4z7que0f+4//Xdd3fq9yypNxMegRiDVi2YvmC0fQUD+w/yaM/6MSyIBSymZicPQ6pMRHh13/iRpLx2vpzsyyL99+3k0/+/Q/49gtniyqmqITXzwzSPzxByLZ4+PkzvgjkMlkP98wgP3i9hx8c7WFodJLbru2oyN+JtuYEFizYgsSyLAjHVewgEjCX+5dnl+M4cdd1x4HfBBTI+YjGc10ylfH49gtneXD/SVITGe7es4H3vHE7zY0xPGOYmMwyPpklPZGhpTFWc0Fcwa7NLdx0dRv/8uxp7tmzgaYrOItXas8cukAsGuJH7tzKVx4/wYmuYa7aUJ/nMi/0p3hw/0kOHOsjNZEhGrG5YXsr+3a1s8+pTIAaCdsk42FGFmkUbUVioEBOJFAu9x3p68DrjuOcAhKO4zyx0INc1727DOuSMjPpYY3nAg4c6+WLjz3H+d7RG5cnAAAgAElEQVQxdm9bzU+96Wo2dVzabrYti0QsTCIWZvWq8vQHK6WfuHcHn/ib53lw/yl+5m27qrqWyaksL7rd3LKrnTft28RDz57h2y+c4Zd/7PqqrutKvHK8l089cAiAfVe3s29XO7u3ryFahS3sZDxMaiKz8M1wTGfkRAJm0UDOdd2POI7zRnJjuG4FPlOpRUn5mfER7OZ11V5G1YxPZvjH7x7jiQNdbF7byG+8fw83XLWm7tt3rG9t4O69G3js5U7ecsumBUeAVcqB432kJ7Lccf06ErEw9+zdwLefP0vvvWnamks/i7QcjDE89Oxp/vnxE2zuaORj77uh6mtPxiOkxhcO5KyIAjmRoLnsHpHruk8BTzmOE3Vd9/4KrUkqwKSHsdZdXe1lVMXxriE+/eBr9Ayk+eE7tvBL772RwYFUtZdVMj/2hm08c/ACX378OL/63hvm3T95fpgfvN7DaHqKsfRU7tfxDKnxKdpbErmtwl3trGlaWcPhZw5eoKUxyrVbVgPwlps38cgLZ/nOi+f4wJtr/+/exGSWzz50mBeOdHPbtR185J3X1kQRSTIWXjyQC2trVSRoip3s8FnHce4FPgxsBDqBz7uu+2gZ1yZlYjwPMzEauDNyWc/jm0+f5oH9p1i9Ksq//+mbcLasJhKu/jfnUmpujPGO27fw9adOcqxziJ0bc9WNx84N8cD+kxw82U/ItmhMRGhIREjGw7Q2xdnU3sDpi6P8w3eO8g/fOcrWdavYt6udW5x21rcuPk5sISOpSV490cdbb9k83XJkTVOcW6/t4IkDXbz7Ddtr9qwh5Gbo/tk/v8q5nlHef98O3nHblprJ1ibjYc73LfKDRySGmfDPDyUisrSi/iV1HOcXgf8C/A3wHLAF+ILjOJ9wXffTZVyflIGZGAVjfNsMeDQ9xcWBFGPpDGPjuazT2HiGV473cfL8MHfuXsvPvNWp6UBipd5+22Yee6mTL37vGO+75yoe2H+Kw6cHaExE+Il7d3DfTRtJxBb++i/0p3IVma/38NUnTvDVJ07w4bc73FtE8+OCF450k/UMd+xeO3tdt27h2UMXeeJAF++4fcuKvsZSMsZwoT/Fqyf6OXiiD/fsIJGQzb99/x6uv6q12subJZeRm1rwnhWOYcYGKrwiEammYr+T/Xvgra7rHihccBznn4CvAArk6oyfx3NNZTw+8TfPMTQ2v6qvpTHKR9+9m9uvW7vAZ/pLPBrmx+7azue+5fIH//ASTQ1RfvK+ndx300Zi0ctnINetSfLOO7byzju2MjAywf3fOsLnHnYBig7mnjl0gU3tDfNGkW1dt4prtrTwyItnecstmwiHqtuL7+JAioefO8OrJ/rpG871X1vfmuSevRt4y82b6FhdvTOGi2mIRxYvdojENKJLJGCKDeRagdfmXHOBhYdMSk3z83iu77vdDI1N8sE3X832DU00xMO57cNYuOpBQ6XddeN6zl4cZd2aXGByJRWWq1fF+NX33sCff/XVXDBnwb17Lx/MXRxIcbxzmPffu2PB+2+7bQt/+uVXePFIN3fsvlRwMzGV5aWjPfQMpHnnnVvL3nB5fDLD//jiAQZHJ9m9fQ3v+qGtXL99TdWLGZaSiIeZnPLIZL15f6dzZ+Q0okskSIoN5J4C/thxnN92XTflOE4D8F+Bp8u3NCkXP4/neuzlLjpaErz5lk3YNXKmqVpCts2H3u6s+HkiYftSMPetfGbuMsHcs4cuYsGimc8bd7Sybk2Sh58/y23XreXo2UGePniBF450M55vwDyZ8XjfPQsHgqXyj989SvdAevqsZL1I5rfEU+OZ+b0CVbUqEjjF/sj7y8AeYMhxnIvAYP73Hy3XwqR8TNqfW6udvWO8fnaQe/ZuCHwQV2qFYO7GHa187lsuj73cueDjjDE8c+gCzpaWRatebcvibbdt5vTFEf7dn+/nD/7hJZ4/3M3NTju/9cGbuOvG9XzzmdO8cry3bF/Pi0e6eeLAed5559a6CuIAGvJnOxfaXrXCMchOYjyv0ssSkSoptmr1PHC34zibgA1Al+u658q6MimbS3NW/RXIPf5yJyHb4g03rq/2UnxpbmZuaHSS+27aOCsrdKJrmO6BNO+6c+tln+uHdq/jsZc6aUxEeP+9O9m3q3367N6ODU2cPD/Cpx98jf/0kdtobV5ZG5S5+ofHuf9bR9i2bhU/9sbyD7ovtUKRztgCBQ9WJP9nlZmAaG1vEYtIaSyrbC8fvCmAq3NmvDBn1T9tNyansjz96gVudtppSlZ/NJVfFYK5v37gEF9/6iQP7j/FDVet4Q03rGfPzlaeOXSBSNjm5l0dl32eaCTEf/rIbYve+9X3Xs/v/e8X+MuvH+Q//My+eWfBjDE8caCL/Ycusm1tI3dct47t61ct2SLEM4bPfPMwU1mPf/3u3XV5bjIZiwCQXqiXXCQ3fcRkJrAUyIkEgn/7L8iiTHoY22fZuBeOdJOayCx5EF9WLhK2+dUfv4HOnlGePnSBZw9d5MDXDpKMhcl6hr0721bc2mXtmiQfeee1/OXXDvKlR4/zwbdcaiB8cSDF/f9yhCNnBtnU0chjL3XynRfP0dGS4Pbr1nLH7rWL9r379vNnOXx6gH/1w9ewropTL1YisdTWKoDOyYkEhgK5ADLjI1jJ5movo6Qee7mTdWuSOFtaqr2UwNjY3sj7793J++7eweHTAzx98DwHT/bzpn2lCaZvvaaD12/exCMvnmXX5mZuurqdb79wlq89eYJQyOLn3uHwvrc4nDk3wPfdHp47fJFvPHOKB58+xfrWJDs3NrNzUzM7Nzazbk2SMxdH+crjx7l5Vzt31fH2e8P01urlM3IiEgxLBnKO49jAvcBTruuqrt0HTGoIe82mai+jZM52j3K8c5gPvGlnzXTfDxLbtti9fQ27t5e+G9FPvWknJ7qG+exDh1m7+jSnLoywd2cbH3q7w+pVMSzLIhmPcNeeDdy1ZwODoxO8cLibQ6f6+cHrPTz5ynkAGhMRbAtWJSP83A9fU9d/Ty5VrS5wRk4ZOZHAWTKQc13Xcxzn667r+msvLsC88RFCCf9k5B57uZNwyOaHbqjfLIssLByy+ZX37Ob3/vYFeofG+ei7d3PbtR2LBmItjTHeeutm3nrrZjxjuNCX4ljnEMfODXG2Z5QPvGknjYlIhb+K0oqEbcIha+GmwMrIiQROsVurTziOc4frus+WdTVSdiabgYkx3zQDHp/M8MzBC9x6TUfdf4OWhbU1J/jPv3g70XBoWWfvbMtiQ1sDG9oauHvPhjKusLIKWciFih0KGTn1khMJjmL/VTwN/IvjOF8HzgKmcMN13d8tx8KkPC41A/ZHIPf84VwT2fuWMQdU6k9LY6zaS6gpyVh4wTNyVj4jhzJyIoFRbCCXAL6W/9g/h6sCyG/juR57qZON7Q3s2OiPr0ekGMl4eOGt1emMnOatigRFsQ2BP1LuhUhlmPQQAHadB3KZrMerJ/o4dWGEn3nrrro+vC6yXItn5GY0BBaRQCj6wInjONcA7wfWuq77McdxHCDmuu4rZVudlNz0eK46C+RG01PTh9aPdQ5x6vwwkxmPxkSEO3cvPNNTxK+S8TA9g+n5N3RGTiRwigrkHMd5P/AXwFeAnwY+BqwCPgm8pWyrk5IrZOTqJZBLT2R46NnTPPz8GTJZQ8i22LJ2Fffs3cjVm5rZtaWFZFxFDhIsyXhk4YbAtg2hsAI5kQApNiP3+8BbXNc94DjOT+WvHQD2lGdZUi5eehhCEYiUdn5lqXnG8MzBC3z58eMMjU5y5+513L1nPdvWNxGL+Ge0mMiVSMbCpMYzGGPmHSuwwnFtrYoESLGBXAdQ2EI1M341Cz9capVJD2Mlmmr6TNnxriG+8J2jnOgaZvv6Jj723hvYsdE/fe9EVqohnhuHNjnlEYvO+cEmElNGTiRAig3kvg98CPjcjGsfAJ4v+YqkrAqBXC0yxvCVx0/w0LOnaW6I8gvvupY7r1+HXcNBp0g1zJy3OjeQs8IxZeREAqTYQO7XgG87jvMLQIPjOA8Du4C3lW1lUhYmPYLVUJvzSB/cf4qHnj3NXTeu5wNvvppETKOARRYyc0zX6lVzeuxFYprsIBIgxbYfOZKvWv0R4BvkmgJ/w3Xd0XIuTkrPpIcItW2p9jLmeeTFs3ztqZO84YZ1/NwPX6MsnMhlJGdk5OaywjHNWhUJELvYB7qumwL2A48BTyqIqz/GmFxGrsa2Vve/ep4vfOco+3a1868UxIksqSFfqb1QLzmdkRMJlmLbj2wB/h64AxgAVjuO8yzws67rni7j+qSUJsbAZLHitRPIvfR6D3/70BGu3bqaj777OkJ20T9biARWYWt1sXmrnrZWRQKj2O+a95MreGhxXbcDWA28mL8udcIbz4/nStZGIHf4VD9/+fWDbFu/io+/7wYiYbUVESlG4nJbq5EYaESXSGAUG8jdDPyW67pjAPlt1d/OX5c6YVL5QK4GMnKHT/Xzp//8KmvXJPmN9+8hHlVhg0ixChm5sfGp+TcjcRU7iARIsYHcs8Btc67dAjxT2uVIOZkaycg9ffA8f/zFA7Q1xfnNn9pLY0KTGUSWIxyyiUVCpBbZWmVqEmPU5lMkCBZNgziO8/szfnsceMhxnG+Sq1jdDLwT+IfyLk9KyaSrm5EzxvCNZ07z1SdOcM2WFj724zdovJbIFUrGwwturRKOgsmCl8lNcRERX7vcftbmOb//5/yvHcAE8FWgtuc8ySy5QM7Ciq+q+GtnPY/PP/w6Txzo4o7da/n5d15LOKTCBpErlYyFFy52KIzfm5pQICcSAIsGcq7rfqSSC5HyM+lhrHhjbrB2BY1PZvjLrx3i1RN9vOvOrfz43VfV9IgwkXqQjIcXOSOXaxBsMhNYNFZ4VSJSaUWfMHccJwnshNn/Mriu+3SpFyXlUa3xXJ9+8DUOneznw+9wuHfvxoq/vogfJWNhBkbnFzVY4Xwgp15yIoFQbB+5DwP/C5gE0jNuGaD2xgTIgrwqBHKZrMfBk/3ct2+jgjiREkrGw3T2js27buUzcpq3KhIMxWbk/hB4n+u6j5RzMVJeJj2M3b69oq95tnuUqYzHrs21Od9VpF4lY5EFq1aZzsipl5xIEBR7WGqS3GguqWPV2Fo91jkEwI4N1e9dJ+InyXiY9EQGb06bEWXkRIKl2EDuE8AfO47TVs7FSPmYzCRMjVc8kDveOcSaphhrmlTgLFJKyXgYA4xPZGffCOf+XzNTk5VflIhUXLFbq68Dvw/8G8dxCtcswLiuq7lKdWC6h1wVMnI7NzZX9DVFgqAw3SE1PkUyfumfcisSzX2grVWRQCg2kPs88Dngn5hd7CB1ohDI2RUM5PqHx+kfnmDHrQrkREqt0Ex7XlPgfB85jekSCYZiA7lW4Hdd19XMlzpVjYzc8a7ca+7cpEBOpNQKWbi5BQ/T7UcUyIkEQrGB3N8CHyKXlVs2x3FayWX1dpArnDgKfNR13R7Hce4APgUkgFPAz7qu253/vCu6J/NVI5A7dm6IaNhmc4eakoqU2vTW6tyMXCgCWLnJDiLie8UWO9wG/I3jOK7jOE/M/K/IzzfAH7qu67iuewO52a2fdBzHBv4O+FXXdXcBTwCfBLjSe7IwryoZuSG2rVulUVwiZVDIyM2d7mBZFkRiaggsEhDFZuQ+nf/viriu28/s9iXPAr8C3AyMu677VP76X5HLrv38Cu7JAkx6GCLx6W2XcpucynL6wghvu23uyF4RKYWGfCC34LzVcEztR0QCoqhAznXd+0v1gvls2q8AD5CbCnF6xuv0Oo5jO46z5krv5YPGorS2lm7Lr7298oPol+OiSWEamiu2zkMn+sh6hn3Xrqv5Pxuo/fdPFhfU987zDJYFhELz/gzS8QTRULYu/mzqYY2yML13taHYEV2LZrpc1/3sMl/zz4BRciO/3rvMzy2pvr5RPG/l9Rvt7avo6RkpwYrKZ3ywHxOr3Dq//9p5ANobozX/Z1MP758sLOjvXTwapqd/bN6fgWdHmBidf73WBP39q2d67yrLtq1Fk0/Fbq1+aM7v15ErXNgPFB3IOY7zR8DVwI+6rus5jnMG2Drjfhvgua7bf6X3il1L0Jj0MPaq9oq93rFzQ3SsTtDUEK3Ya4oETUM8vOiYLlWtigRDsVur9829ls/SXVvsCzmO81/InW17l+u6hX9hvg8kHMd5Y/682y8DX1rhPVmASQ9jdeyozGsZw/HOIXZvb63I64kEVTKWG9M1lxWOYabU8lMkCFZSTvi/gV8o5oGO4+wGfgfYADztOM7LjuN81XVdj1y27y8dxzkK3AP8B4ArvSfzGc/DjI9UrGK1Z2ic4dSU+seJlFkyHp5XtQpgReKgEV0igVDsGbm5AV8S+FlgsJjPd133ELmRXgvdexq4oZT3ZDYzMQrGVCyQO35uCECjuUTKLBEL0z24QOYtHMVkNKJLJAiKPSOXIdcLbqZO4JdKuxwph0vNgCsTWB3rGiIeDbGxraEirycSVA3xCKnx+QfOrUhMDYFFAqLYQG77nN+Pua7bW+rFSHlcCuQqUyp+/NwQV21owrYXTMKKSIkk4+H5kx0AInEVO4gERLHFDqeXfpTUqkpm5NITGc72jPIjd24r+2uJBF0yFmZiMksm682aoJJrCDyJMR6WpckqIn522UDOcZxHmb+lOpNxXffNpV2SlFohkLMrcEbu1PlhjEGFDiIVUBjTlZ7IsCo5o9VPYYJLZhIi8SqsTEQqZamM3N8tcn0j8Gvkih6kxpn0MFg2xMr/dh3rzBU67NhQuZmuIkFVCORScwI5K5IL5MzURK6CVUR867KBnOu6n5n5e8dxWsm1Efkl4J+A3y/f0qRUTHoYK9FUkS2WY53DbGhrIBmPlP21RIIuGcv9fza3KXAhkNO8VRH/K7b9SBPwW8DHgG8A+1zXPV7OhUnpeOmhihQ6eMZwomuIm53KTZAQCbLpjNzc6Q7hSxk5EfG3pc7IJYDfAH4TeAx4Y74nnNQRkx6pSKHDhb4UY+MZdqh/nEhFzNxanUkZOZHgWCojd4rc9Ic/BF4E1jqOs3bmA1zX/V55lialYtJD2M1rl37gCr1+NtcfWo2ARSojGStk5OZMd5jOyKkpsIjfLRXIpclVrf7KIvcNcFVJVyQlZYzJZ+TKX3zw8rFe2prjrFujGhiRSlhsa7VQ4KBeciL+t1Sxw7YKrUPKJTMB2cmyb61OTGZ57dQA9960ActSI2CRSohFQoRsa/7WaqH9iM7IifieOkX63KUecuUtdjh0qp9M1uOmnW1lfR0RucSyLBKx8Pxih4iKHUSCQoGcz1VqqsPLR3tJxMJcvbmlrK8jIrMl42HG5pyRU7GDSHAokPM5L51r0FvOM3KeZzhwvJcbd7TOGhMkIuWXjC0wb1XtR0QCQ991fc6kR4DyBnInuoYZSU2xV9uqIhXXEA+TnlvsYIfADisjJxIACuR8zkxn5Mp3Ru6lYz2EbIsbrlpTttcQkYUl4hHG5p6RA4jElJETCQAFcj5n0sMQTWCFyjcy6+Wjveza3KKxXCJVsODWKrnKVZNRHzkRv1Mg53O5OavlK3S42J/ifF+KvVdrW1WkGhriC1Stki94UEZOxPcUyPmcSQ9jl/F83MvHegF0Pk6kSpLxMJmsx1QmO/tGJI7JTFZnUSJSMQrkfK7cUx1ePtrLpvYG2lsSZXsNEVlcYUzX3HNyVjgKGtEl4nsK5HzOSw+VLZAbTU9x9NyQtlVFqiixyJguwjGN6BIJAAVyPma8DEyMlS2Qe/V4H54x7N3ZXpbnF5GlNeSLjOaN6YrEdUZOJAAUyPlYuXvIvXSsl+aGKNvWl3f8l4gsrrC1mpoz3UEZOZFgUCDnY9PjueKlD7SmMh4HT/SxZ2cbtmWV/PlFpDjJRbZWLfWREwkEBXI+Nt0MOFn69iPu2QHGJ7M6HydSZclFt1ZjmuwgEgAK5HzMjA0CYCdXl/y5Xz7aSzRsc93W0j+3iBQvGQsB86tWCcfAy2KyC0x9EBHfUCDnY15qAACroaWkz2uM4cCxXnZvX0M0Eirpc4vI8kTCISJhe/681Ugs94GyciK+pkDOx8zYIFasseTjuS70p+gbnuCGHa0lfV4RuTK5MV3zix0AnZMT8TkFcj5mUoMlz8YBHDzZD8DubWtK/twisnzJBcZ0FTJymrcq4m8K5HzMGxvAaij9GbZDJ/tZuzqhaQ4iNSIZDy8w2SGe+2BKY7pE/EyBnI+Z1CB2srQZuUzWwz0zyO7tysaJ1IpkLDKvapVCRk5jukR8TYGcTxkvi0kPlTwjd7xziImprLZVRWpIMh6eX+wQjuY+ULGDiK8pkPMpkx4GY7BKnJE7eLIf27K4Rm1HRGpGbmt1TrFDJLe1qukOIv6mQM6nzFiu9Uipe8gdOtnPjo1NJPJjgUSk+nJVqxmMMdPXrHzVquativibAjmfutRDrnSB3Gh6itMXRrStKlJjkvEwxsD4ZPbSxYjaj4gEgQI5nypMdShl+5HXTvVjQIUOIjWmoTCma8Y5uUvtRxTIifiZAjmfMqlBsGyseFPJnvPQyX6SsTDb1q8q2XOKyMol80cdZp2TC0UBC1S1KuJrCuR8yhsbwEo2Y9mleYuNMRw61c+121YTKtFzikhpNMRzgdysjJxlQSSGyaiPnIif6TuyT5nUYEkrVi/0p+gfntD5OJEalMxvrc6tXLXCURU7iPicAjmfMmOlbQZ8qDCWS+fjRGpOQ6KwtTqnKXA4phFdIj6nQM6nvFRpx3MdOtlPh8ZyidSkhYodAKxIXBk5EZ9TIOdDJjMJE2Ml21rNZD2OaCyXSM2KR0PYljV/azWWxEymqrQqEakEBXI+ZFK51iN2iTJyGsslUtssy8pPd5g7bzWhQE7E5xTI+ZA3VtpmwIdO5cdybdFYLpFa1RAPk1ooIzehQE7EzxTI+VAhI1eqrdVDJ/u5amMTybjGconUqmQ8wlh6TiAXTWIm01VakYhUggI5H5qes1qCjNxoeopT50e4XtuqIjWtITF/a9WKJmAyjTFelVYlIuWmQM6HvNQghCIQTa74uQ6dzI3luk6FDiI1rSEemV+1GksCRtMdRHxMgZwPmbFcM2DLslb0PCe6hvn7R15nTVOM7RrLJVLTcsUOs7dWCz/MaXtVxL8UyPmQSQ2seFv14Mk+/tsXXiIeDfFbH7xJY7lEalwhI+cZM33NKgRyKngQ8S19d/Yhb2xl47mee+0i//NLr9DekuD//tDNrF298i1aESmvhngYA4xPzJi3Op2RUyAn4lcqQ/QZYwwmNYDVsPeKPv87L57lC985ytWbW/i1990wPcNRRGpboap8bDwz/f9t7owcoEBOxLcUyPnNZAoyk9gNy8/Ife3JEzyw/xQ3Xd3GR9+9m2gkVIYFikg5NOaDt7HxKdrJjdLT1qqI/ymQ8xlvuofc8s7I9QymeWD/Ke7YvZZfeNe1OhMnUmdmZuSmRXMBnbZWRfxL3619xozlA7llFjucPD8MwNtu3awgTqQONeQzcjNbkOiMnIj/6Tu2z5hUvhnwMosdTl0YIWRbbGxrLMeyRKTMGhL5rdUZ0x2sUBjCUbUfEfExBXI+401n5JYXyJ2+MMKmjkYiYf2VEKlHl7ZW54/pQmfkRHxL37V9xqQGIJrECseK/xxjOH1hhG3r1PRXpF5FwzbhkDV/ukM0qa1VER9TIOczZmxw2RWrPYNpUhMZtiqQE6lblmXREI/Mn+4QS2prVcTHFMj5jJcaWHbF6qkLIwDKyInUudyYLmXkRIJEgZzPmLHBKzofp0IHkfpXGNM1kxVNqI+ciI8pkPMRYzxMahD7CjJym9pV6CBS7xri4VlVq5AvdlBGTsS39J3bR0x6BIy3rIxcodBB5+NE6l8yHpm/tRrLba0aY6q0KhEpJwVyPlLoIbecM3KFQodt6xXIidS7hniY1MScYodoErwsZCersygRKSsFcj5SmOqwnKpVFTqI+EcyHiY9kSXredPXrMKYLp2TE/ElBXI+ciVzVlXoIOIfhekOC4/pUgsSET9SIOcjZmwAsLCSTUV/jgodRPyjIT/dYVYgF8sFcip4EPEnfff2EZMawEo0Ydnh4h5vDGcuqtBBxC+S8fy81YUyctpaFfElBXI+4i2zh1zP0Dhj4xmdjxPxicbpQG5GwcP01qoCORE/UiDnIyY1gJUsPpA7nS90UEZOxB+S+a3VmYFcYWtVgZyIPymQ85HcnNXiCx1OXRgmZFtsalehg4gfLHhGThk5EV9TIOcTJpvBjI8sq2L11HkVOoj4yfQZuZnTHUIRsEOgM3IivqTv4D5hCq1Hijwjp0IHEf+JhG2iEXt2sYNlYUWTaj8i4lMK5HyiEMgVO2dVhQ4i/tQQj8zaWgUgP6ZLRPxHgZxPeGP58VxFZuRU6CDiTw3x8OyqVchn5BTIifiRAjmfuLS1WlxGToUOIv6UjEdmba0C2loV8TEFcj5hxgbADmHFigvMTmuig4gvNcTDpOZl5BIqdhDxKX0X9wlvLNdDzrKsJR9rjOH0BRU6iPhRw0IZOZ2RE/EtBXI+YVKDRW+rqtBBxL+SC5yRI5rUiC4Rn1Ig5xPeaH/RzYBV6CDiXw3xMJNTHpmsN33NiiYhO4nJZi7zmSJSjxTI+YDxMpiRHuymtUU9XoUOIv7VkCjMW9V0B5EgUCDnA2akD4yH3VxcIHe2e5QNbQ0qdBDxoel5q+n581ZRICfiO/pO7gPe0EUArOZ1RT2+q3eMje0N5VySiFRJQ35M1+x5qwkAtSAR8SEFcj7gDecCObupY8nHpicy9A9PsKFVgZyIHxUCuVkFD4WtVRU8iPiOAjkf8IYuQCSOlWha8rHn+3L/kG9oUyAn4kcNha3V8flbqzojJ+I/CuR8wBu6iN28tqgecl29YwBsVCAn4kvTZ73oHMgAACAASURBVORU7CASCArkfMAbulh0xWpX7xjhkE1bS7zMqxKRaigEcqkFAjkVO4j4jwK5OmeyGcxob9EVq119Y6xbkyRk660X8aOQbZOIhWZVrRKJgWXpjJyID+m7eZ0zIz1gDLYqVkUkLxmbPabLsuzcdAdl5ER8R4FcnSu0HikmIzcxmaV3aJwNrclyL0tEqqghESY1Z0yXFU2o/YiID4Ur8SKO4/wR8D5gG3CD67oH89d3AfcDrUAf8GHXdY+u5F7QXOoht3Qg19WXK3RQxaqIvzXEI4xNzB7HZWneqogvVSoj9zXgbuD0nOt/Bfy567q7gD8HPlWCe4HiDV+EaBIrtvS4rULFqgI5EX9LxsOzz8iRL3jQ1qqI71QkI+e67lMAjuNMX3McpwPYB7w1f+kLwP9yHKcdsK7knuu6PWX+UmrOslqP9I0Rsi06VicqsDIRqZaGeGRW1Srktla9kd4qrUhEyqUigdwiNgOdrutmAVzXzTqO05W/bl3hvWUFcq2tpRsa396+qmTPtRxnRnuIb9pV1Ov3Dk+wqaORdWubK7Cy+lKt909WTu/dfO1rkqQmMrS1NU7/kNfd3Mz4wNma+/OqtfVI8fTe1YZqBnJV19c3iueZFT9Pe/sqenpGSrCi5THZKTLDPdixO4t6/VNdQ2xb11SVtdayar1/snJ67xbheUxlPDrPDxGLhACY8CJk0mM19eel969+6b2rLNu2Fk0+VbNq9Syw0XGcEED+1w3561d6L1C84ULrkSIqVqey9A6Oa6KDSAAU5q3Oawo8lcZ4XrWWJSJlULVAznXdbuBl4IP5Sx8EXnJdt+dK71Vu9bXBLKP1yIW+FAYVOogEQUMiF8jNmrdamO4wpRYkIn5SkUDOcZw/dRznHLAJ+I7jOIfyt34Z+LjjOK8DH8//nhXeCwxv+AJAUeO5ChWr6xXIifje9LzVGZWrVkzzVkX8qFJVq78G/NoC148Aty/yOVd0L0i8oYsQa8CKF9F6JF+xulYVqyK+17DAvFXyGTkzkQKdURfxDU12qGOF1iPF6OodY+2aJOGQ3nIRvyuckZs1piua+yFO0x1E/EXf1euYN3SxqG1VyAVyGs0lEgyFjNysM3LaWhXxJQVydcpkJjFj/djN65Z87FQmS/dgWoUOIgERj4WxmJuRy/8gp0BOxFcUyNUpb7gbKK5i9XxfCmNUsSoSFLZlkYyHSS1QtaqtVRF/USBXp7xltB7p6tOMVZGgmTemq3BGbkIZORE/USBXp8xwPpBr6ljysV29Y9iWxdrVOiMnEhTJeJjRmRk5OwSRuM7IifiMArk65Q1dxIqvwootnWXr6k3RsTpBJKy3WyQoGhJzMnLktleVkRPxF31nr1Pe0EWsZbQe0WgukWBpiIdnFTtAvgWJMnIivqJArk55w8W1HpnKeHQPpDXRQSRgkvHIrMkOkM/IKZAT8RUFcnXIZCYwYwNFFTpc7E/hGcOGNp2PEwmShniY1HgGY8ylizEFciJ+o0CuDnlDxbcema5YbVVGTiRIGuIRPGMYn8xOX8tl5NR+RMRPFMjVIW/oAlBkINc7hmXBek11EAmU5ELTHaIJULGDiK8okKtD3nTrkeICuY6WBJFwqNzLEpEaUpi3mpoz3cFMpmZvt4pIXVMgV4fM0EWsRNP0EOzL6ewdUyNgkQC6NG91RiAXS4LxIDNRrWWJSIkpkKtD3tDFomasZrK5ilUFciLBM721OrNyVWO6RHxHgVwd8oYuYhWxrXqxP0XWMwrkRAKoMZHfWp2YvbUKGtMl4icK5OqMmRrHpIewm5cezeWeHQRg27pV5V6WiNSYBYsdYoWMnAI5Eb9QIFdnvKF8oUMRFasHjvXRsTrBujWqWBUJmlgkRMi25hU7AJruIOIjCuTqTLEVqxOTWQ6fHmDPjjYsy6rE0kSkhliWlRvTlZ7TfgRl5ET8RIFcnfH6O8GysFsuX+zw2ul+MlmPPTtbK7QyEak1yXiE0ZnzVnVGTsR3FMjVGa/vDHbzeqxw7LKPO3Csj3g0xK7NLRVamYjUmpbGKIMjl1qNXMrIqWpVxC8UyNWZbN8Z7NYtl32MMYYDx3u5fvsawiG9xSJB1dacoGfoUtBmhaMQCuuMnIiP6Lt8HTHjo5jRviUDuTMXRxkanWTPzrYKrUxEalFbS5yh0UmmMnPmrWprVcQ3FMjVkWz/WQBCbZcP5A4c68UCbrhK5+NEgqytOQ5A3/DM7dWkih1EfESBXB3xes8AYK/ZfNnHHTjey1UbmmhqiFZiWSJSo9qac2fiegdnnImLKZAT8RMFcnUk23cGK9mCnWxe9DFDY5OcPD/CjTuUjRMJukJGrndofPqaMnIi/qJAro54RRQ6vHK8F0Dn40SElsYYIduaF8ihM3IivqFArk6Y7BTeQBehpQK5Y32sXhVjc0djhVYmIrXKti1am+L0zqxcjSbVfkTERxTI1QlvoAtM9rIZuamMx8FT/ezZ0appDiIC5CpXZ2bkiCa0tSriIwrk6oTXlyt0uFxG7vWzg0xMZrlR26oiktfWPDuQs2JJyE5hMpNVXJWIlIoCuTqR7TsD4RhWU8eijzlwrJdI2ObarasruDIRqWWtzQmGxyaZmMr1krMKY7q0vSriCwrk6kSu0GEzlr3wW2aM4eVjvVy7dTWxSKjCqxORWtVe6CWXz8pZsVwghwI5EV9QIFcHjDFk+85cdlv1fF+K3qFxVauKyCzTveQKgdz0vFWdkxPxAwVydcCM9sJk+rKFDgcKbUfUP05EZmid7iWXy8BZ8SYATHqoamsSkdJRIFcHskUUOhw42svmjkbWNMUrtSwRqQPNjVHCIXs6I2fnz9l6w93VXJaIlIgCuTrg9Z4By8Jes3HB+0Njkxw9N8RNV2tbVURmsy2L1pmVq7EGiCbxhi5Wd2EiUhIK5OqA13cGu3k9Vji24P0fvN6DAW5xFq9oFZHgamuOT89btSwLu3mtMnIiPqFArg5k8xWri3nxSDdr1yTZ2N5QwVWJSL1on9NLzm7qUEZOxCcUyNU4MzGGGe1btNBhJDWJe2aQW5x2TXMQkQW1NscZTU8xPpkBcoGcGe3FZDNVXpmIrJQCuRq3VKHDS0d78YzRtqqILGpuCxK7eR0Yk6uIF5G6pkCuxhVGcy2WkXvR7aatOc6WtY2VXJaI1JG2lkILkjmVq0M6JydS7xTI1bhs3xmsRDN2snnevbHxKQ6fGuCWazq0rSoiiypk5KanOzSvBcAb1jk5kXqnQK7GeX1nsNsWzsa9fLSXrKdtVRG5vKZkhGjYpqdQuRpfBZG4Ch5EfECBXA0z2QzeQNei5+O+7/awpinG9vWrKrwyEaknVr6X3HRGzrKwm9SCRMQPFMjVMG+gE7zsgufj0hMZDp7s4xZH26oisrS25sTsFiTNHdpaFfEBBXI1zLtMxeqBY71ksoabnfZKL0tE6lBbS3x63iqA3bQWM9yL8bJVXJWIrJQCuRqW7TsD4ShW09p59150e2hujLJj4/wiCBGRudqa44yNZ0iN53vJNa8Fk8WM9lV5ZSKyEgrkapjXdwZ7zWYse/bbND6Z4dUTfdyyqwNb26oiUoTpytXh/Dm56RYk2l4VqWcK5GqUMYZs3xlCC4zmevVEP1MZj1uu0baqiBSnrTnfSy5fuWqrBYmILyiQq1FmuBsm09jt2+fde/FIN03JCFdvaqnCykSkHk0HcoXK1UQzhKNqCixS5xTI1ahsz0kAQm3bZl2fnMryyvE+9u1qx7a1rSoixWlMRIhFQpcCuekWJMrIidQzBXI1Ktt7CkJh7DUbZ10/cLyPiaksN1+jJsAiUjzLsuZXrjavxeiMnEhdUyBXo7yek9itW7Ds8KVrxvDg/lN0rE5wzRZtq4rI8rQ1xWf3kmvqwBvpwXheFVclIiuhQK4GGc8j23ua0JzzcS8e6eZczyjveeN2QrbeOhFZnrlNga3mteBlMWNqQSJSrxQN1CBv6AJMjc8K5LKex9eePMnGtgZuu3Z+XzkRkaW0tcRJT2QYG58Cchk5QAUPInVMgVwN8vKFDnbbpUDumYMXudCf4j13XaUiBxG5IpdakOSycnaTWpCI1DsFcjUo23MSwjHslvUAZLIeD+w/ydZ1q9i3q63KqxORelVoCjxdudrQAqEo3rAyciL1SoFcDcr2niLUtnV6osOTB7roHRrnx+++CkuTHETkCrW1FHrJ5SpXLcvGbupQ5apIHVMgV2OMl8XrPT3dCHhyKsuDT5/i6k3NXL99TZVXJyL1LBkLk4iFZleuNndoa1WkjimQqzHeQBdkpwi1bwPg0Zc6GRydVDZORFbMsixamxL0zaxcberAG+7GGLUgEalHCuRqTLbnBAChtu2kJzJ885nT7N62mv/T3p1H2XHWZx7/Vt2t91aru9VSt5bWYr2WbNmO5WAbDA5gwgnLgCfBicH2hBPIhJM5w5kJmZmMAbMkxHEScpJgYg6Q4MEYiIOBJGyB2A7G+y7bkl9kqVtbt6RWL1Kvd6mq+eMtyVdCllpWq+uW9XzO6XO769669bv3PX376fett16zvC3hykTk1aBzQR1D1RcFbumCoEI0OZpgVSLySinI1ZhwqB/y9Xiti/jJE7uZmC5z9RtWJ12WiLxKtLe6iwJHUQS41R0ATXgQSSkFuRrjJjr0EoTwb4/u5KI1Hazqbkm6LBF5lehoradYCpicqQBVQU4THkRSSUGuhkRBmXB4J5nOlWwfOMTkTIXXbViSdFki8irSGV9Lbmgsnrna2AaZrIKcSEopyNWQcGQ3hAF+Zy/Pbh8m43usW6Fz40Rk7ixb1ATAi7sPAvElSJoXEWloVSSVFORqSBCv6JDpWMlz20dY3dNKQ1024apE5NWkY0E9S9ob2LT9pfVV3cxV9ciJpJGCXA0Jh/rxCk2M+y3s2Deu68aJyBmxYVU7ducoxVIAuPPkwoP7j0yAEJH0UJCrIcGBPvzOXp7vHwHch62IyFy7YHU7lSBiy053yRG/tQuCEtHUWMKVicipUpCrEVGlSDiyh0znSp7rG6GlIceyrqakyxKRV6Fzli6gkMvw7DY3vOq3LAI0c1UkjRTkakQ4vAuiEK+jl+e2j3DeynZ8reQgImdALuuzvreNTduGiaLIXRQYdJ6cSAopyNWIwxMdBqNOJqbLbFil8+NE5MzZsKqd4UMzDA5P4TUtBD+jmasiKaQgVyOCoX68+lY2DVTwgPWa6CAiZ9Dhc3A3bRvG8zN4zZ0aWhVJIQW5GhEOuYkOz/aPsmJxMy0N+aRLEpFXsfbWOno6G3k2vgyJ39pFcGAHURgkXJmInAoFuRoQlaYJxwYJ25azfc8hztdsVRGZBxtWtfPzXWNMFyvk1l5BND5Eect9SZclIqdAQa4GBMM7gYhdQQdhFOn8OBGZFxesaicII7bsGCW78hIy3esoPn430cxE0qWJyCwpyNWAcP92AJ4eaaS+kGVVd0vCFYnI2WDN0lbq8hme3T6M53kULn8vlKYoPv7tpEsTkVlSkKsB5W2P4Lf18PiOIuf1tpHx1SwicuZlMz7n9S48chmSTPsycuveSHnLPQQju5IuT0RmQYkhYcFQH+GBfiaXv5bR8aLOjxORebVhdTuj40X2DE0CULjkP0O+geKDd2rJLpEUUJBLWHnzPZDN80xwDoDWVxWReXX4MiSHZ696dU0ULrmaYGALlf4nkixNRGZBQS5BUXGS8ouPkFtzOc/snKSno5GFLXVJlyUiZ5G25gLLFjWxKV6uCyC37o34bUspPvwNokopwepE5GQU5BJU/vkDbqHqc67k57vGOF+zVUUkAResbmfr7oNMzVQA8PwMhde+l2j8AKVNP0y4OhE5EQW5hERRRHnLvfiLVrF1qoVKEOn8OBFJxIZV7YRRxOb+kSPbsj3ryfZupPT0v2rFB5EapiCXkGDwBcKxQXLr3sg9T+6hkM+wdmlr0mWJyFlodU8L9YUsT24dOmqCQ+Hy3wLPZ/JbH6P0zA+IwkqCVYrI8SjIJaS8+R4oNPL49Ao2bRvm6tevIpfNJF2WiJyFMr7PRtPJw8/v49O3P84TdogwivCbO2n8jT8m23MexUe+ydS3PkFl79akyxWRKtmkCzgbhVNjVPqeJFz7Rr52bz9rl7Zy1SVLky5LRM5i1/+qYXV3Cz94eCe3fvtZlrQ38LbLVnDp+i7q3/phKv1PMfPgHUz/85+QM68nf+k1+HXNp3SMqDRNsNdS2b2ZYHALpbp6op4LyfVuxF+w+Ay9srkRVUqEI7vd5I8wgCiAMCAKQ7xMDq+5Hb+pAy9XSLpUOcsoyCWg/MJPIQr4p4GlBEHI+9++Dt/zki5LRM5iuazPlRf1cMUFS3jshf18/6EdfPl7W/jO/du5cE0HK5csZtWbb6St/yeUN/2Isr0fCo349a149c149S14dS0uyPgZ8Hx362ehPE0w8ALB/u0uAGVyZBafA2GR0qN3UXr0Lvy2brK9G8muuAivcSFerg5yBTwvmYGjqFIk2LeNYNASDL5AsH8bBCcfWvbqmvGaO/Cb2o/c+k0d7vvmdrx8wzxUL2cTBbl5FoUh5S33Md66hgf6Qt571Tl0tekXW0RqQ8b3uWz9Yi5d18Uz24b59yd288Bze7