Poll of the family for the 2020 Democratic Primary

Pugh Poll.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import FuncFormatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = [12, 8]\n",
    "plt.rcParams[\"font.size\"] = 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"/mnt/c/Users/rfilmyer/Documents/Data Pulls/Pugh Primary Poll.csv\")\n",
    "original_columns = data.columns\n",
    "data.columns = [\"timestamp\", \"age\", \"first_choice\", \"biden\", \"bernie\", \"warren\", \"harris\", \"pete\", \"beto\", \"booker\", \"yang\", \"castro\", \"gabbard\", \"williamson\", \"klobuchar\", \"de_blasio\"]\n",
    "candidate_columns = data.columns[3:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "question_wording = {key: value for key, value in zip(data.columns, original_columns)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "data[\"age\"] = pd.Categorical(data[\"age\"], categories=[\"0-22\", \"23-35\", \"40+\"], ordered=True)\n",
    "\n",
    "FavorabilityDType = pd.CategoricalDtype(categories=[\"Strongly unfavorable\", \"Mildly unfavorable\", \"Neither favorable nor unfavorable\", \"Mildly favorable\", \"Strongly favorable\"], ordered=True)\n",
    "\n",
    "for candidate_colname in candidate_columns:\n",
    "    data[candidate_colname] = data[candidate_colname].astype(FavorabilityDType)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "column_value_counts = [data[colname].value_counts(sort=False) for colname in data.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0-22     5\n",
       "23-35    5\n",
       "40+      9\n",
       "Name: age, dtype: int64"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "column_value_counts[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data = column_value_counts[1]\n",
    "fig, ax = plt.subplots()\n",
    "_, texts, autotexts = ax.pie(plot_data, labels=plot_data.index, startangle=90, counterclock=False, autopct='%1.0f%%')\n",
    "ax.set_title(question_wording.get(plot_data.name))\n",
    "for text in texts:\n",
    "    text.set_fontweight('bold')\n",
    "for autotext in autotexts:\n",
    "    autotext.set_size(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data = column_value_counts[2]\n",
    "fig, ax = plt.subplots()\n",
    "_, texts, autotexts = ax.pie(plot_data, labels=plot_data.index, startangle=90, counterclock=False, autopct='%1.0f%%')\n",
    "ax.set_title(question_wording.get(plot_data.name))\n",
    "for text in texts:\n",
    "    text.set_fontweight('bold')\n",
    "for autotext in autotexts:\n",
    "    autotext.set_size(15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Opinion Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_opinion_table(value_counts: list) -> pd.DataFrame:\n",
    "    \"\"\"\n",
    "    Creates a table of candidate opinions, with a net favorability score\n",
    "    \"\"\"\n",
    "    opinion_totals = pd.DataFrame(value_counts[3:]).fillna(0)\n",
    "    opinion_totals = opinion_totals[FavorabilityDType.categories] # get the order right!\n",
    "    opinion_totals.columns = opinion_totals.columns.astype('str')\n",
    "    opinion_totals[\"total_respondents\"] = opinion_totals.sum(axis=1)\n",
    "    opinion_totals[\"total_positive\"] = opinion_totals[[\"Mildly favorable\", \"Strongly favorable\"]].sum(axis=1)\n",
    "    opinion_totals[\"total_negative\"] = opinion_totals[[\"Mildly unfavorable\", \"Strongly unfavorable\"]].sum(axis=1)\n",
    "    opinion_totals[\"net_favorability_pct\"] = (opinion_totals[\"total_positive\"] - opinion_totals[\"total_negative\"]) / opinion_totals[\"total_respondents\"]\n",
    "    return opinion_totals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Strongly unfavorable</th>\n",
       "      <th>Mildly unfavorable</th>\n",
       "      <th>Neither favorable nor unfavorable</th>\n",
       "      <th>Mildly favorable</th>\n",
       "      <th>Strongly favorable</th>\n",
       "      <th>total_respondents</th>\n",
       "      <th>total_positive</th>\n",
       "      <th>total_negative</th>\n",
       "      <th>net_favorability_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>biden</th>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>-0.368421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bernie</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>19</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>0.105263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>warren</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>19</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>0.842105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>harris</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>19</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>0.315789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pete</th>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>-0.052632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beto</th>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.578947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>booker</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>0.052632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yang</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>-0.052632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>castro</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0.315789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gabbard</th>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>-0.421053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>williamson</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>-0.315789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>klobuchar</th>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>-0.315789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de_blasio</th>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>-0.789474</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Strongly unfavorable  Mildly unfavorable  \\\n",
       "biden                          7                   4   \n",
       "bernie                         5                   2   \n",
       "warren                         1                   0   \n",
       "harris                         1                   4   \n",
       "pete                           0                   6   \n",
       "beto                           2                  10   \n",
       "booker                         1                   4   \n",
       "yang                           2                   5   \n",
       "castro                         0                   2   \n",
       "gabbard                        6                   3   \n",
       "williamson                     9                   1   \n",
       "klobuchar                      1                   9   \n",
       "de_blasio                      7                   8   \n",
       "\n",
       "            Neither favorable nor unfavorable  Mildly favorable  \\\n",
       "biden                                       4                 4   \n",
       "bernie                                      3                 6   \n",
       "warren                                      1                 3   \n",
       "harris                                      3                 3   \n",
       "pete                                        8                 4   \n",
       "beto                                        6                 1   \n",
       "booker                                      8                 5   \n",
       "yang                                        6                 5   \n",
       "castro                                      9                 3   \n",
       "gabbard                                     9                 1   \n",
       "williamson                                  5                 3   \n",
       "klobuchar                                   5                 3   \n",
       "de_blasio                                   4                 0   \n",
       "\n",
       "            Strongly favorable  total_respondents  total_positive  \\\n",
       "biden                        0                 19               4   \n",
       "bernie                       3                 19               9   \n",
       "warren                      14                 19              17   \n",
       "harris                       8                 19              11   \n",
       "pete                         1                 19               5   \n",
       "beto                         0                 19               1   \n",
       "booker                       1                 19               6   \n",
       "yang                         1                 19               6   \n",
       "castro                       5                 19               8   \n",
       "gabbard                      0                 19               1   \n",
       "williamson                   1                 19               4   \n",
       "klobuchar                    1                 19               4   \n",
       "de_blasio                    0                 19               0   \n",
       "\n",
       "            total_negative  net_favorability_pct  \n",
       "biden                   11             -0.368421  \n",
       "bernie                   7              0.105263  \n",
       "warren                   1              0.842105  \n",
       "harris                   5              0.315789  \n",
       "pete                     6             -0.052632  \n",
       "beto                    12             -0.578947  \n",
       "booker                   5              0.052632  \n",
       "yang                     7             -0.052632  \n",
       "castro                   2              0.315789  \n",
       "gabbard                  9             -0.421053  \n",
       "williamson              10             -0.315789  \n",
       "klobuchar               10             -0.315789  \n",
       "de_blasio               15             -0.789474  "
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opinion_totals = create_opinion_table(column_value_counts)\n",
    "opinion_totals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "biden        -36\n",
       "bernie        10\n",
       "warren        84\n",
       "harris        31\n",
       "pete          -5\n",
       "beto         -57\n",
       "booker         5\n",
       "yang          -5\n",
       "castro        31\n",
       "gabbard      -42\n",
       "williamson   -31\n",
       "klobuchar    -31\n",
       "de_blasio    -78\n",
       "Name: net_favorability_pct, dtype: int64"
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(opinion_totals[\"net_favorability_pct\"] * 100).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "net_favorability_scores = opinion_totals[\"net_favorability_pct\"].to_dict()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Opinion Graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.403921568627451, 0.0, 0.12156862745098039, 1.0),\n",
       " (0.8991926182237601, 0.5144175317185697, 0.4079200307574009, 1.0),\n",
       " (0.9657054978854287, 0.9672433679354094, 0.9680891964628989, 1.0),\n",
       " (0.4085351787773935, 0.6687427912341408, 0.8145328719723184, 1.0),\n",
       " (0.0196078431372549, 0.18823529411764706, 0.3803921568627451, 1.0)]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# I regret not using seaborn for this\n",
    "# BUT... it is quite useful!\n",
    "num_categories = len(FavorabilityDType.categories)\n",
    "opinion_colors = [plt.cm.RdBu(x / (num_categories - 1)) for x in range(num_categories)]\n",
    "opinion_colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(1, 1.1, '(Net Favorability: 84%)')"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data = column_value_counts[5]\n",
    "fig, ax = plt.subplots()\n",
    "_, texts, autotexts = ax.pie(plot_data, colors=opinion_colors, labels=plot_data.index, startangle=90, counterclock=False, autopct='%1.0f%%')\n",
    "ax.set_title(question_wording.get(plot_data.name))\n",
    "for text in texts:\n",
    "    text.set_fontweight('bold')\n",
    "for autotext in autotexts:\n",
    "    autotext.set_size(15)\n",
    "ax.text(1, 1.10, \"(Net Favorability: {:.0%})\".format(net_favorability_scores.get(plot_data.name)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(1, 1.1, '(Net Favorability: -79%)')"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data = column_value_counts[-1]\n",
    "fig, ax = plt.subplots()\n",
    "_, texts, autotexts = ax.pie(plot_data, colors=opinion_colors, labels=plot_data.index, startangle=90, counterclock=False, autopct='%1.0f%%')\n",
    "ax.set_title(question_wording.get(plot_data.name))\n",
    "for text in texts:\n",
    "    text.set_fontweight('bold')\n",
    "for autotext in autotexts:\n",
    "    autotext.set_size(15)\n",
