visualizacion y reportes.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 5,
  "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": "3.8.5"
    },
    "colab": {
      "name": "visualizacion y reportes.ipynb",
      "provenance": []
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "beautiful-reaction"
      },
      "source": [
        ""
      ],
      "id": "beautiful-reaction",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "popular-texture"
      },
      "source": [
        "import numpy as np\n",
        "\n",
        "import pandas as pd\n",
        "\n",
        "import matplotlib.pyplot as plt"
      ],
      "id": "popular-texture",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "living-frontier"
      },
      "source": [
        "df = pd.read_csv('netflix_titles.csv') # dataset: https://www.kaggle.com/shivamb/netflix-shows"
      ],
      "id": "living-frontier",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "spoken-grill"
      },
      "source": [
        "# Histograma"
      ],
      "id": "spoken-grill"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "exposed-nitrogen"
      },
      "source": [
        "data = df['release_year']"
      ],
      "id": "exposed-nitrogen",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "important-ladder",
        "outputId": "5122c10e-b1de-4fb1-92b2-ba2e91277131"
      },
      "source": [
        "plt.hist(data)\n",
        "plt.show()"
      ],
      "id": "important-ladder",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "alpine-heritage"
      },
      "source": [
        "## Cambiar el tamaño del contenedor de histograma en Matplotlib"
      ],
      "id": "alpine-heritage"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "accessible-private"
      },
      "source": [
        "Digamos, visualicemos un diagrama de histograma (distribución) en lotes de 1 año, ya que este es un marco de tiempo mucho más realista para los lanzamientos de películas y programas."
      ],
      "id": "accessible-private"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "premium-synthetic",
        "outputId": "efc5d6ec-197e-42b0-da9f-94244d55051d"
      },
      "source": [
        "plt.hist(data, bins = np.arange(min(data), max(data) + 1, 1))\n",
        "plt.show()"
      ],
      "id": "premium-synthetic",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "african-producer"
      },
      "source": [
        "Si queremos tener 20 contenedores, usaríamos:"
      ],
      "id": "african-producer"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pharmaceutical-invite",
        "outputId": "70eee3a3-580e-4761-f886-03d5851e3b98"
      },
      "source": [
        "plt.hist(data, bins = 20)\n",
        "plt.show()"
      ],
      "id": "pharmaceutical-invite",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "closed-tradition"
      },
      "source": [
        "Esto da como resultado 20 contenedores iguales, con datos dentro de esos contenedores agrupados y visualizados en sus respectivas barras:"
      ],
      "id": "closed-tradition"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "contrary-practice"
      },
      "source": [
        "## Trazar histograma con densidad"
      ],
      "id": "contrary-practice"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "heavy-tuesday",
        "outputId": "f2855b14-0b93-4d85-e615-7923274ca2cc"
      },
      "source": [
        "bins = np.arange(min(data), max(data) + 1, 1)\n",
        "\n",
        "plt.hist(data, bins = bins, density = True)\n",
        "plt.ylabel('Density')\n",
        "plt.xlabel('Year')\n",
        "\n",
        "plt.show()"
      ],
      "id": "heavy-tuesday",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ancient-closure"
      },
      "source": [
        "## Personalización de gráficos de histograma en Matplotlib"
      ],
      "id": "ancient-closure"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "caroline-listing",
        "outputId": "86696c19-08f8-43e6-e827-aca97335ebf5"
      },
      "source": [
        "bins = np.arange(min(data), max(data) + 1, 1)\n",
        "\n",
        "plt.hist(data, bins=bins, density=True, histtype='step', alpha=0.5, align='right', orientation='horizontal', log=True)\n",
        "\n",
        "plt.show()"
      ],
      "id": "caroline-listing",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAD8CAYAAACb4nSYAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAS4klEQVR4nO3de6ykdX3H8fcH2CqK6w0kFHazNGWbEi+xHsFEWmmtBKopplXqJV4KuvXWVKvW1UK1t0hMKsVKpVtYLtaCBFHXCiVbE7ulVcMu8baiZgNSliDrhbgSIUD99o95Vs4ez2XOnJkzz8zzfiUbzvk9zzzzG345n/nNd37P86SqkCR1wyHj7oAkafUY+pLUIYa+JHWIoS9JHWLoS1KHGPqS1CGHjbsDSznyyCNrw4YN4+6GJE2MXbt2fb+qjppvW+tDf8OGDezcuXPc3ZCkiZHkjoW2Wd6RpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqkCXX6SdZB1wJHA0UsKWqLkzyJODjwAbgO8BZVXVvklcC7wIC/Bh4Y1V9pTnW6cCFwKHAJVV1/lLPf8/+B7hg+7cHeGmS1E5rD1/DOaccP5bn7ufkrIeBt1fVLUkeB+xKsh14LfC5qjo/yWZgM72wvx14XvMGcAawBTg5yaHARcALgL3AzUm2VdU3Fnvyo9c+mre9YOOgr0+SWmecE9klyztVdXdV3dL8/GPgVuBY4Ezgima3K4AXN/v8T1Xd27R/ETiu+fkkYE9V3VZVDwJXN8eQJK2SZV2GIckG4JnAl4Cjq+ruZtN36ZV/5joHuKH5+Vjgzlnb9gInL+f5JWkarD18zUGz/dUs9/Qd+kmOAD4BvLWq9if52baqqiQ1Z//fpBf6pyy3U0k2AZsA1q9fv9yHS1KrzQ341Sz39BX6SdbQC/yPVdV1TfM9SY6pqruTHAPsm7X/04FLgDOq6gdN813AulmHPa5p+zlVtYXedwHMzMx453ZJU23uzP9A2yhm//2s3glwKXBrVX1w1qZtwGuA85v/frrZfz1wHfCqqpr9Km4GTkhyPL2wfxnwimG8CEmaZPOF+6hm//3M9J8LvAr4WpIvN23voRf21yQ5B7gDOKvZ9hfAk4F/bEpAD1fVTFU9nOQtwI30lmxurardQ3slkjTBLr3pdvbf/9DPfl97+JqRPM+SoV9VN9Fbcz+f58+z/+uA1y1wrOuB65fTQUnqgv33P7Qqy9NbfxMVSZomc2f0B4xqZj+XoS9Jq2i1ZvQLMfQlaQELzcpXYrVm9Asx9CVpAeOelY+CoS9pKkzjrHwUDH1JU2EaZ+WjYOhLarV+Z/DTOCsfBUNfUqs5gx8uQ1/S2PQzi3cGP1yGvqSxcRa/+gx9SUOz3BU0zuJXn6EvaWicubffkrdLlKR+Hbgu/KU33T7urmgBzvQlDc2B68KP88bfWpyhL6lvrpmffIa+pL5Zs598hr6kBa3W3Zy0egx9SQtyZj99DH1pSg3jqpPO7KePoS9NKWfpmo/r9CWpQwx9SeoQyzvShFuodm89XvMx9KUJZ+1ey2HoSy3m9eY1bIa+1GLO4jVshr40Js7iNQ6GvjQmzuI1Di7ZlKQOcaYvraLZJR1LNxoHQ19aRZZ0NG6GvjQE3lxEk2LJ0E+yDrgSOBooYEtVXZjkScDHgQ3Ad4CzqureJAEuBH4H+Anw2qq6pTnWa4Bzm0P/TVVdMdyXI42HM3hNin5m+g8Db6+qW5I8DtiVZDvwWuBzVXV+ks3AZuBdwBnACc2/k4GPACc3bxLvBWbovXnsSrKtqu4d9ouSVsuBGb4zeE2KJUO/qu4G7m5+/nGSW4FjgTOBU5vdrgA+Ty/0zwSurKoCvpjkCUmOafbdXlU/BGjeOE4Hrhri65FWlTN8TZpl1fSTbACeCXwJOLp5QwD4Lr3yD/TeEO6c9bC9TdtC7dLEcYavSdV36Cc5AvgE8Naq2t8r3fdUVSWpYXUqySZgE8D69euHdVhpaJzha1L1FfpJ1tAL/I9V1XVN8z1Jjqmqu5vyzb6m/S5g3ayHH9e03cUj5aAD7Z+f7/mqaguwBWBmZmZobybSSjnD16Rb8ozcZjXOpcCtVfXBWZu2Aa9pfn4N8OlZ7a9Oz3OAHzVloBuB05I8MckTgdOaNmliHJjhn3PK8ePuijSQfmb6zwVeBXwtyZebtvcA5wPXJDkHuAM4q9l2Pb3lmnvoLdn8Q4Cq+mGSvwZubvb7qwNf6kpt5wxf06Kf1Ts3AVlg8/Pn2b+ANy9wrK3A1uV0UGoDa/iaFp6Rq6nU7xmy/XKGr2lh6GsqOTOX5uellSWpQwx9SeoQyzuaWIvV7a3BS/Mz9DWxrNtLy2foa2KtPXwNF2z/9kCP8+QqdZWhr4k1aHAP8kYhTQtDX1Oln/X51vvVZYa+pop1fmlxhr6mgtfGkfpj6GsqOMOX+mPoayostpLH1TrSIwx9TYXFQt3VOtIjDH210jCvkmmdX3qEoa9WskYvjYahr1bq52xba/XS8hn6aqV+wtxavbR8hr76Nuy7Ua2UtXpp+Qx99c06uzT5DH31bdCrWs5+vDV4abwMffVtpYFtDV4aP2+XKEkd4kxfIzHfl75+8SqNn6GvkfBLX6mdLO9IUocY+pLUIYa+JHWIoS9JHeIXuRqJlZ7ItdhxPcFLGpyhr5EYVTB7gpe0Moa+RmJUF2dzrb+0Moa+RsJ1+lI7LflFbpKtSfYl+fqstmck+UKSryX5TJK1TfuaJFc07bcmefesx5ye5FtJ9iTZPJqXI0laTD+rdy4HTp/TdgmwuaqeBnwSeGfT/lLgUU37s4A/SrIhyaHARcAZwInAy5OcOIT+S5KWYcnyTlXtSLJhTvNGYEfz83bgRuA8oIDHJjkMOBx4ENgPnATsqarbAJJcDZwJfGMIr0Et5O0OpXYatKa/m15of4re7H5d035t03438BjgbVX1wyTHAnfOevxe4OSFDp5kE7AJYP369QN2UePk7Q6ldho09M8GPpTkPGAbvRk99Gb0/wf8IvBE4L+S/MdyD15VW4AtADMzMzVgHzWA1bwloitxpNU3UOhX1TeB0wCSbARe2Gx6BfDvVfUQsC/JfwMz9Gb562Yd4jjgrkE7rdFx1Y003QYK/SRPqap9SQ4BzgUubjb9L/BbwEeTPBZ4DvD39Gr3JyQ5nl7Yv4zeG4RaZrFavDV4afItGfpJrgJOBY5Mshd4L3BEkjc3u1wHXNb8fBFwWZLdQIDLquqrzXHeQu8L30OBrVW1e5gvRMOxWKhbg5cmX6raXTKfmZmpnTt3jrsbYnn1fj8VSOOTZFdVzcy3zTNy1bflhLifCqR2MvR1kGGt3nFljtROhr4O4uodaboZ+jqIq3ek6Wbo6yCu3pGmm6Gvvq30blh+UpDGz9BX31Ya2H5SkMbP0J8iq3ndnEG4okcaP0N/irjyRtJSDP0p0m/N3dq61F2G/hTpN8itrUvdZeiPgLV1SW1l6I+AtXVJbdXPjdElSVPC0JekDjH0JalDrOmPwEovVzBqLtmUusvQH4G2B2qb35AkjZblHUnqEENfkjpkqss7bT9Jalw8OUvqrqkOfU+SkqSDTXXoj2sVjatjJLXVVIf+uILX1TGS2mqqQ39cNX1r5pLaaqpD35q+JB1sqkPfmr4kHWyqQ9+aviQdbKpDf1yG8QnDTwuSRsHQH4FhhLWfFiSNQutD/579D3QyAF0BJGkUWh/6R699tCtwJGlIlgz9JFuBFwH7quqpTdszgIuBI4DvAK+sqv3NtqcD/wSsBX4KPLuqHkjyLOBy4HDgeuBPqqqWev6uzvQH4fcAkpbSz0z/cuDDwJWz2i4B3lFV/5nkbOCdwHlJDgP+BXhVVX0lyZOBA2dHfQR4PfAleqF/OnDDUk/uTL9/vjlKWsqSoV9VO5JsmNO8EdjR/LwduBE4DzgN+GpVfaV57A8AkhwDrK2qLza/Xwm8mD5CfyW6dpVNvweQtJRBa/q7gTOBTwEvBdY17RuBSnIjcBRwdVV9ADgW2Dvr8Xubtnkl2QRsAli/fv2AXfSMXEmaa9DQPxv4UJLzgG3Ag7OOdwrwbOAnwOeS7AJ+tJyDV9UWYAvAzMzMknX/hbT9XrWLsT4vaRQGCv2q+ia9Ug5JNgIvbDbtBXZU1febbdcDv0avzn/crEMcB9w1YJ/7NsmhOalvVpLabaDQT/KUqtqX5BDgXHoreaBX2/+zJI+hN/t/HnBBVd2dZH+S59D7IvfVwD/081xdXb1jfV7SKPSzZPMq4FTgyCR7gfcCRyR5c7PLdcBlAFV1b5IPAjcDBVxfVZ9t9nsTjyzZvIE+v8R19Y4kDU/6WCo/Vus2PrX+9KLrxt2NZbEeL2mckuyqqpn5tnlG7gh0sRwlaTK0PvQnkVfZlNRWhv4IeJVNSW1l6I/AMM4EdvWOpFEw9EfAM4EltVXrQ38S1+k7S5fUVq0P/UlcvSNJbXXIuDsgSVo9hr4kdYihL0kdYuhLUocY+pLUIYa+JHWIoS9JHWLoS1KHGPqS1CGGviR1iKEvSR3S+mvvrOSCa96IRJIO1vrQX8kF1ybt6pySNGqtD/2VGMZtCwd9Xj9hSGqjqQ79cQWvnzAktdVUh/64eGN0SW1l6I+AN0aX1FYu2ZSkDjH0JalDDH1J6hBDX5I6xC9yR+DSm25n//0PregYaw9fM6TeSNIjDP0R2H//QwOfRSxJo9T60F/JtXfGxVm6pLZqfeiv5No7kqSDLflFbpKtSfYl+fqstmck+UKSryX5TJK1cx6zPsl9Sd4xq+30JN9KsifJ5uG+DElSP/pZvXM5cPqctkuAzVX1NOCTwDvnbP8gcMOBX5IcClwEnAGcCLw8yYkD9lmSNKAlQ7+qdgA/nNO8EdjR/Lwd+P0DG5K8GLgd2D1r/5OAPVV1W1U9CFwNnDl4tyVJgxh0nf5uHgntlwLrAJIcAbwL+Ms5+x8L3Dnr971N27ySbEqyM8nO733vewN2UZI016ChfzbwpiS7gMcBDzbt7wMuqKr7VtKpqtpSVTNVNXPUUUet5FCSpFkGWr1TVd8ETgNIshF4YbPpZOAlST4APAH4aZIHgF00nwYaxwF3DdhnSdKABgr9JE+pqn1JDgHOBS4GqKpfn7XP+4D7qurDSQ4DTkhyPL2wfxnwipV2XpK0PEuGfpKrgFOBI5PsBd4LHJHkzc0u1wGXLXaMqno4yVuAG4FDga1VtXuxx0iShi9VNe4+LGpmZqZ27tw57m5I0sRIsquqZubb5lU2JalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqEENfkjrE0JekDjH0JalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqkMPG3YGl3LP/AS7Y/u2BHrv28DWcc8rxQ+6RJE2u1of+0WsfzdtesHGgxw76ZiFJ06r1ob/Smb4k6RGtD/2VzPQlSQfzi1xJ6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUNSVePuw6KSfA+4Y1bTkcD3x9CVxwM/GsNx+t1/qf0W2r6c9vnaJnk8BjnGMMZjkG2Ox+CPGfRvY7Ft/YzHOMfiCVV11Lxbq2qi/gE7x/S8W8ZxnH73X2q/hbYvp32Btokdj0GOMYzxGGSb4zH4Ywb921jpeLR1LCzv9O8zYzpOv/svtd9C25fTPqz/B8MwjL4McoxhjMcg2xyPwR8z6N/GYtvaPB6L9qP15Z25kuysqplx90M9jke7OB7t0daxmMSZ/pZxd0AHcTzaxfFoj1aOxcTN9CVJg5vEmb4kaUCGviR1iKEvSR0ydaGf5LFJdiZ50bj70mVJfjXJxUmuTfLGcfen65K8OMk/J/l4ktPG3Z+uS/JLSS5Ncu1qP3drQj/J1iT7knx9TvvpSb6VZE+SzX0c6l3ANaPpZTcMYyyq6taqegNwFvDcUfZ32g1pPD5VVa8H3gD8wSj7O+2GNB63VdU5o+3p/FqzeifJbwD3AVdW1VObtkOBbwMvAPYCNwMvBw4F3j/nEGcDzwCeDDwa+H5V/dvq9H66DGMsqmpfkt8F3gh8tKr+dbX6P22GNR7N4/4O+FhV3bJK3Z86Qx6Pa6vqJavVd2jRjdGrakeSDXOaTwL2VNVtAEmuBs6sqvcDP1e+SXIq8FjgROD+JNdX1U9H2e9pNIyxaI6zDdiW5LOAoT+gIf1tBDgfuMHAX5lh/X2MS2tCfwHHAnfO+n0vcPJCO1fVnwMkeS29mb6BPzzLGovmDfj3gEcB14+yYx21rPEA/hj4beDxSX65qi4eZec6aLl/H08G/hZ4ZpJ3N28Oq6LtoT+Qqrp83H3ouqr6PPD5MXdDjar6EPChcfdDPVX1A3rfr6y61nyRu4C7gHWzfj+uadPqcyzaxfFol4kZj7aH/s3ACUmOT/ILwMuAbWPuU1c5Fu3ieLTLxIxHa0I/yVXAF4BfSbI3yTlV9TDwFuBG4FbgmqraPc5+doFj0S6OR7tM+ni0ZsmmJGn0WjPTlySNnqEvSR1i6EtShxj6ktQhhr4kdYihL0kdYuhLUocY+pLUIYa+JHXI/wPfpZPF2JZfiAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cosmetic-treasury"
      },
      "source": [
        "bins - Número de contenedores en la parcela\n",
        "\n",
        "density - Si PyPlot usa recuento o densidad para poblar la trama\n",
        "\n",
        "histtype- El tipo de gráfico de histograma (el valor predeterminado es bar, aunque otros valores como stepo stepfilledestán disponibles)\n",
        "\n",
        "alpha - El alfa / transparencia de las líneas\n",
        "\n",
        "align - A qué lado de los contenedores están alineadas las barras, el valor predeterminado es mid\n",
        "\n",
        "orientation - Orientación horizontal / vertical, el valor predeterminado es vertical\n",
        "\n",
        "log - Si el gráfico debe colocarse en una escala logarítmica o no"
      ],
      "id": "cosmetic-treasury"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jewish-earthquake"
      },
      "source": [
        "# Aumentemos la dificultad usando otras librerias"
      ],
      "id": "jewish-earthquake"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fourth-library"
      },
      "source": [
        "https://relopezbriega.github.io/blog/2016/09/18/visualizaciones-de-datos-con-python/"
      ],
      "id": "fourth-library"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "above-departure",
        "outputId": "c9fa88ba-b4f8-49f6-efec-8407d1849f0b"
      },
      "source": [
        "# importando modulos necesarios\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from pydataset import data\n",
        "import re\n",
        "\n",
        "# librerías de visualizaciones\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt \n",
        "from bokeh.io import output_notebook, show\n",
        "import folium\n",
        "\n",
        "# graficos incrustados\n",
        "%matplotlib inline\n",
        "output_notebook()"
      ],
      "id": "above-departure",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "    <div class=\"bk-root\">\n",
              "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
              "        <span id=\"1001\">Loading BokehJS ...</span>\n",
              "    </div>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
              "   */\n",
              "  function handleClearOutput(event, handle) {\n",
              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when a new output is added\n",
              "   */\n",
              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
              "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
              "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(\"1001\");\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\": \"T2yuo9Oe71Cz/I4X9Ac5+gpEa5a8PpJCDlqKYO0CfAuEszu1JrXLl8YugMqYe3sM\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\": \"98GDGJ0kOMCUMUePhksaQ/GYgB3+NH9h996V88sh3aOiUNX3N+fLXAtry6xctSZ6\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\": \"89bArO+nlbP3sgakeHjCo1JYxYR5wufVgA3IbUvDY+K7w4zyxJqssu7wVnfeKCq8\"};\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      if (url in hashes) {\n",
              "        element.crossOrigin = \"anonymous\";\n",
              "        element.integrity = \"sha384-\" + hashes[url];\n",
              "      }\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    if (force === true) {\n",
              "        display_loaded();\n",
              "      }} else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"1001\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\": \"T2yuo9Oe71Cz/I4X9Ac5+gpEa5a8PpJCDlqKYO0CfAuEszu1JrXLl8YugMqYe3sM\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\": \"98GDGJ0kOMCUMUePhksaQ/GYgB3+NH9h996V88sh3aOiUNX3N+fLXAtry6xctSZ6\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\": \"89bArO+nlbP3sgakeHjCo1JYxYR5wufVgA3IbUvDY+K7w4zyxJqssu7wVnfeKCq8\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "finished-mother"
      },
      "source": [
        "# Cargamos algunos datasets de ejemplo\n",
        "iris = data('iris')\n",
        "tips = data('tips')"
      ],
      "id": "finished-mother",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "peaceful-earth",
        "outputId": "9ec3dffc-3e60-4603-aa33-64adad55ce4c"
      },
      "source": [
        "# Ejemplo matplotlib\n",
        "# graficanco funciones seno y coseno\n",
        "X = np.linspace(-np.pi, np.pi, 256, endpoint=True)\n",
        "C, S = np.cos(X), np.sin(X)\n",
        "\n",
        "# configurando el tamaño de la figura\n",
        "plt.figure(figsize=(8, 6))\n",
        "# dibujando las curvas\n",
        "plt.plot(X, C, color=\"blue\", linewidth=2.5, linestyle=\"-\", label=\"coseno\")\n",
        "plt.plot(X, S, color=\"red\",  linewidth=2.5, linestyle=\"-\", label=\"seno\")\n",
        "# personalizando los valores de los ejes\n",
        "plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi],\n",
        "          [r'$-\\pi$', r'$-\\pi/2$', r'$0$', r'$+\\pi/2$', r'$+\\pi$'])\n",
        "\n",
        "plt.yticks([-1, 0, +1],\n",
        "          [r'$-1$', r'$0$', r'$+1$'])\n",
        "# agregando la leyenda\n",
        "plt.legend(loc='upper left')\n",
        "# moviendo los ejes de coordenadas\n",
        "ax = plt.gca()  # get current axis\n",
        "ax.spines['right'].set_color('none')\n",
        "ax.spines['top'].set_color('none')\n",
        "ax.xaxis.set_ticks_position('bottom')\n",
        "ax.spines['bottom'].set_position(('data',0))\n",
        "ax.yaxis.set_ticks_position('left')\n",
        "ax.spines['left'].set_position(('data',0))\n",
        "# mostrando el resultado\n",
        "plt.show()"
      ],
      "id": "peaceful-earth",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "amazing-rotation"
      },
      "source": [
        "En este primer ejemplo vemos como podemos acceder a la API de Matplotlib desde el objeto pyplot e ir dando forma al gráfico. "
      ],
      "id": "amazing-rotation"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "twelve-while",
        "outputId": "492f018e-ccf9-4954-e031-50f18913fdcf"
      },
      "source": [
        "# Ejemplo con iris\n",
        "# histograma de Petal.Length\n",
        "iris.head()"
      ],
      "id": "twelve-while",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Sepal.Length</th>\n",
              "      <th>Sepal.Width</th>\n",
              "      <th>Petal.Length</th>\n",
              "      <th>Petal.Width</th>\n",
              "      <th>Species</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.7</td>\n",
              "      <td>3.2</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species\n",
              "1           5.1          3.5           1.4          0.2  setosa\n",
              "2           4.9          3.0           1.4          0.2  setosa\n",
              "3           4.7          3.2           1.3          0.2  setosa\n",
              "4           4.6          3.1           1.5          0.2  setosa\n",
              "5           5.0          3.6           1.4          0.2  setosa"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "acute-integration"
      },
      "source": [
        "# separo en especies\n",
        "setosa = iris[iris.Species == 'setosa']\n",
        "versicolor = iris[iris.Species == 'versicolor']\n",
        "virginica = iris[iris.Species == 'virginica']"
      ],
      "id": "acute-integration",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "provincial-potter",
        "outputId": "48179927-946e-41da-e358-3d52a3f62e90"
      },
      "source": [
        "\n",
        "# crear histograma\n",
        "plt.figure(figsize=(10, 8))\n",
        "n, bins, patches = plt.hist(setosa['Petal.Length'], 12, \n",
        "                            facecolor='red', label='setosa')\n",
        "n, bins, patches = plt.hist(versicolor['Petal.Length'], 12, \n",
        "                            facecolor='green', label='versicolor')\n",
        "n, bins, patches = plt.hist(virginica['Petal.Length'], 12, \n",