nnyT0A1Be6+KXOa9lYv4uOQomWTJFceYJweBfh9CEIShCGEIUvPann4XesJH/hr5HpWU+maw1eNk9nZzP7+vqp9D9Jpf9JSk9/j9JT/1JVjefCXK4OMjnXExYGEIXufL0owis04jW24Te24TXEt80dZBavxW+Y3XnHURQRHdpHsH87wVAfwf7thAf63bE8D799Bbn1byaz+By8QiN4Pp6fiYNqBspFwolhpob3Mrp3gOLofvL7t7LAe4oswdEHy+bBz760fxx4/bZusks3kF22Ab+16/QaUc4qCnLzLNj5DNHkCN+duRCzbAFv2qghVRGpPZ7ncdGaDi5a00EYRgyOTNE3cIi+wUNsHzzEI9syBKGbGNHWXKB3cTMr17pJE+VKSKlcoVKpUC5VCMIIP5cnP+OT25Ehv2cv+VyGRe2NBGVoXPgamrpfR4NfJH9gKzMThyhOTlCanqQyPUVQnIYooJDPUSjkqavLk8tlwfMJZ8Ypjg0TDPSRKT5NNiofeQ3juXamWlZB11qaetcThB4Tw/soju4nODSENzVCfXGY9so+CtEMABUvx1i+i+GGjQzmljHgLWGykqW8PaTyYkh9oUhTXY7GOo/Gep/GOo9DUz7PbvfZua8FaKGl8QLOXb6AfSNTDO8fYqE/SXf9DOe2ByyurxCGAWGlQhhUCIMAShU6B3bRtPMZioDX3El22QYyS88n07HC9VBq1EZehoLcPCttvodJr5Hnysu5SUOqIpICvu/R09FIT0cjV1ywBIByJWDnvgm2D7pw1zdwiKe2Hjhqv4zvkcv6ZHyPShBRqgTMbtUvH2iJv44vn/NpayowMl6kXHG9f/msz6rOPMvrJmge76Nzehe9xaepH34MNrv9qp9xOspz0GthCyvZE3WyO+xkX7iA8oyH70E+myGXC8hnI3LZDIVchsnpCvtHp5mcLjM1UyGKX+eanlZ+/cpVbFjVztJFTUc+2w9Nlni+b4Rn+4b5p+0jTEy7oOkBdYUMdfkshVyGkfEZmoODrMvt4fzKIGvG7ye3+R4AgkwdleYl+G095DuXU+joxm9ciN/YBrk6hbyznJfmtfSMMWuB24F2YBi4wVo7mylVvUDf8PAEYXj6r7+zs5mhofFf2B6FAeHILoK9LxLs20qw70WiiWF+OH0BC6+4hjerN64mvFz7Se1T29WWqZkKlSAkl/XJ53wy/tHnt0VRRBBGlMoh5UpAfVMdu/aMMTlTZnK6wsRMmZlihYa6HC2NeVoa4tvGPADDB2c4cHDmyO3o+AwLW+pY0dXM8q4mFrc3HHXMKIoYnygysvNFintewPd98gsW0dTRRfOiJeQbmk7r9YZRxHSxQsb3qMufvF8kjCLGJ0sU8i4UVgewIAwZODDlejwHDrFzYJTM6E4WZ0bozoyyJDPGkswoDX756CfNFqqGlhe428Y2vDjoefkGoihww93xJI0oDPFyBTcsXWiCbP6oWqJykWj6INH0IaLpccjX47d1u/P/4scd73cvCl2g9nxdEGOu+b5He3sTwEqgv/q+tPfI3Qbcaq29wxhzHfAF4E0J1wRA6YX/oPjgnVApArhftK413D28hr0dl/DrF/ckXKGIyNxqqDvxnxTP88hmPLIZH8jS2dlEntn/M91Yl2N51+xnynqeR0tzHS3nnQ/nnT/r/WbL9zwa63Kn9PjWpuPPas34PssWNbFsURNvuLAbgDC8jPHpMuOTJQ5OleibKDI9doDRwd0M791LXTDBAn+K7rBMV2mCBYf2U5kac4HtlF5IFq/QAJkc0cw4vNyybIVG/AVLyCxYwmhXNzPDw0STo4RTo0STY0RTYwB4Da0vna/YuACvvhWIoFJ2s36DElGl7Ca+eJn4fMF4coyXwcvmIJM/cks2h5fNQyaHd9TPebdPwrz65lOewT2XUhvkjDGLgIuBt8Sbvg58zhjTaa0dSq4yx2/uJHfuG8gsWk1m8Tn4Te7K6Us7Bnjnmg4NqYqIyAn5vkdrY57Wxjwvjd8sATYQhhF9ew/x/PYRftg3zO6hSW68fiM9HQ1EMxNEkyNEk6NEpekjkzI87/AEDZ+oPENUnCSamYSSu42Ckut1q2/Br2+JZyI3E5WmCEcHCMcGCccGqOx8hlF7P+Tqj/QA+j1L8BvawPMIJ0ddwDs4SDiwGUrTrnQvc1Qow88cmbziLuUST2YJyqceRpOUq6P5/bcldvjUDq0aYzYC/89ae17Vts3AddbaJ0+yey/QdwbLExERmTdRFM3ruXJRUMbLzK43MqyU8Py45222zx8GRJUSUbnkruFX9f3h7WGldPTs6IRkWzup61k7X4d71Q2tnpYzfY6cpIPaL73Udumm9kuv+Ws7H6hzXxncVw1ec3n8DL8XVefI/eJ9Z/TIZ9YuoMcYkwGIb7vj7SIiIiKveqkNctba/cDTwLXxpmuBp2rh/DgRERGR+ZD2odXfA243xnwcGAVuSLgeERERkXmT6iBnrX0BuDTpOkRERESSkNqhVREREZGznYKciIiISEopyImIiIiklIKciIiISEopyImIiIiklIKciIiISEopyImIiIiklIKciIiISEopyImIiIiklIKciIiISEopyImIiIiklIKciIiISEopyImIiIiklIKciIiISEopyImIiIiklIKciIiISEopyImIiIikVDbpAhKSAfB9b86ecC6fS+af2i+91HbppvZLL7Xd/Kl6rzPH3udFUTS/1dSGK4D7ky5CRERE5BS8HvhZ9YazNcgVgF8GBoEg4VpERERETiQDLAEeA4rVd5ytQU5EREQk9TTZQURERCSlFOREREREUkpBTkRERCSlFOREREREUkpBTkRERCSlFOREREREUkpBTkRERCSlFOREREREUupsXWt1zhhj1gK3A+3AMHCDtXZrslXJ8Rhj2oGvAquBErAV+K/W2iFjzGXAF4B6oB+4zlq7P6la5eUZY24CPgFssNY+p7ZLB2NMHfBXwFXADPCQtfZ39Rla+4wx7wA+DXjx1yettXer7WqDeuRO323ArdbatcCtuD8oUpsi4BZrrbHWbgC2ATcbY3zgDuD343b8KXBzgnXKyzDGXAxcBuyIf1bbpcctuAC3Nv79+1i8XZ+hNcwY4+H+Ab7eWnsRcD1we/y7p7arAQpyp8EYswi4GPh6vOnrwMXGmM7kqpKXY60dsdbeV7XpYWAFsBGYsdYeXoj4NuCaeS5PTsIYU8D9sfhQ1Wa1XQoYY5qAG4CPWWsjAGvtPn2GpkYItMbfL8CtU96B2q4mKMidnmXAHmttABDfDsTbpYbF/01+CPhnYDlxDw+AtfYA4BtjFiZUnhzfp4A7rLX9VdvUdumwGjf0dpMx5nFjzH3GmCvQZ2jNi4P3NcB3jTE7gO/gQrnarkYoyMnZ6m+BCeBzSRciJ2eMuRy4BPh80rXIK5IBVgFPWWsvAf43cDfQlGhVclLGmCzwR8C7rLUrgHcC/4jarmYoyJ2eXUCPMSYDEN92x9ulRhlj/gI4B/hNa20I7MQNsR6+vwMIrbUjCZUov+hKYB3QZ4zpB5YCPwLWoLZLg51AhXgYzlr7CHAAmEafobXuIqDbWvsAQHw7iTvfUW1XAxTkTkM8M+5p4Np407W4/ziHkqtKTsQY8xnceVXvttYW481PAPXxUA/A7wF3JVGfHJ+19mZrbbe1ttda2wvsBt4K/Dlqu5oXD3nfC7wFjsz2XwT8HH2G1rrdwFJjjAEwxqwDunCz/tV2NcCLoijpGlLNGHMubvp1GzCKm35tk61KjscYcx7wHO6Px3S8uc9ae7Ux5rW4GVd1vHQJi32JFConFffKvSO+/IjaLgWMMauAv8ddqqIM3Git/YE+Q2ufMeZ9wP/BTXoAuMla+x21XW1QkBMRERFJKQ2tioiIiKSUgpyIiIhISinIiYiIiKSUgpyIiIhISinIiYiIiKRUNukCREReCWPMV4Dd1tqPJnBsD3cpjXcDW621r3kFzxEB51hrX5zr+kTk7KEgJyJzIr62WwOw0lo7GW/7AO66br+SXGVnxBW4i9suPfxaj2WMWQL8MfA23HJGe4BvAre83D5JiNvtA9banyRcioi8AhpaFZG5lAE+nHQRp+rwMkOnYAXQf4IQtxB4CKgHLrfWNuOC3wLcAvJzJl4LMxHGGM8Yo78jIglSj5yIzKU/B/6XMebz1tqx6juMMb1AH5Cz1lbibfcBd1hrv2SM+W3gg8CjwPuBEeA6YC3waaAA/KG19vaqp+0wxvwYuAx4Endl+R3xc58L/C1uSbYh4GPW2n+M7/sKbnWPFbh1XN8FHNUjOS8wAAAABStJREFUZYzpBm7D9b6NAH9mrf2iMeZ3gFuBnDFmAvhLa+1Nx7wP/xMYx/VGhgDW2l38Ysi9yhjzA6AT+Brw36y1kTFmNfBF4EIgwq0r+/uH39O4F+3vgPe5H00j8JH4/VuEW+/yRmvtt6tezwfjupbG918H/A9gOfAvxpgA+JS19hZjzGXAZ4H1wA7gw9ba+6ra7AHgV4CLgQ3xEmkfj1/HAeCj1tqvISJnnP6TEpG59DhwHy5UvBKXAptwyzjdCXwD+GVgDS54fM4Y01T1+PfhQl4Hbt3HrwHEwebH8XMsAn4L+LwxZn3Vvu8F/gRoBn52nFq+gVtnshv4DeAzxpg3WWu/jFvT9SFrbdNxQhzAVcDdh0PcCbwjfn0XANfg1o8F8IA/jY+9DlgGfOKYfa8F3g4siIPxNuD1QCvwSeCOeHgXY8x74v1vAFqA/wQMW2uvxy1o/874tdxijOkBvocbFl6Ia8tvGWM6q459PfC7uPduCPgb4NfinsfX4tpCROaBeuREZK59HHjAGPPXr2DfPmvtPwAYY74J3IjrJSoC/2aMKeFC3eGg8D1r7U/jx98IHDTGLMOFif7DzwU8ZYz5FvAeXMgB+K619oH4+5nqIuLneB3wdmvtDPC0MeZLuCB0zyxeRzswOIvH3Rz3so0ZY+4FLgJ+GE+AODwJYsgY81ng2MD4N3EvHwDW2ruq7vumMeaPgNcA3wU+gDs377H4/hNNsLgO+L619vvxzz82xjyOO9fvcG/oV6y1zwMYYyq4NTjPN8bstNYOzvK1i8gcUJATkTkVL2T/r7hFtrec4u7Vi91Px8937LbqHrnqIDNhjBnB9WKtAC41xlQP72aBrx5v3+PoBkasteNV23YAl8zmRQDDwJJZPG5v1fdTxK/NGNMF/DWuh60ZN3oyesy+R9VvjLkBN3TaG29qwvVUguvR2zbL2lcA7zHGvLNqWw6493jHttZOGmN+E9dz92VjzAPAH1hrX5jl8UTkNCjIiciZcBPunLW/rNp2eGJAA3Ao/n7xaR5n2eFv4iHXhcAALmj8h7X2LSfYNzrBfQPAQmNMc1WYW46beTobPwGuNsZ8chbDq8fzmbi+DdbaEWPMu4HPHfOYI/UbY1bgzql7M27INzDGPI0bogX3frzcJItj34ddwFettR88QX1H7WOt/RHwI2NMPW5I9ou4ECoiZ5iCnIjMOWvti/HQ6H8Hno23DRlj9gDXGWO+APwXTn8G59viE+0fxZ0r97C1dlfcI3izMeZ63Llu4IYtJ6y1J+0ljJ/jQeBPjTEfwU24+B3cOXmz8VncEOXtxpiPWmt3xOee/QFuWHLTSfZvBg7ihop7gD88yeMbceFqCMAY837g/Kr7vwR81hjzM1zAXg2U44kh+4BVVY+9A3jMGPNWXCDN4SaTvGit3X3sgePew8vix04DE7ihVhGZB5rsICJnyqdwAaPaB3GhZBg4D3jwNI9xJ673bwQ3O/U6gLgX7VdxkxwGcEOYf4ab+Tpb1+KGKQeAbwM3zfZaa9baEdx5emXgEWPMOPDvuHA2mwsAfxI3I/QgbuLB3Sc53mZc7+dDuGC2ATez9PD9d+EmdtyJm037HVzvJbhJFR81xowZYz4Sn3f3LuD/4oLhLlybvdzfCx83pDuAa4crgQ/N4jWKyBzwouhEowsiIiIiUqvUIyciIiKSUgpyIiIiIimlICciIiKSUgpyIiIiIimlICciIiKSUgpyIiIiIimlICciIiKSUgpyIiIiIin1/wG6GzcUnR9QEAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gb_failed = df[df['state']=='failed'].groupby('duration')['state'].count()\n",
        "gb_successful = df[df['state']=='successful'].groupby('duration')['state'].count()\n",
        "\n",
        "plt.figure(figsize=(10, 10))\n",
        "plt.plot(gb_successful, label='successful')\n",
        "plt.plot(gb_failed, label='failed')\n",
        "plt.legend(loc='best')\n",
        "plt.title('Number of Successful and Failed projects depending on \\nthe project''s length',\n",
        "          size=15)\n",
        "plt.xlabel('Duration') \n",
        "plt.ylabel('Number of campaigns')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 646
        },
        "id": "Q21UkSAmoimN",
        "outputId": "4690bcf4-453e-40ff-9285-3189d08fccba"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Find the name of the main categories that represent 90% of the projects\n",
        "n_categories = 11\n",
        "print(df['main_category'].value_counts(1)[:n_categories].sum())\n",
        "print(df['main_category'].value_counts(1)[:n_categories].index)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E7Q7M-ite-VN",
        "outputId": "20799569-f090-45ed-96a4-be1a55a96dcb"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.926809480129413\n",
            "Index(['Film & Video', 'Music', 'Publishing', 'Games', 'Technology', 'Art',\n",
            "       'Design', 'Food', 'Fashion', 'Theater', 'Photography'],\n",
            "      dtype='object')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Find the name of the categories that represent 90% of the projects\n",
        "n_categories = 73\n",
        "print(df['category'].value_counts(1)[:n_categories].sum())\n",
        "print(df['category'].value_counts(1)[:n_categories].index)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yHO8zccx65oW",
        "outputId": "940e429c-ab7e-4367-a2c5-e5f5ad62487c"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.9020627262160614\n",
            "Index(['Product Design', 'Documentary', 'Shorts', 'Music', 'Tabletop Games',\n",
            "       'Food', 'Video Games', 'Film & Video', 'Fiction', 'Fashion',\n",
            "       'Nonfiction', 'Theater', 'Art', 'Rock', 'Technology',\n",
            "       'Children's Books', 'Photography', 'Indie Rock', 'Webseries', 'Apparel',\n",
            "       'Narrative Film', 'Apps', 'Comics', 'Publishing', 'Web',\n",
            "       'Country & Folk', 'Crafts', 'Hip-Hop', 'Design', 'Hardware', 'Pop',\n",
            "       'Painting', 'Public Art', 'Games', 'Software', 'Mixed Media',\n",
            "       'Classical Music', 'Illustration', 'Animation', 'Restaurants', 'Dance',\n",
            "       'Art Books', 'Gadgets', 'Performance Art', 'Accessories',\n",
            "       'Electronic Music', 'Drinks', 'Comic Books', 'World Music',\n",
