docs/2-Review.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reviewing Data\n",
    "\n",
    "Like the setup notebook, the content of this notebook should be kept private from your users, generally speaking. Here we are publishing the code for illustration purposes.\n",
    "\n",
    "Once your content has gone to users, you can start checking in on responses using `datatops` information from the setup notebook (where we created the database in the first place):\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datatops import Project\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "database = Project(**{\n",
    "    \"name\": \"public_testbed\",\n",
    "    \"admin_key\": \"a-f87528a5-e8cb-4a54-a338-b5e7c9c41249\",\n",
    "    \"user_key\": \"3zg0t05r\",\n",
    "    \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab/\"\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>__datatops_project</th>\n",
       "      <th>__datatops_timestamp_iso</th>\n",
       "      <th>button_name</th>\n",
       "      <th>feedback</th>\n",
       "      <th>section_id</th>\n",
       "      <th>timestamp_utc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>public_testbed</td>\n",
       "      <td>1682534910</td>\n",
       "      <td>happy</td>\n",
       "      <td></td>\n",
       "      <td>Learning Datatops</td>\n",
       "      <td>2023-04-26T18:48:31.836088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>public_testbed</td>\n",
       "      <td>1682534912</td>\n",
       "      <td>happy</td>\n",
       "      <td></td>\n",
       "      <td>Using Markdown Notation</td>\n",
       "      <td>2023-04-26T18:48:33.992925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>public_testbed</td>\n",
       "      <td>1682534913</td>\n",
       "      <td>happy</td>\n",
       "      <td></td>\n",
       "      <td>Datatops-Usage/Spring2023/UsingNamespaces</td>\n",
       "      <td>2023-04-26T18:48:35.559577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>public_testbed</td>\n",
       "      <td>1682534915</td>\n",
       "      <td>happy</td>\n",
       "      <td></td>\n",
       "      <td>Datatops-Usage/Spring2023/UsingNamespaces</td>\n",
       "      <td>2023-04-26T18:48:37.277443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>public_testbed</td>\n",
       "      <td>1682534916</td>\n",
       "      <td>happy</td>\n",
       "      <td></td>\n",
       "      <td>Datatops-Usage/Spring2023/UsingNamespaces</td>\n",
       "      <td>2023-04-26T18:48:38.101836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>public_testbed</td>\n",
       "      <td>1682534964</td>\n",
       "      <td>medium</td>\n",
       "      <td>is there a way to hide the python code</td>\n",
       "      <td>Using Markdown Notation</td>\n",
       "      <td>2023-04-26T18:49:25.929171</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  __datatops_project __datatops_timestamp_iso button_name  \\\n",
       "0     public_testbed               1682534910       happy   \n",
       "1     public_testbed               1682534912       happy   \n",
       "2     public_testbed               1682534913       happy   \n",
       "3     public_testbed               1682534915       happy   \n",
       "4     public_testbed               1682534916       happy   \n",
       "5     public_testbed               1682534964      medium   \n",
       "\n",
       "                                  feedback  \\\n",
       "0                                            \n",
       "1                                            \n",
       "2                                            \n",
       "3                                            \n",
       "4                                            \n",
       "5  is there a way to hide the python code    \n",
       "\n",
       "                                  section_id               timestamp_utc  \n",
       "0                          Learning Datatops  2023-04-26T18:48:31.836088  \n",
       "1                    Using Markdown Notation  2023-04-26T18:48:33.992925  \n",
       "2  Datatops-Usage/Spring2023/UsingNamespaces  2023-04-26T18:48:35.559577  \n",