        "                            facecolor='blue', label='virginica')\n",
        "#plt.legend(loc='top_right')\n",
        "plt.title('Histograma largo del pétalo')\n",
        "plt.xlabel('largo del pétalo')\n",
        "plt.ylabel('cuenta largo del pétalo')\n",
        "plt.show()"
      ],
      "id": "provincial-potter",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ef7ZP2eFT0/ZZB9r+wv5kp6cau/vz3f3u7r53ks8luV53vyfJpzK7n9ceqaojkzwqya2SHJXkRlX1+G3aPr27t3T3ls2bN+9pUwAA+4wdBq+qOmbu/b9KcnaS35lmHZPkf+1Fuw9KclF3X9Hd30ryxiQ/sBfbAwDY5+2sx+uHquqXp/dPSXKfJFclSXd/JslN96Ldv0lyr6q6YVVVkgdm1osGALC2dhi8uvusJNdMk9d193Vbl1XVpiR7PBCguz+YWQ/aeUk+PtVx+p5uDwBgf7DTwfXdfcb09t1V9dzMrkJ8cJInJ3nL3jTc3ackOWVvtgEAsD9Z9D5ez05yRWa9U09K8sdJnresogAA1tFCz2rs7r+vqjOTfDCzU4wXdLdrjgEAdsNCwauqHpbkZUn+OklldkPVJ3X325ZZHADAOlkoeGV289T7d/dnk6Sqbp3kfycRvAAAFrToGK+rt4auyYWZ3b0eAIAFLdrjdU5V/XGS12U2xusnk3y4qn4sSbr7jUuqDwBgbSwavG6Q5LIkPzxNX5HZI4MekVkQE7wAAHZh0asaT1p2IQAA627RMV4AAOwlwQsAYBDBCwBgkJ2O8aqqZ+xseXeftrHlAACsr10Nrj9sSBUAAAeAnQav7j51VCEAAOtuoTFeVXW7qnpXVX1imr5TVT1vuaUBAKyXRQfX/26S5yT5VpJ098eSPGZZRQEArKNFg9cNu/tD28z79kYXAwCwzhYNXl+uqltn9nigVNVPJPni0qoCAFhDiz6r8SlJTk/yfVX1hSQXJXn80qoCAFhDiz6r8cIkD6qqGyU5qLuvXm5ZAADrZ49uoFpVSdxAFQBgdyx6A9Xjk9w9yZun6Uck2XawPQAAO7HQDVSr6r1J7rr1FGNVvTDJ/156dQAAa2TRqxpvluS6uenrpnkAACxo0asaX53kQ1X1pmn60UletYyCAADW1aJXNb6oqt6W5IemWSd190eWVxYAwPpZtMcr3X1ekvOWWMuBY7oqdGVtdC+/fVgTdeqe/33tU/xdY89txD8Vft3vexYd4wUAwF4SvAAABln4VGNV3Syze3klyYe6+/LllAQAsJ4W6vGqqp/K7IapP5nkp5J8cHpQNgAAC1q0x+vXktx9ay9XVW1O8s4kZy+rMACAdbPoGK+Dtjm1+Le78VkAALJ4j9efVNWfJjlrmv7pJH+8nJIAANbTojdQ/bdV9eNJ7jPNOr2737SzzwAA8I/tzg1U35DkDUusBQBgrS0UvKrq6iTb3v/2q0nOSfKr3X3hRhcGALBuFu3xekmSS5L8fpJK8pgkt87sEUJnJLnfEmoDAFgri16Z+Mju/p3uvrq7r+ru05M8pLv/MMmRS6wPAGBtLBq8vlZVP1VVB02vn0ryjWmZR3ACACxg0eD1uCRPSHJ5ksum94+vqkOS/NKSagMAWCu7HONVVQcneXJ3P2IHq7xvY0sCAFhPu+zx6u7vJPnBAbUAAKy1Ra9q/EhVvTnJ65Ncu3Vmd79xKVUBAKyhRYPXDTJ7PuMD5uZ1EsELAGBBiz4y6KRlFwIAsO4WvXP9DZL8fJI7ZNb7lSTp7p9bUl0AAGtn0dtJ/F6S70nykCTvSXJMkquXVRQAwDpaNHjdprufn+Ta7j4zycOS3HN5ZQEArJ9Fg9e3pp9XVtUdkxye5KbLKQkAYD0telXj6VV1ZJLnJ3lzkkOTvGBpVQEArKFFr2p8+fT2PUm+d3nlAACsr50Gr6p6xs6Wd/dpG1sOAMD62lWP12FDqgAAOADsNHh196mjCgEAWHeLXtW44arqiKo6u6o+XVWfqqp7r6oWAIARFr2qcRl+I8mfdPdPVNX1k9xwhbUAACzdSoJXVR2e5L5JTkyS7r4uyXWrqAUAYJSFg1dVPSz/9FmN/24P271VkiuSvLKq/kWSc5M8rbuvnWvv5CQnJ8mxxx67h80AsGxVq65g3+OYsCMLjfGqqpcl+ekkT01SSX4yyS33ot1NSe6a5Le7+y5Jrk3y7PkVuvv07t7S3Vs2b968F00BAOwbFh1c/wPd/bNJvjJd6XjvJLfbi3YvSXJJd39wmj47syAGALC2Fg1eX59+fq2qjsrs2Y0339NGu/tLSS6uquOnWQ9Mcv6ebg8AYH+w6Bivt1bVEUn+W5LzknSSl+/0E7v21CSvna5ovDDJSXu5PQCAfdqiweu/dvc3k7yhqt6a2QD7b+xNw9390SRb9mYbAAD7k0VPNb5/65vu/mZ3f3V+HgAAu7arh2R/T5KjkxxSVXfJ7IrGJLlx3PAUAGC37OpU40Myu8npMUlOm5t/dZLnLqkmAIC1tKuHZJ+Z5Myq+vHufsOgmgAA1tLuXNX4M0mOm//MXty5HgDggLNo8PqjJF/N7NE+31xeOQAA62vR4HVMd5+w1EoAANbcoreT+Muq+udLrQQAYM0t2uP1g0lOrKqLMjvVWEm6u++0tMoAANbMosHroUutAgDgALDQqcbu/nySWyR5wPT+a4t+FgCAmYXCU1WdkuRZSZ4zzbpektcsqygAgHW0aK/VjyZ5ZJJrk6S7L01y2LKKAgBYR4sGr+u6u5N0klTVjZZXEgDAelo0eL2uqn4nyRFV9a+SvDPJ7y6vLACA9bPQVY3d/etV9eAkVyU5PskLuvsdS60MAGDNLHo7iUxBS9gCANhDCwWvqro60/iuJNfP7KrGa7v7xssqDABg3Sx6qvH/X8FYVZXkUUnutayiAADW0W7fBLVn/leSh2x8OQAA62vRU40/Njd5UJItSb6xlIoAANbUooPrHzH3/ttJPpfZ6UYAABa06Bivk5ZdCADAulv0WY1nVtURc9NHVtUZS6sKAGANLTq4/k7dfeXWie7+SpK7LKUiAIA1tWjwOqiqjtw6UVXfnd24+SoAAIuHpxcneX9VvX6a/skkL1pOSQAA62nRwfWvrqpzkjxgmvVj3X3+8soCAFg/u/OsxvOTCFsAAHtot+9cDwDAnhG8AAAGEbwAAAYRvAAABhG8AAAGEbwAAAYRvAAABhG8AAAGEbwAAAYRvAAABhG8AAAGEbwAAAYRvAAABhG8AAAGEbwAAAYRvAAABhG8AAAGEbwAAAYRvAAABhG8AAAGEbwAAAYRvAAABhG8AAAGEbwAAAYRvAAABhG8AAAGWWnwqqqDq+ojVfXWVdYBADDCqnu8npbkUyuuAQBgiJUFr6o6JsnDkrx8VTUAAIy0aYVtvyTJM5Mctr2FVXVykpOT5Nhjjx1X1YGgavvzu8fWAexz6tQd/H7YqX3nd8eOfr3BvmIlPV5V9fAkl3f3uTtap7tP7+4t3b1l8+bNA6sDAFiOVZ1qvE+SR1bV55L8QZIHVNVrVlQLAMAQKwle3f2c7j6mu49L8pgk/6e7H7+KWgAARln1VY0AAAeMVQ6uT5J097uTvHvFZQAALJ0eLwCAQQQvAIBBBC8AgEEELwCAQQQvAIBBBC8AgEEELwCAQQQvAIBBBC8AgEEELwCAQQQvAIBBBC8AgEEELwCAQQQvAIBBBC8AgEEELwCAQQQvAIBBBC8AgEEELwCAQQQvAIBBBC8AgEEELwCAQQQvAIBBBC8AgEEELwCAQQQvAIBBNq26AABg/VXt/Ta6934bq6bHCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYJCVBK+qukVV/VlVnV9Vn6yqp62iDgCAkTatqN1vJ/nV7j6vqg5Lcm5VvaO7z19RPQAAS7eSHq/u/mJ3nze9vzrJp5IcvYpaAABGWfkYr6o6LsldknxwxaUAACzVqk41Jkmq6tAkb0jy9O6+aptlJyc5OUmOPfbYFVS3oKrtz+8eW8eyHSj7eYCoU3fwfS5Zn7Lnf15WVfPe2C9qfqG/wzDSynq8qup6mYWu13b3G7dd3t2nd/eW7t6yefPm8QUCAGywVV3VWElekeRT3X3aKmoAABhtVT1e90nyhCQPqKqPTq9/uaJaAACGWMkYr+5+X5L9YPADAMDGWflVjQAABwrBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgEMELAGAQwQsAYBDBCwBgkE2rLmCfUrXqCmBhder+9+d1f6x5n/bCXnUF7OPW7Z+1jdifXvFfGz1eAACDCF4AAIMIXgAAgwheAACDCF4AAIMIXgAAgwheAACDCF4AAIMIXgAAgwheAACDCF4AAIMIXgAAgwheAACDCF4AAIMIXgAAgwheAACDCF4AAIMIXgAAgwheAACDCF4AAIMIXgAAgwheAACDCF4AAIMIXgAAgwheAACDCF4AAIMIXgAAgwheAACDrCx4VdUJVXVBVX22qp69qjoAAEZZSfCqqoOT/GaShya5fZLHVtXtV1ELAMAoq+rxukeSz3b3hd19XZI/SPKoFdUCADDEphW1e3SSi+emL0lyz/kVqurkJCdPk9dU1QUD6rpJki9vyJaqNmQzQ9vZk20t9pmNO67Mc1yXYz86roN+z2yM/ei47lcc19204D91e3tcb7mjBasKXrvU3acnOX1km1V1TndvGdnmgcBxXQ7HdTkc1+VwXJfDcV2OZR7XVZ1q/EKSW8xNHzPNAwBYW6sKXh9OctuqulVVXT/JY5K8eUW1AAAMsZJTjd397ar6pSR/muTgJGd09ydXUcs2hp7aPIA4rsvhuC6H47ocjutyOK7LsbTjWt29rG0DADDHnesBAAYRvAAABhG8klTVGVV1eVV9YtW1rIuqukVV/VlVnV9Vn6yqp626pnVQVTeoqg9V1f+djuupq65pnVTVwVX1kap666prWRdV9bmq+nhVfbSqzll1Peuiqo6oqrOr6tNV9amquveqa9rfVdXx05/Tra+rqurpG96OMV5JVd03yTVJXt3dd1x1Peugqm6e5ObdfV5VHZbk3CSP7u7zV1zafq2qKsmNuvuaqrpekvcleVp3f2DFpa2FqnpGki1JbtzdD191Peugqj6XZEt3u8nnBqqqM5P8eXe/fLo7wA27+8oVl7U2pkcbfiHJPbv78xu5bT1eSbr7vUn+btV1rJPu/mJ3nze9vzrJpzJ7YgF7oWeumSavN73872kDVNUxSR6W5OWrrgV2pqoOT3LfJK9Iku6+TujacA9M8tcbHboSwYsBquq4JHdJ8sEVl7IWptNhH01yeZJ3dLfjujFekuSZSf5+xXWsm07y9qo6d3oUHHvvVkmuSPLK6dT4y6vqRqsuas08JslZy9iw4MVSVdWhSd6Q5OndfdWq61kH3f2d7r5zZk98uEdVOT2+l6rq4Uku7+5zV13LGvrB7r5rkocmeco0tIO9synJXZP8dnffJcm1SZ692pLWx3Tq9pFJXr+M7QteLM00BukNSV7b3W9cdT3rZjq18GdJTlhxKevgPkkeOY1H+oMkD6iq16y2pPXQ3V+Yfl6e5E1J7rHaitbCJUkumevtPjuzIMbGeGiS87r7smVsXPBiKaZB4K9I8qnuPm3V9ayLqtpcVUdM7w9J8uAkn15pUWugu5/T3cd093GZnWL4P939+BWXtd+rqhtNF9dkOhX2I0lcPb6XuvtLSS6uquOnWQ9M4sKljfPYLOk0Y7KiRwbta6rqrCT3S3KTqrokySnd/YrVVrXfu0+SJyT5+DQeKUme291/vLqS1sLNk5w5XXFzUJLXdbdbH7CvulmSN83+H5ZNSX6/u/9ktSWtjacmee10WuzCJCetuJ61MP0H4cFJnrS0NtxOAgBgDKcaAQAGEbwAAAYRvAAABhG8AAAGEbwAAAYRvAD2QlUdVVVPWHUdwP5B8AKWrqqu2fVaq21/T2qcbmZ7WpJ3zc07saqOWuCzr6qqn9jdNoH9m+AF7FNqZr/43dTdV3b3Y7r70rnZJybZZfACDkz7xS83YD1U1aFV9a6qOq+qPl5Vj5rmH1dVF1TVqzN7pMwtqur507z3VdVZVfVvpnXvXFUfqKqPVdWbqurI7bRzq6p6/9TGf9hm2b+tqg9Pnz91F/UeV1WfrqrXVtWnqursqrrhtOxuVfWeqjq3qv60qm4+9WBtyeyO4h+tqkOq6gVTe5+oqtOnx2lt284Dq+ojU71nVNV37ekxBvZtghcw0jeS/Gh33zXJ/ZO8eC6I3DbJb3X3HZLcNMmPJ/kXmT2wdsvcNl6d5FndfackH09yynba+Y0kv93d/zzJF7fOrKofmdq5R5I7J7lbVd13FzUfP9X1/UmuSvLk6QHw/zPJT3T33ZKckeRF3X12knOSPK6779zdX0/y0u6+e3ffMckhSR4+v/GqukGSVyX56aneTUl+cRc1AfspwQsYqZL8x6r6WJJ3Jjk6s+f5Jcnnu/sD0/v7JPmj7v5Gd1+d5C1JUlWHJzmiu98zrXdmku0Fp/vkHx5y+3tz839ken0kyXlJvi+zILYzF3f3X0zvX5PkBzMLY3dM8o7pWaTPS3LMDj5//6r6YFV9PMkDktxhm+XHJ7mou/9qF/sErAEPyQZGelySzUnu1t3fqqrPJbnBtOzaDW5rew+irST/qbt/Zy+209N2Ptnd997ZB6ferN9KsqW7L66qF+Yf9hc4AOnxAkY6PMnlU+i6f5Jb7mC9v0jyiKq6QVUdmun0XHd/NclXquqHpvWekOQ9O/j8Y6b3j5ub/6dJfm7aZqrq6Kq66S5qPraqtgasn0nyviQXJNm8dX5VXa+qtvZkXZ3ksOn91pD15anN7V3FeEGS46rqNrvYJ2AN6PECRnptkrdMp93OSfLp7a3U3R+uqjcn+ViSyzIby/XVafETk7xsGuR+YZKTtrOJpyX5/ap6VpI/mtvu26vq+5O8fxpadk2Sxye5fCc1X5DkKVV1RpLzMxs7dt00kP5/TKc/NyV5SZJPZjZe62VV9fUk907yu5ldMPClJB/ezr5+o6pOSvL6qto0rfOyndQD7Meqe3u98QCrVVWHdvc1U8B6b5KTu/u8wTUcl+St08B4gL2mxwvYV51eVbfP7HTdmaNDF8Ay6PECABjE4HoAgEEELwCAQQQvAIBBBC8AgEEELwCAQf4fRckE3CHraHMAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "suburban-regard",
        "outputId": "db6b1ee9-b518-4772-9804-d90515b21e81"
      },
      "source": [
        "# Ejemplo diagrama de dispersion entre Petal.Length y Petal.Width\n",
        "plt.figure(figsize=(10, 8))\n",
        "plt.scatter(setosa['Petal.Length'], setosa['Petal.Width'], \n",
        "            c='red', label='setosa')\n",
        "plt.scatter(versicolor['Petal.Length'], versicolor['Petal.Width'], \n",
        "            c='green', label='versicolor')\n",
        "plt.scatter(virginica['Petal.Length'], virginica['Petal.Width'], \n",
        "            c='blue', label='virginica')\n",
        "plt.title('Tamaño del pétalo')\n",
        "plt.xlabel('Largo del pétalo (cm)')\n",
        "plt.ylabel('Ancho del pétalo (cm)')\n",
        "#plt.legend(loc='top_left')\n",
        "plt.show()"
      ],
      "id": "suburban-regard",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "reverse-pointer"
      },
      "source": [
        "Bokeh"
      ],
      "id": "reverse-pointer"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "female-niagara",
        "outputId": "4415dee5-676e-4f08-ea04-af26d26945b2"
      },
      "source": [
        "# Ejemplo de histograma de Petal.Length\n",
        "# solo 2 lineas de código\n",
        "hist = Histogram(iris, values=\"Petal.Length\", color=\"Species\",\n",
        "                 legend=\"top_right\", bins=12)\n",
        "show(hist)"
      ],
      "id": "female-niagara",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "name 'Histogram' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-17-127a1325f2df>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Ejemplo de histograma de Petal.Length\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;31m# solo 2 lineas de código\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m hist = Histogram(iris, values=\"Petal.Length\", color=\"Species\",\n\u001b[0m\u001b[1;32m      4\u001b[0m                  legend=\"top_right\", bins=12)\n\u001b[1;32m      5\u001b[0m \u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNameError\u001b[0m: name 'Histogram' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "stuck-connectivity"
      },
      "source": [
        "Seaborn"
      ],
      "id": "stuck-connectivity"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "objective-field",
        "outputId": "5b479376-eddd-4398-9de2-81eee80afc32"
      },
      "source": [
        "# Ejemplo gráfico de distribuciones\n",
        "x = np.random.normal(size=100)\n",
        "dist= sns.distplot(x)"
      ],
      "id": "objective-field",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/home/wisrovi/.local/lib/python3.8/site-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "significant-feedback",
        "outputId": "d4fff8a4-55fd-412e-def0-91fa8489267d"
      },
      "source": [
        "\n",
        "# Ejemplo gráfico regresión con tips dataset\n",
        "tips.head()"
      ],
      "id": "significant-feedback",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>total_bill</th>\n",
              "      <th>tip</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoker</th>\n",
              "      <th>day</th>\n",
              "      <th>time</th>\n",
              "      <th>size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>16.99</td>\n",
              "      <td>1.01</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>10.34</td>\n",
              "      <td>1.66</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>21.01</td>\n",
              "      <td>3.50</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>23.68</td>\n",
              "      <td>3.31</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>24.59</td>\n",
              "      <td>3.61</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>Sun</td>\n",
              "      <td>Dinner</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   total_bill   tip     sex smoker  day    time  size\n",
              "1       16.99  1.01  Female     No  Sun  Dinner     2\n",
              "2       10.34  1.66    Male     No  Sun  Dinner     3\n",
              "3       21.01  3.50    Male     No  Sun  Dinner     3\n",
              "4       23.68  3.31    Male     No  Sun  Dinner     2\n",
              "5       24.59  3.61  Female     No  Sun  Dinner     4"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "annoying-carnival",
        "outputId": "798463ef-583b-489a-e8e7-e1f96c7de572"
      },
      "source": [
        "reg = sns.regplot(x=\"total_bill\", y=\"tip\", data=tips)\n"
      ],
      "id": "annoying-carnival",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "under-kuwait",
        "outputId": "8cc6e635-9fdf-49b6-bc15-9efd55805254"
      },
      "source": [
        "# Ejemplo pairplot con datase iris\n",
        "g = sns.pairplot(iris, hue=\"Species\", diag_kind=\"hist\")  "
      ],
      "id": "under-kuwait",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 804.75x720 with 20 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "authorized-authorization",
        "outputId": "56452671-b660-498f-bd90-8afc69a24e3b"
      },
      "source": [
        "# Ejemplo FacetGrid con iris\n",
        "g = sns.FacetGrid(iris, col=\"Species\")\n",
        "g = g.map(plt.scatter, \"Petal.Length\", \"Petal.Width\")"
      ],
      "id": "authorized-authorization",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 648x216 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "executed-spray"
      },
      "source": [
        "# Countplot de Seaborn"
      ],
      "id": "executed-spray"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "every-comparative"
      },
      "source": [
        "La biblioteca Seaborn tiene una función countpot () para crear couplot, echemos un vistazo a su sintaxis y parámetros."
      ],
      "id": "every-comparative"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "conceptual-ghost"
      },
      "source": [
        "seaborn.countplot(*, x=None, y=None, hue=None, data=None, order=None, hue_order=None, orient=None, color=None, palette=None, saturation=0.75, dodge=True, ax=None, kwargs)**"
      ],
      "id": "conceptual-ghost"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "public-accommodation"
      },
      "source": [
        "x, y, hue : names of variables in data or vector data, optional\n",
        "  This is the input provided for building the plot.\n",
        "  \n",
        "data : DataFrame, array, or list of arrays, optional\n",
        "  Here we pass the data for the purpose of plotting the graph.\n",
        "  \n",
        "order, hue_order : lists of strings, optional\n",
        "  This is the order used for plotting categorical levels.\n",
        "  \n",
        "orient : “v” | “h”, optional\n",
        "  Through this parameter, we can set the orientation of plot as horizontal or vertical.\n",
        "  \n",
        "color : matplotlib color, optional\n",
        "  In this parameter, we are setting the color of the plot.\n",
        "  \n",
        "palette : palette name, list, or dict\n",
        "  The palette will be deciding the colors for the graph.\n",
        "  \n",
        "ax : matplotlib Axes, optional\n",
        "  These are the axes over which the plot is built."
      ],
      "id": "public-accommodation"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "expensive-hawaii"
      },
      "source": [
        ""
      ],
      "id": "expensive-hawaii"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "frank-reason",
        "outputId": "0677bde6-8fc7-41a5-d81e-213ed8425bfe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        }
      },
      "source": [
        "import seaborn as sns\n",
        "\n",
        "sns.set_theme(style=\"darkgrid\")\n",
        "\n",
        "titanic = sns.load_dataset(\"titanic\")\n",
        "\n",
        "ax = sns.countplot(x=\"class\", data=titanic)"
      ],
      "id": "frank-reason",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "infinite-messenger"
      },
      "source": [
        "Seaborn Countplot with Two Variables using Hue"
      ],
      "id": "infinite-messenger"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "charged-houston",
        "outputId": "6589c4f0-5848-4fca-cfc4-8b3b03cf6ade"
      },
      "source": [
        "ax = sns.countplot(x=\"class\", hue=\"who\", data=titanic, palette=\"spring\")\n"
      ],
      "id": "charged-houston",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "greek-cleveland"
      },
      "source": [
        "Horizontal Countplot in Seaborn"
      ],
      "id": "greek-cleveland"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "small-trustee",
        "outputId": "894a277b-6fe4-4a48-a3b8-d948e12aef93"
      },
      "source": [
        "ax = sns.countplot(y=\"class\", hue=\"who\", data=titanic, palette=\"rainbow\")\n"
      ],
      "id": "small-trustee",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "legislative-communication"
      },
      "source": [
        "Applying styling to the Countplot bar"
      ],
      "id": "legislative-communication"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "competent-cathedral",
        "outputId": "b19ca0dc-309b-48b6-881b-6516b9e6d063"
      },
      "source": [
        "ax = sns.countplot(x=\"who\", data=titanic,\n",
        "\n",
        "                   facecolor=(0, 0, 0, 0),\n",
        "\n",
        "                   linewidth=5,\n",
        "\n",
        "                   edgecolor=sns.color_palette(\"dark\", 3))"
      ],
      "id": "competent-cathedral",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "expected-worth"
      },
      "source": [
        "Distplot con KDE e histograma"
      ],
      "id": "expected-worth"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sorted-resistance",
        "outputId": "991b6d53-1fe2-4b0f-a2c0-4d6ff6239c1a"
      },
      "source": [
        "import seaborn as sns, numpy as np\n",
        "\n",
        "sns.set_theme(); \n",
        "\n",
        "np.random.seed(0)\n",
        "\n",
        "x = np.random.randn(125)\n",
        "\n",
        "ax = sns.distplot(x, color=\"r\")"
      ],
      "id": "sorted-resistance",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/home/wisrovi/.local/lib/python3.8/site-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "institutional-blend"
      },
      "source": [
        "Distplot with Rug Plot Parameter"
      ],
      "id": "institutional-blend"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "corrected-performer",
        "outputId": "0b8087d7-11bd-4340-df3e-83b1e5f6e54c"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns, numpy as np\n",
        "\n",
        "ax = sns.distplot(x, rug=True, hist=False)"
      ],
      "id": "corrected-performer",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/home/wisrovi/.local/lib/python3.8/site-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `kdeplot` (an axes-level function for kernel density plots).\n",
            "  warnings.warn(msg, FutureWarning)\n",
            "/home/wisrovi/.local/lib/python3.8/site-packages/seaborn/distributions.py:2056: FutureWarning: The `axis` variable is no longer used and will be removed. Instead, assign variables directly to `x` or `y`.\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "virgin-brook"
      },
      "source": [
        "Horizontal Distplot in Seaborn"
      ],