            "       'Playing Cards', 'Comedy', 'Drama', 'Jazz', 'Graphic Design',\n",
            "       'Journalism', 'Sculpture', 'Food Trucks', 'Small Batch', 'Mobile Games',\n",
            "       'Graphic Novels', 'Poetry', 'Photobooks', 'Periodicals', 'Plays',\n",
            "       'Digital Art', 'Horror', 'Farms', 'Woodworking', 'People',\n",
            "       'Conceptual Art', 'DIY', 'Faith', 'Wearables'],\n",
            "      dtype='object')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Find the name of the countries that represent 90% of the projects\n",
        "\n",
        "print(df['country'].value_counts(1)[:3].sum())\n",
        "print(df['country'].value_counts(1)[:3].index)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JAbytVPeBAww",
        "outputId": "6a7e22a9-a2f2-4f9d-990b-28b2269b1661"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.9326410114610619\n",
            "Index(['US', 'GB', 'CA'], dtype='object')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# One hot encoding\n",
        "\n",
        "def one_hot_encoding(df, feature, top_values):\n",
        "    \"\"\" Applies one hot encoding on a selected number of values of a feature \"\"\"\n",
        "    for value in df[feature].value_counts(1)[:top_values].index:\n",
        "        df[value] = df[feature].str.contains(value).apply(lambda x:1 if x else 0)"
      ],
      "metadata": {
        "id": "W_mdUvuNz9W8"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "one_hot_encoding(df, 'category', 73)\n",
        "one_hot_encoding(df, 'main_category', 11)\n",
        "one_hot_encoding(df, 'country', 3)"
      ],
      "metadata": {
        "id": "siDZkJGu0FJU"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.drop(['category', 'main_category', 'country'], axis=1, inplace=True)"
      ],
      "metadata": {
        "id": "BmlSHd_CBup-"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def corr_df(df, corr_val):\n",
        "    \"\"\" Drops features that are strongly correlated to other features \"\"\"\n",
        "\n",
        "    # Creates Correlation Matrix and Instantiates\n",
        "    corr_matrix = df.corr()\n",
        "    iters = range(len(corr_matrix.columns) - 1)\n",
        "    drop_cols = []\n",
        "\n",
        "    # Iterates through Correlation Matrix Table to find correlated columns\n",
        "    for i in iters:\n",
        "        for j in range(i):\n",
        "            item = corr_matrix.iloc[j:(j + 1), (i + 1):(i + 2)]\n",
        "            col = item.columns\n",
        "            row = item.index\n",
        "            val = item.values\n",
        "            if val >= corr_val:\n",
        "                # Prints the correlated feature set and the corr val\n",
        "                print(col.values[0], \"|\", row.values[0], \"|\", round(val[0][0], 2))\n",
        "                drop_cols.append(i)\n",
        "    drops = sorted(set(drop_cols))[::-1]\n",
        "\n",
        "    # Drops the correlated columns\n",
        "    for i in drops:\n",
        "        col = df.iloc[:, (i + 1):(i + 2)].columns.values\n",
        "        df.drop(col, axis=1, inplace=True)\n",
        "    return df"
      ],
      "metadata": {
        "id": "n6rtjDSyF4nF"
      },
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "corr_df(df, 0.6)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 574
        },
        "id": "kBu2YgNSF7Da",
        "outputId": "1ede44da-f1ba-4627-ecfa-e0b6a8d3d1ff"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Indie Rock | Rock | 0.67\n",
            "Web | Webseries | 0.73\n",
            "Design | Product Design | 0.85\n",
            "Games | Tabletop Games | 0.6\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             state  count_chars  usd_goal  year_launched  month_launched  \\\n",
              "0           failed           43    5000.0           2012               3   \n",
              "1           failed           51   19500.0           2015               7   \n",
              "2       successful           52    1000.0           2014              12   \n",
              "3           failed           42   25000.0           2016               2   \n",
              "4           failed           16    2500.0           2013               9   \n",
              "...            ...          ...       ...            ...             ...   \n",
              "301979      failed           44   50000.0           2014               9   \n",
              "301980      failed            8    1500.0           2011               6   \n",
              "301981      failed           61   15000.0           2010               7   \n",
              "301982      failed           22   15000.0           2016               1   \n",
              "301983      failed           27    2000.0           2011               7   \n",
              "\n",
              "        duration  count_projects_7_days  Product Design  Documentary  Shorts  \\\n",
              "0             30                  871.0               0            0       0   \n",
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              "2             20                 1051.0               0            0       0   \n",
              "3             44                 1297.0               0            0       0   \n",
              "4             30                  880.0               0            0       0   \n",
              "...          ...                    ...             ...          ...     ...   \n",
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              "301980        27                  487.0               0            0       0   \n",
              "301981        45                  224.0               0            0       0   \n",
              "301982        30                 1005.0               0            0       0   \n",
              "301983        28                  511.0               0            0       0   \n",
              "\n",
              "        ...  Farms  Woodworking  People  Conceptual Art  DIY  Faith  \\\n",
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              "\n",
              "        Wearables  US  GB  CA  \n",
              "0               0   1   0   0  \n",
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              "      <th>3</th>\n",
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              "\n",
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              "\n",
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            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Modeling and Evaluation**\n",
        "\n",
        "# **Models:**\n",
        "- Logistic Regression\n",
        "- Rndom Forest Classifier\n",
        "- XGBoost Classifier\n",
        "\n",
        "# **Metrics:**\n",
        "- Accuracy\n",
        "- AUC"
      ],
      "metadata": {
        "id": "N-KBzjLKwgJ1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.inspection import permutation_importance\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import accuracy_score, roc_curve, roc_auc_score\n",
        "from sklearn.model_selection import StratifiedKFold, train_test_split, RandomizedSearchCV\n",
        "\n",
        "from xgboost import XGBClassifier"
      ],
      "metadata": {
        "id": "yhwd4rZjDNHg"
      },
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# X: input, y: target variable\n",
        "X = df.drop('state', axis=1)\n",
        "y = df['state'].replace({'failed': 0, 'successful': 1})"
      ],
      "metadata": {
        "id": "Pafla7nvC_-I"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 60/20/20 + Stratified (Training/Validation/Test)\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, stratify=y, random_state=42)\n",
        "X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size=0.25,\n",
        "                                                  stratify=y_train, random_state=42)"
      ],
      "metadata": {
        "id": "4taSm8ZSDAoj"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Logistic Regression using RandomizedSearch cross-validation\n",
        "\n",
        "lr  = LogisticRegression(random_state=42)\n",
        "param_dist = {'C': np.arange(0.01, 10, 0.5)}\n",
        "\n",
        "rs_lr = RandomizedSearchCV(lr, param_dist, scoring='accuracy', cv=5, random_state=42)\n",
        "rs_lr.fit(X_train, y_train)\n",
        "\n",
        "rs_lr_score = rs_lr.score(X_val, y_val)*100\n",
        "print('The selected RF Classifier model: ', rs_lr.best_estimator_)\n",
        "print(\"Accuracy of LR model on vaidation dataset: {:.2f}%\".format(rs_lr_score))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xmsTfBe8C6YI",
        "outputId": "6e41158b-ede3-44d7-e5aa-4bf7b8b2ea77"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The selected RF Classifier model:  LogisticRegression(C=8.51, random_state=42)\n",
