{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bars plots\n",
    "\n",
    "Now that we have an understanding of the core components of plots and some basic plot types, let's dive more deeply into bar plots and the ways we can customize them, in particular, how we can make stacked and grouped bar plots. To begin with, let's create some data that we'll plot for this exercise that shows the output of grain, wheat and barley in tons, for three different farms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>Grain</th>\n",
       "      <th>Wheat</th>\n",
       "      <th>Barley</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Farm A</th>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Farm B</th>\n",
       "      <td>15</td>\n",
       "      <td>98</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Farm C</th>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Grain  Wheat  Barley\n",
       "Farm A     50     75      36\n",
       "Farm B     15     98      33\n",
       "Farm C      0     20      77"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%config InlineBackend.figure_format = 'retina'\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "data = {\n",
    "    \"Farm A\": [50, 75, 36],\n",
    "    \"Farm B\": [15, 98, 33],\n",
    "    \"Farm C\": [0, 20, 77],\n",
    "}\n",
    "columns = [\"Grain\", \"Wheat\", \"Barley\"]\n",
    "\n",
    "farm_data = pd.DataFrame.from_dict(data, orient=\"index\", columns=columns)\n",
    "farm_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Standard bar plots\n",
    "\n",
    "We can make bar plots in one of two directions: vertical or horizontal. We've already seen vertical bar plots, but lets revisit those by looking at the total grain, wheat, and barley output across the three farms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Grain      65\n",
       "Wheat     193\n",
       "Barley    146\n",
       "dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total = farm_data.sum()\n",
    "total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Quantity (Tons)')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 433,
       "width": 571
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.bar(total.index, height=total.values)\n",
    "ax.set_xlabel(\"Crop Type\")\n",
    "ax.set_ylabel(\"Quantity (Tons)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Creating a horizontal bar plot instead is trivial using the `barh` command which just swaps the x and y axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Crop Type')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Tpk3Ttm3bbL755tl///0zcODArLHGGgu169y5c0aOHJlzzjknt956a/7zn/+kefPm6dKlS77yla/ku9/97iL3W9723HPPvPXWWxk8eHDuuOOOPP/88/nwww+zyiqrpEOHDtl0003Tq1evHHLIIdlkk01q7Ktp06Y57LDDKmGe0/4AAACAulYql8vlhi6CFcNuu+2WoUOHZtNNN60sLL88vffee+ncuXOSpONJQ9K4dfvlfkwAAFhRjDm7b0OXAKwk5v/8/e6776ZTp04NVovF1KmV119/PUOHDk0y7yqAAAAAAHVNUEWt/P73v08ybzH5AQMGNHA1AAAAwMrIGlUs0rRp0zJ27NhMnTo1t99+ey677LIk867+1769U/AAAACAuieoYpGefPLJ7LHHHgvc16lTp/zyl79soIoAAACAlZ1T/6hRqVTKuuuum6OOOirDhg1L27ZtG7okAAAAYCVlRhWL1Lt377ggJAAAAFCfzKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAAqhcUMXALXxxM/2SqdOnRq6DAAAAGA5MqMKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAaN3QBUBs9z3owjVu3b+gyAAAAoFpjzu7b0CWs8MyoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKoXF9H/DNN9/MlVdemeHDh2fChAmZNm1a7rnnnnTt2rXSZtSoUXnnnXfSsmXL9OrVq75LBAAAAKAB1FtQNXfu3PzkJz/J+eefn7lz56ZcLidJSqVSZs6cuUDbd999NwcccEAaN26c0aNHp2PHjvVVJgAAAAANpN5O/fvmN7+ZP/zhD5kzZ07WXXfdHHroodW23W+//bLhhhtmzpw5uemmm+qrRAAAAAAaUL0EVQ8//HAuu+yyJMnPfvazjBkzJjfccEON+xx22GEpl8v597//XR8lAgAAANDA6uXUv4svvjhJsv/+++fMM8+s1T477LBDkuSll15abnUBAAAAUBz1MqNq+PDhKZVKOf7442u9T6dOnZIkEyZMWF5lAQAAAFAg9RJUTZw4MUmywQYb1Hqfxo3nTfaaNWvWcqkJAAAAgGKpl6CqRYsWSZKpU6fWep933nknSbLGGmssl5oAAAAAKJZ6CaqqZlI9++yztd7njjvuSJJsttlmy6UmAAAAAIqlXoKqffbZJ+VyOZdccknmzp272PbPPPNMrrrqqpRKpey77771UCEAAAAADa1egqqTTz45LVq0yIsvvpgTTzyxxnWn/vnPf2bffffNzJkz07p163zjG9+ojxIBAAAAaGCN6+MgHTt2zJ///OeceOKJGTJkSO67777069evsv2yyy7L1KlT88ADD+Ttt99OuVxOqVTKJZdcktVXX70+SgQAAACggdVLUJUkxx9/fEqlUk455ZSMHTs2f/vb31IqlZIk559/fpKkXC4nSZo1a5aLL744hx12WH2VBwAAAEADq5dT/6ocd9xxefXVV/ODH/wgG220Ucrl8gJfHTt2zEknnZRXXnklAwYMqM/SAAAAAGhg9TajqkqnTp3y+9//Pr///e/z2WefZeLEiZkzZ07atWuX9u3b13c5AAAAABREvQdV82vdunVat27dkCUAAAAAUBD1euofAAAAAFSnQWZUPfPMM3nggQcyatSofPTRR0mStm3bZosttsiXv/zlbLfddg1RFgAAAAANqF6DqhEjRuQ73/lORowYUW2bn/3sZ+nRo0cuvPDC9OjRox6rAwAAAKAh1dupfzfccEN22WWXjBgxonKVvyZNmmSttdbKmmuumSZNmlTuf/rpp7PLLrvkxhtvrK/yAAAAAGhg9RJUvfrqqxkwYEBmzZqVRo0a5aSTTsrTTz+dKVOmZNy4cRk/fnymTJmSESNG5KSTTkrjxo0za9asHHPMMXn11Vfro0QAAAAAGli9BFXnnHNOZsyYkebNm+e+++7LhRdemO222y6NGjWqtGnUqFG23XbbXHjhhbn//vvTvHnzzJw5M7/73e/qo0QAAAAAGli9BFUPPvhgSqVSvve976V3796Lbd+rV69873vfS7lczgMPPLD8CwQAAACgwdVLUDVp0qQkyf7771/rffr27bvAvgAAAACs3OolqOrQoUOSpHnz5rXep1mzZkmS9u3bL5eaAAAAACiWegmqdtlllyTJ008/Xet9nnrqqSTJrrvuulxqAgAAAKBY6iWo+sEPfpBGjRrlrLPOqtWpfBMnTsxvf/vbNGnSJN///vfroUIAAAAAGlq9BFXbb799/va3v2XixInZcccd869