       "3  Datatops-Usage/Spring2023/UsingNamespaces  2023-04-26T18:48:37.277443  \n",
       "4  Datatops-Usage/Spring2023/UsingNamespaces  2023-04-26T18:48:38.101836  \n",
       "5                    Using Markdown Notation  2023-04-26T18:49:25.929171  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(database.list_data())\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    0.5\n",
       "5    0.5\n",
       "dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nbz+nT5/W+vXr9eSTT+rcuXP218mpU6cUFhamP/74w372j6enp/bs2aM//vjjhs9PurYNpEvfO3np0iV98803mT6/rF7zS5cuVVpaml555RX7npzrlytJ0dHROnv2rLp37+7wWi9UqJAaNmyoDRs22B+vaNGi2rhxo86cOXPT53AvIIzkccnJyfYP89OnT2vw4MHy9fWVq6urvL29FRgYKEnZHl/x/fffKzQ0VMWLF5enp6e8vb01cuTIbC/j8OHDqlatWob2+++/337/9apUqeJw22azqXLlyvbjooGBgRo2bJhmzZql0qVLKywsTFOnTnWo5fTp04qPj7dPOR1Lkv5G0aJFCz3xxBMaN26cSpcurU6dOmnOnDlKTU116L9ixQo1atRILi4u8vLykre3t6ZNm+bwuIcPH5aTk5N9/aerXLmyw+2//vpLZ8+e1YwZM+Tt7e0wRUZGSrq2Cz/dypUr1aZNmwwfnGFhYVq7dq3Onj2rzZs3a8CAATp8+LDat2/vML+UcZ1LUtWqVTMciy5cuHC2Dvuku/6DRJI9mKS/mab/7/++DrJqu96gQYO0Zs0azZo1S7Vq1XK4z9XVNcP/SLoWyNPvz8xbb72lmTNnasKECQ6nSV+vQoUKCg0NVffu3fXf//5XFStWVGhoqEMg+fHHH/XXX3/lKozkdNvLSnbWfXa2x8yMGjVKV65cueHYkZy8b/y91vQvHH8/lJbenv4c9u3bJ8uyNHr06AyvlfQzrNK39fHjx+vs2bOqWrWqgoOD9a9//SvTMw+dnJxUsWJFh7aqVatKksPrITuv+f3798vJyUlBQUFZrqf0cNSqVasMz+Hrr7+21+/s7Kw33nhDq1evlq+vr5o3b64333zTfkjxXkQYycOOHj2qxMRE+xvKk08+qZkzZ+rZZ5/Vl19+qa+//tr+jSgtLe2my9u/f79at26tkydP6p133tHKlSsVHR2toUOHZnsZd8KkSZP0yy+/aOTIkfZBeDVq1NDRo0clSY8//rj8/f3t0+DBgyXd/Jtx+p6W9H42m02LFy9WbGysBg4caB9UWrduXSUnJ0uSvv32W3Xs2FEuLi764IMPtGrVKkVHR+upp57K8voTN5K+Tnv27Kno6OhMpyZNmtjr3bhxY5YfnJJUrFgxNWvWTFOmTNGoUaN05swZrV69Osd1SdfeEP/+De9GChUqlGl7btbL9caNG6cPPvhAr7/+up5++ukM9/v7+2f6rT29LbOxDnPnztVLL72kZ599Nkenynbu3FlHjhzR5s2b7W2rVq1SQECAw4fQndj2buROrXvp2t6Rnj17Zrl3JKfvG1nVerPnkL6cF198McvXSvp7YfPmzbV//37Nnj1bNWvW1KxZs/Tggw9q1qxZOX7+t/M1n/4c5s+fn2n9y5Yts/cdMmSIfv/9d0VFRcnFxUWjR4/W/fffn+mg3nsBA1jzsPnz50u69q34zJkzWrduncaNG6dXXnnF3iez3ZTp38b+bvny5UpNTdVXX33l8O0lfddhdpZRoUKFTK9B8dtvv9nvv97f67MsS/v27dMDDzzg0B4cHKzg4GCNGjVKMTExatKkiaZPn65XX31VkyZNctiVmf7h4+3trWLFimV5TYy9e/eqWLFiGQYuNmrUSI0aNdJrr72mBQsWqEePHlq0aJH69eunL774Qi4uLlq7dq3DoYE5c+ZkWA9paWk6ePCgw56Iffv2OfTz9vaWm5ubrl69qtDQ0EzrTLd+/Xqlpqaqbdu2N+yXrl69epKU4QMks23i999/v+OD4tL/939fB1m1SdLUqVM1duxYDRkyRC+99FKmfWrXrq0NGzYoKSnJYRDrli1b7Pdfb9myZerXr58ef/xxTZ06NUfPIT1cXP+NeOXKlRkC4p3Y9m5FdrfHrIwaNUqffPKJw4DYdDl537gV6XswihQpctPXiiR5eXkpMjJSkZGRSk5OVvPmzTV27FiHdZmWlqYDBw7Y94ZI114Lkuyvh+y+5itVqqS0tDT973//y7DNXd9HunaWW3aeQ6VKlfTPf/5T//znP/XHH3+odu3amjRpkv0MynsJe0byqPXr12vChAkKDAxUjx497N8q/p7UJ0+enGHe4sWLS1KGi55ltozExMQML7r0ZWR20bRHH31UW7duVWxsrL0tJSVFM2bMyPDtUfr/MzvSLV68WMePH7d/4CYlJenKlSsO8wQHB8vJycm+C7tu3boKDQ21T+mPUahQIbVp00bLly9XXFycwzLi4uK0fPlytWnTxv68z5w5k2H9pb+ppD9WoUKFZLPZHK7YeejQIS1dutRhvrCwMEnXLg53vb+PdyhUqJCeeOIJffHFFxlOr5WuHcZJt2rVKtWrV8/hjBdJWrduXYb50vtLynDYbOnSpQ5X1ty6dau2bNmS7ZCTW2XKlFHNmjX18ccfO3zb37Rpk3bt2pWh/6effqoXXnhBPXr00DvvvJPlcjt37qyrV69qxowZ9rbU1FTNmTNHDRs2dNj9v3nzZnXr1k3NmzfXf//73yz3/Fy/3q/30UcfyWaz6cEHH5R07Uyo7du3ZzhEcye2vVuR3e0xK5UqVVLPnj314YcfZjhUkJP3jVvh4+Ojli1b6sMPP8x0D831/7PrL2cgXRu3Vrly5UzX5ZQpU+x/W5alKVOmqEiRImrdurWk7L/mw8PD5eTkpPHjx2fYG5S+bsLCwuTu7q6JEydmOjYo/TmcP3/efpgxXaVKleTm5nZbtof8iD0jecDq1av122+/6cqVK0pISND69esVHR2tChUq6KuvvpKLi4tcXFzsxxUvX76ssmXL6uuvv9bBgwczLK9u3bqSpJdfflndunVTkSJF1KFDB7Vp00ZFixZVhw4d9I9//EPJycmaOXOmfHx8Mrz469atq2nTpunVV19V5cqV5ePjo1atWmn48OFauHCh2rZtqxdeeEFeXl6aN2+eDh48qC+++CLDm7+Xl5eaNm2qyMhIJSQkaPLkyapcubL69+8v6VroGjhwoLp06aKqVavqypUrmj9/vv1D/GYmTpyoRo0a6cEHH9QzzzyjgIAAHTp0SDNmzJDNZtPEiRPtfefNm6cPPvhAjz32mCpVqqRz585p5syZcnd3t3/zbdeund555x098sgjeuqpp3TixAlNnTpVlStXdjgmXbduXT3xxBOaPHmyTp06ZT+VMv1b1/V7ll5//XVt2LBBDRs2VP/+/RUUFKTTp09r+/bt+uabb3T69GlJ18JF+jiS63Xq1EmBgYHq0KGDKlWqpJSUFH3zzTdavny56tevrw4dOjj0r1y5spo2barnnntOqampmjx5skqVKqV///vfN12ft2rixInq1KmTmjRposjISJ05c0ZTpkxRzZo1HQLK1q1bFRERoVKlSql169b673//67Ccxo0b278pN2zYUF26dNGIESN04sQJVa5cWfPmzdOhQ4f00Ucf2ec5fPiwOnbsKJvNps6dO+vzzz93WOYDDzxg3yP32muv6fvvv9cjjzyi8uXL6/Tp0/riiy/0448/atCgQfbDAatWrZKLi4seeuihTJ/r7dz2bkVOtsesvPzyy5o/f7727t3rcL2WnLxv3KqpU6eqadOmCg4OVv/+/VWxYkUlJCQoNjZWR48e1c8//yzp2iDZli1bqm7duvLy8tK2bdu0ePFih8Gq0rXDZGvWrFGvXr3UsGFDrV69WitXrtTIkSPtlzvI7mu+cuXKevnll+0DyB9//HE5Ozvrxx9/VJkyZRQVFSV3d3dNmzZNTz/9tB588EF169