            "Accuracy of LR model on vaidation dataset: 64.04%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#ROC curve\n",
        "pred = rs_lr.predict_proba(X_val)[::,1]\n",
        "fpr, tpr, thresholds = roc_curve(y_val, pred)\n",
        "auc_score = roc_auc_score(y_val, pred)\n",
        "\n",
        "plt.figure(figsize=(15, 10))\n",
        "plt.plot(fpr, tpr, label='AUC = %.3f' % (auc_score))\n",
        "plt.legend()\n",
        "plt.title('ROC curve', size=20)\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.grid(True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "id": "r5LSjdyKFEim",
        "outputId": "e5caae69-5d32-4000-f54a-5ffbf7934d76"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Random Forest Classifier using RandomizedSearch cross-validation\n",
        "\n",
        "rfc = RandomForestClassifier(random_state=42)\n",
        "param_grid = {\"max_features\": np.linspace(1,10,10, dtype=int),\n",
        "              \"min_samples_leaf\": np.linspace(1, 50, 50, dtype=int),\n",
        "              \"min_samples_split\": np.linspace(2, 10, 9, dtype=int),\n",
        "              \"n_estimators\":[100, 200, 300]}\n",
        "\n",
        "rs_rfc = RandomizedSearchCV(rfc, param_grid, scoring='accuracy', n_iter=5, random_state=42)\n",
        "rs_rfc.fit(X_train, y_train)\n",
        "\n",
        "rs_rfc_score = rs_rfc.score(X_val, y_val)*100\n",
        "print('The selected RF Classifier model: ', rs_rfc.best_estimator_)\n",
        "print(\"Accuracy of RF model on vaidation dataset: {:.2f}%\".format(rs_rfc_score))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XkynTjNoEbaF",
        "outputId": "659bf8e1-63d8-48bd-cf91-908d18befe51"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The selected RF Classifier model:  RandomForestClassifier(max_features=6, min_samples_leaf=20, min_samples_split=4,\n",
            "                       n_estimators=200, random_state=42)\n",
            "Accuracy of RF model on vaidation dataset: 69.69%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#ROC curve\n",
        "pred = rs_rfc.predict_proba(X_val)[::,1]\n",
        "fpr, tpr, thresholds = roc_curve(y_val, pred)\n",
        "auc_score = roc_auc_score(y_val, pred)\n",
        "\n",
        "plt.figure(figsize=(15, 10))\n",
        "plt.plot(fpr, tpr, label='AUC = %.3f' % (auc_score))\n",
        "plt.legend()\n",
        "plt.title('ROC curve', size=20)\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.grid(True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "id": "i3mbskNoE2Jm",
        "outputId": "55372812-8d88-47dd-93f2-bf0739e2ba29"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ],
            "image/png": 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kZvT75xxJWloqRUVFlJSUkJLS+4s5k6n89QmnetBw4/Gl/uTxpf7mMab+5PHVe/n5peT3YU+Ooojm1k6aWzvYX9vM1j11xCOoP9jGvuom6g620dLWQWVtS6/eLzcrjVgsRtnIbBqbOygryiY1JUZKSozUlBid3YWxMD+TtNQYURQjHo8YkZdBSkqMlFjs0GNbRycj87NIT0uhozNOXnY6sViMlBjEYjFiPR5TXntNjHgUkZGeeuhCy9kzSqmtaeq7/2hvQlXVwde97jHVwxElU/nbCUwCXup+ffiZQEmSJEkJEEURLW2dNDa309DUTn1TGw0H26htbKXuYBt7DhwkKyON8v2N1B1sA/56Bq+njLQUCnIzaO+IU5iXyZKTCkhLTWFEbgajirKJxWJMHp1Pfk4GWRmppKelkJoSS8rLUdPTUhMd4YQlU/n7LfDhIAh+DxQDVwHnJDaSJEmSNDTF4xHV9S1U1jZzoK4FYrC3qonM9FTaOjppONhOVc/1R5GdmUZOZirNrZ2ML82lMD+D4oIsJo8uICszlRE5GYwrzaUwL5OM9MFXmIaSgZrq4VvANcBo4NEgCKrCMJwTBMEDwJfCMFwO/Bw4DdjUvdu/hmG4bSDySZIkSUNRFEXsrWriQF0LyzfspyMep66xjV2VjTQ0tR91v7TUGNmZaRQXZDGxLJ/504rJykgjJyuNsqJsRuRlkpedTnFB5qA8AzZcDdRon58APnGE5Zf3eN4J/P1A5JEkSZKGko7OOHsOHKR8fyNb9tRTWdtMdX0Le6veeE/apNH5TBs7guzMNEaPzKZsZA4jC7IozM0gMyOV3Kx0UlKS7zJLvXXJdNmnJEmSpCNobu3gQF0L+6qbaOvoPHT2rrK2hc276464T8mILM6aO5qCvAxOmlhE2cgcSguzBzi5konlT5IkSUoC7R2d7KhoZOveenZXNrJ1Tz1NrR00tXTQ2t55xH1yMtOYMqaASWV5lBZlM7Y4l4ll+RTlZw5weg0Glj9JkiSpH3V0xqmqb2HPgYM0t3ZNb1C+v5Hm1g527mugvTNOZ2fXnHaHK8rPZMlJoygtzKa4IIuszFTGluSSnZlGfvcUBVJvWf4kSZKkPtLa3sn67TXsq2liY3kt2/bWU3ewjeiwXleQk04ETBs3ghgwrjSPzPQUSguzGVOcS9nIbLIy/FVdfcsjSpIkSToBURRRWdfC1j117DnQREdnnO1769m5r5Gm1o5D22VnpjFrYiFlI3MoLsgiJyuNyaO7Lsm02CkRPOokSZKko6hrbGVbRQO79jeyeXcduysPUlX/xjnvigsymViWx7RxIxhTnMOUMQWMHpnjZZlKKpY/SZIkCYhHEbv2NxLurKW8spEVYeXrzuQB5GalMXNCIVPHFjBvykjKRuZQlJ9pydOgYPmTJEnSsBNFEftrm9lTeZD1O2rYX9vM6i1Vr9tmfGkus4tHcsacMsaV5FJSmE2KJU+DmOVPkiRJQ14URazbUcOWXXW8tGE/uw8cfMM2c6eMZOrYAuZOKWbK2HxSU1ISkFTqP5Y/SZIkDTlt7Z3sqKjnpTV7eHljJRVVTRyo67pXLy01hTPmjCY3O41TZ3VNozAiN8NLNzXkWf4kSZI0aLW1d7JzfyMbdtSwZXcdFTXN1DW20tL2xknRb7hwOqfOGkVhfqaXb2pYsvxJkiRpUIiiiIamdsr3N7JuRzXb9zawfkfNofWpKTHGluSyaEYpZUXZjCzKoWxEJmOKc8nLTk9gcik5WP4kSZKUVKIoYue+RtZuq6KqroU9Bw7SEY+oqGp63eibY4pzOH/hWCaPKWDWxEJKC7Nfd+lmaWk+lZUNifgSpKRk+ZMkSVJC7TlwkG1761m16QC7KhupbmilvSN+aH0MGFmQxaKZJZQV5TCyIJOF00vIyfJsnnQiLH+SJEnqdx2dcfbXNLNtbz3V9S1s29vA9op6ahvb3rDtpNH5LJ5RQjCxiKljC0hLddRNqS9Y/iRJktTnmls72F7RwMqNleypOsi67TWvW5+dmUZedhrzpxUzvjSPkyYVMW1cAVkZ/noq9Rf/dkmSJOkta+/oZEdFIys2VvLihn1U17ceWpeXnc4Zc8qYPLqASaPzmViWZ8mTEsC/dZIkSTohTS0d7KpsZP2OGlZuqmTnvsbXrc9IS+HMuaNZML2EWRMLyc/JSFBSST1Z/iRJknRMDU1tbCyv5dXtNazecuB1Z/VGFmQytiSXkhFZnD67jOnjRlBSmJ3AtJKOxvInSZKkQ+JRxIYdNazZWkVtYxt/Wbfv0LrUlBjjR+WxYHoJwYRCgolFjMj1rJ40WFj+JEmShrHaxla2720gLK+hsraF9TtqaO4xl95Jk4ooHpHFaSeVMWtSIakpjrwpDVaWP0mSpGGkvaOTrXvq2Vhey1Ov7HndJZxpqTEWTCth2rgRLJ5ZwqiinAQmldTXLH+SJElDXHNrB6s2H+BPf9lJ+f6/Ds6SlprCvKnFnDl3NCdNLqLAgVmkIc3yJ0mSNMR0dMbZsruO9TtqWL2lip37GolHEbEYzJpYyKmzRjF/WgkjCzKJxWKJjitpgFj+JEmSBrEoiqg72MZL6/dTUd3Eik2V1DW2HVo/YVQeF548jvnTipkxvpDM9NQEppWUSJY/SZKkQaa2sZUtu+tYHlby0vr9xKPo0Lrp40YQTChk7pRiZkwYQZn37UnqZvmTJElKYq3tnazeUkX5/kb21zSxq/Igew4cPLS+bGQOC6YVM39aMTMnFJKW6micko7M8idJkpREoihie0UD67ZXs3VPPSs3HXjd+nlTi1k0o2tEzlkTC8nK8Nc5Sb3jdwtJkqQE2lt1kOVhJdX1LeyrbmLDztrXrT99dhmzJhUxd8pIivIdoEXSm2f5kyRJGkAdnXEqqppYvbWKJ1fu5kBdy6F1E8vyOG12GSNyM1g4vYRgYqFlT1KfsfxJkiT1oyiKWLejhsdf3sXabdV0dMR5bXiW9LQUzpk/hgsXj2diWZ5FT1K/svxJkiT1g21763l8xS6eW1NxaFnJiCxGj8xhcVBKWVEOwcRCUix8kgaI5U+SJKmP7K5sZMWmA6zdWsWmXXUALJhWTDCxiPMXjXVwFkkJ5XcgSZKkt2Bv1UGeWrWHddur2VXZNQVDQU46S08ez8VLJlAyIjvBCSWpi+VPkiTpBERRxJbd9Tz6cjlb99QfGrAlLTXG1edM4dSTyhg90onVJSUfy58kSVIv1DS0sm57NXc9vpnG5nYARo/M4foLprFwegmjR+Y4YIukpGb5kyRJOooDdc0s31DJ06/soaK6CYC87HQuPnUC5y4Yy9iS3AQnlKTes/xJkiT1EI9HbN5dxz3PbD004fqY4hyuOXcqU8YUEEwsJC01JcEpJenEWf4kSZKAjeW1vLRhP0+s2E08ishIT2HpKeM5eWYpMyc42bqkwc/yJ0mShqXq+ha27Kln9eYDvLhhP+0dcWLAnCkjmTtlJGfOG0NednqiY0pSn7H8SZKkYaGjM86zq/eysbyWlZsO0NreeWhdUX4mp88u47LTJ1n4JA1Zlj9JkjQkxeMRYXktL67fR21DK2u3VdMZjwCYNraAcaW5LJxRytQxBRTkZiQ4rST1P8ufJEkaUnZVNvL82gqeXb330JQMAGfNHc2sSUWcMmsUmempCUwoSYlh+ZMkSYNeW3snj6/YzfNr97Kr8iAAJSOyuPqcKcybWkxJYXaCE0pS4ln+JEnSoNTS1sEzr+zlpQ372by7DoDszFQuWTKB8xaOY/TInAQnlKTkYvmTJEmDyo6KBp5bu5cnVuymMx6RlprC+QvHMn96CQumFTslgyQdheVPkiQlvX3VTTy8vJxN5bWHLuucOraAq8+ZyuzJRRY+SeoFy58kSUpK5fsbefAvO9hdeZDy/Y0A5GSmcf3501g8s5QyL+uUpBNi+ZMkSUkjHkW8uq2aJ1fuZuWmAwCMLMjkyrMms2hGKZNG5yc4oSQNXpY/SZKUcE0t7fxl3T6eemUPO/c1kpGewpKTRnHtedModaROSeoTlj9JkpQwFVUH+ckf1/HCqxVEQGpKjHdfNINzF4whK8NfUySpL/ldVZIkDaimlg5eWFfB/c9vp7axDYBxJbm88+wpLJ5ZSkqKg7dIUn+w/EmSpAFRUd3Erx/bxOotVQCUFmZx1XnTOGVGCWNLchOcTpKGPsufJEnqN7WNrWwsr+X5tRWs2VpFjBhzp4zkktMmMntSEaNGFVBZ2ZDomJI0LFj+JElSnzpQ28xzaytYvaWKbXvrAchMT+W8heO49LSJjHIAF0lKCMufJEnqE8+t2cuyP++goroJgLTUGKfMGsWSWaOYN7WYzIzUBCeUpOHN8idJkt60ytpmfvfUFjbvrqO6vpUYcPb8MSw9eTwTy5yTT5KSieVPkiSdsMbmdn76wPpDE7HnZadzw4XTuWDRODLSPcMnScnI8idJknptd2Ujv3tqK69sOUAUwUmTinjP0hmMK81LdDRJ0nFY/iRJ0nHt3NfAkyt38+SqPUDXpZ0XLh7H5NEFCU4mSeoty58kSTqijs44jy7fxe+f3kpHZxyAk4NSrj5nqvPySdIgZPmTJEmvs35HDfc8s5VNu+oAGJGbwWmzy1h68nhKnKZBkgYty58kSWJv1UFWbT7Ao8t3UdPQSm5WGnOmjOT02WWcMWc0KSmxREeUJL1Flj9JkoapKIpYtekAz6+t4OWNlQCMHpnDxadO4J1nTyE7018TJGko8bu6JEnDTG1jK/c/v53lG/ZT39QOwKVLJnLG3NFMGOWonZI0VFn+JEkaBuJRxPIN+3n6lT2s214DQMmILK47fyIXLBrnWT5JGgb8Ti9J0hDV0RlnU3ktD71Uztqt1cSjCICLTh7POfPHMLEsP8EJJUkDyfInSdIQEkURG8tr+ePz29m8u4629jhpqTHGFOdw/qJxnDN/DBnpqYmOKUlKAMufJElDxNOv7OG+57ZRXd8KQGlhFteeN43504rJyvBHviQNd/4kkCRpEItHEX9eW8GjL+9iR0UDRfmZvPuiGZw2u4wRuRmJjidJSiKWP0mSBqGd+xp4fm0Ff1m3j7qDbRTlZ3LVOVO4/PRJpKWmJDqeJCkJWf4kSRpEVm6s5N5nt7FzfyMA08eN4IaLprNkVpkTsUuSjsnyJ0lSkttV2cgjL5WzZmsVtY1tFORmcNXZUzhz7mhKCrMTHU+SNEhY/iRJSkLNrR38+dUKVm+pYvWWKgAyM1JZevJ4rjt/miN2SpJOmOVPkqQksm1vPQ/8eQcvb6w8tOzS0yZy5tzRjC/NS2AySdJgZ/mTJCkJNDa3c++z23js5V0ATBmTz2WnTWLB9BLS0xzARZL01ln+JElKkCiKWLO1mqdW7Wb1lio64xElI7L4zI2LGOW9fJKkPmb5kyRpgEVRxAuv7uOJVbvZvKuOrIxUzpg7mnPmj2HG+MJEx5MkDVGWP0mSBsjBlnZWbjzAfc9t40BdC7lZaVx1zhQuWTKRTAdwkST1M8ufJEn9rL0jzjOr9/CbJzbT1h6ntDCLD1w2i7PnjyEl5tx8kqSBYfmTJKmf1DW28tSqPdz33HbiUcSY4hzes3QmsyYVkpriIC6SpIFl+ZMkqQ91xuM8t6aCZ17Zw5Y99QBMGVPAeQvHcs78McQ80ydJShDLnyRJfaC9I85jL+/ikeXl1DS0Mqoom4tPncDpc8qYPLog0fEkSbL8SZL0VuyoaODZNXv589oKmlo7KCvK5sPvmM1ps8u8n0+SlFQsf5IkvQlNLe387KGQF9fvB2BMcQ7vvXgmp88u89JOSVJSsvxJknQCDtQ18+jyXTy6fBfxKGL+tGKuO38a40vzEh1NkqRjsvxJknQc8Shi485anl2zl+fXVgAwd+pILl0ykdmTRyY4nSRJvWP5kyTpKOoaW/nd01t5dvXeQ8vmTC7iPW+byZji3AQmkyTpxFn+JEk6zIHaZn764AbW76gBuu7nO2POaM6aN4ai/MwEp5Mk6c2x/EmS1C2KIv6yfh93PbaZ+qY2Fk4v4apzpjCxLD/R0SRJessGrPwFQTATuAMoBqqA94dhuOmwbUYBPwUmAOnAE8AnwjDsGKickqThp70jzuMrdvGbx0y8xtoAACAASURBVDcTAdmZafzz+09hyhjn55MkDR0Deebv+8B3wzD8RRAE7wN+AFx42Db/G1gfhuHbgyBIB54FrgF+M4A5JUnDyPodNfzg3rXUN7VTmJfB0lMmcNHi8WRmpCY6miRJfWpAyl/3Gb3FwNu6F90JfCcIgtIwDCt7bBoB