//Stz585dqN3cuXNz6623ZqeddsqkSZNy0UUXZYcddqiPEgEAAABoYI3r4yDHHXdckmSzzTbL888/n0MOOSRrrLFGttlmm6y55poplUp5//3389xzz+Wjjz5Kkmy11VYZOnRohg4dusg+S6VSLrvssvooHwAAAIB6UCqXy+XlfZBVVlklpVKp8n3VIee/r6b7/1u5XE6pVMqcOXPquFKK5L333kvnzp2TJB1PGpLGrS2sDwAAQHGNObtvQ5ewVOb//P3uu++mU6dODVZLvcyoWm+99RYbPgEAAADwxVYvQdWYMWPq4zAAAAAArMDqZTF1AAAAAFgcQRUAAAAAhVAvQdW3vvWtPP300/VxKAAAAABWUPUSVF1yySXp2bNntthii5x//vn54IMP6uOwAAAAAKxA6iWoatKkScrlcl5++eX88Ic/TKdOnXLooYfmzjvvzNy5c+ujBAAAAAAKrl6CqvHjx+f888/P1ltvnXK5nJkzZ+aWW27JgQcemPXWWy8///nP8+abb9ZHKQAAAAAUVL0EVW3bts0pp5ySkSNH5tlnn83JJ5+ctm3bplwuZ9y4cTn77LOzySabZPfdd8+VV16ZqVOn1kdZAAAAABRIvV/1b6uttsqf//znjBs3LjfeeGP222+/rLLKKimXyxk2bFgGDhyYddZZJ9/4xjfyxBNP1Hd5AAAAADSQeg+qqjRp0iSHHHJI7rzzzrzzzjs566yz0q1bt5TL5Xz++ee57LLLsssuu2SzzTbLeeedl4kTJzZUqQAAAADUgwYLqua3zjrr5Kc//WleeeWV3HXXXVl77bWTJOVyOa+99lp+/OMfp3PnzjnyyCMzcuTIBq4WAAAAgOWhEEFVkjz66KMZOHBgDjvssLz//vspl8tJktatW6dcLmfWrFm58cYbs8MOO+SUU05xtUAAAACAlUyDBlXvvvtuzjzzzHTt2jV77LFHrrzyykyZMiWlUin77rtvbrrppkyaNClvvPFGTj311LRr1y5z587NhRdemL/85S8NWToAAAAAdazeg6oZM2bk2muvzT777JMNNtgggwYNyttvv51yuZzOnTvnjDPOyJgxY3LXXXfl4IMPTuPGjbPRRhvlN7/5Td56663sueeeKZfLueSSS+q7dAAAAACWo8Z13eFxxx2XUqmUM888M+uss07l/qeeeiqDBw/Oddddl88++yzJvDWomjRpkgMPPDAnnHBC9tlnn5RKpWr7Xm211XLGGWfkoYceyltvvVXXpQMAAADQgOo8qBoyZEhKpVJ++MMfVoKqzTffPK+++mqSVNae2mSTTXL88cdnwIAB6dChQ637r+pz5syZdVw5AAAAAA2pzoOqRXnllVeSJC1atMhhhx2WE044IbvuuutS9dW6descc8wxNc68AgAAAGDFUy9B1TbbbJMTTjghX//619O6detl6qtDhw4ZMmRI3RQGAAAAQGHUS1D1zDPP1MdhAAAAAFiB1ftV/wAAAABgUQRVAAAAABTCcjv1769//WvWXHPNOunr9NNPr5N+AAAAACiu5RZUXXTRRXXWl6AKAAAAYOW33IKqcrlcJ/2USqU66QcAAACAYltuQdXll1+eDTbYYHl1DwAAAMBKZrkFVTvssEM222yz5dX9CqVqVtigQYNyxhlnNGwxAAAAAAX1hbvq35w5c9K6deuUSqVsu+22NbYtl8tp165dSqVSSqVSLr/88hrbX3/99ZW2559/fh1WDQAAALDy+8IFVY0aNcrOO++cJHn++efz6aefVtv2pZdeykcffVT5/tFHH62x78cee6xye/fdd1/GSotpzJgxlTBuyJAhDV0OAAAAsBL5wgVVyf8PkebOnZvHH3+82nZVwVOjRo0W+H5x7Vu3bp2tttqqLkoFAAAA+ML4QgdVSc2zpKqCp8MOOyxJ8vbbb2fs2LGLbPvJJ59k1KhRSZJddtmlEm4BAAAAUDtfyKBqhx12SPPmzZPUPEuqalv//v2zySab1Nh+6NChmTt3bpKV97Q/AAAAgOWpzoOqQYMG5fTTT8+aa65Z113XmaZNm2bHHXdMkjz99NOZPn36Qm3GjBmT9957L0my6667Ztddd01S/QysJVmf6umnn85Xv/rVdOrUKc2aNUvHjh1z9NFH55VXXqlV/a+99lpOOeWUbL755ll99dXTokWLbLjhhhk4cGBGjhxZ477jx4/PX//61xx66KHZeOON07Jly0oNBx10UK6//vpK4PbfSqVSNthgg8r3AwcOrKxXVfXlqoYAAADA0mpc1x0OGjSorrtcLnbfffc88sgjmTlzZp588sn06tVrge1VwdOGG26YddddN7vuumsuu+yyamdUVQVYLVq0SI8ePao97l/+8pd8//vfz+zZsyv3jRs3LldffXVuvvnm3H333TUGXb/+9a/zq1/9aoH9k2T06NEZPXp0rrjiivziF7/IL3/5y4X2nTNnTjp16rTIIGrcuHG57bbbctttt+Wyyy7LzTffnFatWlVbBwAAAEBdq/OgakXx3+tUVRdUVc2kqvq36kqAbdu2rbSdNm1annnmmSRJz54907Rp00Ue8957782TTz6ZLbfcMt/97nfTvXv3TJs2Lbfcckv+9Kc/ZerUqTn66KPzxhtvLLKP008/Pb/+9a+TJDvvvHOOO+64bL755mnSpElee+21/OUvf8nw4cPzq1/9Ku3bt8///M//LLB/uVxOkuy5557Zb7/90r1793To0CGff/553n777fz973/P8OHDc//99+c73/lOrrjiigX2f/HFFzNu3Lj06dMnSXLmmWfmoIMOWqDNksykq5qxVp3x48fXui8AAABgxfeFDap22mmnNGnSJLNmzVrkLKmq+3bbbbckSdeuXbP22mtnwoQJGTp0aA488MBK2yeeeCKzZs1KUvNpf0888UT233//3HLLLQsEUbvttlvatWuX0047Le+8807uvPPO9O/ff4F9n3766fzmN79Jkpx22mmVwKrKdtttlyOPPDIDBgzI1VdfnZ///Oc5+uij06ZNm0qbRo0a5bXXXkvXrl0Xqq1Xr14ZOHBgBg0alF/96le56qqrctppp2XjjTeutNliiy0WmGXVsWPHbLHFFtU+3sXp3LnzUu8LAAAArHy+kIupJ0nLli2z7bbbJkmGDx++wKl0kyZNyquvvprk/wdVybyr+SULr1NV2/WpmjdvnsGDBy9yttQpp5xSuX9Rwdk555yTuXPnZrvttsuvfvWrRfa/yiqr5IILLkizZs3y+eef56abblpge6lUWmRINb/TTz897du3T7lczm233VZjWwAAAIC69IUNqpL/HypNnjw5zz77bOX+oUOHJkk6dOhQudpf8v9P//vvIKkquGratGl22mmnao+39957V3tq3GqrrVaZvfT2228vsG3WrFm5++67kySHHnpoSqVStcdo06ZNunfvnmReAFeTuXPnZty4cXnttdcyatSojBo1Kq+88ko6deqUJHn++edr3H9ZvfvuuzV+PfXUU8v1+AAAAECxfGFP/UvmzZY699xzk8wLm7bffvskC69PNX/7JBk5cmSmTJmSli1bZvbs2XniiSeSJD169EiLFi2qPd6XvvSlGuupWvfq888/X+D+l19+OVOnTk2SnHrqqTn11FNr9fgmTJiw0H3lcjnXXHNNLrvssjz55JOZNm1atft/8MEHtTrO0qoKxAAAAACSL/iMqt122y2rrDLvRzD/LKnqgqqtt946rVq1yuzZsyuzlapCq6Tm0/6SZNVVV61xe1Utc+bMWeD+iRMnLu6hLFJVuFVl+vTp6du3b44++ug8/PDDNYZUSRa7HQAAAKAufaFnVLVp0yZbbLFFXnjhhQwdOjTlcjlTpkypnAY4//pUybzFyHv27JkHHnggjz76aL785S8vsF7V4oKqpTV/cHXuuedm3333rdV+LVu2XOD73/zmN5VTCHv16pXvfOc72XbbbbP22munRYsWlaBs9913z2OPPVa5SiAAAABAffhCB1XJvFDmhRdeyIcffpiXX345Y8eOzZw5c9KyZctss802C7Xfdddd88ADD1RmXVX926hRo8pi63WtXbt2lduzZs1aqivtlcvlXHrppUnmPYaHHnqoEkz9t48//njpCgUAAABYBg126l+5XM5bb72Vp59+Ok8//XTeeuutBpnBM/8sqEcffbQSPPXs2TONGy+c41WdDvjkk09mxowZGTZsWJJkq622SuvWrZdLjZtvvnnlioD33XffUvXx0UcfVdasOvzww6sNqSZPnpzXXnut2n5qWsgdAAAAYFnUe1B19913p1+/fmndunW6deuWnj17pmfPnunWrVtat26dfv36VU5Pqw/zB1WPPfZYtetTVakKsKZNm5YrrrgiH3744UL91LVVV101e+21V5Lk4YcfXqqr4c2ePbty+7/XrprfZZddllmzZlW7vXnz5pXbM2bMWOI6AAAAAKpTb0HVlClT8pWvfCUHHHBA7rrrrkyZMiXlcnmBrylTpuSuu+7KAQcckP79+1cWKV+e1lprrXTr1i3JgiHQf69PVaVly5bZeuutkyTnnHNO5f7lGVQlyc9//vPKbKYjjzwyb731VrVt58yZk3/84x957733Kvd16NAhbdq0SZJcd911mTlz5kL7Pf300znttNNqrKNdu3aV2V011QAAAACwpOpljaq5c+dmv/32y7Bhw1Iul9OkSZPss88+2WGHHbLWWmulXC5n4sSJefrpp3Pfffdl5syZue2227L//vvn4YcfXu6nm+2+++55/fXXM378+CRJ48aN07Nnz2rb77rrrhkxYkTefvvtJPNOh6su2Koru+yyS04//fT88pe/zOjRo7P11lvn+OOPzz777JN11lknM2bMyJgxYzJ8+PDcdNNNGTduXF588cV06tQpybwrCn7961/PhRdemOeeey677bZbvv/976dr16759NNPc9ddd+Wvf/1rWrVqlXXXXTevv/76Iuto3Lhxtt9++wwbNiyXX355ttlmm2y99dZp0qRJkqRt27Zp27btcv1ZAAAAACunegmqLr744gwdOjSlUil9+vTJpZdemo4dOy6y7dixY3PiiSfmnnvuydChQ3PxxRfnpJNOWq717b777pWFxpNkm222WeiKefPbddddc/7551e+33TTTdO+ffvlWWKS5IwzzkibNm3y05/+NJMnT86f/vSn/OlPf1pk26ZNmy5wml4y76p/w4YNy3PPPZennnoqX/3qVxfY3rZt2/zzn//M6aefXm1QlSSnnnpq+vXrlw8//DBf+9rXFtg2aNCgnHHGGUv3AAEAAIAvtHo59e/KK69Mkmy//fa58847qw2pkqRjx465/fbbs8MOO6RcLueKK65Y7vX992l71a1PVeW/Z08t79P+5ve9730vb731Vn7xi1+kZ8+ead++fRo3bpyWLVumW7duOeSQQ3LxxRdn7Nix6dq16wL7rr766hk2bFh+/etfp3v37mnevHlatWqVTTfdND/60Y/y/PPP1+qx9O3bNw8++GAOOuigrLvuupXZVAAAAADLolSuh0vtrb766pk8eXL+8Y9/5IgjjqjVPjfccEOOPPLIrLbaavn000+Xc4UU0XvvvZfOnTsnSTqeNCSNWy//WWsAAACwtMac3behS1gq83/+fvfddyvLCDWEeplRVbXGVNWi5bWx8cYbL7AvAAAAACu3egmqNtpooyTJxIkTa71PVduqfQEAAABYudVLUPXVr3415XK5slZVbVx55ZUplUq1PlUQAAAAgBVbvQRVp5xySrbddttcd911+d3vfrfY9ueee26uvfbabLPNNvne9763/AsEAAAAoME1ro+DTJgwIZdeemm++c1v5tRTT821116bAQMGZPvtt8+aa66ZUqmU999/P08//XSuuuqqPPfcc9l+++1zySWXZMKECdX2u95669VH+QAAAADUg3oJqrp06bLAougvvPBCfvjDH9a4z4gRI7LttttWu71UKmX27Nl1ViMAAAAADategqokKZfL9XUoAAAAAFZA9RJUDR48uD4OAwAAAMAKrF6CqgEDBtTHYQAAAABYgdXLVf8AAAAAYHEEVQAAAAAUQr0tpj6/999/Pw8//HBGjRqVjz76KEnStm3bbLHFFundu3fWWmuthigLAAAAgAZUr0HV+PHj84Mf/CA333xzZs+evcg2jRo1yqGHHprzzjsv66yzTn2WBwAAAEADqrdT/55//vlsueWWueGGGzJr1qyUy+VFfs2ePTvXX399ttpqq7z44ov1VR4AAAAADaxegqopU6akb9+++fDDD1Mul/PlL385119/fcaMGZPp06dn+vTpGTNmTG644Ybss88+KZfL+eCDD9K3b99MnTq1PkoEAAAAoIHVS1D1l7/8JePGjcsqq6ySv//977nvvvty2GGHZb311kvTpk3TtGnTrLfeejn00ENzzz335NJLL02pVMrYsWNz4YUX1keJAAAAADSwegmqbr311pRKpRx77LE5/vjjF9v+uOOOy8CBA1Mul3PLLbfUQ4UAAAAANLR6Capef/31JMmRRx5Z632++tWvLrAvAAAAACu3egmqJk+enCRp27ZtrfdZY401ksxb3woAAACAlV+9BFUdOnRIkrzyyiu13qeqbfv27ZdLTQAAAAAUS70EVT179ky5XM4f/vCHzJ49e7HtZ82alfPOOy+lUik9e/ashwoBAAAAaGj1ElQdc8wxSZLnnnsuffv2zbhx46ptO3bs2BxwwAF57rnnkiTHHntsPVQIAAAAQENrXB8H6devX77yla/kX//6Vx544IFsuOGG2XvvvbPjjjtmrbXWSqlUyoQJE/Lkk0/m/vvvz6xZs5Ik/fv3T9++feujRAAAAAAaWL0EVUly7bXX5phjjsmNN96YmTNn5q677spdd921ULtyuZwkOeyww3LllVfWV3kAAAAANLB6OfUvSZo1a5brr78+t99+e/bbb7+0aNEi5XJ5ga8WLVpkv/32yx133JHrr78+zZo1q6/yAAAAAGhg9Tajqkrfvn3Tt2/fzJkzJ2+//XY++uijJEnbtm2z4YYbplGjRvVdEgAAAAAFUC9B1Z577pkkOfroozNw4MAkSaNGjbLxxhvXx+EBAAAAWAHUy6l/jz32WB555JF06dKlPg4HAAAAwAqoXoKqNddcM0nSpk2b+jgcAAAAACugegmqttpqqyTJ66+/Xh+HAwAAAGAFVC9B1QknnJByuZyLL764Pg4HAAAAwAqoXoKqgw8+OEcddVQeeeSRHHfccZkyZUp9HBYAAACAFUi9XPXvyiuvzF577ZUXXnghV1xxRW699db069cvW265ZdZYY400atSoxv2POeaY+igTAAAAgAZUL0HVsccem1KpVPn+448/zlVXXVWrfUulkqAKAAAA4AugXoKqJCmXyzV+DwAAAMAXW70EVaNHj66PwwAAAACwAquXoGr99devj8MAAAAAsAKrl6v+AQAAAMDiCKoAAAAAKITlElTdfffd2XbbbbPtttvmH//4xxLte80111T2feCBB5ZHeQAAAAAUUJ0HVeVyOd///vfz/PPPp127dvna1762RPt/7WtfS7t27fLcc8/lhz/8YV2XBwAAAEBB1XlQ9dBDD+X111/PKquskvPPP3+J9y+VSvnTn/6URo0aZdSoUXn44YfrukQAAAAACqjOg6p//vOfSZK99947m2+++VL1sdlmm6VPnz4L9AcAAADAyq3Og6qnnnoqpVIp/fr1W6Z+DjjggJTL5TzxxBN1VBkAAAAARVbnQdV//vOfJMkmm2yyTP1069YtSTJmzJhlLQkAAACAFUCdB1WffvppkqRt27bL1E/V/p999tky1wQAAABA8dV5UNW6deskySeffLJM/VTtv9pqqy1jRQAAAACsCOo8qFpzzTWTJC+//PIy9fPKK68s0B8AAAAAK7c6D6p22GGHlMvl3HbbbcvUz6233ppSqZTtt9++jioDAAAAoMjqPKjab7/9kiT3339/Hn300aXq49FHH8199923QH8AAAAArNzqPKg65JBDsuGGG6ZcLufwww/Pa6+9tkT7v/766zn88MNTKpXSpUuXHHrooXVdIgAAAAAFVOdBVePGjXPeeeelVCpl0qRJ6dGjR/74xz9m8uTJNe43efLknH/++enRo0cmTpyYJDnvvPPSuHHjui4RAAAAgAJaLinQQQcdlDPPPDM///nPM3Xq1PzoRz/KoEGDsttuu2XbbbfNWmutlZYtW2bKlCl5//33M3LkyDz22GOZMmVKyuVykuSXv/xlvvKVryyP8gAAAAAooOU2XenUU09Np06d8u1vfztTpkzJ5MmTc8899+See+5ZZPuqgGrVVVfNX/7ylxx77LHLqzQAAAAACqjOT/2b39FHH53XX389P/zhD9OhQ4eUy+Vqv9q3b58f/ehHef3114VUAAAAAF9Ay30BqHXWWSfnnntuzj333Lz88st5/vnn88EHH+Tzzz/Paqutlvbt22errbbKZptttrxLAQAAAKDA6nWl8s0220wgBQAAAMAiLddT/wAAAACgtgRVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABRC44YuAGrjiZ/tlU6dOjV0GQAAAMByZEYVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCE0bugCoDZ6nvVgGrdu39BlANSLMWf3begSAACgQZhRBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKg6gtoyJAhKZVKKZVKGTNmTEOXAwAAAJAkadzQBazo5s6dm9tuuy333ntvHn/88UyYMCEff/xxmjdvnvbt26d79+7ZaaedcvDBB6dbt24NXS4AAABAYQmqlsFdd92VH/7wh3n11VcX2jZr1qx8/vnnGT16dG677baceuqp6dWrV84666zsvPPODVAtAAAAQLEJqpbSOeeck1NPPTXlcjlJsssuu6Rfv37ZZptt0q5du0yfPj3vv/9+hg0bljvvvDOvvfZaHnnkkfzqV7/KPffc06C1H3vssTn22GMbtAYAAACA/yaoWgpXXnllfvrTnyZJ2rdvn2uuuSb77LPPItsefPDB+f3vf5/bb789p556an2WCQAAALBCEVQtobFjx+Zb3/pWkqRly5Z59NFHs+mmm9a4T6lUyoEHHph99tknt99+e32UCQAAALDCcdW/JfSHP/wh06ZNS5KceeaZiw2p5te8efMcdthhC91fdQW+M844I0ny0EMP5bDDDkvnzp3TpEmTdOnSZYH2o0aNyplnnpk+ffqkU6dOadasWVq1apWNN944AwYMyBNPPFFjHYu76l/v3r1TKpXSu3fvJPPCuR/84Afp2rVrWrRokXbt2qVPnz65++67a/3YAQAAABbHjKolUC6Xc+WVVyZJWrVqleOPP77Oj/Hzn/88Z511VrXbH3744eyxxx4L3T9z5sy8+eabefPNNyunJv72t79d5nqGDh2ar3zlK/nwww8r902fPj333Xdf7rvvvpx77rn50Y9+tMzHAQAAABBULYGXXnopH3zwQZJkt912y2qrrVan/d9yyy154YUX0r1793z/+9/PFltskWnTpuW5556rtJk9e3ZatmyZvn37Zs8998yXvvSltG7dOhMnTsxLL72UP//5z/nPf/6Ts88+O926dcvAgQOXup7x48enf//+adSoUc4+++zsuuuuadq0aYYOHZpf/epX+eSTT3Lqqadmv/32y+abb77E/b/33nuLPT4AAADwxSGoWgIvvPBC5fa22267XPrfa6+9cuedd6ZZs2aV+3fffffK7a233jrvvfde2rRps9D+ffr0ycknn5wDDjgg999/f375y1/mmGOOSaNGjZaqntdffz3rr79+hg0blo4dO1bu33777