    "ax.text(1, 1.10, \"(Net Favorability: {:.0%})\".format(net_favorability_scores.get(plot_data.name)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(1, 1.1, '(Net Favorability: 11%)')"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data = column_value_counts[4]\n",
    "fig, ax = plt.subplots()\n",
    "_, texts, autotexts = ax.pie(plot_data, colors=opinion_colors, labels=plot_data.index, startangle=90, counterclock=False, autopct='%1.0f%%')\n",
    "ax.set_title(question_wording.get(plot_data.name))\n",
    "for text in texts:\n",
    "    text.set_fontweight('bold')\n",
    "for autotext in autotexts:\n",
    "    autotext.set_size(15)\n",
    "ax.text(1, 1.10, \"(Net Favorability: {:.0%})\".format(net_favorability_scores.get(plot_data.name)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(1, 1.1, '(Net Favorability: 32%)')"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EZ25AjJ+QlGU97unnCNfQRrimrAwzgal5CRW83+5AsIw6My+Omb1DsNqCMLqdx+lmNj/neIf6SJ0lvv+ujrvlnt2qkbQ+xXf5d82sXstPVtPG/M3Mns05/neCkjaIYp8ESaMIHo0BTi3RHzipA7Km+z557xjrYL4J1ZRFOQ6Nv9NKPPMQBigAdinVpsS+6/XAGsB/CMsc5vr4cJyuoCol2Myep9iJzq4JDGE0KOG2MvEqeYW+t8TxZA215fICJW2t4Czjyeg8ID2Rf68YbdW8tF3EM3ErAHdKOkrS+pLU0QwtOA1IXnRfzgQfSDAxfsbMsmWcOC66pUz2N8ffdUs55ugEcwnmMh0hkf1NM3ssL4IFN/qvZOJnmV4i7SKKdbdU2nJ0qL5mUXCilXReqrlPpWQtJU/NMmXO81DsoOXxb4JpVTm5Ost9BAVlBeDvkoZUiA+ApAGSvqLg+OfV6EQmaReS6xlM6TJ5pMTxN1L/S3XcEyVsibzrIFcuXd0OmpnKbSzZLmXlGxLbwunR2cxHKfkeqEK+XIcqnYi3GDObS9EJ5HUKztA2r8eHCEn7KjizejE62knfl8RhWfq66/7+iHJ0Sb1LMT3vYJXtbLl7tn38XVXB4VbuRrFDv0Yq7T/j76mSfhedBVXVfuSQyH5rvKY8Si3/mFxDAXihzDXsn3MNaeryzqkVSasrOC37j4JjrIWpunNGjFavPlayhuxMM7u7Rjk728bklm9UxJN2P13GTYRR2UUU+77ZtM8TzKlrIalrb1jppYLuoPjuXYI6lEU5kvp8VJm6fF+MM5TSH/OOA8YTyueTZraEMzzH6UqqWSc44d8EZWsnWNxx35pgApfuLCYvu3S8ZFS47PrAVnqZk3nxdwnvj5KOIYxSJR2ExHnAh3F/WcKLvd7KXUnMbKGkAwlK69rA6XGbKelmwryRq0p8NSzHOYRRwAMlHWPRvTxhThDA+TlpVoy/5RZjTz5wiKBo1PNL3NtlOgyVqEZ2CPKvloqfpVz6JKxU2pJ0pL6WYBTFD1LV3KdSspZbJqhWmdLnKSmTmc2T9DZhJLDmMqySqwkOQs4nzHG9UtL/lBgRAYJHU+A6ii9rCB9k3qQ44jc6/g4jjDJnKbW28eKRaCu9/nESp11510muJeiJ7WAaSasQlKR1U4c/oOjopT+h7Skn35tVnq7aeFkOIyy9tQHBwuFE4H1J/wYuBi4xs5KdziySBhDm5aVHP+cT7mlSP1YkPPuLr7sr3h9dVe8ydKadLXfPklHcAkUZy5H24H0qYTrIZ4FvxG2BpHsJcxrPrqHjncjeViZOqTJIrqE/tV9DmkrvnFr6dFUhaWfCc5FeInNW6pxDCFYg9WpbkvJ5sZZEdWpjan2HJnViVoURzFco/WEjj2revfMlvUVYd7cddSqLciT1edm4VaJUfU4sHs6NAz2O063UssRCosBuF1/uWxM6VbdnlJyHCSZI2yksWbAVxfVCyyrBtSJpI8JLToRO8kaE+TKjzGxlM1uZ4DUVip3DbsHM7iN84TqYYDr1PEHZ2Re4Eri6A6MMNxLmYCxPeKknZbAloVN1QZm0jXI5Xw/T1a6UvVvrRRX0xKUBGi6TmV0AHE4wSfsE8DeVWBIlcgKhw/8WwXRrtJkNNbOVYruwWipud9aBusvVk9vBFL8kdMieJ8yvG2Vmw1PXvW3Z1IFq25IOtTlxxGZTgtL6B+AJQsd/T4LieXdUJqvlqzGvOcC3CP4wBpvZiqn7kihU7e5LF7w/Gv08VMqz3D1L+imXV7JGiNuUJKGZzTezvQjTAH5G0flUsv+0pM06fFVLUuo6k2t4oMprmFRHmTpMbGP/RHgObiQMbgwxs5GpOnx0Er1ep+1gunq0MV1FV7W7pfLt6rJI6vNeVdbnGSXyGRV/3ygR7jhdSi1KcGJmO4zwZTW9PvBiLMzXu4vw5edjqXivxE5GPfk84RquM7MjzOxxW3K+YDVfXbsEM5trZn82s0PNbB3CV/2TCS/hTxE69bXkZxTn/Camh1+Jv9eZWd4X6uQL+5gyWa+enIL2IwDJqMfgMmmr+QrYURLZ16wQL5G/1GhCOZOf5ItmR0eP6kGyZAdUd5+6S9aKdUfSYIqmTl0ql5n9gaBMQPB6eUn8IJfHfvH3CDO70MyyL9lGtQtdIVePbgejNVBijn2QmV2WY17fMPnSmNkCM7vCzL5uZhsS2odjCaNAHwN+VEN2yb0+0cx+bWYvpwOjErtCGVnq+f7ojuehq9rZZGpBVevw5mFmd5nZ98xsO4I56wGEkcYVCRZW1ZDIXs11ZkmuYXyZNqsnsh3hvTOToPDcambzMnHq/ewmPjEqvfcX08A2JqkTy6r8GuK1zkmvWNfiNS9hZtxNZdHpZzKS6CC1WkU6Tl2oWgk2sycpVvydKD/P99aceHUdBY4kSsEDeYEK81tLffFalIrXLaMjZvaCmX2fsKwOFBexr4XzCV/NPylpDGGkAJZ0iJVwf3KuMteZLJz+dMakJzETW50cYn5bVCV1x0hkHyYp1+mVpHUpjmLcnxeHEuUc5U8+0pRK2+VYMGtP5pbuUiZqcp+6S9bkPOMlrVYizk4UTfC6XC4z+w3B6yQERzUXSsprx8q2DQTvlo2gK+TqTDvYHaxA0Zqgp92PspjZa2b2c8LICtTWZle61ztQ/gNjVpbOvD+643noqnY2mS+8XrR66BRm9oGZXUJYixlgC1XnCyORfccy79JS9yS5huEEh4PdSdLX6Ug/J6k3T5vZnBJx6v3sJk4FR0mqtt1qVBvzAEGB60dYKmkJJK1FDQp9JKlro2MfJ4/tyTd/72xZVFNfkvr8+TJxqmF/Qp/n753Mx3E6RC0jwVBUbicSHsB5FCe/p7ktEw+6RgmeFX83KRH+A8KC3nnMTv0fWSJOh4hf4soxN/7WbGZqZq8QPEj2B/5M+JL9JqUbkcQMciOKXwfTso6mOKJwaSY4meu9VZxjkuUgapvnUisPAomnxu+XiDMl/s4grFGZR4ukvHt8MEH+RYT1PBtJcp8m5ZW1pN0pevbN3qeu4nrCczKQMBqWlak/wcwSgrOYJbxadwVmdhrww7h7AHBOTqe0ZNsQTVp/0HUSlqUr5OpMO9gdJMtFQf51rwIc0a0SLSnDwAofQzvSZpe71wMo4fG+i94f3fE8dFU7exPF+aFnlDMDl7RcZr9cWSblKMJ840pcRriG1Sh+fM6eO3d0Pg4iJMrdqeWU7ujQqJ5TUJK+Tkf6OUm9GR+tftoR30vlPtzWTCyr5F3+swrTXhIa0sZY8IycOKz8bok25LgOZJ3u+3wvGxjPUyrfzpZFNfVlWvzdUtKXysRb4plMEy00ppewYnScLqdWJThRZPcgOEK424rOmdLcTXDIsgdFc9lKnqE7wg3x99OSvp+Yo0haUdJphAW7cyfbW3CGkTx4Zb2adoA9Jd0p6atxtJYo11BJXyUojxAclXSExHwr8Yb5JyuxjICFZTiSpZHOU/BU2j/KswVB0VmOMMr/q0zy2wllVAAujl80k+v4OnA2Ra+idSeaf0+Ou3tJ+o2k5aMMy0v6NUEJAphspR1wDQaulbRxTDtQ0qEUl6o418xqcsLRBfyW4IhpCEHWLSEompI+D1wS491oZjeXyKOuRKuAZBmGIyX9IJkTGUeGLyZ8/V5E8T51C2Z2IvDTuPtl4PeZKEnbcLqkxVYQkrYidKpLmqF2MV0hV4fbwe7AzN6nqACcJ2nzKF8/SbsR3iuNnpu/EfCopG9LWjd1XwbG5y+Z91hLm53clxMk7ZVqd9cnLFGyNflOCLvi/dEdz0OXtLPx3XYERX8A10vaJnUNAyRtIekUwhzINI9KOknSVolCrMDWhLV1Ae7NMRfNk+O/FC2uzpT0pURBk7QJ4T1bbmT/CIJjtI2BWyV9PH4MSZ6FjSRNBp6jvst0JSsrfE5hSZpauJ0wp315gtXNKrBYUW8G/o+uaVuOJkzHmkDqfRjPvYKk/SX9OTnW4DZmCqFu7gZMUxhYQNKykk4iWBzMLp18SWLfZ0rcbVbwzD0y5juaUA93JdybbNrOlkVSX/ZQ/uAHFpbbTD5onSfpx+m4kpaLbd6VBKd+uajoKb+mqYGOUzeshkWFCU5DLLWdWCbunal4r5eJNzaJVybOREos5E5ohJPzLKI4v9KAcymz8Ddhjdkk7fuE0cQZwLdrKJMk/djUsb0z5TQnI1eytt6AWso/lf8AgnKa5LVxhfgrUjTbMcIX8Nmp/ZnAdiXS7kMwv07izgI+qlS+5e5ZB663NXX+hVHetEwnV7g3BxI6m0Yw8Z6fCrsTGJ6TttR1dba+zohhE3PCto7Xlsg2O96rZP8hYKVqZc3EmR7jTKqx7PsTHK4lMizI1OWFwDdKpK0oV4Vzz6jiun6eku2M1PG1CRYS6Tr/PsXncfdU2Nha5K6yDpSqP52Ra0o8Pi3nfB1uByvcg0mVrrWauIQVAuakZHw/tf82wUqlVNqq6i5lnq1K8Qjrcqbb7HlRrnQ7cy8wooayG0UYzUnSf0hoP5PnaFIJWer+/uhMvasi7860s1Xd2xj3y5k85xJ8WCxIl1cmzbupsAXxnn6YOvYmsGkNz9lwis61knqSnON9wkfZks8LYS53WqbEW3haJgPGlCjj3HtDmTYJWD9Vbh8RPA7PAG5LxZlI6XfWkRnZ3qXYB3iA4geK6R19Jktc0/6xfNPPwXup/RmZ+F3axpS7FoKlVLb9TerlL0rlX67cY/hvU/lm371HlpKpk2WxQoxjhPbv1XiebHkPI3hYz9aNWZlj51fRdhxea/3wzbd6bLWOBD8SH8KEW0tFzIR1xShwwhcJZiFPEBpmEb5eHmpmXymXEPgJwdTk4ZhuTNw6ax59M3AIQXl4hND4LENoWG4keOf8H6thuY00MV2y2Pm9ZlZqrdIk/psEU9rvEMzXPyKM7j5DmOu2kZnlrtNoZpcTOki3EF5A/QmmOodVUb51wcwmE76yXknoMAwnlOXfgY+b2fEVsriD8FK4lGJn4CmCSe1EC19OG46Z3UNwNHEG8DTBDHkB4Z4dC2xjSzq06WqZFprZoQSvtNcTXnLDCS/Gi4GtzSw7Ctud8h1D6CgAfFvSyfH484SPCn8ieJ7sT5D9z8BWZnZ9A8TtSrk60w52ORbW+9yOsOzPO4S6/QZwFkEB7eha4vXiCUIdP5PQsX+XYO00mzC95whgBzOrekTHgqnktsBUisubzSWUwc5mNq1E0rq/P7rpeejSdtbMzgfWI7yzHiO0jcsSyuUW4BiCMphmL4IzscSqaThB4XwYOIXw7nu4BhneJyguPyS00RAUtb8QyrfsGtVmdg3Ba28rYd7nPEJ/Yzah/H4IbGBh1LkuWDAv/gRhpHoWYUmdMZTw9ZGT/tcE/wvJqPAA4EmCk7jtKb+sUIexMG97A0L7npT1IsKzeg7wpUz8hrUxFqbofIpQD98nlNF9wJfM7DudyPebBNP7uwnPlAgjuZ+J96VUug6XhZm9RTBxv4zwkWhFin3jdLwPzGwfgpPKywgfV4YQ+pbPAhcR2tRv1HjZjtNtyMwaLYPTASQ9TVhCo8XMzqwUvy+isCg8wFpW2kW/4ziO00G8nXUcx3GWRmodCXZ6AHFex3iC6dlFDRbHcRzHcRzHcRxnqcGV4KUMSSsAp8Xd82oxz3Mcx3Ecx3Ecx+nruBK8lCDp55JeJMxraiLMjc1dYsNxHMdxHMdxHMfJx5XgpYcVCGstziU4KNq1u50kOY7jOI7jOI7jLO24YyzHcRzHcRzHcRynz+AjwY7jOI7jOI7jOE6fwZVgx3Ecx3Ecx3Ecp8/gSrDjOI7jOI7jOI7TZ3Al2HEcx3Ecx3Ecx+kzuBLsOI7jOI7jOI7j9BlcCXYcx3Ecx3Ecx3H6DK4EO47jOI7jOI7jOH0GV4Idx3Ecx3Ecx3GcPoMrwY7jOI7jOI7jOE6fwZVgx3Ecx3Ecx3Ecp8/gSrDjOI7jOI7jOI7TZ3Al2HEcx3EcpwSSLpT0hqRhjZbF6TySXpb0bA3xx0kySedkjv8pHl+9UlyndiTtEMvyoEbL4vROXAl2HMdxHMfJQdKWwMHAKWb2Qer42NhBN0l3S1KJ9Cbp5TrIMZzd68IAACAASURBVEPSjA6km5KSM2+rOU+ndvIU5gbIsK+kv0p6StK7kuZKelrSnyU15cRfRtIhki6JaeZIek/SPZK+JWlgTpr+kr4r6ZkY905JO5eQp0nSR5K+khduZrcD1wKnSBrS2et3nCwDGi2A4ziO4zhOD+UkYDYwtUycrYEvApd0i0Qd41/A9Jzj73azHEsj/wU2oLqyqiVud/N5oAm4D3gV+AgYD+wL7C9pkpn9MRV/N+BC4G3gZuByYBSwF/BLYB9JnzCzj1JpvgOcSlBeryI8F9dL2tzMnkgiSRoAnAfcYmbnlpH5ZELdbQFO7+iFO04ergQ7juM4juNkkLQu8HHgHDObWyLai8DKwEmSLjOzD7tNwNqYbmZTGi3E0khU8p6sd9wG8GUzm5c9KOljwN3A6ZIuMrOFMehl4ADg/9KKrqRjgduAnYGvAb9LZdcCXGNme8a4ZxHK46vA0al4xwPjgL0ryHwr8ALQIukMM7NqL9ZxKuHm0I7jOI7jOEvSDAj4S5k4LxFGidcCjqglc0mflPRPSW9Jmi/pOUmnSRqZijNRkgFjgDEZU+ZpNV9RZZmaJV0m6floLjtL0m2SDsyJ+4ykeZKWK5HX5Cjn1zPHt5J0uaQ343XPkPRbSSvn5JGYEa8ZTXAfiXLdGMMHSTpC0jWS/hvzmynpBkmfrHCtIyX9XlJbvI7HJP1v1rS9lnm+2biSBsT7l8xrfSl1/56Nce6VtFDSGiXyPC7G/1al85cjTwGOx+8HngVWAEamjt9nZpdkRnoxs1nAGXF3YkpOAWsA96TiPkWwpBiTircRMBk4zsz+W0FmIzx/44CdKl6k49SAK8GO4ziO4zhL8nFgIXBXhXg/IZi//kDSqGoylvRDgsnoNsDVwK8JisgxwO2SRsSoM4AfA7Pi9uPUdkUN11ItZxEUmX8RTF4vJSj4f5b0o0zcC4FBwP4l8joEmE/qI4KkvYHbgT2B6wkmrs8C/wvcK2nNEnn9DpgCPAz8CrgjHl8xyjkcuCHm93dgC+AaSZNK5DeIYOL7ceAi4GxgeeC3Mb96sYhwrx6J+2dQvH+/jsemEvrjh2UTR8XyMGAeobyT44dHxfjMzgoYldK1gTYze7vKZIlivCA5EBXWlwlln+Q9HhhBMBNHUn+CGfRdwO+rPNft8fcTVcZ3nKpwc2jHcRzHcZwUCp6gNweeSDvEysPMZkr6KXAaYYTr6HLxJe1CUILuBPY0s3dTYZOA82P4UWY2A5iSKHOdMGmeKCkv7bR4joT1zey5jLyDgOsISv5ZZvZaDLogynkomTnTkrYD1gUuTa4vKvbnExS+nczsjlT8HwCtwJkEBTnL5sDmOSOHbwFrmtkrmfOPJJTvaZIuNrP5mXSrA88D2yYm7JJ+DNwLHCnpL2n5OoqZLSLcv3HAJsDpZpZ1lHYx8HPgK5J+kjJHhjAvdx3gQjN7p7PyAEjaA9iW8CFgbeB/CErtEkp4Gb4cf6/NHD8TOFnSVcDTwBdi3sm836MJ5bBZDabN98ZfHwl26oqPBDuO4ziO47RnNaA/wYFQNfyGMGr7v5LWrhD3yPj71bQCDGBm04AHKZrP1oudgR/lbGMz538umzAqkL8HBgK7po6/SHC2tY2k9TLJDo2/F6SO7UMwt70oR8H8GWF+9ackrZYj/yl5prNmNi+rAMfj7xIU7hVIjUxmOC49h9vM3gJ+Gne/nJ+k/sT55hcQ6txnMsGJKflZmeOXEBxwZUfnq2GPmO44gpI6E/ismV1TTWJJxwC7EMye/5QJPg34fpTt60AbsIeZPRZHhX8MnGBmz0Tz9hclLYim6HkfPwDeJIyol7IScJwO4Uqw4ziO4ziL55+mtomNlqneSNpV0o2S3pG0KHWtYzNRl4+/VY2+RUXx+0ABOKVC9O0Io2P7KSxh1G6LeawoafmyudTGj81MOdv0JIKk6anymBM3i3NaE5PmrII6Lf4+mUo7iOAV+DXCCHLCx+LvzVnh4rzT2+Lu5jny35NzLJF7E4W1nJ+Pc3sTmU8tITPAh+SbuU+Pv0ssGdTFTAWMotKLpJUInpgfyX40MLN3zexJM3u91hOZ2bfNTMAywJYE0/IbonJbFkn7E8r1ZWC/zKg1ZrbQzE42s3FmNtzMtjGzm6NZ97kEc/YzYj6/BC4DPgk8A1yZ8zElGU1/l/BBw3HqhptDO47jOL0aSZ8jODnagqDczCcoN22EuXr3mdlZmTTTKI5m/dfMxnaXvE7XIGlDwvzbwVVET7xBVxM34RLgKIJyu62ZlZpLvDyh/1VpFG84YXma7iK9Fut84I+EecgLCWazhxBMaNP8H2E+bSF1bC/CiO/PM0rSsvG31Oh6cnxkTthrOceQtANwI2FQ5ybgSuA9wsjhxwimvlmZAd4oYY6bnGfZnLAuw8yelnQT8ElJY+KodzNh9D07Clyvc74P/EfSFwlld6qk683s4bz4Md6fgFeAXaIlQLV8kzD/vcnMFil4mH7MzL4d876P0B5/h+BxOssQoOy0BMepFVeCHcdxnF5L9NL6lczhgQQFYw1Cx2w/uqij6fQo9qWo1BrB2VJiYjszE/eN+Fv1aKyZWRxN+xdhjueOJaLOAvqZWVVOtLqRtHfih8wsMdtG0iEEJbgdZvaBpMdpP3qbZwoN4bohLCmVxyqZeO1OVSLNCYR7OsHMbksHSDqBoATnsZIk5SjCiWx5MnQ1UwmOur4aZT8MmMOSJsd1Jdbb6wgmzjsRRmvbIekgwv18maAAv1Bt/tHK4iTgJ2b2eDy8PuEDSiLDLEnPARvlpB9MUIKrPqfjVIMrwY7jOE6vRNLutFeAHyCYZ84CRgGbEuZKdtX5R5jZ7K7K36mZsan/r5hZuSWNXiXMRVzCPLMcZvZvSVcCe0n6fIlodwGflrSRmT1WZdYLaT/augSSljGz92oQN8uQMmHlnpMHaa8E7w7cb2aPZuI9EH8nklGQJQ0EdsjEq4ZxhFHd23LCyslcIDiHujNzfGIHZKiGZES8f5k4VxJGWZsJHpHXAc6LSxJ1NYnJ+IJsgKQvA+cQ5rzXOgIMwVLgGaJ5ejSNhiVH6AcTRvGzbBB/H6zxvI5TFp8T7DiO4/RW9kj9fw7Y2syON7NTzOy7ZrYHYYmVxSNckibF+YSHptJm12edko6b2sZJ+q6kJyTNJyzVQirvPRXWYH1F0oeSZkt6UNJJkkZnhc/M0ZwuabSkqTH9fIV1Wo9NdSrTaUdI+oWkl+I8yacU1hsdkHct5ZD0l1T8+3PCx2byPKCKPKel4s+okN+kVFi2zNdWWC7mQYX1Y9+SdJGkVbNpaO/saPXs+SWNknSqpBsInoOXA1ZQmD98RyzrrKK4XSqf4+Ox7xKUiWRu8GoxfL6kFSiusXqupNaY9zuSPpL0hqSbFOYHp/tobxNGL9uVi6R9Yvr3COuxJmvTnijpaopOuE6Q9K6k+2JY3tq+7daRlbSipDMlvU3xY9J2GbmgOJqeMIDiXGEkDZR0GOGZMmBSlOV6SfvFaN8hrCV7bZ6jqzLMIMyfbjeCqLA28W4V0p4iafGHhXhvfhB3z69BhmpIzNpLOneKpuNnE0bEz46Hc5dAUljjeP28dqNE/KGStikRtj3h/i4gLFuVDvsaYS7vc8DOtSrAkr5K+LDQbGYLYPFSSk8Auyp4YUfS+oQPGnkfhbaNv7fUcm7HqYSPBDuO4zi9lfSoy0jCeqfPpCPEeXFX1el85wETsgej0nAuMCkTNBDYLG5flfRZM8uOTCWsAdwPrJo6No7gVXcowetqcr5hBJPc9OjcusDJFDuUtfBLghdZgCZJW5tZ2lFRep3Yd4DLO3COjjKN9mU+GDiAIOfmOUvjlGNVggKbZSTBmdV2wP6S0ku1vAWsFP8fDJwc53f+AfhGJp8rogfimySdBhxLMMdPsyLBA/OuwA6xTswlzNncKhP3GHLMRwllMDlzrB9hnusWcTtEYd5yeq7tKxTNgTcnPCvZubF7EkYFm3POm/ARYdkfFNZNvjZH9mUJ675+QtJr8bxtQEuZfPM4g6Ds3iHpUsKHgK0J9+r/gFKj8S8THEM9KunvhFHJfaMcv67H8kgZbiLMFz9X0mXA+8BMM8uulfsHwr1bDXjAzO4ln/0J5tNnAYdXcf4RwF2SHiOMqL4CDCPUn4mEjxNHmtnzSQKFpZTOBERQQA/L+d72lpn9Nu+ECl6+TyN49s6O4v6M4GztDkk3E8p+IfCLnKx2J9SperXTjgO4Euw4juP0XtKjlssDT0l6BLiPYO54q5k9lElzL0E5+SLBcyoExe6kVJxSHeQJhBGOvxMc8ySjhsfSXgF+lGD6OJowOjaQ4Pn0SknjS5g/rk0YqZtKcNrUksr/aEknRQ+7AD+hvQL8SDzf+HhdNWFmd0q6h6BcQPBgW0oJ/pOZtRtR7GImEBSMO4C9CWuQQphzuDeho13pniblvQh4knBtrxEUquMITqKWJfSZPkYo+7/FNK9RVII3lNRkZg8AU4AvEeaeJ5wNIKk/S66Fu4hwf42gnECYH/orgqOgVsKHkPTSSRsRRhj/QpjDnCiaRpg/eRdhdHV7ghIzI5bB0Hh8MsFhUcL7qf+J8tsW89mFMDIO8GVJV5hZO0uHFFdHZR/gwpRc8wjOw+YRlgJaPR5fGbgb2MfMql2SKlyo2dWS9iKM4O5PGM28h6DYrU9pJXg+4UPDycCBhPbhOcISSb+rRYYa5PwuYcT1KII59nOEpafS8V6VdC2hfOrpp+BdQp3cmXAvVyDUuZcJH5J+Z2b3ZdKMJSjAkO+sCuApIFcJJsj/CnBiNsDMLlXwfv0d4H8Jz93XzOypdDwFD+mfBi7riCdsxymLmfnmm2+++eZbr9sISstdBKWg1PYksHdO2mmpODNK5D8pk9edwOBMnH6EuaVJnGfTcQgmuuk8jkqFTc+E7ZUK+1YmbJPUNc9KHX8OGJJKd2Im3ZRU2MRM2MRU2IGp4x8Ay8bj62XSbFrlvSlZvoTOdzrPSWXK/DJAMWwUQQlKwn5R6z2N8VYjKNDfIHiTNsKoaJL2pkz8x/POSfgYkRx/PiXn/2SuoTVTX25OhS0AVihRLrOANctcxwoEBeJw4GjCyPG/0nUjE396Jv+dUmHjCaNxSdg/U2FT0ulSxzfO5PeFzPlOTYW9DfRvdJvR6I1gvfJfwtzY4Y2Wp9Eb4ePVImCrRsviW+/bfE6w4ziO0yuxMAdtN4Kp8Msloq0HXCaplBfZWvi5LTkKuh7t17e8OBPnj7R3RrMD+bSZ2ZWp/acy4cko3XoE08f0+eam9s8tkX8l/koYFYQwknhw/J8eBb7XSiyv0oVMNTMDMLOZBPPkhLx5ryWRtJykK4CXCCbdv6M4YjsuFXX1TNJ0mR6QmjN7YOr4eYmcLOk1evH8UwtroqadRvWntAn7hZYzR1PSYAWv6K8B/yBYD/yCYJqaNuXOWz834QUz+3dKrmdo70RqyyWTLEF2akB6brnR3vR8FEUHSH2ZLxLmDU+zMFWjzyJpOKGOXGSlzcIdp8O4Euw4juP0WszsAzObYmZrEBTELxHM9N5IRRNhpKyzPJlzLLsMTrv1TqOinlbcSi2bMyOzn53rmrzPs2usZs1Lc9dbrYQFU+upqUNfj79p8+pzOpI3RZPLhLx1XUsxI7OfLpda+zjnEta4XWLiY4asfBcAH8b/qwC7SdqW4N0XwlzHtKOlsnUiZ79UncirbxDMvL9CeU/EUL6c80xP08eq+cBQ6xJQK9YYv1egwHFxnvhUgln6qQ0WqyewFuFD1HGNFsTpnficYMdxHKdPYGZPA08Df5R0LEGJSBxNjanDKT7IOZZdf7bdGqmSBtB+pDgbP+GjzL7lxgpz/9KslNkvtUZrNZxJmHs5GNhE0uEUR+/mEOZ7Vsui1P+sx+XxNeRTbbmURdJQ4LOpQ7cQ5kG+YGYLo9Ol/fLSmtlb0bnSvvHQwURPzZFrrL3H47w68VxmP02pOpFX36D96PyjhBHpJ83sI0k/I5iYViLP63D6WLae5ZGV+1Taf/DJ8lyZsN5Mf8Lc5I8I3pGPMbNSlit9BjN7hODPwHG6BFeCHcdxnF6JpEMJToYuMrNsp30+xdE7KC5hkpBWroZ2QoynCB3/RNHdX9JPUybRh9D+XXx7J84FQbGfTdEkej9JrVZ0mvWV/GSVicreRRQ9A5+RCr7UalsTOX0/VpS0jpk9J2kQYe5qdzOS9iOn/zCzZwGiA59dKqQ/h6IS/DmC87J0WJrsPf4y0ZtzNKU+NBW2kDCvvRbSH1VuicoEcXmnz+YnWYK1JE0ws1tj2vEEj8sJ1ZinZtfunW9mP89GkrQysF2eaXdfIFqDVLI+cBynzrgS7DiO4/RW1gJ+BPxS0u0Ej9BvEpZG+TTB0VDCPzNp0yMxK0qaRhilMeCPVqWnUjNbJOl0ip6IxwH3xrmnK9Ne4XmLTq5PGkctz6Fo3r0BYWmUfxCWSdq/ZOLq+BVFJXhw6nitptB3Z/Zvl/QvgvflcTnxu5o3CIp5Yk4+Oa7BaoQPFSuUShi5geDQaAzBI3TiFfpVgnOtNFcTnGltGPd/IGndeGw32s8ZnmZFT8vV8hTBKRWEpbeM8GFkP8KUgGq5WtJ5hI9FX6J9n/EPlRKb2SOSrgE+FQ/9UNKOBE/ecwlWGFsSvEffSvcureU4Th/HlWDHcRyntzOQ4Pl4Yonw+4DsCNVlwAkURwfTyup08udMluJUgjJ6SNzfmKKSkjCT4KW6GjPTSvyQsPxLskzSx+IGQQH7dCpu2iy5Imb2sKRbaD8y+oSZ1TqCfQVBWUuUstEU1yL+B2GJmG7DzBZIOomwfimEOa+J46ZXCEruJ8qkXyTpfIKn5DTT4khfOu5CSfsA11H8EJNnan0LcGQNl5HwE+DS+H9wKo/3KL92bppnCBYQ38oJu9DMrqhSlkOAayguk5Ssgew4jtNQ3DGW4ziO01v5JcE09dcEz7YvEOZRfkQY+buFsE7qDmb2XjphNCH9PGHEck5nhDCzRWb2JYIp6pWE0cGPoiwPE5TkjTugSJY63weE9UDPIChwHxKWZjqBsCZnmnc6cIpfZfZr9jhtZsk6rRcTPgDMJ4zUTwKO6IBMncbMTiM4/HqCcH/eBP4MbEPRM3Y5zqP9RwWjRNnE+embAccT6tgsgpfwt4AbCeXwCTOrue6Z2V8J9f4/hHv/DmHt6m0Jc4SroY2guJ5LcNT1IcHU/miC+Xa1srxNWKe4maD0v04o23cIlhV/i/nlzrd2HMfpKpI16xzHcRzH6SVIGpJZGik5fhRweurQtmaWNU2ulPd4goMxCMrR6mb2ZoeFdRzHcZxuxs2hHcdxHKf38WicB30HYX7zSII5eNqs+/ZqFWBJgwkjiSNo77jqYleAHcdxnKUNHwl2HMdxnF6GpNfIX+Ym4RFgDzOrxswXSWMJ5uRpZgKb+XIujuM4ztKGzwl2HMdxnN7HqYS5pa8A8whmy68C1wKHAVtWqwDn8DZhjulOrgA7juM4SyM+Euw4juM4juM4juP0GXwk2HEcx3Ecx3Ecx+kzuBLsOI7jOI7jOI7j9BlcCXYcx3Ecx3Ecx3H6DK4EO47jOI7jOI7jOH0GXyfYcRzHKUuhqVnAKGBFYKX4uyKwPDAI6E94nwxI/o+YN2f2vk/eNRJYELeFqd+PgPeBN4A3U9sbZ9qMed13ZY7jOI7j9EVcCXYcx+mjFJqaBwPrA2sTlNu0gpv+vwJBua2aeQMGPgxsWqtMh2vs+2QU48z+K8DTwEtn2gxf3sBxHMdxnJpxJdhxHKeXU2hqHgSsB2yU2damRuW2Gxget7UqxJtzuMY+AzyV2p4AHvfRZMdxHMdxyuFKsOM4Ti+h0NRcoKjsbkhR2R1Hz1N2O8tQYLO4pVkYleOHgIfj9tCZNuOlbpbPcRzHcZweiszcmsxxHGdppNDUPAKYAOwCTCQohD3i42ZhwUcPH/zorTWbQ3chbwG3ArfE7TE3p3Ycx3GcvokrwY7jOEsJhabmYcCOBKV3F2ALeugIbw9UgrO8CUwnKMTTz7QZTzRWHMdxHMdxugtXgh3HcXoohabmIcAOFJXeLYGBDRWqSpYCJTjLa7RXip9urDiO4ziO43QVrgQ7juP0IApNzVsAnyUovdsAhcZK1DGWQiU4yysEpfhG4O9n2oyZjRXHcRzHcZx64Uqw4zhOgyk0NW8IHAB8ERjfYHHqQi9QgtMsIIwQ/w24/Eyb8WaD5XEcx3EcpxO4Euw4jtMACk3N61BUfDdusDh1p5cpwWkWAv8G/jZx1/F/3f+mG1whdhzHcZylDFeCHcdxuolCU/MaBKV3f4JTq15LL1aCARgwoN/c43+4+3xJdwN/Ai5fdfLUDxotl+M4juM4lekRS2k4juP0VgpNzaOB/QiK7/aAGiuRUw+atlj9IUnbAp+M2wdtrS1XEBTiG1adPHVhQwV0HMdxHKckrgQ7juPUmUJTs4BPAUcCH6eHLmPkdJxtthubPTQMOChur7e1tpwP/HbVyVNf6WbRHMdxHMepgCvBjuM4dSKu43soQfldr8HiOF1EYVD/95YbNXSzMlFGA8cBx7S1tvwVOGPVyVPv7R7pHMdxHMephCvBjuM4nSTO9T0COAxYrsHiOF3MlluPeUTS9lVEHUBwfnZAW2vLHcAvgcvcVNpxHMdxGosrwY7jOB2k0NS8PfBtYB+8Pe0zbLXNmgM7kGz7uL3Y1tryG+DsVSdPnVVfyRzHcRzHqQbvtDmO49RAoal5AMHR1beBrRssjtPNDB4y8N0RIwZv3oks1gROA37U1toyDfjVqpOnPlsX4RzHcRzHqYp+jRbAcRxnaaDQ1Dyq0NR8PDADuAhXgPsk22w39lFJHRkJzjIc+CbwVFtry1VtrS271iFPx3Ecx3GqwEeCHcdxylBoah4OHAscTVBcnD7MFlutMbTOWfYDPgN8pq215V7ge6tOnnpLnc/hOI7jOE4KV4Idx3FyKDQ1DwS+DpwArNRgcZwewLDhhTeHDSuU8wrdWbYCbm5rbbmGoAw/0oXnchzHcZw+i5tDO47jpCg0NavQ1PxF4AngN7gC7ES233HtJyR1x5rPnwIebGttuaCttWXNbjif4ziO4/QpXAl2HMeJFJqadwXuAS4B1mmwOE4PY/Om1UZ24+n6AV8izBk+ra21xZfechzHcZw64Uqw4zh9nkJT8+aFpubrgJuALRstj9PzWHbZwa8OHjJwkwacejBwDPBcW2vLd9taWwY3QAbHcRzH6VW4Euw4Tp+l0NQ8ttDU/CfgfmD3Rsvj9Fx23HmdpyWpgSIsB5wKPN3W2jKprbXF39+O4ziO00H8Jeo4Tp8jLnd0BvAUcBDQSOXGWQrYeNNVV2y0DJE1gPMJc4b3bLQwjuM4jrM04kqw4zh9ikJT8xcITq++DRQaLI6zFLD8CsP+O2jQgA0bLUeGTYCr21pbLm9rbVm50cI4juM4ztKEK8GO4/QJCk3NqxSami8H/oJ7fHZqYMLO68xotAxl2Bt4vK21ZVKjBXEcx3GcpQVXgh3H6fUUmpq/DDxOUBgcpyY22GjlVRstQwWWA85va225xpdUchzHcZzKDGi0AI7jOF1Foal5DPAH3OmV00FWXmWZ5wYO7D++0XJUyR7Ao22tLccBU1edPNUaLZDjOI7j9ER8JNhxnF5HoalZhabmbwKP4gqw0wkm7Dzu5UbLUCPLAL8DbmlrbRnXaGEcx3EcpyfiSrDjOL2KQlPzusC/gN8AwxssjrOUM369lZZW8+KdgYfbWluOaWtt6d9oYRzHcRynJ+FKsOM4vYJCU3P/QlPzd4GHgAmNlsdZ+lljzZFPDhjQb61Gy9EJhgCnAbe3tbb0NO/WjuM4jtMwXAl2HGepp9DUvBFwF3AqMLjB4ji9hAk7j3u90TLUiW2AB9paWyb7qLDjOI7juBLsOM5STqGpuRm4F9iy0bI4vQpba53l12m0EHWkAJwI3NDW2uJLhDmO4zh9GleCHcdZKik0NQ8tNDWfD5xLMPt0nLqx9jrLP9q/f7/VGy1HF7ALcH9ba8t2jRbEcRzHcRqFK8GO4yx1FJqa1wfuASY1WBSnl7Ljzuu802gZupDVgH+1tbZ8s9GCOI7jOE4jcCXYcZylikJT80HAfcBGjZbF6aWIRWuOGbVeo8XoYgYCv2lrbflzW2vL0EYL4ziO4zjdiSvBjuMsFRSamgcWmpp/C/wJGNZoeZzey3rrr/Rwv34a3Wg5uokDgbvbWlvGN1oQx3Ecx+kuXAl2HKfHU2hqHg3cBPxvo2Vxej877rTOe42WoZvZGLivrbVl70YL4jiO4zjdgSvBjuP0aApNzVsRzJ997V+ny+nXTwtWXW3ZvmhqPwK4rK215RRfRslxHMfp7bgS7DhOj6XQ1DwJuBXojV56nR7IRhuv8qCkUY2Wo0EI+B5wvS+j5DiO4/RmXAl2HKfHUWhq7ldoav41cD4wqNHyOH2H7SesNb/RMvQAdiUso+RrbzuO4zi9EleCHcfpURSamgvApcARjZbF6Vv0799v/kqjl9mk0XL0EFYDbmlrbdmt0YI4juM4Tr1xJdhxnB5Doal5OHA18PlGy+L0PTZrWu1BSSMaLUcPYjjwz7bWFn8eHcdxnF6FK8GO4/QICk3NywM3Ax9vtCxO32TbHcYuarQMPZACcGlba8vXGi2I4ziO49QLV4Idx2k4habmNYDbgK0aLYvTNxk4sP+c5Zcftlmj5eih9APOamtt+X6jBXEcx3GceuBKsOM4DaXQ1LwecDuwfqNlcfouH9tqjYckDW20HD2cn7a1tpze1tqiRgviOI7jOJ3BlWDHcRpGoal5S8II8BqNlsXp22yz7RhfG7c6jgIuaGttGdBoQRzHcRyno7gS7DhOQyg0Ne9KmAO8QqNlcfo2gwYPmLXsyCFuCl09hwCXt7W2DGm0FD6/XgAAIABJREFUII7jOI7TEVwJdhyn2yk0Ne8D/BNYptGyOM7W2455VJKvR10bnwGua2ttWbbRgjiO4zhOrbgS7DhOt1Joav4K8FfAlQ6nR7Dl1msObrQMSykTgH+1tbas3GhBHMdxHKcWXAl2HKfbKDQ1HwmcA/j8S6dHMHRY4e3hwwe5KXTH2Qy41RVhx3EcZ2nClWDHcbqFQlPzIcAvGy2H46TZdvuxj0lyJ0+dYxzBNHpkowVxHMdxnGpwJdhxnC6n0NT8GeA8wJdWcXoUTVusMaLRMvQSNgWucmdZjuM4ztKAK8GO43QphabmCcClgI+2OT2KZUYMen3o0IGbNlqOXsSOwF99+STHcRynp+NKsOM4XUahqXkz4CrAR4ecHscOE9Z+SpK/B+vLp4Hz21pb3OrDcRzH6bH4y99xnC6h0NS8DnAt4EuoOD2STTdfbVSjZeilHAyc0WghHMdxHKcUrgQ7jlN3Ck3NKwPXA+4x1umRLDdq6MuDBw/cuNFy9GK+1dbaMrnRQjiO4zhOHq4EO45TVwpNzSOB64C1Gy2L45Rix53Xea7RMvQBTmxrbTm80UI4juM4ThZXgh3HqRuFpuYhhDnA7mzI6dFstPHKbqXQPfyurbXlC40WwnEcx3HSuBLsOE5dKDQ1DyB4gd6x0bI4TjlWGj38hUJhwHqNlqOP0A/4Y1try+6NFqQeSJokyVLb2FTYtNTxGY3Mc2lB0gBJP5D0mKS5qWud3mjZGo2ksZl6MamGtDNS6aZ1nZSOs/TiSrDjOJ2m0NQs4FzgM42WxXEqsePO4/7baBn6GAXgsrbWlm26+8Q5ioRJek3SoBLxH8qJP7Z7pe5TnAC0AhsCgxssi+M4fQhfy89xnHrwfeBLjRbCcaph/Q1WWqPRMvRBhgFXtLW2NK06eeprDZZlNHAQcF76oKSPU3kqx73Asan9mfUVrc9xSOr/i8A5wFzgpcaI4zhOX8GVYMdxOkWhqfkTwE8aLYfjVMOqqy37zIAB/cc3Wo4+ysrApW2tLbuuOnnqggbLchQZJRj4TqVEZvYY8FiXSNQ3GZv6f6GZndgoQboCSSPMbHaj5XAcZ0ncHNpxnA5TaGpeE7gIb0ucGniK9zmL/y6xPc57i+Pcy7tcwEtcxCvMYM4SeVzF6zxM7X3LCRPXaeuU8E5nmQD8rIHnXxh/N5b0ieSgpA2BT2biLEG5+buVkLSVpGslzZb0nqSbJO1c6wVIGiVpTkqGb+XEmZIKf1fSkCryTV/XlDL5WSZsenour6TRkqZKekXSfEnPSDpWkrJpAKWympw9v6SJks6RdJ+ktjhveJ6kFyVdJmn3jCxfSeWxUNJqOdf5cCrO/2XCNpb0B0lPxzKeK+lZSedK2qxCOZukYZJOlvS8pI+AX8d4m0v6vaQ7Jb0k6YNYNm2S/inpi5XuT8xnF0k3p+rQdZK2riZtJp81JJ0Wy+K9KMvzks6W5P4SnD6Bd1wdx+kQhabmAvBXYIVGy+IsnXyG0ezNyou3tRgKwIvM5VFmsyOj2IDh3MxbzEvpJS8whw9YwEYsU/M5x41fca26XYDTUY5qa23Zr0HnvjItR+r/0RQVsivqfdKocN9GULSXAYYDuwI3AzWVhZnNBP6YOvT1nGhppeoiM5tbk8AdZw3gfuBwYFXCfPBxhA8fP+xAfp8BvgJsAaxCmDc8KJ5nH+A6Scen4l8Ci7+m9QMOTGcmaWNgk9Shc1JhX4uyfxUYDwyJ51sHaAbuk9RSQd5rgOOAtWhvbbkj0AJsC6wODCWUzSrAp4BLJJ1ZIe/9gBuBXSjWod2Bf6c/6FRC0p4Ea4ZjCGUxPMqyFnAY8KCkz1Wbn+MsrbgS7DhOR/kVUPMXaMdJWIkCoxm0eBtCfwBeYR7jGMY6DKOJZRlGf15nPgALMe7iHbZjOfq3G0SqzJi1Rj3ev3+/Net+IU5HOK+ttWWDBpz3EeCG+H8PSRtIWgk4OB57Cri6nieUNBi4kKBoABhwMXAi8BCwZwey/VXq/waSJqTOtzmwfir8HLqPtYFRwFTgdML83oSjJQ2M/6fSfm41hPtybNyuj8c+AG4Ffkcor+OBU4D7Uul+LGlVADP7APhLKuxg2nNQ6v9LhDXtkbR9lCmR7y3gDODnwBvx2ADgd5LKrYAwAbgH+GlM+3Q8Pj8ePyuGHR9/p6fSfl3SlmXy3hN4mFAOFxHqEYSPAhfEelYWSWMIH6+TL4gvAKcCPwYejMcGA3+WtHal/BxnacaVYMdxaqbQ1Hwo4Uu/49SdRRgDUq+nAfRjUfz/MLMZwQDGxFHjWpiw8zpv1klEp/MMJ3iMrn04v/P8Iv6KMBr8TYIiAfBLispFvdiLMB864UQzO9DMfghsBzxRa4Zm9jhFZR7ajwanR4EfMLP7a82/k+xvZt8ws+8QlL2EEUTl3Mz+YmY/z6S7w8x+Hrc7YrwfATsD5wPPAHOAt2k/Wj8Q2C21n1b6N5W0CUA0xz4gFXaemSVNy3co9okXAhPM7GgzO5YwipvMYRdLKu9pLgO2M7PJZnasmZ0Ur+NsM9sG+A1hFPYD4B3CB5f0fI9Plcn7CWBbM/uhmR1EUIYTVgE+WyZtwhGwuPF8DdjczI4zsymEUerEIdlg4Mgq8nOcpRZ3jOU4Tk0Umpo3I3wxd5xOcTGvMI9FjGAAmzKCDePgxAoU+A+z2IjhzGYBM/mQ5RnIHBbyELPZq50+UTU2dq3l163rBTidZX2Cc6puNY02s+skPQZsRPBO/EEMehu4gPZKZD3YKrN/QUqW+ZIuIYzE1cqvgMQMdl9J3zKzt2kvf3eOAgO0mVna5PypTPhytWQmaTfgbIKpbjlWT/6Y2d2SHqFo9nww8D2CMjsmHltEe8do6dHdO83syVR+z0i6DZgYD+1QRo6TUop1+jo2J9z3St7HVy8TdomZzU/tX0B7E/MtgUsr5D8h9X9lYFZqqnaWciPejrPU4yPBjuNUTaGpeSThS3dFJyuOU4qh9GcrlmUXVmAPVmIlBnErMxc7uhrHMJZlABfTxtW8wRaMZAQDuZt3GM8wlltssVg949dd8ZF+/bRKva/F6TT7trW2VPTK3AWcHn8HA8vH/2d20dzZkZn91yvsV8s/CaOjEEayD5W0DUWFcS7w5w7mndWMctdVzmFGZn9+Zr/qfmc0cb6SygowLCnfuan/B0rqR3tT6OvN7MXU/qjU/7wlvNLHyinyT2YPRKdkV1NZAYby5Vyp3lTzgWFU5SiLWbGGuI6z1OEjwY7jVEWhqVn/z959h7dVnm0Avx9JluVtJ3GGszeZxAnZwwmEsMsoUNqyamj7uesrUPq1hbZAA3TQFlra0EINYZRSWlr2aiGskJAQZ5KQkJ0423vK1nm/P96jWJa3I/nVuH/X5QuNc47uIytGz3kX9GQsHCdEp2QwkjA44DrKECTBB4V1KMckpMEJwQXoh0o0wgVBEpw4hnrsQy2uQg6q0Ih3cALH4EU23FiI3kjp4H9n8xaMLAv3eVG3/bx4acGanNuXvduDr/kUgHug1wwGAC+AB8P0WsGfvX4AdgXd7zKllBKR30F3sQWAr0FPGOX3T6VUeVcOiabiN/hCZ2eXFWto5ZjddSH0+tJ+twL4i1KqVESS0dSC35onoMe6JkK3ri5G8x4HwS3kJQD62rdb62oS+FhpWy9qj0kONh96kjC/30KPaz5m/w6PonMFZ/DnJPh+Z/7GBa5rvRftf+Yr23mOKOqxJZiIOutH0F9KiEJuBJJRDwuVaFo+Ng2uk5NlrUQpzkAmEuHEByhBJhLwZQxEBhLwQdvfSQEAIvANHJxpYhIm6hwX9PrBOR1uGSJ2t9I/BDz0tFKqtRbAUFgTdP86/w0RcQO46hSO/RgAf6E7Fs3nauhqV+jAImqGf0kje0ztRd0NeAqCVx4oVEr5/7G3+57ZM2j/K+ChZWhqBT0K4IWgXT4IuD1bRE5OLCYio9G8a3Dgtp0RfB5PKqWO2gXwmeh8i+tV9ufF77qg54M/Z615P+B2PwAvB4zDPvljb7e6k7mIohJbgomoQ+7c/LMB3GU6B8Wnz1ANLyyMQyoAoBj1uBiZSIAD45GKFzroTTpufP8NDodM7Yms1G39oAvhRTm3LwtuTQyX30HPFg3omXvD5QXorqv+lrsfi8goADuhLyx2+wKNUqpKRArRtNyTf4bgHUqpd7p4uNUAzrVv5wFYJSLF0K2o7jb3Cp/g8cSviMjL0K3SX2pl+2CPoKlYDuzBtFwpFfwZ+zWAS6Bbwp0A3hORx6HHDl+Lpu/LCk0Tq3VW8Hk8JSJPQ09mdX0XjjMOwGoReRF62abASb4Oo2Vh35rfQy/V5F/+abWI/AP6s5gAvZzVAugeBV9B04zRRDGHRTARtcudm98XejkG9hyhsNmNGnjgQFrQ/5YaYWE1SpGH3nAEDFNstHtZNnSit+XcBSNqOtyIIsFc6Blvf9ATL2Z3FQ75msCtvE6tiFwPPb7VDV1o+Ys4Bb1MzsJTeInfA/hfNP8b/Zc2tm3Pr6DXnfUfx78EXg2At6HXp+1JL0AXYVPs+zPtH0DPFv2VDvZ/C7rbefAQnhbvjVLqAxH5JvSFERd06+3NQZv5ANyklOpSt32l1Mci8gqalsI6DU0Tob0JXdy2NyGW3wroixNTgh73AviKUqquE1n2iMgV0Et0pdk/Hb2PRDGJX2qJqCMPomV3LqJuewPHsB7l2Ida7EUN3sJx7EQNpiEDEjQfz3pUoA/cGBQwRDEHiViDMhxALdagDAPamUvG6RRv/wHpE8N2MhRq3yteWjDLdIhQU0q9Bt3C9gaAKujxrO9CL4mzvJ1dO3Ps3WjeCtjYnWMqpd6CXmZnDfSEVmXQXYqn21l7lN1aexZ0i+4x6GLvU+ixwTd2Yn+FlgXve0qp4JZZ//bLAEyz99kJoA76fdgN3e18ulLq963t2wmXQ68bfBB63PQeAPdCv9++Th5jOfTn5V3oz1AVdBGdZ3++OkUp9TKA8dDjktdBj/1tsLN9BD3r+GJ0f1I1oqgg+m8EEVFL7tz8S6FngybqEndjw8arN7/X6myoq1GK3ahBNXxQALKQgElIwxi7u7NfFRrxLA7hMvRHRsCM0JVoxAocPzkx1iL0QWobHZtOzx245uLLJgcvUUORbTuAKTm3LwvHTM0xSUTuhp63AQD+rZS61GQeIqJIx+7QRNQqd25+FoA/ms5BsWcmsjCzE6t5pMKFrzSb7FZLgwsXdXKt4DnzRvTU+FIKnTEA7kbL7qgUQESGQS8fNBrAtwKeesBEHiKiaMLu0ETUlt+g9aUiiKKCy+Wo7ZOd0pm1OSny/G/x0oL5pkNEuOuhx73+CUC6/dizSqkVpgIREUULFsFE1II7N/8cdG3WSqKIkztt8AYRSe14S4pADgCPFi8tSOlwS/JBjzG9B3omYyIi6gCLYCJqxp2bnwbgz6ZzEJ2qmXOGmY5Ap2YkdGFHrVBK3aGUEqWUSyk1XCl1W2dmCCYiIhbBRNTSzwEMMR2C6FS4E52VWVlJp5vOQafsW8VLCzixGRERhRSLYCI6yZ2bvwBAgekcRKfqjBlDN4lIUsdbUoRzAHikeGkBJ/IkIqKQYRFMRAAAd25+EvR6jNLRtkSRbvrMIQkdb0VRYjKA75kOQUREsYNFMBH53QW91AZRVPMkJZSlp3ummM5BIfWT4qUFI02HICKi2MAimIjgzs2fDuAm0zmIQmHWnGGbRYQtwbElCcBDpkMQEVFsYBFMFOfcufkO6NmgnaazEIXC1DMGc1md2LS4eGnBF02HICKi6McimIi+DIBdRykmpKYmHktJcU82nYPC5u7ipQVu0yGIiCi6sQgmimPu3PxEAD8znYMoVObMH75VRNirIXYNB2ewJyKiU8QimCi+fQvAUNMhiELl9NxBmaYzUNjdXry0IN10CCIiil4sgonilDs3PxPAj0znIAqVjAzPIY/HNcl0Dgq7PgC+bzoEERFFLxbBRPHrBwB6mQ5BFCrz8kZuFxGucx0fbipeWjDAdAgiIopOLIKJ4pA7N38QgO+YzkEUShMn52SbzkA9JhnAHaZDEBFRdGIRTBSf7oRed5MoJvTuk7I3MdE13nQO6lH5xUsLxpoOQURE0YdFMFGccefmTwBwnekcRKE0P2/kHtMZqMe5ANxrOgQREUUfFsFE8edeAFxChmLKuAn9c0xnICMuLV5aMNt0CCIiii4sgoniiDs3fz6Ai0znIAql/gPSP0tIcI42nYOM+YXpAEREFF1YBBPFl1+aDkAUavMXjjxoOgMZNb94aQEv7hERUaexCCaKE+7c/EsBzDKdgyjURo/pO9R0BjLu3uKlBRzmQUREncIimCh+3GY6AFGoDR6Suc3lcgwznYOMmwDgMtMhiIgoOrAIJooD9ljgaaZzEIXa/LxRR0xnoIhxk+kAREQUHVgEE8UHfjmkWKSGj+w90nQIihizi5cWzDAdgoiIIh+LYKIY587NHw7gYtM5iEJtxMg+W5xOxyDTOSiifNd0ACIiinwsgoli33fAf+sUg+bnjSwxnYEizuXFSwsGmg5BRESRjV+MiWKYOzc/DUC+6RxEISewBg/NOs10DIo4CQC+aToEERFFNhbBRLHtBgDppkMQhdppp/Xb6HBIX9M5KCJ9rXhpQZLpEEREFLlYBBPFKHduvgPAt03nIAqHuQtGVJrOQBGrN4BrTIcgIqLIxSKYKHZdDGCE6RBEoeZwSGPOwIwJpnNQRPtf0wGIiChysQgmil2cJZVi0oSJA9aLSC/TOSiijS9eWrDEdAgiIopMLIKJYpA7N38qgAWmcxCFw5z5w+tNZ6CowAuBRETUKhbBRLHpJtMBiMLB6XTU9+2XNsl0DooK5xYvLRhrOgQREUUel+kARBRa7tz8AQC+YDoHUTicnjtwvYjMNJ0jFF7cvBP/XL8dm4qPoaLei5F9MvE/c0/HJZNHn9zm+U2f4cVNO/Hx/iM4WlWD31y6EF+Y2nxlqCOV1fjff76FogNHMW1wP9x/2Znom5Z88vndJ8pxwUP/xH++dSVyMlJ77PwigECPDf6G6SBERBRZ2BJMFHuuhV4rkyjmzJ473DKdIVT+vHIjUtwJ+Ol5c/Dol8/DnOED8c1n/4vCVZtObvPyll3YX1aJxWOHtHmcO15ZqY931RI0Wgp3vrqy2fN3vfYhvjpncrwVwH7XFi8tSO54MyIiiidsCSaKPV80HYAoHBISnNW9eiefbjpHqCz/8rnoldK0nO28EQNxpKIaf/5gI/Jn6R7fD115NhwOQXV9A/768bZWj/PeroN48przMWVQX6QlunHdk6+efO7dnQew5dBx/PHKxeE9mciVAuAiAM+YDkJERJGDLcFEMcSdm38agJgpEogCTZs+eIOIxEyrXmAB7Dcxpw+OV9eevO9wSIfHafD54EnQ17STElzw+nwAAJ9l4Y5XPsBt58xCUkJcX/Pm8BAiImqGRTBRbLnKdACicJkxe1jMV3Jr9x3GmL5ZXdpnUk42ln+0GWW19Xjsoy04fWBfAMATaz5BuicRF08aFY6o0eS84qUF6aZDEBFR5GARTBRb2OJBMSnR4yrPyPBMMZ0jnN7beQCvb9uD62ZM6NJ+PzlnNl7ZshsT7nkUr2/djZ+cMxtltfX4zdtrcdf5c8OUNqp4AFxiOgQREUWOmL+qThQv3Ln5UwCc1uGGRFFoxqyhm0UkZiu6/aUV+Naz/8U5pw1rMftzRyYPzMZH37sa+0srMSQrDW6XEz9++X2cPXYYJg/MxitbduHuN1ah2tuAL00bh+8vnhGms4hoVwF43HQIIiKKDGwJJood7ApNMeuMGUM8pjOES2lNHa5+/BUMzEzF7y8/q1vHSHQ5MSo7E26XEzuOluK5DTvwf4tn4FhVDW7619u4/7JFeK3gcjy3YQfe/HRviM8gKiwuXlrQ23QIIiKKDCyCe4CILBQRFfCzMMyv5xKR20Rki4jUBrzuinC+bjQQkWFBv4vru7DvnoD9Hgtfym5jV2iKSckp7hOpqYkxOeFbrbcB1z35Khp8Fh6/+nwku099dbM7Xl2Jb8ybgr5pyVi3/whG9M7E9KED0D89BedPGIGVuw6GIHnUSQBwmekQREQUGU6pCBaRy0TkJRE5JCJeEakUkX0iskpEHhaRr7eyz2MBhcSeU3l9atOPASwFMB56LBTFOHdu/iwAw0znIAqH2XOHfyIiMTd8p9Fn4WvPvIndJ8rxxLXno09qy9miu+rNT/diT0k5bpwz+eRjtQ2NJ2/XeBugTvlVohZ7yxAREYBTGBMsIo8AuCHo4QQAqQAGA5gJ4AoAf+p2OuquawJu7wPwCIBaAPvNxKEewC93FLNypw6KyZl9f/TSe3hr+z7cdf5clNXW4+P9R04+N3FAHyS6nNh+tATbj5aivlEve7Sx+BhS3AnonZKE2cNzmh2vwefDXa+uxI/PmY1ElxMAkDuoH/aXVmDZ++sxKDMNz2/6DA9cdmbPnWRkWVi8tKB/zu3LDpsOQkREZnWrCBaRJWheABcBeB1AOYBeACYDyDvldG2/frpSqiJcx48BwwJuP66U+pmpIOHA339z7tx8B/QFJ6KYk57uOZyUnDDJdI5weOczfV3yJ6980OK5VTd/CYOz0vHi5p34zdsfn3z8sdVb8NjqLZg9bAD+ccPFzfYpXLUZAzJSce744Scf65uWjN9ctgj3vLEKVfUNuHb6BCwZNyw8JxT5/H8rf286CBERmdXdluBzA27vBDBDKdUYuIGIpAJYFHD/egCPBh1nqIgE9sy6Uyl1RyvbjoYey/MVACMAfAhgYcCxzwdwI3TrczaAOgC7ALwC4AGl1JGAY8EeG+sv0t+BHkt5B4DPAegD3Xr6ZwD3KaVU0L7pAH4K4Er7tfbaWe8D0BB8LmiHiDxjHwcAipRSU4OeHwZgd8BDX1JKPd3O8QLPy+92Ebk9MJM9JvlqAFMA5ADIAiAAjgJYC+AhpdQbAce9Abo1GQAsAEOUUs0GlYnIRgD+L6rPKaU+H/DcRADfgf6dDbJf6yD0e/87pdSGoGPdAf0e+6UCuB369zQYwFMArheRKQC+BiDXPm4v6M/0CQDrASxXSj3T1vsV8HqLoLuQn2FnWwngx0qpjzraN+g4g+3zPAfAcABu+zz/C/1Z+rQrx+uCBdC/R6KYM3fBiO0i0t90jnBYfcvVHW5zy5nTccuZ0zt1vK/PPR1fn9ty6PTFk0ZxreAmV4FFMBFR3OvumGBnwO1M6C/8zSilqpRSL3bz+MEKAfwCevkXt/9BEXGIyKMAXgZwKXQhkAAgDcDpAH4IYLOIzG7n2IMBrAPwP/b+bgCjAPwSwE8CNxSRFOjC7WbooisRwBgA9wL4RzfO6/6A27kiErxuRWAX11IA/+rGa7TmQuiW/GkABkCPG06Efi8uBfC6iPwwYPu/Aai0bzsAfCnwYHaRG9hS80jAc1+Dfn+/Cn0xI8l+vZEA8gGsFZGCDvK+CuAH0J+zwAs38wAUAJgF/ftIhv79DQBwHoC/ichDHRz7CgD/gb5gkwZdcC8B8K6InN3BvifZF2K2APge9HuRamcZDn2BZr2IhGtSFnaFppg16fQczuhLoTS7eGnBYNMhiIjIrO62BK8LuN0bwKcisgm6FbEIwHvBrXsA1gC4Fbo17wz7sVIA9wRss7KN15sPYCuAF6BbIv2zh9wK4PqA7TYDeB5APwDXQRfEfQA8LyKjlVLlrRx7BHTL8TLocbMFAce/WUTuUUr5W3jvgm499dtkv95odGNmXqXUhyLyEQB/8ft1AIGtj4HFzZNKqboODrkMwEsAfhXw2JsA/K26/ve3GsB7ADYCKAFQAyADwGI0/W7uFJHlSqlipVS13Wp9o/3c1UGv8eWA2/uhu8ZDRObYmfwXW44DeAKAD8C1APpCfwb/ICKblFLvt3Fe86Hflzehi/VS+/F6+/Ei+9hV0MXnXDT1FPi6iDyilFrbxrHPh241fhG6MP8idGtwIoDlIjKio/ddRIYCeBa6CAd06/3foT9XF0N/ZjwAnhKRCUqpXe0dryvcuflOAJ/vcEOiKJTVK/mAx5MwwXQOiikC3QPr16aDEBGROd0tgp+CLhZn2vcFehzwyekoReRTAD9QSv0bAJRSWwBssVsN/YVWhVLqvk683ioAiwKLERFxQLe6+e0EMN2/jYishG5BBnS35XwAv23j+FcppZ6399uHphbadOjW5032zKQ3BuyzC8BMpVStvd8O6C67XfUA9PsJAFeJyM1KqXIRGQvdmu33SMtdm/N3/RWRwAJ1ZfB7rJT6qd3leCr0DNJZABoB/BtNv5sEAGdBF63+1/ef/2QRmaSU2iQiAl04+hUqpSz79i1oKoB9AOYrpbbZGf8M4BPoz6BAX9Boqwh+DsAVAcf1n8fDAB4WkQnQn70+0F3SX4a+sOAvSs+DvkDTmq0AZiml6u1cn6GpB8AA6C7yf29jX79vB7zWYQBT/GOWReReADugW9k90N2lv9vB8briDOjzJoo58/JG7oTu5UEUSueARTARUVzrVndoe/zvWQDuBHCgjc3GAnhORC7qZrZA97XSGjcWzb/8Px20zRPQhZ3f3DaOXewvgG3B4zazAl4vcIbSp/0FsO0vbRy/I88CKLZvJ0O3sgLNW4HXKKU2dvP4LYjIWdAXDdYCeBy6EP8V9LJKgU5++VRKrYZu+fbz55wHYKh920LThQf/c34f+gtg+3g70Lzobev3AwD3BBfA9nlMEZEN0D0A/grgd9Bjs3+FpqK02Xm04m/+Ati2POj5M9Cx+QG3+wMo9y8DBt0aHNj1bh5Cq9NdtomizYSJ/WNyLDAZN7d4aYG7482IiChWdXudYKVUtVLqDqXUYOgC8Vro5ZCOBmwm0ONnT9W2Vh7rFXS/2ZIHdqF+vJ3t/fYE3a8Puu9/jzKDHj/U3ut3lt3Velm5qd0UAAAgAElEQVTAQ/61lQO7V3fYCtxZIpID3YW7xTjuViQG3Q8s9L9kt8YHdoV+Qym1L+B+4Hve2vsT+FhWK8/7tfj9i0gSdIvv5JabtxB8HoGOdHC/vVx+bX22WpPdhW07g0UwxaS+/VJ3u92usaZzUExKRtMwJCIiikPdXic4kFJqO4DtAJ4QkVuhixb/bLVD29yx86pbeawk6H6zFgO7+3JgS3Hw9n4NQfdVq1sBZUH3+7b3+l30EIDboLvLThKR/wEwzn6uBnpiqlC5EEBKwP1bAfxFKVUqIslo/b32ewJ6grJE6NbVxWi+NE9wsV6Cpveptfcn8LHSVp4HoC+4tPLwfDSfEfm3AH4O4JhSSonIUXSu4OzXwf3g33trAj9bewE82M62le081yXu3PwU6EnBiGLO/LxR+9C5i3VE3bEIbQ/BISKiGNetlmARuU5EviEiwa2jgG5J9QbcPxH0fGDRmYzu+xTNW3qvEhFPwP1r0LzIb7kQY9dsAxC4Nu0VIpIQcP8GdJNS6jh0d16/wLHLfw/xmrjB40cLlVL+ArTdWYaVUiVoPkP1MjS1gh6FnrgsUOB7PltETvPfEZHRaN41uKu/n+DzeFIpddQugM9E51tcrxKRwG5x1wU9v6YTxwj8ItUPwMtKqfuCf+ztVncyV2fkIWC2dKJYMnZcX44FpnBaaDoAERGZ092W4OHQ67jeLyIfQM/Oewx6iZkLAAwL2PaVoH0DxxBni8hj0EvLKABPBK/p2xallCUiv0HT7NKjAKwRkX9DtzAGFjPH0XKN4i5RSvlE5BE0de8eB2CViLwEvUzSqS5T8wD05F2AbhH2C1lXaFvwmOdXRORl6Bmuv9TK9sEeQdO5jgh4fHnALNp+vwZwCXS3eCeA90Tkceixw9ei6fOn0PVJSoLP4ykReRp6Mqvru3CccQBWi0jg7NB+h9GysG/N79E0q7jHPt4/oMddJ0B/NhdAjw3+CvRs1KHArtAUkwYOytjucjnHmM5BMW1O8dKCxJzblwUPgSIiojhwqt2hE6Cvpi5s4/m10BMVBXoOwI/RtNZwYLG6Ai3HZLbnF9BFzDX2/Yn2T6ASAJcopTrTrbUjPwFwJpqWSZpq/wB6fOoFAdu2mMipPUqpjSLyNnQXLb+tSqlTbcEO9gJ0EeY/h5lomuX7UegirT1vQc+MPSLo8RYTgymlPhCRb0JPWOXvnh48RtwH4Cal1LudPQH72B+LyCvQSxwBehbvO+3bb0J/LjrTkrQCukV1StDjXgBf6cSyVFBK7RGRKwA8DX0hKA0dv4+hcFYPvAZRj5u/cNQh6IuLROHigR5O8o7pIERE1PO6OzHW/QAugy5uPoReF7UauqvzUQBvA/gWgLlKqWZjIJVSm6DXNV0NPd6125RSllLqWuhlbJ6Hnqyqwc6yEbpInhiqQtIem5oH3V35IHSh9Bl0Uf/NoM3bHOPajgeC7nd3xuk22a21Z0G36B6DPodPoccG39jOrv79VSu53lNKBbfM+rdfBmCavc9O6NmS66E/M49BL2v1++6cC4DLoS+yHIT+ve8BcC/058HXyWMsh15C6V3odYaroIvoPKXUa50NopR6GXq5qZ9Dr6NdaWc6CL2W8QPQY6ifausYXeHOze+Flhd8iGLCyFF9gi+yEYXDoo43ISKiWCS6pqHOEpGkoKWR/I/fBOA3AQ/NspcV6sqxR0NPMAbo4nSQUupYt8NSzHLn5vsv/BBFJHdjw8arN7/Xmdnbmxk2vNeWa/NnTghHJqIg7+Tcvmyh6RBERNTzQjI7dJzZbI+DXgk9vjkTujt4YLfuDzpbANuTec2CXoP4ewFPPc0CmNoxv+NNiKLPvLyRxzveiigkZhUvLfDk3L6sw2EvREQUW1gEd10K9Bjka9p4fhOAK7twvP7Q3ccDlQC4vevRKI6wCKZYpIYN782xwNRTEgHMgZ7rgoiI4kh3xwTHs18A+A/0WM866G7LhwC8Bj2m9gylVHE3j30CeuKqBUqpAx1tTPHJnZufjKYJ2Yhixugx2ZscDhlgOgfFFY4LJiKKQ2wJ7iKl1G/RfB3fUz3eHuglhIg6axb0zOxEMWVe3shQzOJP1BULTQcgIqKex5Zgougzz3QAolATgW/QoMzxpnNQ3JlZvLQgyXQIIiLqWSyCiaJP8JrGRFFv3IT+G8QhfUznoLiTAL2uPBERxREWwUTRh8vHUMyZO3/EKa0bT3QK+DeViCjOsAgmiiLu3PxEACNN5yAKJadTvP0HpE8ynYPiFotgIqI4w4mxiKLLWABO0yF6gvJWo3Hbc4DVCNekqyHOBKiGGlhHt8CqPAh4KwGnG5I6AM6cMyAJyU37NtTAt/c9qJpjkJRsOIfMb/58fQUat78I19hLIO4UE6dHASZOztkgItNN56C4xbHoRERxhi3BRNElbr6s+YrXAo7mk2CrmhOwyvfCkTUCzuGL4cyZDlVzHI3bX4byNTTte/AjAIBz2CJAKfgOrml+7IMfwZE9gQVwhJgzb0RDx1sRhQ1bgomI4gyLYKLoEhdf1qyqw1CVB+Do2/x0JaUvXOMug7PfZDjSBsCRNQKu4WcBDVVQ5XtObqcqi+HImQpH+kA4BkyDqjzYdOzKYqjaEjj6Tuyp06F2uFyO2j7ZKZNN56C4Nrx4aUFyx5sREVGsYBFMFF1iviVYKQu+A6vh6DcF4vQ0e05ciRBp/mdLPBmAwwXVWBdwEAsierSHOJyAspqOfXC17j7t4GiQSJA7bfAGEUk1nYPimoAzRBMRxRUWwUTRJeZbgq3jnwLKB0d2576TqtoSwGqEJGaefEySe8M6vg2qsR7W8W2Q5D4njy1ONxxZI8KSnbpu1pxhpiMQAXHwt5WIiJqwCCaKEu7cfDeAUaZzhJNqrIN1eB2cA6e3aPFtdXul4Du4GkhMh6QPPPm4M2c6rPI9aNz8V1jl+/TY4cZ6WEfWwzlwZjhPgbrAneiszMxK4rrXFAlYBBMRxRH2BySKHjE/M7R1aB0kORuO9MGd3H4tVPUxOEed16xoluQ+cI2/EvBWAe5UiMMJ34FVkPTBkOQ+sMr26Im3rEY4eo+Bc8DUcJ0StWP6jKEbRWSu6RxEYBFMRBRX2BJMFD1i+kuaqi2FVbIDjv5ToBrr9Y9q1E/6vFBWY7Ptfce3wjq6Gc4h8+BIyW5xPHE4IZ4MiMMJVVcGq3QnnAOmQjXUwrfvfTiHzIdr7Odgle6EVb6/J06RgkyfOdRtOgORLab/vhIRUXMsgomiR0xPiqXqKwBlwbfjZTRu/qvuynxgFQCg8ZO/w2ffBgCrbA+sA6vhyDmjU+N7fQc/gqPvJEhCMlTNUUhiOhyp/SAJyXBkDIWqOhS286LWJSUllKalJ7IrNEWKocVLC7hmGhFRnGB3aKLoEdMtFZLaD86R5zZ7TFUehHV0E5wjzoa40wAAVuUh+Pa+C0ef0+DsO6nD41rl+6HqK+AcflbTcQNbla1GgDNF97iZc4ZtEZF5pnMQ2fwzRK81HYSIiMKP3/yIokdMtwSLywNJG9DsMctbpZ9L6QdxJkDVlcG3+y0gMQOSNRxW9dHm+yemN9tfKQu+4o/gzJmul0oCIMnZgLcKvqObIO5UWKW74Rw6P8xnR8GmnjGYrW4UaSaARTARUVxgEUwUPYaaDmCaqj4GWF6grgS+Ha80e06yRsEVVMxaxz6BJKTAkdn01klCMpxD5sFX/DFgNcDRZywcGUN6JD9pqamJx1JS3JNN5yAKMrDjTYiIKBawCCaKAu7c/BQASaZz9DRH79Fw9B7d5v2OOPtOBPpObHncrBFcK9igOfOHbxWRBaZzEAVpOcMeERHFJE6MRRQd+OWMYsbpuYOyTGcgakVf0wGIiKhnsAgmig4sgikmZGQmFXs8rpbN80Tm8e8sEVGcYBFMFB345YxiwrwFI3aIiJjOQdQK/p0lIooTLIKJogO/nFFMmDg5h11OKVLxs0lEFCdYBBNFBxbBFPV690nZm5joGmc6B1Eb+pgOQEREPYNFMFF0YAsFRb35eSP3mM5A1A538dKCDNMhiIgo/FgEE0UHtgRT1Bs3oX+O6QxEHeDfWiKiOMAimCg68IsZRbX+A9I/S0hwdn6RZyIz2OuGiCgOsAgmig4sgimqzV848qDpDESdwL+1RERxgEUwUXTgFzOKaqPH9B1qOgNRJ/BvLRFRHGARTBQd+MWMotbgoVnbXC7HMNM5iDqB3aGJiOIAi2CiCOfOzfcASDWdg6i75ueNPGI6A1En8YIjEVEcYBFMFPm4ZAdFMzV8RO9RpkMQdRIvOBIRxQEWwUSRT0wHIOquEaP6bHY6HQNN5yDqJP69JSKKAyyCiYgobOYvGFlqOgMRERFRIBbBREQUHgJr8NCs00zHICIiIgrEIpiIiMLitNP6bXQ4hLPtEhERUURhEUxERGExd8GIStMZiIiIiIKxCCYiopATEZUzMGOC6RxEREREwVymAxBRh5TpAERdldI7qzzlC18tlZpKWJVlDquiNMGqKE22KktTraryDFVT3QtQvBBLREREPY5FMBERhZov7/KLBr1Tl1m85LRR81rbQCllAeoEfL4y1eCtVHU1taqmqsGqqlBWZanoornEY1WWpVmV5RmqtqoXlHL29IlQ3OESSUREcYBFMBERhVSfAf1W9uqXPf+NHSc8i0b2qktwOjzB24iIA5DecDl6iysBSEoBsrLbPKYumlECX2OZavBWqfraGlVT5bWqKiy7aHZbFSUeq6LMbmmu6gVl8f9xRERE1AK/IBARUSjVLL78wjEAYCnkPLf56IovnN5/4akeVBfN6AVXQq+TRXNmnza3V0opAKXw+cpUo7dS1dXWqNqqBquq3GdVltktzaUeq7I01aosz1A1lb1gWQmnmpOIiIgiH4tgIiIKmSGjR6xJSU/N899fvb98yoXjsstS3M7MnswhIgIgCy5XlrhcgCcZyOzd7j5KqXJYvlLV4K1Q9bW1qqbaa1VX+KzKUodVXuq0Kks9VoU9prm6shcsn7tnzoaIiIhCiUUwERGFyom8zy3JDXos88mi4hVfnzl4oYlAXSEiGXC6MsRpF80ZnSqay1RDgy6aa6vqddFcLlZFicuqKPVYFaUpqqo8w6qu7AVfY2IPnQoRERG1g0UwERGFxLhpk7e4PYkLgh//9FjNrJKahuJeyQk5JnKFS/OiOQnI6NXu9kqpSli+EtXYUIn6uhqrtrpeVVdYVkUprIpSl1VZmmhVlKVYVWUZVlVFL/gaW4ylJiIiolPHIpgo8vlMByDqiDgc+2eevWBWG097Ctce3PW9BcNiqgjuKhFJg9OVJk4XkJgER3pWu9srpapgWaVobKhQ9bXVVm21V1VXNlpVZWJVlLqs8pJEq7I02aosT7eqK3qhsSG5h04lllmmAxARUfixCCaKfGXQawVz6Q6KWGcsnLPP6XQObuv54or6OfvKancMyUwa3ZO5opmIpMLpTIXTCUn0dKZoroFllaCxoUJ56+yiuaLBqiwPaGkuTbEqy9Kt6oosNHhTeuhUokm56QBERBR+LIKJIpy3qLDRnZtfCqD9vpZEhrgSXNsmzZo6p4PNHI+uLS776eKRPZIpHolIMpzO5JNFc1omgIFtbq+UqoWyStDYUK7q62usuuo6VV3psyrLYFWUOq2KErdVWZZiVZalWdUVveCtT+25szGmxHQAIiIKPxbBRNHhGFgEU4Saf+HZ1fZszO0qr2ucvvlw1fqJ/VOn9EQuap+IJEGcA+F2DhS3B460DKDtpZqhlKrTRXNjufLW1ajamjqrpqLRqixXumguTbQqSpKtqvI0q6oiC9669J47m5ApNR2AiIjCj0UwUXQ4BmCs6RBEwTwpyetGjB8zrbPbP7X+UMK957JHdDQSEQ/EmQO3M0fciUBqBpwY0Ob2Sql6KFWKxoYy5a2vVnU1dVZNZaNVWeYvmt1WRWmyVVWWrqrKM1V9XUYPnk5b2BJMRBQHWAQTRYdjpgMQtUKd9fkLkrqyQ32jNeH93aUfzhueNTtcoSgyiEgiRPrDndhfF83pcKJ/m9srpbxQqgS+xgrlratUdTV1VnVlo1VVHlg0J1mVZWmquiJL1dWEY+1pFsFERHGARTBRdGARTBEno3fWh/0H53Q0FriF5z85OmD20MxGp0P4/yA6SUTcEOkPh7u/JLiBlHQ4e7dbNDfYRXO58tZX2S3NDUoXzQ6fv6W5sixNVZVn2kVzR9322R2aiCgO8AsIUXRgEUyRxnv2lRe1ORt0e3wKw17eduzdz43v22JNYaLOEpEEiPSDw91PF81pcPbu1+b2SqlGKFUKX2OZavBWqbqaWrtohlVRKlZFqbvxyIHjPXgKRERkCItgoujAIpgiSv8hA1dl9MrqdhH7zq7SceeM6VOd6HJwmR7qESLigkg2HO5sSXADyalw9uobvBmLYCKiOOAwHYCIOuWo6QBEASrOvOz8CadyAAVkP7Ph8JpQBSIKgeokj6fKdAgiIgo/FsFE0YEtwRQxRk4YW5SUktz7VI+z/lDltIq6Rn62KVIcNh2AiIh6BotgoujAQoEigogcmXv+WdNDdLi05euKPwnRsYhOFYtgIqI4wSKYKDqwCKaIMGn2tO0J7oTkUB1vd0ntnCOV9XtDdTyiU8AimIgoTrAIJooOnKyFjHM4nbun5c3u8pJIHUgoXHuwOMTHJOqO/aYDEBFRz2ARTBQFvEWFXgBlpnNQfJu1JO+Iw+Fwhvq4x6obZu08UcNu0WTaDtMBiIioZ7AIJooeu0wHoPjlTnRvGjd10qwwHV4e+7i4PkzHJuqs7aYDEBFRz2ARTBQ9tpgOQPFr4SXnqXAev9rry/34YMXacL4GUQfYEkxEFCdYBBNFDxbBZERKetpHg0cNmxzu1/n7hsPpllJWuF+HqBV14JhgIqK4wSKYKHpwzCSZ4Dv7igtPeU3gzmiw1Ji3Piv5sCdeiyjIziSPhxdgiIjiBItgoujBlmDqcb37Z3/Yu3/fkT31eq9tPz60wWdxfDD1NHaFJiKKIyyCiaLHbgA1pkNQXKldfPlFPVYAA4ClMOjfW46u6snXJAKLYCKiuMIimChKeIsKFYBtpnNQ/Bg0cthHqRlpA3r6dT/cVz65tsFX3tOvS3GNM0MTEcURFsFE0YVdoqmnlC68+Jwphl4766miQ0WGXpviE1uCiYjiCItgoujCIph6xNjciRsTkzwZpl7/k6PVM0trGw6Zen2KOyyCiYjiCItgoujCGaIp7MQhB2YvyZtlOEbSo2sPfmY4A8WHI0keT7HpEERE1HNYBBNFF7YEU9hNWzB7r9PlSjSd40B5/ZwD5XU7TeegmLfGdAAiIupZLIKJogtniKawcrlcn06ec8Zs0zlszsI1B0+YDkExj0UwEVGcYRFMFEU4QzSF29wLzqoUkYj5f0NZXeOMrUerNprOQTHtI9MBiIioZ0XMFx0i6jR2iaaw8CQnFY2aeNoZpnMEe2LdITGdgWIaW4KJiOIMi2Ci6MNWCwoHdebnzzc+Drg1dY3WpJV7y1aZzkExaVeSx8Mu90REcYZFMFH0edt0AIo96b0yVw0YMmi86Rxt+deWo/0spXymc1DM4UVFIqI4xCKYKMp4iwq3ADhmOgfFlIazr7gox3SI9vgsNfzVT4+vNJ2DYg6LYCKiOMQimCg6rTAdgGJHv0E5H2b26TXUdI6OvPVZyRhvo8XZ0SmUWAQTEcUhFsFE0WmF6QAUMyrP/Pz540yH6AwF9Pv7psMsWihUGgEUmQ5BREQ9j0UwUXTiuGAKieHjRq9LTk3JNp2js9YdrJxaWd/IiYwoFDYkeTzsWUBEFIdYBBNFIW9R4VYAh03noCgncmz+BYunmY7RRemPryvebDoExYQ3TQcgIiIzWAQTRa93TAeg6DZxRu7WhER3qukcXbXzRO3sY1Xe/aZzUNR73XQAIiIyg0UwUfRil2jqNofTsWf6mXPnmM7RTe7CtQf3mQ5BUa0KAGcbJyKKUyyCiaIXi2DqtpmLFxxyOBwu0zm660iVd86ukpqtpnNQ1FqR5PF4TYcgIiIzWAQTRSlvUeF2AMWmc1D0SXC7t4w/4/TZpnOcInlsbXGt6RAUtd4wHYCIiMxhEUwU3VaYDkDRJ+/icxpMZwiFKq9v6vriio9N56CoxPHARERxjEUwUXRbYToARZfktNQ1Q8eMmGI6R6j8bcPhFKWUMp2DosqeJI9nu+kQRERkDotgoujGccHUFdbiyy/MNB0ilLw+ddqKXaWc4Ii6gl2hiYjiHItgoijmLSr8DMAnpnNQdOjVt8+H2Tn9RpvOEWovbzs2pNFSUTfJ0c6dO/Gtb30LM2fMQGpKCs5ZsqTV7TZv3ozLLrsM/fv1Q9/sbMyfNw/r1q07+fynn36KBfPno3+/frj2mmtQVVXVbP/3338fI0eMaPF4HGNXaCKiOMcimCj6PWM6AEWFusVXXDjcdIhwsBQGv/DJ0Q9N5+iqTz75BK+/9hpGjRqF0aNbvzaxYcMGnLloETIzMvD4E0/gyaeewvkXXIC62qY5wb721a9i5MiReOLJJ7Ft2zb88pe/PPmcZVm49dZbcdfPfobU1KhbEjocGgH813QIIiIySziUiii6uXPzxwD41HQOimwDRwx559wvXppnOkcYnbj7nFEJSQnOdNNBOsuyLDgc+lr0l774RZw4cQKvv9G8p27eggUYPnw4Hlu+vNVjVFVVoW92Nvbu24fs7Gz849lncf/99+P9Dz4AABQWFuKxRx/FO+++CxEJ7wlFh9eTPJ5zTYcgIiKz2BJMFOXspZLWm85BEa1s4SXnnW46RJj1fnr94XUdbxY5/AVwW7Zu3Yo1a9agoKCgzW28Xt0LPCkpSf83ORkNDXry74qKCtx111247777WAA3+ZvpAEREZB6LYKLYwC921KYxp4/f4EnyxNSEWK3ZfKRqRlltwxHTOUJlzZo1AIDSsjLMnDEDaampmDB+PB577LGT2/Tq1QvDhg3DsmXLUFJSgsLCQuROnQoA+Pm99+LMRYswY+ZME/EjUT2Af5kOQURE5rEIJooNLIKpVSJSPPvcRfFSBSU/9nFxzCx9c+SIrue/euON+MIXvoCXXn4ZZy9Zgm8UFOC11147ud1v778fv/zFLzBo4EDs2L4dt/3oR9i5cyeWL1+Ou372M1PxI9FrSR5PuekQRERkHotgohjgLSrcC2CV6RwUeabMn7HL5XJ5TOfoKfvK6uYcqqjfbTpHKFiWBQC4/vrrcfMttyAvLw/3338/8vLycN+vfnVyu3POOQd79+3Dho0bUbR+PQYPGYL/+7//w7e+/W0MGjQIDz30EMaMHo0xo0fjT3/6k6nTiQS8WEhERABYBBPFEn7Bo2acLueO3Hkz55jO0cOcf1lzMCa6RGdlZQEAFuQ1n88sb+FCbNu2rdljycnJGD16NJxOJ9566y1s2rgR3/3ud7Fx40b87K678OJLL+HFl17CnXfcgU2bNvXYOUSQGgAvmg5BRESRgUUwUex4FoBlOgRFjrnnnVkmInH3d76ktmHWtmPVUV/pnXbaaa0+rpRqc1KtxsZGfP/WW3H33XcjKSkJ7737LvLy8jB27FiMHTsWCxcuxPvvvRfO2JHqxSSPp9p0CCIiigxx9+WIKFZ5iwqLAcTlt1tqKTHJs3705PHTTecw5Yl1xVG//t+sWbOQlZWFFW+/3ezxFW+/jUmTJrW6z8MPP4zMzExcfsUVJx+rCVhTuLqmBnG6NCJ7yhAR0Uku0wGIKKT+BiCW14KlTjrzsvMTTGcwqbbBmrxqX9lHs4ZkzjCdpS01NTV43Z7gqri4GJWVlfjXc88BAM4591wkJyfjhz/8IW677TZkZGZi2rRp+Pe//433338fbwStJwwApaWluPeee/D8Cy+cfGzuvHm47bbbsNxeZ/idFSvws/ibLKsCwKumQxARUeSQOL0iTBST3Ln5fQAcAi9wxbW0zIxVV37z+lmmc5jmcsjOn583ephDxGk6S2v27t2LcW10ed66bRuGDh0KAPjdAw9g2bJlKC4uxpgxY3Db7bfjkksuabHPLTffjOqaGjz00EPNHv/Dgw/ivl//GgDw/VtvRcE3vhHiM4l4y5M8nutNhyAiosjBIpgoxrhz818DcI7pHGRM42Vfu3p/Vnbv4aaDRIKzR/d+77yxfeabzkFG5SV5PO+aDkFERJGDY4KJYs9fTQcgc7IH9v+QBXCT/+w4Mcrrs2o73pJi1GYWwEREFIxFMFHs+TuAEtMhyIjqsz5/wVjTISKJAgb8c9OR1aZzkDHLTAcgIqLIwyKYKMZ4iwrrAPzFdA7qeUPHjlybkpba13SOSLPmQEVutddXajoH9bhKAE+YDkFERJGHRTBRbPojuGZwvDm+4KIlU02HiFAZj68r3mg6BPW4J5M8nkrTIYiIKPKwCCaKQd6iwj0AXjadg3rOhOlTPnEnutNM54hUO47XzDpe7T1gOgf1qD+aDkBERJGJRTBR7HrQdADqGQ6HY++Ms+bNNp0jwiUWrj2413QI6jHvJXk8m02HICKiyMQimCh2vQngU9MhKPymnznvoMPpTDCdI9IdrvTO3ltay38T8YGtwERE1CYWwUQxyltUqAD8znQOCi+XO+GTCTOmsBW4cxyPrj1YZToEhd0RAP80HYKIiCIXi2Ci2PYYgBOmQ1D45F20pF5ExHSOaFFR75u28VBlkekcFFaPJHk8DaZDEBFR5GIRTBTDvEWFNWC3wJiVlJry8bDTRuWazhFtnl5/KFEppUznoLCoBfB70yGIiCiysQgmin0PAqgzHYJCzlp8+QWppkNEo3qfGv/u7tIPTeegsPhzksdzxHQIIiKKbCyCiWKct6jwKIDHTeeg0MrM7v1h34EDxprOEa1e2npsoM9S7DIbW+oB/NJ0CCIiinwsgoniw68BWKZDUMjUn33FhfQ3haYAACAASURBVENNh4hmPoWhL249ttJ0DgqpwiSPp9h0CCIiinwsgonigLeocDuAF0znoNDIGTZ4VXpW5iDTOaLde7tLJ9Q1+CpN56CQaADwc9MhiIgoOrAIJoofPwVbg2NB+aJLz5tkOkQsUECfv204/LHpHBQSjyd5PPtMhyAioujAIpgoTniLCjcCeMp0Djo1oyaNW+9JTuplOkes2Hi4anpFXeMx0znolPgA3Gs6BBERRQ8WwUTx5cfQk8dQFBKRQ3PPWzTDdI4Yk/Loxwe3mg5Bp+SvSR7PTtMhiIgoerAIJooj3qLCvdBLJlEUOn3O9J2uhIQk0zlizd7SujmHK+v3mM5B3WIBuNt0CCIiii4sgonizz0AykyHoK5xOp07cxfMnG06R4xy/WXNwUOmQ1C3PJPk8XxqOgQREUUXFsFEccZbVFgCzqIadWafu/CEw+Fwms4Rq07UNMzecbx6i+kc1CX1AH5kOgQREUUfFsFE8ekBAAdMh6DOcXsSN46dMpFjgcNs+cfFjaYzUJf8Nsnj2WM6BBERRR8WwURxyFtUWAe9ZBJFgTMvPV9MZ4gHNQ3W6Wv2l68xnYM65Qj00A4iIqIuYxFMFL+WA2D3zwiXmpG+euCIIVwXuIf8Y9ORTEsprqcd+W5P8ngqTYcgIqLoxCKYKE55iwp9AH5gOge1y3f2FRdmmw4RTxosNfo/O06sNJ2D2rUeQKHpEEREFL1YBBPFMW9R4UsA3jWdg1rXZ0C/lb36ZY8wnSPevLHjxIgGn1VnOge16eYkj4et9URE1G0sgono/0wHoFbVLL78wjGmQ8QjSyHnuc1HV5nOQa16Psnjedt0CCIiim4sgoninLeocBWAZ0znoOaGjB6xJiU9tZ/pHPFq9f7yKdVeH9fTjixeAN8zHYKIiKIfi2AiAoD/BVBiOgSddCLvc0tyTYeIc5lPFhWvNx2CmnkwyeP5zHQIIiKKfiyCiQjeosIjAG4ynYO0cdMmb3F7EtNN54h3nx6rmVVS01BsOgcB0Oua32E6BBERxQYWwUQEAPAWFT4O4FXTOeKdOBz7Z569YJbpHAQA8BSuPbjLdAgCAHyTSyIREVGosAgmokBfB1BhOkQ8O2Ph7P1Op9NtOgdpxRX1c/aX1e0wnSPO/SPJ43nBdAgiIoodLIKJ6CRvUeF+AN83nSNeuRJc2ybNmjbbdA5qxlG49iAnyDKnDMC3TYcgIqLYwiKYiIL9GcAK0yHi0fwLz64WETGdg5orr2ucvvlwFSfJMuN7SR7PYdMhiIgotrAIJqJmvEWFCsCNAGpMZ4knnpTkdSPGj5lmOge17qn1hxJMZ4hDryd5PH8xHaK7RGSPiCj757Fu7H9HwP4qDBHDQkSyReTPIrJPRBoCzuEO09lME5HrA3+nIjKsk/sNC9rv+rAGpU4REZeI3CYiW0SkNuD3s8J0NtNO5TN7qn87O4tFMBG14C0q3AngdtM54og66/MXJJkOQW2rb7QmvL+79EPTOeJIOfTFuFPSyhcxJSJfbWW7x3qy4BSRFTH8hflZAF8FMBiAy3AWonD6MYClAMYD8BjOQl3EP05E1JYHAFwJgDMVh1lG76wP+w/OmWM6R2vKD+3D+heW4+iOTSjZ9xn6j8vFxXe2bJw7sXcHVv/1dzi8tQhKWcgcOBwLvnobskeOBwCUHtyNtx/8McoO7sHg3LlY+D8/RUJS8sn9iz/5GP+5/wf44gPPN3s8kjz/ydEBs4dmNjodwv93ht/NSR7PgTAd+04ReUopFe7eLncDyLBvbw7za0UEERkCIC/gofcBvATAB2ClkVBE4XNNwO19AB4BUAtgv5k41BX8HzkRtcpbVGi5c/PzARQBSDSdJ4Z5z77yosGmQ7Sl5MBO7Ct6H/1GT4KvsaHVbY7v3obnf5KPYdMXYvFNvwAAHNu5BY3e+pPbvP2HnyC9/2BM/8I38OETv8W6fz2CmV/6DgBAWRZWPvYrzPzydyK2AAYAn8Kwl7cde/dz4/suMJ0lxr2a5PEUhvH4AwDcAuBnYXwNKKUeDufxe5qIpCmlOlqmaljQ/TuUUv8NU6QeZ8/ZkKKUqjKdJV5E+Hs+LOD240qpsP5N6Wkikq6UitkVQ9gdmoja5C0q3Iowf1GMd/2HDFyV0SsrYovgYdPycM1Dr2PJLfeh16CRrW7z7sN3Y+i0BTjrO/dgSO5cDMmdi2mXfw0DxuUCABpqa3B0xybMvf5WDJ4yB1MvuxEHNq46uf/Wt/4Fh9OFMQsu7JFzOhXv7CodV99oVZvOEcOOArihB17nVhHp25UdRGSJiDwrIvtFpF5EKkTkIxH5noi0uHrT2rg2/zhfNG8tzevM2Dl7/OEtIvKJ/fqHReQhEUlvY/txIrJMRLaJSLU9ZvFTEfmtiAxsZfvALuF7RKSPiPxRRA6ISCP0hYP23h8F4J2gh/8TcMyF9nb5IvI3exzlURHxikiViGwVkT+JyLig4z4RcIxPW3nd7KCxx98Oev58EXlORA7ar1UhIutF5B4R6dfK8Zp1VReRoSLypIgcgW7Rvtze7hIReVxENti/i3oRqRGRnfb2M9t7v5peTr5uH6PWfj8eFZGcTuwbfKCZdp5d9rGqRWSjiNwlIr26eKzg96Cf/Vk6aJ/nDhG51S5QW9s/LO95B5kD/w3dEfRcm+Pru3Ou/n0ABJ7/7cGvLyILReQREVkrIsX276VO9Hj550RkSVCWGwKO4ZPW/51uDNjmn0HPTRQ9Hn+7/VmsFZHPROQvInJ6K8dq9r6ISIqI3Gt/hhoA/M7eborovwUfiv77V22/N8Ui8oqIfKGj3499nEUi8pb9eagUkddFZEZn9g06zmAR+ZX9XlTaWXaJyMMiMrazx2FLMBF15BcALgFwhukgMajizMvOn2A6RHvE0f610pL9O3F0xybMue57bW7jb0F2ufWQKVeiB1ZjIwDAW1OFNX/7I879/m/RxvepiKKA7Gc2HF5x7bSchaazxCALwNVJHs+hML7GIeiW4DQAPwXwzY52sL/8/gl6nGsgN4Dp9s+1IrJYKXU0tHGbeRHAuQH3+0Gv7T4GwJmBG4rIDQD+aGcMNMb+uU5ELlJKfdDGa6UAeA/AaSHIHewbAIInAUywX+s0O9u5SqkV9nOPALjavj1GRKYrpdYE7PsFNH2frQPwJACIiAPAXwBc38prnW7/fFVEPqeUamu8fw6A1dDvdbCrAXy+lcdH2D9fFJFrlVJPtXFsQBcZgVf/PHbes0RktlLqYDv7niQiPwFwB5oXZQAwyf65TkSWKKVaXETohMEA1kG/F36jAPwSQDKAOwNyhPs9D7dOn2snXYjWL+oNtn8uFZEfKaXutR//G4DfQv99cgD4EoBf+XcSkYnQv0+/RwKe+xqAB6Hf60Aj7Z9rReQ7Sqll7eR9FcD8Vh6fB6CglccH2D/nicgipdT/tHPsK6D/fgV+qVgCfRHwIqXUm+3se5KInA/9PqUFPTUceh6Jq0Xky0qp5zo6FotgImqXt6iw0Z2bfzmAjwH0Np0nloycMLYoKSU5r+MtI9fRzzYBAOqrK/Ds965Eyf6dSMsegNxLb8C4sy4FAHjSMpDWdyA2vfY0xi++HFv/809kj9BjhT/+x58xaPJM9Bsz2dg5dNX6Q5XTLqlrPJbucWWbzhJj7k3yeDr1RegUPAbgKugvTF8TkfuVUjs62OcWNC+AXwXwIYBsANdCj/udBF18LWmxd3NvAKiC/kI5wn5sF4DAL6ZrgneynQvgXwA+AfBlNHXFXCQiM5VSqwHdIgi91J3/y+YmAM9DF0hXQX8hzgLwLxEZrZQqb+W1+tg//4Ue15sFoKOC7Fb72IFfhB8CsNO+7f/vMehxwp8BKAXQAKA/gEuhC4NE6C/zEwFAKfWOiGyHLt4BXXwGvkdfDrj9T6VUaUCe6wOe2wz9PvQDcB10sdAHwPPtvA+j7f/+G3po0EAAJ+zHygD8B/r3UQpdgPcBcAF0Me8A8ICI/FMpVdfKsQFdJL0EXXgtQlMBMhjA7wFc1sZ+J4nI5WhenH0A4E3oCxnXQL+3Q6B/35OUUr6OjhlkBPS5LYMe71oAwD+R480ico9Syj9WJtzvebh19lyXQf/efhWw75vQ/76BpvHv1dAXkzYCKIFedSMDwGI0NSzcKSLLlVLFSqlqEXkGTZMCXh30GoGf9f0AXgcAEZljZ/L/mz8O4AnoVvRrAfSFrvn+ICKblFLvt3H+8wF8ZJ9LIvTnGgDq7ceL7GNXAUgFMBfAQnubr4vII0qptW0c+3wA66Ev5o0E8EXov0mJAJaLyIh2/p3APs+h0BPv+Xve7Abwd+jf2cUApkBfSHpKRCYopXa1dzwWwUTUIW9R4V53bv6XAbwCDqMICRE5Mvf8s6abznGqasr0d5O3H/wxTr/4OvQdORG7Vr2Jdx66E8lZfTB0qv5ON//GH+KNX9+Kj/76e2QMGIJ5N/wQ5Yf2Ydtb/8YVv37W5Cl0R9rydcXrvj1nSFRfwIgw70K3zIabF8BtAP4K/R3o52i9NQ/AyZat7wc8tEwp9Y2A51+F/rsIAGeLyBSlVJtrSiulVgJYKSIXoqkI3q+Uuq8T2e9XSt1kv+6z0F8o/WZAt54BuhDx/53eAGCGUspr7/cb6GLWA13EfwXA/W283gNKqe92IhcAQCl1n+guz4FF8DMBLbr+7c4TEQ/0pIsjoVt09kMXlF+xN5sgIoOVUv4Jhgqhf1cAcJWI3KKUahSRkWg+eeMj9nk6AAR2T9kJYLr/S7aIrLSPCej3IR+6Ba41NymlWrxHSqkbRcQF/d6PgS5uDkN/Hvwt6L2hewq818axC5VSN9iZ7oS+6LDQfu4SEemvlOponewfBNx+BcCFSillH/NR6CIdAMYBuAi6uOyqq5RSz9vH3Iemz0w69Llu6on3vId0eK5KqWfs5wML1JXB/46VUj8V3TV6KvQM0lkAGqF/B/4iOAHAWdBFK6A/w/4ieLJ94WKT3SPliwGHL1RKWfbtW9D0b94HYL5Sapud8c/QnwEXdNF5K/SFrdY8B+CKgOP6z+NhAA+LyAQAk6EvZDQAeBn68+8vSs8D0FYRvBXALKVUvZ3rMwA/sZ8bAOBz0AXt/7d353FSVOf+xz8Pa7UCoqgYQcVdFBkQZXEP7uLu6DXuGrNM8vvFxMSs5vpLcjXX6I0m3mRiIh2XGI1O4pK4JUZN0LC4tCOiohJRAQFlB0camPP741Q7NU3PdM9Md9f09Pf9evWLXqqrnqoueurpc85z2vN/I9taDIzJjFk2sx8Db+J/QAqArwDtfn8pCRaRgqRTycf7jb30B3S8O5DksP/EcW/07dc3V7ejiuKa/d/KfSafzthT/fXrsFEHsWLB26TuT36SBO889lAumvok65YtZdDQ4fTq3ZtH//tyRp90PgOGDOWVx+7hpQduA2DM6Zcw6riChhjF5u3lTQcvWbv+naED+u8Sdyw9wIfAuYkg6GgLVWfdg79oHAecYWaT2ll2b/wFe0admeXqFphxKK2T02L6ZeR+drfWrSP3o98rNcD6doYaHErbSXBJ6kGY2eXAD/FJRXuG01Jl9zb8VDR98K1ax+Bb5M+NLP8WLWOS98ZfqGfcndXKdCe+tTxzHXwIuROyFfhW6Vz7cQ5+FoV8Y8uHt/Pa7Zk7zrlmM7uTliTY8MnTIznel4lhi3CZjBOB5jyfd0eT4EWZpDDU1rlX8mNeBoXua0HM7CjgN/ieJ+355Bxxzs00s9m0dHs+H/gW/rPL/L1ppuUHBcLXMqZnEuBwfW+a2TO0nFeHtBPHtdkJcLgfY/Dnar4uW+2d6/dkEuDQ7bQkweB/FMiXBEe/23YAVuU519ulFh0R6Ygf4X/5ky7o1bv32+OOnNTehXfFCAb4GWCGjWrdqD1s//GsWNC6J1Lf/gkG77gLvXr3ZsHLM1j2zhvUnHwhH86fy3P3/JIp369nyvfrmXX3/7LsnTfKtg+d1Df53MKCxutJuxxwQSIIynYsw1ayKyNP/aSdxTtUUIjWCXOxzY/cX5/1WvR6riMxtxXvh865ondBNbNT8El3vgQYIrMSOOeW4LufZmTGCEeT4FszLaBsfgxataY65zbif3zJaOuYzQuXbcXMxgJ3kT8BhvZnV1iS53G+pGtrNh8H3J7OnJ/zsx63de6V9Jh3UPYxKXSGi/lZj9v7f9Z+AL642YPkT4Bh8/ii8xCeG7ayR7tC/9U5927kcfRY5uo5EH2uvXPq9ewnzCyBv+4rZMxSKc91KM532yfUEiwiBUunkq7f2EsvwHd32S3f8pLbxGMOX9qrV69C/jB2e4OHt7EbzuH/bm+uedNGnr3teiae/1X69A9YNOd5ho0az9bD/LqGj5rAoldfYMgue+V8f3fxwboNk+Yt++jV3YdssW/csVSwnySC4LFyb9Q591TYlfkEfItBW99ny7MeN9DS7TiXtor9dFlk3CXOOddOC8hyWpKzFL7rd1vamou5VBXQz8naRi3wD+dcU1jwpr0fWW/FF2kE31X4CFq6HW8k0qrK5p/bDtEHYTfmaKtl9vLRGHM5i5aEyOGT8j8759aY2b7AnLZ2IstQWrc2ZheDWpnn/SvC7WdOhifxLeRtebWd19qSPTeey7lU6Y95PtHjkMh6bU8KU+i+FuIk/LjsjCuBqc65FWELfnv7eSe+KGl/fOvq0fhzLuPWrOWj/+d3YHPR51bkeB0A51yumA6jdaGwG/FDEz4Iv4eWUtiPK9nndkfPdWh9zrxD+z0G8k3npiRYRDomnUqu6Df20jPxhR+y/9BIHv3695s9ctzoQqbOqAg77DWG/lsOYsHsmew05uBPnl8weyZDRuROYl/9awP9txzEHocc98lzG9JNLffXN4HryrVH2dhtLyxa/6Nj94g7jkr1LHBVjNv/JnAcPplpa0qaufhCTpmLvG3wY3NbtVSFrSVnt1NtOVv0YrvYk2M/Q0tBpR2B32WPKw1blo7CdyEup2gS9G/nXPQHkHOyF87yGD5pH44/ZtHuoH/J2se5+FbHzPbOMbNrIt1zL6D1NXChn1tGdD9W4bt6ZrqR5tuPqIvw4+Ezn8kFkdccviBlm5xzH5lZipYu0TsAv8qeU9fM+uLHA5fsRxpKf8zzWUlLa+J4M7MwSdsfv+/ltm3W42SkaFu754hzbrmZ3R9Zrp6WVtClwENZb3kWX1gOYJKZ7RMZE7wnrbsGd+VcB/99sjRc92QK711wjpn9d6Y+Af7cj2qrIGDUM/gxyOCT6Iedc69lL2RmE/HFstqlJFhEOiydSr7Ub+yldfhxWtIBR552QkVkdxkb1jfx7ou+hsa65UtJN61l3nRfwHfnAw6lb/8E4876PDPuvIn+Ww5ku9334+2Zf+f9117k1B9M3Wx969eu5vn7bmHKVS3DG3fcdxwzfncTrz/ph6otfGUWE877Shn2ruvWpTeNfWHh6ufHDRukKcQ65kPgM4kg6Gq3x05zzr1iZrfTUowp1zLNZnYDvlUG/FREs83sL/iKtdvguwkejv9R8PacK9pctAV2nJn9HMh0b/yFc64px3sKdQO+xbQX/kJxtpk1hOvfAt96egT+4vXT+Aqr5TIXP54XYP+wEu4r+PGKk9t6E4BzbpP5+ZYzP5xEW+9/k7Vsc1gE7NrwqT2A58zsAXyiGL0A/xD4bSf2I2Mw8KiZTcOPMz8t91tyutT8fNUv4D+LwyOvPVRAUSzw5+Yfwvv7AnPCBGoxvtv5fvjjOwjfNbfNlsCuKMMxz2cmLVOIHQHMMLNF+FbU7KnCyiF7PPEjZvYwvlX63BzLZ7uVliQ4eq7fHu0VEvof/HlnQG9gmpndgR87fCEt+Z4Ll+2I7P24y8zuxhezurgD6xkJzDSzaHXojMVsntjncjMtFbuDcH0N+CJsffHn3OH44liXkKc+g5JgEemUdCp5e7+xl07Cz1MpBdhy0MBZO+0xosMTw8epadVy/vbTK1s9l3l87i8epu/2wxg95Xxcs+OVR+/m+Xt/xeAdR3Ds12/gUyMP2Gx9z91bz4gDj2C73UZ+8ty2u+7DxPO/yqy7fc+mSRdewbYjCp7vPnb3Ni4eNHbHgc292ur/LdnSwOmJIHgv75Kl9338hWZ7vVqux1+4Ziq2Zuaz7Yr7aLmA7IWveppxG356lk5xzk0P5wzNzBO8La0rNsfpJvxFeWZM8NnhDXxS1OYPEqGp+Ore0b7gCwinislyHf7CO9O6Oiq8RS0HTnPOFdIVMyqJrzybKQR0LC3TYxWyHxlP4bvNnpT1/EJanxNtcs7da2Yj8dXVDT8d0uUFbr/YSnnM87ke/xlkvoczf2s/wh/nTxd5e/k8hE/CxoSPJ4Q3KOwceRI/fVr2UI3Nfl12zj1rZl/Gzzud6XZ+RdZim/BVt/9Z6A6E637BzB7BF10D/92XKZD6N/zn3V5BrIyn8T9OjMl6Pg1ckm96pDCW+WZ2FnA3vqr8QAr/v7YZJcEi0hWX47thVfxUP2Ww6ZizTqq4eZYHbT+ML96Xv9htzckXUHPyBXmXO/TSb+V8fvSU8xg95bycr3V3G5rdXk++tfzZo/cc0l7VTWlxWSII2pqio6yccwvN7CbgO+0s44DPmdk9+ER4Ir4VZAPwPr4l9a/4+S8L3e4jZnYZPtHZh8IL9xS6/qlhRdgv41tYR+Cv+Zbgk8Z/hvHOKOZ2C4hrnpkdhh9TeDg+aXsZ33q4hjwXtOFF8BO0tCYD/DbX3Ldh9+QLw+mkPotPirbFX3TPw4+d/Zlz7v1O7McKMzsUX1TtWHyr1Fx8tein8u1HxGX4eYU/j/+hZQ1+XPT3nHMFF4tzzv0gbGWsw4/hzCQli/E9AP6OH7M8v9B1dkYpj3kB234yLLx2Nb53RhP+s7gK/0NLWZNg59yGsDr0dfg5bLfCf1fcCvyU/Oe6M7OpwDWRp6c557JbZjPL15vZs/ipgY7Ez69swCJ81fSfO+dSndydWnxF98/gxx4vxCeiPyRHMa023I7/f/9dWrrvTwf+0zlX8PeQc+7hcNz9l/H/9/bE//9bGsY1Hf/dljfZN1cZ465EpJvqN/bSnfFdubLHjUjEkB22e+a0z56bt2S/VKZexoIfH7/ndn179ypqMtMDXZMIgjjHAYuIiGiKJBHpmnQq+S7+18FyzfFZiZqOrj1597iDkNJpdgx/YM7SsraqVaD78N2PRUREYqUkWES6LJ1KPoHGBrdp+O4jZg3YauCn4o5DSmv6u6tGN23YtCruOLqpWcBFiSBQ9zMREYmdkmARKYp0KjkV+HbccXRDK4489bjsQhDSM219V+r9zo656sneBU5JBEFXKh6LiIgUjZJgESmadCp5HX56DgntPXbUy/0TwVZxxyHl8erSdRNWNG0oetGXCrYGOCkRBEviDkRERCRDSbCIFFU6lbyS4s//V5Gsly2YdOwRE+OOQ8oq8dvnF74VdxDdxCbgnEQQzI47EBERkSglwSJSCp8DHow7iLgdcPjEd3r36aNqwVVmwar1By9Y9fG8uOOImQMuTQTBI3EHIiIikk1JsIgUXTqV3AScg5+brir17tPnjZqDD5oUdxwSi97J5xcuizuImNUlguCOuIMQERHJRUmwiJREOpX8GDgFqMpCQYdOOWq1mek7tkqtbNo4/rWla1+OO46YXJEIglviDkJERKQtukATkZJJp5KrgeOBN+OOpZyCLRKpPUbtc2DccUi87nzxfYs7hhh8PxEEN8YdhIiISHuUBItISaVTyaXAscCiuGMpEzf5zBM1Dlj4eGPz/v96Z+WMuOMoo2sTQfBfcQchIiKSj5JgESm5dCo5H58Ir4g5lJIbtM3gGZ/aefi+ccch3cP9c5YObXZuU9xxlMFNiSD4XtxBiIiIFEJJsIiURTqVnAOcQM9OhDccc9bJO8YdhHQfm5rdro/O/fBfccdRYr9OBMHX4g5CRESkUEqCRaRs0qnkTOAI4P24YymFocN3nD542212iTsO6V6efGv5XumNzR/FHUeJ3AHUxR2EiIhIRygJFpGySqeSs4FDgJ42j+qayWeeODLuIKT7cTD03tmLZ8UdRwncDFycCILmuAMRERHpCCXBIlJ26VTybXwi/FLcsRTLriP3fHGLAVtuF3cc0j29uHDNAWvWb+xJcwdfnQiCrySCwMUdiIiISEcpCRaRWKRTySXAkcC0mEPpOrMPDpty9Li4w5BubdAdLy56Je4giqAZ+FIiCH4YdyAiIiKdpSRYRGKTTiVXAccBf447lq4YNX7sa3379xsQdxzSvc1b1jTpg7Xp9+KOows2AOcmgqA+7kBERES6QkmwiMQqnUo2AWfgC+xUnF69e80/aPIhB8cdh1SEfsnnF74bdxCdtA44KREEf4g7EBERka5SEiwisUunkhuBi4EbYw6lw8YfddjiXr169Yk7DqkMS9amD357edPrccfRQcuBoxJB8Ne4AxERESkGJcEi0i2kU0mXTiWvAL4XdyyF6tuv35z9DhozMe44pKLYbc8vXBd3EB2wEDgsEQQz4w5ERESkWJQEi0i3kk4lrwW+gC/A060dcepxG+KOQSrPmvSmcS8tWv1C3HEUYBYwPhEEr8YdiIiISDEpCRaRbiedSv4aOBlYEXcsbdli4IDndtlrtzFxxyGV6Z7GxVs657rz9EJ3AIcngmBR3IGIiIgUm5JgEemW0qnkI8A4uudcws1H1540OO4gpHKlN7l9nv73in/FHUcOm4ArEkFwUSII1scdjIiISCkoCRaRbiudSr4NTAJuizmUVrbZftvp2+04dM+445DK9vDrH+y8sdml444jYjlwfCIIKq5AnYiISEcoCRaRbi2dSn6cTiUvwY8T7g4tUx8ffdZJu8YdhFS+ZsdOD726dHrccYTm4Mf/PhF3ICIiIqWmJFhEKkI4TvgwINZ5VofttvPMgYO32jHOGKTneGb+vPrEegAAEOdJREFUylFNGzatjjmMB4CJiSCYF3McIiIiZaEkWEQqRjqVfA44APhbTCGsPPK0E2pi2rb0TEPufmnxizFtuxn4IXBGIgjWxhSDiIhI2SkJFpGKkk4llwHHA9cAZa2uu1fNvo1BIlBBLCmqV5asHb+yacOSMm92IXB0IgiuTgRBd65SLSIiUnRKgkWk4qRTyeZ0KnkVcCqwqhzbNLNFk47/9IRybEuqzha3vbDojTJu70/A6EQQPFXGbYqIiHQbSoJFpGKlU8k/46dRaiz1tsYcNv7fffr0CUq9HalO7678+OD3V69/u8SbWQdclgiCMxNBsLzE2xIREem2lASLSEVLp5LzgAn47tEbS7GN3n16vzn20AkHl2LdIqHeU59bWMou0S8ABySCYGoJtyEiIlIRlASLSMVLp5Lrw+7R44GXir3+g4+fvNLM9H0pJbW8acPEuR+sm13k1TYD1wGTEkFQzi7XIiIi3ZYu6kSkx0inkingIOAqijSncP9E0LhXzb4HFWNdIvnc8eKiYhapyhS/+nYiCDYUcb0iIiIVTUmwiPQo6VRyYzqVvAYYC8zo6vomn3Fin65HJVKYpg3No2e8u3JWF1fjgF8B+6n4lYiIyOaUBItIj5ROJV8DDgGuAD7qzDoGDt5qxo4jdtqvqIGJ5PGnV5YOaXZuUyffPhs4JBEEdYkgKEvldBERkUqjJFhEeqxwKqUbgdHA0x18+8Zjzj55aPGjEmnfxma3++NvLPtXB9/2EfBtfPGr6SUIS0REpMdQEiwiPV5YQXoy8EVgdSHv2W7YDtO33m7IriUNTKQNT7y5bI/0puamAhd/FBiVCILrEkFQkgrpIiIiPYmSYBGpCulU0qVTyVuAUcAjeRZfd9SZU/YuQ1giOTn41B9nL5mZZ7H3gf9IBMGJiSAo9RzDIiIiPYaSYBGpKulU8r10KjkFOBF4Ndcyu+