+UEQpACZQAaweyAySpKGl1e3V3PXY5vZVdlIXnY6H76ie2L2FOfokyQNTQN15m8CsDsMw06AMAw7gyDY0728Z/n7N+B3wF4gF/hOGIbPncgHFRcn5zxLpaXeL6L+4/Gl/jSUjq/G5naWPbeV3z2+iebWTgDetXQm114wnZys9ASnG76G0jGm5OPxpf402I6vZBvw5XpgNXARkA88GATBdWEY3t3bN6iqaiQej/or35tSWppPZWVDomNoiPL4Un8aKsdXR2ece5/dxoMv7CQeRZSNzOHCxaWct2AsJYXZHGxo4WBDS6JjDktD5RhTcvL4Un9KxuMrJSV2zJNhA1X+yoFxQRCkdp/1SwXGdi/v6ePA34RhGAfqgiC4F7gA6HX5kySpp/U7avjanSsBmDKmgGvOncrsyUXEYl7eKUkaXgak/IVhuD8IglXAjcAvuh9XHna/H8A24FLgxSAIMoClwO8HIqMkaWhZu62K+57dzubddRTkpLN4Zin/65LA0idJGrYG8rLPjwJ3BEHwJaAGeD9AEAQPAF8Kw3A5cAvw/SAI1gCpdE318KMBzChJGsTiUcTTr+zh5Q37eXV71wTtc6aM5O+unENetvf0SZKGtwErf2EYbgBOO8Lyy3s838JfRwSVJKlXoijipQ37eWrVHtbv6Cp9FywexzvPmkJBbkaC00mSlBySbcAXSZJOyIvr9/Hzh0IOtnQQA95+xiSuOmcKqSkpiY4mSVJSsfxJkgaluoNt3PnoRl5cvx+Aq86ewiVLJjo5uyRJR2H5kyQNKjUNrfzwvlfZuree9o445y0cy7XnTfOePkmSjsPyJ0kaFDrjcVZtOsD3732VznjEuNJcbrpkFtPHj0h0NEmSBgXLnyQp6b2wroLbH9xAW3ucEbkZfPDyWcyfVpLoWJIkDSqWP0lS0tq6p57fPrGZsLyWjLQUbrhwOhcsGkdGuvf1SZJ0oix/kqSkU9vYyj3PbOPpV/aQk5nGZadN5IozJ5Od6Y8tSZLeLH+KSpKSRnNrB/c9t40nVuymvSPOGXPKuP6C6RTmZSY6miRJg57lT5KUFJ5bs5e7Ht9MY3M7xQVZfOyaeUwanZ/oWJIkDRmWP0lSQtUdbOPXj23iL+v2MbIgk0+9YwHzphYnOpYkSUOO5U+SlBDtHZ0s+/MOHn6pnJa2Ts6ZP4b3LJ3pJO2SJPUTy58kacCFO2v49WOb2bGvgYmj8vjQFbOZMCov0bEkSRrSLH+SpAGzo6KBZX/ezvKwEoAPXzGbM+aOTmwoSZKGCcufJKnfNTa3c8eDG3h5YyVZGamcv2gc7zxrMiMcxVOSpAFj+ZMk9Zsoinh+bQU/eyikvSPOuJJcPvueRRTkZCQ6miRJw47lT5LU514rfY+v2MW2vQ0AfPrdC5kzeWSCk0mSNHxZ/iRJfaYzHueeZ7bxwqsVVNW3kpGewtXnTuWCRePIy05PdDxJkoY1y58k6S3rjMd5+KVyfvvElkPLbrxoBucvGkt6mlM3SJKUDCx/kqS35NXt1fzi4Y3sq24iIz2FcxeM5d0XzSAlFkt0NEmS1IPlT5J0wqIo4pnVe3n85V3s3N9ISizG+y8JOHfhWEufJElJyvInSeq1eBSxatMB7nlmG7sqG8nOTOWGC6dz1rwx3tMnSVKSs/xJknrllc0HuP/57WzZUw/A0lPGc/3500lPS0lwMkmS1BuWP0nSMa3cWMlDL+5k4646AN594XTOmDuafOfqkyRpULH8SZKO6OlX9vDI8l3srmwkIy2Fq86ewgWLx1n6JEkapCx/kqTX2V/TxNfuXElVfStpqSlcedZkLlkykexMf2RIkjSY+ZNckgRA3cE27n5yMy+u3097R5zZk4v4j5vPpqb6YKKjSZKkPmD5k6RhrrK2mUeWl/PcmgqaWzuYPDqfD15+EhNG5ZGW6mAukiQNFZY/SRqm4lHEwy+W88fnt9HS2smcqSO54ozJzJxQmOhokiSpH1j+JGkYWre9ml8/tpldlY2MLcnl5v81l7EluYmOJUmS+pHlT5KGkQO1zfx42Xo2ltcCcOPSGSw9eTyxWCzBySRJUn+z/EnSMNDc2sG9z27jkeXlRBFcsmQCl58+yWkbJEkaRix/kjTErdp0gG/9bjUAJ88s5Z1nT2H8qLwEp5IkSQPN8idJQ1R7Ryc/uG8dKzZWkpaaws1XzWXhjJJEx5IkSQli+ZOkISaKIp5ctYd7ntlKQ1M7k8ryueX6+YzIy0x0NEmSlECWP0kaIqIoYsXGSn72UEhDUzvFBVn8w9WzODkoTXQ0SZKUBCx/kjQEdMbjfPUXK9iypx6Aq8+ZwtvPmExKiqN4SpKkLpY/SRrkKmub+e7v17BzfyPnzB/DjUtnkJXht3dJkvR6/nYgSYPYpl21/L/fvEJrWyfvOHMyV50zxTn7JEnSEVn+JGmQeuHVCn74x3WMyMvgY1fPY86UkYmOJEmSkpjlT5IGmYrqJh58YQfPrN5LcUEmX/zAqRQ4WbskSToOy58kDRJNLR3c99w2Hn6pHIAz547mxqUzyM1KT3AySZI0GFj+JGkQWLmxktuWraeptYOykTn8/TvnMLEsP9GxJEnSIGL5k6Qk1tzawZ2PbeLZ1XvJyUzjH29YwNwpxYmOJUmSBiHLnyQlqY3ltfzP3a/Q3NpJyYgsvvSBU8nL9hJPSZL05lj+JCnJtHfEueeZrTz4l50U5GbwN5fPZvHMEqdwkCRJb4nlT5KSSE1DK9/8zSvsqmxk/rRi/vaK2Z7tkyRJfcLyJ0lJIB6PePAvO7jnmW10xiNuujTg3AVjPdsnSZL6jOVPkhKssbmdH9z3Kq9uq2b0yBw+6kiekiSpH1j+JCmBXt1ezff+sJbm1g6uOXcql58+iZQUz/ZJkqS+Z/mTpASoqmvhB398lc276iguyOKT181n5oTCRMeSJElDmOVPkgZQS1sHj6/Yzd1PbgFg3tRiPnTFSRTkZCQ4mSRJGuosf5I0ANo74jyzeg/3PLONxuZ2ggmFXHf+NKaNG5HoaJIkaZiw/ElSP1u9pYof37+OxuZ2xhTn8L6LZ3LqrFGO5ClJkgaU5U+S+klDUxu3P7iBlZsOkJWRypVnTebKs6eQYumTJEkJYPmTpD4WRRFPrNzNLx7eCMAZc8r4wGUnkZ6WkuBkkiRpOLP8SVIfamhq49/uWM6BuhaK8jO57rxpnDF3dKJjSZIkWf4kqS9EUcR9z23n3me3AXDewrG8920zSUv1bJ8kSUoOlj9Jeouq6lr48f3rCMtrmTO5iKWnTGDB9JJEx5IkSXody58kvQWbd9fx7d+tpqGpnaUnj+fGpTMcxVOSJCUly58kvQm79jdy1+ObeHV7DblZaXzi2vksnOHZPkmSlLwsf5J0AuJRxF2PbeaR5eXEgLPnjeH6C6aRn5OR6GiSJEnHZPmTpF7auqeeW+9ZQ1V9Kwunl/Det82keERWomNJkiT1iuVPko6jozPOH57ZyoMv7ATgijMnc825UxOcSpIk6cRY/iTpKKIoYmN5LXc9vpntFQ2cMmsU7106gxF5mYmOJkmSdMIsf5J0BK1tnXzjrlVs3l1HZkYqH3r7SZw5d7QjeUqSpEHL8idJh9m2t54f37+OvVVNXHnWZJaeMoG87PREx5IkSXpLLH+S1K21vZMHX9jBfc9tB+ADl83i3AVjExtKkiSpj1j+JA17URTx6Mu7+MPTW2lp62RMcQ6fvG4+o4pyEh1NkiSpz1j+JA1rO/c18LOHQrbuqacgN4OPvGMO86cXk+K9fZIkaYix/EkalnZUNPCzhzawbW8DAFecOYmrzplq6ZMkSUOW5U/SsPPi+n38+P71dHTGmT+tmJsunUVRvtM3SJKkoc3yJ2nY2LmvgR/c9yp7q5oYVZjNp9+9kNLC7ETHkiRJGhCWP0nDwpOrdvPzP4WkpMQ4b+FY3nXBdLIz/RYoSZKGD3/zkTTkPfiXHfz2iS2ML83llusXMLIgK9GRJEmSBpzlT9KQFY9H3PfcNu57bjvjS3P5/HsXk5PlZO2SJGl4svxJGpJqG1v5z1+8TGVtC4tmlPCRK+eQmZ6a6FiSJEkJY/mTNORsr6jn63euoqm1g4tPncC7L5qR6EiSJEkJZ/mTNGREUcTjK3bzy0c2EovBzVfN5ZRZoxIdS5IkKSlY/iQNCU0tHXz/vrWs3VpNyYgsPvWuBYwpzk10LEmSpKRh+ZM06G0sr+Ubd62ivSPO0lPGc/3500lPS0l0LEmSpKRi+ZM0qG3dU89Xf7mCzPRUL/OUJEk6BsufpEEpHkU89vIu7nx0EwD/5/0nM740L8GpJEmSkpflT9Kg09TSzn//djWbd9dRXJDFR985x+InSZJ0HJY/SYPKjooGvv371dQ2tHH1OVO49LSJpKc5f58kSdLxWP4kDRprt1Xx3T+sJSUGt1w/n7lTixMdSZIkadCw/EkaFB55qZw7H9tEdmYat1w/nxnjCxMdSZIkaVCx/ElKevc8s5X7nttOyYgsvvLBJeRk+a1LkiTpRPkblKSk1RmP89sntvDwS+WUjczhC+9bbPGTJEl6k/wtSlJS2lt1kFvvWcuuyoMsOWkUf3P5SWSkO7CLJEnSm2X5k5RUoijiqVV7+PlDIWlpKXzgslmcu2BsomNJkiQNegNW/oIgmAncARQDVcD7wzDcdITt3gV8EYgBEbA0DMN9A5VTUuK0d8T579++wvodNRTlZ/KZdy9kTHFuomNJkiQNCSm93TAIgrcFQXBbEAR/7H59ShAEF57AZ30f+G4YhjOB7wI/OMJnnAJ8BXhbGIZzgbOBuhP4DEmDVH1TG//vrlWs31HD6bPL+K+PnmHxkyRJ6kO9Kn9BEHwcuBXYBJzbvbgZ+Pde7j8KWAzc2b3oTmBxEASlh236KeDrYRhWAIRhWBeGYUtvPkPS4BXurOHLt71IWF7LDRdO5yNXziEttdf/NiVJkqRe6O1ln7cAF4VhuD0Igs91L9sABL3cfwKwOwzDToAwDDuDINjTvbyyx3azgW1BEDwN5AG/B/4jDMOol59DcXFebzcdUKWl+YmOoCFssB5f8XjEbX9cy31PbyU3K41//uASTps7JtGxdJjBenxp8PAYU3/y+FJ/GmzHV2/LXz5Q3v38tSKWDrT1cZ5UYD7wNiAD+BOwE/hZb9+gqqqReLzXXXFAlJbmU1nZkOgYGqIG6/EVRRG/f3ory/68g5ODUm66dBZ52emD8msZygbr8aXBw2NM/cnjS/0pGY+vlJTYMU+G9fa6qqeBzx+27BPAE73cvxwYFwRBKkD341j+WihfsxO4OwzD1jAMG4B7gSW9/AxJg0R1fQtf/eUKlv15Bwunl3DzVXPJy05PdCxJkqQhrbfl7+PA1UEQbAfygyAIgXcB/9ibncMw3A+sAm7sXnQjsDIMw8rDNv0VcHEQBLEgCNKBi4BXeplR0iCwc18D/3rHcjbvquMdZ07mY9fOIxaLJTqWJEnSkNeryz7DMNwbBMGpwKnAJLrO2L0YhmH8BD7ro8AdQRB8CagB3g8QBMEDwJfCMFwO/Bo4BVgHxIGHgNtO4DMkJal9NU388pGNrN1aTWZ6Kp+9cRGzJhUlOpYkSdKw0avyFwTBvWEYvhN4sfvPa8t/H4bhNb15jzAMNwCnHWH55T2ex+k6m9irM4qSBodVmw/wvT+spbMzzkWLx3PpaRMpHpGV6FiSJEnDSm8HfLngKMvP76MckoaojeW1fOvu1RQXZPLxa+czsWxwjYolSZI0VByz/AVB8K/dTzN6PH/NVGBHv6SSNCSs3VbFrfe8SlF+Jl9438mMLPBsnyRJUqIc78zfhO7HlB7PoWu6h3LgK/2QSdIQsHzDfm69dy3paSl88rpFFj9JkqQEO2b5C8PwgwBBEDwfhuGPBiaSpMHuyVW7+dmfQooLsvj0uxcyemROoiNJkiQNe70d7fNHAEEQ5AMlQKzHuq39E03SYPTbJzbz4F92MmFUHv/4rgWMyMtMdCRJkiTR+9E+T6JrDr4FdF3yGet+BEjtn2iSBpN4FPHLRzbyxIrdnDSpiI9fO4+sjN6OKSVJkqT+1tvfzG4FnqBr1M9twGTgP4Hn+yeWpMGk/mAb3/vDGjbuqmPe1GJuvmoumRn+u5AkSVIySenldguAz4VhWAvEwjCsAz4L/Fu/JZM0KNQ0tPKFH/6ZTbvruO78aXzqXQssfpIkSUmot2f+WoB0oB04EATBRKAGKO6vYJKSWxRF3P/8dh54YSet7Z18/Np5LJpRmuhYkiRJOorelr9ngHcBtwN3Aw8CrcDj/RNLUjKLoogf/nEdf1m3j4y0FP7pxkXMmlSU6FiSJEk6ht6O9vmuHi//N/AqkAfc0R+hJCWveDzix8u6it+ps0bxd1fOISUldvwdJUmSlFAnPBRfGIZx4OdBEGQAHwa+2+epJCWlfTVNfO3OlVTXt7JoRgkffsdsi58kSdIgcdzyFwTBRcBCYHMYhvcGQZAG3Ax8DqjG8icNC7sqG/mvX67gYEsH118wjUuXTCQWs/hJkiQNFscsf0EQfA74Il2Xec4JguB7wPl03e/3kTAMl/V7QkkJ9+e1Ffzo/nVkZ6bxz+8/haljCxIdSZIkSSfoeGf+/g44LwzDl4MgOB14Dvh0GIb/3f/RJCVae0ecnz8c8uzqveRlp/OPNyxg8miLnyRJ0mB0vPJXEobhywBhGL4QBEEr8D/9H0tSotU2tvLVX6xgf20zZ88bw41LZ5CdecK3CUuSJClJ9Oaevxjw2p+W7mWHJofvHgBG0hBS19jKv92xnJqGVt590QwuPnVCoiNJkiTpLTpe+csDOnq8jvV4HQMiILUfcklKkLrGVr7261XUNLRy81VzOWXWqERHkiRJUh84XvmbMiApJCWF+oNtfP6HL9Da1skHLptl8ZMkSRpCjln+wjDcMVBBJCVWTUMr37hrFa1tnXzo7Sdx1rwxiY4kSZKkPuToDZKoqmvhv361gur6Vj542SyLnyRJ0hBk+ZOGuTVbq/jW3asB+Nx7FzFjfGGCE0mSJKk/WP6kYezBF3bw2ye3kJedzgcum2XxkyRJGsJOqPwFQTABGBeG4Qv9lEfSAHl+7V5+++QWJo3O51PvWkBBTkaiI0mSJKkf9ar8BUEwEbgTWEjX9A55QRBcB1wahuHf9mM+Sf1gf00TP31gA3nZ6XzuPYvIyvAiAEmSpKEu5fibAPADYBmQD7R3L3sEeFt/hJLUf1rbOvneH9bSGY/4xLXzLX6SJEnDRG/L3xLgq2EYxuk680cYhnXAiP4KJqnvdXTG+eovV7BzfyPvPHsK08f7V1iSJGm46G352wdM77kgCILZwM4+TySpX0RRxM8fCtmxr4HLT5/EO8+ekuhIkiRJGkC9vd7r68D9QRD8J5AWBMGNwP8GvtpvyST1mZa2Dr5192o27Kzl/IVjue78aYmOJEmSpAHWq/IXhuFPgiCoAv4OKAfeD3wxDMN7+jOcpLfuQG0zX7ztRVrbO7n2vKlcdvqkREeSJElSAvR2tM/UMAzvBe7t5zyS+lBTSzv/7zev0NreyfXnT7P4SZIkDWO9veevIgiC7wVBcFa/ppHUZw62tPPN37xCRXUTH7lytsVPkiRpmOvtPX8XAzcCdwZB0An8GvhVGIZr+i2ZpDetsraZ/+9XK6mub+HGpTM4ffboREeSJElSgvXqzF8YhivDMPynMAwnAh8AioDHgyBY3Z/hJJ24fdVN/MfPllPb2Monr5/P206ZkOhIkiRJSgK9veyzpw3AerqmeZjcp2kkvSV1B9v46i9X0NDczievm8/8aSWJjiRJkqQk0dsBXwqBa4H3AKcDDwP/BdzXf9EknYg1W6v4ybL11B1s47M3LuKkSUWJjiRJkqQk0tt7/vYAzwO/Aq4Nw7C2/yJJOlHPrdnLT5atJyszlX+4ep7FT5IkSW/Q2/I3LQzDvf2aRNKb8vjycm5btp4Jo/L4p/csIjcrPdGRJEmSlISOWv6CIDg3DMOnu1+eFATBSUfaLgzDx/slmaTj2lHRwHfvfoWC3Aw+/97FZGf29t9zJEmSNNwc6zfF7wFzu5/fdpRtImBqnyaS1Cvb9tbz9V+vBODj18yz+EmSJOmYjvrbYhiGc3s8nzIwcST1xsvhfn70x3XkZKXxLx85k/yMNzNwryRJkoaTXv3GGATBvUdZ/vu+jSPpWNo74vz2yc189w9rSU9L4ZbrFzB13IhEx5IkSdIg0NvrxC44yvLz+yiHpOPojMf59u9Ws3ZbNQunl/Dhd8z2Uk9JkiT12jF/cwyC4F+7n2b0eP6aqcCOfkkl6Q1+8fBG1m6r5rLTJnL9BdMTHUeSJEmDzPFOG0zofkzp8Ry6BnopB77SD5kkHebJlbt5atUepowpsPhJkiTpTTlm+QvD8IMAQRA8H4bhjwYmkqSenl+7l589FJKfk84t189PdBxJkiQNUsea529yGIbbu18+FgTBEad0CMNwa38Ek4a7KIr4xSMbeWLFbsaW5PLpGxaSn5OR6FiSJEkapI515m8N/3979x1mV1Xoffw7Lcmkt5lU0ghZgYRQQ0C6FBFFUZpB4bUiXAV7ud4rYnuv3teKoqBYUCHSruAFFAFpKgIhCYFAVkIIKZM2SSZl0iYzc94/zomGmGROkjlnn/L9PE+ezNmz5+zfyawnc36z9l4bemU+foX0qZ4Vu+yTAqpykEsqe9Mens+jMxqYPL6e9507nm5dXNxFkiRJ+29v9/nrtdPH3kRMyqMFDet5+LmlHDK8D1e+fQIVFbv+3kWSJEnaN/tV6kIIY0IIozo5iyRg9bot/ODu2fToVs3VF0yy+EmSJKlTZHuT92khhDdkPn4fMAeYE0L4QC7DSeXmlaXr+c+bn6Z5SysfOm8CPWtrko4kSZKkEpHtzN8ZwPTMx58EzgSOAz6fi1BSOWpobOa7dz4PFfCZqUcy6eABSUeSJElSCcl2BYkuMcaWEMIwoH+M8a8AIYRBuYsmlY9V67bwnTuep629nc+86ygOHtYn6UiSJEkqMdmWv1khhH8HRgL3A2SK4IZcBZPKRVzcxPfunA3Axy88wuInSZKknMj2tM8PAIcDtcAXM9tOAG7NRSipXKxs2sz375pN1y5VfP7dRzN+ZL+kI0mSJKlEZTXzF2NcAFy6y7a7gLtyEUoqBy3b2/jmrTPY2tLGpy45kpGDe3X8RZIkSdJ+yvqu0ZlVPi8DhgENwK9jjL/IVTCplK3dsJXr75rNuuYWLj59rKd6SpIkKeeyKn8hhP8ALge+DSwife3fZ0MIQ2OMX89hPqnkrFy7ma/9ajqbtrZy0ekHc86UEUlHkiRJUhnIdubvg8BpMcZFOzaEEB4EngAsf1KWps9dxc8feJnWthT/dv5Ejh1fn3QkSZIklYlsy18PoHGXbWtILwAjKQvzlqzjxnvnMLBPN665cBJDB/ZIOpIkSZLKSLbl74/ArSGEzwOLSZ/2+XXgwVwFk0rJohUb+d6dz9O7Rw2fe/fR9OvVNelIkiRJKjPZ3urho8BGYDbQDMwCNgFX5yiXVDKmz13Fl3/5LK1tKT524REWP0mSJCWiw5m/EEIf4GDgI8B7gYHA6hhje26jScXvtRUb+NE9L9KtSxXXvncyg/t3TzqSJEmSytRey18I4S3AHaSv7dsInB9jfDQfwaRiN2/JOr5z+yy61lTxH5cdY/GTJElSojo67fOrwOeAnsC1uLKnlJU5r63lG7fOoKqqks9eehTD6nomHUmSJEllrqPyNybG+MMY42bgBmBsHjJJRe2J55fxnd/OomdtDV95/3GMHtI76UiSJElSh+XvH5+PMbaS/eqgUll6aPoSfvmHuQyv78l175vMgD7dko4kSZIkAR2Xue4hhCd2etxrl8fEGE/p/FhScWnesp1fPPAyM+ev5qD6nvz7e46mWxd/VyJJkqTC0dG70w/s8vhnuQoiFat1zdu47hfPsmFTC8cdWs/7zz2ULjVVSceSJEmSXmev5S/GeEu+gkjFqHnLdr5520w2bGrhYxdO4oixA5OOJEmSJO1Wtjd5l7SLzVu3881bZ7By7WamnnmIxU+SJEkFzYuSpP30o3tepGH1Jq5422Ecf9jgpONIkiRJe+XMn7QfHnluKS+91sRZxx5k8ZMkSVJRsPxJ++jFhWu49aF59O5ew9tOGpV0HEmSJCkrWZ32GULoClwLTAUGxBj7hBDOBsbFGH+Yy4BSIXnm5ZXcfN9LDO7fnU+/60h6dKtJOpIkSZKUlWxn/r4LTATeDaQy2+YAV+UilFSIXl22gRvvncPAPrV87tKj6N/bG7hLkiSpeGRb/t4BXBpjfApoB4gxNgDDchVMKiRr1m/l5vteAuAj75hIn55dE04kSZIk7ZtsV/ts2XXfEEIdsKbTE0kFJi5u4vq7X6C1rZ1rLpzEsLqeSUeSJEmS9lm2M393AreEEEYDhBCGAD8EfpurYFIhWLZ6E9+543mqKiv40nsnc6T38pMkSVKRyrb8fQFYCLwA9AXmA8uAL+col5S4VCrFT/53Du3tKT51yZEMHdgj6UiSJEnSfsvqtM8YYwvwCeATmdM9V8cYUx18mVTUHpq+lMUrm7ng1DGMHNwr6TiSJEnSAcn2Vg9jdtnUK4QAQIzx1c4OJSWtaeM2bv/zfCoq4M3Hj0w6jiRJknTAsl3w5RXSt3io2Gnbjpm/qk5NJCWsZXsbX/vVdFIp+NQlR1JZUdHxF0mSJEkFLtvTPl93bWAIYTDwJeDJXISSknTbw/Np2riNxnLlPAAAIABJREFU9507ngmj+ycdR5IkSeoU2S748joxxhXAx4H/6tw4UrJ+dv9LPPH8MiaM7s/Jk4YmHUeSJEnqNNme9rk7AejeWUGkpD07dxV/fWEFJ0wYzAfecmjScSRJkqROle2CL0/yz2v8IF36JgBfyUUoKd+at2zntofn0aW6ksvfFKis9Do/SZIklZZsZ/5u3uXxJuD5GOP8Ts4j5V3L9jZ+cPds1je38P5zD6VrF9cwkiRJUunpsPyFEKqANwJXxBi35T6SlD+pVIqv//o5lqxq5q1vGMVJk4YkHUmSJEnKiQ7LX4yxLYRwNtB+IAcKIYwDbgEGAGuAy/c0cxjSNxGcCfwoxvjpAzmutDdPzl7OklXNvHnKCN55yq63s5QkSZJKR7arfX4X+HIIoeYAjnUjcEOMcRxwA3DT7nbKzDTeBNxzAMeSOrRoxUZufWgePbpVc/7JFj9JkiSVtr2WvxDC1MyHVwOfATaGEJaEEBbv+JPNQUII9cDRwLTMpmnA0SGEut3s/nngPmBeNs8t7Y+Fyzfw39NmUFlZweffcww11ft11xNJkiSpaHR02udNpIvaew7wOAcBDTHGNvjHqaTLMtsbd+wUQjgCeBNwOvDFAzymtFsLGtbzrd/Oorqqgk+/60iGDeyRdCRJkiQp5zoqfxUAMcbHcx0kc0rpT4D3Zcrhfj3PgAE9OzVXZ6mr65V0BAHrNm7jm7fNoGuXar79sVMYVleY42VfOb6US44v5ZpjTLnk+FIuFdv46qj8VYUQTidTAncnxvjnLI6zBBgWQqjKFLsqYGhm+w5DgIOBBzLFry9QEULoHWO8IotjALBmTTPt7amOd8yjurpeNDZuTDpG2dve2s4Xb36atvYUl509ji6kSuL74vhSLjm+lGuOMeWS40u5VIjjq7KyYq+TYR2Vv67Az9hz+UsBHa6UEWNcFUKYBUwFfpP5e2aMsXGnfRYDA3c8DiFcB/R0tU91lj/8fRGr1m1h6pmHcNyhg5KOI0mSJOVVR+VvU4yxs5ZBvBK4JYRwLdAEXA4QQngAuDbGOL2TjiP9i6Wrmvnfv73GwcN6c+Yxw5OOI0mSJOVdh/f56ywxxrnAlN1sP3cP+1+X60wqD+2pFDf87gWqqyv58HkTqKjY41nMkiRJUsnqaH173yWr6N356CusbNrCBaeMYWDf2qTjSJIkSYnYa/mLMRbX8jXSLmbNX82Dzyxh0sEDOMPTPSVJklTGvLO1StaSVc386J4X6d2jC1ecd5ine0qSJKmsWf5UklY1beZbv51JVeZG7t271SQdSZIkSUqU5U8lp629nW/eNpONm7fziYuOYHiJ3MhdkiRJOhCWP5Wcn9//Mk0bt3HmscMZd1DfpONIkiRJBcHyp5Iyfe4qnpqzkkOG9+HSM8clHUeSJEkqGJY/lYyVazdz0+/nMLh/dz55yZFJx5EkSZIKiuVPJWHLtla+ffss2tpTXHX+RLrWVCUdSZIkSSoolj8Vve2tbfzk93NYvX4rH3nHRA6qd4EXSZIkaVfVSQeQDkQqleKG373I7AVreNuJozgm1CcdSZIkSSpIzvypqN37l4XMXrCGIw4ewPknj0k6jiRJklSwLH8qWvOXruP3f32N8SP6cs2Fk5KOI0mSJBU0y5+K0taWVq6/azYA7z33UCoqKhJOJEmSJBU2y5+K0p2PLWDT1lbef+6h1PetTTqOJEmSVPAsfyo6s15ZzaMzGphy2CBOmjQk6TiSJElSUbD8qahs2NzCjfe+SJfqSt591rik40iSJElFw/KnovJ/f/UcLdvb+fhFR9CztibpOJIkSVLRsPypaEx7eD6r1m3hrGMPYvzIfknHkSRJkoqK5U9F4Ynnl/HQ9CVMOngA7zpjbNJxJEmSpKJj+VPBW71uC3c/voAu1ZVc+fYJ3tZBkiRJ2g+WPxW07a1tfP03z7G1pY3PXHoU3bpUJx1JkiRJKkqWPxW0Pzy9mPXNLVx2duDgoX2SjiNJkiQVLcufCtachWu598mFjB3ehxMPH5x0HEmSJKmoWf5UkDZsauHH97xIrx5d+Og7D/c6P0mSJOkAWf5UcDZv3c7373qezdta+fDbJtC7e5ekI0mSJElFz9UzVFC2t7bzX7+ZQcPqTUw98xAO9X5+kiRJUqew/Kmg3P34AhpWb+Kys8dx+tHDk44jSZIklQxP+1TBePm1tfzp2SWMHtKb044alnQcSZIkqaRY/lQQtrW08eN759C1poqrvJG7JEmS1OksfyoID01fQvOW7Vx1/gQG9q1NOo4kSZJUcix/StzC5Rv4nydeZfyIvhw+ZkDScSRJkqSSZPlTotrbU/zs/pepqa7kw2/zdE9JkiQpVyx/StTvnnyVZas3ceFpB9OnZ9ek40iSJEkly/KnxDw7dxUPPLWIg4f15sxjvK2DJEmSlEuWPyUiLm7ix/e8SI/aGv7t/MM93VOSJEnKMcuf8q5lexu//MNcAK5977H06+XpnpIkSVKuWf6Ud9Memc/Kpi185B0TGdjH2zpIkiRJ+WD5U141NDbz+KxlnHbkUI4J9UnHkSRJksqG5U95055K8fMH5lJTXcnbTxqddBxJkiSprFj+lDcPPr2Yhcs3cOoRQ72tgyRJkpRnlj/lRVzcxJ2PLWDssD5ccsbYpONIkiRJZcfyp5xbu2Er1989m65dqvjQeYdRVemwkyRJkvLNd+HKqS3bWvnvaTPZsq2Nz049irq+ru4pSZIkJcHyp5zZ3trOV26ZzqqmLVzyxrGMHtI76UiSJElS2bL8KWd+++f5rFy7mYtPH8ubjhuRdBxJkiSprFn+lBN3P76AR2c0cPxhgzhnisVPkiRJSprlT53utRUbuP+pRQzs0433nXto0nEkSZIkYflTJ1u9bgtfu+U5artW8alLjqSm2iEmSZIkFQLfmatT3fX4AtpTKa65YBKD+ndPOo4kSZKkDMufOs1Dzy7hmZdXcfyEQYQR/ZKOI0mSJGknlj91ipVrNzPtkfkMGdCd954zPuk4kiRJknZh+VOn+P1fFwLwwbceRpeaqoTTSJIkSdqV5U8HrGH1Jp55eRUnTxrijdwlSZKkAmX50wFpbWvn27+dSUVFBe88ZUzScSRJkiTtgeVPB+RXD0bWNbcweXwdfXp2TTqOJEmSpD2w/Gm/LVy+gb/MXs7EMf350HkTko4jSZIkaS8sf9ovqVSK2x+ZT2VFBZefHZKOI0mSJKkDlj/tl2fnrmLe0vW86biDGNi3Nuk4kiRJkjpg+dN+ufPRV+jXqyvnnzw66SiSJEmSsmD50z6bu6iJNRu2cWyop6bae/pJkiRJxcDyp32ycXMLN/zuBXp0q+a8E0clHUeSJElSlix/2iffv2s2m7a2cuX5E+lZW5N0HEmSJElZsvwpaw2Nzby6bANvOWEkE0b1TzqOJEmSpH1g+VPWnpy9HIAphw5KOIkkSZKkfWX5U1ZeXLiGh6Yv4ahDBjK8vmfScSRJkiTtI8ufOrRp63Z+8vuX6FJdxeXnjE86jiRJkqT9YPlTh+748ys0b9nOlW+fQJ8eXZKOI0mSJGk/WP60V9u2t/GXF5ZzwoTBHDF2YNJxJEmSJO0ny5/26pmXVpJKwZTDXORFkiRJKmaWP+3Rlm2t/M8TrzJkQHcmjvbWDpIkSVIxs/xpj27541zWb2rh8jcFKisrko4jSZIk6QBY/rRbTRu3MWNeI8PrehBG9Es6jiRJkqQDZPnTbt320Dxa21J84C2HJR1FkiRJUiew/OlfPPXiCp6b18hpRw1j5OBeSceRJEmS1Aksf3qdhsZmfnrfS/Tr1ZVLTh+bdBxJkiRJncTyp9f5w9OLAbj6gsPp2qUq4TSSJEmSOovlT/+wYXMLz7y8ioPqezJqcO+k40iSJEnqRJY//cN9f32N1rZ2LntTSDqKJEmSpE5m+RMALdvb+NuLK6jvW8vYYX2SjiNJkiSpk1n+BMD375rN5m2tXHrWIUlHkSRJkpQDlj/x4qtreHlREwN6d2PSwQOTjiNJkiQpByx/Za69PcUv/jAXgC+9b3LCaSRJkiTliuWvzN368DyaNm7jvDeMomdtTdJxJEmSJOWI5a+MtadSPDqjgX69uvKOU8YkHUeSJElSDln+ytjTL60E4NzjRyacRJIkSVKuWf7KVGtbO7974lXq+9Zy+tHDko4jSZIkKccsf2Xq73NWsnr9Vs49YSSVFRVJx5EkSZKUY5a/MvXUnBX07l7DSZOGJB1FkiRJUh5Y/srQmvVbmbuoicmHDnLWT5IkSSoT1fk6UAhhHHALMABYA1weY5y/yz5fBN4FtAHbgS/EGB/MV8Zyccejr5ACzjxmeNJRJEmSJOVJPmf+bgRuiDGOA24AbtrNPs8Ak2OMk4D3A7eHEGrzmLHkLV+ziWfnruK4Q+sZ1L970nEkSZIk5Uleyl8IoR44GpiW2TQNODqEULfzfjHGB2OMmzMPZwMVpGcK1Ul+86d5VFTAO72vnyRJklRW8jXzdxDQEGNsA8j8vSyzfU8uBxbEGJfmIV9ZWLqqmZcXNXHGMcOp7+esnyRJklRO8nbN374IIZwKfBU4a1+/dsCAnp0fqBPU1fVKOgK/eTh9ieUlZ4+nbkCPhNOoMxXC+FLpcnwp1xxjyiXHl3Kp2MZXvsrfEmBYCKEqxtgWQqgChma2v04I4QTgN8DbY4xxXw+0Zk0z7e2pAw7cmerqetHYuDHRDA2NzTw6fQmnHDGEqvb2xPOo8xTC+FLpcnwp1xxjyiXHl3KpEMdXZWXFXifD8nLaZ4xxFTALmJrZNBWYGWNs3Hm/EMJk4HbgwhjjjHxkKwepVIpf/nEuVVWVvO3E0UnHkSRJkpSAfJ72eSVwSwjhWqCJ9DV9hBAeAK6NMU4HfgTUAjeFEHZ83WUxxhfymLPkPBcbWdCwgQtOHUP/3t2SjiNJkiQpAXkrfzHGucCU3Ww/d6ePJ+crT7nYvHU7tz48j7q+3Th78oik40iSJElKSD7v86cE3HjvHNY3t/CuNx5CTbXfbkmSJKlc2QZK3KvLNlDfr5ajxtV1vLMkSZKkkmX5K2ENjc1s3tbKMRY/SZIkqexZ/krYLQ9GKirgjGOGJx1FkiRJUsIsfyXqlaXreWXpeqYcNsgVPiVJkiRZ/krVfU+9RlVlBVPPOCTpKJIkSZIKgOWvBG3c3MLsBWuYMLo/vbp3STqOJEmSpAJg+StBf3h6MQBvP2l0wkkkSZIkFQrLX4lJpVI8OrOB0UN6M3pI76TjSJIkSSoQlr8S87cXV7CtpY3J4+uTjiJJkiSpgFj+SkgqleKPTy+mvl8tZx93UNJxJEmSJBUQy18JeejZJTSs3sSbp4ygsqIi6TiSJEmSCojlr4Q8MXs5ACcePiThJJIkSZIKjeWvRDSs3sSy1Zs4ceJgqqv8tkqSJEl6PVtCiXhk+hIAzjtxVLJBJEmSJBUky18JmLdkHY/NWsZJk4ZQ36970nEkSZIkFSDLXwl4cvYyAC467eCEk0iSJEkqVJa/Ite8ZTtPvbiS4ycMolf3LknHkSRJklSgLH9F7tEZS2lPpTjtyGFJR5EkSZJUwCx/Re652Eh931oOGd4n6SiSJEmSCpjlr4jFxU0sXtXMiYcPpsKbukuSJEnaC8tfEXtuXiMAUw4blHASSZIkSYXO8lekWtvaeXj6UiaO6e/tHSRJkiR1yPJXpGbNXw3ApDEDEk4iSZIkqRhY/orUc/Maqe1azamu8ilJkiQpC5a/IpRKpZgxr5FDhvehptpvoSRJkqSO2RyK0JyFa9ne2s74Ef2SjiJJkiSpSFj+itDDzy0F4IQJrvIpSZIkKTuWvyLT2tbO3EVNnDBhEH16dk06jiRJkqQiYfkrMo/OaKCltZ3jDnXWT5IkSVL2LH9FJJVK8adnFzOsrgeTDvYWD5IkSZKyZ/krIrPmr2bNhm2cduQwKioqko4jSZIkqYhY/opEa1s70x6ZT6/uNbxh4uCk40iSJEkqMpa/IvHYzAZWr9/KxaePpbZrddJxJEmSJBUZy18RSKVSPDKjgUH9ajnBWT9JkiRJ+8HyVwTmLmpi5drNnHHMcCq91k+SJEnSfrD8FYG7Hl9AVWUFJx4+JOkokiRJkoqU5a/AbdjcwsLlGwkj+nqtnyRJkqT9ZvkrcH97YQUAbzpuRMJJJEmSJBUzy1+Be2j6Egb3787hY7ypuyRJkqT9Z/krYDPmNdK0cRvHjq9LOookSZKkImf5K2CPzlgKwNmTPeVTkiRJ0oGx/BWolU2bmfNaE2ceO5yetTVJx5EkSZJU5Cx/BeqxmQ0AnHH08ISTSJIkSSoFlr8CNW/JOrp1qWJQ/+5JR5EkSZJUAix/BWjN+q0sXL6RM489KOkokiRJkkqE5a8A/enZJQBMGNUv4SSSJEmSSoXlr8C0p1I8NH0JY4b2Joyw/EmSJEnqHJa/AvPiq2sBmDi6f8JJJEmSJJUSy1+BefCZxdRUV/LmKSOTjiJJkiSphFj+CsjSxmZeXtTExNH96dqlKuk4kiRJkkqI5a+APDVnBQDvOGVMwkkkSZIklRrLXwGZs3AtI+p7MryuZ9JRJEmSJJUYy1+B2NrSyuKVzdT3q006iiRJkqQSZPkrEE/MWgbAUePqEk4iSZIkqRRZ/grEky8sp65vN44/bFDSUSRJkiSVIMtfAVi7YSsNjZs4edJQKioqko4jSZIkqQRZ/grAozMbADjykIEJJ5EkSZJUqix/BeD+pxZR27WaYQN7JB1FkiRJUomy/CVs/aYWAIYO7O4pn5IkSZJyxvKXsBnzGgG4+PSxCSeRJEmSVMosfwl7eVETAKMG9044iSRJkqRSZvlL2Pwl6xjYpxs11X4rJEmSJOWOjSNBy1ZvYv2mFiaM7p90FEmSJEklzvKXoL+/tAKAc6aMSDiJJEmSpFJn+UvQc7GRnrU1DOrXPekokiRJkkqc5S8hW7a1snzNZkYPcaEXSZIkSbln+UvIE88vA+CEiYMSTiJJkiSpHFj+EvJc5v5+k8fXJ5xEkiRJUjmw/CVgw+YWXlm6nuMPG0RVpd8CSZIkSbln80jAjMys30mThiScRJIkSVK5sPwl4NVlGwAYObhXwkkkSZIklQvLXwLmLFxLBdCjW03SUSRJkiSVCctfnq1r3sa65m2MH9kv6SiSJEmSyojlL8+emrOCVAouPfOQpKNIkiRJKiOWvzybv2Q9fXt2YVhdz6SjSJIkSSojlr88m/XKakYMcqEXSZIkSfll+cujpY3