bP99ttn9913z+zZs3PJJZfkT3/60xL337lz56WqCwAAAFg5CaqWQNVsqiTp0KFDjW1feumllMvlRW7bYIMN0rJly4XuX2WVVXLppZcuEFL9t/bt29d43KZNm+bcc8/N1ltvnf/85z957rnnst1229W4T00uuOCCBUKqKrvuumt23HHHPPHEE3nssceWun8AAACAKoKqJfD5559Xbrdq1arGtltttVXmzJmzyG3//ve/KwuVz2+XXXZZaOH0xZkxY0bef//9TJ48OXPnzk2SBQKy559/fqmDqjZt2qRv377Vbt9uu+3yxBNP5O23316q/t99990at48fPz477LDDUvUNAAAArHgEVUtg/jWppkyZUuf9b7nllrVqN2XKlPz5z3/Oddddl5deeqnaQCxZcBbYktp4442zyirVXxiybdu2SRYM8JZEp06dlmo/AAAAYOVUfQrBQtq1a1e5PWnSpBrbzp49O+VyufI1aNCgxfa/xhprLLbNmDFj0r179/zsZz/LCy+8UGNIlSTTpk1bbJ/VWXXVVWvcXhViVc3kAgAAAFgWgqolsNVWW1Vujxw5ss77r82i50cffXRGjx6dUqmU4447Lvfdd1/efffdTJ8+vRKKzR9eVbdOFgAAAEDROPVvCWy++eZp165dPvzwwzz22GOZMmXKIhdFX15effXVDB06NEly6qmn5je/+c0i23388cf1VhMAAABAXTGjagmUSqUcc8wxSeatyzRkyJB6Pf5LL71UuX3kkUdW227EiBH1UQ4AAABAnRJULaEf/OAHadGiRZLkZz/7Wd588816O/bs2bMrt6dOnVptu4svvrg+ygEAAACoU4KqJdSpU6dceOGFSZLPPvssu+22Wx5++OHF7lcXp+NtvPHGldtXXHHFIttcdNFF+de//rXMxwIAAACob9aoWgoDBw7M2LFjc/rpp2fChAnZY489svvuu+fAAw/MlltumXbt2qVcLmfixIl5/vnnc8stt+Spp56q7F81I2tJbbPNNtliiy0yatSoXHTRRfnkk0/y9a9/Peuss07efffdXH311bnpppuyyy67ZNiwYXX1cAEAAADqhaBqKZ122mnZaqut8sMf/jBvvPFGHn300Tz66KM17rPLLrvknHPOyY477rhUxyyVSrnqqquy55575uOPP861116ba6+9doE23bt3z4033ph11113qY4BAAAA0FAEVcugX79+2X///XPbbbflnnvuyfDhwzNhwoR8/PHHadGiRdq2bZvNN988O+ywQw477LBsttlmy3zMrbfeOs8991x++9vf5u677864ceOy2mqrpWvXrjn88MPzne98J82bN6+DRwcAAABQv0rlcrnc0EXAorz33nvp3LlzkqTjSUPSuHX7Bq4IoH6MObtvQ5cAAMAXyPyfv99999106tSpwWqxmDoAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABRC44YuAGrjiZ/tlU6dOjV0GQAAAMByZEYVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAApBUAUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACqFxQxcA1Zk9e3bl9vjx4xuwEgAAAFh5zf+Ze/7P4g1BUEVhTZo0qXJ7hx12aMBKAAAA4Ith0qRJ6dKlS4Md36l/FNb777/f0CUAAAAA9ciMKgrrS1/6UuX2448/ns6dOzdgNSwv48ePr8yYe+qpp7LOOus0cEUsD57nLw7P9ReD5/mLw3P9xeB5/mLwPH9xLM1zPXv27MpZTd27d1+u9S2OoIrCat68eeV2586d06lTpwashvqwzjrreJ6/ADzPXxye6y8Gz/MXh+f6i8Hz/MXgef7iWJLnuiFP95ufU/8AAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAAAAUgqAKAAAAgEIQVAEAAABQCIIqAAAAAAqhVC6Xyw1dBAAAAACYUQUAAABAIQiqAAAAACgEQRUAAAAAhSCoAgAAAKAQBFUAAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqKKQ3nnnnfzoRz/KpptumpYtW6Zt27bZYYcd8vvf/z5Tp05t6PKoxsiRI3PWWWdlv/32S+fOndOsWbO0atUq3bp1y7HHHpvHHntssX0MGTIkpVKpVl9DhgxZ/g+KRartc9S7d+/F9nXPPffk4IMPTqdOndKsWbN06tQpBx98cO65557l/0CoVu/evWv9PFd9Pfzwwwv0YTwXw8SJE3PHHXfk9NNPz3777Zf27dtXfu7HHnvsEvdXF2N26tSpOffcc7PDDjukbdu2adWqVTbddNP86Ec/yjvvvLPENVE3z/P06dNz66235n/+53+y4447pm3btmnSpEnatm2bnXbaKWeccUbGjx+/2H6W5PWDJVcXz3Vdvz4b03VvWZ/nMWPGLPH7eJcuXRbZlzG9/NTF56f5rTTv0WUomDvuuKO8+uqrl5Ms8muTTTYpv/XWWw1dJv9l9913r/Y5m//r6KOPLs+YMaPafgYPHlyrfpKUBw8eXH8PkAXU9jnq1atXtX3MnTu3/I1vfKPG/b/xjW+U586dW38PjIpevXrV+nlOUl5llVXK77333gJ9GM/FUNPPfcCAAbXup67G7JtvvlneZJNNqu1j9dVXL995553L+Ki/eJb1eX7++efLq6222mLH6mqrrVa+/vrra+xrSV4/WHJ1Mabr8vXZmF4+lvV5Hj169BK9jycp77PPPovsy5hePurq81O5vPK9RzcOFMjzzz+fww8/PFOnTk2rVq1y6qmnZo899si0adNy3XXX5e9//3tee+219O3bN08//XRatWrV0CXzf8aOHZskWXfddXPYYYdlt912y3rrrZc5c+Zk+PDhOe+88zJ27NhcddVVmT17dv7xj38sts9777036667brXbO3XqVGf1s3ROOumkfPvb3652e8uWLavddtppp+WSSy5JkmyzzTb58Y9/nI022ihvvfVWfve73+XZZ5/NJZdckg4dOuTMM8+s89qp2eDBgzNlypQa27z88ss54ogjkiR77bVXOnbsWG1b47kYOnfunE033TT33XffEu9bF2N28uTJOeCAA/Laa68lSU488cQceeSRadGiRf7973/nt7/9bT799NMcdthhGT58eLbccsulf7BfYEvzPH/22Wf5/PPPkyS77LJLDjjggPTo0SPt2rXLpEmTcvPNN+fSSy/N559/nq997WtZbbXVst9++9XYZ48ePTJ48OBleizUbFnGdJVleX02puvH0jzPHTt2zIsvvrjYdr/97W8r/y8fMGBAjW2N6bpVl5+fVrr36OUehcES6N27dzlJuXHjxuXHH398oe2/+93vKmnuL3/5ywaokOr07du3fP3115dnz569yO2TJk0qd+vWrfL8Pfroo4tsN/9f+EaPHr0cK2ZZVD1HgwYNWqr933jjjXLjxo3LSco9evQoT506dYHtU6ZMKffo0aPyevDmm2/WQdXUtR//+MeV34Wrrrpqoe3GczGcfvrp5dtvv708YcKEcrm84F/Zazv7oq7G7KBBgyrH/t3vfrfQ9scff7xynD322GPJHugX3LI+z8OGDSsffvjh5ZdeeqnaNv/617/KpVKpnKS80UYbVfuX+arZFzXNqmXp1cWYrqvXZ2N6+amL53lxZs+eXV533XUrsyWnTJmyyHbG9PJRV5+fVsb3aEEVhfHUU09VBsY3v/nNRbaZM2dOedNNNy0nKa+xxhrlmTNn1nOVLIvbb7+98hyfcsopi2zjg+2KYVmDqm9/+9uVPoYPH77INsOHD6+0Ofnkk5ehWpaHOXPmlDt27FhOUm7VqtUi/3NrPBfT0nzYqYsxO3PmzHKbNm3KScqbbrppec6cOYvs55vf/GalnxEjRtT6cbGg5fGhtlwulw855JBKvyNHjlxkGx9q61dDBVXGdP1aHmP6nnvuqfQ5cODAatsZ0w2nNp+fVsb3aIupUxj/+te/KrcHDhy4yDarrLJKjjnmmCTJxx9/vNDCvRTb/Atrv/XWWw1XCA2qXC7n1ltvTZJ86UtfSs+ePRfZrmfPntlkk02SzHt9KJfL9VYji/fggw9WpqwfeuihWXXVVRu4IpaXuhqzDz/8cD755JMk804vWWWVRf83dP5Fgm+++eZlrJ66tscee1Ruey//YjOmV3xXXnll5fbiTvujYSzu89PK+h4tqKIwqq5o0LJly2y33XbVtuvVq1fl9tChQ5d7XdSdmTNnVm5X9+LHym/06NGVgGP+8bwoVdvfe++9jBkzZnmXxhKY/z+3VX9AYOVUV2N2/isX1dRPjx49KuvbeZ8vnhkzZlRuey//YjOmV2yff/55ZaLA+uuvn913371hC2KRFvf5aWV9j/buQmG88sorSZKuXbumcePq1/n/0pe+tNA+rBgeeeSRyu35n8fqHHvssVlrrbXStGnTtG/fPj179sxpp51WeTGm4d14443ZZJNN0qJFi6y22mrZeOONM2DAgPz73/+udp/5x+3ifg+M92KaPHlybrnlliTJeuutt8Bf+6pjPK+46mrM1rafxo0bZ6ONNlpkHzS8JXkvf/XVV7P99ttntdVWS/PmzdOpU6ccdNBBufLKKzNr1qzlXSq1tLSvz8b0iu2mm27K1KlTk8z7g1OpVFrsPsZ0/Vvca+7K+h4tqKIQpk+fng8++CDJ4q/8tMYaa1RS3HfffXe510bdmDt3bs4+++zK94cffvhi93nkkUcyceLEzJo1Kx9++GGefPLJ/OY3v0nXrl3zt7/9bXmWSy29/PLLef311zN9+vRMnjw5b775Zq688srsueee6d+/fz799NOF9pl/3C5uvHfu3HmR+9Gw/vnPf1auCHj00UfX6j+3