ZN3t7eiouL08qVK9WkSRNNmTJFv//+u1q3bq0nn3xSQUFBKly4sJYsWaKEhAR169bttq7TfOPun8CDdOmn2KVPRYsWtfz8/KyHH37Yeu+99xxOibUsyzp69Kj12GOPWZ6enpaHh4fVpUsX688//8xw6p5lWdaECROssmXLWk5OTg6nGH711VfWAw88YLm4uFgBAQHWG2+8Yc2ePTvDqcDx8fFWu3btLDc3N0uSw2mN+/fvtzp37mx5enpaLi4uVoMGDawVK1Y4PH76qb0LFy60RowYYfn4+Fiurq5Wu3btHE7vO3DggNWnTx+rUqVKlouLi+Xl5WU99NBD1jfffJPt9fjrr79aXbt2tXx8fKzChQtbPj4+Vrdu3axff/3Vod/27dut7t27W+XLl7ecnZ0tHx8fq3379ta2bdsc+n300UdWlSpVLGdnZ6t69erWnDlz7KdYXi8lJcUaMGCA5eXlZZUoUcIKDw+39u7da0myXn/9dYe+CQkJ1oABA6xy5cpZRYoUsfz8/KzWrVtbM2bMsCzLsnbv3m1JsrZu3Zrh+S1cuNDq1q2bValSJcvV1dVycXGxgoKCrJdfftlhG7n+dNNJkyZZ5cqVs5ydna1mzZpZP//8s8Mye/XqZRUvXjzT9ZnVqb2ZnYaY2ba3aNEiq3r16pazs7NVs2ZN66uvvrKeeOIJq3r16vY+f9/2/z7NmTPHYZkXLlywXnzxRcvPz89ydna26tevb61Zs8ahT/o2l9V0fZ1ff/211b59e6tMmTJWkSJFLDc3N6tJkybWnDlz7KdpWpZlde7c2Xr00UczXU+Wdfu3vb/Xmb7dXX8a6vXr7/rXbHa3xxtdUiD9dNi/n9qb3feNChUqZHrKrSRrwIABDm1ZbVf79++3IiIiLD8/P6tIkSJW2bJlrfbt21uLFy+293n11VetBg0aWJ6enparq6tVvXp167XXXrMuXbrk8FyKFy9u7d+/32rTpo1VrFgxy9fX1xozZkyGU3Oz+5q3LMuaPXu2VadOHcvZ2dkqWbKk1aJFCys6Otqhz4YNG6ywsDDLw8PDcnFxsSpVqmT17t3b/v8+efKkNWDAAKt69epW8eLFLQ8PD6thw4bWZ599luHx7hWEEdwR6R8Mubl+SH6Wft2UTz75JEfzvfHGG5avr6/DB2FO3ezaFybVqlXLCg0NNV1Gjly+fNlyd3e3pk6darqUXMvt9lgQ3ChwI+9hzAiQS5mdSTF58mQ5OTmpefPmOVpWQECA3n333WztTs/LLl++nGEM0MaNG/Xzzz87/KRAfnD69GkNHTo0w1WF86rbuT0CdxtjRoBcevPNN/XTTz/poYceUuHChbV69WqtXr1azzzzzA0vT56ZJ5988g5VeXcdO3ZMoaGh6tmzp8qUKaPffvtN06dPl5+fX4YLd+V1Pj4+mf6mS151O7dH4G4jjAC51LhxY0VHR2vChAlKTk5W+fLlNXbs2Cx/gv5eULJkSdWtW1ezZs3SX3/9peLFi6tdu3Z6/fXXVapUKdPlFWhsj8jPbJZ1G66aAwAAkEuMGQEAAEYRRgAAgFH5YsxIWlqa/vzzT7m5ueX7sw0AALhXWJalc+fOqUyZMjf8Lax8EUb+/PNPRoMDAJBPHTly5Ia/Ep4vwoibm5uka0/m+h/KAgAAeVdSUpLKlStn/xzPSr4II+mHZtzd3QkjAADkMzcbYsEAVgAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABiVozAybdo0PfDAA/bLsoeEhGj16tU3nOfzzz9X9erV5eLiouDgYK1ateqWCgYAAAVLjsLIfffdp9dff10//fSTtm3bplatWqlTp07as2dPpv1jYmLUvXt39e3bVzt27FB4eLjCw8O1e/fu21I8AADI/2yWZVm3sgAvLy+99dZb6tu3b4b7unbtqpSUFK1YscLe1qhRI9WuXVvTp0/P9mMkJSXJw8NDiYmJ/FAeAAD5RHY/v3M9ZuTq1atatGiRUlJSFBISkmmf2NhYhYaGOrSFhYUpNjY2tw8LAAAKmMI5nWHXrl0KCQnRxYsXVaJECS1ZskRBQUGZ9o2Pj5evr69Dm6+vr+Lj42/4GKmpqUpNTbXfTkpKymmZAAAgn8hxGKlWrZp27typxMRELV68WL169dKmTZuyDCS5ERUVpXHjxt225d1uAcNXmi4hzzr0ejvTJQAA8pkcH6YpWrSoKleurLp16yoqKkq1atXSe++9l2lfPz8/JSQkOLQlJCTIz8/vho8xYsQIJSYm2qcjR47ktEwAAJBP3PJ1RtLS0hwOqVwvJCRE69atc2iLjo7OcoxJOmdnZ/vpw+kTAAAomHJ0mGbEiBFq27atypcvr3PnzmnBggXauHGj1q5dK0mKiIhQ2bJlFRUVJUkaPHiwWrRooUmTJqldu3ZatGiRtm3bphkzZtz+ZwIAAPKlHIWREydOKCIiQsePH5eHh4ceeOABrV27Vg8//LAkKS4uTk5O/7+zpXHjxlqwYIFGjRqlkSNHqkqVKlq6dKlq1qx5e58FAADIt275OiN3Q167zggDWLPGAFYAQLo7fp0RAACA24EwAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwKgchZGoqCjVr19fbm5u8vHxUXh4uPbu3XvDeebOnSubzeYwubi43FLRAACg4MhRGNm0aZMGDBigH374QdHR0bp8+bLatGmjlJSUG87n7u6u48eP26fDhw/fUtEAAKDgKJyTzmvWrHG4PXfuXPn4+Oinn35S8+bNs5zPZrPJz88vdxUCAIAC7ZbGjCQmJkqSvLy8btgvOTlZFSpUULly5dSpUyft2bPnhv1TU1OVlJTkMAEAgIIp12EkLS1NQ4YMUZMmTVSzZs0s+1WrVk2zZ8/WsmXL9MknnygtLU2NGzfW0aNHs5wnKipKHh4e9qlcuXK5LRMAAORxNsuyrNzM+Nxzz2n16tX67rvvdN9992V7vsuXL+v+++9X9+7dNWHChEz7pKamKjU11X47KSlJ5cqVU2Jiotzd3XNT7m0VMHyl6RLyrEOvtzNdAgAgj0hKSpKHh8dNP79zNGYk3cCBA7VixQpt3rw5R0FEkooUKaI6depo3759WfZxdnaWs7NzbkoDAAD5TI4O01iWpYEDB2rJkiVav369AgMDc/yAV69e1a5du+Tv75/jeQEAQMGToz0jAwYM0IIFC7Rs2TK5ubkpPj5ekuTh4SFXV1dJUkREhMqWLauoqChJ0vjx49WoUSNVrlxZZ8+e1VtvvaXDhw+rX79+t/mpAACA/ChHYWTatGmSpJYtWzq0z5kzR71795YkxcXFycnp/3e4nDlzRv3791d8fLxKliypunXrKiYmRkFBQbdWOQAAKBByPYD1bsruAJi7hQGsWWMAKwAgXXY/v/ltGgAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFE5CiNRUVGqX7++3Nzc5OPjo/DwcO3du/em833++eeqXr26XFxcFBwcrFWrVuW6YAAAULDkKIxs2rRJAwYM0A8//KDo6GhdvnxZbdq0UUpKSpbzxMTEqHv37urbt6927Nih8PBwhYeHa/fu3bdcPAAAyP9slmVZuZ35r7/+ko+PjzZt2qTmzZtn2qdr165KSUnRihUr7G2NGjVS7dq1NX369Gw9TlJSkjw8PJSYmCh3d/fclnvbBAxfabqEPOvQ6+1MlwAAyCOy+/l9S2NGEhMTJUleXl5Z9omNjVVoaKhDW1hYmGJjY7OcJzU1VUlJSQ4TAAAomHIdRtLS0jRkyBA1adJENWvWzLJffHy8fH19Hdp8fX0VHx+f5TxRUVHy8PCwT+XKlcttmQAAII/LdRgZMGCAdu/erUWLFt3OeiRJI0aMUGJion06cuTIbX8MAACQNxTOzUwDBw7UihUrtHnzZt1333037Ovn56eEhASHtoSEBPn5+WU5j7Ozs5ydnXNTGgAAyGdytGfEsiwNHDhQS5Ys0fr16xUYGHjTeUJCQrRu3TqHtujoaIWEhOSsUgAAUCDlaM/IgAEDtGDBAi1btkxubm72cR8eHh5ydXWVJEVERKhs2bKKioqSJA0ePFgtWrTQpEmT1K5dOy1atEjbtm3TjBkzbvNTAQAA+VGO9oxMmzZNiYmJatmypfz9/e3Tp59+au8TFxen48