NANT3rU04iSRJkqRyY/nLo9kL1gBwzpQRCSeRJEmSVG4sf3nU0LiJnrU19OvVNekokiRJksqM5S+PljY2M3RAdyoqKpKOIkmSJKnMWP7ypK29neVrNjG83lU+JUmSJOWf5S9P5ixsorUtxdhhfZKOIkmSJKkMWf7yZMa8RgAmjO6fcBJJkiRJ5cjylycNq5vp0a2aXt27JB1FkiRJUhmy/OXJgoYNjB/RL+kYkiRJksqU5S8P1m7YCkD/3t0STiJJkiSpXFn+8uD3TywA4LhD6xNOIkmSJKlcWf7y4KWFa6mqrGDM0N5JR5EkSZJUpix/ebBsdTNHj6vz5u6SJEmSElOdrwOFEMYBtwADgDXA5THG+bvsUwVcD5wDpIBvxBhvzlfGXGjesp31zS0Mr+uRdBRJkiRJZSyfM383AjfEGMcBNwA37WafdwNjgUOAE4DrQgij8pYwBxY0rAdgyADLnyRJkqTk5KX8hRDqgaOBaZlN04CjQwh1u+x6CfDTGGN7jLERuAe4KB8Zc2Xh8g2AN3eXJEmSlKx8zfwdBDTEGNsAMn8vy2zf2Qhg0U6PF+9mn6KyZsNWBvatpbZr3s6wlSRJkqR/UXKNZMCAnklHeJ2PXnwUq9dvpa6uV9JRVMIcX8olx5dyzTGmXHJ8KZeKbXzlq/wtAYaFEKpijG2ZhV2GZrbvbDEwEng283jXmcAOrVnTTHt76kDzdqpRQ3rT2Lgx6RgqUXV1vRxfyhnHl3LNMaZccnwplwpxfFVWVux1Miwvp33GGFcBs4CpmU1TgZmZ6/p2difwoRBCZeZ6wPOBu/KRUZIkSZJKWT5X+7wSuDqEMA+4OvOYEMIDIYRjM/v8GngVmA/8HfhKjHFhHjNKkiRJUknK2zV/Mca5wJTdbD93p4/bgKvylUmSJEmSykU+Z/4kSZIkSQmx/EmSJElSGbD8SZIkSVIZsPxJkiRJUhmw/EmSJElSGbD8SZIkSVIZsPxJkiRJUhmw/EmSJElSGbD8SZIkSVIZsPxJkiRJUhmw/EmSJElSGbD8SZIkSVIZsPxJkiRJUhmw/EmSJElSGbD8SZIkSVIZsPxJkiRJUhmw/EmSJElSGbD8SZIkSVIZqE46QCeqAqisrEg6x24Vai6VBseXcsnxpVxzjCmXHF/KpUIbXzvlqdrd5ytSqVT+0uTWScCTSYeQJEmSpISdDPxl142lVP66ApOB5UBbwlkkSZIkKd+qgCHAs8C2XT9ZSuVPkiRJkrQHLvgiSZIkSWXA8idJkiRJZcDyJ0mSJEllwPInSZIkSWXA8idJkiRJZcDyJ0mSJEllwPInSZIkSWWgOukApSKEMA64BRgArAEujzHO32WfKuB64BwgBXwjxnhzvrOq+GQ5vr4IvAtoA7YDX4gxPpjvrCpO2YyxnfYNwEzgRzHGT+cvpYpVtuMrhHAx8EWggvTPyTNjjCvzmVXFJ8ufkfXAL4CDgBrgUeCaGGNrnuOqyIQQvgVcAIwCDo8xvribfYrmPb4zf53nRuCGGOM44Abgpt3s825gLHAIcAJwXQhhVN4SqphlM76eASbHGCcB7wduDyHU5jGjils2Y2zHD7ibgHvymE3Fr8PxFUI4FrgOOCvGOBE4CVifz5AqWtn8//UF4OXMz8hJwDHAO/MXUUXsHuAUYNFe9ima9/iWv06Q+W3S0cC0zKZpwNEhhLpddr0E+GmMsT3G2Eh6MF2Uv6QqRtmOrxjjgzHGzZmHs0n/5nxA3oKqaO3D/2EAnwfuA+blKZ6K3D6Mr08A34oxrgCIMa6PMW7NX1IVo30YXymgVwihEugKdAEa8hZURSvG+JcY45IOdiua9/iWv85xENAQY2wDyPy9LLN9ZyN4/W8NFu9mH2lX2Y6vnV0OLIgxLs1DPhW/rMZYCOEI4E3Ad/OeUMUs2//DDgPGhBCeCCHMCCH8ZwihIs9ZVXyyHV9fBcYBy4EVwIMxxr/mM6hKWtG8x7f8SSUmhHAq6R9yU5POotIRQqgBfgJcueNNltTJqkifjncWcCrwZuCyRBOplFxE+qyYIcAw4JQQwoXJRpLyz/LXOZYAwzLXwuy4JmZoZvvOFgMjd3o8Yjf7SLvKdnwRQjgB+A1wfowx5jWlilk2Y2wIcDDwQAjhNeDjwIdCCD/Jb1QVoX35GXlXjHFbjHEjcC9wXF6TqhhlO76uBm7NnJa3nvT4Oj2vSVXKiuY9vuWvE8QYVwGz+OdMy1RgZuac353dSfrNUmXmXPTzgbvyl1TFKNvxFUKYDNwOXBhjnJHflCpm2YyxGOPiGOPAGOOoGOMo4Hukr2+4Iu+BVVT24WfkbcDZIYSKzEzzGcDz+UuqYrQP42sh6ZUYCSF0Ac4E/mXVRmk/Fc17fMtf57kSuDqEMI/0b5euBAghPJBZwQzg18CrwHzg78BXYowLkwiropPN+PoRUAvcFEKYlflzeDJxVYSyGWPS/spmfP0WWAW8RPrN/BzgZwlkVfHJZnx9HDg5hPAC6fE1D/hpEmFVXEII14cQlgLDgYdDCHMy24vyPX5FKpVKOoMkSZIkKcec+ZMkSZKkMmD5kyRJkqQyYPmTJEmSpDJg+ZMkSZKkMmD5kyRJkqQyYPmTJBWFEMJjIYQPJp1jb0II7w4h/Gkvnz85hBDzmUmSpB281YMkKe9CCK8Bg4C2nTaPizEu28vXPAb8JsZ4cyfmeAw4HmgFtgJPAB+JMS7vpOdPAYfEGF/pjOfby3GuA/4D2Eb6tbwEfCrG+FSWX5+XnJKkZDnzJ0lKynkxxp47/dlj8cuxj8YYewLjgL7AdxPKcaBuz7yOgcCjwJ0J55EkFZjqpANIkgQQQugH/BqYQvrn01+BK2OMS3ez71jgZ8CRwHbgkRjjJZnPjQd+ABwDNAJfjDHe0dHxY4xrQwh3A1dlnucNwPdJl8J5wMdijH/LfO69wLVAHbAa+M8Y462Z7R+MMZ4UQngi89TPZ2bWPgCsJD17OTyE8Dlgcozxwp1e1/eBihjjNSGEPsB3gHOBduAXwJdijDvPlu7udbSGEG4FvhBCqIsxNoYQjsu8lkOBLcDdwCdjjC27yxljvD2E8Fbga8Ao0jOJV8YYZ3f07yhJKlzO/EmSCkUl6YIzEhhBuqT8cA/7fhX4E9APGE667BFC6AE8BNwG1APvAn4UQjiso4OHEAYCFwAzQwj9gfuB64EBpEvY/SGEAZljXA+8OcbYC3gDMGvX54sxnpL58IjMzObtu+zyW+DcEEKvzPGrgIsz2QF+SfoUzrHAUcDZQIfXPIYQugCXA2uApszmNuATpGcFTwDOAP5tTzlDCEcBPwc+nHn9NwG/DyF07ej4kqTC5cyfJCkp94QQWjMfPxZjPJ/0jBQAIYSvkz59cXe2ky6JQzMzg3/JbH8r8FqM8ReZxzMzs3kXAV/ew3NdH0L4FrAJeAz4JPAWYH6M8deZfaaFEK4BziN9OmU7MDGEsDhzfeA+XyMYY1wUQpgBvAP4FfBGYHOM8e8hhEGkZ/z6xhi3AJtCCN8FriBdxHbn4sxsXS9gHXBBjLE1c6zndtrvtRDCTcCpwPf28FxXADfFGJ/OPL4lhPAF0tdHPr6vr1WSVBgsf5KkpJwfY3x4x4MQQnfS19udQ3pGD6BXCKFqN6c6fpb07N8zIYQm4Nsxxp+TLoRTQgjrdtq3mvTppHtyza6LyIQcNdGYAAAClklEQVQQhgKLdtlvETAsxrgphHAJ8GngZyGEv5JeXGVuFq95V7cBU0mXv0v556zfSKAGWB5C2LFvJbBkL891R4zxPZkZzLtJn/b6WOb1jCM9e3ks0J30v8lze3ieHcf/PyGEq3fa1gUYmu0LkyQVHsufJKlQfAoIwJQY44oQwpHATKBi1x1jjCuADwGEEE4CHs5cu7YEeDzGeNYBZllGugDtbATwx8zxHwQeDCHUkr4u7qfAyftxnDuBb4cQhpOeATwhs30J6ZU7B+6YvctWjHF1COEKYHoI4bbMzOSPSf9bTo0xbgwhfBy4cC9PswT4eozx6/v4eiRJBczyJ0kqFL1IX+e3LnPN3Zf2tGMI4SLgqcwpn01AivSpmPcB3wghXEb6mjpILwrTHGN8eR+yPAD8IIRwKXAH6WsBDwPuy5ySeTzwcCZvc+bYu7MSGAPs9hYKmcVYHiN9rePCHRljjMsz9wv8dgjhi5ljjAaGxxg7PO0yxhhDCA+SniH9BOl/2w1Ac2ZBnKtIL4azp5w/BX4XQngYeIb0bOFpwBMxxo0dHV+SVJhc8EWSVCi+B9SSXj3z72Rm2fZgMvB0CKEZ+D3plThfzRSTs0kv9LIMWAF8E9inhUpijGtIXz/4KdILp3wWeGuMcTXpn52fzDz/WtLXzl21h6e6jvT1cutCCBfvYZ/bgDP55ymfO1xO+lTLl0gX3LuAIfvwMv4fcEUIoZ70KaqXAhtJF7tdF595Xc4Y43TSM6s/zBz7FeC9+3BsSVIB8ibvkiRJklQGnPmTJEmSpDJg+ZMkSZKkMmD5kyRJkqQyYPmTJEmSpDJg+ZMkSZKkMmD5kyRJkqQyYPmTJEmSpDJg+ZMkSZKkMmD5kyRJkqQy8P8B5NwSAZBiswIAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Top 10 Random Forest Feature Importances \n",
        "\n",
        "rf = RandomForestClassifier(max_features=10, min_samples_leaf=47,\n",
        "                       min_samples_split=10, n_estimators=300, random_state=42)\n",
        "rf.fit(X_train, y_train)\n",
        "\n",
        "sorted_idx = rf.feature_importances_.argsort()[-10:]\n",
        "plt.figure(figsize=(10,10))\n",
        "plt.barh(X.columns[sorted_idx], rf.feature_importances_[sorted_idx])\n",
        "plt.title('Top 10 Random Forest Feature Importances')\n",
        "plt.xlabel(\"Feature Importances\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 627
        },
        "id": "qzml3ZiuRuLy",
        "outputId": "4278e50f-ed8f-4569-aef5-e39b3fc46e7e"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# XGB Classifier using RandomizedSearch cross-validation\n",
        "\n",
        "xgbc = XGBClassifier(random_state=42)\n",
        "param_grid = {'learning_rate' : [0.05,0.10,0.15,0.20,0.25,0.30], \n",
        "          'max_depth' : [ 3, 4, 5, 6, 8, 10, 12, 15], \n",
        "          'min_child_weight' : [ 1, 3, 5, 7 ], \n",
        "          'gamma': [ 0.0, 0.1, 0.2 , 0.3, 0.4 ], \n",
        "          'colsample_bytree' : [ 0.3, 0.4, 0.5 , 0.7 ]}\n",
        "\n",
        "rs_xgbc = RandomizedSearchCV(xgbc, param_grid, scoring='accuracy', n_iter=5, random_state=42)\n",
        "rs_xgbc.fit(X_train, y_train)\n",
        "\n",
        "rs_xgbc_score = rs_xgbc.score(X_val, y_val)*100\n",
        "print('The selected XGB Classifier model: ', rs_xgbc.best_estimator_)\n",
        "print(\"Accuracy of XGB model on vaidation dataset: {:.2f}%\".format(rs_xgbc_score))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "574eTn93FRJ0",
        "outputId": "f90ea102-50d5-4f9b-f464-85a50d4a6efa"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The selected XGB Classifier model:  XGBClassifier(colsample_bytree=0.7, gamma=0.3, max_depth=8, min_child_weight=7,\n",
            "              random_state=42)\n",
            "Accuracy of XGB model on vaidation dataset: 70.32%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#ROC curve\n",
        "pred = rs_xgbc.predict_proba(X_val)[::,1]\n",
        "fpr, tpr, thresholds = roc_curve(y_val, pred)\n",
        "auc_score = roc_auc_score(y_val, pred)\n",
        "\n",
        "plt.figure(figsize=(15, 10))\n",
        "plt.plot(fpr, tpr, label='AUC = %.3f' % (auc_score))\n",
        "plt.legend()\n",
        "plt.title('ROC curve', size=20)\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.grid(True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "id": "jxDLh3OCFpU6",
        "outputId": "7adeed5c-fd90-44ee-c391-33191de025c3"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Selected model (XGB Classifier) performance on test set\n",
        "y_pred = rs_xgbc.predict(X_test)\n",
        "test_accuracy=accuracy_score(y_test,y_pred)*100\n",
        "print(\"Accuracy of our best model on test dataset: {:.2f}%\".format(test_accuracy))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AMJ2DQ6iT366",
        "outputId": "aa619da6-4cc4-42e7-9f41-8e220b8aa0a0"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of our best model on test dataset: 70.26%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Recommendations**\n",
        "\n",
        "## **Project**\n",
        "The main things to look at before launching your project on kickstarter are:\n",
        "- The duration of the kisckstarter campaign (Avoid 30-60 days, make it either short or long)\n",
        "- The name of your project (around 20 characters looks to be the perfect option)\n",
        "- The type of your project (Music projects are the ones with the highest rate of success, however there is a large disparity inside main categories. Ex: DIY electronics projects have a good success rate (similar to music) while being part of a category that doesn't perform well (Technology's category))\n",
        "- The number of projects that have been launched during the last 7 days"
      ],
      "metadata": {
        "id": "dxYFEIQ43G26"
      }
    }
  ],
  "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": "3.7.9"
    },
    "colab": {
      "name": "Kickstarter_prediction_notebook.ipynb",
      "provenance": [],
      "collapsed_sections": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}