xvOKq67GbNX3LVu2TJs2bWrVz6RJkxaYwUPDev7553PnnXcmSTbffPNsttlmNbZ///33M2LEiEyePDkzZszI2LFjc9ttt2XAgAHZeuuthRYFsbSvz8b0im1pZkYb0/WrNp+fVtb36OqnrUA9qroccpK0atVqse1btmyZKVOmZPLkycuzLOrQH//4xzz11FNJkv79+6dHjx7Vtt1www1z8MEHZ6eddqq8EL799tv55z//mZtuuinTp0/Pt771rZRKpXzjG9+ol/pZ0KqrrpoDDzwwe+21V770pS+lVatWmTRpUh555JFcfPHF+fDDD/Ovf/0rBx10UO6///40adKksu+SjPeqUDqJ8V4gS/KfW+N5xVdXY7aqn9q+z8/fT7NmzWpVK8vPjBkzcsIJJ2TOnDlJkrPOOqvatqusskr22muv7L///tlqq63Srl27fP755xk5cmT+9re/5ZVXXsnLL7+cPfbYI0899VTWW2+9+noYzGdZX5+N6RXXO++8U5mps/POO6dr1641tjemG0ZtPj+trO/RgioKYfr06ZXbTZs2XWz7qsEwbdq05VYTdeeRRx7JT3/60yTJmmuumYsuuqjatv3798+AAQMWmqGx/fbb54gjjsgdd9yRgw8+OLNmzcr3v//9HHjggVl77bWXa/0sbOzYsYv8a8vee++d//mf/8l+++2XZ599No888kguuuiinHLKKZU2SzLe53/jM96L4b333qtcyKJnz57p1q1btW2N55VDXY3Zqn6W5H1+Uf3QME4++eSMGDEiybyFdg888MBq2958882LfI/Ybbfd8u1vfzsnnnhirrjiirz//vv53ve+Z4HtBlAXr8/G9Irr6quvriymXZvZVMZ0/avt56eV9T3aqX8UQvPmzSu3518wrjpVUwxbtGix3Gqibrz00kvp379/Zs+enWbNmuWGG27IWmutVW371VdfvcbTiA444IAMGjQoSTJ16tRcdtlldV4zi1fTlOC11lorN910U+WN7oILLlhg+5KM9/mnExvvxXD11Vdn7ty5SRZ/hSDjeeVQV2O2qp8leZ9fVD/Uv9/+9re59NJLkyTbbbddLrzwwhrb1/Qe0aRJk1x66aWVNVBuueUWa9U1gLp4fTamV1xXXXVVknmBwxFHHLHY9sZ0/VqSz08r63u0oIpCWG211Sq3a3N6T9XaKLWZmkjDGT16dPbZZ598/PHHadSoUa699trFXo2iNk488cTKf67mX2CQ4thwww2z9957J0nefPPNjBs3rrJtScZ71VhPjPeiWNL/3C6O8Vx8dTVmq/pZkvf5RfVD/frb3/6Wn/3sZ0mSTTbZJHffffcCp30sjcaNG+f444+vfG/sF9PiXp+N6RXTU089lVdffTVJcuCBBy52PaLaMKbrzpJ+flpZ36MFVRRC8+bN0759+yTzTiupyccff1wZHPMvCEexjBs3Ll/+8pczbty4lEqlXH755enfv3+d9L3mmmtWfl/8xaa45l9kd/7naf6FHhc33udf6NF4b3gjRozIyy+/nGTeX9vXWGONZe7TeC6+uhqzVf1MmTIln3zySa366dChg7VsGtC1116bb3/720nmXb7+gQceSIcOHeqk7+reIyiOxb0+G9MrpqVZRL02jOlltzSfn1bW92hBFYWx6aabJpk3+2L27NnVtqv6C8D8+1AsH3zwQfbee++8/fbbSead+lWXb4RJKufVU1zVPUfz/0dm/vG8KMZ7scz/n9vFnfa3JIznYqurMVvbfmbPnp233nprkX1Qf2677bYcc8wxmTt3btZZZ508+OCDi72i1JIw7lcMNT1PxvSKZ9asWbn++uuTzAsi99133zrr25heNkv7+WllfY8WVFEYu+66a5J5Ke4zzzxTbbv5p5Lusssuy70ulsynn36aPn36VGZdnH322fnOd75Tp8eYOHFiPvzwwyTJuuuuW6d9U3eqfgeSBZ+nDTbYoPL94qaGP/roo0mSjh07pkuXLnVfJLU2a9asXHfddUnm/QVtv/32q5N+jefiq6sxW/U+v7h+RowYUZk57X2+YTz44IM5/PDDM3v27LRr1y73339/Ntpoozo9RnXvERTH4l6fjekVz5133pkPPvggSfK1r30tjRvX3bXVjOmltyyfn1bW92hBFYXxla98pXJ78ODBi2wzd+7cyl/027Rpkz322KM+SqOWpk6dmr59+2bkyJFJkp///Of5yU9+UufHueSSSyp/tamLNa+oe2+//Xbuv//+JPPWq+rYsWNlW6lUykEHHZRk3l9snnjiiUX28cQTT1T+onPQQQfVuOgry9/dd9+dSZMmJanb/9waz8VXV2O2d+/eWX311ZMkV1xxRbV/fR8yZEjldl2dMk7tPf744znooIMyY8aMtG7dOvfee28233zzOj3G7Nmzc/nll1e+33333eu0f+rG4l6fjekVz/KaGW1ML71l/fy00r5Hl6FAdtttt3KScuPGjcuPP/74Qtt/97vflZOUk5QHDRpU/wVSrRkzZpT32WefyvPz3e9+d4n7GD16dHnkyJE1trn99tvLTZs2LScpN2/evPzee+8tZcUsrdtuu608a9asardPmDChvM0221R+F84777yF2rz22mvlxo0bl5OUe/ToUZ46deoC26dOnVru0aNH5fXg9ddfr/PHwZI55JBDKs/pM888s9j2xnNxjR49uvJcDhgwoFb71NWY/cUvflE59u9+97uFtj/++OOV4/Tq1WtJHxrzWZrn+dlnny23adOmnKTcsmXL8tChQ5f4uA899FD5448/rnb7zJkzywMGDKjU1q9fvyU+Bgta0ue6Ll+fjen6szRjen4ffvhh5Tnt3r17rfczppefuvj8VC6vnO/RdTfXD+rAn/70p+yyyy6ZNm1a9tlnn/zsZz/LHnvskWnTpuW6667LJZdckiTp1q1bfvjDHzZwtczvq1/9au67774kyZ577pnjjz8+o0aNqrZ906ZN061btwXuGzNmTPbYY4/stNNO6devX7beeuusueaaKZfLefvtt3PTTTflpptuqiT8v//97xeYqUP9+J//+Z/MmjUrhxxySHbaaad06dIlLVq0yAcffJCHH344F198ceVUgV133XWRU5e7deuWH/3oRzn77LMzYsSI7LLLLvnJT36SjTbaKG+99VbOOeecPPvss0mS//3f/83GG29cr4+RBX388ce54447kiRbbLFFtt1228XuYzwXx9ChQ/Pmm29Wvq867SOZty7k/H8dTZJjjz12oT7qasz+7//+b66//vq8/vrr+fGPf5w333wzRx55ZFq0aJF///vfOeusszJ79uy0aNEi559//jI/9i+SZX2e33rrrfTp06eyiO6ZZ56Z1Vdfvcb38jXXXDNrrrnmAvddccUVOfDAA3PggQemd+/e2WSTTdK6detMnjw5zzzzTP72t7/llVdeqez/pz/9aSke7Rfbsj7Xdfn6bEwvP3Xx2j2/6667LjNnzkyyZLOpjOnlpy4+PyUr6Xv0co3BYCncdttt5datW1fS3P/+6tatW/mNN95o6DL5L9U9X9V9rb/++gv18e9//7tW+6666qrlv/3tb/X/ICmXy+Xy+uuvX6vn6ZBDDqnxL3Bz5swpH3fccTX2cfzxx5fnzJlTfw+ORbroootq/AvbohjPxTH/X7pr81Wduhqzb7zxRnnjjTeuto/WrVuXb7/99rr+Maz0lvV5Hjx48BK/ly9qdntt6+jevXv5pZdeqoefzMpnWZ/run59NqaXj7p67a6y4447lpOUGzVqVB4/fnyd12FML7klfc1d1OenKivbe7QZVRROv3798sILL+RPf/pT7rzzzrz33ntp2rRpunbtmsMOOywnn3xyVl111YYuk+Vgu+22y9VXX53hw4dnxIgRGT9+fD744IPMnj07a6yxRjbffPPstddeOeGEExb6Cy7154orrsgjjzyS4cOH5+23384HH3yQzz77LK1atUrnzp2z8847Z8CAAdlpp51q7GeVVVbJZZddlkMOOSSXXHJJnn766XzwwQdp3759tt9++3zzm9+sswW7WTZXXXVVkqRRo0b5+te/Xqt9jOeVT12N2a5du+bZZ5/NhRdemBtvvDFvvvlmZs6cmc6dO2f//ffPd7/73ay//vr18IhYHn7yk59k6623zvDhw/Pyyy9n0qRJ+eijj9KsWbOstdZa6dGjRw499ND0798/jRo1auhyv5Dq+vXZmC6+N954I08++WSSZO+9987aa69d632N6RXDyvYeXSqXXUcSAAAAgIbnqn8AAAAAFIKgCgAAAIBCEFQBAAAAUAiCKgAAAAAKQVAFAAAAQCEIqgAAAAAoBEEVAAAAAIUgqAIAAACgEARVAAAAABSCoAoAAACAQhBUAQAAAFAIgioAAAAACkFQBQAAAEAhCKoAAAAAKARBFQAAAACFIKgCAAAAoBAEVQAAJEnOOOOMlEqllEqlhi5liX300Udp3759SqVSnnjiiYYupxD233//lEqlDBo0qKFLAYBaE1QBACuFTz/9NBdeeGH233//dOnSJauuumpWX331dOvWLUcddVRuvPHGzJkzp6HLZDk544wz8uGHH6ZPnz7p2bNnkmTIkCGV4G1pv3r37t2wD2wZnH766UmSc889N++++24DVwMAtSOoAgBWeJdeemk22mijnHzyybn77rvzn//8J9OmTctnn32WN954I9dcc00OP/zwbLPNNhk+fHhDl1uv5g9rxowZs0x99e7du5DhzTvvvJO//e1vSeYFVszTs2fP7L333pk2bVrOPPPMhi4HAGqlVC6Xyw1dBADA0vrf//3f/P73v0+SNG7cOEceeWQOPPDArL/++pk5c2Zee+21XHvttXnwwQeTJM2bN8/111+fAw88sCHLrjdDhgzJwIEDkySjR49Oly5dlrqv3r1755FHHkmvXr3y8MMP102BdeA73/lO/vrXv2bnnXfOsGHDKvd/8sknee+99xa5z7hx49KnT58kyUEHHVRtkNOyZctssMEGdV90Pbn33nuz7777pkmTJhk9enQ6duzY0CUBQI0aN3QBAABL68ILL6yEVJ07d87tt9+erbbaaoE2u+66a44//vhcf/31OeaYYzJ9+vQcccQReeaZZ7LZZps1RNnUoU8++SRXXHFFkuSoo45aYFubNm3Spk2bRe7XqlWrBdptscUWy63GhvTlL385a665ZiZOnJiLLrrIzCoACs+pfwDACuk///lPfvSjHyWZFzo89NBDC4VU8zviiCMqgcb06dNz9NFH10udLF/XXXddpkyZkiZNmuTwww9v6HIKp1GjRjniiCOSzJtdN3fu3AauCABqJqgCAFZI559/fqZPn54kGTRoULp27brYfY488sj07ds3STJy5Mjcf//9C7Xp0qVLSqVSjj322Br7OvbYY1Mqlao9le7jjz/O4MGDc9RRR2WzzTZLq1at0rRp06y99trp06dPLrnkksycObPa/seMGVNZW2rIkCFJkvvvvz/9+vXL2muvnWbNmmWDDTbISSedtMjT2x5++OGUSqXKaX9JssEGGyy0WPj8p/BVd9W/qsf6yCOPJEkeeeSRhfqp+jn8+c9/rtz35JNP1vgzTJJDDjkkpVIpbdq0ybRp0xbb/r/dcMMNSeadltiuXbsl3n9xJk+enLPPPjs77bRT2rZtm2bNmqVTp0459NBDc8cdd9S473+v6TV27Nj84Ac/SNeuXdOiRYu0a9cuffr0yd13311jP3PmzMmQIUPSp0+frL322mnatGnatGmTjTfeOHvttVfOOuusvPzyy9Xuf8ghh1SOP3To0CX7AQBAPRNUAQArnHK5nCuvvDJJ0qJFi5x44om13veUU06p3L7sssvqvLYq22yzTY477rhcc801eeWVVzJlypTMmjUr77//fu67775885vfTM+ePTNhwoRa9ffTn/40++yzT+644468//77mTlzZsaMGZOLL7442267bV555ZXl9liWxNFHH53mzZsnSQYPHlxj2w8++KAS9hx55JFp0aLFEh1rxowZlcXxq670V5eeffbZbLLJJjn11FPzxBNP5OOPP87MmTMzduzY/POf/0y/fv1yyCGHVALTmgwdOjRbbbVV/vjHP+att97K9OnT89FHH+W+++7L/vvvXzmF9b9Nnjw5e+yxRwYOHJj77rsv77//fmbNmpVPP/00b775Zh566KH8/Oc/r1zhb1G23377NGrUKEkKtbYYACyKoAoAWOG89NJL+eijj5Iku+++e1ZfffVa77vXXntl1VVXTZLlOrtkzpw52XHHHfPrX/86d9xxR55++ukMGzYsV199dfbdd98k84KQI488crF9/f3vf88555yTXr165R//+EdGjBiRBx54IMccc0ySZNKkSTnuuOMW2Gf77bfPiy++uMCaRPfee29efPHFBb623377xR7/N7/5TV588cX06NEjSdKjR4+F+rnvvvuSJGussUb69++fZN5peTXNkrrmmmsqs8r+u/7aePrppyshUW0ex5IYO3Zs9tprr4wbN64yM+3ee+/NiBEjcuWVV1ZOM7355pszYMCAGvsaP358+vfvn0aNGuXss8/O0KFD89RTT+UPf/hDZQ2tU089NS+99NJC+55xxhl57LHHkiQHHHBArr322gwbNizPPPNM7rnnnpxzzjnZbbfdFpoFN79VV101m2++eZJU+gKAwioDAKxgrr766nKScpLyqaeeusT777TTTpX9J0yYsMC29ddfv5ykPGDAgBr7GDBgQDlJef3111/k9tdff73G/S+//PJKDQ888MBC20ePHl3ZnqR84oknlufOnbtQuxNOOKHSZuTIkQttHzx4cGX76NGja6xp0KBBlbaL0qtXr3KScq9evWrs56GHHqr0c80111TbbquttionKW+xxRY19ledc845p3Kcd999d4n2nf/nu6jn+tBDD61sv/TSSxfaPn369PIee+xRaXPXXXct1Kbq51X1e/Lee+8t1Oaxxx4rl0qlcpLyKaecstD2zp07l5OUDz300Bofz4cffljj9oEDB5aTlFu2bLnI3yMAKAozqgCAFc4HH3xQub322msv8f5rrbXWIvuqSxtvvHGN2wcOHJhtttkmSfKvf/2rxrbrrLNOLrjggkXOmqlaUD4pzmyZ3r17V9YMq+70v5EjR+b5559PsnSzqZIssDbXmmuuuVR9LMr48eNzyy23JEn69OmT448/fqE2zZo1y+WXX57GjeddRPsvf/lLjX1ecMEF6dix40L377rrrtlxxx2TLPr5qzo1dLfddqux/7Zt29a4vernM2XKlHzyySc1tgWAhiSoAgBWOJMnT67cbtmy5RLvP/8+9fGhvVwuZ8KECXn99dczatSoyte6666bJJXApjqHHnpomjVrtshtm2yySVq1apUkefvtt+u28KVUKpUq4dODDz6Yd955Z6E2VQFWkyZNctRRRy3VcSZNmpRk3qltTZs2XcpqF/bvf/87c+bMSZJFhlRVunTpkr333jvJvLWfqvb5b23atKks4r8o2223XZJFP3/rrLNOkuT666/P1KlTa/cAFmH+IKvq5wYARSSoAgBWOKuttlrl9vyhVW3Nv091AVBduPPOO3PAAQdk9dVXzzrrrJNNNtkk3bt3r3zdeeedSRY/q+tLX/pSjdvXWGONJMnnn39eN4XXgYEDB6Zx48Ypl8u54oorFtg2Y8aM/OMf/0iS9OvXLx06dFiqY1StU1b1+OvKqFGjKrerZjtVp2r71KlTqw0KN95446yySvX/7a4KkRb1/FWtf/X4449ngw02yMknn5xbbrllicOm+X9GH3744RLtCwD1SVAFAKxw2rdvX7ld26vmze/9999fZF91pVwu54QTTsgBBxyQO++8c7EBUk0LjiepLP5enaoQpLoZPQ1h7bXXrswiGjJkSMrlcmXbrbfeWgmZapqxtDhVVxdc3M9vSVXVlix4muiizH/q6fz7za+2z9/cuXMX2vaLX/wixx13XEqlUiZOnJgLL7wwBx98cNZaa6107949gwYNWuD3uTrz/4yW9OqKAFCfBFUAwApnyy23rNx+9tlnl2jfOXPm5IUXXkgy7wP7euutV6e1Jcnll1+eyy67LEmy9dZbZ8iQIXnllVfy2WefZfbs2SmXyymXyzn66KOTZIEQZ2VywgknJJl3Stujjz5aub/qtL911103ffr0Wer+q2ZiffLJJw32M1zex23SpEkuu+yyjBo1Kqeddlp23nnnNG3aNOVyOaNGjcqvfvWrdO3aNbfeemuN/cwfoi3tDDYAqA+CKgBghbP55punXbt2SZJHH300n376aa33feCBBypr/ey6664LnZJV0+yW+U2ZMqXabX//+9+TJBtttFEef/zxDBgwIF/60pey2mqrpVGjRpV2H3/8ca3rXhHtt99+lQXEq8KpsWPH5v77708y77S2+X8eS6oqcJk7d+4S/Q4szvzrOS1uttL82xe3oPmy2GyzzfLrX/86w4YNyyeffJL7778/AwcOTKNGjTJ58uR89atfzfjx46vdf/7fteUxixAA6oqgCgBY4ZRKpRxzzDFJ5p3SVBUM1cYFF1xQuX3YYYcttL1q/avFhUivvfZatdteeumlJMlBBx1U7WlW5XI5I0eOXGy9y2pRVwqsr74aNWqUY489Nkly0003ZfLkybniiisqpygOHDhwmerp3r175fbrr7++TH3Nb4sttqjcfvLJJ2ts+9RTTyWZd3rfBhtsUGc11KRFixb58pe/nMsvvzznnntuknnj4I477qh2n6qfT7du3ZbrumwAsKwEVQDACul73/teJQT65S9/mTfffHOx+1x33XWVBczXXnvtyql386sKG0aOHFntaV2jRo3Kiy++WO1xZs+enSQ1XqXttttuy7hx4xZb87KqWscpmbeIeV30tST9HH/88SmVSpkyZUquv/76DBkyJEmy++67Z+ONN16menbbbbfK7aeffnqZ+ppf7969KzO9qk7hXJR33nmnMjusd+/eady4cZ3VUFt77bVX5XZNi/KPGDEiyYI/MwAoIkEVALBCWm+99XLeeeclmXcVv7322ivPP/98te1vuOGGyhXUknkzq+YPcar06tUrSTJu3Lhce+21C23//PPPc9xxx9VYW1UAc/vtty9yZtZbb72Vb3/72zX2UVfWWWedBY5bF329/fbbtV6baYMNNqiEKaeddlreeOONJFnsz7A2OnfunPXXXz/J/5/ZVBfWXXfd9O/fP0ly77335vLLL1+ozcyZM3Pcccdl1qxZSZKTTz65zo5f5aOPPsptt91W48/6vvvuq9yubkbX22+/XQmxBFUAFF39/9kHAKCOnHTSSXnrrbdy3nnn5Z133kmPHj3y1a9+NQceeGDWX3/9zJo1K6+++mr+8Y9/5MEHH6zs9/Of/zyHHnroIvs86qijcsYZZ+Szzz7L8ccfnzfffDN9+vRJqVTKiBEj8oc//CFjx47NNttsU+1C7sccc0z+93//N2PHjs3OO++cH//4x9l8880zffr0PPTQQzn//PMzY8aMbLvttsv99L9tttkmzZs3z/Tp0/OLX/wijRs3TpcuXSprcXXs2LHWV4HbeeedM3jw4EycODE/+MEPctRRR2X11VdPMm/R76rQ6L+dcMIJeeCBBypXaFxttdUWedrl0ujbt2/++te/5qGHHkq5XK6zUx3/+Mc/5sEHH8zHH3+cE044IcOGDcuRRx6Ztm3b5tVXX83vf//7PPfcc0mSww8/PPvtt1+dHHd+n332WQ466KB06dIlBx98cHbcccesv/76ady4ccaPH5/bb789l156aZKkU6dO6dev3yL7qfrdb9So0TItXg8A9aIMALCCu+SSS8rt2rUrJ6nxq3nz5uULLrhgsf3dcMMN5UaNGlXbxw033FAeMGBAOUl5/fXXX2j/mTNnlvfZZ59q