y9+/NbDhywfXkjE2ntuQWrx65Lb1qR46VNwC+BkYkguLfMYYmIiFQ8JcEiUpXSqeSj+LHCXwSWRl768PCTjz0gnqhEWtnqjhcXvZz13KNATSIIvqzCVyIiIp2jJFhEqlY6ldwUdpHeA/gx8PF+B415tV//fgNjDk0EgDc//Gjih+vSC4BG4Jiw6/OcuOMSERGpZEqCRaTqpVPJNelU8rvA3gdOPuQNoDnumERCi++fs/Tr+KrPT8QdjIiISE9gzrm4YxAR6VbqGhr3Bf4LOD3uWKRqLcWfg7fU19ak4w5GRESkJ1ESLCLShrqGxvHAtcBRccciVWMVcD1wU31tzbq4gxEREemJlASLiORR19A4AfgWcCoaRiKlsQi4Ed/yuybuYERERHoyJcEiIgWqa2jcG/gGcAHQP+ZwpGd4Hd/y+zt1exYRESkPJcEiIh1U19D4KeBy/PRKW8UcjlSm6cB1wEP1tTX6QywiIlJGSoJFRDqprqFxEPAF4KvAjjGHI92fAx4GflJfWzMt7mBERESqlZJgEZEuqmto7Aech0+IJ8QcjnQ/q4G7gZvra2s0x6+IiEjMlASLiBRRXUPjKOCz+HHDQ2IOR+L1DDAVuLe+tuajuIMRERERT0mwiEgJ1DU09gdOAy7DT7Fk8UYkZbIUuAO4tb62Zm7cwYiIiMjmlASLiJRYXUPjCHzr8MXA8FiDkVJoBh7Ht/o+VF9bsyHmeERERKQdSoJFRMqkrqGxN3AMcDZwCuouXckcMAu4H/h9fW3NezHHIyIiIgVSEiwiEoMwIT4COAPfbXpYvBFJATYB/wT+BNxfX1uzMOZ4REREpBOUBIuIxKyuodGA8fiE+Axgj3gjkoj1wBP4xPeh+tqaD2OOR0RERLpISbCISDdT19C4Pz4ZPg44EOgbb0RVZzHwFPAQ8HB9bc2amOMRERGRIlISLCLSjdU1NG4JHAp8OryNA3rHGlTP8wHwND7xfaq+tub1eMMRERGRUlISLCJSQeoaGgcBhwFH4pPisUCvOGOqQMuAf+CT3qeBOfW1NfpjKCIiUiWUBIuIVLC6hsbBwMH4ZHhMeNsdzUucsQZ4GXgpvD0HvKykV0REpHopCRYR6WHqGhoHAjW0JMVjgFFA/zjjKoP3gRQtCe9LwFtKeEVERCRKSbCISBWoa2jsA4wE9gJGZN12AQbGE1mHNAOLgPnh7Z3w37eB2fW1NUvjCkxEREQqh5JgERGhrqFxCK0T452BbYDBOW4DirjpjcAqYGWO2/u0JLzzgXfra2s2FHHbIiIiUoWUBIuISIeErcpb0ZIUD8RXrI7eegEO2IRvwd0U3tbTkuSuqq+tWVvu+EVERKS6KQkWERERERGRqqFpNURERERERKRqKAkWERERERGRqqEkWERERERERKqGkmARERERERGpGkqCRUREREREpGooCRYREREREZGqoSRYREQqhpldbGYuchsRee22yPPz41xnZ5nZbmZ2t5m9b2YbI9u+uNTb7u7M7P9FP6cOvO/IrM/3yBKGKSIiFUBJsIiIlIyZjchKQJyZLTaz/m0s35hj+RHljToeZpYAHgHOAXYAescbkYiISM/UJ+4ARESk6gwFzgOS0SfN7GhgdJ73PgdcGXm8vLihxeogYO/I478A04Bm/H6LiIhIESgJFhGROHyNrCQY+Hq+Nznn5gBzShJR/EZkPf6qc25eHIGUgpn1Afo655rijkVERKqbukOLiEg5bQr/HWVmx2SeNLN9geOyltlMe+N38zGzg8zsMTNbbWZrzOzvZnZER3fAzLYxs48iMVyeY5no+NWVYVfnttY3IhzjenvWS29l76eZXWlm95vZXDP70Mw2hPvyspn91MyGZ617WmQdj+fY9gFZx/PkyGtmZp8xs0fNbImZpcN9mWlm3zGzQTnWNz+yrtvMbH8ze9DMlgEbgAnhcpea2T1mNsfMlobrXmtmr5nZLWY2sr3PIFxHXzP7dngsPjazBWZ2k5ltle+9OdZ1rJndZ2bvmdn68ByZZWbfMLMtOro+ERHp3pQEi4hIOT0Yuf+1yP0rAAvvP1DsjYYJ9zP4RHsgMACYDDwJnNWRdTnnlgN3Rp76Qo7F/iNy//dFbP38FnAasBcwBN+jawCwP/54vhz+oJBxa+T+UWa2Q9b6zo3cX4Qfk5wZn/wo8HvgeGB7oC+wFTAeuBZ4ycz2bCfW0cB04BRgm6zXvoQ/RvsC24Xr3hLYB/g8kCqggNWfgB/jj0V/YBhwOfBPMxuQ572E+2lm9mvgcaAWGA70w58jBwHXAzPMbPtC1iciIpVB3aFFRKScZuMTjGOA48MWv2XA+eHrc4GHgTOLtUEzC4A78MkNgAPuAd4CTgJO7MRqf4ZP1gBGmtlhzrlp4fbG4JO5jFuz35xlOX6c84G0Tp6vBVZElgFYADwNvBO+5vCJ29n4RHNr4Cf4/QK4N4x1K3yhrc8AN4Zx9sIX4cr4rXMu0wr/U1pa5sEns3/DJ5yZ9+wKPGhmo51zG3Ps11h8q/5d+M91D2Bd+NoH+DHPb4X7sQFfDOx0YCd8Uvu/wKgc682Ygk/S5wEnA2PC50cDP8T/sJLP14HPRR4/Gu7rdsCF+OO2P/A74NgC1iciIhVASbCIiJTb/+CTYMO3Xi7GJz0AN+ETu2I6FZ9gZfzIOXc1gJldA6SAvN1vo5xzr5rZ3/D7Ab41eFp4P5rIppxzL+ZZ12rgBvPTIEXf+xvn3PysZceY2UBgEn4M8Zb4JHAafj8Bjjazvs65Dc65JjO7G/hi+Nr5hEkwcCS+9RT8MZ8Kvrs3cFlks9OAT2cSZDN7A/jP8LWR+AT0/jZ2r9Y5t1nLvnPuhPDHiYnA7vgfRt4DngAuCRfbz8x2cs6918a6r3bO/SiM6Rr8DyyZlunLzOybbSTnhO/pBXwz8lS9c+5LkdcfJWwZB44xszHOuZfaWp+IiFQOdYcWEZGycs49TktxqwvwXWPBtwhnj4sthoOyHn+yDefcenyrcGf8LHK/1syGhPejiWy+VuCCmVkvM7sW34r6OHALvsX2eloSYPA/KGwbefybyP0DIuNtz4s8/6Rz7u3w/gRa/0h+e6SFGDYvaHZIGyG/kisBDvflcmAJ8BT+GN0Y7sclWYsOp23tfY4D8a3W7dkb3+KbUWet5yF+JGv5Q/OsT0REKoSSYBERicNPw38D/NhWgF+VqHLw4KzHS/I8LtQjwJvh/f7ARWY2Ad9NGKAJ3xW4WP4P8B1aWs3b88kyYUt0KvLa+ebnaY52OY8mytnjdxfneZy9fMbruZ40s1PwLf6bFdbKob19zfc5bp1n3W3F3Zbt8i8iIiKVQN2hRUQkDnfhx7wODR+n8WNAS2Fl1uOhwL+zHneYc86Z2c+Bm8OnPo8fz5rxR+fcqs6suw3R8buL8Elsyjm33sy+BPyinfdOpeX4nodPijNVlJfRuhhZ9tzL2cW0sh+3NVfzujaePydrmVrgH2HX7RPxY8ILMRR4N+txVPbnni077gZgZjvLTy8wLhER6ebUEiwiImUXdl+NJm13O+eyWxiL5bmsxxdl7phZP1onZR11G5BJdPemZewtFLErdCjaxfkF59yMMAHuRf4K13fhW6YBdgGui7x2Z/h5ZMwEomNpLwy3kXFp1rqfzR96K9H9+Ldz7rFID4COfBbRz7F/1nvX4ItxtWcuvmt5xjbATc65G6I3/Hn6gXOuo/spIiLdlFqCRUQkLj/HFzMCmFXC7TyE7yqbaSn8vpntgS8odRIdLIoV5Zxba2ZJWqZ7CsJ/33TO/aOz623DXFoKP00xs98AC/FVkg/ME+dKM/sjLVW4d4u8fGvWssvDfcpUvz4ceCYsBLYnrZPNucCfO7EfmYJi+5vZH4BX8IW6JndgPT8ws31oqQ4dna4p2V5RLADnXLOZ3UDLDwKTgdlm9hd86/g2+ErThwMJSjNeXUREYqAkWEREYhF2FS76nMA5ttMUVl5+ED9NktEyP67DTzl0ZBc2cTN+ftpoa+nULqyvLT/GT1vUN9xWpoLzRvwUPue38b6MW3MsM905NyfHsl/FJ8pHh48nhbeod4FT8yWbOdyEn34oMyb47PAG8Fs2L47VlqdpPc9xxiu0VK/O53p88pw5lvvQenorERHpgdQdWkREejzn3GP4Fr2/AmvxY1H/CZxAF1v4wqrKD0We2tjVdbaxnX/hk9JpwMf4Lr9PAkcAfy/g/f8A3sh6OmeX7bB78nH46t2P47sNbwRWA88DVwE1zrl8XY5zrXsecBh+Tt51wEfADOAU/HzOhToBuBo/13AaP076ZuDwcNqpQmJxzrnP4Y/rPcB8YD3+HHkTf758A9/VXUREeghzrtjTMYqIiFSXcJ7a74YPH3DOnR5nPCIiItI2dYcWERHpBDMbgZ8OaU/89EUZP8u1vIiIiHQPSoJFREQ652J8d9yo+5xzT5c/FBERESmUkmAREZGu2QS8B/we+FHMsYiIiEgeGhMsIiIiIiIiVUPVoUVERERERKRqKAkWERERERGRqqEkWERERERERKqGkmARERERERGpGkqCRUREREREpGooCRYREREREZGqoSRYREREREREqoaSYBEREREREakaSoJFRERERESkaigJFhERERERkaqhJFhERERERESqhpJgERERERERqRpKgkVERERERKRqKAkWERERERGRqqEkWERERERERKqGkmARERERERGpGkqCRUREREREpGooCRYREREREZGqoSRYREREREREqoaSYBEREREREakaSoJFRERERESkaigJFhERERERkaqhJFhERERERESqxv8H4bFsifYF7Z8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data = column_value_counts[6]\n",
    "fig, ax = plt.subplots()\n",
    "_, texts, autotexts = ax.pie(plot_data, colors=opinion_colors, labels=plot_data.index, startangle=90, counterclock=False, autopct='%1.0f%%')\n",
    "ax.set_title(question_wording.get(plot_data.name))\n",
    "for text in texts:\n",
    "    text.set_fontweight('bold')\n",
    "for autotext in autotexts:\n",
    "    autotext.set_size(15)\n",
    "ax.text(1, 1.10, \"(Net Favorability: {:.0%})\".format(net_favorability_scores.get(plot_data.name)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(1, 1.1, '(Net Favorability: -5%)')"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data = column_value_counts[10]\n",
    "fig, ax = plt.subplots()\n",
    "_, texts, autotexts = ax.pie(plot_data, colors=opinion_colors, labels=plot_data.index, startangle=90, counterclock=False, autopct='%1.0f%%')\n",
    "ax.set_title(question_wording.get(plot_data.name))\n",
    "for text in texts:\n",
    "    text.set_fontweight('bold')\n",
    "for autotext in autotexts:\n",
    "    autotext.set_size(15)\n",
    "ax.text(1, 1.10, \"(Net Favorability: {:.0%})\".format(net_favorability_scores.get(plot_data.name)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Group Comparisons"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Zoomers v. Boomers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [],
   "source": [
    "boomer_value_counts = zoomer_value_counts = [data[(data[\"age\"] == \"40+\")][colname].value_counts(sort=False) for colname in data.columns]\n",
    "zoomer_value_counts = [data[~(data[\"age\"] == \"40+\")][colname].value_counts(sort=False) for colname in data.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [],
   "source": [
    "boomers_opinion_totals = create_opinion_table(boomer_value_counts)\n",
    "zoomers_opinion_totals = create_opinion_table(zoomer_value_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Strongly unfavorable</th>\n",
       "      <th>Mildly unfavorable</th>\n",
       "      <th>Neither favorable nor unfavorable</th>\n",
       "      <th>Mildly favorable</th>\n",
       "      <th>Strongly favorable</th>\n",
       "      <th>total_respondents</th>\n",
       "      <th>total_positive</th>\n",
       "      <th>total_negative</th>\n",
       "      <th>net_favorability_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>biden</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bernie</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-0.444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>warren</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>harris</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pete</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.222222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beto</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-0.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>booker</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yang</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>castro</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gabbard</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>williamson</th>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-0.888889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>klobuchar</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de_blasio</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-0.888889</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Strongly unfavorable  Mildly unfavorable  \\\n",
       "biden                        1.0                 2.0   \n",
       "bernie                       5.0                 1.0   \n",
       "warren                       0.0                 0.0   \n",
       "harris                       0.0                 0.0   \n",
       "pete                         0.0                 2.0   \n",
       "beto                         1.0                 5.0   \n",
       "booker                       0.0                 2.0   \n",
       "yang                         1.0                 4.0   \n",
       "castro                       0.0                 1.0   \n",
       "gabbard                      3.0                 1.0   \n",
       "williamson                   7.0                 1.0   \n",
       "klobuchar                    1.0                 3.0   \n",
       "de_blasio                    5.0                 3.0   \n",
       "\n",
       "            Neither favorable nor unfavorable  Mildly favorable  \\\n",
       "biden                                     2.0               4.0   \n",
       "bernie                                    1.0               2.0   \n",
       "warren                                    0.0               3.0   \n",
       "harris                                    0.0               1.0   \n",
       "pete                                      3.0               3.0   \n",
       "beto                                      3.0               0.0   \n",
       "booker                                    2.0               4.0   \n",
       "yang                                      2.0               2.0   \n",
       "castro                                    6.0               1.0   \n",
       "gabbard                                   4.0               1.0   \n",
       "williamson                                1.0               0.0   \n",
       "klobuchar                                 1.0               3.0   \n",
       "de_blasio                                 1.0               0.0   \n",
       "\n",
       "            Strongly favorable  total_respondents  total_positive  \\\n",
       "biden                      0.0                9.0             4.0   \n",
       "bernie                     0.0                9.0             2.0   \n",
       "warren                     6.0                9.0             9.0   \n",
       "harris                     8.0                9.0             9.0   \n",
       "pete                       1.0                9.0             4.0   \n",
       "beto                       0.0                9.0             0.0   \n",
       "booker                     1.0                9.0             5.0   \n",
       "yang                       0.0                9.0             2.0   \n",
       "castro                     1.0                9.0             2.0   \n",
       "gabbard                    0.0                9.0             1.0   \n",
       "williamson                 0.0                9.0             0.0   \n",
       "klobuchar                  1.0                9.0             4.0   \n",
       "de_blasio                  0.0                9.0             0.0   \n",
       "\n",
       "            total_negative  net_favorability_pct  \n",
       "biden                  3.0              0.111111  \n",
       "bernie                 6.0             -0.444444  \n",
       "warren                 0.0              1.000000  \n",
       "harris                 0.0              1.000000  \n",
       "pete                   2.0              0.222222  \n",
       "beto                   6.0             -0.666667  \n",
       "booker                 2.0              0.333333  \n",
       "yang                   5.0             -0.333333  \n",
       "castro                 1.0              0.111111  \n",
       "gabbard                4.0             -0.333333  \n",
       "williamson             8.0             -0.888889  \n",
       "klobuchar              4.0              0.000000  \n",
       "de_blasio              8.0             -0.888889  "
      ]
     },
     "execution_count": 247,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boomers_opinion_totals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Strongly unfavorable</th>\n",
       "      <th>Mildly unfavorable</th>\n",
       "      <th>Neither favorable nor unfavorable</th>\n",
       "      <th>Mildly favorable</th>\n",
       "      <th>Strongly favorable</th>\n",
       "      <th>total_respondents</th>\n",
       "      <th>total_positive</th>\n",