eP2283btxYCxYs0IwZM1SrVi0tXrxYS5cuveGgVwAAcO/I0Z6R7FySZOPGjRnaunTpoi5duuTkoQAAwD2C36YBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgVI7DyObNm9WhQweVKVNGNptNS5cuvWH/jRs3ymazZZji4+NzWzMAAChAchxGUlJSVKtWLU2dOjVH8+3du1fHjx+3Tz4+Pjl9aAAAUAAVzukMbdu2Vdu2bXP8QD4+PvL09MzxfAAAoGC7a2NGateuLX9/fz388MP6/vvv79bDAgCAPC7He0Zyyt/fX9OnT1e9evWUmpqqWbNmqWXLltqyZYsefPDBTOdJTU1Vamqq/XZSUtKdLhMAABhyx8NItWrVVK1aNfvtxo0ba//+/Xr33Xc1f/78TOeJiorSuHHj7nRpAAAgDzByam+DBg20b9++LO8fMWKEEhMT7dORI0fuYnUAAOBuuuN7RjKzc+dO+fv7Z3m/s7OznJ2d72JFAADAlByHkeTkZIe9GgcPHtTOnTvl5eWl8uXLa8SIETp27Jg+/vhjSdLkyZMVGBioGjVq6OLFi5o1a5bWr1+vr7/++vY9CwAAkG/lOIxs27ZNDz30kP32sGHDJEm9evXS3Llzdfz4ccXFxdnvv3Tpkv75z3/q2LFjKlasmB544AF98803DssAAAD3LptlWZbpIm4mKSlJHh4eSkxMlLu7u+lyFDB8pekS8qxDr7czXQIAII/I7uc3v00DAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwKsdhZPPmzerQoYPKlCkjm82mpUuX3nSejRs36sEHH5Szs7MqV66suXPn5qJUAABQEOU4jKSkpKhWrVqaOnVqtvofPHhQ7dq100MPPaSdO3dqyJAh6tevn9auXZvjYgEAQMFTOKcztG3bVm3bts12/+nTpyswMFCTJk2SJN1///367rvv9O677yosLCynDw8AAAqYOz5mJDY2VqGhoQ5tYWFhio2NzXKe1NRUJSUlOUwAAKBguuNhJD4+Xr6+vg5tvr6+SkpK0oULFzKdJyoqSh4eHvapXLlyd7pMAABgSJ48m2bEiBFKTEy0T0eOHDFdEgAAuENyPGYkp/z8/JSQkODQlpCQIHd3d7m6umY6j7Ozs5ydne90aQAAIA+443tGQkJCtG7dOoe26OhohYSE3OmHBgAA+UCOw0hycrJ27typnTt3Srp26u7OnTsVFxcn6dohloiICHv/Z599VgcOHNC///1v/fbbb/rggw/02WefaejQobfnGQAAgHwtx2Fk27ZtqlOnjurUqSNJGjZsmOrUqaNXXnlFknT8+HF7MJGkwMBArVy5UtHR0apVq5YmTZqkWbNmcVovAACQJNksy7JMF3EzSUlJ8vDwUGJiotzd3U2Xo4DhK02XkGcder2d6RIAAHlEdj+/8+TZNAAA4N5BGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGBUrsLI1KlTFRAQIBcXFzVs2FBbt27Nsu/cuXNls9kcJhcXl1wXDAAACpYch5FPP/1Uw4YN05gxY7R9+3bVqlVLYWFhOnHiRJbzuLu76/jx4/bp8OHDt1Q0AAAoOHIcRt555x31799fkZGRCgoK0vTp01WsWDHNnj07y3lsNpv8/Pzsk6+v7y0VDQAACo4chZFLly7pp59+Umho6P8vwMlJoaGhio2NzXK+5ORkVahQQeXKlVOnTp20Z8+eGz5OamqqkpKSHCYAAFAw5SiMnDx5UlevXs2wZ8PX11fx8fGZzlOtWjXNnj1by5Yt0yeffKK0tDQ1btxYR48ezfJxoqKi5OHhYZ/KlSuXkzIBAEA+csfPpgkJCVFERIRq166tFi1a6Msvv5S3t7c+/PDDLOcZMWKEEhMT7dORI0fudJkAAMCQwjnpXLp0aRUqVEgJCQkO7QkJCfLz88vWMooUKaI6depo3759WfZxdnaWs7NzTkoDAAD5VI72jBQtWlR169bVunXr7G1paWlat26dQkJCsrWMq1evateuXfL3989ZpQAAoEDK0Z4RSRo2bJh69eqlevXqqUGDBpo8ebJSUlIUGRkpSYqIiFDZsmUVFRUlSRo/frwaNWqkypUr6+zZs3rrrbd0+PBh9evX7/Y+EwAAkC/lOIx07dpVf/31l1555RXFx8erdu3aWrNmjX1Qa1xcnJyc/n+Hy5kzZ9S/f3/Fx8erZMmSqlu3rmJiYhQUFHT7ngUAAMi3bJZlWaaLuJmkpCR5eHgoMTFR7u7upstRwPCVpkvIsw693s50CQCAPCK7n9/8Ng0AADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjchVGpk6dqoCAALm4uKhhw4baunXrDft//vnnql69ulxcXBQcHKxVq1blqlgAAFDw5DiMfPrppxo2bJjGjBmj7du3q1atWgoLC9OJEycy7R8TE6Pu3burb9++2rFjh8LDwxUeHq7du3ffcvEAACD/s1mWZeVkhoYNG6p+/fqaMmWKJCktLU3lypXToEGDNHz48Az9u3btqpSUFK1YscLe1qhRI9WuXVvTp0/P1mMmJSXJw8NDiYmJcnd3z0m5d0TA8JWmS8izDr3eznQJAIA8Iruf3znaM3Lp0iX99NNPCg0N/f8FODkpNDRUsbGxmc4TGxvr0F+SwsLCsuwPAADuLYVz0vnkyZO6evWqfH19Hdp9fX3122+/ZTpPfHx8pv3j4+OzfJzU1FSlpqbabycmJkq6lrDygrTU86ZLyLPyyv8IAGBe+mfCzQ7C5CiM3C1RUVEaN25chvZy5coZqAY54THZdAUAgLzm1KlT8vDwyPL+HIWR0qVLq1ChQkpISHBoT0hIkJ+fX6bz+Pn55ai/JI0YMULDhg2z305LS9Pp06dVqlQp2Wy2nJRc4CUlJalcuXI6cuRInhhPg7yPbQa5wXaD3EhMTFT58uXl5eV1w345CiNFixZV3bp1tW7dOoWHh0u6FhTWrVungQMHZjpPSEiI1q1bpyFDhtjboqOjFRISkuXjODs7y9nZ2aHN09MzJ6Xec9zd3XmDQI6wzSA32G6QG05ONx6imuPDNMOGDVOvXr1Ur149NWjQQJMnT1ZKSooiIyMlSRERESpbtqyioqIkSYMHD1aLFi00adIktWvXTosWLdK2bds0Y8aMXDwdAABQ0OQ4jHTt2lV//fWXXnnlFcXHx6t27dpas2aNfZBqXFycQwJq3LixFixYoFGjRmnkyJGqUqWKli5dqpo1a96+ZwEAAPKtXA1gHThwYJaHZTZu3JihrUuXLurSpUtuHgo34ezsrDFjxmQ4rAVkhW0GucF2g9zI7naT44ueAQAA3E78UB4AADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjMqTP5SHG5szZ466du2qYsWKmS4F+dClS5d04sQJpaWlObSXL1/eUEXIS0qWLJnt3wA7ffr0Ha4G9wquM5IP+fr66sKFC+rSpYv69u2rxo0bmy4J+cAff/yhPn36KCYmxqHdsizZbDZdvXrVUGXIS+bNm2f/+9SpU3r11VcVFhZm/z2x2NhYrV27VqNHj9bQoUNNlYkChjCSD125ckXLly/X3LlztXr1alWsWFGRkZHq1avXDX8NGfe2Jk2aqHDhwho+fLj8/f0zfPutVauWocqQVz3xxBN66KGHMlxxe8qUKfrmm2+0dOlSM4WhwCGM5HMJCQn65JNPNG/ePP3222965JFH1LdvX3Xo0OGmv5KIe0vx4sX1008/qXr16qZLQT5RokQJ7dy5U5UrV3Zo37dvn2rXrq3k5GRDlaGg4dMqn/P19VXTpk0VEhIiJycn7dq1S7169VKlSpUy/Z0g3LuCgoJ08uRJ02UgHylVqpSWLVuWoX3ZsmUqVaqUgYpQUDGANZ9KSEjQ/PnzNWfOHB04cEDh4eFasWKFQkNDlZKSovHjx6tXr146fPiw6VJhUFJSkv3vN954Q//+9781ceJEBQcHq0iRIg593d3d73Z5yOPGjRunfv36aePGjWrYsKEkacuWLVqzZo1mzpxpuDoUJBymyYc6dOigtWvXqmrVqurXr58iIiLk5eXl0OfEiRPy8/PLcMYE7i1OTk4OY0PSB6tejwGsuJEtW7bo/fff16+//ipJuv/++/XCCy/YwwlwO7BnJB/y8fHRpk2b7KPbM+Pt7a2DBw/exaqQF23YsMF0CcjnGjZsqP/+97+my0ABx54RAMBNXbx4UZcuXXJo49AebhcGsOZT69atU/v27VWpUiVVqlRJ7du31zfffGO6LORx3377rXr27KnGjRvr2LFjkqT58+fru+++M1wZ8qLz589r4MCB8vHxUfHixVWyZEmHCbhdCCP50AcffKBHHnlEbm5uGjx4sAYPHix3d3c9+uijmjp1qunykEd98cUXCgsLk6urq7Zv367U1FRJUmJioiZOnGi4OuRF//rXv7R+/XpNmzZNzs7OmjVrlsaNG6cyZcro448/Nl0eChAO0+RD9913n4YPH57hQkRTp07VxIkT7d94gevVqVNHQ4cOVUREhNzc3PTzzz+rYsWK2rFjh9q2bav4+HjTJSKPKV++vD7++GO1bNlS7u7u2r59uypXrqz58+dr4cKFWrVqlekSUUCwZyQfOnv2rB555JEM7W3atFFiYqKBipAf7N27V82bN8/Q7uHhobNnz979gpDnnT59WhUrVpR0bXxI+m/RNG3aVJs3bzZZGgoYwkg+1LFjRy1ZsiRD+7Jly9S+fXsDFSE/8PPz0759+zK0f/fdd/YPHOB6FStWtJ+VV716dX322WeSpOXLl8vT09NgZShoOLU3HwoKCtJrr72mjRs32k/v/eGHH/T999/rn//8p95//3173xdeeMFUmchj+vfvr8GDB2v27Nmy2Wz6888/FRsbqxdffFGjR482XR7yoMjISP38889q0aKFhg8frg4dOmjKlCm6fPmy3nnnHdPloQBhzEg+FBgYmK1+NptNBw4cuMPVIL+wLEsTJ05UVFSUzp8/L0lydnbWiy++qAkTJhiuDvnB4cOH9dNPP6ly5cp64IEHTJeDAoQwAtxjLl26pH379ik5OVlBQUEqUaKE6ZKQx8TGxurUqVMOh30//vhjjRkzRikpKQoPD9d//vMfOTs7G6wSBQmHafK59Cz590t8A+n69OmTrX6zZ8++w5Ugvxg/frxatmxpDyO7du1S37591bt3bwUFBenNN99UmTJlNHbsWLOFosBgAGs+9dFHH6lmzZpycXGRi4uLatasqVmzZpkuC3nQ3LlztWHDBp09e1ZnzpzJcgLS7dy5U61bt7bfXrRokRo2bKiZM2dq6NChev/99+2DWYHbgT0j+dArr7yid955R4MGDbIPYI2NjdXQoUMVFxen8ePHG64Qeclzzz2nhQsX6uDBg4qMjFTPnj0z/LAicL0zZ87I19fXfnvTpk1q27at/Xb9+vV15MgRE6WhgGLMSD7k7e2t999/X927d3doX7hwoQYNGqSTJ08aqgx5VWpqqr788kvNnj1bMTExateunfr27as2bdpwiA8ZVKhQQfPnz1fz5s116dIleXp6avny5fa9Jbt27VKLFi3s1x0BbhWHafKhy5cvq169ehna69atqytXrhioCHmds7OzunfvrujoaP3vf/9TjRo19PzzzysgIEDJycmmy0Me8+ijj2r48OH69ttvNWLECBUrVkzNmjWz3//LL7+oUqVKBitEQUMYyYeefvppTZs2LUP7jBkz1KNHDwMVIT9xcnKSzWaTZVm6evWq6XKQB02YMEGFCxdWixYtNHPmTM2cOVNFixa13z979my1adPGYIUoaDhMkw8NGjRIH3/8scqVK6dGjRpJkrZs2aK4uDhFRESoSJEi9r5cmAiS42Ga7777Tu3bt1dkZKQeeeQROTnxnQSZS0xMVIkSJVSoUCGH9tOnT6tEiRIOAQW4FYSRfOihhx7KVj+bzab169ff4WqQ1z3//PNatGiRypUrpz59+qhHjx4qXbq06bIAwI4wAhRwTk5OKl++vOrUqXPDwapffvnlXawKAP4fp/YCBVxERARnzADI09gzkk9t27ZNn332meLi4nTp0iWH+/iGCwDITxi5lg8tWrRIjRs31q+//qolS5bo8uXL2rNnj9avXy8PDw/T5QEAkCOEkXxo4sSJevfdd7V8+XIVLVpU7733nn777Tc9+eSTKl++vOnyAADIEcJIPrR//361a9dOklS0aFGlpKTIZrNp6NChmjFjhuHqAADIGcJIPlSyZEmdO3dOklS2bFnt3r1bknT27FmdP3/eZGkAAOQYZ9PkQ82bN1d0dLSCg4PVpUsXDR48WOvXr1d0dLTDL20CAJAfcDZNPnT69GldvHhRZcqUUVpamt58803FxMSoSpUqGjVqlEqWLGm6RAAAso0wko8kJSVlq5+7u/sdrgQAgNuHMJKPpP/A2c3w42cAgPyEMSP5yIYNG+x/W5alRx99VLNmzVLZsmUNVgUAwK1hz0g+5ubmpp9//lkVK1Y0XQoAALnGqb0AAMAowggAADCKMJLP8WusAID8jgGs+cjjjz/ucPvixYt69tlnVbx4cYd2frUXAJCfEEbykb//Im/Pnj0NVQIAwO3D2TQAAMAoxowAAACjCCMAAMAowggAADCKMAIUMC1bttSQIUNMlwEA2UYYAeDg0KFDstls2rlzp0N77969FR4ebqQmAAUbYQQAABhFGAEKoCtXrmjgwIHy8PBQ6dKlNXr0aKWfxW+z2bR06VKH/p6enpo7d64kKTAwUJJUp04d2Ww2tWzZUmPHjtW8efO0bNky2Ww22Ww2bdy4UZK0a9cutWrVSq6uripVqpSeeeYZJScn25edvkfl7bfflr+/v0qVKqUBAwbo8uXL2XouAQEBmjhxovr06SM3NzeVL19eM2bMcOjz0ksvqWrVqipWrJgqVqyo0aNHOyx/7Nixql27tmbPnq3y5curRIkSev7553X16lW9+eab8vPzk4+Pj1577TWH5Z49e1b9+vWTt7e33N3d1apVK/3888/ZqhtA9nHRM6AAmjdvnvr27autW7dq27ZteuaZZ1S+fHn179//pvNu3bpVDRo00DfffKMaNWqoaNGiKlq0qH799VclJSVpzpw5kiQvLy+lpKQoLCxMISEh+vHHH3XixAn169dPAwcOtIcbSdqwYYP8/f21YcMG7du3T127dlXt2rWzVY8kTZo0SRMmTNDIkSO1ePFiPffcc2rRooWqVasm6dovWM+dO1dlypTRrl271L9/f7m5uenf//63fRn79+/X6tWrtWbNGu3fv1+dO3fWgQMHVLVqVW3atEkxMTHq06ePQkND1bBhQ0lSly5d5OrqqtWrV8vDw0MffvihWrdurd9//11eXl7Z/XcAuBkLQIHSokUL6/7777fS0tLsbS+99JJ1//33W5ZlWZKsJUuWOMzj4eFhzZkzx7Isyzp48KAlydqxY4dDn169elmdOnVyaJsxY4ZVsmRJKzk52d62cuVKy8nJyYqPj7fPV6FCBevKlSv2Pl26dLG6du2aredToUIFq2fPnvbbaWlplo+PjzVt2rQs53nrrbesunXr2m+PGTPGKlasmJWUlGRvCwsLswICAqyrV6/a26pVq2ZFRUVZlmVZ3377reXu7m5dvHjRYdmVKlWyPvzww2zVDiB72DMCFECNGjVy+BHFkJAQTZo0SVevXr2tj/Prr7+qVq1aDr+P1KRJE6WlpWnv3r3y9fWVJNWoUUOFChWy9/H399euXbuy/TgPPPCA/W+bzSY/Pz+dOHHC3vbpp5/q/fff1/79+5WcnKwrV67I3d3dYRkBAQFyc3Oz3/b19VWhQoXk5OTk0Ja+3J9//lnJyckqVaqUw3IuXLig/fv3Z7t2ADdHGAHuMTabzT5+JF12x2/kVpEiRTLUkJaWdlvmj42NVY8ePTRu3DiFhYXJw8NDixYt0qRJk266jBstNzk5Wf7+/vaxMdfz9PTMdu0Abo4wAhRAW7Zscbj9ww8/qEqVKipUqJC8vb11/Phx+31//PGHzp8/b79dtGhRScqwF6Vo0aIZ2u6//37NnTtXKSkp9r0j33//vZycnOzjOe60mJgYVahQQS+//LK97fDhw7e83AcffFDx8fEqXLiwAgICbnl5ALLG2TRAARQXF6dhw4Zp7969Wrhwof7zn/9o8ODBkqRWrVppypQp2rFjh7Zt26Znn33WYQ+Bj4+PXF1dtWbNGiUkJCgxMVHStcMcv/zyi/bu3auTJ0/q8uXL6tGjh1xcXNSrVy/t3r1bGzZs0KBBg/T000/bD9HcaVWqVFFcXJwWLVqk/fv36/3339eSJUtuebmhoaEKCQlReHi4vv76ax06dEgxMTF6+eWXtW3btttQOYB0hBGgAIqIiNCFCxfUoEEDDRgwQIMHD9Yzzzwj6dqZKeXKlVOzZs301FNP6cUXX1SxYsXs8xYuXFjvv/++PvzwQ5UpU0adOnWSJPXv31/VqlVTvXr15O3tre+//17FihXT2rVrdfr0adWvX1+dO3dW69atNWXKlLv2XDt27KihQ4dq4MCBql27tmJiYjR69OhbXq7NZtOqVavUvHlzRUZGqmrVqurWrZsOHz5814IWcK+wWX8/eAwAAHAXsWcEAAAYRRgBYMy3336rEiVKZDkBuDdwmAaAMRcuXNCxY8eyvL9y5cp3sRoAphBGAACAURymAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABj1f9cywFnZYankAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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7ERERhS7h3Llzp9WxY0fLbrdbd911l5WQkGDNmDHDkmSlp6dfcz+ud6nyFfrNpb0FBQXW5MmTrfr161t2u91q1aqV9fe//73QZaBXLu3985//XGidV1/ae7WXX37ZkmTNnDnT0fb1119bYWFhlpeXlxUcHGzNmTPHUfvVLl++bE2YMMFq0KCBVb58eSswMNAaNWpUoffFsixr1qxZliTr2WefdWqPjIy0JFnr168vUb1X9rGoy2KvdvWlvb8VExNjSSp0GXhJ9yc9Pd3q3r27VblyZUuS4zNy6dIl68UXX7Rq165tVahQwWrfvr2Vmppa5Ofos88+s5o1a2aVK1fOaX9++55almWdO3fOGj58uFWnTh2rfPnyVqNGjaw///nPjsugr/jt5+aK+vXrWzExMdd8vYDfw2ZZzEoCTHvhhRc0d+5cnT9/vtgJhABQVjFnBLjFfntlz+nTp/XBBx+oQ4cOBBEAdyTmjAC3WHh4uDp37qymTZsqIyNDCxcuVFZWlsaMGWO6NAAwgjAC3GLdunXTihUrNG/ePNlsNt13331auHBhoXuqAMCdgjkjAADAKOaMAAAAowgjAADAKLeYM1JQUKAff/xRlStX/l33fQAAALeOZVk6d+6c6tSpU+y9syQ3CSM//vijAgMDTZcBAABK4dixY7rrrruKXe4WYeTK13AfO3ZMvr6+hqsBAAAlkZWVpcDAwOveTsMtwsiVUzO+vr6EEQAA3Mz1plgwgRUAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGuRxGvvnmG/Xs2VN16tSRzWbTqlWrrjsmOTlZ9913n+x2uxo2bKjFixeXolQAAFAWuRxGsrOz1bJlS82aNatE/Q8fPqzu3burS5cu2rVrl1544QUNGjRIa9eudblYAABQ9rh8o7xHHnlEjzzySIn7z5kzRw0aNNCUKVMkSU2bNtWmTZs0bdo0RUVFubp5AABQxtz0OSOpqamKjIx0aouKilJqaurN3jQAAHADLh8ZcVV6err8/f2d2vz9/ZWVlaWLFy+qQoUKhcbk5OQoJyfH8TwrK+tmlwkAAAy56WGkNBISEjRhwgTTZRQraORq0yXcto682d10CbctPjfF43MD3Nlu+mmagIAAZWRkOLVlZGTI19e3yKMikjRq1ChlZmY6HseOHbvZZQIAAENu+pGR8PBwrVmzxqlt3bp1Cg8PL3aM3W6X3W6/2aUBAIDbgMtHRs6fP69du3Zp165dkn65dHfXrl1KS0uT9MtRjejoaEf/Z555RocOHdLLL7+sffv26b333tMnn3yi4cOH35g9AAAAbs3lMLJt2za1atVKrVq1kiTFx8erVatWGjt2rCTpp59+cgQTSWrQoIFWr16tdevWqWXLlpoyZYoWLFjAZb0AAEBSKU7TdO7cWZZlFbu8qG9X7dy5s3bu3OnqpgAAwB2Ae9MAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMKlUYmTVrloKCguTt7a22bdtqy5Yt1+w/ffp0NW7cWBUqVFBgYKCGDx+uS5culapgAABQtrgcRpYvX674+HiNGzdOO3bsUMuWLRUVFaUTJ04U2X/p0qUaOXKkxo0bp71792rhwoVavny5Xn311d9dPAAAcH8uh5GpU6dq8ODBio2NVbNmzTRnzhxVrFhRiYmJRfZPSUlR+/bt1a9fPwUFBalr1656/PHHr3s0BQAA3BlcCiO5ubnavn27IiMjf12Bh4ciIyOVmppa5Jh27dpp+/btjvBx6NAhrVmzRt26dSt2Ozk5OcrKynJ6AACAsqmcK51PnTql/Px8+fv7O7X7+/tr3759RY7p16+fTp06pQ4dOsiyLOXl5emZZ5655mmahIQETZgwwZXSAACAm7rpV9MkJydr8uTJeu+997Rjxw6tXLlSq1ev1qRJk4odM2rUKGVmZjoex44du9llAgAAQ1w6MlKjRg15enoqIyPDqT0jI0MBAQFFjhkzZowGDBigQYMGSZLuueceZWdn6+mnn9bo0aPl4VE4D9ntdtntdldKAwAAbsqlIyNeXl4KCwvT+vXrHW0FBQVav369wsPDixxz4cKFQoHD09NTkmRZlqv1AgCAMsalIyOSFB8fr5iYGLVu3Vpt2rTR9OnTlZ2drdjYWElSdHS06tatq4SEBElSz549NXXqVLVq1Upt27bVgQMHNGbMGPXs2dMRSgAAwJ3L5TDSt29fnTx5UmPHjlV6erpCQ0OVlJTkmNSalpbmdCTktddek81m02uvvabjx4+rZs2a6tmzp954440btxcAAMBt2Sw3OFeSlZUlPz8/ZWZmytfX13Q5Chq52nQJt60jb3Y3XcJti89N8fjcAGVTSX9/c28aAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARpUqjMyaNUtBQUHy9vZW27ZttWXLlmv2P3v2rIYMGaLatWvLbrfr7rvv1po1a0pVMAAAKFvKuTpg+fLlio+P15w5c9S2bVtNnz5dUVFR2r9/v2rVqlWof25urv7whz+oVq1aWrFiherWraujR4+qSpUqN6J+AADg5lwOI1OnTtXgwYMVGxsrSZozZ45Wr16txMREjRw5slD/xMREnTlzRikpKSpfvrwkKSgo6PdVDQAAygyXTtPk5uZq+/btioyM/HUFHh6KjIxUampqkWP+93//V+Hh4RoyZIj8/f3VokULTZ48Wfn5+cVuJycnR1lZWU4PAABQNrkURk6dOqX8/Hz5+/s7tfv7+ys9Pb3IMYcOHdKKFSuUn5+vNWvWaMyYMZoyZYpef/31YreTkJAgPz8/xyMwMNCVMgEAgBu56VfTFBQUqFatWpo3b57CwsLUt29fjR49WnPmzCl2zKhRo5SZmel4HDt27GaXCQAADHFpzkiNGjXk6empjIwMp/aMjAwFBAQUOaZ27doqX768PD09HW1NmzZVenq6cnNz5eXlVWiM3W6X3W53pTQAAOCmXDoy4uXlpbCwMK1fv97RVlBQoPXr1ys8PLzIMe3bt9eBAwdUUFDgaPvhhx9Uu3btIoMIAAC4s7h8miY+Pl7z58/XkiVLtHfvXj377LPKzs52XF0THR2tUaNGOfo/++yzOnPmjIYNG6YffvhBq1ev1uTJkzVkyJAbtxcAAMBtuXxpb9++fXXy5EmNHTtW6enpCg0NVVJSkmNSa1pamjw8fs04gYGBWrt2rYYPH657771XdevW1bBhw/TKK6/cuL0AAABuy+UwIklxcXGKi4srcllycnKhtvDwcP3zn/8szaYAAEAZx71pAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARhFGAACAUYQRAABgFGEEAAAYRRgBAABGEUYAAIBRhBEAAGAUYQQAABhFGAEAAEYRRgAAgFGEEQAAYBRhBAAAGEUYAQAARpUqjMyaNUtBQUHy9vZW27ZttWXLlhKNW7ZsmWw2m3r16lWazQIAgDLI5TCyfPlyxcfHa9y4cdqxY4datmypqKgonThx4prjjhw5ohEjRqhjx46lLhYAAJQ9LoeRqVOnavDgwYqNjVWzZs00Z84cVaxYUYmJicWOyc/PV//+/TVhwgQFBwf/roIBAEDZ4lIYyc3N1fbt2xUZGfnrCjw8FBkZqdTU1GLHTZw4UbVq1dLAgQNLtJ2cnBxlZWU5PQAAQNnkUhg5deqU8vPz5e/v79Tu7++v9PT0Isds2rRJCxcu1Pz580u8nYSEBPn5+TkegYGBrpQJAADcyE29mubcuXMaMGCA5s+frxo1apR43KhRo5SZmel4HDt27CZWCQAATCrnSucaNWrI09NTGRkZTu0ZGRkKCAgo1P/gwYM6cuSIevbs6WgrKCj4ZcPlymn//v0KCQkpNM5ut8tut7tSGgAAcFMuHRnx8vJSWFiY1q9f72grKCjQ+vXrFR4eXqh/kyZNtGfPHu3atcvxePTRR9WlSxft2rWL0y8AAMC1IyOSFB8fr5iYGLVu3Vpt2rTR9OnTlZ2drdjYWElSdHS06tatq4SEBHl7e6tFixZO46tUqSJJhdoBAMCdyeUw0rdvX508eVJjx45Venq6QkNDlZSU5JjUmpaWJg8PvtgVAACUjMthRJLi4uIUFxdX5LLk5ORrjl28eHFpNgkAAMooDmEAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwqlRhZNasWQoKCpK3t7fatm2rLVu2FNt3/vz56tixo6pWraqqVasqMjLymv0BAMCdxeUwsnz5csXHx2vcuHHasWOHWrZsqaioKJ04caLI/snJyXr88ce1YcMGpaamKjAwUF27dtXx48d/d/EAAMD9uRxGpk6dqsGDBys2NlbNmjXTnDlzVLFiRSUmJhbZ/6OPPtJzzz2n0NBQNWnSRAsWLFBBQYHWr1//u4sHAADuz6Uwkpubq+3btysyMvLXFXh4KDIyUqmpqSVax4ULF3T58mVVq1at2D45OTnKyspyegAAgLLJpTBy6tQp5efny9/f36nd399f6enpJVrHK6+8ojp16jgFmt9KSEiQn5+f4xEYGOhKmQAAwI3c0qtp3nzzTS1btkyffvqpvL29i+03atQoZWZmOh7Hjh27hVUCAIBbqZwrnWvUqCFPT09lZGQ4tWdkZCggIOCaY9955x29+eab+vLLL3Xvvfdes6/dbpfdbnelNAAA4KZcOjLi5eWlsLAwp8mnVyajhoeHFzvu7bff1qRJk5SUlKTWrVuXvloAAFDmuHRkRJLi4+MVExOj1q1bq02bNpo+fbqys7MVGxsrSYqOjlbdunWVkJAgSXrrrbc0duxYLV26VEFBQY65JT4+PvLx8bmBuwIAANyRy2Gkb9++OnnypMaOHav09HSFhoYqKSnJMak1LS1NHh6/HnCZPXu2cnNz1bt3b6f1jBs3TuPHj/991QMAALfnchiRpLi4OMXFxRW5LDk52en5kSNHSrMJAABwh+DeNAAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAowgjAADAKMIIAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIwqVRiZNWuWgoKC5O3trbZt22rLli3X7P/Xv/5VTZo0kbe3t+655x6tWbOmVMUCAICyx+Uwsnz5csXHx2vcuHHasWOHWrZsqaioKJ04caLI/ikpKXr88cc1cOBA7dy5U7169VKvXr30r3/963cXDwAA3J/LYWTq1KkaPHiwYmNj1axZM82ZM0cVK1ZUYmJikf3/8pe/6OGHH9ZLL72kpk2batKkSbrvvvs0c+bM3108AABwfy6FkdzcXG3fvl2RkZG/rsDDQ5GRkUpNTS1yTGpqqlN/SYqKiiq2PwAAuLOUc6XzqVOnlJ+fL39/f6d2f39/7du3r8gx6enpRfZPT08vdjs5OTnKyclxPM/MzJQkZWVluVLuTVOQc8F0Cbet2+U9uh3xuSkenxugbLry/7ZlWdfs51IYuVUSEhI0YcKEQu2BgYEGqoEr/KabrgDuiM8NULadPn1afn5+xS53KYzUqFFDnp6eysjIcGrPyMhQQEBAkWMCAgJc6i9Jo0aNUnx8vON5QUGBzpw5o+rVq8tms7lScpmXlZWlwMBAHTt2TL6+vqbLgRvgM4PS4HOD0sjMzFS9evVUrVq1a/ZzKYx4eXkpLCxM69evV69evST9EhTWr1+vuLi4IseEh4dr/fr1euGFFxxt69atU3h4eLHbsdvtstvtTm1VqlRxpdQ7jq+vL/9AwCV8ZlAafG5QGh4e156i6vJpmvj4eMXExKh169Zq06aNpk+fruzsbMXGxkqSoqOjVbduXSUkJEiShg0bpoiICE2ZMkXdu3fXsmXLtG3bNs2bN68UuwMAAMoal8NI3759dfLkSY0dO1bp6ekKDQ1VUlKSY5JqWlqaUwJq166dli5dqtdee02vvvqqGjVqpFWrVqlFixY3bi8AAIDbKtUE1ri4uGJPyyQnJxdq69Onj/r06VOaTeE67Ha7xo0bV+i0FlAcPjMoDT43KI2Sfm5s1vWutwEAALiJuFEeAAAwijACAACMIowAAACjCCMAAMAowggAADCKMAIAAIy6LW+Uh2tbtGiR+vbtq4oVK5ouBW4oNzdXJ06cUEFBgVN7vXr1DFWE20nVqlVLfA+wM2fO3ORqcKfge0bckL+/vy5evKg+ffpo4MCBateunemS4Ab+85//6KmnnlJKSopTu2VZstlsys/PN1QZbidLlixx/Hz69Gm9/vrrioqKctxPLDU1VWvXrtWYMWM0fPhwU2WijCGMuKG8vDx9/vnnWrx4sb744gsFBwcrNjZWMTEx17wbMu5s7du3V7ly5TRy5EjVrl270F+/LVu2NFQZbld//OMf1aVLl0LfuD1z5kx9+eWXWrVqlZnCUOYQRtxcRkaGPvzwQy1ZskT79u3Tww8/rIEDB6pnz57XvUsi7iyVKlXS9u3b1aRJE9OlwE34+Pho165datiwoVP7gQMHFBoaqvPnzxuqDGUNv63cnL+/vzp06KDw8HB5eHhoz549iomJUUhISJH3CcKdq1mzZjp16pTpMuBGqlevrs8++6xQ+2effabq1asbqAhlFRNY3VRGRoY++OADLVq0SIcOHVKvXr3097//XZGRkcrOztbEiRMVExOjo0ePmi4VBmVlZTl+fuutt/Tyyy9r8uTJuueee1S+fHmnvr6+vre6PNzmJkyYoEGDBik5OVlt27aVJG3evFlJSUmaP3++4epQlnCaxg317NlTa9eu1d13361BgwYpOjpa1apVc+pz4sQJBQQEFLpiAncWDw8Pp7khVyarXo0JrLiWzZs3a8aMGdq7d68kqWnTpnr++ecd4QS4ETgy4oZq1aqlr7/+2jG7vSg1a9bU4cOHb2FVuB1t2LDBdAlwc23bttVHH31kugyUcRwZAQBc16VLl5Sbm+vUxqk93ChMYHVT69evV48ePRQSEqKQkBD16NFDX375pemycJvbuHGjnnjiCbVr107Hjx+XJH3wwQfatGmT4cpwO7pw4YLi4uJUq1YtVapUSVWrVnV6ADcKYcQNvffee3r44YdVuXJlDRs2TMOGDZOvr6+6deumWbNmmS4Pt6m//e1vioqKUoUKFbRjxw7l5ORIkjIzMzV58mTD1eF29NJLL+mrr77S7NmzZbfbtWDBAk2YMEF16tTR+++/b7o8lCGcpnFDd911l0aOHFnoi4hmzZqlyZMnO/7iBa7WqlUrDR8+XNHR0apcubJ2796t4OBg7dy5U4888ojS09NNl4jbTL169fT++++rc+fO8vX11Y4dO9SwYUN98MEH+vjjj7VmzRrTJaKM4MiIGzp79qwefvjhQu1du3ZVZmamgYrgDvbv369OnToVavfz89PZs2dvfUG47Z05c0bBwcGSfpkfcuVeNB06dNA333xjsjSUMYQRN/Too4/q008/LdT+2WefqUePHgYqgjsICAjQgQMHCrVv2rTJ8QsHuFpwcLDjqrwmTZrok08+kSR9/vnnqlKlisHKUNZwaa8batasmd544w0lJyc7Lu/95z//qW+//VYvvviiZsyY4ej7/PPPmyoTt5nBgwdr2LBhSkxMlM1m048//qjU1FSNGDFCY8aMMV0ebkOxsbHavXu3IiIiNHLkSPXs2VMzZ87U5cuXNXXqVNPloQxhzogbatCgQYn62Ww2HTp06CZXA3dhWZYmT56shIQEXbhwQZJkt9s1YsQITZo0yXB1cAdHjx7V9u3b1bBhQ917772my0EZQhgB7jC5ubk6cOCAzp8/