62jRosVi+xg9enSl/eDBg2usd/311y8nKQ8YMGCR23/84x9XW8u///3vSrtBgwZV7l+Uzz//vLzhhhsusp9FPYYqM2bMKLdv377S9sQTT6zx8SyJ4cOHV/p95JFHar3f/D/f6n5uI0eOLK+77ro1/k4dfPDB5WnTpi1y/169epWTlHv16lVjLdX93Oevsaavjh07lkeOHFlt/7179y4nKffp06fGOgCgCJz6BwCs8E488cS89dZb+ctf/pJ99903nTt3Xui0vtVXXz0vvfRSrU7ROuyww/L444+nf//+6dChQ5o2bZrOnTtnwIABGTFixGJnAzVp0iR33nln/vznP6dHjx5ZddVV06JFi3Tt2jXf+ta3MnLkyDqbUVQbZ599dv7+979nt912S9u2bZf6SnutWrXK448/nu9+97vZdNNNs+qqq9Zqv6ZNmy7weOvitL8qPXv2zLbbbpskueaaa/5fe3fsSn0bx3H8c+4kBnWSScoosRhkkoxnPYMo/4ayyKIURymURUkGi8X5B6RjZyEmKRslidEz6L7rrrse9Ry33/G8XuMZrt+1/Trvru/vatq6yftptKurqywvL2dsbCzlcjnt7e3p7e1NtVrN0dFRDg8P/zhC2gz9/f05OzvL6upqKpVKBgYGUi6X09bWlp6enkxMTKRWq+Xy8jIjIyN/XOPu7i4nJydJ8tfGTQHgvyi9vX3wAwMAAC1obm4utVotyftI3u7ublNvwuNjxsfH02g0Mjg4mIuLi6aufXBwkJmZmZTL5dze3v66uZFkaWkpCwsLGRgYyMXFxa+RTwAoKm8qAOBbW1lZSbVaTZLs7e1lfn7+i3f0/3N9fZ1Go5Hk/RbAZpuamsrQ0FAeHx+zubnZ9PVb1fPzc9bX15Mki4uLIhUALcHbCgD41kqlUvb39zM6OprkPVz9/PPO3/HzRFtHR8dvNy82y48fP7K6upokWVtby/Pzc9Of0Yq2trby8PCQ0dHRTE9Pf/V2AOBD3PoHAHx7nZ2dqdfr2d7eztvbW56envL4+JhyufzVW/uWXl9fc3d3l5eXl9Tr9ezs7CR5v/2vp6fnU55ZqVSysbGR+/v73NzcZHh4+FOe00q6urqyuLiYarVq3BWAluEbVQAANNXx8XEmJyd/+62vry/n5+fp7u7+ol0BAK3A6B8AAJ+iVCqlt7c3s7OzOT09FakAgH/lRBUAAAAAheBEFQAAAACFIFQBAAAAUAhCFQAAAACFIFQBAAAAUAhCFQAAAACFIFQBAAAAUAhCFQAAAACFIFQBAAAAUAhCFQAAAACFIFQBAAAAUAhCFQAAAACFIFQBAAAAUAhCFQAAAACFIFQBAAAAUAhCFQAAAACFIFQBAAAAUAhCFQAAAACFIFQBAAAAUAj/AIRT3jHhhwehAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 432,
       "width": 597
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.barh(total.index, width=total.values)\n",
    "ax.set_xlabel(\"Quantity (Tons)\")\n",
    "ax.set_ylabel(\"Crop Type\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "'''{note}\n",
    "Bar plots should ALWAYS have their base at 0. If this isn't the case, they can be misleading to the reader.\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stacked bar plots\n",
    "\n",
    "Where this gets more interesting is when we want to create stacked bar plots. Each bar that's plotted is actually a rectangle and so it has a baseline which is 0 in standard bar plots. However, we can adjust that baseline through the `bottom` keyword parameter and that becomes the starting point for the bar. Let's set a different baseline for plotting the grain, wheat, and barley totals to show how that would look. You'll notice that the length of the bar plot remains the same, the value of the baseline has just been added to it. For example, for wheat, 50 was added to the plotted value of 193 which means the top of the bar was 243 - very close to 250 as is visible in the plot below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Quantity (Tons)')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 432,
       "width": 571
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "bottom = np.array([0, 50, 100])\n",
    "\n",
    "ax.bar(total.index, height=total.values, bottom=bottom)\n",
    "ax.set_xlabel(\"Crop Type\")\n",
    "ax.set_ylabel(\"Quantity (Tons)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Grain starts at 0, wheat at 50, and barley at 100. We can use this to make our stacked bar plot by plotting each element by adding it as a new set of bars. Let's start by plotting just one farm instead of the totals and we'll begin with Farm A."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Quantity (Tons)')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 432,
       "width": 562
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.bar(farm_data.columns, farm_data.loc[\"Farm A\"].values, label=\"Farm A\")\n",
    "\n",
    "ax.legend()\n",
    "ax.set_xlabel(\"Crop Type\")\n",
    "ax.set_ylabel(\"Quantity (Tons)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, to create the stacked items, we'll plot each part of the bar on top of these first sets of bars by resetting the baseline each time to the cumulative total of any previously plotted bars. Using this approach, let's iterate through each row of the `farm_data` DataFrame and plot it to make the stacked bar plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Quantity (Tons)')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 433,
       "width": 571
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "bottom = np.zeros(\n",
    "    3\n",
    ")  # Stores the current baseline of the bars to set as the baseline for the next set of bars\n",
    "\n",
    "for (\n",
    "    farm_name,\n",
    "    farm_crop_yields,\n",
    ") in (\n",
    "    farm_data.iterrows()\n",
    "):  # Recall that for a DataFrame using the `iterrows()` method allows us to iterate over the rows of the DataFrame\n",
    "    ax.bar(\n",
    "        farm_crop_yields.index, farm_crop_yields.values, label=farm_name, bottom=bottom\n",
    "    )\n",
    "    # Note that here, farm_crop_yields.index is the farm name, farm_crop_yields.values is the crop yields for the current farm in the loop\n",
    "\n",