      "id": "virgin-brook"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "clean-brother",
        "outputId": "98935d02-66b2-4c79-8d4c-6ce4d1286682"
      },
      "source": [
        "ax = sns.distplot(x, vertical=True)\n"
      ],
      "id": "clean-brother",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/home/wisrovi/.local/lib/python3.8/site-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n",
            "/home/wisrovi/.local/lib/python3.8/site-packages/seaborn/distributions.py:1647: FutureWarning: The `vertical` parameter is deprecated and will be removed in a future version. Assign the data to the `y` variable instead.\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "deluxe-glance"
      },
      "source": [
        "Distplot with Rug, KDE and Histogram plot"
      ],
      "id": "deluxe-glance"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "literary-lobby",
        "outputId": "73c6747a-0f6f-4dfe-bdb3-2e3081e67ddb"
      },
      "source": [
        "ax = sns.distplot(x, rug=True, rug_kws={\"color\": \"g\"},\n",
        "\n",
        "                  kde_kws={\"color\": \"k\", \"lw\": 3, \"label\": \"KDE\"},\n",
        "\n",
        "                  hist_kws={\"histtype\": \"step\", \"linewidth\": 3,\n",
        "\n",
        "                            \"alpha\": 1, \"color\": \"y\"})"
      ],
      "id": "literary-lobby",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/home/wisrovi/.local/lib/python3.8/site-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n",
            "/home/wisrovi/.local/lib/python3.8/site-packages/seaborn/distributions.py:2056: FutureWarning: The `axis` variable is no longer used and will be removed. Instead, assign variables directly to `x` or `y`.\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "productive-design"
      },
      "source": [
        "categorización en capas de contenedores de histograma usando Hue en Seaborn"
      ],
      "id": "productive-design"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "irish-appraisal",
        "outputId": "a92f53e4-d261-4b86-cf49-6eb257e5b5a1"
      },
      "source": [
        "mpg = sns.load_dataset(\"mpg\")\n",
        "mpg.head()"
      ],
      "id": "irish-appraisal",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>mpg</th>\n",
              "      <th>cylinders</th>\n",
              "      <th>displacement</th>\n",
              "      <th>horsepower</th>\n",
              "      <th>weight</th>\n",
              "      <th>acceleration</th>\n",
              "      <th>model_year</th>\n",
              "      <th>origin</th>\n",
              "      <th>name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>18.0</td>\n",
              "      <td>8</td>\n",
              "      <td>307.0</td>\n",
              "      <td>130.0</td>\n",
              "      <td>3504</td>\n",
              "      <td>12.0</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>chevrolet chevelle malibu</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>15.0</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>165.0</td>\n",
              "      <td>3693</td>\n",
              "      <td>11.5</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>buick skylark 320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>18.0</td>\n",
              "      <td>8</td>\n",
              "      <td>318.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>3436</td>\n",
              "      <td>11.0</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>plymouth satellite</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>16.0</td>\n",
              "      <td>8</td>\n",
              "      <td>304.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>3433</td>\n",
              "      <td>12.0</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>amc rebel sst</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>17.0</td>\n",
              "      <td>8</td>\n",
              "      <td>302.0</td>\n",
              "      <td>140.0</td>\n",
              "      <td>3449</td>\n",
              "      <td>10.5</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>ford torino</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    mpg  cylinders  displacement  horsepower  weight  acceleration  \\\n",
              "0  18.0          8         307.0       130.0    3504          12.0   \n",
              "1  15.0          8         350.0       165.0    3693          11.5   \n",
              "2  18.0          8         318.0       150.0    3436          11.0   \n",
              "3  16.0          8         304.0       150.0    3433          12.0   \n",
              "4  17.0          8         302.0       140.0    3449          10.5   \n",
              "\n",
              "   model_year origin                       name  \n",
              "0          70    usa  chevrolet chevelle malibu  \n",
              "1          70    usa          buick skylark 320  \n",
              "2          70    usa         plymouth satellite  \n",
              "3          70    usa              amc rebel sst  \n",
              "4          70    usa                ford torino  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "allied-supply",
        "outputId": "ceda51cd-89cb-47d7-a759-fb8139156d3c"
      },
      "source": [
        "sns.histplot(data=mpg, x=\"mpg\", hue=\"cylinders\")\n"
      ],
      "id": "allied-supply",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='mpg', ylabel='Count'>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "surrounded-belarus"
      },
      "source": [
        "Categorización de contenedores de histograma usando Hue y Stack"
      ],
      "id": "surrounded-belarus"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pressing-payday",
        "outputId": "62a42fe2-c84f-48a3-f9cd-dea3a59cb24a"
      },
      "source": [
        "sns.histplot(data=mpg, x=\"mpg\", hue=\"cylinders\", multiple=\"stack\")\n"
      ],
      "id": "pressing-payday",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='mpg', ylabel='Count'>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "incorrect-bookmark"
      },
      "source": [
        "Categorización de contenedores de histograma usando Hue y Step"
      ],
      "id": "incorrect-bookmark"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "enclosed-duration",
        "outputId": "edd4f91e-12b8-47ae-9ab5-e7017faabd0e"
      },
      "source": [
        "sns.histplot(mpg, x=\"mpg\", hue=\"cylinders\", element=\"step\")\n"
      ],
      "id": "enclosed-duration",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='mpg', ylabel='Count'>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "structured-paintball"
      },
      "source": [
        "Histograma con forma de polígono en Seaborn"
      ],
      "id": "structured-paintball"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "divided-conversation",
        "outputId": "35771afc-be1e-4fbc-96ec-f1e517137d04"
      },
      "source": [
        "sns.histplot(mpg, x=\"mpg\", hue=\"cylinders\", element=\"poly\")\n"
      ],
      "id": "divided-conversation",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='mpg', ylabel='Count'>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vital-discipline"
      },
      "source": [
        "Histograma de Seaborn para comparación"
      ],
      "id": "vital-discipline"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "overall-saturn",
        "outputId": "9375c5dc-f2cf-4b29-e938-b99604e6abe3"
      },
      "source": [
        "sns.histplot(data=tips, x=\"day\", hue=\"sex\", multiple=\"dodge\", shrink=.9)\n"
      ],
      "id": "overall-saturn",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='day', ylabel='Count'>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lucky-council"
      },
      "source": [
        "Bivariate Histogram\n"
      ],
      "id": "lucky-council"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wooden-chaos",
        "outputId": "8b3ddb88-512e-4dd2-8065-b914dc5a63a1"
      },
      "source": [
        "sns.histplot(tips, x=\"total_bill\", y=\"tip\", color = \"yellow\")\n"
      ],
      "id": "wooden-chaos",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='total_bill', ylabel='tip'>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "outer-carrier"
      },
      "source": [
        "Bivariate Histogram with Colorbar"
      ],
      "id": "outer-carrier"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "young-functionality"
      },
      "source": [
        "planets = sns.load_dataset(\"planets\")\n"
      ],
      "id": "young-functionality",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "assigned-posting",
        "outputId": "3f54c867-eeb8-42ed-cbe1-04836bd2f74e"
      },
      "source": [
        "sns.histplot(\n",
        "    planets, x=\"year\", y=\"distance\",\n",
        "    bins=30, discrete=(True, False), log_scale=(False, True),\n",
        "    cbar=True, cbar_kws=dict(shrink=.75),color=\"pink\"\n",
        ")"
      ],
      "id": "assigned-posting",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='year', ylabel='distance'>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "unlike-theology"
      },
      "source": [
        ""
      ],
      "id": "unlike-theology",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fantastic-rapid"
      },
      "source": [
        ""
      ],
      "id": "fantastic-rapid",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "affiliated-employment"
      },
      "source": [
        ""
      ],
      "id": "affiliated-employment",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "internal-going"
      },
      "source": [
        ""
      ],
      "id": "internal-going",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "legal-graph"
      },
      "source": [
        ""
      ],
      "id": "legal-graph",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "forty-marketplace"
      },
      "source": [
        ""
      ],
      "id": "forty-marketplace",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tender-family"
      },
      "source": [
        "Folium"
      ],
      "id": "tender-family"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "prompt-enemy",
        "outputId": "c7048bd4-ea7a-40c6-8cbc-60f9bb0b3f66"
      },
      "source": [
        "# dataset de bicicleterías de Ciudad de Buenos Aires (Buscado en: https://data.buenosaires.gob.ar/)\n",
        "# descargado desde https://data.buenosaires.gob.ar/dataset/bicicleterias\n",
        "bici = pd.read_csv('data/bicicleterias.csv', sep=',')\n",
        "bici.head()"
      ],
      "id": "prompt-enemy",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>WKT</th>\n",
              "      <th>id</th>\n",
              "      <th>nombre</th>\n",
              "      <th>direccion</th>\n",
              "      <th>telefono</th>\n",
              "      <th>email</th>\n",
              "      <th>web</th>\n",
              "      <th>mecanica_s</th>\n",
              "      <th>horario_de</th>\n",
              "      <th>calle</th>\n",
              "      <th>altura</th>\n",
              "      <th>calle2</th>\n",
              "      <th>direccion_</th>\n",
              "      <th>barrio</th>\n",
              "      <th>comuna</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>POINT (-58.4256879365174 -34.5923050897605)</td>\n",
              "      <td>1</td>\n",
              "      <td>Bicicletas Araoz</td>\n",
              "      <td>Araoz 1458</td>\n",
              "      <td>011-4833-7887 / 011-4832-7704</td>\n",
              "      <td>info@biciccletasaraoz.com.ar</td>\n",
              "      <td>http://www.bicicletasaraoz.com.ar/</td>\n",
              "      <td>True</td>\n",
              "      <td>Lun a Vier de 9.30 a 19</td>\n",
              "      <td>ARAOZ</td>\n",
              "      <td>1458</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ARAOZ 1458</td>\n",
              "      <td>Palermo</td>\n",
              "      <td>Comuna 14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>POINT (-58.4259820523858 -34.5813777353459)</td>\n",
              "      <td>2</td>\n",
              "      <td>Roda2oro</td>\n",
              "      <td>Oro 2305</td>\n",
              "      <td>4774-0403</td>\n",
              "      <td>Roda2oro@gmail.com</td>\n",
              "      <td>http://www.roda2oro.com/</td>\n",
              "      <td>False</td>\n",
              "      <td>Lun a vier de 10 a 13 y de 14.30 a 19 / S</td>\n",
              "      <td>FRAY JUSTO SANTAMARIA DE ORO</td>\n",
              "      <td>2305</td>\n",
              "      <td>NaN</td>\n",
              "      <td>FRAY JUSTO SANTAMARIA DE ORO 2305</td>\n",
              "      <td>Palermo</td>\n",
              "      <td>Comuna 14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>POINT (-58.4153429603451 -34.6533516212895)</td>\n",
              "      <td>3</td>\n",
              "      <td>Walter</td>\n",
              "      <td>Linch 3914</td>\n",
              "      <td>4912-2738</td>\n",
              "      <td>walterbikes-10@hotmail.com</td>\n",
              "      <td>NaN</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>LYNCH</td>\n",
              "      <td>3914</td>\n",
              "      <td>NaN</td>\n",
              "      <td>LYNCH 3914</td>\n",
              "      <td>Nueva Pompeya</td>\n",
              "      <td>Comuna 4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>POINT (-58.4432441275002 -34.5943508729756)</td>\n",
              "      <td>4</td>\n",
              "      <td>Bici Shop</td>\n",
              "      <td>Villaroel 1093</td>\n",
              "      <td>4855-8329</td>\n",
              "      <td>info@tubicicleteria.com</td>\n",
              "      <td>www.tubicicleteria.com</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>VILLARROEL</td>\n",
              "      <td>1093</td>\n",
              "      <td>NaN</td>\n",
              "      <td>VILLARROEL 1093</td>\n",
              "      <td>Villa Crespo</td>\n",
              "      <td>Comuna 15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>POINT (-58.3773343753292 -34.6083635891506)</td>\n",
              "      <td>5</td>\n",
              "      <td>Bicicleterias El colo</td>\n",
              "      <td>Rivadavia 770</td>\n",
              "      <td>4342--3887</td>\n",
              "      <td>info@bicicleteriaelcolo.com.ar</td>\n",
              "      <td>http://www.bicicleteriaelcolo.com.ar/</td>\n",
              "      <td>True</td>\n",
              "      <td>Lun a vier de 9 a 19/Sab de 9 a 13</td>\n",
              "      <td>RIVADAVIA AV.</td>\n",
              "      <td>770</td>\n",
              "      <td>NaN</td>\n",
              "      <td>RIVADAVIA AV. 770</td>\n",
              "      <td>Monserrat</td>\n",
              "      <td>Comuna 1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                           WKT  id                 nombre  \\\n",
              "0  POINT (-58.4256879365174 -34.5923050897605)   1       Bicicletas Araoz   \n",
              "1  POINT (-58.4259820523858 -34.5813777353459)   2               Roda2oro   \n",
              "2  POINT (-58.4153429603451 -34.6533516212895)   3                 Walter   \n",
              "3  POINT (-58.4432441275002 -34.5943508729756)   4              Bici Shop   \n",
              "4  POINT (-58.3773343753292 -34.6083635891506)   5  Bicicleterias El colo   \n",
              "\n",
              "        direccion                       telefono  \\\n",
              "0      Araoz 1458  011-4833-7887 / 011-4832-7704   \n",
              "1        Oro 2305                      4774-0403   \n",
              "2      Linch 3914                      4912-2738   \n",
              "3  Villaroel 1093                      4855-8329   \n",
              "4   Rivadavia 770                     4342--3887   \n",
              "\n",
              "                            email                                    web  \\\n",
              "0    info@biciccletasaraoz.com.ar     http://www.bicicletasaraoz.com.ar/   \n",
              "1              Roda2oro@gmail.com               http://www.roda2oro.com/   \n",
              "2      walterbikes-10@hotmail.com                                    NaN   \n",
              "3         info@tubicicleteria.com                 www.tubicicleteria.com   \n",
              "4  info@bicicleteriaelcolo.com.ar  http://www.bicicleteriaelcolo.com.ar/   \n",
              "\n",
              "   mecanica_s                                 horario_de  \\\n",
              "0        True                    Lun a Vier de 9.30 a 19   \n",
              "1       False  Lun a vier de 10 a 13 y de 14.30 a 19 / S   \n",
              "2       False                                        NaN   \n",
              "3       False                                        NaN   \n",
              "4        True         Lun a vier de 9 a 19/Sab de 9 a 13   \n",
              "\n",
              "                          calle  altura  calle2  \\\n",
              "0                         ARAOZ    1458     NaN   \n",
              "1  FRAY JUSTO SANTAMARIA DE ORO    2305     NaN   \n",
              "2                         LYNCH    3914     NaN   \n",
              "3                    VILLARROEL    1093     NaN   \n",
              "4                 RIVADAVIA AV.     770     NaN   \n",
              "\n",
              "                          direccion_         barrio     comuna  \n",
              "0                         ARAOZ 1458        Palermo  Comuna 14  \n",
              "1  FRAY JUSTO SANTAMARIA DE ORO 2305        Palermo  Comuna 14  \n",
              "2                         LYNCH 3914  Nueva Pompeya   Comuna 4  \n",
              "3                    VILLARROEL 1093   Villa Crespo  Comuna 15  \n",
              "4                  RIVADAVIA AV. 770      Monserrat   Comuna 1  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "honest-district"
      },
      "source": [
        "# corregimos el campo de coordenadas del dataset.\n",
        "def coord(c):\n",
        "    coor = re.findall(r'-?\\d+\\.\\d{7}', c)\n",
        "    coords = [float(s) for s in coor]\n",
        "    return coords[::-1]\n",
        "\n",
        "bici['WKT'] = bici['WKT'].apply(coord)\n",
        "\n",
        "# filtramos solo las bicicleterías de palermo\n",
        "bici_palermo = bici[bici.barrio == 'Palermo'][['WKT', 'nombre']]"
      ],
      "id": "honest-district",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "western-perry"
      },
      "source": [
        "# creamos el mapa con folium\n",
        "mapa = folium.Map(location=[-34.588889, -58.430556], zoom_start=13)"
      ],
      "id": "western-perry",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "maritime-premiere"
      },