r2bNmsnHx8d0SbjNpKam6vTp006nfd9//32NGzdO2dnZ6tWrl959913Z7XaDVaIs4TSNm7uSJX/7Fd/AFU899VSJ+iUmJt7kSuAuJk6cqM6dOzvCyJ49ezRw4EA9+eSTatasmd5++23VqVNH48ePN1soygwmsLqphQsXqkWLFvL29pa3t7datGihBQsWmC4Lt6HFixdrw4YNOnv2rH7++ediH8AVu3bt0kMPPeR4vmzZMrVt21bz58/X8OHDNWPGDMdkVuBG4MiIGxo7dqymTp2qoUOHOiawpqamavjw4UpLS9PEiRMNV4jbybPPPquPP/5Yhw8fVmxsrJ544olCN1YErvbzzz/L39/f8fzrr7/WI4884nh+//3369ixYyZKQxnFnBE3VLNmTc2YMUOPP/64U/vHH3+soUOH6tSpU4Yqw+0qJydHK1euVGJiolJSUtS9e3cNHDhQXbt25RQfCqlfv74++OADderUSbm5uapSpYo+//xzx9GSPXv2KCIiwvG9I8DvxWkaN3T58mW1bt26UHtYWJjy8vIMVITbnd1u1+OPP65169bp+++/V/PmzfXcc88pKChI58+fN10ebjPdunXTyJEjtXHjRo0aNUoVK1ZUx44dHcu/++47hYSEGKwQZQ1hxA0NGDBAs2fPLtQ+b9489e/f30BFcCceHh6y2WyyLEv5+fmmy8FtaNKkSSpXrpwiIiI0f/58zZ8/X15eXo7liYmJ6tq1q8EKUdZwmsYNDR06VO+//74CAwP1wAMPSJI2b96stLQ0RUdHq3z58o6+fDERJOfTNJs2bVKPHj0UGxurhx9+WB4e/E2ComVmZsrHx0eenp5O7WfOnJGPj49TQAF+D8KIG+rSpUuJ+tlsNn311Vc3uRrc7p577jktW7ZMgYGBeuqpp9S/f3/VqFHDdFkA4EAYAco4Dw8P1atXT61atbrmZNWVK1fewqoA4Fdc2guUcdHR0VwxA+C2xpERN7Vt2zZ98sknSktLU25urtMy/sIFALgTZq65oWXLlqldu3bau3evPv30U12+fFn//ve/9dVXX8nPz890eQAAuIQw4oYmT56sadOm6fPPP5eXl5f+8pe/aN++ffqf//kf1atXz3R5AAC4hDDihg4ePKju3btLkry8vJSdnS2bzabhw4dr3rx5hqsDAMA1hBE3VLVqVZ07d06SVLduXf3rX/+SJJ09e1YXLlwwWRoAAC7jaho31KlTJ61bt0733HOP+vTpo2HDhumrr77SunXrnO60CQCAO+BqGjd05swZXbp0SXXq1FFBQYHefvttpaSkqFGjRnrttddUtWpV0yUCAFBihBE3kpWVVaJ+vr6+N7kSAABuHMKIG7lyg7Pr4eZnAAB3wpwRN7JhwwbHz5ZlqVu3blqwYIHq1q1rsCoAAH4fjoy4scqVK2v37t0KDg42XQoAAKXGpb0AAMAowggAADCKMOLmuBsrAMDdMYHVjfz3f/+30/NLly7pmWeeUaVKlZzauWsvAMCdEEbcyG/vyPvEE08YqgQAgBuHq2kAAIBRzBkBAABGEUYAAIBRhBEAAGAUYQQoYzp37qwXXnjBdBkAUGKEEQBOjhw5IpvNpl27djm1P/nkk+rVq5eRmgCUbYQRAABgFGEEKIPy8vIUFxcnPz8/1ahRQ2PGjNGVq/htNptWrVrl1L9KlSpavHixJKlBgwaSpFatWslms6lz584aP368lixZos8++0w2m002m03JycmSpD179ujBBx9UhQoVVL16dT399NM6f/68Y91Xjqi88847ql27tqpXr64hQ4bo8uXLJdqXoKAgTZ48WU899ZQqV66sevXqad68eU59XnnlFd19992qWLGigoODNWbMGKf1jx8/XqGhoUpMTFS9evXk4+Oj5557Tvn5+Xr77bcVEBCgWrVq6Y033nBa79mzZzVo0CDVrFlTvr6+evDBB7V79+4S1Q2g5PjSM6AMWrJkiQYOHKgtW7Zo27Ztevrpp1WvXj0NHjz4umO3bNmiNm3a6Msvv1Tz5s3l5eUlLy8v7d27V1lZWVq0aJEkqVq1asrOzlZUVJTCw8O1detWnThxQoMGDVJcXJwj3EjShg0bVLt2bW3YsEEHDhxQ3759FRoaWqJ6JGnKlCmaNGmSXn31Va1YsULPPvusIiIi1LhxY0m/3MF68eLFqlOnjvbs2aPBgwercuXKevnllx3rOHjwoL744gslJSXp4MGD6t27tw4dOqS7775bX3/9tVJSUvTUU08pMjJSbdu2lST16dNHFSpU0BdffCE/Pz/NnTtXDz30kH744QdVq1atpG8HgOuxAJQpERERVtOmTa2CggJH2yuvvGI1bdrUsizLkmR9+umnTmP8/PysRYsWWZZlWYcPH7YkWTt37nTqExMTYz322GNObfPmzbOqVq1qnT9/3tG2evVqy8PDw0pPT3eMq1+/vpWXl+fo06dPH6tv374l2p/69etbTzzxhON5QUGBVatWLWv27NnFjvnzn/9shYWFOZ6PGzfOqlixopWVleVoi4qKsoKCgqz8/HxHW+PGja2EhATLsixr48aNlq+vr3Xp0iWndYeEhFhz584tUe0ASoYjI0AZ9MADDzjdRDE8PFxTpkxRfn7+Dd3O3r171bJlS6f7I7Vv314FBQXav3+//P39JUnNmzeXp6eno0/t2rW1Z8+eEm/n3nvvdfxss9kUEBCgEydOONqWL1+uGTNm6ODBgzp//rzy8vLk6+vrtI6goCBVrlzZ8dzf31+enp7y8PBwaruy3t27d+v8+fOqXr2603ouXryogwcPlrh2ANdHGAHuMDabzTF/5IqSzt8orfLlyxeqoaCg4IaMT01NVf/+/TVhwgRFRUXJz89Py5Yt05QpU667jmut9/z586pdu7ZjbszVqlSpUuLaAVwfYQQogzZv3uz0/J///KcaNWokT09P1axZUz/99JNj2X/+8x9duHDB8dzLy0uSCh1F8fLyKtTWtGlTLV68WNnZ2Y6jI99++608PDwc8zlutpSUFNWvX1+jR492tB09evR3r/e+++5Tenq6ypUrp6CgoN+9PgDF42oaoAxKS0tTfHy89u/fr48//ljvvvuuhg0bJkl68MEHNXPmTO3cuVPbtm3TM88843SEoFatWqpQoYKSkpKUkZGhzMxMSb+c5vjuu++0f/9+nTp1SpcvX1b//v3l7e2tmJgY/etf/9KGDRs0dOhQDRgwwHGK5mZr1KiR0tLStGzZMh08eFAzZszQp59++rvXGxkZqfDwcPXq1Uv/+Mc/dOTIEaWkpGj06NHatm3bDagcwBWEEaAMio6O1sWLF9WmTRsNGTJEw4YN09NPPy3plytTAgMD1bFjR/Xr108jRoxQxYoVHWPLlSunGTNmaO7cuapTp44ee+wxSdLgwYPVuHFjtW7dWjVr1tS3336rihUrau3atTpz5ozuv/9+9e7dWw899JBmzpx5y/b10Ucf1fDhwxUXF6fQ0FClpKRozJgxv3u9NptNa9asUadOnRQbG6u7775bf/rTn3T06NFbFrSAO4XN+u3JYwAAgFuIIyMAAMAowggAYzZu3CgfH59iHwDuDJymAWDMxYsXdfz48WKXN2zY8BZWA8AUwggAADCK0zQAAMAowggAADCKMAIAAIwijAAAAKMIIwAAwCjCCAAAMIowAgAAjCKMAAAAo/4fMwnTn6/Wvl8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for section, section_df in df.groupby(\"section_id\").groups.items():\n",
    "    counts = df.loc[section_df].value_counts([\"button_name\"])\n",
    "    counts.plot(kind=\"bar\", title=section)\n",
    "    plt.xticks(range(4), [\"Happy\", \"Meh\", \"Sad\", None])\n",
    "    plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "scripting",
   "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": "3.9.7"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}