    "    bottom += farm_crop_yields  # Collects the total amounts of grain, wheat, and barley already accounted for and establishes the new baseline for the next farm to stack on the plot.\n",
    "\n",
    "ax.legend()\n",
    "ax.set_xlabel(\"Crop Type\")\n",
    "ax.set_ylabel(\"Quantity (Tons)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It can sometimes aid in reading bar plots to add a sliver of whitespace between the components. This can be easily done by setting the `edgecolor` property:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Quantity (Tons)')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 433,
       "width": 571
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "bottom = np.zeros(\n",
    "    3\n",
    ")  # Stores the current baseline of the bars to set as the baseline for the next set of bars\n",
    "\n",
    "for (\n",
    "    farm_name,\n",
    "    farm_crop_yields,\n",
    ") in (\n",
    "    farm_data.iterrows()\n",
    "):  # Recall that for a DataFrame using the `iterrows()` method allows us to iterate over the rows of the DataFrame\n",
    "    ax.bar(\n",
    "        farm_crop_yields.index,\n",
    "        farm_crop_yields.values,\n",
    "        label=farm_name,\n",
    "        bottom=bottom,\n",
    "        edgecolor=\"white\",\n",
    "    )\n",
    "    # Note that here, farm_crop_yields.index is the farm name, farm_crop_yields.values is the crop yields for the current farm in the loop\n",
    "\n",
    "    bottom += farm_crop_yields  # Collects the total amounts of grain, wheat, and barley already accounted for and establishes the new baseline for the next farm to stack on the plot.\n",
    "\n",
    "ax.legend()\n",
    "ax.set_xlabel(\"Crop Type\")\n",
    "ax.set_ylabel(\"Quantity (Tons)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Grouped bar plots\n",
    "\n",
    "Grouped bar plots require that we do a small amount of math to get them to work. Let's look at how we do this, then explain how it's made:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Quantity (Tons)')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4AwAAAAAAYGEUdwAAAAAAACyM4g4AAAAAAICFUdwBAAAAAACwMIo7AAAAAAAAFvZ/DdZvdmJ5M4kAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 432,
       "width": 571
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "num_columns = farm_data.shape[0]  # Number of bars per group\n",
    "num_rows = farm_data.shape[1]  # Number of groups\n",
    "\n",
    "x_values = np.arange(num_rows)\n",
    "\n",
    "bar_width = 1 / (\n",
    "    num_columns + 1\n",
    ")  # width of the bars. To ensure a gap between groups, this could be 1 / (N+1) where N is the number of bars per group\n",
    "column_count = 0  # Count of how many sets of bars have been plotted so far\n",
    "\n",
    "for crop_name, farm_crop_yields in farm_data.items():\n",
    "    offset = (\n",
    "        bar_width * column_count\n",
    "    )  # Offset from the x axis value for the group to the place where the bar will be centered\n",
    "    ax.bar(\n",
    "        x_values + offset,\n",
    "        farm_crop_yields.values,\n",
    "        width=bar_width,\n",
    "        label=crop_name,\n",
    "        edgecolor=\"white\",\n",
    "    )  # The edgecolor property adds a small amount of space between the bars for ease of reading\n",
    "    column_count += 1\n",
    "\n",
    "tick_locations = (\n",
    "    x_values + (1 - offset) / 2\n",
    ")  # Place the ticks at the center of the groups of bars\n",
    "ax.set_xticks(tick_locations)\n",
    "ax.set_xticklabels(farm_data.index)\n",
    "\n",
    "ax.legend()\n",
    "ax.set_xlabel(\"Farm Name\")\n",
    "ax.set_ylabel(\"Quantity (Tons)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To create these grouped bar plots, we need to tell matplotlib where we want each of the bars to go along the x-axis and spread them out based on how many bars we will plot per group. Let's look at this on an iteration-by-iteration basis to show how this works. There are four key quantities:\n",
    "\n",
    "1. The width of the bars to plot\n",
    "2. The iteration that we're currently on, starting at zero and walking through each item in the group (e.g. grain, wheat, barley, in our last example)\n",
    "3. The offset for where to center the bar along the x axis (assuming a vertical bar plot)\n",
    "4. The x values of the offset bars. For example, if the x values are [0,1,2] and we include an offset of 0.5, we'll plot the centers of those bars at [0.5, 1.5, 2.5]\n",
    "\n",
    "The figure below shows step-by-step how these grouped bar plots are created."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Making a grouped bar chart](img/5.1-grouped-bar.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Stacked and grouped bar plots are common tools to use when comparing values and will be a regular tool in your growing toolbox."
   ]
  }
 ],
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