      "source": [
        "# agregamos los markers con el nombre de cada bicicletería.\n",
        "for index, row in bici_palermo.iterrows():\n",
        "    location = row['WKT']\n",
        "    folium.Marker(location, \n",
        "                  popup=row['nombre'],\n",
        "                  marker_color='red',\n",
        "                  marker_icon='info-sign').add_to(mapa)"
      ],
      "id": "maritime-premiere",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "joint-february",
        "outputId": "46c3899f-0fc7-46f2-9b4a-cc0431fad469"
      },
      "source": [
        "mapa"
      ],
      "id": "joint-february",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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            ],
            "text/plain": [
              "<folium.folium.Map at 0x7f98a9ddea60>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bottom-singing"
      },
      "source": [
        ""
      ],
      "id": "bottom-singing",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "favorite-intersection"
      },
      "source": [
        ""
      ],
      "id": "favorite-intersection",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aging-friendship"
      },
      "source": [
        ""
      ],
      "id": "aging-friendship",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "modified-tourist"
      },
      "source": [
        ""
      ],
      "id": "modified-tourist",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "connected-distributor"
      },
      "source": [
        "## Grafico radar"
      ],
      "id": "connected-distributor"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "focal-motor"
      },
      "source": [
        "## Cómo hacer impresionantes gráficos de radar con Python"
      ],
      "id": "focal-motor"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eastern-supervisor"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.graph_objects as go\n",
        "import plotly.offline as pyo"
      ],
      "id": "eastern-supervisor",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "appointed-relay",
        "outputId": "c22ae825-3b32-4ef9-becf-3ac43b560dfd"
      },
      "source": [
        "categories = ['Food Quality', 'Food Variety', 'Service Quality', 'Ambiance', 'Affordability']\n",
        "\n",
        "restaurant_1 = [4, 4, 5, 4, 3]\n",
        "restaurant_2 = [5, 5, 4, 5, 2]\n",
        "restaurant_3 = [3, 4, 5, 3, 5]\n",
        "\n",
        "label_loc = np.linspace(start=0, stop=2 * np.pi, num=len(restaurant_1))\n",
        "\n",
        "plt.figure(figsize=(8, 8))\n",
        "plt.subplot(polar=True)\n",
        "plt.plot(label_loc, restaurant_1, label='Restaurant 1')\n",
        "plt.plot(label_loc, restaurant_2, label='Restaurant 2')\n",
        "plt.plot(label_loc, restaurant_3, label='Restaurant 3')\n",
        "plt.title('Restaurant comparison', size=20)\n",
        "lines, labels = plt.thetagrids(np.degrees(label_loc), labels=categories)\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "id": "appointed-relay",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "floppy-central",
        "outputId": "3073288f-83d3-4b5c-f7a8-bec4574f9594"
      },
      "source": [
        "categories = ['Food Quality', 'Food Variety', 'Service Quality', 'Ambiance', 'Affordability']\n",
        "categories = [*categories, categories[0]]\n",
        "\n",
        "restaurant_1 = [4, 4, 5, 4, 3]\n",
        "restaurant_2 = [5, 5, 4, 5, 2]\n",
        "restaurant_3 = [3, 4, 5, 3, 5]\n",
        "restaurant_1 = [*restaurant_1, restaurant_1[0]]\n",
        "restaurant_2 = [*restaurant_2, restaurant_2[0]]\n",
        "restaurant_3 = [*restaurant_3, restaurant_3[0]]\n",
        "\n",
        "label_loc = np.linspace(start=0, stop=2 * np.pi, num=len(restaurant_1))\n",
        "\n",
        "plt.figure(figsize=(8, 8))\n",
        "plt.subplot(polar=True)\n",
        "plt.plot(label_loc, restaurant_1, label='Restaurant 1')\n",
        "plt.plot(label_loc, restaurant_2, label='Restaurant 2')\n",
        "plt.plot(label_loc, restaurant_3, label='Restaurant 3')\n",
        "plt.title('Restaurant comparison', size=20, y=1.05)\n",
        "lines, labels = plt.thetagrids(np.degrees(label_loc), labels=categories)\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "id": "floppy-central",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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egDIaH4mtwNNCiFlSysNCCFcgREpZALQD7kCD5ZzbhBBhQDow53iuiYrKZKEKu4rKOCCEcAACgSAg2N7ePsTHx2eWg4NDiBDCS0rpbjKZ3E0mk4tGo7HTaDQarVarjYyM1Li4uEg3Nzfp7OyMRqNBo9EIrVaLRqOEwEgpMZvNmEwmzGazNBqNdHV1ifb2dhEZGYnJZDKZzWaTyWSSQogerVbbodFo2oUQ7Wazuamrq6u4qampEKge8GqUUpon+LJcDTxrSRsrQpmbHm77tcBLQgiJMiIfjjdQhP09y//XATdbXOX5KKI9LFLKeiHENcAbQghHy+b7gQLgeWCdEKLKMs8Oylz7XCll80h9q6hMJWq6m4rKKBBC+ABxQog4nU6X4eDgMMtsNgebTCZfrVbr4OzsrAkKCpIRERHaiIgIp/DwcJfg4GCh0+nw8PDA3d0dNzc33Nzc0Gq1E2ZnT08PHR0dtLe3097eTktLCzU1NVRWVhqKi4u7SktLeysqKmRjY6Po7e01mM1mvZ2dXS1Q3t7evre1tTUPRdgKpZQ9E2boNEQI8QnwmJTym6m2RUVlOFRhV1GxYHHFzgLifHx8Ul1dXdONRmOsRqNx9/f3FykpKdrU1FT3hIQEh7CwMIKCgvDz8+sfWU9Henp6qKmpoaqqipKSEvbu3duZm5vbVVBQQHt7u9HOzq4G2N/Y2Jjd3d29H0X0y0aTCz5TsAT2bQdypZRrptgcFZURUYVd5aTEkjud7unpmeXu7r7SYDDEe3l52ScmJpKamuqWnJzsHBcXx6xZs3B1dZ1qc6cEKSV1dXUUFBSQn58v9+zZ07Znz56eoqIiYTQaWzUaTXZtbe3XRqNxJ7BPSmmYaptVVFRUYVc5CbC40dO9vLwWu7u7rzAYDHF+fn72WVlZdkuWLPHKzMwUcXFxE+oin2l0dHSwe/dutm/f3vvDDz+07tmzB71e32ZnZ5ddV1f3TW9v7w4UsbfJ4D4VlZmMKuwqMw4hRJhWq10RFBR0odFonKfT6eyzsrIclixZ4pmRkSHi4uKmtfvcVuns7OwTe8P69etbd+/eLXt6eppMJtMXdXV1HwNbpJSdU23nZJOdna2zs7P7N5CCWhRsKjEDe41G4w0ZGRl1U23MRKIKu8q0RwgRqtVqV1qEfH5ERIT9Oeec437aaac5paenY2c3+ckfBoOBnp4e9Ho9BoMBo9GI0WjEZDL1//vYl9lsRkrJcN9JIQRCCOzs7NBqtdjZ2Q37cnBwwMnJCUdHxyl5mGlqamLDhg189tlnLd9++62hq6uryWg0rqurq/sE2Cyl7Jp0oyaZ3NzcjwIDAxP9/f3bNBqN+oM7RZjNZlFfX+9ZU1OzPzU19dyptmciUYVdZdohhPDXarWrgoKCLjIYDPMjIyPtzznnHLdTTz3VOT09HXt7+5E7OU6klHR3d9PZ2Yler0ev1/cLuF6vx2g0AmBnZ9cvqPb29kMK70Bx1mq1WCqg9f899txAf+rbUA8IA/f19PT029d3vKOjY79tTk5OODk54ezsjJub24ReOxgs9J2dnY2WEf1HwIaZOE+fm5tbNHv27GZV1Kces9ks8vLyvFNTU6On2paJRBV2FZvHUsQlwdvb+xInJ6fLfHx8fNesWeO2atUq54yMjHEXIyklvb29dHZ20tHR0f/q6lIGl87Ozri6uvaL4kCRnGhhPFGklEeJfd+ru7ubjo4OjEYjWq0WNzc3XF1d+1P0XF1dJyQGoampifXr1/PBBx80f/XVV0aNRpNbXV291mQyfTZT8sVzc3NLUlNT1VXibITc3Fy/1NTUyKm2YyJRhV3FJrEsuLEkMDDwJ1LK1cnJyfY/+clPfM466yytTqcbt/OYTCba2tpobW2lpaWFtrY2zGYzDg4ORwmbm5sbfQVkZjoGg4HOzs6jHmw6OzsxmUw4OTnh6emJl5cXnp6euLi4WPUuHA9SSvbs2cO7777b9fbbb3e2tbXVdnZ2vt7W1vaulPLwuJxkClCF3bZQhV1FZRIRQrhrtdqzg4KCrjGbzWmnnnqq3WWXXea9cuVKnJycRu5gBPpEvKWlpV/EATw8PPrFysPDY0rm5KcDfaP9lpaW/gehrq4uHB0d+6+fl5fXuIl9VVUVH330kfE///lP8+HDh/VarXZdZWXlWmDrJFTNGzdsQdi1Wm1GbGxst8lkEmFhYT1vv/12sZ+f35hqEWzevNm5vLzc4dJLL22dKDtPxIaamhrteeedF5OXl+d68cUXN7766qtl1vpQhV1FZYKxjMxXhYSE/MLe3j718ssvd1mzZo3r3LlzT1gc9Ho9jY2NNDQ00NLSAigi3idAHh4eaorbOKDX6/uFvk/sHRwc8PPzw9fXF29v7xO+zvX19bz00kts3769cdOmTb1ms/l/9fX1z0kp94/T25gwbEHYXVxc0rq6unYBXHjhhZGxsbH6v/71rzVj6ePJJ5/03blzp+tQgjlWjEbjmB+ih7Ohra1Ns2XLFpfc3FznvXv3Op/Mwq4OTVQmHcuc+cKgoKDbgoKCTj3vvPMcb7jhBs/09PQTEvOenh4aGhpoaGigubkZe3t7/Pz8CA0NJSUlRRXxCaIvziAgIKB/W99DVWVlJXv37u3/LPz8/PDy8hrzZ9HW1sYll1zC3Xff7dvd3c3HH3982zPPPPPjoKCgNr1e/++WlpZXpJRV4/3eZiILFy7s3LNnjzPAvn37HG+++ebwpqYmOycnJ/O///3v0rS0NP1LL73k/dBDDwVrNBrp7u5u2rhxY8FDDz0UrNfrNQkJCW6/+tWvqmfNmtXzy1/+Mrynp0fj5ORkXrt2bXFqamrPseK7cuXKWb/61a9qzz777HYXF5e0K664on79+vUeTz75ZNlXX33lvm7dOq+enh5NZmZmx3/+859SjUbD/Pnz4zMyMjo2btzo0d7ern322WdLVqxY0XmsDTfeeGN/HIaHh4d51apVHfn5+Y5DvfeTBVXYVSYNIUS8v7//TwMCAi7LyspyvOWWW3xPOeWU4xbc3t5e6uvrVSG3QZycnAgJCSEkJAQ4IvQVFRXk5eUdJfTe3t4jxi5UV1eTmZkJKMGLl1xyieaSSy7xa2xs9Hv77bcfePbZZ38ZEhJS2dTU9E+9Xv8/KWXbhL/J4+A37+SGFdS0u4xnn3GB7l2PXJxaPpq2RqOR7777zv36669vALjhhhsinn/++dLZs2f3fPvtt6633HJL+NatWwsefvjhoC+//LIgKirK0NDQoHVycpL33ntv1UDBbmpq0uzYseOgvb09H3zwgftdd90V+sUXXxQOd/7u7m7NggULOl944YUKgLlz53Y/+uij1QDnn39+1Jtvvun54x//uNViq8jLyzvw1ltvef7pT38KXr16dcGxNqhYRxV2lQlFCOHh7u5+raur621LlizxvPXWW33PO+88jYvL8f22tbe3U1tbS01NDVJK/P39CQkJUYXcxhlO6Pfs2YOHhweBgYHodLpBmQV6vR4hhNU4C19fX2655Rb7W265xb+kpMT/lVdeeXLt2rUPh4SE7K6qqnoY+G46zcdPFD09PZqEhISk2tpa+5iYGP3555/f1traqtm1a5fbmjVrYvra9fb2CoDMzMyOK664IvKiiy5qvuKKK6xmJzQ1NWkvvfTSqJKSEichhDQYDCO627RaLddcc01/f59//rn7P/7xj0C9Xq9paWmxS0pK6gZaAdasWdMMkJWV1fmb3/zG4QQvwUmFKuwqE4IQIiMoKOjeiIiIZbfccov7dddd5+Tv7z/mfsxmM01NTdTW1lJfX4+zszOBgYFkZmaOS0CdytQwUOillLS2tlJTU0NhYSF2dnYEBAQQGBiIq6sr1dXVBAYGjthnZGQkf/jDH1x+//vfu+Tk5Jz6j3/8I/2bb77p8vb2fq6lpeVZKeWUR6aPdmQ93jg6OpoPHjy4v729XbNixYrYhx9+WHfrrbc2uLu7Gw8ePDgoTuG///1v2bfffuv60UcfeWZkZCRlZ2cPanP33XeHLF++vP2rr74qzM/PdzjllFPiAezs7KTZfORZqqenp98d4+DgYO6bV+/q6hK/+tWvIrZt27Z/1qxZhjvvvDNYr9f3t3VycpKW/jCZTOOTenGSMPNzd1QmDSGEs6ur60+DgoIKVq1ate7111+/qLi42P/uu+8ek6gbjUYqKyvJzs7mhx9+oLKyEl9fX5YuXcqCBQuIiIhQRX0GIYTAy8uLhIQEli1bRlpaGhqNhr25ORT89148378cj87iYSvyHdtfRkYG//nPf3wKCgpC//znP/8uJibmQEhIyOdCiCwxXvl50xB3d3fzk08+WfbMM88EuLu7m0NDQ3tfeuklb1Aeords2dI/937KKad0Pv7441Xe3t7GoqIiBw8PD1NHR0e/ZrS1tWlDQ0N7AZ577jm/vu0xMTG9+/btczGZTBw+fNh+z549VldR6urq0gAEBgYaW1tbNR9//LH3SPYfa4OKddQLpHLCCCEiAwIC/hUcHFx65513/mPXrl2x69at8zvllFNGHQxnNpupra0lOzubjRs30tbWRnR0NCtWrCA1NZXAwEDV1X6S4GyvJarxexZsu4W4gmfwai/A/Yufs/Gbzzlw4ADt7e2j7svDw4PbbrvN4dChQ37/+9//Vp9zzjkfBQYGFri4uNwghHCewLdhsyxevLg7ISGh+/nnn/d54403il5++WW/+Pj4pNjY2OR3333XC+CXv/xlaFxcXFJsbGzyvHnzOhYuXNh9xhlntBcUFDgnJCQkvfDCC9533313zR//+MfQxMTEpL6KiwCnnXZaR1hYWM+sWbOSb7nllvCkpCSrZYP9/PxMV1xxRX1iYmLyypUr41JTU0dcR+BYG47dHxISMvt3v/td2DvvvOMbEBAwJzs7+6QcAajpbirHjRBiaXBw8EN+fn7xv/3tb30uvPBCzVgqr0kpaW5upqKigsbGxv7ANy8vr3EreqIyjTAZYPd/Yf2j0FoGIRnUJl2PQWoJ/eYWzClrqF74B8rLy+nt7e135Y/Ve1NdXc0///nPzrVr13Yajca36+rqHpRSjin1ayzYQrqbyhFOhnQ3VdhVxoQQQmg0mjN1Ot3fMjIyAv/85z/7pKWljamPjo4OKioqqKmpwd3dnbCwMPz8/E6Kqm4qVjAZIPcNWP8ItJRBcDqs/C3MOpUtW7cyZ84cXLc/AT/8FS54HlIvpaenh6qqKiorK9FqtYSGhhIUFDSmvOje3l7eeust0wMPPNDc2dn5VU1Nzf1SyqLxfnuqsNsWqrCrqFgQQtg5Oztf5uHh8afTTjvN+w9/+IPXrFmzRn1837x5WVkZ9vb2hIaGEhgYqFZ5O5kxGSD3TYugl0JwGqy4F2JPByEwGAxs2bKFZcuWgckIa8+C2r1w8wbwObKGR2dnJxUVFVRXV+Pu7k5kZCQ+Pj5jmgb65JNPzPfff39TQ0PDzurq6ruklHnj9TZVYbctVGFXOekRQji5u7vf4OLics+aNWvc7733Xo/g4OBRH9/a2kpJSQlNTU2EhIQQHh6uBr6d7JiMsOctWP83aC6BoLmKoMetggFiXF5eTldXF/Hx8cqGljJ4dgn4xMB1X4Dd0RlQfVM7JSUltLW1ERYWRlhYGA4Oo8uUklKyfv167r333saSkpL86urqX0spt5zo21WF3bZQhV3lpEUI4e7t7X2Ho6Pjz2644Qa3O++809Xbe8SgVUAZAVVVVVFSUoK9vT2RkZHodDp13vxkx2SEvLfhh79BczEEzlFc7nGrjxL0PrZt20ZSUhLu7u5HNu77AP53NSz+BZz2pyFP1dvbS3l5OeXl5Xh6ehIVFYWXl9eoTc3Ozua+++5rys3Nrairq7vLbDZ/KY/zx1IVdtviZBB21Q+qchRCCGcfH5/fBAcH33bnnXd63HzzzY6urlazVQbR3d1NaWkp1dXVBAQEkJGRgbPzSRl4rDIQkxH2vqMIelMhBM6Gy/4L8WdaFXRQVpjr7u4+WtQBks+Homtg0xMQtRxm/cjq8Q4ODsTExBAdHU1DQwMFBQX09vYSGRlJcHDwiPEcGRkZrFu3zic/P9/nD3/4wxvff/99rVar/ZnJZPr2OK6Aisqkoo7YVQBlDt3d3f0GV1fX3//iF7/w+sUvfuE8WlFubW3l0KFDdHd39/9wqqlpKphNkPeO4nJvPAwBs2HFPZBw1pCC3kdlZSXt7e0kJCQM3tnbBc+vgO5muGUzuI2uRkJXVxclJSXU1tYSEhJCVFTUoCp3Q3Ho0CHuuOOOpuzs7MLa2tqbpJS7RnUg6ojd1jgZRuxqGPJJjhBCODs7XxQQEHD4xhtv/NuBAweC7rnnnlGJemNjI1u3buXAgQNERUWxdOlSwsLCVFE/2TGbYM//4OkF8P5PQesIl7wGN62HxLNHFHVQlmwNCgqyvtPBBS5+CfSt8MHNYB5dxVgXFxeSkpJYtmwZ9vb2bNq0if3796PX60c8NjY2lk8//dTn008/nbdw4cKvgoKC1gkhYkY80EbQarUZCQkJSbGxscmnnHLKrIaGhjF/STdv3uz81ltveU6EfeNhw/vvv++RnJycGBcXl5ScnJz40UcfuVtrdzKgCvtJjBBieUBAwP41a9b8OycnJ+Lvf/+7+0jzkFJKamtr2bhxI8XFxSQmJrJw4UJ8fX0nx2gV26VvhP7MQnjvBtDawyWvws0bIelcGGU6o8lkorOzEw8Pj6EbBabAqgfh8New7V9jMlOr1RIVFcWyZctwd3dn27Zt5Obm0tVltY7KUWRkZLBlyxbf119//fSkpKStgYGBrwshRq53O8X0lZQ9dOjQPi8vL+Mjjzwy5vrOO3fudPn000/HTdgHFrUZDxt0Op3h008/PVxQULB/7dq1xTfccEPUCRs5TVGF/SRECDE3KCho2xlnnPHe+vXrE1599VWvkSLdpZRUVFSwfv16qqurmTt3LpmZmXh6TukDvIotYDbD3nfhmUXw7vUgtLBmLdy8CZLOG7Wg91FXV4e/v//IwZbzblDm6b/6A1TtHrPZGo2GsLAwli1bhk6nIzs7m+zsbNraRl4Y7kc/+pHYu3ev31NPPXVZZGRknk6ne0wIMcyTiO2wcOHCzsrKSgdQSscuXbo0Njk5OTEjIyN+165dTgAvvfSSd2xsbHJ8fHxSZmZmvF6vFw899FDwxx9/7N1X9e27775zmTt3bkJiYmJSWlpaQm5uriMoa6ZfddVV4X3nW7ly5axPPvnEHZR14W+88cbQ+Pj4pG+++cbt17/+dVBKSkpibGxs8uWXXx7RV2N+/vz58bfcckvI7NmzEyMjI1PWrVvnZs2Gge9r8eLF3ZGRkQaAjIwMfU9Pj6a7u/ukjNhVg+dOIoQQuoCAgGfnz5+/7Omnn/btWwZzOMxmM2VlZZSUlODn58f8+fPVgDgVBbMZ9n+gFI6pPwj+CXDxy5B0/pjFfCBVVVVER0eP3FAIOO9p+NdieOc6xdXv6Dbm8wkhCAoKIjAwkMbGRvbt24dGoyEuLo7hMkGEEKxZs0Z7wQUX+P373/++9c9//vOPPT09/9TW1vavIVeU++BnYdTtH9dlW9EldXH+0+qyrQN45ZVXvJOTk7ucnZ1PyiAyVdhPAoQQWi8vr1+Ehobe88QTT/hccMEF2pFGQ1JKKisrOXz4MIGBgWRlZY06H1hlhmM2w4EP4fu/Qv0B8IuHi16E5AtAc2LxFSaTiba2ttGnprn4wIXPwyvnwOd3wfnPHPe5hRD9a8S3tLSQn5+PEILExMTB0fkDsLOz4+abb3a44oordPfdd99f3n777duEEFdKKXcetzHjzMm0bOvOnTudfv/734esW7fu0GiPmWmowj7DEUJk6XS6V6666qqABx54wH2kddCllNTX13Pw4EG8vb1ZtGgRjo6Ok2Stik1jNsPBjxVBr9sHfnHjJuh9NDQ0jM4NP5CopbDs10oFu+iVMGfNCdvh5eXFggULaGxsJDc3F1dXVxISEob1Vrm7u/Pkk0963HzzzR5XX331F4GBgV/W1tbetnv37iONRjmyHm9OlmVbCwsL7S+++OJZL774YnFycnLP6K/QzEKdY5+hCCF0gYGB7y9evPjjjRs3znrkkUdGFPXm5ma2bNlCeXk5GRkZzJ49WxV1FYvL/SN4bim8fRWYeuHCf8OtW2H2xeMm6jBCNPxwLL8HQufDJ7+EpuJxs8fX15fFixcTFBTE9u3b2bdvH729vcMek5SUxPbt230ee+yxi0NCQvZ3dXW520pa8UxetrWhoUF75plnxj7wwAMVp59++ogrxc1kVGGfYQgh7Ly9vX8dGhq695lnnjlnw4YNPrGxscMe097ezvbt28nPzyc5OZmMjAxGW5RGZQYjJRz4BJ5bBm9fCYZuZRGWn21TRsXjKOigCEtLSws+Pj5jP1hrBxf9G4RGCeAzGcbNLiEEgYGB/VH0mzZtoqCgYNiobiEEl19+ud2BAwd0UkrvAwcOJLe3t4/v3PpxMlOXbf3b3/6mKysrc3zooYeCExISkhISEpIqKytPSq+0WqBmBiGEWBAQEPD6lVdeGfjAAw+4jTRC1+v1HDx4kI6ODhISEvDz8xu2vcpJgpSQ/xl8/xDU5CkLriy/G1IuVgR0gqirq6O6uprU1NTj72Tf+/C/a2DJL+HUP46XaUdhMpkoKSmhrKyMqKgoIiIihp06OHDgAJGRkZSVlZns7e3bwsPDS+3s7EwTYpzKiJwMBWpOyqeZmYYQwsnf3/8f6enpl77xxhs+cXFxw7Y3m80UFxdTVlZGfHw8qampah13FUXQC9Ypgl6dC95RcP6/YPYlEyrofVRXVzOWBYasknwBFH4LGx9XSs7GrBwX2wai1WqJiYkhPDycgoICNmzYQEpKyrCeBmdnZ+Li4rRNTU1eBw8edAsODi718fFpHXfjVFRQhX3aI4RYoNPp3rz77rsD7rjjDueRamA3NDSwb98+AgICWLZsmVolTsUi6F9YBH03eEfCec/AnEsnRdAVEyRNTU3Mnj37xDtb/TCUbYX3b1JKzrpOjCfK3t6e5ORk2tvbycvLw9nZmaSkpCHjUoQQ+Pr6Cg8PD/vS0tKo5ubm9oiIiBJ19K4y3qiu+GmKZZT+99DQ0Mvefvttn5HWRtfr9ezbtw+DwcDs2bPVOXQVRdAPfaUIelUOeEXAst9A6mVK1bhJpLGxkfLycubOnTs+HdbkwQunQPQK+PHboypjeyJIKamuriY/P5/IyEgiIyP7vWAHDhwgMTFxUPumpiZZXV1tVEfvk4vqilexSYQQ83U63Vt33XVXwC9/+cthR+l9bvfy8nISEhIIDLT56pcqE42USinW7x+CymzwCodzn4LUyydd0Ps47mj4oQicDaf/n5Lbvu1ZWHjL+PVtBSEEwcHB6HS6Ubnnjx29t7S0qHPvKuOGKuzTCCGEo06nezQtLe3yt956y3ekaPeBbvelS5eqbveTHSmh8Bv47iGo3Ame4XDOk4qg201d8SEpJQ0NDSQnJ49vx/N/qsy3f/V7iMiCoBMIyhsldnZ2JCUl0d7ezt69e3Fycho2ZdTe3p6YmJj+ufeQkJASb2/vkWvaqqgMg+qKnyYIIdJ0Ot27v/nNbwLvvPPOYUfpBoOBffv2odfrVbe7ikXQv4XvH4aK7eAZBkt/BXOvmFJB76OpqYni4mIyMjLGv/PORvhXllJq9qc/HFfJ2eOlzz1fW1tLcnIy9vb2wwapGgwGSktLTRqNpi08PLzEzs5udMvWqYyJk8EVr+ax2zhCCOHj4/PrhISErzZs2BD161//elhRr6urY9OmTfj4+LBgwQJV1E9m+gT9pVXw+oXQVgVnPwa350DmtTYh6jBO0fBD4eqrlJxtLIR1d0/MOYagzz3v6OiIwWCgq6sL8zBLzPaN3j08PLzy8/OTOzo6xm1RhpNh2dbvvvvOpS9/PT4+PunVV1/1mmTzbAZV2G0YIYS3Tqf7+sILL/zdrl27fIdLYzMYDOTm5lJUVMSCBQsIDw9XU9hOVqSEou/hpdXw2gXQWgFn/R1+ngOZ19mMoIMyqq2rq0On003cSaKXw9I7YdfryrKyk4wQAldXVxwcHOjo6KC3t5ehPKWWevUiOjraoaysLK6mpkY3Hl7Vk2HZ1szMTH1eXt7+gwcP7v/yyy8P3XHHHREGw/gVKppOqMJuowghFgYGBuY9/fTTy/797397ODk5Ddm2vr6eTZs24e3tzYIFC9TV105WpISiH+DlM+HV86ClDM58FH6+S1ni1M72ygO3tbXh7u4+8fEfK+6F0HlKydnmkok91xDY29vj5uY2qtG7s7MzCQkJdnq9Pvjw4cOxRqNx3C7QTF221d3d3WxvrwR/dnd3i5N5YKMGz9kYQgiNr6/v/bNnz/7FRx995BMZGTlkW6PRyL59++ju7lYF/WSneIMS5V66CdyD4IxHIP0qsB/6gdAWGPdo+KHQ2islZ59dCu/eANd+PiUZAI/sfISDTQeRUmI2m9FoNCN51rQGo8Gjd09vqsZe0y00YtDTwCzvWV1/XvxnddlW4Ntvv3X96U9/GllVVeXw7LPPFvcJ/cmGKuw2hBDCX6fTfXjppZem/P3vf3cf7qZsaGhg7969REVFMWfOHNXtfrJSslEJiivZAG6BsPqvkHGNzQt6H7W1tYyU3TFueEfCOY8ra7d//xD86PeTc14rCCHQarWYTEp223AeC3s7e7QardDr9S5SI3s1dprhV6GxwsmybOspp5zSefjw4X05OTlOV199ddTFF1/c6uLictJFiKvCbiPY2dktCwoKevOFF17QnXXWWUN+y81mM/n5+TQ3N6uj9JOZ0s3w3V8sgh6gVFvLuAbsp8/90NbWhrOzM33LeE4KKRcpAYUb/qGUnI1ePnnnBu6ePziAr7e3F71ej7OzM8M9zJvNZioqKrR6vZ6oqKjD9vb2o855P1mWbe0jPT1d7+rqatq5c6fzsmXLrC5CM5NR59inGCGE8PX1vWv27Nnvb9++PWg4Ue/u7mbLli1oNBoWLVqkivrJSOkWeOVcePkMqM+HVQ/BL3KVAizTSNRhgqPhh+OMv4HvLHjvp0o63BTj4OCAm5sbPT096PX6IQPrNBoN4eHhWp1O51pQUJDU2dk5ZrfMTF629eDBgw59wXIFBQUORUVFTrGxsWP2bswEVGGfQiwFZ95atWrVb7du3eoTGho6ZNva2lq2bt1KfHw88fHxquv9ZKNsmxIQ9/JqqNsPpz+oCPqiW6edoPdRU1MzNZUQHVzh4hehuwk+vFUJOpxiNBoNrq6uSCnp7OwcNrDOy8tLREdHO5SUlMQ3NjZ6jfVcM3XZ1m+++cYtMTExOSEhIen888+P+fvf/14WFBQ09tD7GYBaoGaKEELo/P39v7r33ntj77jjDuehhNpsNnPgwAHa29tJS0sbtoqViu1iMpno6emht7cXo9GIyWTCaDQOepnNZqSU/aM258Y8gg6uxb1uB0ZHL+rjrqA1bg1aJze0Wi12dnaDXg4ODjg6Otr0w19nZyd5eXksXLhw6ozY+i9Yd48ygl9w04Sdxlqt+OEwGAx0d3eP6Jo3Go0UFRWZXFxc6kJCQqps+fO2JU6GAjXqHPsUIISYGxAQ8Olrr70WeNpppw3pNenq6iInJ4eAgAAWLFhg0z/UJzNGo5HOzk46Ozvp7u5Gr9ej1+v7hRyUEZmjoyMODg6DhNje3r5/rlmr1SqBVTW7cNn2OPal6zE7+9C1+B70c67EXuuE94CHgj4RGPhw0NvbS09PD6AEaTk5OfWXNnVycsLFxQVXV1dcXFym7J6atGj44VhwMxR+B1/er5ScDRyHleXGAXt7e7RaLV1dXRiNRpycnKx+TnZ2dsTGxmrLy8t1hYWFrlFRUYVarVatVqeijtgnGw8Pj8t1Ot2Tn3/+ud9w0cBVVVUUFBQwZ86cYdd5Vpkc+lykHR0d/X87OjowGAxotVpcXV1xdXXF2dn5KCF1cHAYm3hWZCsR24e/AhdfyPq5koN+nKVQzWZz/9xt36urq4vOzk66uhQPqbOzM25ubke9JtoztH79ehYuXIiDwxQXy+lsUErOOnnCT79X3PTjzFhH7H1IKenp6cFoNOLi4sJwFScbGhpkXV1dT3R0dIGTk9PJWZVllKgjdpVxQwih8ff3/1t6evp1H374obenp/UCTlLKftd7VlbW1P/wnYRIKeno6KClpYXW1lZaWlowGAy4urri7u6Oq6srYWFhuLm5jd/nU5mtpK0d+hKcfeBHf1AWMTnB2uYajQZnZ+chAy2llHR3d/c/qFRWVtLe3k5vby+urq54enri5eWFl5fXuIl9V1dX/5TBlOPqp5ScffV8xS1/7lMTchop5Zi9I33eFqPRSEdHBy4uLkNmEPj5+QknJyenwsLCxLCwsEIPD48R56tPRsxmswBmvFdDHbFPAkIIV51O99Hll18+7+9//7v7UDmrBoOBnJwcPDw8SEhIUF3vk0RPTw+NjY00NjbS2tqK0WjE1dUVLy+vfmGbMBGqzLEI+hfg7A1Zt1sE3X1izjdK+jwUfQ82LS0t9Pb24uLigre3N76+vnh7ew87ihyKwsJCNBoNUVFRE2D5cfL1H2HjY7BmLSRfMK5dFxcX4+7ujq+v73F/p81mM52dnf3xE0PR29tLYWGh0dfXt1Kn0zUcr80zEbPZLOrr6z1ramr2p6amnjvV9kwkqrBPMEIIX39//x8efvjh2Ouuu25Idejs7GTnzp3MmjWLkJCQyTTxpKNPyBsaGmhqasLe3h5fX198fX3x8vIaNmBp3KjaBd//FQo+BycvyLoN5t8ETh4Tf+7jREpJV1cXzc3NNDY20tzcjIODA76+vvj5+Y1a6Ddu3EhmZibDlUmedEwGZbGchsNwy0ZljfpxwmAwUFFRgV6vP6F+pJT0pXMNt1Kc2WymoaHBbGdn1+7m5tZyQiedWZiBvUaj8YaMjIy6qTZmIlGFfQIRQoTrdLofXn755bAzzzxzyPz0+vp69u7dS1paGl5eXpNo4cmByWSioaGB2tpampub0Wq1+Pn54evri4+Pz+SuU1+dq4zQ8z9T5nUX3a5EZNuwoA9Hd3d3/0NSS0sLDg4O+Pn5ERgYiLu7+yDx0ev17Ny5kyVLlkyRxcPQVKyUnA1Igms+A63tzVRKKTl8+DD19fVkZmYO6UkyGo1cc801rV9++eX79fX110spZ7z7WeUIqrBPEEKIlMDAwC8/+OCDoAULFlhtI6WkpKSEyspK2xvBTHN6enqoqamhtraWzs5O/P39CQgImHwh76N6D/zwVzj4iUXQb7MI+pSugjnudHd3U19fT21tLR0dHf0i7+vri0ajobi4GLPZTExMzMidTQV578C718Oyu+CU+6bamiGpqanh4MGDpKen4+Fh/aFQSsk999zT8fLLL2+sr68/X0rZM8lmqkwRqrBPAHZ2dkuCg4Pf+/LLL/0TEhKstjGbzeTl5WEymUhNTZ0asZlhtLW19Yu5EIKAgAACAwNxc3ObuniFmr1KlPvBT8DRUykos+BmcPaaGnsmEZPJREF5KV8dzCa37hC15nraelt44vT7SYu0UWEH+OBW2P1fuPpjiFo61dYMSVtbGzk5OSQkJAxb6OeJJ57ofvDBB/fV19f/SErZNokmqkwRqrCPM66urheEhIS88N133/kONVfe29vLjh07CAwMJDo6Wg2SOwG6u7upqKigqqoKJycngoKCCAgImPpCPrX7FJf7gY/A0QMW3qqUfZ2hgl7V1sTG0v3srs6noOUw1V2ltJsqkXZN/W2k1AJmPLpW8Pf0HxMRHk5AQIDtPdT2dMBzy8DQDbdsAhfbTTft7e1l586d6HQ6YmJihvwteeuttwy33357UX19/XIpZe0km6kyyajCPo74+PjcGhUV9eevv/7ax9vbetnj7u5utm/fTnx8/NSU05wBGAwGqqqqqKioACA0NJTg4ODJCXobidr98MPDsP9DcHBXxHzRrUrE+wygpKmOTeX72V2Tz+HmQmq7S+mQlUhta38babbDwRyIj0MY4e5RJPrGsiA0kUCzE7/Z/iCF3XlcGfgM50S6Ultbi5eXF6Ghofj5+dnOQ27Vbvj3qRB7Olz2H7AVu6xgNpvJzc3F3t6e5OTkIa/hN998Y/7xj39cWVdXt1JKOezyqirTG1XYxwEhhPD39//znDlzfvbxxx97DZUz3N7eTnZ2tlp05jgwm83U1tZSXl5Od3c3wcHBhIaG2s5COHUHlDn0fR+AgxssvFkZpdvwaG8ozGYzhxpr2Fy2j9y6AopaCqnTl9Epq0Db3t9Omh1wlEH4OoQR4R5Nsn8sC0MTSQ+OwcFKvvWWLVuwD7Xn2m+vpbfuTN649B7SwrxoamqivLyc5uZmdDodYWFhQ84bTypbnoYvfgtnPgrzb5xqa4alr/5Fd3c3aWlpQ2Yn7Nq1i7PPPru2qqrqDCnlrkk2U2WSUIX9BLGI+hMrV6686j//+Y/nUAUkmpqayM3