       "      <th>total_negative</th>\n",
       "      <th>net_favorability_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>biden</th>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bernie</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>warren</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>harris</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pete</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beto</th>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>booker</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yang</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>castro</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gabbard</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>williamson</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>klobuchar</th>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de_blasio</th>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-0.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Strongly unfavorable  Mildly unfavorable  \\\n",
       "biden                        6.0                 2.0   \n",
       "bernie                       0.0                 1.0   \n",
       "warren                       1.0                 0.0   \n",
       "harris                       1.0                 4.0   \n",
       "pete                         0.0                 4.0   \n",
       "beto                         1.0                 5.0   \n",
       "booker                       1.0                 2.0   \n",
       "yang                         1.0                 1.0   \n",
       "castro                       0.0                 1.0   \n",
       "gabbard                      3.0                 2.0   \n",
       "williamson                   2.0                 0.0   \n",
       "klobuchar                    0.0                 6.0   \n",
       "de_blasio                    2.0                 5.0   \n",
       "\n",
       "            Neither favorable nor unfavorable  Mildly favorable  \\\n",
       "biden                                     2.0               0.0   \n",
       "bernie                                    2.0               4.0   \n",
       "warren                                    1.0               0.0   \n",
       "harris                                    3.0               2.0   \n",
       "pete                                      5.0               1.0   \n",
       "beto                                      3.0               1.0   \n",
       "booker                                    6.0               1.0   \n",
       "yang                                      4.0               3.0   \n",
       "castro                                    3.0               2.0   \n",
       "gabbard                                   5.0               0.0   \n",
       "williamson                                4.0               3.0   \n",
       "klobuchar                                 4.0               0.0   \n",
       "de_blasio                                 3.0               0.0   \n",
       "\n",
       "            Strongly favorable  total_respondents  total_positive  \\\n",
       "biden                      0.0               10.0             0.0   \n",
       "bernie                     3.0               10.0             7.0   \n",
       "warren                     8.0               10.0             8.0   \n",
       "harris                     0.0               10.0             2.0   \n",
       "pete                       0.0               10.0             1.0   \n",
       "beto                       0.0               10.0             1.0   \n",
       "booker                     0.0               10.0             1.0   \n",
       "yang                       1.0               10.0             4.0   \n",
       "castro                     4.0               10.0             6.0   \n",
       "gabbard                    0.0               10.0             0.0   \n",
       "williamson                 1.0               10.0             4.0   \n",
       "klobuchar                  0.0               10.0             0.0   \n",
       "de_blasio                  0.0               10.0             0.0   \n",
       "\n",
       "            total_negative  net_favorability_pct  \n",
       "biden                  8.0                  -0.8  \n",
       "bernie                 1.0                   0.6  \n",
       "warren                 1.0                   0.7  \n",
       "harris                 5.0                  -0.3  \n",
       "pete                   4.0                  -0.3  \n",
       "beto                   6.0                  -0.5  \n",
       "booker                 3.0                  -0.2  \n",
       "yang                   2.0                   0.2  \n",
       "castro                 1.0                   0.5  \n",
       "gabbard                5.0                  -0.5  \n",
       "williamson             2.0                   0.2  \n",
       "klobuchar              6.0                  -0.6  \n",
       "de_blasio              7.0                  -0.7  "
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zoomers_opinion_totals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>boomers</th>\n",
       "      <th>zoomers</th>\n",
       "      <th>difference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>biden</th>\n",
       "      <td>11</td>\n",
       "      <td>-80</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bernie</th>\n",
       "      <td>-44</td>\n",
       "      <td>60</td>\n",
       "      <td>-104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>warren</th>\n",
       "      <td>100</td>\n",
       "      <td>70</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>harris</th>\n",
       "      <td>100</td>\n",
       "      <td>-30</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pete</th>\n",
       "      <td>22</td>\n",
       "      <td>-30</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beto</th>\n",
       "      <td>-66</td>\n",
       "      <td>-50</td>\n",
       "      <td>-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>booker</th>\n",
       "      <td>33</td>\n",
       "      <td>-20</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yang</th>\n",
       "      <td>-33</td>\n",
       "      <td>20</td>\n",
       "      <td>-53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>castro</th>\n",
       "      <td>11</td>\n",
       "      <td>50</td>\n",
       "      <td>-38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gabbard</th>\n",
       "      <td>-33</td>\n",
       "      <td>-50</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>williamson</th>\n",
       "      <td>-88</td>\n",
       "      <td>20</td>\n",
       "      <td>-108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>klobuchar</th>\n",
       "      <td>0</td>\n",
       "      <td>-60</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de_blasio</th>\n",
       "      <td>-88</td>\n",
       "      <td>-70</td>\n",
       "      <td>-18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            boomers  zoomers  difference\n",
       "biden            11      -80          91\n",
       "bernie          -44       60        -104\n",
       "warren          100       70          30\n",
       "harris          100      -30         130\n",
       "pete             22      -30          52\n",
       "beto            -66      -50         -16\n",
       "booker           33      -20          53\n",
       "yang            -33       20         -53\n",
       "castro           11       50         -38\n",
       "gabbard         -33      -50          16\n",
       "williamson      -88       20        -108\n",
       "klobuchar         0      -60          60\n",
       "de_blasio       -88      -70         -18"
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zoomers_v_boomers = pd.DataFrame({\"boomers\": boomers_opinion_totals[\"net_favorability_pct\"], \"zoomers\": zoomers_opinion_totals[\"net_favorability_pct\"]})\n",
    "zoomers_v_boomers[\"difference\"] = zoomers_v_boomers[\"boomers\"] - zoomers_v_boomers[\"zoomers\"]\n",
    "(zoomers_v_boomers * 100).astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "zoomers   -0.800000\n",
       "boomers    0.111111\n",
       "Name: biden, dtype: float64"
      ]
     },
     "execution_count": 276,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zoomers_v_boomers.loc[\"biden\", [\"zoomers\", \"boomers\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1872x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 4, sharey=True, figsize=(26, 8))\n",
    "\n",
    "fig.suptitle(\"Zoomers v. Boomers: Net Favorability\", fontsize=36)\n",
    "\n",
    "category_labels = [\"0-40\", \"40+\"]\n",
    "\n",
    "curr_ax = ax[0]\n",
    "curr_ax.bar(category_labels, zoomers_v_boomers.loc[\"harris\", [\"zoomers\", \"boomers\"]], color=['C0', 'C1'])\n",
    "curr_ax.set_title(\"Kamala Harris\")\n",
    "curr_ax.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n",
    "\n",
    "curr_ax = ax[1]\n",
    "curr_ax.bar(category_labels, zoomers_v_boomers.loc[\"williamson\", [\"zoomers\", \"boomers\"]], color=['C0', 'C1'])\n",
    "curr_ax.set_title(\"Marianne Williamson\")\n",
    "curr_ax.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n",
    "\n",
    "curr_ax = ax[2]\n",
    "curr_ax.bar(category_labels, zoomers_v_boomers.loc[\"bernie\", [\"zoomers\", \"boomers\"]], color=['C0', 'C1'])\n",
    "curr_ax.set_title(\"Bernie Sanders\")\n",
    "curr_ax.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n",
    "\n",
    "curr_ax = ax[3]\n",
    "curr_ax.bar(category_labels, zoomers_v_boomers.loc[\"biden\", [\"zoomers\", \"boomers\"]], color=['C0', 'C1'])\n",
    "curr_ax.set_title(\"Joe Biden\")\n",
    "curr_ax.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = zoomers_v_boomers[[\"zoomers\", \"boomers\"]].transpose()[\"bernie\"].plot.bar()\n",
    "ax.set_title(\"Zoomers v. Boomers: Bernie Sanders (Net Favorability)\")\n",
    "ax.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = zoomers_v_boomers[[\"zoomers\", \"boomers\"]].transpose()[\"harris\"].plot.bar()\n",
    "ax.set_title(\"Zoomers v. Boomers: Kamala Harris (Net Favorability)\")\n",
    "ax.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Elizabeth vs the World"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [],
   "source": [
    "liz_lads_value_counts = [data[(data[\"first_choice\"] == \"Elizabeth Warren\")][colname].value_counts(sort=False) for colname in data.columns]\n",
    "warren_wary_value_counts = [data[~(data[\"first_choice\"] == \"Elizabeth Warren\")][colname].value_counts(sort=False) for colname in data.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Strongly unfavorable</th>\n",
       "      <th>Mildly unfavorable</th>\n",
       "      <th>Neither favorable nor unfavorable</th>\n",
       "      <th>Mildly favorable</th>\n",
       "      <th>Strongly favorable</th>\n",
       "      <th>total_respondents</th>\n",
       "      <th>total_positive</th>\n",
       "      <th>total_negative</th>\n",
       "      <th>net_favorability_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>biden</th>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bernie</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>warren</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>harris</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pete</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beto</th>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>booker</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yang</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>castro</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gabbard</th>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>williamson</th>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>klobuchar</th>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de_blasio</th>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Strongly unfavorable  Mildly unfavorable  \\\n",
       "biden                        7.0                 3.0   \n",
       "bernie                       3.0                 1.0   \n",
       "warren                       0.0                 0.0   \n",
       "harris                       0.0                 4.0   \n",
       "pete                         0.0                 4.0   \n",
       "beto                         1.0                 6.0   \n",
       "booker                       1.0                 2.0   \n",
       "yang                         2.0                 1.0   \n",
       "castro                       0.0                 2.0   \n",
       "gabbard                      4.0                 2.0   \n",
       "williamson                   4.0                 0.0   \n",
       "klobuchar                    1.0                 7.0   \n",
       "de_blasio                    4.0                 6.0   \n",
       "\n",
       "            Neither favorable nor unfavorable  Mildly favorable  \\\n",
       "biden                                     0.0               0.0   \n",
       "bernie                                    1.0               4.0   \n",
       "warren                                    0.0               0.0   \n",
       "harris                                    1.0               2.0   \n",
       "pete                                      3.0               3.0   \n",
       "beto                                      2.0               1.0   \n",
       "booker                                    4.0               3.0   \n",
       "yang                                      3.0               4.0   \n",
       "castro                                    2.0               2.0   \n",
       "gabbard                                   4.0               0.0   \n",
       "williamson                                3.0               3.0   \n",
       "klobuchar                                 1.0               1.0   \n",
       "de_blasio                                 0.0               0.0   \n",
       "\n",
       "            Strongly favorable  total_respondents  total_positive  \\\n",
       "biden                      0.0               10.0             0.0   \n",
       "bernie                     1.0               10.0             5.0   \n",
       "warren                    10.0               10.0            10.0   \n",
       "harris                     3.0               10.0             5.0   \n",
       "pete                       0.0               10.0             3.0   \n",
       "beto                       0.0               10.0             1.0   \n",
       "booker                     0.0               10.0             3.0   \n",
       "yang                       0.0               10.0             4.0   \n",
       "castro                     4.0               10.0             6.0   \n",
       "gabbard                    0.0               10.0             0.0   \n",
       "williamson                 0.0               10.0             3.0   \n",
       "klobuchar                  0.0               10.0             1.0   \n",
       "de_blasio                  0.0               10.0             0.0   \n",
       "\n",
       "            total_negative  net_favorability_pct  \n",
       "biden                 10.0                  -1.0  \n",
       "bernie                 4.0                   0.1  \n",
       "warren                 0.0                   1.0  \n",
       "harris                 4.0                   0.1  \n",
       "pete                   4.0                  -0.1  \n",
       "beto                   7.0                  -0.6  \n",
       "booker                 3.0                   0.0  \n",
       "yang                   3.0                   0.1  \n",
       "castro                 2.0                   0.4  \n",
       "gabbard                6.0                  -0.6  \n",
       "williamson             4.0                  -0.1  \n",
       "klobuchar              8.0                  -0.7  \n",
       "de_blasio             10.0                  -1.0  "
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "liz_lads_opinion_totals = create_opinion_table(liz_lads_value_counts)\n",
    "liz_lads_opinion_totals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Strongly unfavorable</th>\n",
       "      <th>Mildly unfavorable</th>\n",
       "      <th>Neither favorable nor unfavorable</th>\n",
       "      <th>Mildly favorable</th>\n",
       "      <th>Strongly favorable</th>\n",
       "      <th>total_respondents</th>\n",
       "      <th>total_positive</th>\n",
       "      <th>total_negative</th>\n",
       "      <th>net_favorability_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>biden</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bernie</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>warren</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>harris</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.555556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pete</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beto</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-0.555556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>booker</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yang</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-0.222222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>castro</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.222222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gabbard</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.222222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>williamson</th>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-0.555556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>klobuchar</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de_blasio</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-0.555556</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Strongly unfavorable  Mildly unfavorable  \\\n",
       "biden                        0.0                 1.0   \n",
       "bernie                       2.0                 1.0   \n",
       "warren                       1.0                 0.0   \n",
       "harris                       1.0                 0.0   \n",
       "pete                         0.0                 2.0   \n",
       "beto                         1.0                 4.0   \n",
       "booker                       0.0                 2.0   \n",
       "yang                         0.0                 4.0   \n",
       "castro                       0.0                 0.0   \n",
       "gabbard                      2.0                 1.0   \n",
       "williamson                   5.0                 1.0   \n",
       "klobuchar                    0.0                 2.0   \n",
       "de_blasio                    3.0                 2.0   \n",
       "\n",
       "            Neither favorable nor unfavorable  Mildly favorable  \\\n",
       "biden                                     4.0               4.0   \n",
       "bernie                                    2.0               2.0   \n",
       "warren                                    1.0               3.0   \n",
       "harris                                    2.0               1.0   \n",
       "pete                                      5.0               1.0   \n",
       "beto                                      4.0               0.0   \n",
       "booker                                    4.0               2.0   \n",
       "yang                                      3.0               1.0   \n",
       "castro                                    7.0               1.0   \n",
       "gabbard                                   5.0               1.0   \n",
       "williamson                                2.0               0.0   \n",
       "klobuchar                                 4.0               2.0   \n",
       "de_blasio                                 4.0               0.0   \n",
       "\n",
       "            Strongly favorable  total_respondents  total_positive  \\\n",
       "biden                      0.0                9.0             4.0   \n",
       "bernie                     2.0                9.0             4.0   \n",
       "warren                     4.0                9.0             7.0   \n",
       "harris                     5.0                9.0             6.0   \n",
       "pete                       1.0                9.0             2.0   \n",
       "beto                       0.0                9.0             0.0   \n",
       "booker                     1.0                9.0             3.0   \n",
       "yang                       1.0                9.0             2.0   \n",
       "castro                     1.0                9.0             2.0   \n",
       "gabbard                    0.0                9.0             1.0   \n",
       "williamson                 1.0                9.0             1.0   \n",
       "klobuchar                  1.0                9.0             3.0   \n",
       "de_blasio                  0.0                9.0             0.0   \n",
       "\n",
       "            total_negative  net_favorability_pct  \n",
       "biden                  1.0              0.333333  \n",
       "bernie                 3.0              0.111111  \n",
       "warren                 1.0              0.666667  \n",
       "harris                 1.0              0.555556  \n",
       "pete                   2.0              0.000000  \n",
       "beto                   5.0             -0.555556  \n",
       "booker                 2.0              0.111111  \n",
       "yang                   4.0             -0.222222  \n",
       "castro                 0.0              0.222222  \n",
       "gabbard                3.0             -0.222222  \n",
       "williamson             6.0             -0.555556  \n",
       "klobuchar              2.0              0.111111  \n",
       "de_blasio              5.0             -0.555556  "
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "warren_wary_opinion_totals = create_opinion_table(warren_wary_value_counts)\n",
    "warren_wary_opinion_totals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>liz_lads</th>\n",
       "      <th>warren_wary</th>\n",
       "      <th>difference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>biden</th>\n",
       "      <td>-100</td>\n",
       "      <td>33</td>\n",
       "      <td>-133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bernie</th>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>warren</th>\n",
       "      <td>100</td>\n",
       "      <td>66</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>harris</th>\n",
       "      <td>10</td>\n",
       "      <td>55</td>\n",
       "      <td>-45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pete</th>\n",
       "      <td>-10</td>\n",
       "      <td>0</td>\n",
       "      <td>-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beto</th>\n",
       "      <td>-60</td>\n",
       "      <td>-55</td>\n",
       "      <td>-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>booker</th>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yang</th>\n",
       "      <td>10</td>\n",
       "      <td>-22</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>castro</th>\n",
       "      <td>40</td>\n",
       "      <td>22</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gabbard</th>\n",
       "      <td>-60</td>\n",
       "      <td>-22</td>\n",
       "      <td>-37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>williamson</th>\n",
       "      <td>-10</td>\n",
       "      <td>-55</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>klobuchar</th>\n",
       "      <td>-70</td>\n",
       "      <td>11</td>\n",
       "      <td>-81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>de_blasio</th>\n",
       "      <td>-100</td>\n",
       "      <td>-55</td>\n",
       "      <td>-44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            liz_lads  warren_wary  difference\n",
       "biden           -100           33        -133\n",
       "bernie            10           11          -1\n",
       "warren           100           66          33\n",
       "harris            10           55         -45\n",
       "pete             -10            0         -10\n",
       "beto             -60          -55          -4\n",
       "booker             0           11         -11\n",
       "yang              10          -22          32\n",
       "castro            40           22          17\n",
       "gabbard          -60          -22         -37\n",
       "williamson       -10          -55          45\n",
       "klobuchar        -70           11         -81\n",
       "de_blasio       -100          -55         -44"
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "liz_vs_world = pd.DataFrame({\"liz_lads\": liz_lads_opinion_totals[\"net_favorability_pct\"], \"warren_wary\": warren_wary_opinion_totals[\"net_favorability_pct\"]})\n",
    "liz_vs_world[\"difference\"] = liz_vs_world[\"liz_lads\"] - liz_vs_world[\"warren_wary\"]\n",
    "(liz_vs_world * 100).astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, sharey=True, figsize = (8, 10))\n",
    "\n",
    "fig.suptitle(\"Liz Lads v. Warren-Wary: Net Favorability\", fontsize=36)\n",
    "\n",
    "category_labels = [\"Warren\", \"Other\"]\n",
    "\n",
    "curr_ax = ax\n",
    "curr_ax.bar(category_labels, liz_vs_world.loc[\"biden\", [\"liz_lads\", \"warren_wary\"]], color=['C0', 'C1'])\n",
    "curr_ax.set_title(\"Joe Biden\")\n",
    "curr_ax.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}