NJSMjwzZ+tKYJXV1dlJaWUlNTg7+/P2FhYQxV3GdKqDtoEfT3laplC25SAuOmgaCbzWb211WwuXwfe2oLKG4rol5fRjdVoB2wbofJCSeC8XMMI9IjhhRdLItCk5gTGIHdKN3oBoOBzZs3s3z5cq75/Hpyqg/i0fAHPvv5SjycFE+LyWSirq6OsrIyDAYDERERBAcHT52r3myG/14Cxevhp99BQPLU2DEGCgsLqaurIzMzc0gPVmFhIaecckp9WVnZ2VLK7ZNsosokoAr7CWAR9adXrVp1xSuvvOIx1FNyTU0N+fn5zJ8/33ZGmDaMlJL6+nqKi4sxGo1EREQQFBRkW3Ox9fnww99g77tg76IIetbtNinoRpOJ3JoStpbvZ2/9IUraiqjvKaNHVINmQG61yQVnQtA5hRPlGc0cXTxZ4Ukk+occVyGagZSXl9PV1UV8fDybqzZz01c30VN9MasizuXJy+YOch93d3dTWlpKdXU1Op2OyMhIXF3Hv9zriHTUKyVnXXzgxu/AwWXybRgjFRUVFBcXM3/+/CFjTUpLS1m+fHlDRUXFuUajccskm6gywajCfpxYRP35s84665IXX3xxSFEvKyujrKyM+fPn20YJTRvGYDBQVlZGeXk53t7eREVF2Z53o74A1v9NSYuyd4EFP1Vy0V19p9oyeo1GdlYeZlvFAfY1FFDWVkyjoYIeUY3QDFiW2uSOqwghwCmcGC9FwBdHJBPjE3DCAj4U27ZtIykpCXd3d6SUXPrJpVS3tVGe9zMeuXguazLDrB5nNpupqamhuLgYOzs7oqKi8Pf3n9y5+MJv4bULIONaOOfxyTvvCVBXV8f+/fuZN2/ekA9E5eXlLFu2rLG8vPx8o9G4cZJNVJlAVGE/DoQQQqfTvXjeeedd9Nxzz3lY+5HpKyTR2NhIZmbmkDWeVZSc88LCQmprawkPDyc8PNw2AuEG0nBYcbnvfQfsnJQ516yfK7XGJ5kuQw/byw+xo/IA+xsOUdZRTLOhgl5Rg9AcWX5amLxwEyEEOIcT6z2LuYHxLA5PIsLbf1LtNRqNbNy4kRUrVvRv+7z4c+5afxdhhlsoKYvm49uXEOM/fF381tZWiouLaW1tJSYmhuDg4Al7EBnEV7+HTU/AJa9C0nmTc84TpLm5md27d5Oenj7k9FVlZWWfuF/c29v7/eRaqDJRqMI+Riwj9X9fcMEFa5599ln3oUR937599Pb2Mnfu3Mn78ZlmdHV1cfjwYZqbm4mOjiYk5MRdvuNOY6Hics97WxH0eTfA4l9MiqC393SztSyfHVUHONBwmIrOYloMFRi0dQhh6m8njD54aEMIcokk1juG9MAEsiISCfawjWmByspK2trajlrhzGg2cvb7Z+Nh70P+7qsJ9XLhvVuzcLQbebqlu7uboqIi6uvriYyMJCwsbOKnaYy9SsnZpkK4eRN4Wfcw2BodHR3s3LmT2bNn4+tr3atUXV3NkiVLGkpLSy9QR+4zA1XYx4BF1J89++yzL3vxxReHHKnn5eUhhCAlJcV20ndsiLa2Ng4dOkRXVxezZs0iMDDQ9q5TYyGsfwT2vAVaR5h3PSy+A9zGf7Tb3NXBxtID5FQfJL/pEBWdpbQZKzBqGxBCqQQqpUBr8sPDLoQQl0jifWaRHpTAksgkfF2mdsGYkdixYwdxcXGDRo1vHHyDv2z7C7clPMZD7/dw/ZIofnd20qj77e3tpbi4mKqqKsLCwoiIiJhYT09TETy7DAJT4OpPbLLkrDW6u7vZtm0bKSkp+PlZfyCtrKxk6dKlDWVlZeqc+wxAFfZRYnG/P7l69eorX375ZU9rI0spJXv27EGr1Q6bT3qy0traysGDBzGZTMTGxtpW3nIfTUWw/lHIfRO09kdG6G66E+66vqONDaX7yKk+SEHzYao7S2kzVWDSNiGE8j2UUoOdSYeXXSihboqAZwYnkhWRgKeT7QduHYvJZGLDhg0sX758cICcsZtV76xitv9s/Dpu4ZUtpbx87TxWxo/tWhuNRkpLSykrKyMoKIiYmJiJE/g9b8N7N8Lye2DlvRNzjglAr9f3xzn4+1t/OK2oqOgbuZ+lRstPb1RhHyU6ne7R00477YbXXnttSFHvKxKRlJRke4I1hXR2dnLw4EH0ej2JiYm2mcPfVGwR9DcUQc+8ThmhuweMuauK1iY2le5jV81BDjUXUtPdV4Wtub+NNGuxNwfgbR9GmFsUiX6zmB+SyILQeFynumreOFJdXU1TUxPJydZTxZ7NfZandz/NG2e+w6//U0t9ew+f37EUnfvY100wm82UlpZSUlJCeHg4kZGRE+Oif/9mxZNz9ScQuXj8+58genp62Lp1K4mJieh01h+eysrKWLZsWX1paekqNc99+qIK+yjw8/P71aJFi+7/8MMPvYYTdQcHBxITE1VRt9DT00NBQQHNzc0kJCRMfjTzaGguOSLoQqsI+pI7wH3kqoBFTbVsKt3H7tp8CluKqO0upVNWHVOFzR4HGYivvVKFLckvlvkhicwLnYWT/czPksjOziY6OpqhKjG29rRy2juncVrEaVwTew/n/HMj8yJ9eOXa+Wg0x3evGI1GioqKqKysJCYmhrCwsPG973ralZKzxh64eaNNpjgOxWjEvaioiKVLl9ZWVVUtVivUTU9UYR8BDw+Py5OTk5/+/vvvva3lhPa53+3t7VVRt2AwGCgsLKSmpqZ/fXmbuy7NpbDhUWWxD6GFjGtgyS/BI+ioZmazmYLGKjaX7leqsLUqVdi6ZBVoO/rbSbMjTn1V2DyiSfGPZWFoMmnBUdjbUv79JGI2m/nhhx9YsWLFsJ//X7f/lTcPvslnF37G9/sN3PteHveekcBNy09soZje3l4OHTpEQ0MD8fHxBAQEjN99WLUL/n0axK2CS1+36ZKzx9In7sO55Xft2sXq1avL6+rq5qm15acfqrAPg4ODw49iY2Pf3rJli4+1fOq+QDmtVqu63zmyDG1JSQmRkZFERETYXpR7Sxls+Dvseh2Epl/QzW6B7K0rY0vZfvbUFShFXPqrsHUfOd7kjBPB+DuGEekRzeyAeBaFJTEnINz23usUU1tbS11dHbNnzx62XXVHNWe+dyaXJVzGXfPu4mf/zeHLfbW8e0sWqWFeJ2xHd3c3Bw8epKuri+TkZLy8TrxPADY/BV/eD2f9QwmunEb0zbknJycPGVBnqS1/qK6ubr66Ktz0QhX2IRBCpEVGRn65detWv4CAwfOsUkr27t0LoEa/o5TM3bt3L76+vsTHx9te3n5LOWz4O6Zdr1NlZ8eOsBV85xpPQVc9jb0V6EUVQjNguWqTKy4iGH/HcKI9Y0gNiCMrPJl4v0nMnZ7m7Nq1i/Dw8CHTrAby2w2/5euyr/nq4q/A5MKZT27ATiv45PYluDuNTyBcW1sbeXl5uLm5kZiYeOIFo8xm+M/FULpJqUoXMPqIfltAr9ezdevWYVPhLKvC5dbX1y9R13OfPqjCbgUhRExQUNCmDRs2BMTEWHcH5ufno9frmTNnzkkt6j09PRw4cICuri5mz56Nu7ttpF71Go3sqDxETuEmWovfpUNfQKG9HYX2jhg0A+55kweuIoRAp3CivWOYG6AUcYnxVVfeOxHMZjPff/89K1euHNX3o6C5gIs+uojb5t7GTak3sbOkiUue28J5c0N47NK542aXlJKKigoOHz5MdHQ04eHhJ/b97aizlJz1U+rJ20+vktF9qXBpaWlDFrF5/PHHux966KH1dXV1Z0opzZNsospxoAr7MQghAnQ63Y5169aFpaWlWW1TUlJCfX09mZmZJ62oD3S7x8fHExQUNCXXosvQw7byAnZUHGB/4yHKO0po6i3HqKkBzZEiLp5GO+w0Ufi6xDHLK4a0oHgWhycT5jX1pWBnIvX19VRVVZGamjrqY279+lb2Ne7ji4u+wMnOiSe/OcQ/virgH5ekcmF66LjaZzAYyM/Pp6WlhZSUlBNzzx/+Gl6/CDKvh7P/MW42ThYdHR3s2LGD+fPnD1l+9q677up45ZVX3qurq7tGqqJh86jCPgAhhIe/v/+ON954Y9aPfvQjq/7WqqoqiouLWbhwoW0tSjKJNDc3k5eXh5+fH3FxcZPidm/Vd7Gl7CA7qw5ysPEQFR0ltBr7qrAdKeJib/IkzmxmXncVMQYDfoEriFtxDwEhKRNuo8oRcnNzCQ4OHjI4yxo7a3Zy7RfXcv+C+7k04VJMZsnlL2xlX2Urn/x8KVF+478IzED3fFJS0vHnv395vzLnfunrkHjO+Bo5CbS0tLB7924WLVpkdeEYKSVXXnll25dffvlUXV3d/VNgosoYUIXdghDCXqfTbXziiSfSLrvsMqvf7oaGBvbv38+iRYtsr5b5JGAymcjPz6epqYnU1NQJcbsrVdj2k119kPzGw1R2KQJu0jYMKOIisDP542EXSohrBPE+s5jv5c+Syi/w2P1fkCaYewUs/RV4R4y7jSrDI6Xk+++/Z/ny5WOKR5BS8pPPfkKTvomPL/gYO40d1a3dnPHEBsK8XXj3liwc7MY/vmGgez45OXnINLBhMfbCi6cp6ZO3bALP8fUwTAZ1dXXk5+ezaNEiqw/rRqORM844oyU7O/vupqam56fARJVRogq7hYCAgLW33Xbbxb/73e+sDgtaW1vZtWsXCxcuxMlp7MUzpjvNzc3s2bOH0NBQoqOjT9jtXtvRysbSfeRUKUVcqrpKaDdVDqrCZm/S4WUfSqhrFAm+s8gMSWRhWPyRKmztNbDxMdj5MpiNMPfHsOzX4B15gu9Y5XhpbGykrKyMoaayhuOb0m+44/s7eGTZI6yOWg3AF/tquOm1bH66LJrfnpk4Qg/Hj16vJzc3F0dHR5KTk8f+8N5YqOS3B86Baz4BzfTz6FVUVFBeXs6CBQusPpR1dnaSmZnZdOjQoXOMRuPmKTBRZRSMKOxCiPuAHwMmwAzcJKXcdsInFuJPwHop5dcn2E8o8DSQBGiBz4BfjSWC08fH57Zly5b9+f333/dauXIljz76KJmZmZx55pn897//pbu7m40bN3LGGWfg5jb8ClQzjYGj9Llz5475/Ze3NLKxdC+7avI5bKnC1iErkdqW/jbSbIe9OQAfhzDC3CJJ8o1lXmgiC8LicLEfogpbey1sehx2vgQmA8y9HJb+Gnyijv/NqowLeXl56HQ6rGWTjIRZmjnvg/NwtnPmrbPf6n+A/N0He3ltaymvXDef5XETtzrdCY/ec9+E92+CFb+FFXdPjJETTGFhIS0tLaSnp1t9gC8rK2PRokU1VVVV86WU5VNgosoIDCvsQohFwD+AFVLKHiGEH+AgpawaVedC2EkpjSO3PD6EctdtA/4lpXxZCKEFngc6pJS/GE0fdnZ2SxMSEj7YsWOHj7OzMytWrOgXdlCivn/44QceffRRvvzyy4l6KzbJWEbphY01bCzdR25tAYUth6nVl9EpK0Hb3t9Gmu1xlEH42IcRYanCtiAskYzgmNFXYeuog42Pw84XFUFPvUwZoftEn+C7VRkPjtcNP5D3Dr3HHzb/gedPe55FwYsA0BtMnPfPTTR29vD5L5bh7z6xZXdPaPT+3k8h739wzWcQsWjijJxA9u/fj8lkGjKVd9OmTfKCCy4oqK+vT5dSdk2BiSrDMJKwXwhcK6UcFA0ihMhAEX03oAG4RkpZLYT4HtgNLAE+Bq4DoqSUZiGEK3AQiAZeAD6RUr4jhJgHPAG4Aj3Aj4Au4GFgBeAIPC2lfO4YG34E/EFKuWzANg+gFAgDLgYypZS3WfZ9AjwqpfxeCPEvYLGdnV3Sbbfdpn3ssccAjhL22NhYnnvuOT766COee+454uPjOe2006itreXCCy/k/PPPB+CKK67gkksu4bzzpsc6zSMhpaSgoID6+vqjRulms5n8hio2lykCXtRaSH1PXxW2ziPHmx1xksH4OYQR6RlNin8cC0MTmRsUhd3xBhx21Csj9B0vgqkH5lgE3ffEqpOpjC/Nzc0UFRWRkZFx3H30mnpZ/e5qYrxieOH0F/q3F9S2c85TG1kQ7cvaa+Ydd8nZ0dI3ei8sLBw213sQ+jbFJW8ywC0bwdl6OV1bRkrJ7t27cXd3Z9asWVbbvPDCCz333Xffd/X19WeqkfK2xUjhzF8CvxdCFABfA29JKX8QQtgDTwHnSSnrhRCXAg+iiDgoo/pMACFEOrAc+A44G/hCSmnoewoUQjgAbwGXSil3WIS5G7geaJVSzhNCOAKbhBBfSimLB9iXDGQPNFhK2SaEKAGs341HeNDf3//bDz74QPvb3/6WPXv2MGfOnIH98OMf/5iAgADuuOMOvv76a3bv3g3ADz/8wGOPPcb5559Pa2srmzdv5pVXXhnhdNMDvV7Pzp07adAYqLTr4L/fvUBxWxENPWXoqR5Uhc2ZYMKd5hPpEc0cXRyLwpNI0Y1jFbaOetj8hCLoRj3MuRSW/UYVdBulqqqK4ODgE+rDQevAT5J+wmPZj7GvcR/JvsoCMnEB7vz+nCTue38vL24s5sZlE+ulEUIQFhaGr68vOTk56HQ6YmNjR44vcfKAi1+EF0+Hj34Ol7w6rUrOgvLeU1NT2bp1K25ubgQGDq7rcOONNzrm5ORkvfvuu38G1Eh5G2JYYZdSdlhG5kuBlcBbQoh7gJ1ACvCV5SbXAtUDDn3rmH9fiiLslwHPHHOaeKBaSrnDcs42ACHE6cAcIcTFlnaeQCxQzAkihNC4urp+5ezsPOvmm2+murqa/fv3HyXsBQUFtLa2EhAQQEdHx1HHL1++nFtvvZX6+nreffddLrroIturtDYKjCYT2ZVFbKvYz96GAoqaD9HYW4HBrhah6T3S0OSGiwgm0mkJ0Z7RpOriyIpIIs53AquwdTbA5idh+wuKoM9eA8vuAr+RntdUpgopJfX19SQkJJxwX2vi1vDCnhdYu3ctjyx/pH/7j+eHs6Gggb99cZAF0T7MCfU64XONhIuLC1lZWRw8eJCtW7eSlpY2cgBtSAb86Pfw1e8hey1kXjvhdo43Go2GzMxMNm/ejIuLC9bKaj/11FMee/bsudXV1TWns7PzvSkwU8UKI6qRlNIEfA98L4TIA65GGSXvk1IONYHUOeDfHwF/EUL4ABnAt6O0TQC3Sym/GKbNfhR3+5GDlBF/IJCP8vAxUHmcALy8vP5lNpvjdu/eLby9vbnmmmvQ6/X9jbq7uzEYDHz00Ufcf7/1B9GrrrqK119/nTfffJOXX355lG9patAbetlRcZjtlQfY33CIsvZiGg3l9IoahMZwpKHRAze7ECKck5nlFcPcwHiywpOI9hl7ENRx09l4RNANXYqgL78L/GInzwaV46KtrQ1XV9dxqe/g7uDOmvg1vLLvFX7e9nPCPMIAZST58EWzOfOJFn7+xi4++flS3Bwn/qFao9GQlJREXV0dW7ZsISUlZeQc/UW3Q+F3sO4eCF8IuomL6J8oHBwcSE9PJycnh6ysrEFleO3s7Pjkk0+8MzIynhNCFEgp906RqSoDGPYbIYSIB8xSykOWTXNR5q/zAX8hxCIp5RaLaz5OSrnv2D4so/4dKHPon1geFAaSDwQJIeZZXPHuKK74L4BbhBDfWlz3cUCllHLgQ8M3wMNCiKuklK9aguf+DvxTStltccnfKoTQACHAfHt7++XR0dGXGQwGjaenJ7W1tXz++eesWLECAF9fX9rb2zn11FMxm5XCJ+7u7rS3tzOQa665hvnz5xMYGEhSkm3UiO7s6WFL+UF2VB7kQOMhKjqKaTZUYNDUIgZUYRNGb9y1IUQ5zyHaIxKvbkeWRc1mydyMqauk19WkFPjY/jz0dkLKRbD8bvCPmxp7VMbMeLjhB3Jl4pW8vv91Xtn/CvcvPPKA7eXiwOOXpXHZ81v4/Yd7+cclc8ftnCOh0+lwd3dn165d/avGDem10mjggueUkrPvXA83fjPtSs4CeHh4kJCQwM6dO1m4cOGg9+vt7c1nn33mt2LFis+EEGlSysYpMlXFwkiPum7AU0IIL8AIHAZ+KqXstbjInxRCeFr6eRwYJOwW3gL+hxIIdxSWvi61nMcZRdRPBf4NRAI5luj3euD8Y46VQogLgKeFEL8D/FHiAB60NNmE4rrfDxwA9nt7e//ym2++8bjjjjtISEggLCyMxYsXA0oE/OrVq/H29j7qydTX15fFixeTkpLCGWecwSOPPEJAQACJiYn9AXSTSau+i02lB9hZdYD8psNUdpTQYqzAqK0/qgqb1uSLhzaUINdM4rxnkR6UwOKIJALclJrQdXV17Nu3jznz54w+MGi86WqCLf+Ebc9ZBP1CxeWuO3F3rsrkUltbS2zs+HlW/F38OTfmXD44/AG3pN6Cr/ORe3R+lA8//1Esj399iKWxflyQNnkFYZydnVm0aBEFBQVs3bqVjIwMq9XaAHAPgAueVRaL+fJ3cNajk2bneBIYGEhbWxv79u2zulpfQkICzz33XNBPf/rT94QQK9RguqllRhWoEUJkAW8AF0gpc47Z56DT6XI/+eSThHnz5g061mw2s2XLFmbNmjWq/Nu+RU9ycnKGXDzhRGnsamdjyX5yqg8qAt5VQpux8pgqbBrsTH542oUSYinikhGcwOLwRLycrZfglFJSVFREdXU1mZmZU1Nwp6sJtjxtEfQOSD5fGaFPQ3elCrS3t7N//34WLFgwrv0WtxZz3gfnceOcG7k97faj9hlNZn78wjb2VbXy2S+WEuE7/iVnR6K2tpYDBw6Qnp5udQ66ny/uUx5gL/svJJw1eQaOI1JKsrOz8ff3JyLCekXHm2++ue1///vfw42NjQ9NsnkqA5hRwj4cAQEBL9x5551X3H333VZ9Ybm5ubi6ug6Z2jGQr7/+muuvv55f/vKX3HHHHSdsW1VbExtL97O7Op+ClsNUd5XSbqpE2jX1t5FSe1QVtkS/WcwLTmRheDzujqN375lMJvbs2QPAnDlzJr/efXczbHkGtj0LPW2QdL4i6NNsyUuVo8nPz8fFxYWwsLBx7/uO7+5gR80Ovrr4K1zsXY7aV9nSzZlPbCDS14X/3TwxJWdHor29nezs7P7FkKxi7FFKzraUwc2bwDNkco0cJ0wmE5s3byYpKcmql6+np4f09PSm/fv3r5JS7pwCE1U4SYTd2dn5vIULF7787bffelubQy4pKaGxsXHISkvjRVlLPRtK97HbUoWttr8KW2t/G2m2w0EG4m0fSribUsRlXkgi88Nih67CNkp6enrYuXMnQUFBREVFTe58encLbH0Gtv7LIujnWQQ9efJsUJkw1q9fP2FrKOyp38MVn13BXfPu4sqkKwftX7e3mptfz+Gm5dHce8bUeHx6e3vJzs7Gx8eHuLg469+thsNKfntwGlz90bQsOQtKcPHWrVtZuHAhzs6DBxWFhYUsXry4vLa2draUstVKFyoTzIwXdiFEWGho6M7du3frrD1htra2snv3bpYsWTIuo1ez2UxhUy2bSvexpy6fwpYiavWldMqqY6qwOeAog/B1CCPCPZpk/1gWhiaSHhyDwwSkzrW2tpKTk3P8i1wcL/pWRcy3PAM9rcrKV8vvgUB1tbWZQmdnJ3v27GHRoomrsnbtumup6Kjgsws/w14z+OHhvvfz+M+2Ml69bj7LJrDk7HCYzWb279+PXq9n7ty51lNgd/8XPrgFVt4Py38z+UaOE42NjRw4cICsrCyrwYNvvvmm4Re/+MV3dXV1q9X59slnRgu7EMIuKCgo780334xftmzZoEdoo9HIxo0bycjIGPNKZWazmf11FWwu38ee2gKK24qo15fTTSVoB1RYNDvhKIPwdwwn0iOaFP9YFoYlkRoYefxV2MZIdXU1BQUFZGRkTF6te30rbH0Wtj6t/DvhbGWEHjRn5GNVphWHDh3CwcFhyHnX8WB9xXp+9s3PeHDJg5wbc+6g/XqDiXP/uZGmTgPr7liKn9vElpwdjtLSUkpLS5k/f/7g+BUp4b0bYe97cO1nShrcNCU/Px+TyTRkVtBVV13V+vHHH/++ubn5yUk27aRnRgu7Tqd74oorrrj5wgsvdEhLSztK1KSU/dWkhpsXNJpM5NaUsLV8P3vrD1HSVkR9Txk9oho0R3LfMbngTDD+TuFEeUQzJyCOrLBkknShE1fEZRSUlJRQWVnJ/PnzJ2epWX2bEhC35Z+gb4H4s5TFMIJSJ/7c0wyTyURPTw96vR6DwYCUErPZjJTyqJcQAo1GgxCi/6XRaHB0dMTJyQkHB4epS1MENmzYwPz584eODB8HpJRc9PFFSCl599x30YjB36n8mnbO/edGFkb78vIklJwdjoaGBvbu3UtmZubgh2l9Gzy7BKQZbt4Izl5TYuOJIqXsDzi25gXs7u5m7ty5jQUFBadIKfdMgYknLTNW2J2cnFalpaW9sWnTJu+2tjZ2795NTExMv4iXlZXR0NBAeno6AL1GIzlVhWytOMC++kOUthfR2FtOj6g+pgqbO64imACnCGK8opmji2dxRDIxPgFTKuDH0lfvvbW1lYyMjIkPkutpVwLiNvcJ+pnKCD147sSe1wYxmUzo9fpBrz4R7+1V7qeB4mxvb3+UeA/897GCbzabMZvNg/oTQuDk5NT/6ut74P/H+wGgu7ubXbt2kZWVNa79WuPjwo/57cbf8vSPnmZZ6DKrbV7bWsrvPtjL/WclcsPSqV0YqG/6a+7cuXh7H1MvvmInvLRK8WStWTvtSs72odfr2bJlC4sWLbKaXXPw4EGWL19eWldXlyKl7LDShcoEMCOFXQjhFxwcnJednR3YV+PYYDCQl5eHlJIWZ8EHu76n3bmb8s4Smnsr6NXUIDRHFqITJk/cRAgBzhHM8laqsC0OSyLSZxLnp48TKeVRke8TOprraVeKymx+Sol4j1sNK+5RAoROAoxGI62trbS0tNDa2kpbWxtCCFxcXAYJa5+4TtQI22w2D3qIOPbl4OCAp6cnXl5eeHp64ubmdkK2FBYWotFoiIqa+OVyDWYDZ713FkGuQbxyhvW1GaSU3PRaNt/l1/H+rYtJCZmYVNTR0tnZyY4dO0hKSho8qt34GHz9RzjnSci4ekrsGw/q6uo4fPgwixYtsnovvfjii7333XffhzU1NZdMgXknJTNS2AMDAz//17/+deoFF1wwKHrlwx0buW/frf154MLkg7smhCCXCOK8ZjE3KJ4lEUkEe/hMut3jgclkIicnB3d3d+Lj4ydO1Hs6Bgh6E8SuUlzuIce/qpetM1DEW1paaG9vR6PRHCWUHh4eNuW5OZbe3t5++1tbW+ns7MTOzq7/PXh5eY1J7Ddu3DiptRBe3/86f93xV1474zXm6uZabdPS1csZT2zAyV7LJ7cvwXUSSs4OR09PD9u3bycqKorQ0AGFdMxmeP0CKNsGN/0A/vFTZ+QJcuDAATQaDfHxg9+DlJLTTjuteePGjVfo9frPp8C8k44ZJ+yurq5rTj311Oc+/PBDq2slfrlpK3fm346viOSRzPuYl5I6pfOT44nBYGD79u0EBwdP3AiqpwN2vACbnlQEfdZpsOJeCJ15gm4wGKirq6O2tpa2trajRNzLywt3d3ebFvHR0tvbe9QDS5/Y+/j4EBgYiLe3t9XvSN9KgEuWLJk0W7sMXZz+7ulk6DJ44pQnhmy3taiRH7+wlQvTQ3l0zdTHdxiNRnbs2IFOpyMmZsDKhO01SslZ9yC44Ruwn4JiUeNAX4Gv+Ph4/Pz8Bu2vqakhPT29qrq6OklNgZt4ZpSwCyH8goKC9ubl5QVYS22rqKigurqaa7f9C3v3vbyU/hz6Dv3oVmuycXp7e9m6dSuzZs0a13rdR07QCTv+DZuegK5GmHWqkrYWNriK33Sms7OTmpoaamtrMRqN6HQ6AgIC8PT0nBEiPloMBgMNDQ3U1NTQ0tKCl5cXAQEB6HS6/jSu4uJizGbz0UI1Cfxz1z95fs/zfHD+B0R7Dj2P/o+vCnjym0M8cdlczps79QVhzGbzUd60fgq+hP+ugfk3wZl/mzoDT5C+/PasrCyrgZSvv/664de//vVHNTU1F1s5XGUcmVHCHhgYuO7ZZ5899fzzzx8UKdbd3c22bdtYvHgxZ/z7ZWpdnuLxlY8z22k2+/btIykpaVSlZG2Rnp4etm3bRlxcnNV1k0+I3q4Bgt4AMT9S5tDD5o/veaYIKSXNzc3U1NRQX1+Pg4MDgYGBBAYGWi2+cTIy1DWqqKggIyMDFxeXkTsZR5r0Tax6ZxVnRJ3Bnxb/ach2RpOZy57fysGadj77+VLCfSfXTmtIKdm1axfOzs4kJCQc8YSsu1cp4HT5mxB/xtQaeQJUV1dTUVGBtbLdUkpOP/305g0bNvxEr9d/NgXmnTTMGGF3cXG5ZNWqVc+9//77Xsfuk1Kybds2YmJi8Pf35+dv7OT77ttYFbOUR5Y/Qk9PD7t27cLNzY3ExMTJL7N6AvT09LB161YSExPHt/BMbxfsfAk2PQ6d9RC9UnG5h49vLfCpwGg0Ul9fT01NDc3NzXh5eREYGHjUaFRlaDo7O6msrOTQoUO4u7uj0+kIDAzE09Nz0qa1Htz6IO8ceocvLvoCncvQ931FcxdnPrGBKH833rl5Efbaqfe6SCnZvXs3jo6OJCYmKtfM2AP//hG0VsItm8BjArxuk0R2djaBgYGEhAz2ktTU1JCWllZdU1OTqLrkJ46pv8vHASGEv7e395Mvvviil7X9ZWVlODs796+fPEvnSU/bbL4v/54uQxeOjo4sWLAAZ2dnNm3aREfH9MjKmBBRN3Qri7M8kQpf3qeUfL3uC7jqg2kt6lJKmpqa2LVrFxs2bKCpqYmIiAhWrlxJeno6wcHBqqiPEldXVxwdHYmLi2PRokW4ublx+PBhfvjhBw4dOkRPT8+E23B18tWYpZnX978+bLtQbxcevmgOueUt/OOrggm3azQIIZg7dy69vb0cOHAAKSXYOcLFL4NRD+/9FMzHrm49fZg9ezYFBQVW74PAwEAeffRRv4CAgJemwLSThhkh7AEBAa8/88wzfj4+gyPZu7u7KS4uJjn5SE3yGH83jK1z0Jv0/FDxA6B82WJiYpgzZw47d+6krKwMW/Zm9Pb2sm3btvETdUO3Uvr1iVT44rfKsqnXfg5XfTitq2P19vZSVFTE+vXrKSoqIjQ0lBUrVpCcnIyPj8+MCZycbKqrqwkODsbe3p7Q0FAyMzNZvHgx9vb2bNu2jR07dlBXVzdh36FQ91BWRazi7YK3aettG7btmbODuHx+OM/+UMjGQw0TYs9YEUKQmppKT08P+fn5yka/WDjzESjZoKTCTVMcHBxITEwkNzfX6uf/4x//2H7OnDkrnZycpucyd9OAaS/sbm5ul2VlZc0/77zzBvnPpZTk5uaSnJx81Ggs2t8VU3ckHvZ+fFZ89FSPl5cXS5YsobGxkezsbAwGw8S/iTHSFygXHx9/4qJu0CulX5+YC+vuAb84uOYzuPpjiJj4oiMTRUtLCzk5OWzevBkpJQsXLiQzMxN/f39VzE8Qg8FAT08Prq5HL5Nqb29PZGQky5YtIzY2lurqar7//nsOHTrUX0RnPLk25Vo6DZ28nf/2iG1/f3YSMf5u/PLt3TR2TLxHYTT0jdy7urqOiPvcKyDlIvjuL1C+fWoNPAECAwOxs7Ojqqpq0D4hBK+99pq3t7f3C0IIr8m3buYzrefYhRBeQUFBB/fu3RtgbbReWlpKS0sLqalHp7voDSYSf7+OhZmbONj1Od9f8j2ejoMLWVRUVHD48GHmzJmDtf6nAqPR2B/9fkKBcgY95LwKG/8B7dUQsUQJiotaOn7GTjJms5mamhqKi4uxs7MjJiYGX19fVcjHmfLycrq6uqzmLB+L0WikvLyc0tJSvLy8iI6OHn7d8jFy01c3UdBcwLqL1uGoHb6k7YHqNs57ehOLY3x56Zp5NnNf9K1z7u3trWQY6FstJWeBmzdM25Kzvb29bNq0aciqdJYo+fdqamoumwLzZjTTesQeEBDw+F/+8hef0brg+3Cy1xLs6YxTTwZGs5Fvy7612n9oaCjz5s1j3759FBQUTLlr3mw2k52dTXh4+PGLurEHtr8AT6bB578B7yhldH7tp9NW1A0GA4cOHeKHH36gqamJuXPnsmDBAvz8/Gzmx3smUVVVNeqUSjs7O6Kioli+fDnBwcHs37+fzZs3U1tbOy7fp2tTrqWhu4GPCz8esW1ikAf3n5XId/n1vLyp5ITPPV4IIUhPT6euro6Kigpw8oSLXoK2Svjkl8rCMdOQPpf8nj17rH7WV1xxhX14ePipQojMKTBvRjNthV0IkRoUFHTO1VdfPWhlk76o05SUlCEDoqL9Xalv1BHqFsq6knVDnsfV1ZXFixdjNBrZsmULer1+yLYTSd+0go+PD+Hh4WPvwNijpK09mQaf/Rq8I+Cqj5QVpqKs1922dUwmE4cPH2bjxo1otVqWLl1KSkrKIBexyvhhNBrp7u4e82qIQgh0Oh0LFy5k9uzZVFdXs2nTJhoaTmzOe0HgApJ8k1i7by2mUQScXbkwglMTA3j484PsrbSdoGyNRsO8efMoLi6mrq5OqQ9xyn2w7z3YNXyAoC3T55KvrKwctE8Iwdq1a30DAgJeE8LKqj4qx820vJhCCBEQEPD62rVrfayNyMrKynBxcbFaAamPGH83ius7WR21mm3V22jsbhyyrUajISkpidjYWLZs2UJtbe24vI+xcODAAezt7Zk1a9bYDjT2wo4X4cl0+PRX4BkKV36gBMZFL5+Wi09IKSkrK2P9+vVIKVm6dCnR0dFqVPskUFtbe8L1Htzd3Zk7dy5z586luLiYrVu30tp6fCIrhOC6lOsobSvlu/LvRtX+kYvn4OPqwM/f2EVnj3HEYyYLOzs75s+fz/79+2lubobFdygP3Z/fBfW2EdF/PMyePXvIbImkpCTWrFkT4uHhcfMUmDZjmZbC7u7uft25554bfuzcORyJgh5qjeA+ov1d6ew1Md//R5ikia9Lvx7xvP7+/mRlZVFcXExeXh4m0+SkpBQWFtLd3U1ycvLoXcvGXtj5MjyVDp/eqeTFXvm+kroWs3LaCnp1dTXr16+nvb2dxYsXExsbqwr6JDIWN/xIuLm5MW/ePOLj49m3bx/Z2dl0dnaOuZ9Tw08lzD2Ml/a+NCr3vrerA49dOpfixk4e+Hjf8Zg+YTg6OjJ//nx2795NR1c3XPA82DnBO9cpcTHTEHt7e+Lj49m/f7/V/X/5y1/c3dzc/iCEsI1AphnAtBN2IYSXm5vbg3/729+sRuAcOHCA2NjYEdcej/FX1kg26wOI8Yzh85LRrU3Ql/Pu4uLCpk2baG9vH+M7GBsVFRXU1dWRlpY2OlE3GSB7LTyVAZ/cAe6B8JP34PovIeaUaSnoAI2NjWzatIna2lrmz59PcnIyDg4OU23WSYXJZKKjo2Ncg98AvL29ycrKIiwsjOzsbPbs2TOmXHitRss1ydeQ15DHztqdozpmUYwvt62cxds7K/god3Dk9lTi4uJCeno6O3fuRO/gDef/C2rzlJXgpilBQUHo9XqampoG7XN3d+eRRx7xCQgI+OcUmDYjmXbCHhAQ8Nhf/vIXHy8vr0H7Wlpa6OjosFrx6Fii/ZV52KLGLlZHrSanNoeazppR2dCX856amkp2djalpaUTEljX2NhIUVER8+bNG7lOucmgRLk/lQ4f/wLc/OGKd+H6r2DWj6atoLe1tbF161YKCwtJTU1l7ty5aqnXKaKurg6dTjdhAYk6nY6lS5fi6+vLli1bOHjw4KjTTc+NORcfJx9e2jv6uie/+FEs6eFe3PdeHuVNXcdr9oTg6elJSkoKO3bswBhzKiy4Gbb9C/KHjgeyZYQQzJ49m71791r9rbz88svtwsLCTlcD6caHaSXsIwXM5eXlMXv27FH98AR6OOHioKWovoPVkauRSL4s+XJM9nh6erJkyRKamprGPee9q6uLPXv2MG/evOFdzSYD5LymjNA/uh1c/OCKd5SVomJPnbaC3t3dTXZ2Nnl5ecTHxzN//vwxB2ypjC/j6YYfCiEEISEhLFu2DEdHRzZu3EhRUdGID85Odk5ckXgFGys3kt+UP6pz2Wk1PHFZGgj4+Zu7MJjM4/EWxg0/Pz/Cw8PZvXs38tQ/QsBs+PBWaKueatOOCzc3N/z8/CgpKRm0ry+QTqfTqYF048C0uYADAuZ8hwqY8/b2HrWbUAhBlJ8rRfWdRHpGkuiTOGx0/FDY2dmRlpZGUFAQmzZtsupqGitGo5GdO3eSmpo69OjUZIRd/4F/ZsJHt4GLD/z4bbjxW4g9bdoKel9g3NatWwkNDSUrKwtvb6sr8KpMImazmba2Nqx5yiYCjUZDVFQUS5cupaenZ1TTXpfGX4qLnQsv73t51OcJ83Hh4QvnsKushce/tr0AtYiICBwdHTlUXA4Xv6RUiHx/+pacjYuLo6SkxOpUS3JyMmvWrAlWA+lOnGkj7C4uLlecffbZwwbMjaZgxkCi/d0oalDqwp8RdQZ5DXmUt5cfl30hISH9Ea0nkvPet/pTZGSk9aI4JiPs/q8i6B/equS8Xv4W3PgdxK2atoIOR1bga25uZsmSJQQEBKh56DZCfX39lNQFsLOzIzExkZSUFHJycjh8+PCQ3y1PR08ujruYdcXrqOwYnF41FGfNCeKyeWE8830hmw/bRsnZgSQnJ9PY2Ei10R3O+CsUr1dWW5yG2NnZDRtI99BDD3lYAukGVwxTGTXTQtiFEA7u7u4PP/zwwycUMHcs0X6uVDR3ozeYWB25GoB1xcc/h+Xi4kJWVhYmk4ktW7bQ3d095j4KCgpwcXEZnKtuMkLum/D0fPjgFnB0h8vegJ/+APGrp7WgDxylR0dHk5qaOubPUmVimQw3/HD0lXo2GAzDjt6vTLoSgeC1/a+Nqf/fn5NEtJ8rd7y1m6bO8S9/eyJoNBoyMjLIz8+nLeY8SL4Avv0/KN8x1aYdFyMF0t13331efn5+f5gC02YM00LYvby8br/xxhu9rOWljyVg7lii/V2REkoaOwlyCyJNlzbq6Pih0Gg0JCYmEhsby9atW6mpGV1AHig/ns3NzUen6plNkPsWPLMA3r8JHFzgsv/CTesh4cxpLeigjNK3b99OU1MTS5YsGd+lZ1XGBbPZTEtLy5SXVdZqtSQmJpKcnDzk6D3QNZAzo8/kvUPv0aJvGXXfLg52PHV5Oi1dBn7zP+uLl0wlDg4OZGRkkLNrF72rHgGPEHj3eqX87DRDCEFKSsqQgXQ33nijg6ur65VCiBOomX1yY/PCLoRwc3Z2/s3dd989qJyYlJK9e/eOOmDuWPpS3orqldzZ1ZGrOdR8iMPNh0/Q6iM576WlpaPKeW9ra6OgoICMjAzlvZhNsOd/8PQCZU7Nzhku/Q/ctAESzpr2gi6lpLy8nK1btxIVFcXcuXPVUbqN0tjYaFMr4Xl7e7NkyZL+WuTHLrN8Xcp1dBu7eePgG2PqNynYg9+emcA3B+t4ZXPJOFo8Pri7u5OYmMjOvYcwX/g8tFZM25Kz7u7u+Pn5UVpaOmifvb09f/vb37wDAgIenQLTZgQ2L+x+fn6/u+eee7zc3NwG7aupqcHNze2482r7U97qlR+G0yNPRyM0xxVEZ42+YhOurq7Dug+NRiM5OTlkZGRgr9VA3jvwzEJ47wbQOsAlrykj9MSzp72gA+j1erZv305jY6M6Sp8GTLUb3hparZakpCSSk5PJzs6msLCwf/QX4xXDitAV/Pfgf+k2jm067OqsSH6UoOMvnx1kf9Xwy8FOBQEBAfj6+lLQ7Q0r74W97yoxN9OQ2NhYiouLMRoHV/9bs2aN1sfHZ5UQYoylNlXAxoVdCOHv4uJy7c033zxo2Saz2Ux+fv6YA+YG4uJgR5CnU/+I3c/Zj3mB81hXsm7cXHFCiP5546Fy3vfs2UN0ZATuJV/AM4sUF5vGDi55FW7eCEnnwkh57NOEqqoqtmzZoo7SpwlSSpqamvD19Z1qU6zSN3rvi5zv6lLy0a9NuZaWnhbeP/T+mPoTQvDImlS8XOy5/Y0cunptp+RsH3FxcTQ1NVEffyVELoXPfgMNh6barDFjb29PeHg4RUVFg/YJIXjyySd9AwMD1aI1x4FNq0VAQMBf//KXv3hbqzBWXl6OTqc74WIl0f6uFDYcKWN5RuQZlLaVcqDpwAn1eyx9Oe/Nzc3s3LmzP+e9rLQEr8rvCPv0MkXQhQbWrIWbN0HSeTNG0KWU7N+/n/LycnWUPo1oamrCy8tr5AJJU0jf6D0pKYlt27bR2NhIekA6c/3n8ur+VzGaxybOPq4OPH7pXIoaOvnTx9ajt6eSvtXg9u4/gP6sp8DOQSk5a7SNdebHQmRkJJWVlfT2Dg5YPPXUU0VkZGSmECJ9Ckyb1tjst1UIEenp6XnO5ZdfPqg6i8lkoqioaOwLolgh2s+NovqO/lH0qRGnYifsTig6fijs7OyYO3cuwcHBbNy4kYbNr+P71jlEZ/8JAXDxy3DLZiXq1YZ/SMeKwWBg+/btCCGYP3++OkqfRtiiG34ofHx8WLhwIfv376e0tJTrUq6jsqNyzIWnALJm+XHrihje3FHOJ3tsq+QsgJOTE8nJyew6XIM872mo2QNfPzDVZo0ZrVZLTEwMhw5Z9zg8/fTTvoGBgc9OslnTHptVj8DAwCcff/xxX2sjheLiYkJDQ8elVni0vyvteiMNHcoTo6ejJ1khWawrWYdZTkwlqpCQEOYlReHz5e1oNSAvelER9JQLZ5SgA3R2drJ582ZCQkJITEy0mQAslZGRUtLQ0DDsKom2hrOzM1lZWTQ0NODd7E20Z/SoF4c5ljtOjSMt3It7bbDkLCgleD09PTmkiYX5P4WtT0PB2B9ippqwsDAaGhqspgenp6eTnp4eo9VqV06BadMWm1QRIURKSEhI1urVqwepgMFgoLy8nOjo6HE5V19kfGH9kcja1ZGrqe6sZk/9nnE5hzVq9v6ABjN16XeyuS2I7h7byp0dD+rr69m+fTupqamEhoZOtTkqY6SlpQUPDw+0Wu1UmzImtFot6enpuLq4ssRxCfnN+Wyu2jzmfuy1Gp68LA0k/OLNXRhtrOQsQEJCAnV1dTRm/BJ0yUqNi/bRp9jaAkII4uPjOXjwoNX9TzzxhI+/v/8zQh0VjBqbFPagoKC/P/bYY1ZLxx46dIjo6Ohx+7E5Ehl/ZJ59ZdhKHLWOfF58YjntQ1FdXY22WQkYCU87hfj4eLZu3Up19fSsAX0sUkqKiorIz89n0aJFk1aGVGV8mU5u+GMRQhAbG8tlqZfhpfXi+d3PH1c/YT4u/OXC2eSUtfDEN7YXoKbRaEhPT2fP/nwM5z8PvZ1KvQuz7T2EDEdAQACdnZ1WM4dmzZrFihUrAjQazelTYNq0xOaEXQgxy9/fP33p0qWD9un1eurq6ggLCxu38wV7OuNkr+lPeQNwc3BjWegyvij5AtM412Tu7e3l4MGDhLnolXWWPcPw8/Nj8eLFlJWVsWfPnklb530iMJvN5Obm0tLSwqJFi3Bycppqk1SOAykl9fX10z7IMSw4jJ8k/oSchhx+yP/huPo4JzWYSzJD+ed3h9lS2DjOFp44Li4uxMTEsK/OCGc8DEXfw+Ynp9qsMSGEIDExkQMHrActP/DAA946ne5vk2zWtMXmhD0wMPDBBx980GpuTX5+PnFxceMaoavRCCJ9XSkaEBkPiju+Ud/IjtrxLdvYt1qZXXMx+MT0z6k7ODj0r2C2ceNG2tpsL4d2JHp6etiyZQvu7u6kpaVNOxeuyhHa2tpwdXWdEZ/hFbOvwM3ejZf2vsShQ4eOa779j+cmE+Xnyh1v7bK5krOgzFP39PRQF3qGkk3z7Z+hInuqzRoTvr6+SClpbm4etC8+Pp45c+aECCEWTYFp0w6bEnYhRLCbm9spZ5111iAfvF6vp6WlhaCgoHE/b4y/21EjdoBloctwsXMZ1+j46upqpJSKe7PxEPjFHrVfCEFUVBRpaWns2rWLkpISmyttORTt7e1s2bKF2NhYYmJi1CC5ac50dsMfi5uDG5clXMaujl0UtxSTk5ODeYyuahcHO568LI3mTgN3vbPH5r6XQghSU1PZt38/htV/B/cgePc60E+vAUJ8fDwFBdZX2XvooYd8g4KCHplkk6YlNiXsOp3u9w888IC3NVEoLCycMMGI9nelvLmbXuORL7uTnROnhJ/CV6VfYTCd+DrrfS742bNnK/mmzaWDhL0PDw8PFi9eTGtrKzt37rSa42lL9NmZnp4+7V23Kgq1tbUEBARMtRnjxhWJV2CvsWercSuenp7s2LFjzFNeKSGe3HNGAl8fqOW1rYNLoU41Tk5OzJo1i31FlXDRv6GlDD69c1qVnPXy8sJkMln1WKanpxMREREvhEiZAtOmFTYj7EIIbycnpwsvueSSQb6/3t5e6uvrJ2wEEe3visksKWs62h1/RtQZtPW2saV6ywmfY8+ePcTHx+Po6AhNxSBN4Gtd2EHJeU9NTSUkJIRNmzbR2Gh7c3ugRE7n5OQwb9684y7tq2JbtLe34+zsjJ3doBIS0xY/Zz/OnXUuHx7+EK8QL3Q63XGJ+7WLIzklQcf/fXqAA9W2NxoODQ1VXPJO0bDiXsj7n7Iq5DQiNjZ2yLz2hx9+2C8oKOivk2zStMNmhN3Pz++ue+65x9Paj0lxcTGRkZETVv2qL+XtcN3Rwr4oaBEeDh4nHB1fVaUUuOh/MGm03LR+IxfYCQ4OZsGCBRw8eJD8/HybcgE2NTWxe/du5s+fj7Va/irTk5nkhh/INcnXYDAb+M+B/xAVFUVQUBDbtm2zWqt8KIQQPHLxHDyd7bn9jV1099pWoGu/S37fPgwLfw4Ri+HTX0HDiS9sNVn4+fnR1dVFZ2fnoH3Lli3D19d3vhAiagpMmzbYhLALIVwdHByuu+666wZVnDEajVRVVY1rJPyxRPlZUt4ajp5nt9fac1rEaXxb9i16o/64+jYYDOTn5zNnzpwjG/vqOg8zYh+Ii4sLixYtQkrJ5s2bj2ud9/GmsbGRPXv2sGDBAlxdBy28pzKNqampITBw5q2YGeERwakRp/LWwbfoNHQSERFBWFgY27Zt6y/xPBp83Rx5/NK5FNZ38KdPbK/kbJ9Lfv/BfLjwBaXk7LvXgdG2p/T6EEIwa9YsDh8e/DAihODBBx/0CQwMfHAKTJs22ISwe3p6/uz22293d3QctNYLpaWlhIaGTmh0rruTPTp3x6Ny2ftYHbWaLmMXGyo3HFffBw8eJDo6+ugqeY2HwS0AnEbvutZoNCQkJNhEzntTUxN5eXksWLDghGv1q9gWnZ2dODg4zNiyv9elXEe7oZ13Ct4BlGjyyMhItm/fPqaR++JZfty8PIY3tpfxWZ7t1Z8IDQ2lo6ODFukK5/4TqnPhm+lTcjYwMJDm5mb0+sEDqttvv13T2Nh4iRBirxBi5xSYZ/NMubALIeycnJzu+NnPfjZIIcxmM2VlZURGRk64HdH+roMi4wHmBczD18n3uNzxbW1ttLa2Eh4efvSOhkPgF3dcdvblvJeXl5ObmzvpOe/Nzc39I3VV1GceM9UN30eKXwrzA+fz6v5X+4NiQ0JCCA8PZ/v27WP6Pt15WhypYV7c8+4eKpptq+SsEILZs2ezd+9eZMJZMO8G2PJPOPT1VJs2KoQQxMTEDLny2+OPP45Op/tWSpk5BebZPFMu7Pb29hdefPHFru7u7oP2lZeXExgYOCmjh2h/t0G57ABajZbTI09nfcV6Og2D9w+FlJK8vDxSUlKOjuSXEhoKwPf4F7BxcHDoD1abzJz31tZWcnNzmT9/virqM5SZ6oYfyHUp11HXVccnRZ/0bwsLCyMkJGRMAXX2Wg1PXZaGWcIdb+62uZKzHh4eeHl5UVZWBqf/H+iS4IObob12qk0bFSEhIdTW1lqdJjn//PO1dnZ2lwoh1ApYVphyYff19b3/zjvvHOSTllJSXFw8bjXhRyLaz5WWLoPV4hNnRJ1Bj6mH78q/G3V/FRUVuLu7Dy6n2tUI+pYhU91Gy7E578XFxRMaWNfW1kZOTg6ZmZm4uLhM2HlUpo7u7m40Gg3WpsRmElnBWcR7x7N239qjFnqKiIggICCA7OzsUee5h/u68OAFKewsbebJb20vQC0+Pp6ioiJ6pRYufgl62hVxnwYlZzUaDRERERQXFx+1XQjB2Wefjclk8rOzs3tuisyzaaZU2IUQs2NjY4OsiXdtbS0+Pj6T9iNjbTGYPlL9Uwl0DRx1sRqDwcDhw4dJSEgYvHOMgXMj4eHhwZIlS2hra2PHjh0TkvPe3d1NdnY2mZmZavT7BGIymdDr9XR3d9PZ2UlHRwft7e10dHTQ1dVFd3c3PT09E/YAN9Pd8H0IIbg25VqKWov4ofzoMrNRUVH4+Piwa9euUV/n8+aGcHFGKP/89hBbi2wrLdXe3p5Zs2YpC6zoEmH1Q1D4reKWnwZERERQWVl51IPWxo0bycnJ4auvvtJIKS8TQiybQhNtkilNVA0KCrr//vvvt7omZHFxMSkpk1eHoE/Yi+o7mBfpc9Q+jdCwOnI1rx94ndaeVjwdPYftKz8/f3DAXB9jSHUbLVqtltTUVKqqqti0aROzZ88et6U2jUYjO3bsIDU1FWvTJSqjw2Qy0d7eTmdnJ3q9vv/V09PT/zCm0WhwcHBACIEQoj+9U0rZ/zKZTP3thRA4OTnh6OiIk5NT/8vd3R0XF5cxF3Oqrq4mM/PkmLJcFbmKp3Y9xUt7X2Jl+NErgs6aNYs9e/Zw+PBhYmNH9wD+wLnJZJc288u3dvPZz5fi7XriS0qPF6GhoZSVldHS0oJXxrWKsH/zAEQuhpCMqTZvWLRaLTqdjqqqqv4VIkNCQgCYPXs2UVFRpsOHD68B1k+hmTbHlAm7EMIrIiLilFNPPXXQvvb2dqSUkyokId7OONhprEbGg+KOX7tvLV+Xfs1FcRcN2U97ezvNzc0kJydbb9BwCLQO4BUxHmYfRXBwMN7e3uTk5NDQ0HDCdfWllOzevZvIyEh8fHxGPkAFoL9yVktLC62trbS2tgKKd8XV1bVffPuE2N7e/rgqKprNZnp6eo56UGhubqa0tJSuri4cHR3x9PTEy8sLLy+vYcW+L/r4ZFm0x05jx1VJV/HQ9ofYVbeLNF3aUftTUlLYunUr7u7uo4o5cHW046nL07jgmU3c/e4enrsyw2bKKvcF0uXl5ZGVlYU450moXArvXA83bwBH235gj4qKIicnh9DQUDo7OzGbzbi7u9PZ2YmTk5Ozl5eXWj/+GKZM2D08PK772c9+5mZNeCZzbr0PrUYQ6etC4RDCnuiTSIRHBJ+XfD6ssB84cICkpKShv9SNh8EnGjQTk77n7OxMVlYWBQUFbNmyhbS0tOOeEy8oKMDJyWlwVL/KUZhMJhoaGqipqaGlpQU4ErgUERExYWuaazQanJ2dhwxk1Ov1tLa20tLSQkVFBV1dXTg4OODv709gYCDu7u7992l1dfWErMNgy5w/63z+lfsvXsp7iad+9NRR+zQaDZmZmWzevBkXF5dRVVVMCfHk7tUJ/N+nB3h9WxlXLhz/h/fjxcPDAxcXF2pra5UHlYtegLVnwae/hgtte5raxcUFBwcHWlpaaGpq4oILLgAUb+Lll1/O2rVrI4QQflLKhik21WaYEmEXQoiAgIDbr7/++kHDA4PBQGNjo1JTfZKJ9nOjoG7wesCgPPWujlzNC3kv0NDdgJ/zYFd3c3MzZrMZX1+ri9MpNBwCnZW593FECEF8fDx+fn5s27aN+Pj4Mc+dVlVV0dTUxIIFCybIyulNT08PNTU11NbW0tXVhZ+fHyEhIaSkpNjMimh9HoGBNd/1ej319fXk5+fT0dGBn58fAQEBVFVVkZaWNkxvMw8Xexd+nPBjnsl9hsPNh5nlffT0mIODA+np6eTk5JCVlWV9au0YrlscxcbDDfz5k/3Mi/QmIdB2yiwnJCSwfft2AgICEBFZsPxu+P4hiFkJqZdNtXnDEhUVRXFxMWlpaeTm5h61z9PT0+P3v//9zcD/TY11tsdUBc9lLVq0yMOae7eyspLQ0NApcWNF+7tS1tiFYYi0lTOizsAszXxZ8uWgfVJK9u/fT2Ji4tAnMBmguXjcAudGwtfXl8WLF1NRUUFubu6oC3C0tbVRUFBAZmbmhJXxnY50dHRQUFDAhg0b+gMVExMTWb58OSkpKfj5+dmMqA+Fk5MTYWFhzJs3j+XLl/eLenNzM/v27aO8vHxMVdimO5cnXI6znTNr9621ut/Dw4OEhAR27tw5qkh5jUbw6JpUPJzs+bmNlZx1dnbGz8+P8vJyZcPSX0N4llJytrFwao0bAT8/P1pbW60GB1999dUOjo6ONwkh1B8rC1NyIYKDg3/761//epCqSykpKyubMtdvtL8bRrOkvMl6sYkYrxhivWNZVzI4Or6+vh4nJyc8PYcJrGsuAbPxhFPdxkJfzrunpyebNm0aMee9p6eHnJwcMjIyZmz1sbFgMpkoLy9n06ZN5OXl4eTkxPz581myZAmxsbFHubOnGxqNBp1Oh7e3N3FxccTFxdHV1cXGjRvZvXs3zc3NNrU2wUTg5eTFBbMu4NPiT6nprLHaJjAwEH9/f/bt2zeqPv3cHHns0lQKajv4v09tq+RsbGwshYWFSq6+1g4ufB40dvDu9TZdclYIQVhY2JGHkgF4eHhwyimnuAIrBx95cjLpwi6E8HJ0dJyflZU1aF9LSwsuLi5Tlkcb7a/UPB9qnh3gjMgz2FW3i+qOI2UkpZQcPHjQenrbQMY51W20CCGIjIwcMefdbDazc+dOEhMTT/oI+M7OTvbu3cv69evp6OggLS2NRYsWER4ePuPyvKurqwkODsbT05P4+HhWrFhBSEgIhYWFbNiwgdLS0kmvcDiZXJV8FVJKXtv/2pBtZs2aRW9vL6Wlo1uudWmsPzctj+Y/28pYt9d2Ss46ODgQEhJCSUmJssErDM59Cqp2wbd/nlLbRqJP2K39dt15553eISEh90yBWTbJpAu7i4vLpddff72rtVFOSUnJpJSPHYoYvyMpb0OxOnI1AF+UfNG/rbKyEm9v75EXQ5mAVLex0Jfz3t7ezvbt2we5tfLy8ggICJhR63CPBSklDQ0NbNu2jd27d+Pj48Py5ctJTEycsUV5DAYDPT09R9UnEELg7+9PZmYmCxYsQK/Xs379evbv328TCxCNNyFuIayOWs07Be/Q2tNqtY0Qgrlz51JWVjbqJZR/dVo8qaGe3PXOHipbbOe6RUdHU1ZWdmTKJelcyLwONj8Jh7+ZWuOGwcHBAQ8PD5qamgbts3gY5wohbCeoYQqZdGH39PS87aqrrhoUxmswGGhtbR0+8GyC8XSxx8/NYciUN4AwjzBSfFP4vESpHW82mzl8+DBxcaOo/d5wCFz8wNl7vEweM1qtljlz5hAeHs6mTZtoaFACSYuLizGZTMTExEyZbVNJY2MjmzZtorS0lPj4eBYvXkxwcPCMjzEYqYSso6Mj8fHxLF++HHd3d7Zv305eXh49PT2TaOXEc23ytXQZu3g7/+0h22i1WjIzM9mzZw9dXSPXhnew0/Dk5UrJ2V/aUMlZOzs7IiMjKSwcMK++6i/gnwjv3wwddVNn3AhERkYe8TYMQAjB1Vdf7eLk5HTx5Ftle0zqr5YQIiwgICDA2hKsfVWvpnq+MtrPbdDyrceyOmo1+xv3U9pWSmVlJf7+/qNzzzYentT59eEICgpi4cKF5Ofns3v3bsrLy0lNTZ3y6z/ZtLW1sW3bNgoLC0lNTSUjI2NwGeAZzGjT3DQaDWFhYSxbtgxvb2+2bNnCwYMHZ0ygXbxPPItDFvP6gdeHXaLZ2dmZ1NRUcnJyRhV/EOHryv+dn8L2kib++Z3tlJyNiIigurr6yOdn72wpOdsGH9xisyVnvb29aW9vt3rfXX311S4+Pj63TYFZNsekCru3t/e1t9xyi9XhakVFRX9loalEWeVt+MVeVkWuAmBd8TqKiopGP8ptOGQzwg7Kj9TChQupq6vrL3ZystDV1UVOTg55eXnExsYyf/78ky6uwGg00tXVNaoc7T6EEISGhrJs2TIcHBzYuHEjRUVFM2IO/vqU62nSN/FR4UfDtvPx8cHHx8fqymPWOD8thAvTQ3jym0NsLx7sRp4KNBoN4eHhR8cMBCTBqgfh8New9ZmpM24YhBAEBQVRUzM40DEqKgpfX99QIcTJVZDBCpMq7A4ODtdecsklg3Lnu7u7kVLaxDxmtL8rjZ29tHQNHSEa6BpIui6djw99jKen5+iqdXU1QVfDpAfOjcThw4eJiIhgzpw5bN++naqqqqk2aULp6ekhLy+PHTt2EBISQlZW1klbVa+2tva44yk0Gg3R0dEsXboUg8HA+vXrhwxsmi5kBmQy2282a/etxWQe/kElPj6eiooKOjqG9+718afzUgj3ceGON3cN+9symURERFBeXn70Q1nm9ZBwNnz9R0wV2aSlpXH22WdPnZFWCA0NpaKiwuq+m266ycvLy+vqSTbJ5pg0YRdCzElJSXGz5ubsy123BaL9+haDGX7UfkbUGZR2liJ0o3RdN1rccDY0Ym9tbaWuro7Y2Fh8fHxYvHgxlZWV7N69e9Q579OJyspKNm/ejJeXF8uWLVMKdZxkUw8D6YuGPxHs7OyIj48nKyuL5uZmNm/eTGfn6Jc3tiX6Focpby/n67Lh1y3vi1XZvXv3qB5m3BzteOrydOo7erjn3TybeACys7MjODj46BQyIZQoeTcdbS9dTFqS7fxe9eHq6orRaOwvgzyQyy67zN7JyenGKTDLppg0YdfpdDffeuutViPjKisrbWZVqRjdyJHxABnuGWjQ8EPND8O262eKUt2Gwmw2k5ubS2pqan+AmL29PZmZmXh7e7Np06b+GufTnZ6eHnbs2EFNTQ2LFy8mLCzspBZ0UPLzOzo6xuSGHw5HR0fmzJlDQkICO3bsmPBlhCeKU8JOIcIjgpf2vjSi/d7e3vj4+BwdhDYMs0M9uWtVAuv21fDf7WXjYe4JExUVRUlJydHFd1x8qFv6IB6mJh5cYhvehWMJCQmhsrJy0HZfX1/i4uI8hBDDVAqb+UyKsAshNEKIC84666z/Z++8w9o6zP3/ORoIsZfE3mCMB3hgbOMRZ9tp0mYnbdMmcZruka5729vb+WtvOpI2nUlHmjRJm51mtXFGY8c2noDBxmwMmA1iDwk0zu8PIcKQQAKNI8ef58njPBrnvAhx3vOu7zvvajo8PExgYKBTco3eIDlSjVIucE63cNShO6+jQFvAG01vOHcB66u3CkFESkM/ur6+nri4uHkXdkEQSE1NZcOGDVRUVHDu3Dm/vEDb6Ojo4MiRIyQlJbFx40bJfM98TU9PDxqNxu03ONHR0Wzfvp2xsTGOHj3qVPe4lJDL5Ny1+i6q+qo40XVi0dfn5OTQ3t7OyIh9Keq53LM9nZ0rNPzotSrqup17jyex7Q6YW4L7/M/+TnfOJ4nv3s+uKOl1yTty7ABf+MIXorRa7We8bJKk8FbEfsnll1+ustc53tbWhr0ueV+hkMtIiQpaMGIfHBxEJpNxbda1tI22cbbPCUUqXT1EpoPc92puthR8VpbjefrQ0FC2bdvG6OgoJ06c8LvGOluU3tnZybZt2z5wC04Ww5NLXxQKBWvWrCEnJ4cTJ074XfR+XeZ1RAdG89fKvy76WtvK5IqKCqd+RplM4MFb8gkNVPClf5zCYPR902FGRgaNjY3T9r/++utotVoSbvsVQ2G5fD61AfqdaxT0FiqVioCAALs3VNddd51MEIRbhA9wWs4rjj0hIeFz995777xueFEUl9XA4ykyNCELdsY3NjaSlZXF5amXo5ApeKPpjcUP2tcAMU7MunsYeyl4R9jqiKmpqRw5coTe3l4vWbk8uru7L0bpC2CxWBgaGiIy0rN6CnOjd3s1USmikqu4Y9UdHOk4QnVf9aKvj4iIIDo62umUvCZUxYO3rqO2e4Sf/Gvx43satVpNeHj49N93cXExr776KmmZWVz+h3NMGE00/vxSyUnOOmqiU6vVbN++XQVs8b5V0sDjjl0QBJnFYtm5Y8eOec/19fUREREhucUZGZpgWvrGMVvm34EbDAbGxsaIiooiLCCM7Ynb2de8D4u4wNynxWy94/WR4txMHKXgFyIuLo4tW7ZQX19PdXW1U8swfIEoitTX19PY2EhRUdHFKN0Bvb29xMTEeKXPwBa9Z2dnc+zYsem1tlLn1pxbCVYG81jlY069fsWKFS6l5C9ZoeHTOzN48lgLb561r1HvTWzb0wDuv/9+2traaG5u5oG/PMcj7blkBg7C/p/41sg5xMXF0dXVZTdT8olPfCJaq9V+3AdmSQJvROwbt27dKrfnvKXUDT+TzJgQJs0W2gbm1wdbWlpIS0ubvijuSdtDz3gPp3pOOT7gYAuYJ33eOOdMCt4RarWarVu3IpfLOXLkiORqp2azmbKyMvR6PVu2bLng9NzdiTu64V1Fo9GwadMmKioqHNZGpURYQBi3rriVN1vepG3E/mjVTFxNyQN846oc1iZaJWc7fCw5Gx4ejslksjvRUDyggY13QfFD0Piu121zhEKhICwsjIGBgXnPXXHFFchksut8YJYk8Lhj12g0H/voRz86rxteFEX6+/t9KiHriPeXwcyus1ssFjo6OkhMTJx+bFfyLgLlgQun420d8T4cdRNFkdOnTzuVgneEIAisWLGCVatWceLECclcoPV6PUeOHCE6Opq8vLwLXgZ2OVgsFgYGBnwyux8cHExRURFtbW1UV1dLvu7+8dyPIxNk/O3s35x6vS0lb4t8F8MmOWsyW7jv2XK7GUJvYk+uddeuXbz++utw9f0QkzMlOSudkpwjsZrg4GAyMzPVgiB8IDWyPX4FlMvlH9m9e/e8nN/Q0BBhYWGSvAhnamwjb7PvXru6utBqtbNKB0HKIC5JvoS3W97GZHEw+y2BUbeOjg7Cw8PdMt5km3nv7Ozk1KlTPp15HxgY4NixY6xatcqnC4T8hb6+PqKionw27qdUKiksLEQURU6cOCFpSdrY4Fiuy7iOlxtept/gnGJcdnY2LS0tTv9c6THB/L/r13CiqZ/f+1hyNj4+np6eHvsqggFBVslZ/aCkJGe1Wq3D3p877rgjMiws7CYvmyQJPOpVBUFITUlJCbEn1bnY8glfEhkcQGSQcp5IjaPtc3vS9tBv6Hc8HtNXb138Euyb7ITFYqG+vp6cnBy3HVOpVLJx40aioqI4fPiwT2beW1tbOXPmDJs3b5Zk5keKeLIb3lkEQWDVqlUkJiZKXtDmrjV3YTAbeLrmaadeb3fByiLcuCGJG9Yn8tA7dZQ0+05yViaTERcX51h9Mm7NlOTs23D8Ee8a5wCFQkFAQIDd79CHP/xhRUhIyB0+MMvneNSxBwcH3/jxj388wt5z3d3daLVaT55+WVg7499PxdukI+2tZt2etJ0QZYjjdLyuwafRektLC3FxcW6vO9tm3jdu3EhFRcWskRlPc+7cOdrb2ykqKpKEFLE/YFtLGxMT42tTAGtXs03K2NmmM2+TEZ7BpcmX8nTN04wbnesrSU1Npaury6UR0R99ZDXJUUF85ZlyhsZ9l8VITU1deOf8pk9BzjXw9vego9xrdi2ErYluLgkJCYSGhsYJguC7dZo+wqOOPTw8/BPXX3/9vMFtvV6PUqlEqfT9TLcjMmKCZ4nU2Jrm7KGSq7gs5TL+0/IfJs12RkL66n026mYymWhubvboOlbbzPv4+LhXZt4bGhrQ6XQUFhaiUMxbPXARB/T39xMZGSmp8ldkZCQbN26kpKSE4eFhX5tjl71r9jI0McRL9S859XqZTEZWVha1tbVOnyM0UMlvbl9P97CBb7102mf9B0FBQSgUCse/C0GAj/wegjXw4j0w4ZxWvieJi4uju7vb7nO33HJLkFwu3+Nlk3yOx/7CBUEICwoKSkpJSZn3nJTT8DYyNCH0jkwwYjAiiiI9PT0L2rwnfQ8jxhGK24tnP2EYgtFun426NTY2kpKS4vGbKLlcztq1az0+815bW8vg4CAFBQWSclD+gC+64Z0hLCyMgoICSktLJSljvE67jg3aDTxR9QRGi3PRdGJiIoODgy6VGfKTI/jm1Tm8UdnFMydbF3+Dh0hJSZmtHz+XoCi48U/Q1whv/Lf3DHOAWq3GZDLZ7Wu4+eabg+Pj4+/yvlW+xZOO/eobb7xRbe85/3Ds1pT7ud4xent7iY6OXtCRbI7fTIQqgjea56TjdVMNMT5IxU9OTtLR0eHVprK4uDi2bt1KfX09VVVVbp15r6+vZ3R0lI0bN1506i4iiuL0/LoUCQ0NZdOmTZSVlUkyct+7Zi+dY53sa9rn1OsFQWDlypXU1NS4dJ57d2SwIzuGH752lnofSc7GxsbS09OzcNYgfQfs/AaUPwVnXvCecQ7QarX09MyXvs3Ly0MUxXxBEKSbHvYAHrs6JiYm3nXzzTeHzH3caDQyOTkp+bpo5oyRN2d2xStlSq5MvZIDrQdm1+L6fDfqVldXR1ZWltcFgAIDA9m6dSsKhYLi4mK3NEc1NjYyMDDA+vXrP/ALXJbC4OAgYWFhkhODmklISMh05O7sOlRvsSNpB1kRWTx29jGn0+QajYaJiQmXshAymcCDt+YTHKDgS0/7RnJWLpcTGRmJTqdb+IWXfAuSCuH1r0K/cyN+nsJRnV0QBK644golsN37VvkOjzh2QRAEk8m0YePGjfOe6+3tRaPReOK0biUlKhi5TKChe4Th4WGn5Df3pO9Bb9JzsP3g+w/q6kGQW3Xivcj4+Dh9fX0+EwCyzbyvXr2akydPOtyf7AzNzc3odLqL6fdl0NHR4fNueGcIDQ1l48aNnDx5UlIiSDJBxt1r7qZ+oJ5D7Yeceo8gCOTm5lJdPV821mAwUFhYSH5+PqtXr+b73//+9HPa0EAeuDWfmq4R7v+3byRnF9p5Po1cATf9BRDgxU+B2XdNf+Hh4QwPD9vNEF5//fWRGo3mwz4wy2d46iqZmZOTI7d3Ee7u7pZ8Gh6s4hEpUUFUtfU5vbd7g3YDGrVmdrqur9660U3hXb3ympoacnJyfB7d2mbeu7q6ljTz3tPTQ1tb20WnvgxsaXgpT6HMJCwsjHXr1nHy5ElJzbnvSd9DXHCc0zKzYG0OlMvl86JflUrFu+++S0VFBeXl5ezbt49jx45NP39pjpZPbU/nb0dbeLvKfmOYJ4mOjmZwcND+TPtMIlPhw7+G9hLY/3/eMc4OgiAQGRlpV4Vu586dKBSK3T4wy2d45EqpUqku//CHPxxu77nBwUEiIiI8cVq3kxETzLneUaejXrlMztVpV3Oo7RAjk1P1MR+Mug0PD6PX6yWzXMc28x4dHc3hw4ed1gsfHR3l7NmzFBQUSDqFLHWGh4cJDg72qwmCyMhIMjMzKSsrk4xCnVKm5BO5n6Cku4TTvaedfp8tap/5cwiCQEiItVJpNBoxGo3zbsK/uTuHNYlhfPOFCrqGvLtARxAEYmNjHXabz2L1DbDhk3D4V3DugMdtc4RGo7FbPoiKiiIoKChaEIT5s8oXKB5x7BqN5obLL798Xog6Pj5OYGCg30ReqVGBdI6aCQ6e1yrgkN3pu5m0TLK/db9Vnam/0ev19draWlauXOnzaH0mgiCQkpJCQUEBp0+fXnTm3Wg0Ulpayvr16wkMDPSipRceUu2GX4ykpCRCQ0NdbkDzJDevuJmwgDCnVrraCAkJITQ0dJ6TNJvNrFu3Dq1Wy5VXXsnmzZtnPa9SyPnN7euZNFm479lTXpecTUpKWrg7fia7f2q9zr30GRhbpDbvIaKjox32BVx22WUKYKt3LfIdbvewU/X1dWvXrp33XF9fn2S7cu0RqTBitEC7Cwsa8mLySAhOsIrVDLWCyeBVxz4+Ps7ExIRkldhCQkLYtm0ber2e48eP2515F0WRsrIysrKy/Ca7I2WkLga1ELm5uQwPD0tmL0GQMojbV97Ou+ffpWnI+YaxzMxMzp2bvdNcLpdTXl5OW1sbJ06coLKyct77MjQh/Ogjazh2rp+HD3hXcjYsLAyDwcDkpBPrWgOCpyRn++Hlz4MPsiyBgYEYjUa75YNrrrkmUqvVXut1o3yEJ0LnzJUrV8rsReVSUr1yhiCzNZ0+dxnMQgiCwO703RzrOMZA59TGNy+m4puamkhP926jnqvI5XLWrFlDeno6R44cmTemUl1dTVhY2KxlOxdZGiMjIwQGBkpaDGohBEFgw4YNNDQ0SGbl68dWfowAeYDTy2HA2hQoCILdUb6IiAguvfRS9u2zP0p304ZEPrIugV+9U09pi3clZ+Pi4uyOkdl/8Vq46sdQ/yYc/6NnDXNAZGSk3e/Jzp07kcvlV3vfIt/gdseuUqkuv+666xzW18PD7T4lOYxGI9pA613n3GUwi7EnfQ8m0cTb59+xPuCliN1kMtHT0+MX3c9gnZfdunUrDQ0NnD17FovFQltbG6Ojo6xcudLX5l0Q+Es3/ELYejROnTqFweDdWrM9otXRXJ91Pa82vkrvuPNCTBkZGdNRe29v77QD0uv1vP322w6/84Ig8OPr15AQEciXny5nSO+9hkJHY2QOKfw0rNgNb38XOp3vQ3AXMTExDuvswcHBH5g6u9sdu1arvfFCqK/39PSQlRRLWKCCczrXZmpzInNID09nX99pUIVb5Re9QGtrK4mJiX7zGcP7M+8BAQEcPHiQurq6i7PqbsRfplAWIyQkhNWrV0umme7OVXdiFs08Vf2U0+/RarUMDg4yOTlJZ2cnl156KXl5eWzatIkrr7ySa691nCmeKTn7Py+d8dpnEBYWxsjIiPNCU4IAH/kDqKPghb0w6d0FP4vU2ZV8QOrsbvUAgiAIRqMxz1593d/S8F1dXcTHx08tg3HtyykIAnvS9lBiGqAnJt36ZfcwoiguqGcvZQRBICvLKrlrsVic68S9yKKMjY2hVCoJCPDuqKWn0Gq1hIaGztsZ7guSw5K5MvVKnqt97v0JmEWwLU1qaWkhLy+PU6dOcfr0aSorK/ne97636PvXp0Ty9aty+NeZTp4r8Y7krCAIREdH09fX5/ybgqOnJGcbvC45u0idPeKDUmd3d2iXmZuba7e+7k+NcxaLheHhYcLDw8nQBLvs2AGuTr8aEXgr1DulB51OR3h4uN9exBsbG4mNjeWSSy6hu7ubsrIyn+55vxDw1274hcjNzaWlpUUS4jV71+xl1DjK83XPO/2e5ORk2tralhxxf2ZnBtuzYvjBq1U09HhHctbldDxAxiWw42tw6kmofNEzhjnAUZ19x44dyOXyD8Q8u1sdu1wu33b11Vf7fX29v7+fqKgoBEEgUxNC17CBsQnXnExGoJaVE5O8gXekMf01Wgdrg1d7ezsrVqyYrqdqNBqXZt4vMp/Ozs4LIg0/E4VCwdq1aykvL/d5Sn5V9Cq2xG/hqaqn7G91tINCoSAqKmrJS5JkMoFf3pqPOkDOl54u94rkrC297fLnvevbkLQJXrsPBpo9YZpdFqqzq1SqKEEQ/DP6cQG3Ova4uLjLCwsL5y391uv1flVf7+7unhZ3yYix9lo06VyM2vsa2D02xumJXtpGli6n6gwTExOMjY355WiYKIpUVFSQn58/S4QmOTmZgoICzpw5Q0NDg88v4v6GXq9HJpOhUs37c/R7oqOjCQsLk0RKfu+avfTqe3n93OtOv2fRneeLoA0L5MFb8qnuHOanb3h+xl8ulxMSEsLIiIsZArlySnIWr0rOLlQ6WLduHcBqrxjiQ9zqaS0WS+GGDRvmPe5PanMwW88+Q2MVp3Fl5A0AXT27x6zpwjeb33SrfXNpa2sjOTnZLxvOGhsbiY6Otvv9sM28T0xMcOzYMUl0RPsLF0I3/EKsXLmSlpYWtywYWg5b4reQG5XLY5WPYRGdazCLiIhAr9cv6/t86Uote7el8/iRZt7xguRsbGys6+l4gMg0uO4haDsJB37qbrPsEhgYyMTEhN1gYOfOnREKhaLAK4b4ELc5dkEQ5AqFIspeut2fHLterycgIGA6ekyNDkImQKOrdfa+ehJNFvKi17Kv2blVj0tBFEVaW1t9tuxlOdhS8Dk5OQ5fI5PJWL16NZmZmRw9etT5mdoPOLbmzwsVW0q+oqLCp9kcQRDYu2YvzcPN7D+/3+n3Lbrz3An+e08Oq+KtkrPdw5696XUk1+oUa26C9XfAoQeh6eDir3cDQUFBdvswNm3apIyNjb3CK0b4EHdG7CtWr7af4RgaGvIbxz63yS9QKScpMohzS4jYiUhhT8Y11PTXcG7o3OLvWQL9/f2Ehob6ZdPcmTNnyMvLc6pEo9Vq2bp1K42NjdMz7xexj8FgQBRF1Gq1r03xKNHR0YSGhi5rc6A7uCL1CpJCkvhr5V+dvslITEykvb19WTclKoWc335sPQajhfueKfeo5KxarWZycnLpf3d7fg7RWfDSp2HMhQ77JRIREWG3P2fdunWYzeb5a0cvMNwZsW/cuXNn6NzHRVGcrrH7A/bG8pbUGd9XDzHZXJV2FQICbzZ5Jh3f3t5OcnKyR47tSXp6elCpVE6tw7URGBjIli1bUKlUFBcXS25nt6tYLBaGhoZoaWnh7NmzlJaWUlxczIEDB+z+995773Hs2DHKy8upra2ls7MTvV4/zzlc6NH6TFasWEFjY6NPb/QUMgV3rr6T07rTlHaXOvUepVJJaGioS7va7ZGpCeGHH1nN0XN9PPJe47KOtRiOnKVTBATDzY/CeB+88gWPS846sjUkJASVShUmCIJ/SjE6idvWPcXHx1++efPmed7bYDAQGBjoN/XfwcFB8vLyZj2WERPC8XP9WCwiMpkTP4fFAn2NkLYDbZCWgrgC3mh+g8/mf9atn4MoivT19bFmzRq3HdMbiKJITU0NGze6fuNsm3mPjo6mpKSEzMxMv7mxEUWR/v5+urq66Ovrw2KxEBoaSkREBBqNhsDAwGn5V3vfE4vFwsTEBAaDAb1ez+DgIM3NzRgMBtRqNVqtlri4ODo6OmxNQhc8KpWK+Ph4mpubycjImPVca2srn/zkJ+nu7kYQBD796U/zla98xSN2XJ91PQ9XPMxfK/9KQZxzJVxb3Xq52cxbNiZxqF7HL9+uY2tmNBtSnL9ZdgVbt3lUVNTSDhCfD1f+CPZ9C078GTZ/2r0GziA8PJzGRvs3Ovn5+bS0tKwCKjxmgI9xW8QuiuJmf2+cs9XX56aGMzTB6I1mupytY410gHHcmnoCdqftpmmoibqBOrfaOzIyQkhIiN9MG9jo6OggIiKC4OClqztGRkaybds2ent7KS0tldTe7pmIojg9l3/gwAFaW1uJjo6mqKiIXbt2sXHjRjIzM9FqtYSFhREQEODw5k8mk6FWq4mMjCQhIYHc3Fy2bt3Krl27yMvLQxAETp06RX9/Py0tLX6f0XCWzMxMWlpa5ukeKBQKHnzwQaqqqjh27Bi///3vqaqq8ogNgYpAPrbyYxxqP+T033lsbKxbekYEQeAnN6whPjyQLz99imGDZ/4WFlJ1c5rNn4Xsq+Gt/4WuM+4xzA4f9AY6t3gEQRBkCoUi2p4DHxoa8pv5dUciOhkaqwNyujNeV2/9d0oj/srUK1EICv7d9G+32GnDH+eULRYL9fX1rFixYtnHUiqVbNiwAa1WS3FxMQMDA26w0D1MTExQV1fHgQMH6O7uJj09nV27drFu3Tri4uLcuhtdEASCgoJIT08nKSmJrKwswsLCOH36NMXFxXR2dl7Q44IKhYLU1NR5EVp8fDy2YCM0NJTc3FyPbom7feXtqBVqHq983KnXK5VKFAoFer3z2yMdERao5DcfXU/nkOckZ5ddZwerCuf1fwB1hMclZ4OCgux+toWFhcq4uLgLuoHOXaHeitzcXLtP+FPE7kj2NnNq5M3pOrvNsU9tdYsMjGRLwhb2Ne1z6x9cT0/P9Ly9v9DS0kJsbKxbey5sM++VlZU+n3mfnJyksrKSo0ePEhAQwI4dO8jLyyMyMtIr5ajOzk6SkpJITEykqKiI/Px8dDod77333rIUz6ROWloanZ2ddtcAAzQ3N3Pq1Kl5O8/dSbgqnJuyb+KNpjfoHO106j2xsbFuk1DekBLJ165cweunO3m+1DMNhcuqs9sIjrFKzurqYd+33WKXPcLDw+3aun79+gu+gc5djn39jh07wuw9odfr/aY719FNiDZURYhK4XxnfF89BIRA6PvR9J70PXSMdXBa556NRwaDAZlM5lfd8CaTiebm5mldeHfi65l3k8lEbW0txcXFhIeHc8kll5CWlubWyHwxjEYjExMThISETD8WEhLC2rVr2bp1KwMDAxw6dIienp4LzsHLZDKysrKoq5ufBh8dHeWmm27ioYceIizM7mXKbdy5+k4Anqh6wqnXL0mudQE+e0kmRZnRfP+Vs65rbziBI1U3l8nYBdvvg7K/wdl/Lv94dliogU6pVEYIgiCf/64LA7c4do1Gs3Ht2rV2G+dUKpVfNM4ZjUYUCoXderUgCNbOeGfV53T11vr6jJ/70uRLCZAFsK/JPTPtM9Xx/IWmpiZSUlI8tht87sy7t5bJdHV1cejQIRQKBTt37vSZWNBCm9xUKhVr166loKCA1tZWjh8/7pYUsJRITExkYGBg1s9lNBq56aab+PjHP86NN97ocRviguO4JuMaXqx/kUHD4KKvDw4OxmAwuG0vglwm8Kvb1hGolPGlf5xiwuReydnIyEj3lbwu/Q4kboRXvwKD591zzBlEREQ4nDpIT08XAf/oul0CbnHsgYGB+fZqpqOjo4SGzpuAkySLadlnxLgw8tbXMG8He2hAKDuSdvBm85uYLcv/Y+vq6vKr+rpt13pqaqrHz6XVaikqKqKpqYnKykqPjUIZjUbKyso4f/48RUVFZGZmzpLF9TbOqM0FBQVNN+wdO3aM8+fPXzDRuyAIpKen09TUBFgbF++55x5yc3P52te+5jU77lp9F3qTnmdqn3Hq9Vqtdsna8faIDQvkgVvyqeoc5mdv1LrtuOBY+GVJyJVw06MgWqYkZ9279EmlUjkszeTl5amA5Tf6SBS3OHaj0Zg5d9QErI59ZlpQyizWC5ChCaF9UI9+chGnPDkOQ60QM/87szt9N736Xsp6ypZlq9lsRq/X+81nC9YbEY1G47XUtEqlYvPmzQQGBnL48GG3d4jrdDoOHz6MVqtl06ZNPtdkN5lMjI+PO30jrdFo2L59OwMDA5w4cYLJSeeWmEidxMREuru7MZvNFBcX8+STT/Luu++ybt061q1bx7//7d4GVntkR2azM2kn/6j+B3rT4lkRd6fjAS7PjeWuojT+WtzEuzXuy1wJgkBAQIBDh+kyUelWydnW4/Dez9xzzCkEQUAmk9ld4ZqXlxemUqnsN4ZdACzbsQuCICgUimB7F7axsbFljTR5k8W6922d8Ysug+mf6syNnl9H3pm4E7VCzRtNbyzZTpitZe8vnDt3bt6csaexzbzn5eVRUlLitui0ubmZ6upqtmzZQlJSkiRKTbZGSldsUSqV5Ofnk5KSwpEjR1xf8iFBZDIZCQkJtLW1sX37dkRR5PTp05SXl1NeXs4111zjFTv2rtnLwMQArzS8suhrbeltd2dOvrVnJbnxYXzj+dP0uFFydqEU95JYezOs+zgc/AU0HXLfcbGWOuztE8jJyRE0Gs0FO/Lmjog91tHOZ3+K2BcrG2TEOLkMRjfVvDMnFQ8QpAxiV/Iu3m55G6Nl6bOm/paGHxoaQqlUEhQU5JPzR0REsH37dnQ6HWVlZUueebdYLFRUVNDX10dRUZGkmkKXs/TFNhZWWlrqtb4ET5KWlkZLS4tPSwwbtBvI0+Tx+NnHMVkWTjELguDe2vUUgUo5v/3oevSTZr76XDkWN0nOuqUzfi57fg5RGVbJ2fF+tx02JCTEbrZuqnS8ym0nkhjucOwr1q5daze/6i8d8UajEblcvmC0kz61vnXROruuwfpvVKbdp/ek7WFwYpDjnceXZKsoigwMDCxd/ckHSGFXvEKhYMOGDcTGxi5p5t1sNnPixAmCgoLYsGGDT2vpczGbzYyMjCxLLyIsLIytW7fS0NCwrJWiUkClUqFWq93vfFzAthymfbSdt1veXvT1nkjHA2RpQ/jBh1dR3NDHHw+6Z1+FozGyZaEKgZv/CmO98MoX3SY56yhi12q1mM1m/4mOXGTZjl0ul+fk5+fPmyGxNSxJIU25GM7M2qsD5CRGqDmnWyRi76uH8GQIsB+dbkvcRqgydMnp+PHxcYKCgvzicwVr7bevrw+tVutrUwBISkpi06ZNVFZWUl9f71RUZzKZOH78OPHx8WRnZ0vus+/t7UWr1S7bLpVKxZYtW+jo6JDErvPlsNyd5+7g0uRLSQtL47HKxxb9nkVHR9Pf775IdSa3FiTzobx4HnyrllPnl58VcOQsl03COrjyh1D7Lzj5F7cc0lHELggCISEhSkEQfNsc4yGW7dhjY2MLVq5cOS9i1+v1Pku9uoqz6nhOLYOxjbo5IEAewOWpl/Pu+XeZMLvegOJPgj9gTREnJCRIyhkGBwezbds2jEYjR48eXXDm3Ww2c/LkSRITE73S0b8U3Ll7XS6XU1hYSGdnp88d43LQaDQMDAy4bYxsKcgEGXevuZvq/mqOdh5d8LUBAQEYjUaPlA8EQeD/blhLbFggX35m+ZKztgY6jzRcbv4cZF0Jb34Hus8u+3DBwcEOG2dXrFghAt5t/PESy3bsMplsraNRN3+pr4+MjDglXJGpCeFc76jjPz5RnBp1W3iKYk/aHkaNoxxuO+yyrf7m2Nva2iS5pEUmk7Fq1SqysrIczryLosipU6eIjY2VrFO3bYhzZUveYtice1tbm9/W3AVBICEhgc5O5xTgPMW1GdeiVWv5a+VfF32to+jSHYSrlfzmo+voGDTwv/+sXPYNRGhoqGeaLWUyuP5hCAyfkpxd3midUql0eHOXn58fxAU68rZsx24ymZLsXbj9ybE7272foQlmbNJMz4iDSHukCyZH7TbOzaQwvpCowCjeaHY9He9Pjt1oNGIymSSduZk78z5zNKa+vh6VSuX1bn5XsMkguzsjIpfLKSgooLq62m+75ePi4nx+YxIgD+COVXdwvPM4Z/sWjkA90pQ2g42pUXz1imxerejgxbLlaeZ78iaEEA3c+EforYE3/2fZh1MqlXYbZtesWRMSHh6eZ+ctfs+yHLsgCEJAQIDKnlrb6Oio34y6mUwmp9TQpjvjexx8oftsGvELS6YqZAquTL2S91rfY9zo/B2pKIpMTk76fGbaWXp6eiRTW18I28y7Wq2e3vPe1dWFTqdj9erVvjZvQdyZhp+LSqWa7pb3xzn3sLAwRkZGfLqrHeDmFTcTogzhscrHFnxdeHi4e8fI7PC5XVlsyYjie69UOi+RbYeQkBDP1NltZF4G274CpY9B1eIjgwvh6CYkLS2N0NBQ/9p57STLjdjDHEWPBoNB0pGaDZuUrDNMb3lzNMu+wKjbXPak78FgNnCg9YBT54b3G+f8BX8ayxMEgczMTPLy8jhx4gSnT59m48aNkl6Ja7FYGBgYIDo62mPnCAsLIycnh1OnTtlN3+7duxetVsuaNdK7PgqCQHR0NH19fT61IzQglFtzbuXtlrdpHW51+DpPR+xglZx96Lb1BChkfOnppUvOLlS7dhuX/i8kbIBXvwSDjj+3xVCr1Xblk6d6f5KWY6JUWe5VKz4xMdHuEzadeKnjSskgLiwQtVLu+E5X1wDKIAi1P9c/k/Xa9WiDtC6l4/0pDW+xWBgeHvablb02wsPDCQgIICwsjDNnzkh2zztY1wxHRUV5vDExPj6ewMBAWlvnX1zvuusu9u1zz/4DT+CpMTJXuSP3DuSCnMfPPu7wNZ5soJtJXHggv7g5n7Mdw/xi39IkZ90qLesIRQDc/ChYLPDSvUuWnA0MDLTbIBsXF4fRaPSvhRtOsmzHnpqaajeHLYqipKMdG66UDGQyYeHO+L56iM60NoAsdixBxu603RxuP8zQhHPpt6GhIb9x7P39/V5xOu6mqamJiIgItmzZQlxcHMXFxR4bQ1ounZ2dHkvDz2XVqlWcO3duXuSzc+dOSWsqREdHo9PpfK6HrwnS8OHMD/Nyw8vo9I63o3k8xT3FlatiuXNrKn853MT+2h6X32/7u/b45xqVAdf+Es4ftSrTLQFHjl2lUiGTyaQvtLIElu3Y09LS5uWGff1H5ApjY2MuNfllaEIcz7Lr6qd3sDvDnvQ9mCwm3j3/rlOvX2xRjZTo6uryu+1zY2NjnD9/ntxcq4S0bea9qqqKuro6SX2vRVGkr6+PmJgYr5xPqVSyevVqKioqJPU5LIZcLickJEQSDYB3rb4Lo8XIP6r/4fA1HhF/ccC3r8llZVwo33iugp4R1yVnHaW43U7erZD/UTj4c2gudvntCy2DUSqVSsHfog8nWJZjDw0NTUtKSpqXb5+YmPCLNDy43r2fERNM24Aeg3FObcposK4eXGTUbSaro1eTFJLEvubFU5miKDIxMUFg4LztuJJDFEV0Op3f6dlXV1ezevXqWapywcHBFBUVYTKZOHr0qGRWnQ4MDBAREeHVrJhGo0GpVLp1E5k3kEo6Pi08jctTLueZ2mcYM9qPyr1RZ7dhk5wdmzTx9ecqXJac9Whn/Fyu+QVEpllT8i5KzjqK2AGio6NFwHNNKj5iWVeFsLCwLHupQIPB4BcOCKwNaa7I3mZoghFFaOmbU1/qPweITjXO2RAEgT3pezjeeZw+/cINPv4k+GPrr5CS7OpiDA4OYjQa7d6M2Gbes7OzOXbsmCSchCe74RciNzeXmpoav4raNRqNZG5G7l5zNyOTI7xY96Ld592+YGURsmND+f51qzlUr+PPh1yTnPVKnd2GKtQqOTvaY22mc+H7t1DEnpSUJADe/0PyMMty7HK5PMXeAhh/itgtFotLq0QzNQ6WwTg56jaX3em7MYtm3ml5Z8HX+VMa3p+a/GxUV1dPp+AdodFoKCoqoqWlhTNnzthdB+kNRFH02Ya/oKAgIiMjaW9f3hy0NwkMDGRyclISNyN5mjwKYgt4ouoJjOb5jZk2RTdv2nr7pmSuWRvHL96spaJ10On3BQYGum99qzMkrIcrvg81r0PJ4oI/NhbKtKelpQVw0bHPxmQyxftzxL6UP573l8HMcey2UTcXHXt2RDaZ4ZmLdscvtn1OSvibY9fpdCiVSqdsVqlUFBYWEhwcTHFxsU9qt4ODg4SFhfksI7JixQoaGhoQRZGPfvSjbN26ldraWpKSknj00Ud9YtNieDW6XIS9a/bSPd7Nv5vs74ZfKHXsCQRB4P4b8qYlZ0eclJxVqVRetROALV+AzMutwjXdVU6/TRAEu3oGUz1iFx37TCwWS7g9KVZ/cexGo9EpYZqZBKsUxIcHzu+M1zVYx9xUrqntCYLA7vTdlHWX0TXmOMXrL58p+Ff3PkBjYyPZ2a6VUDIyMsjPz6e0tNTrK0K92Q1vD5VKRXR0NF1dXTz99NN0dnZiNBppa2vjnnvu8ZldC+HtFPdCbE/cTnZkNo9VPoZFnO9svB4JA+FBSn59+zpa+8f53ivOabSr1WrvO3aZDG54xJqaf2EvGJ3reXGUjk9MTFRGRkZKV1pyiSzLsSuVSoW9NIe/OKGl2pmhCZ4vUtNXDzGuRes29qTvQUTkzeY3Hb7GXz5TURTR6/V+YStYeyxMJtOSyhzh4eFs376dgYEBSktLvTLzLoqiJBT90tPTaWpq8qkNruDNprTFEASBu1ffTeNQI4faDs173tsRu42CtCjuu2IF/zzVzktlbYu+fqHatUcJ0Vqde2+1dVmMEzj6TOPj4wkODra/Y9uPWbJjFwRBplAo7OYCJycnCQgIWLpVXmLJjj1mzjIYUbRG7C6Mus0kNSyVVdGr2NfkuDveXzribZ+pv0yQtLS0LGvBi0KhYN26dcTHx3tl5n1kZITg4GCX+kI8gW2SxBsz1+7Am2NkzrA7fTfxwfF2l8P4yrEDfOHSLArTo/juy5U0OVLYnEImk/lOrjfrCij6EpQ8CtWvLfpyR9vowsPDEQRBukIMS2Q5EXtwcHCw3d+qyWTy+YXHGZba5JehCWbEYEI3OvVFGeuFiSGXRt3msidtD5V9lQ4lJ81ms190mftTfV0URbq6utyS1k5MTKSwsNDjM+++6oa3R2pqKufPn/e1GU5hS29LoYEOQClTcufqOynrKaO8p3zWcz6LhLFKzv769nUoFTK+/PQpJk2LO26ffaaXfQ/i18ErX4ShhTMMCoXC7pa3qb4l/2hecoHlOPZQR6tO/cWxLz0Vb41WphvodFMd8UtMxQNcnXY1gN2ZdqlcjJzB2d32UmBoaMitTWhBQUEUFRVhNps9NvMuJeEfrVZLT4/rqmW+IigoSDI6BAA3ZN1AuCp8XtTuy4gdID5czc9uyuNM+xAPvLWw5KxKpfLdgiBFgHUEzmKCF+8Fi+MplYUcu8ViuejYZxDiqEvbX6LLpW5Ky5jqjG+0NdBNj7otLRUPEB8Sz3rtervd8Utp8vMVw8PDTu22lwKecJIymYzc3FyPzLyPjIygVqsl811QKpUEBARIptt8McLCwhgeHva1GdMEKYP46MqPsr91P+cG358h97VjB7h6dRyf2JLKnw6e4706xxoAAQEBPssuAFYJ7w89COePwMEHHL7MkWMPCQnBYrH4xxpSF1hWxB4REeHw/f5QY11qZiExQo1KIZsdsSsCIXz+XnpX2J22m/qBehoGGmY97i+Nc2C11RXBH1/S09Pjseh35sz76dOn3TLz7utueHtIRdXNGaTgMOfysZUfI1AeyGNn31/pKhU7v/OhXHJiQ/n6c+X0jth33o4cplfJvx3yboP3fgotR+2+xJGdKpUKi8XiH6IrLrCsiD08PFz6YfkCLNWxy2QC6THBnLM1l+jqIcq55S8LcVXaVcgE2bx0vL80zoFV8McfsjUTExPI5XKPRr+2mfeQkBC3zLxLcQ1ubGys36TjpeIwZxIZGMkN2Tfw+rnX6R7rBqxZHymU3wKVcn77sfWMGEx8/Xn7krOScOwA1zwAEanw4qdAPzDvaUd2CoKA3B8uWC6y3Ihd+oX0BVhOL0CmJuT9iH0Zo24ziVHHsCluE/ua9836w/aXFbhSuBg5i7ea/GbOvJeVlS155n1sbGw69S0lbItA/OF374v5cGf45KpPIooiT1U/NetxKXymK2JD+d51qzhY18ujh+ePN0rGsQeGWVe8jnbBq1+eJzm7kJ0yf1hD6iLLitgjIiLmXWVEUfSLNDwsz7FnaIJpHdAzOWGAgZZldcTPZE/aHlqGW6jur55+zF9S8f7UC+Dt7v3w8HC2bdvGwMAAJSUlLs+8SzEND9YbFylGwvaQqp1JoUlclXYVz9c9z/CktQfA0XiWL/hYYQq7V8fx8zdrON02OOs5yTh2gMSNcPn3oPpVKH181lMKhcJhOUwmk12M2GcQas+x+0tHPFhtXWoWJkMTjNki0tlUBaJ5WY1zM7ki9QoUgmLWTLu/OHZ/sRN8M5Znm3lPTEx0eeZdqo4dpCX+shA+kUB1kr1r9jJmHOO52ucAad2ECILAT29aiyZExZefPsXoxPuOXFKOHWDrlyDjUtj3Leh5PzhayM6AgAAEQfCPiMRJluzYQ0JCokNDQ+eF5stxlt5GFMUlr73MiLGOvPW1TOkVuyEVDxCuCqcosYg3mt+Ylpu80AV/fIEvt+UlJCRMz7zX1tYumnLV6/XIZDLJlmPCw8Ml1W3uCKnUru2xMmolRQlFPFX1FBPmCZ/OstsjIiiAh25fz/n+cb73SuX04wtFwj5BJoMb/ggBIfDCPdOSsws59tDQUJELbJZ9yY5dpVKF2bswms1mv4nYl0OGxjohMdE1dVfopogdrBKzXWNdVPRWAP7VkOYPjt12cfdlycg28y6KIkeOHFlwvlrK0Tr4SDN8GUjVue9ds5c+Qx+vNr4qyZuQwvQovnx5Ni+VtfPPU1ZBGMlF7AChsVbJ2Z6z8NZ3AZDL5Q7tDA4OBvCPndhOsmTHLpfLFfYcuD/V2JdDaKASTagKxUAjhMRamzfcxKXJl6KSq3ijyTrTbrFY/OIznZiY8IvMglR6AWQyGStXriQnJ4djx47R2dlp93VSd+xSShsvhpRq13MpjCtkdfRqHq98HFEQfSfXugBfvDSLwrQo/veflbT0jS3oML2FIAio1erp/w4fPgzZV8LWL8LJP0PNvxAEweGN0lTQJJtxvO2CINj9QguC8GFBEPoFQZgUBMEoCMIBQRCWHHUJgmASBGHF1P8Pzzj/75Z6TFieVrzcXhr7g+LYATI1wYSONrs1WgcIVgazM2knbza/icli8pvP1F+EiaRWMoiJiWHbtm2cP39+3sy7wWBAFEVJawNIuXY9F5/qmy+CIAjsXbOX8yPnOTlwUnIRO4BCLuNXt69DIbdKzposoiTs1Ov10/9t377d+uDl34P4fHjlCwgjHQ7fO+XHFvWFgiBEAi8CPxdFMQCIA1ZPPbZsRFG0RYcFwC3LOZbbHfsHiQxNCHGmVrfV12eyJ30P/YZ+SrpLltUL4E385QZkqTsCPElAQACFhYWEhoZy+PDh6Zq1FGfX5yLFtLEjpG7r5SmXkxKawssdL0v2BiQxQs3PblpLRdsQDx9efAucL3j22WcJiYhm7Q9PMjY8gOEfn0S0mKyPh4SgVqtJSEigqanJFoxcLwiCXhAEPfBLB4f9JXBeFMWfAoii2AfcClwHMBW9T2+kEQTBIAjC9qn/7xQEYWzqsSftHVwQBNsX8/8B2il7XhYEYVAQhNtmvG5IEIQFHf9yvMUHPmLPDZskglHGwty/9W9H4g6CFEHsa9rnN6l4f7kBkWpmQRAE0tPTWb9+PadOnaK5uZn29nYSEhJ8bdoFw0IpWSkgl8m5c/WdNIw2UNZX5mtzHLJ7TTwf35zC3050sK9+ecJL7sCWhrf9rdx111385Cc/4UyHnl/XJ6PuLiWn9g/Tj+v1erKysrjxxhtt16yfAt8URXGh1FgeUD7zAVEU9wOCIAiLrYjcJopiMBAP3CIIwkLR4HeBHlEU1aIoXg88B3wL64muAhSiKD6/0MmWcxWW2XM2Uv6jcTerA6yKWx3yRLcfO1ARyGUpl/F2y9sYLUa/cewX7Vw+YWFhbNu2jfb2dvr6+nzWve8KQ0NDvjbBKTo6OiS/avYjWR8B4Dvlzu0a9xX/tXslAH84Ocj5Pt/uC7Cl4Ts6Ojh//jxGo5GvfOUrYDFz7S13ABDf9Q63rRStjwM/+MEPqK2t5a233tICSlEUbXXtn3nAxL9OZQM6ABVwiQvv/TawWhAENfBD4F+LvWHJ7esz0gZzH1/qIf2OFNoBqDXF4d4qu5U96Xt4/dzr1Ohr2MY2D5zBvUg9GrIh9e+oKIo0NjZisVgQRZHXXntN8jYDvP766742wSmOHz8u6c9zzGK98UiWJ0v2MzWY4M/VAAIJQSIVR97ltI8+0oCAgFmf0/DwMAnRIZx99Iuk9bxJ3kQPI5OgDgzgaI8w/drz588THR1NVFSU+fTp086c6gywY+YDgiBcAphEUWwRBMHI7GBZNvWa+4D1QJIoin2CIAziwnjd1HvqsKboC4CPLvaeJTt2URQtUq0BeYuo8RYmRQWVY+Fc64Hjb43fSlhAGCWjJdxtudsDZ3Av/uTYpfrd1ev1lJWVER0dzbZt26ipqSEiIkLy6fgDBw6wa9cuX5uxKCdOnGDNmjWSzoK81vgaHIavb/g6l6+63NfmzGNgbJK7Hj9Jw8gQP/pQJvlhBvLz831mz+TkJNdeO3UF7muEE3/i2r0WwlqfhKRCfvhmEP86J+PnD/6K8/fvobm5mS9+8Yvs2rULjUZDTExMHxAuCMLnRFF8GPimg1N9FegRBOGboij+YqqZ7jngz1PP1wMfAhAE4WOAbfRGA+inHPQeYLG91r1Yo/qZ3A88AbSLoti82Gey5FS8KIomexdHf7m4uwNZfwMd8ngadJ7pCFbKlVyZeiXlo+XojdLZI+0IKTvMmUh15Kmjo4Njx46xcuVKVq5ciUwmIyEhgY4Oxx29UsCf/t6lXoYB2N+6n0hlJDnhOb42ZR5dQwZu/eNRqjuHeeSOjVy7WiONz7NxP/zjNvjtRjj5KP2aLex8yoz6S4d55HAPzzxvbVx//PHH+da3voVaraa2tpYXX3zRds36FvDLqXS53R9IFMUBrN3q/yMIwiTQD5wSRfELUy/5DhA8NSr3A8B2kfkpIBcEYQL4K7BY3eolwGJrnps6998BE/BHZz6O5SjJmB1dxP3pD31Z6OoZUKdyTjfqsVPsTt/Ni/UvUtxZzIeyP+Sx87gDf7mpk9rctdlsprKykomJCbZt2zZLCyA8PJyRkRHJNvyBVRfAH/QLQPqaEJPmSYrbi9kWtQ25xCTMm3VjfPwvxxnSG/nb3YVszYymr6/PdwZNjsPpZxF/txmevB6CYmDnN2HTPaSFxnHwa++/1GKx0Nraym233cZtt9026zBT46X/FEXxocVOKYriy8DLAIIg3A98QxCEIlEUj0w5/hgHb9U4OJ5ixv8LU//qgaiZrxMEYT3WG46fLmYjLMOxWywWu47dXy7uy8ZshIEmJuK2cr55HKPZglLu/o7wTbGbCJOH8WbLm5J37FKNhOciJbnO4eFhTp06RWpqKqmpqfOcjiAIaDQaent7JTv25i/bB0E64kSOONF1gnHTOAWRBZK6AanqGOaTfz2BRRR5+t4trE2yZpN9csM51G4Vnil93LqiNXYtfOQPsOYmUDrWp3D0eU75MZdTjaIofhtrY5tHEQThj8A9wK9FUXRKv3fJjt1oNI7bi3rkcrlfpGOXzUALWEzItTmYzom09o+ToQlx+2nkMjmF4YUc7DzI6OQoIQHuP4e7UKlUftEdLYVZZlEUaW5u5vz586xfv56wMMfKhQkJCTQ3N0vasUtJ8GchpC7PfKD1AGqFmlUhqyTj2Eua+7n78ZOEqBQ8ec8WsrTvX4O8tvRLFKH1BBx/GKpeBUTIuQa2fA5St8Ein9VCNyBTcs6SjUhEUfwM8BlX3rPkEHN0dLRvdHR+ClqS2sELsOQLfF89AKFJuQA09npuhGZr1FYmLZPsb93vsXO4A6mluBdCoVD4LLswOTnJyZMnGR4eZvv27Qs6dYDIyEiGhoYke8M8MjJCSIh0bzht+PpmbjFEUWR/6362JWxDMAuSyCzsr+3hjkePowlR8cLnimY5dfCCYzdNQsWz8OdL4a9XQcO7Vmf+5XK4/e+Qtn1Rp26z05FjHx0dFQDfD+O7kSU7dpPJNDw4ODhvqbQ/OXa5XL70zUQ6q2OPz8gD4Fyv5+rsa6LWoA3Usq953+Iv9iH+5NjDw8N9kl3Q6XQUFxeTnJxMfn6+U9GjIAhER0ej0+m8YKHr+GIF7lKQ+pbEqv4qesZ72JW8SxJZkFcrOrj3byVkaUN47rNbSYyYr93iMcc+2gvv/RweWgP//DRMjMI1D8DXquDqn0DkYnowzts5Pj4uANLvTnaB5fxGRgcHByd5v6UfkLYW81xsNyFL+mLq6iAohvAoDdHBAZzzYMQepA5iW8w2Xmt/jaGJIcJVi01L+AYp1a4Xw7ZDXKOx29PidiwWC3V1dfT19bFlyxaXtd8TEhJoa2tDq9V6yMKlMzIyQmio9LdeSlFKeCYHWg8gE2TsTNrJmY4zPrX1qWMtfPeVSjalRfHonQWEBtrPHpjNZvfa2Xkajj8CZ14A8wRkXm6tn2deZl3JukQWus5bLBazKPV0jossp9trZGhoaF7E7k8sK7vQ1wAxVlmaTE2IRzvjAwMD2Ry+GZNo4p2Wdzx2nuUihdq1s9gcuzcYHx/n6NGjCIJAUVHRkha6REdHMzAwILnP12QyIZPJ/EJKWApR8ELsP7+fdZp1RAZG+qwXQBRFfr+/gf99uZLLcrQ8sbfQoVMHN0XsFrO1bv7YNfDHHXD2n7D+DvjCCfjES5B9xbKc+mJ2WiwWCS2Udw/L+Y2MDA4O+vUHsizHrquHnD2AdTf721XdbrRsNiqVigR5AqlhqbzR/AY3rbjJY+daLrapCKk0/jgiJCSEkZERj9va0dFBbW0teXl5REdHL/k4giAQGRlJX18fMTGOJmq8j06nW9bP5U2k7Ng7RjuoHajl6xu/7rObN1EU+b9/V/PnQ03csD6Rn9+ct+ikz7Icu34Qyp6AE3+GofMQngJX/j/Y8AlQRy7tmEuw02w2+0eK2QWWm4r36w9EoVAsrcauH4BxHcSsAKyOvW9skqFxI+FB7m94CQwMZGJigt1pu/nzmT+j0+uIUUvn4j6TgIAAJiYmJHsBtWFzlP39/R5xTCaTibNnzzI5OTlvNn2p2MRqpOTYu7q6SE5O9rUZTmEwGAgODva1GXY50HoAgF3Ju3zSC2AyW/iff57huZI27ipK43vXrkImc64pzWXHrqu3ptvLnwbjmLWr/eqfWLvc5Z5pxDObzXbtNJlMiKLoH01hLrDcVLzdW0t/qbMrlcqldUbrGqz/TqXiM2KsnaKNHkrH22rXe9L3YBEtvNX8lkfO4w6Cg4OxNy0hReLi4ujq6nL7cYeHhykuLiY8PJyCggK3XaRjYmLo6+uTTDpeFEUGBgaIiopa/MUSYGxsTLKOfX/rftLD00kLT/N6ZsFgNPOFf5TxXEkbX7k8m+9f55xTB2tDolPd+xYL1L8DT90EvyuwRuqrPgKfOQh3/xtWfdhjTh0c34CMjo4il8ulvRVoCSzHsY+OjNifEPCXzvgld3FPjboRPeXYNdaLRWOPZxyarXadGZFJdmS2pLvjfdVtvhRswi/ucpSiKNLU1MSpU6dYv349aWlpbk3zy2QywsPDGRgYcNsxl8PAwADh4eGSL7vYGB4elmST38jkCCVdJexK3gV4t8lvdMLE3sdP8ubZbr5/3Sq+euUKl36fi9o6MWpNtf9hM/z9Jug6A7v+B756Fm54GOK9ozG/kGOXyWT+EYm4wLJS8SMjI3a/ATbHLuXRErA69iU1UOnqQaaYHrlIjgpCIRM4p/PsjZ8oiuxJ28NvTv2GztFO4kPiPXq+pRAREUFDQ4OvzXAKhUJBSEgIg4ODREYur6Y3OTnJqVOnUKvVbN++3WONT7Z0vBSi5NbWVhIT3b+y2BOYzWYEQZCkOE1xezEm0cSlyZcC3usFGBib5K7HTlDZMcwvb83nxg1JLh/DYZPf4Hk48SdrZG4YgoT1cMOfYPUNoPC+X3A0xz4yMoIgCMNeN8jDLGcJzKSjNLYvxT9cQaVSLS1i19VBZDrIrSkopVxGSnSQR2fZZ9bZAclG7aGhoTjK5EiR1NRUWlpalnUM22x6SkoKeXl5HnUe7s4yLBWTyUR/f78kx+/sMTQ0tKgQkK94t/VdogKjyIuxamJ4w7FPL3PpGuGPd2xcklOf9x0URWguhmfvgF/nw9E/QMalsPdNuHc/5N/mE6cOjqWEpxpoLzjHvqyihslBvt3mhKTO0lPx74+62cjUhHh0lt12E5IckczamLW80fQGd6+R3ipXmUyGXC6XvCa3jZiYmOkmN1czTBaLhdraWvr7+5c0m74U5HI5oaGhDA0N+VQUpq2tjcTERL9Jww8NDREeLj39B6PFyOG2w1yeevn00heDweDRSYMm3Rh3zFnmshSm/2aMBqh80doQ13UaAiOg6MtQeC+Eu37D4Akc3Sz19PQwOTl53gcmeZRlDQdaLBa9PQfuLwpkSxJUsZih/xxEZ816OEMTTEvfOGaLZyKpmZ/p7rTdVPdX0zzU7JFzLZewsDCGh/3jJlgQBFJTU2lubnbpfePj4xw5cgSZTLbk2fSl4utVrjad+9RU19S/fIlU1fHKussYMY5M19fBsxH72Y4hbnnkCHqjmafv3bJkpw4w2d9KevPTVnW4Vz4P5km49iH4WjVc+UPJOHVw/Jm2t7eL/f39/lE7dIFlOXalUtltr6vYXxz7kgRVBlusX+CpUTcbmTEhTJottA2Mu9HC9wkKCmJ83Hrsq9OuRkCQbDrem+Iv7iAlJYX29naMRuf0ltrb2zlx4gSrVq0iJyfH61GrVqulp6fHZ+n4trY2YmJiJK3iNpfh4WFJpuL3t+5HJVexNX7r9GN6vd4jjv1kcz+3/+kYAXIZz31m6/SGNpdpL4OXPk3In7cQX/cEJGyAT/wTPn8MCu6GgCD3Gu4GHI27nT9/fsxkMrX7wCSPsly5qNbOzs55D/qLY7fh0gVyzqibDVtnvKfS8eHh4dPOMjY4lg2xG3ij6Q2f11rt4W+OXS6Xk5GRQX19/YKvM5lMlJeX09HRwbZt23zWwKZQKAgKCvJJL4PZbKahoYEVK1Ys/mKJYNOqkFrjnCiKHGg9wJb4LQQprc7QU7bur+3hE1PLXJ63s8xlUcwmqHwJHr3KupCl5l+MrryF8x95GT7+nFXyVaJlmYWukc3NzQZgvhPzc5bl2A0GQ5M9x+5PmuEu34TMGXWzYVvZ2uihBrq5TWl70vZwbugc9YMLOyNfEBoayvDwsCRvOhyRnJxMT0+Pw+/C0NAQhw8fJjIykoKCAp/3D/gqHd/c3ExCQoLkJ15mMjAwIMk0fP1gPe2j7bPS8J7Q3X+lvH3RZS4OGe+Hw7+yNsO9cDeMdsPV98PXqujIvw9FbI5bbfUEC4notLa2mrno2Gej0+ka2tvb50m3+VPE7rKgiq7OKncYPLs2FRUcQESQ0mPrW2138LY7+itSr0AuyNnXJL10vEwmIyQkxG/q7GC1OScnh7Nnz856XBRFzp07R0VFBRs3biQ1NVUSDWOxsbF0d3tOxtgeExMTnD9/nszMTK+ed7l0dXVJcpf9/vPWNcwzHbu7ewGePNbCfc+WszE1kqfv3UJMiJPlk55qeO0r8MtV8M4PIDoDbn8avlQGWz8PgeGSFvyZyUI9C52dnTLAu39IXmBZjl0UxY7m5uZ5nkwul/uF8hxYNcPHxlxwxrqGedG6jYyYYI+OvM0Uf4lWR7M5frNk0/GeUnXzJPHx8Vgslmm7JyYmOHHiBGNjY2zbtk1S4iZKpRKVSuU1lT9RFKmoqCA3N9ez+7fdjCiK9Pb2SkqG18aB1gPkxeTNkod217SDbZnLd1+u5PKVWv62yDIXwKoOV7sPnvgI/GELVDwDa2+GzxbDna/BymtA9n6JYHR01O8du8FgMIuiKP3ZbBdZbo29s6WlxeGHIkWHM5eQkBDXLo599fPq6zasW948N/I2V9Vtd9pu2kbbONt3doF3+YbY2Fh6enp8bYbL5OXlUV1dTWdnJ0eOHCE1NZW1a9dKrj4L3k3Hd3R0oFAoJBn5LoTN+Ujt99cz3kNlX+WsaB3cM28viiI/+Vc1v3izlhvWJ/LwHRsJVC7w80+MwLFH4Hcb4enboLcWLvsufLUKPvI7iFtj920Wi8UvbvIcqeNZLBZMJtMF59TBDY59qkYxD6VS6XSXsS9xybEbhq01pjmjbjYyNCH0jkwwYvDMzz23Ke3y1MtRyBS80fSGR863HAICApDJZH5TkrGhVCoJDg6moqKCzZs3S9qReSsrotfrqaurY+3atR4/l7uRahretvTFpjYHVkezXGdpMlv4rxdO85fDTdxVlMaDt+Q73tDW3wT7vm1Nt+/7bwiKhpsehfvOwM5vzCs3zsRpjXgJ4Chi1+l0yOXyPh+Y5HGW69h7e3t77R5DrVaj1+uXeXjP41I/gK1xLsZ+R7CnO+PnzoeHBYSxPXE7+5r3YRGlV/rwRR14Odhm0yMiIoiLi8NeY6iUCAgIQKFQTI9BegKz2UxJSQlr1671mwv5TLq7u4mNjfW1GfM40HqApJAkMiPe71dY7kiebZnL86Vt3HeFg2Uuogjn3oOnPwq/WW+VfV1xNXzqXfjUO9bUu3zx3/Po6CghIS521vsIR469s7MTmUx2wY26wfJr7GaDwWBXfS44ONi12rWPsDVCOdUT4GDUzUambRmMh+rscxvowNod3zPew6meUx4553Lwpzr7zNn0FStWkJeXR1dXl+TLCZ5Mx4uiSHl5OcnJyZKsUS/GxMQEoihKbt5+3DjO8c7j7EreNasRcznqeHOXudx3xZxlLkY9lP4NHt4GT3wYWo/Djq/DfZVw018gaaNr5/Mjxz42NmbX1tbWViYnJxt9YJLHWW7EDtDf398/70GXa9c+JDg42Lmop68eBLlVJ94OKVHByGWCR6Vl50btu5J3oVaoJZmODwkJQa/XL23nvZcwmUycOnWKzs7OWbPpMpmMgoICqqqqJK19Hx8f77Gbp4aGBhQKBWlpaR45vqfp7u6WZBr+SMcRJi2TXJZy2azHl9oRPzA2ycf/fIzjTf388tZ87t424/o03AH/+ZE13f7al62z5h/+nXW72uXfhbClLZLyJ8fuSPCnpqZmsqenp9QHJnmcZTt2mUxWbU/Yw18idnDhJkRXZ93o5mCRQYBCRnKkmnMe2ssO8+vsQcogLkm6hLea38Jkkd6q3NjYWMmmtG2z6VFRUWzcuHFeqlmlUrFhwwZKSkok+11WqVQIguD2sldLSwt9fX1+WVe30d7eTny89DYg7m/dT1hAGOu062Y9vpSI3eEyl9aT8MJeeGgtHPolpBbBna/DZw/Dhk+AcnkSyP7SEW/LxNobUa2oqBgRRbHO2zZ5g2U79sHBwdLa2tp57e/+FLE7vUN8gVE3G55eBmNP1W13+m4GJgY40XnCY+ddKikpKcvenuZuRFGksbHRqdn0sLAw1q1bx8mTJyXr3OPj491689TS0kJ7ezubNm1CJnNHUs/7jI+PY7FYJBdVmi1mDrYdZEfSDpSy928kl9I416Qb46aHj9A5ZOCJvYVcsSISTj8Pf74MHr0C6t+GzZ+Fr5TD7X+H9B1uU4cbHx/3C8e+kJ2VlZVmQHoKX25g2X+1o6OjlZWVlfM8uEKhkHQKdiYz5VodYrFAf6PD+rqNDE0wTboxLB5aBhMWFjbvJmR74nZClCG80Sy9dHxwcDCCIEjmJm9iYoLjx48zPj7u9Gx6ZGQk+fn5nDhxQpJpeXc69qamJjo6Oti8ebPkRsRcoaWlRZJLasp7yxmcGJzVDQ+uj7nNXOby3B3ZbGn7qzU6f+lToB+EPb+Ar1XB1T+ByDS3/gy2jngpCDUtxkIiOr29vaIoivPryBcA7rgdr6uoqLCbB1QqlX6xl33mghWHDLWCyeCEYw9hwmShfdAzEwFyuRyVSjXLXpVcxWUpl/Gflv8waZbe5+2OnefuoLe3lyNHjpCWlubybHpkZCQbN26ktLRUcg11arUai8WyLBlni8XC6dOn6evro7Cw0K+duk1kSIpp+AOtB1DIFGxL2DbrcVe6923LXHKF8xzIfoFVz2yBd38MsavgY8/DF0tg86dB5RlBpcHBQUmuwLWHo16AsbExLBaL/0hjuog7HHtTQ0OD3Vs3f6mzC4Iwve/cIQ404ueSETM18uZBoRp73eZ70vcwYhyhuL3YY+ddKvHx8fT09Pgsg2OxWKiqqqK+vp6tW7cuuaEqLCyMrVu3Ul9fT2Njo6QEmJYTtU9OTnLs2DHUajUbN270a6cO1tl1jUYjyZ/jQOsBCuMKCQmY7Wx6enrQarWLvn9/VSePP/o7npD/iCeNXyOs8VVY/3H4/HHrhrUVV4GHyyfuUsfzBo4c+1Rj6AWZhgc3OHZRFI3j4+OT9i5yF1SdfZFRNxvTy2B6PPdz23Psm+M3E6GKkGQ6XiaTkZCQQFtbm9fPPTY2RnFxMUqlkq1bty57HaZKpWLr1q2MjIxQWloqmYzUUh17X18fR44cISMjg+zsbL9Iry5GU1MT6en2J1d8ybmhczQPN89Lw+v1ehQKxcI6AYYhKl/4CZnP7uT38gfJCxqAK35o7W6/9legXelh69/nQojY6+rqGBsbK/OBSV7BLXqACoWio6OjIzExMXHW4yEhIQwMDLjjFB7H1pTmMB3WVw+qcAjWLHicmJAAQgMVHu2MV6vVmEwmjEbj9MVAKVNyZeqVvH7udcaN49NrIKVCamoqx48fJyUlxWvOo62tjYaGBvLy8ty6YlUmk7Fu3To6OjooLi4mNzfX52NVwcHBGI1GJicnndq8ZjKZqKmpYXh4mE2bNvlFI5QzDA4OTqsHSg2b2txcGdkF1fF0DXDijxhLn2SNWU91wGr0H/op6rUfAblv5Fz9adTNaDTa/Xs4e/asvr+/v8IHJnkFt+RsRFE8W1c3f2rA5c1pPmTRHeK6OojJWrSrVBAEMjzcGQ+g1Wrn1Xr3pO9Bb9JzsP2gR8+9FAIDAwkNDUWn03n8XLbZ9K6uLo/uTU9ISKCoqIjW1lZKS0t9Lp/rrCBQb28vhw8fJjg4mK1bt0rSCS6VxsZGMjIyfG2GXQ60HiA3Kpe44NlOfJ5jF0Vo+A/8/Rb43UbMJx/j1ckCfpTwMOn/dQj1upt85tT9qXHOZDI5nOqoqKgYBS7IUTdwk2PX6XQna2pq5km3+UuNHd5voHNYN3Vi1M1GpibY447d3kV8g3YDGrVGkqtcAbKzs6mtrfVobXpwcJDDhw8THR1tdzbd3ahUKjZt2kRCQgLHjh2jqqrKZzsSEhISFkzHDw4OcvToUVpaWigsLCQ9Pd0vLtDOMjw8jMFgIDrasca5r+g39FPeUz4vDW8ymZicnCQoKAgmx+Dko/D7zfDUjYgdpzgYfw9b9L/m8Jof8+17bl94mYsX8Kc0/EISvdXV1QANXjXIi7jFsU9MTFQcPXp0Xs5dJpMhl8v9YhmMIAiOu+MnRmGkwxqxO0GmJoSuYQNjE54TjAkPD2d4eHiWFK5cJufqtKs51HaIkUnpjWWFhoYSEhLiEaU022z66dOnKSgo8GrKH6w17p07dxIcHMzhw4epq6vzev09JCQEg8Ew7+9tcHCQkpISqquryc3NpaCgwOpILjBqamrIzc2V5M3Ke63vISLOS8P39PQQH2SGt75rVYf719dAGYj5ww/z7ZSn+WTT5XyoaN3Cy1y8SH9/vyRvnOzhSMnPbDYzNDQ0KYqi55Ys+Bh3fVPKT5w4YVds3WnxFwkQHR1tP1XcZ2ucs7/8ZS62zvgmD3bGC4JAVFQUc+V896TvYdIyybvn3/XYuZdDTk4OdXV1bo3abbPper2ebdu2+az+J5PJSE1NZefOnSiVSo4cOUJ5eTkDAwNe66C3Ld4xm820trZy+PBhamtrSUtLY+vWrX7Tzewq/f39iKLosbLLcjnQeoC44DhWRk01uYkitBxF/dpnyf73TXD0d5BxCdy9D8Pd7/K5yhU8c6rH8TIXH6HT6fzGsTvq3q+rq0OpVNZ63yLv4ZZCjSiKY/Hx8fqZzVw2bI7dH5ZIxMTEcO7cufnCFjbH7mQqfrozvneUNYmeS1vZ0vEzP9u1MWtJDEnkjeY3+EjWRzx27qWiVquJiYmhtbWVlJSUZR+vp6eHs2fPsmrVKsls8ZLL5aSnp5OWloZOp6OxsZHR0VE0Gg1xcXFERUV5JKo0Go3I5fLp0b64uDg2bNhwQUbnMxFFkerqasnK3xpMBo52HuUjmR9BME9C5Utw/GHorCBEEQJbvwSF90JEMqMTJj79txKONPbx/etWzdZ99zFmsxmz2Sy5pTqOGB4etitAVVJSIg4PD+/3gUlew20dGEql8mxVVVVKfn7+rMcjIiJoaPCPUobtJkQUxdkXXl09IECUc005qdFBCAI0erjOHhMTQ3V19Sx7BUFgd9puHj/7OAOGASIDIz1qw1LIzs6muLiYxMTEJc8aWywWqqurGR4edssYmycQBAGNRoNGo8FkMtHb20trayunT58mJCSEiIgIwsPDiYiIcKqTfSaiKDI2NsbQ0BCDg4MMDg5iNpvRarXI5XK2b9/ul2tWl0JPTw9qtXpZK089yfHO4+hNei7t74ZfrYGxHojJYezSH9MQtJH8TUWAdZnLXY+doLJjmF/emv++7rtE6O/vJzJSetcTe9g0M+xdXw4fPjw4NDR0xNs2eRO3OfaBgYF3S0pKrs7Pz5+V3g8NDZWkDKc9ZtbZZ3UK99VDRAoonXMegUo5SZFqznlofasNuVyOWq1mdHR01p3pnvQ9PFr5KG+3vM2tObd61IalEBAQQFJSEk1NTWRlOde3MJOxsTHKysqIi4tjy5YtkqypzkWhUBAfH098fDyiKDI6Osrg4CA9PT3U1dVhMpmmhZICAwMJCAhAEAQEQUAURcxmMxMTE7Nq6EFBQYSHhxMTE0NWVtZ0JGWxWOjt7SUhIcGXP7JXEEWRmpoaNm3a5GtT7NNRzv5D/49gi4WCE3+D7Kus+u2Zl9FcVYV2qnTQOaTnE4+e4Hz/OH+8YyNXrJJG9mkmfX19fpF5hYUX6hw5csQIXLAz7OBGxz46Onr80KFDg/fcc8+sItfMBjp/iCBsdfZZjl1Xt6gwzVwyYjw/8gbWpq2Ojg5ycnKmH1sRuYL08HT2Ne+TpGMHSE9P59ChQ6Smprr0vWhtbaWxsZH8/Hy/iR7mIggCoaGhhIaGkpycPP24TRbW5rwtFguiKCKTyZDJZNNOf7Fxo4SEBBobGz8Qjr2trY3o6GhplRvMJqh5HY4/guX8Ud5LSWJ7UAIBX3xlugFXFEV6e3vJycmhSTfGHX85zpDeyBN7C9mSIc0atk6nk6Twjz0cOfapm16TKIqD3rfKe7izzfLU8ePH7WqGzt0hLmViYmLo6+t7/wGLBfoana6v28jUhHh0GYyNhIQEOjo6ZjVnCYLAnrQ9lHSV0DMuLV1zGwqFgqysLKqqqpx6vdFopKysjJ6eHrZt2+a3Tn0hZDIZarWayMhItFotcXFxxMfHExsbi0ajISwsbDqSXwjbxIS/LGFaKpOTkzQ0NJCd7drfpscY74fDD8Fv1sHzd8JwO5U7v4JOLmNX4VdmTdXodDoiIiKo7RmbXubyzKe3SNap+1t93VFH/FTj3AU7v27DbY5dFMXRwcHBCZNp/ojXouIvEmJmnR2wjrkZx50edbORoQlGbzTTNexZ0RKFQkFUVBS9vb2zHr86/WpERN5qfsuj518OSUlJ6PX6RZeqDA4OUlxcjEaj8cpsur9jq+3P/U5caJw5c4acnBzfO5ueGnjtPvjVanjn+9Ztarf9Hb5czoGIGOSCnB2JO2a9paWlhX55JLf/6RgBchnPfWarRxttl4s/1dfB8Qx7SUmJODIyckE3zoF7I3aUSmXV1OD/LPzJsdvSpNMZBt3UngAnR91sZGimlsF4IR1vb3taRngGK6NWSlI73oYgCOTn53P27Fm7WgeiKNLQ0MCZM2coKCiYlba+yMLYMjkXKp2dnVgsFt+VGywWqHsLnrwB/rAZyv8Ba26Ezx6Gu16H3GtBJmd/6342xm4kXPW+056YmOBI0xCff64KTaiK5z9XRJZW2hKtrmyf8zWLNM4NXeiNc+Bmxz44OPhuSUnJvNzzLEfpB8TGxr4vouLiqJuNzBkjb54mIiICvV4/T9J0d9puTveepm3E+8tXnEWtVpOZmcnZs2dnPW4wGDh27BgTExM+nU33VyIjIxkcHJwlYHShMDk5SU1NDXl5ed4/+cQoHP8T/H4T/OMW6KmGy/7Xuvv8I7+HuPdH7lpHWmkYbJgnSvPEgSp+XWYgSxvC85/ZSmKE2ss/hGuIoohOp/ObxrmBgQGHeg1HjhyZ5AJvnAM3O/aRkZHD7777rl0FusDAwMV3nkuE2NjY99PDunoICIFQ15Z8aENVBAfIPd4ZbyMlJYXW1tZZj+1O3w3Am81vesWGpZKcnMzExMT0Z97T08PRo0fJzMxk9erVDvWeL+IYQRCIiYnxija/t/FJCn6gGfb9D/wyF974JgRGwE2PwldOw85vQvB8p2dv6cuTR5v5v/0dbEyN5Ol7txAdIv2a9ejoKEFBQZJcg2sPR937RqOR3t5eoyiK/XbedkHh7itmyaFDh+x27PjTRSYgIACZTGaNgHV1EL348pe5TC+D8aD63EwSExNpa2ub1USXGJJIniaPfc3S1I63IQgCeXl5nD17ljNnztDY2MjWrVud2k99Eccsph3vj3R2diKKondS8KIITYfgmY/Db9bDiT9C9pVwzztw739g7c2gcKw/cKD1AFkRWSSHJiOKIr97t57vvnKWjQkqnrhnM6GB/tErsuD2OQniKLtQVlaGQqE46QOTvI5bHbsoihNGo7HLnhb4vG5ziWOT5qSvweVRNxsZXlgGY0OpVBITEzNPh/2a9Guo6a/h3NA5r9ixVGxdt/39/WzZskWSgjP+RnR09LTU6oXAxMQENTU1nleYMxqg7El4ZDv87VpoOQLbvwr3nYGb/wrJi8/MD00MUdpdyqXJl2KxiPz4X9U88FYdO5JVPPzxDT5f5uIK/lZfNxqNdrM577zzjr6zs/MlH5jlddye45yYmHj9wIED864k4eHhftNAB1a51p72Zhhqdbm+biNTE0L7oB79pHfGjtLT0zl3brYDvyr1KgQEyW58A+tseklJCRs2bCA4OJjz58/72qQLAkEQiIyM9KsbakdYLBZKS0tZtWqV51Lww53wn/8Hv1oFr37RGrF/+LfW+vnl34Mw57MEh9oPYRbN7EjcyX+9eJpHDzfx8U2JfDo/EE20NPXs7TExMQHg+8kDJxkYGHDYvf/aa6+NmM3mA961yDe43bH39fX9+1//+pff19lDQkKgf8pJLiNiB88ug5lJSEgICoVi1tIdTZCGTXGbeKPpDclFbkajkdLSUnp7e6f3pq9bt46WlpYLwhlJgQulO76yshKNRuOZyLGtFF78FDy0Bg49CMmb4c7X4HPFsOGToHS9ue1A6wGiA2P4w75JXiht474rsrl9hZxMie6Kd4Q/ReuwcH29paXFKIpiq523XXB4oivp5IVQZweIU0xJ4S7Vscd4rzPehr2ofXf6bpqHm6kdkM5Co4GBAYqLi9FqtWzYsGF6Nl2hULBp0yZOnz7tNzeBUsZWApPaTZ0rNDc3YzQalyQ/7BCzEc68AH+5Av5yGdTug8JPw5fL4KNPQ/pOl/tqbEyaJznUdhjLWC5vV/fyg+tW8cVdGeh0Or+qVYO1p8GfbHZUXy8tLf3A1NfBA459qs7eeSHU2WOEqcRDVOaS3p8e471ZdhsajYahoaHpFBrAFSlXoBAUvNHk+5l2URSpr6+nsrKSTZs22Z1NV6vV5OfnU1JSgj3Bo4s4j0wmIzw8nIGBeUk0v0Cn09Ha2sq6devcsxNgrA8OPgAP5cGL98B4H+z5OXy9Gnbf7/Sip4XY33yUcdMYnZ2Z/Oq2fO7als758+dJSkryqwmPyclJDAaD3Q1pUmSh+vrbb7/9gamvg2cidgwGwwVRZw8cbcOg0mAUlta9qg6Qkxih5pzOexG7IAhkZmZSV/e+amJkYCRbErawr2mfTyM322z65OQk27Ztm63HP4eoqCjS0tIoLy/362hTCvhrd/z4+Pi0ONGyR626z8KrX7LWz9/9f6BZAR97Dr5YCps/Ayr3OK/OIT3ffec5RIuSX3/kFm5Yn4TJZKKlpYW0tDS3nMNbdHR0+NW+gYGBAaKi7PcvvP766x+Y+jp4yLH39/e/8frrr9uts6vVar9JsQq6OsyRGcu6KHqzM95GUlIS/f39sz7nPel76Bjr4LTutFdtsdHd3e3ybHpKSgqBgYGzblIu4joajYaenh6/ukEymUycPHmSdevWoVYvUcDFYoaaf8PfroOHi+D085B/O3z+GHzyFVhxNbgxgm7SjXHTw0cYV5xmvWYz16xJAeDcuXMkJyf7nRRye3s7SUnSWh27EI7S8EajkfPnz39g6uvgIccOnDh8+LDdOrtGo7GOkUkdUYS+BgISVtPWtnTltkxNCOd6R716URUEgZUrV1JTUzP92KXJlxIgC/B6d7zZbKayspKmpiaKiopcnk1ftWoVAwMDFzvll4FcLic0NHRWU6WUMZvNlJSUkJGRsTR9csMwHP0D/HYDPPNR6DsHV/zA2t1+3a9Bm+t2m892DFmXuXAeQTHIjTlXAdZ0dnt7u99sRbNhCwqWfFPlA3p7exeqr5/wgUk+wyOOXRTFSaPR2GGvGzcuLs4/HPtIF0yOoozNxWKxoNfrl3SYDE0wY5NmekYmFn+xG9Fqtej1+mkp39CAUHYk7eDN5jcxW7wzfjc6OkpxcTFqtZrNmzcvaWRGJpNRUFBAa2sr7e3tHrDyg4G/dMdbLBZKSkrQarWu7wboa4Q3/tuqDvfmtyEkDm55HL5SYZ1DD/LMmNnJ5n5u/6N1mcvNO4cRENiZtBOA+vp6MjMz/Ua1zYa/ResGgwGZTEZAwHzBoLfeeusDVV8Hz0XsjI2NPfvaa6/N63wKDg7GYDBIvymqz7b8JZukpKQlOxVfdMaDNWrPzc1l5lKe3em76dX3UtbjWalkURQ5f/48JSUl5OXlkZmZuazGJ4VCQWFhIU1NTX5ZK5YCWq1W8ul4URQpKysjOjqaDGfHwkQRGvfDP26D326Ek4/Cyg/Bvfvhnjdh9Q0gV3jM5v01PXzi0eNowqzLXCr6ilmnXUe0Ohq9Xo9Op/O75UWiKPpdfX2hsbznnntuxGw2S1tX2814zLEPDQ298Pe//91uK65Wq5X+Sknd+459OdGObZa90ct1drA2oAmCMD2JcEnSJagVao92x9v2put0OrZv3+5wGYOrKJVKNm/eTENDw0XnvgQUCgVBQUGMjIz42hS7WCwWysrKCA0NdW6sbXIcSh6DP2yFJ6+H9lK45L/gq5Vw458gcYPHbX6lvJ17nyiZXuYiVw5R3V89rQ1fW1vLihUr3NPN70WGh4dRq9V+1RPgSPa2t7eX/v7+PlEUJe5w3IvHHLsoivX19fUGe41ycXFx86RPJUdfAyiDIDSBgIAAVCrVkjbUxYUFolZ6bxnMXGxRuyiKqBVqLk2+lLdb3sZomb8mdbnYZtNjY2PZsGEDCoV7IyWlUsmWLVtobGy8mJZfAlLtjrel38PCwsjJyVn4xUNt8Pb3rd3tr98HciVc/zB89Sxc+j8uL2taKk8ea+G+Z8tnLXOZufRlZGSE0dFRv5oBt9Ha2upXWQaz2Yxer7e7AfK1114z6/X6Z3xglk/x6FClKIqvv/POO/Mej4yMZGBgQNJpQXT1EJ053TWblpZGc3Ozy4eRyQTSY7zfGW8jNDSU4ODg6b6GPel7GJwY5FjHMbedY+5suidrc7bIvbm5+WJDnYvMWkcsEcxmMydOnCA6OprsbAdCUKII54/D83dZ58+P/AbSdsDdb8BnDsK6j4HCO5Kn08tcXq7k8pVa/ra3cHqZy/7W/aSFpZERnkF1dTW5ubl+F62bzWZ6e3v9Sm2ut7cXjUZj97mnnnqqf3Bw8Dkvm+RzPOrYu7u7//7000/PW5Fn07CWtGiGrm6WRrxWq6Wvr29JvQEZmmCvzrLPZeXKldTW1iKKIkUJRYQGhLpt45vBYODo0aMYjcZFZ9Pdhc25d3R0TP9cF1kcpVKJSqVidNR338WZ2L47cXFxZGbaEYEyTULFs/DnS+GvV0Hju7D18/DlcrjtSUgtWrI63FKYuczlxvWJPHzHxullLqOTo5zoOsGu5F3Ti3eio6O9Zpu76OjoIC4uzq+EdByl4Q0GA1VVVZOAdCQ3vYSnf3vH3nvvPZPFYpn3hKTT8UYDDJ6fJSUrCAIJCQlLSgFnakJoG9BjMHqnG30uarWamJgYWltbCZAHcEXKFfzn/H+YMC+vU982m56VlcWqVau8ejGwNdQZjcaLCnUuIJXu+MHBQY4ePUpOTs584ZbRXjjwM6t2+z8/DZNj8KEH4WvVcNWPITLV6/aazJbpZS53FaXxwC35KOXvf9+LO4oxWUxcknTJdLTuj7S0tJCa6v3Pd6mIouhw8cv+/fsRBGGf+AG88/d0Kt4sk8lOlJSUzHvOJpohSfrPAeK8rW6pqam0tLS4HCFmaIIRRWjp850wT3Z2No2NjZhMJnan72bMOMbhtsNLOtZyZ9PdhUwmY82aNcTGxnLkyJEljyR+kJDCDXV7ezsVFRUUFhbOTqF2VsA/P2etnx/4P4jLgztehM8fh02fggDPZ4PsYTCa+fzfy3ihtI2vXrGC71+3CplsdqZgf+t+IlQRJJCAWq0mLCzMJ7Yuh+Hh4ekmS39hcHCQsLAwu0HFM88809/V1fWUD8zyOR4PsTo7Ox97/vnn57XiKhQKAgMDGRvzTe15QWaMus0kMDCQoKAgl0sImRprU4evGugAAgICSEtLo6amhsK4QqICo3ij2fXu+JGRkWXPprublJQU1qxZw7Fjx+jvn1f5ucgMAgICUCgUPlF/FEWR6upq2traKCoqspZtLGaoehUeuwb+uBOqXrFuVPtiCdzxAmRd4VZ1OFcZnTCx9/GTvFXVzQ+uW8VXrsieVzc3WowcbDvIjoQd1FbX+m20fu7cOefHDCWCozS8KIq88847ZqDY+1b5Ho//xVgslrf++c9/Guw9t9TUtsexjbpFzx+7ycjIoKmpyaXD2ZbBeHuWfS5paWkMDw8zNDDElalX8l7re4wbnbvAi6JIS0sLpaWlbplNdzdRUVFs2bKFyspKWlpafG2OpPFFd7xNIlYURQoLC1GaRqH4N/DrdfDcJ2Co1Zpm/1qVNe2+xI2K7qR/bJKP//kYx5v6p5e52KO8p5yRyRHSLelkZmb6lVqbjcnJSQYHBx02oUkRURQdzq+fOnUKmUxWJoqi+8d//ACPO3ZRFEf1ev15e84wPj6ejo4O6TU/9TVAaAKo5o9PREZGMjY2hsFg917FLsEqBXFhgT7rjLchCALr1q3jzJkzXJVyFQazYXpEZyFse9P7+/vdOpvubtRqNUVFRfT29lJeXo7R+IH8m16UuLg4rzp22xhkQkICqzQKhH99HX65Ct7+LkSkwG1PWRviir4E6giv2bUQnUN6bv3jUWq6RvjjHRu5Yb3jSY93z7+LUqZkhWqFX42JzeT8+fMkJydL6mZ9MQYHBwkNDbU7VvvCCy+MdXZ2Pu59q6SBV3JcAwMDf/r73/8+rwCqVCoJDg6Wnoa1rh5i7ItkCIJAWlqay1F7hiaYRp3vyw5BQUGkpqai0qnQBmkXTcf39/dTXFxMXFwc69evd/tsurtRKBRs3LiR6OhoDh8+LN0+Dh8SGBiIIAge70kwm81UVVVxtvIMhVHDJB34Cvx+E5x6ClbfCJ85BHf/C3KvA5l0JFebdGPc/PBRuoYM/G1vIVescjz6JYoi+8/vJzsgm8J1hX7lGG1YLBZaW1tJSUnxtSku0dbWZne0VhRFnn766XGz2fwvH5glCbzi2PV6/XOPPfbYqL3IPCkpaVlLVtyOKE7NsDtOBSYlJdHV1eVSRGjd8ubdZTCOSEtLY2x0jF1xuzjcfpihifk3VqIoUldXR1VVlcdn092NIAgkJyezZcsWmpqaLkbvdoiPj/do1D44OMiRA28T0/Qy28q/hvrFO6DrDFz6v1Yxmet/D/F5Hjv/UrEtczEYzTzz6S1syVh4ZK1xsJH2sXYuS73ML1PwYHWQsbGxfqU0Z7FYHM6vl5WVYTQay0VRlKbMohfwimMXRXHQYDBUnT49f2VobGwsvb29knB4AIz1wsTQgjU+mUxGamqqS4I1mZoQRgwmdKOTbjByedhS8injKZgsJt49/+6s5/V6PUePHsVkMr3f5OSHqNVqCgsLiYqKuhi9z8FTjt1sNtNQ8h9GX7qP7SfuRXvyZwiqULjxz3BfJVzyTQiRZh33RNP7y1ye++xW1iSGL/qe12peA+D6tdd72DrPIIoi586ds68jIGFsm9zsdcP/+c9/Hmpvb/+1D8ySDF5rN+3q6nro0UcfnafJKpPJiIqKko52vM5+R/xcUlJSaGtrw2x2bjY9QwKd8TMJCgpi54qdxKpiZ2nHd3V1cezYMbKzs70+m+4JBEEgJSWFLVu2cO7cuYvR+xRqtRqLxcLEhJu2DooiI5X76H/kQ2T+62YSW19FyLoC7nkb7n0X8m4FxfzNW1Jh5jKXFz5XND3JshBGo5H/NP+HVVGriA32H6W2mXR1dREVFSWJ6RZXcJSGN5lMvPrqqxPAW963Sjp47aptsVjeePHFFyfsOUJJpeNto24LpOLBWstNSEhwWtY0I8Z3y2AckZaWxoagDRzvPE7vWC9nzpyhpaWFoqIiv+qOdQbbeJ4tem9oaHD6puxCJT4+fvkz7UYDE8f/yvivCgh94TZiRqoRtt2HcN8ZuOUxSC70qjrcUrAtc8mOtS5zSYhwLqVeXF5My2QLl6Vc5mELPYMoijQ0NDi3dEdCmEwmRkZG7IrSvPvuuwBvf1C74W14zbGLojghiuKBgwcPznsuKiqKoaEhaaiH6epBEQjhi3e3ZmRk0NzcjD1lvbkkRqhRKWSSidjBGs1+YtMnsGDh1//5NcHBwRQWFvrd3buz2KL3HTt2IIoiBw8eXJLg0IWCbSplSYx0YXrrhxh/kYPqja8SoBDgul8jfK0arvg+hCe611gP8eTR5nnLXJyhp6eHk/0nAbg05VJPmugxdDodQUFBfiVIA9DZ2UlcXJzdRsVHHnmkr7Oz83c+MEtSeDXP2tnZ+dtHHnnErnZ8XFzc9KISn9LXAFGZToliKJVKtFqtU7P408tgJNAZb0MURcImw8gOyOaVgVd4se9FTKIEbq48jEKhIDs7m23btjE6Osp7771HZ2fnB87BBwcHYzQamZx0oe+jvRTLC/cg/mo18iO/whS3HvETr6D40knYeBcE+IeTEEWR3/6nnu++cnbeMpfFMBqNnD17lnOycySGJJId4fuZ+6VQX1/vePGOhHGUhh8bG+PIkSMG4Lj3rZIW3i6gFr/33nsT9mbAk5KSaG1t9bI5dtDVORx1s0dmZiaNjY1OOQVbZ7wUsM2mDwwM8OQNT3JZxGU8UfUEd+27i85R6a329AQBAQGsXr2azZs3093dTXFxsbQaOb2AUxKzZhNUvoT4lyvhz5dhqf4XIzm3IX6xBPXelxEyd0k+3T4T2zKXB9+ev8xlMURRpKysjJTMFE52n2RX8i6/HHHr7+9HLpf7nfStwWDAZDLZXdH6yiuvWMxm8zMfRG34uXjVsYuiaBFF8YXXXnttXu46NDQUk8nkW71v0yQMtCxaX59JYGDg9IKVxciICaF1QM+kafHUvSexzabHx8ezbt06ggODeeCaB9gbs5eGgQZufu1m3mt9z6c2ehO1Ws26devIz8+ntbV1OkX/QajBL9gdP94Ph36J5aE18MLd6HXn6S34OnytirDb/oDMhRtgqbDYMpfFqKmpISwsjGaamTBPcGmy/6XhbdK+K1eu9LUpLnP+/HmH8/Z/+MMf+nQ63Z+8bJIk8XrLc09PzyO///3v7Qp625as+IyBJhDNLstZrlixgsbGxkUdQaY2GLNF5Hy/b9LxoihSW1tLVVUVhYWFJCa+XwdVKpXce8m9fEP7DeKC4vjiu1/klyW/xGj54PSghIaGsmHDBrZs2YLBYODgwYOcPXtWMmtOPUFoaCgGg2H2pEBPNeKrX0b8ZS7854cMK2Ppu/oPBH6jEs2130MRHOU7g5eBM8tcFqK9vZ3h4WFWrlzJgdYDhCpD2RC7wXMGe4je3l4CAwMJD198nE9KiKJIe3v7rOuWjd7eXhobG4dEUazzgWmSw+syYqIoVsXHx/d3dHTEJCQkzHouISGBgwcPsmLFCt+MWTk56jaXgIAAEhMTaW5uXnAeNCPGmj5q7B0jSxu6ZDOXgl6vp6ysjKioKIqKiux+viEhIVySfwmaWg2HtId47OxjnOo5xS8u+QVxwfMXLVyoqFQqcnJyyM7OpqurizNnzmCxWEhNTSUuLk7y6nuuEhsbS3dXJ0njVZiP/A55yyEssgAGU64mYMeXicgs9LWJy2Z0wsS9fyvh6Lk+fnDdKoe6744YHBykoaGBoqIiLKKFg20H2Z60HaXMf0RdwOoca2pq2Lhxo69NcZmenh6ioqLs/v09+uijhrGxsQ9805wNnwwpDw8PP/jHP/5x3vYRuVyORqPxXROdk6Nu9sjIyOD8+fMLzkhnaHyzDMY2m56Tk0Nubu6CN01arZbkhGSuU1/Hz3b8jLqBOm557RYOtR3yosXSQCaTkZCQwNatW1m3bh0jIyMcPnyY48eP09LS4tK+AMkhijDQjHj6ORJP/5qov18JT9+GqauKwY1fQbzvLNF3PUXoBeDUbctcTjQvvMzFEQaDgVOnTlFQUIBSqeS07jT9hn4uS/a/Mbf29nYiIyP9UnSqubmZtLS0eY9bLBYefvjh0ZGRkce8b5U08YljHx8f//ujjz46Zi917aqim1vRNUBILAS63lCiUChIS0ujsbHR4WtCA5VoQlVeWwZjNps5ffr09Gx6TEyMU+/LyMhAFEVWspJnr30WbZCWz//n8zxU+hAmy4XfNW+P4OBgcnNz2bVrF6tXr55uPjx06BC1tbUMDQ1Ju+nOqIeWI3D4IcSnP4b551nw63yEl+4lqPYl9Cotkx9+BNV/1RJx3Y9QhGl9bbFbcGWZiz3MZjMlJSWsWbNm2hnub92PQlCwLXGbJ0z2GBaLhYaGBlasWOFrU1xGr9czOTlpt3ywf/9+jEbje6IozhNA+6Dik5yiKIpj8fHx+9544407rr322llFrtDQUERRZGRkhNBQ76ar6VtYI34xUlNTOXjwIGlpaQQGBtp9TUaMdzrjR0ZGKCsrIzk5mbVr17rUuSsIAnl5eRw9epQVISv4+zV/56cnfsqjlY9yqucUP9/5c79V2nIHISEhZGVlkZWVxeTkJN3d3dTX1zMyMkJYWBgRERFEREQQHh7um7S9KMLgeWg7idh6HPH8cYSeswhTN2V6dTyTmo0o0osIWrELedwaumvrmIiIIEHuX6nlhTjXO8onHj3BkN7I3/YWLqr7PhdRFKmoqCAxMXGWYNOB1gMUxBUQGuDl69MyaWlpIS4uzi91KpqamkhPt59p+fnPf97X2dl5v5dNkjQ+KxZ2dXX9/Be/+MWea6+9dl4YmZ6eTnNzM2vXrvWuUbo6WPWRJb9dJpORnZ1NXV0deXn2F1xkaEJ4o9Jz42S2vektLS2sW7duyQ0ycrmcgoICjh49yqZNm/hB0Q8oiCvgR0d/xK2v38r92++nKLHIzdb7HwEBASQnJ5OcnIzFYmFkZITBwUHa2tqoqqrCbDYTGhpKeHg4ERERhISEoFKp3DsiZdRDxynMLcesTry9BLleB4BFpmI0IgdjzseRpWxGvWInQdHJzJ02j4+P59y5c8zte/FXznYMcedfTyCK8Myntzil+z6Xc+fOIZfLZ6V/m4eaaRpq4vac291orecxmUw0Nzezfft2X5viMmazme7ubrtd/F1dXZw+fXpAFMVSH5gmWXzm2EVRrExISOhqamqKmXsnFhcXR01NDUaj0Xsbh8b6QD+wrIgdrA2ATU1NDA8P250RzdQEMzhupH9skqhg92pnT05OUlFRgVKpZNu2bcuOFgMDA1m/fj2lpaUUFRVxbca1rIpexdcPfJ3PvvNZ7s27l8/nfx65hFZu+hKZTEZ4eDjh4eGkpqYC1vTn6Ogog4ODdHR0MDY2Nq3PLggCKpWKwMBAAgMDUalUBAQEIAgCMpkMQRAQBAFRFLFYLNZ/zWZMfU3IO0tR9VSg7qskeOQcMtGMHDAEJTChLYDkQlRZOwhM3kC4fPHvQUREBMPDw5jNZuRy//59nmjq557HTxIaqODJT212Svd9Lj09PXR1dbF169ZZN2EHWg8AsCt5l3uM9RK1tbWkpaX51QY3G+3t7cTHx9vtDfrd7343Njw8/AsfmCVpfNreq9PpfvyrX/3qT7/5zW9meUBBEKb14x2lX9xO39I64uciCAJr1qzhzJkzFBUVzYvMMmcsg4ly49hQf38/p0+fZsWKFW6NuiIiIsjKyqK0tJTCwkIywjP4x4f+wf3H7+dPp//EqZ5T/GzHz9AEXVja8u5CJpMRFhZGWFjYvPlb2xIWg8Ew/e/Y2BiiKE7/h1GPerCW4OEyjQAAXiRJREFUoP6zqHVnUOvOoDD0ASAq1IgJGxDyroOkTZC0icAQDfaLQAsjCAIajYbe3l7i4vx3AuLdmm4+91QZSZFqnrxns9O67zMZHh6mqqqKrVu3znMm+1v3kxOZQ0KI/2Q2RkZG6O/vZ9WqVb42xWVEUaS5uZlNmzbNe85oNPLYY4+NjY+PP+kD0ySNTx270Wh86bnnnnvopz/9adhcveLU1FSOHDlCWlqad5SdljjqZg9byrWtrY3k5Nma8zM74wvSlu/YbXvTe3t7KSws9Ijuc2JiIgaDgdLSUjZu3IhaoeZH235EQVwBPz72Y25+7WZ+tvNnbInf4vZzX8jIZDLUavX7e7xn1MZpPQFtJ6w7zG0Ni5HpsOIKqxNPLkTQrkZwIhp3loSEhOk6rD/ySnk7X3+ugtz4MB6/e5PTuu8zGR0dpbS0lIKCgnm16AHDAOW95Xw679PuMtnjiKLImTNnWL16td8q5AUFBdnddf/SSy9ZTCbTC6Io+lDVTJr41LGLomiMiYl57O9///s37r333lk5ooCAAGJiYujo6LArSOB2+upBHgARqW45XG5uLsXFxcTFxc1KfyVFBhEgl7mlM942mx4dHe1wNt1dZGZmYjabOXXqFBs2bEAQBD6c+WFWR6/m6we+zqff+jSfzf8sn8n7zMXUvLMY9dBRbnXgrSesDn10atRTGQQJG6DoS5BUaHXmHt5jHhkZSUVFBRaLxe/W9T55tJnvvXqWwrQo/nJngdO67zMZGxvj5MmTbNy40W7j7sG2g1hEi1+l4Ts7OwkKCiIqyj9Fherr68nNzbX73P/93//19/T0/NzLJvkFPlfa6Ovr+/UvfvGLez/1qU/FzEtbZ2Zy8uRJEhISPH+3qWuAqAxwk1MKCAggIyOD2tpa1qxZM/24XCaQGh207PWtnZ2d1NTUsHbtWqfH2JbLihUrqK6upqKigvz8fARBIDMik3986B/85PhPeLjiYcq6y/jpzp8So/aOTX7DzGjcFpF3nZ4djWfsmk6pE7sG3BiNO4MgCERHR6PT6dBq/WPcTRRFfvduAw++XccVubH87mPrndZ9n8n4+DgnT55k/fr1DvXTD7QeQBukZVWUf6S0TSYTtbW1FBX5Z5Pr0NAQgN0G4FOnTqHT6apFUfShVKl08bljF0WxOz4+/uCbb755w+7du2d5b7VaTWhoKL29vZ6/0PTVQ4x75ztTUlIoLi6e10iXoQmmvmdpI29ms5nKykoMBgPbtm0jIMC9DXiLsXLlSqqqqjhz5sz0GF2QMoifbP8JBbEF/N/x/+OW127hZzt+RmG8/4ubLBmJRePOYlvl6g+O3bbM5a/FTdy4PpGf35yHwgXddxsGg4ETJ06Ql5dHRESE3ddMmCco7ijmw5kf9puUdl1dHWlpaX453gYLb5/77ne/29/R0fEdL5vkN/jcsQN0dXX9z3e+852du3fvnhfmZWdnU1FR4dkLjdkI/edg5YfcelhHjXQZmhD+U92D0WxxaQHF8PAwp06dIiUlhby8PJ9cYARBYNWqVVRWVs5y7gA3ZN/Ampg1fO3A17j3bWvH/L159yIT/Cut6zKiCEOt7zvwVlttfEqFMDId0i+B5EKfRePOEh0dzZkzZxBFUdIOzGS28K2XzvBCaRt3FaXxvWtd0323odfrOX78OGvXrl0wXX288zh6k95v0vAjIyPodDp27Njha1OWxOjoKBMTE0RHz9ceaGhooKSkpFMUxQ+eHKaTSOLqIopibUJCwumjR49etnXr1lnPhYSEEBAQQH9/v+fqRAMt1pToMkfd7BEREUFYWBgtLS3T87CZmhBMFpHW/nEynBjFmTmbvlCq0FvYbliqqqpmpeUBsiOzefbaZ/nRsR/xu/LfUdpdyv077ida7Zo4iKSZjsZPTkXkJ2F0avXpdDT+RclF484gk8mIioqir6/PayUeVzEYzXz56VO8VdXNV69YwZcvz1rSTcj4+Ph0pL7YteVA6wGCFEEUxkk/C2UT1nFVmEpKNDQ0kJVlf3vgD37wg8He3t7/9rJJfoUkHDtAZ2fnN7/97W+/eeDAAbtRe21tLZs3b/bMyd006uaI3NxcDh8+jFarJSgoaLoz/lzv2KKOfXJykvLyclQqlVtm092FLXKvqamhrKyM9evXTzdcBSmDuH/7/RTEFnD/8fu59bVb+dnOn1EQV+Bjq5fAotF4GqTv9Ito3FkSEhLo7OyUpGOfuczlhx9ezZ1FaUs7zugoJSUl5OfnExkZueBrLaKF91rfY1viNgLk3i19LYVz584RFRW16M8lVfR6PcPDw+Tn5897rqOjg3feeWfAYrH82wem+Q2SuQKJoliWkJDQVFlZGTOz2QysUa/FYnEo+rJsbKNu0Z7ZL61QKFi7di3l5eVs3bqVzOktb6NcgWNp1r6+Pk6fPk1OTo4kFcEEQSA3N5e6urrpUTibcxcEgZtX3MzamLV8/b2vc89b9/Cl9V9i75q90k7NGw3QWf7+uNkFFI07S0xMDGfPnpVcOr5/bJK7HjvB2Y5hHrptHdevX9q0zMjICCUlJWzYsMEpZcaqvip69D1+sXt9dHSUtrY2v1SYs9HY2EhmZqbd7979998/PDw8/F1R0osZfI9kHDtYo/b//d//fenll1+elxfLzs6mvr7eM+sG++ohKAaCPDcSEh0dTWho6HRKPjo4wOHIm8Vioa6ujr6+PjZv3uyR2XR3smLFChoaGjhx4gQbN26cNd6XE5XDs9c+yw+P/JBfl/2aku4S7t9+P5GBEogmZkXjJVZH3nl6gWh8NVxAWuqOsCnoDQwMSGZMqnNIzx1/OU7bgJ4/3rGRK1YtbVdBf38/FRUVbNy40ekgYX/rfuSCnB2J0q5Xi6JIeXk5eXl5fqseODk5iU6nY/Xq1fOeGxgY4Pnnnx/W6/XP+sA0v0JSjh04ePz48e6mpqaouYpz0dHR1NTUMDo6SkiI6xKRC6Jr8FgafiYzU/IZmmDO6eZ3xs+cTbenfCVVsrKyUKvVHDlyhI0bN876HQUrg6dT8T878TNufu1mHrjkAdZr13vXyIWicYUaEjfA1i+878hDpN8Z7ini4+Pp7OyUhGO3LXMZ1ht5Ym8hm11c5mLD1qeyZcsWu4InjjjQeoD12vVEBEYs6bzeorGx0a9T8GAtIzgSJfvlL385NjY29lNRFD+YKyZdQFKOXRRFUalUfuuHP/zh3x5//PGImc8JgkBOTg41NTUUFLi5Vqurg5w97j2mHWam5NNjgvlPdc+s5zs6OqitrSUvL89uN6jUSUxMJDg4mJMnT7J69epZkwyCIHBrzq3Tqfm7993Nlzd8mbtW3+WZ1LwowlDb+w78YjTuElqtlpqaGlatWuXTdHxlu3WZC8DTS1zmYrFYqKqqQq/XU1RU5FKfSttIG3UDdXyj4Bsun9ebjIyM0N7e7tcp+ImJCbq6uti5c+e858bGxvjLX/4yMjo6+hcfmOZ3SMqxA5hMptf37ds30NXVFTFX2lKj0dDQ0MDg4KDDeVOX0Q/AuM4rETu8n5KPlBvoG5tkaNxIiEpGZWUlExMTPplNdycRERFs3bqVkpISRkZGyMjImOUYcqNzefbaZ/n+ke/zq9JfUdpdyk+2/WT50dCsaHxKBGZkaovexWjcZeRyOaGhoQwNDbnvb81F3LHMZXJyktLSUqKiopYkq/pe23sAkq6vWyyW6ekUf03Bg3XuPisry26W8pFHHjEYDIbfi6I44QPT/A5Bij0IarX6E3v37v3973//+3m6joODg1RXVzN3LG7JtJ6ER6+A25+Glde455iLYDKZ+N1L7/FQmYEn78zH0tNIamoqqampkmpWWg5ms5nTp08D2K35iaLI0zVP80DJA0Sro3ngkgfI18zvgrWLM9F40iZrg1uyrVP9YjTuKh0dHQwNDTmU9PQk7ljmMjIyQmlpKTk5OcTHxy/Jjk+99Sl04zpevv7lJb3fG1RXVyOTycjJyfG1KUtmfHyckpISduzYMe8aqNfrycrK6uno6MgSRXHERyb6FZIs4BoMhn+8+OKLutbW1nnPRUREoFQq6e3tdc/Jpkfd3Ks6txAKhYJLC6zNId9/+Qz/7g5lX4uZ1093UnZ+gO5hAxaL9G64XEEul7Nu3TrCwsI4evTo9KpSG4Ig8LHcj/HknieRC3LueuMu/nb2b9i90TQa4PxxOPJbePYT8MtceGgNvLAXSh8HRaA1Gr/9H/CNevhKBdz0F9j8aUhYf9GpLxGtVkt3d7fXz/tKeTuffqKUFbGhPPeZrUty6t3d3ZSWlrJhw4YlO/XhyWFKu0olLUrT29vLwMAAK1Z47/rlCaqrq1m5cqXdwOZXv/qVXq/X/+6iU3ceyaXiAURRNCuVyq9885vf/NszzzwzrxNk5cqVnDp1ipiYmOVHuLp6kCkg0j3LX5xhcnISfW8LlyQrOT8isq9ax1BZ56zXBMhlxEcEkhihtv4XOfvf+HA1AQpJ3pdNIwgCmZmZhIaGcuTIEbvjRatjVvPcdc/xveLv8UDJA5R0lfDjtZ8jvKd6Kho/CZ0V70fjEamQtv1iNO4FFAoFQUFBnhsztcMTR5v5/jKWuYiiSGNjI93d3WzdunVZcqqH2w5jEk2SdewGg4HKysp5O+P9jaGhISYmJtBo5o+ODg4O8pvf/GZwYGDgAR+Y5rdI0rGDtdZ+4MCBtqqqqsi5e4RDQkIICwujs7Nz+fPdffVWyU8vOQedTseZM2dYuXIljxfGUVZWhlarJVIbT/uAno5BPW2DetoH9LQP6mkfGOdgfS89IxPMDGYFAbShqilnHzTt9JMi1CRM/X+IShq/XpswT2lpKVlZWbO39RkNhHVV86uADP6uqOHB1v3c2vQOD/ToWGuRT9XGPz/lyAsv1sa9jK073tOO3R3LXMxmM+Xl5SgUCrdMlBxoPUBUYBR5mrxlHccTiKJIWVkZq1evJjAw0NfmLIvq6mpyc3Pt3pz86Ec/GhkfH//RxdWsriHJGrsNQRCKLrvsstf+85//zJu5MRgMHDt2jJ07dy7vD/j3WyAqHT769HJMXZSZs+kbNmyYHrcxGo0UFxdTUFCw4BjfpMlC55DN2c/5d1BP56CBSbNl1nvC1cpZUX5S5JTTn3osOjjAq3f6RqORyuJ9RI03kkwnsvaSedH4mYRVfMN4nh7zOF/bcB93rL7Tr6MRf8doNHLkyBEuueQSj51j1jKXDYn8/CbXl7kMDQ1RUVFBcnIyc0dll4LRbGTnszu5Ku0qflj0w2Ufz93U1dVhMpmYG/T4G319fTQ2NlJYOF+qt6Ojgw0bNrR0d3dnXRxxcw1phHQOEEXxSHx8/NmjR4/umNssFxgYSGxsLOfPn5/WYHcZixn6GyH7yuUbuwDj4+OUlZWh0WhmLYMBUCqVrF+/nrKyMrZt2+awqzVAISM1OpjU6GC7z1ssIr2jE3Yd//m+cY429jE6MftvI1Apm3b0SVPOf6bjjwsLXNK2rGmMBqvjntpwpmwrYf1IBwBmWQDGuHyUtmg8aROExrIWeG5iiO8Wf5eflz5IaW85P9r2I8ICfKuP/0FFqVSiUqk8ox+BdZnLf794hhfLlrbMxWKxUF9fT3d393RPhzso6S5h1DjKrqRdbjmeO+nr66Onp8dv17HaEEWR6upqu9KxAN/61rcGBwYGvn7RqbuOpCN2AEEQVm/YsOG9kpKS6LmRm9Fo5PDhw+zYsWNpGur95+A36+HDv4UNn3STxbPp6Oigrq6OtWvXLjib3tTUxNDQ0KyFKu5EFEWG9abpCL99YHzG/1v/1Y1OznqPXCYQFxY4K+pPmFnvj1CjDphxIzLUNkdT/TSYp44ZkTo1alYISQWMh2VSfuYsoaGh5Obmzvv9iaLIE1VP8FDpQ8QGx/LgJQ+yOma+GtVFPE9LSwuTk5MOV2guFYPRzJeePsXbS1zmMjw8THl5ObGxsWRnZ7tVzOn+4/fzUv1LHLz9IGqF6817nsJgMHD06FG/UKRcjM7OzukbsrnU1dWxc+fO6u7u7tUX5WNdR/KOHSA+Pv7lv/zlL9d96EMfmveX29TUhF6vX1pKqu4t+MctcPc+SHXT+NwUJpOJyspKjEYj+fn5i86mi6LIqVOniIyMdEsqcSkYjGbaB611/plRv63m3zVswDzVra9iktVCM9sDm9isbGCVuZZIsw4AszwQgyYPecpmVOmbEZIKIXS+BKhta11zc7PDG5/ynnK+efCb9On7+EbBN/joyo9eTM17mcnJSY4fP+7WFaDLWebiqSjdhiiKXP3i1eRE5fDby37r1mMvB7PZzNGjR8nJybHbaOZPmM1mDh06xJYtW+z2COzZs6d/3759N4qi+J4PzPN7/MKxC4KQkp2dXVpTUxMz965cFEUOHTrE+vXrCQ2dN/a+MEd/D2/+D3zzHAS7T+ltaGiI8vJyl2fTJf2HO9SGueU4+qZj0HoCdf9Z5FO18R55HGeEFRydzOC4MYtqMQXTVJUnOEBuN9q3pv6D0IaqMBj0lJeXO4zeBw2DfKf4OxxsO8hVqVfxg6IfEBrg4u/6IsviyJEjrFu3zi1R4sxlLg/eku/SMpfh4WEqKirQarVuj9Jt1PbXcvNrN/PDoh9yY/aNbj/+UrDpwIeHh5ORkeFrc5ZNTU0NSqWSzMzMec+VlJRw3XXXHe/s7NziA9MuCPzCsQPExcX95ec///mdn/zkJ+fl3Pv7+6mtrWXLli2uRXOv3QdVL8N/N7vFRlEUaWpqorW1dcl7022ptsLCQoKD7dfTPY5pwlobn6mpPlUbRxFo3XCWvGlWbRysP//AuHEq2h+nzU6T3+C4cdaplHKB+HCrsw9TmAg0j5OfnUxOksY61hcRiEohxyJa+NvZv/Hrsl+TEJLAA5c8wKpo/24c8ieampqwWCx2L8Su0DGo5xOPWpe5/OHjG7g817llLhaLhYaGBrq6usjPz3dqK9tSeaTiEf5Q/gfevfVdYtTSWF3b2NjIyMiIx0p13mRsbGxajMZeoLZ58+a+kydPXiGKYrlvLPR//MaxC4IQlZCQUF1TU6O1F5mfOnWK2NhY18bfHr/W6sQ+9fay7ZucnOTUqVOo1WpWr169LGnHwcFBKioqKCoqmrUpzWMMtU3VxW0qbhUzauMp74+aJW2CuLXLGg0cmzDZGel7/9/uYQNzv5HaUNV0tK8KbuHo6K/Rm4e5e+VXuHvtRwlT+68Er79gMBgoKSlZlhb5zGUuf7mzwOllLt6I0mdy2+u3oZQpeeqapzx6Hmfp6emhvr7er5ZCLcSxY8fIzs62W3p74YUXTF/84hdf6+rqkkaqxE/xG8cOEB4e/vlPfvKTP/3tb387z7NPTExw5MgR1xrpHsiBrMvh+j8sy66Zs+lLVbmaS1tbG+3t7RQWFrr3Dt2ZaDyp4P1GNzu1cU9iNFvoHNRTWtNEZVMnojqCUTFg2vF3DBowMkJgwrMoQuowDuWhHLiVxPDI6c7+xKk0vy3tHxPi3bG+C5Xi4mI2bty4pLnpmctc/ra30KllLhMTE9TW1jI0NEReXp5Ho3QbXWNdXPnClXxlw1f41NpPefx8izE6OkpJScmyxXakQldXF+3t7XbXb4+NjbFy5cretra21aIoukla9IOJpMfd5jI8PPzI888//6XPfe5zK+c2y6lUKtLS0qirq3Oukc4wbF3ZGZ21ZHssFgu1tbX09/e7vApyMZKSkhgeHqa6unp5s6pD7XM01edE46lFbovG3YFSLiMlOpiUbWv40KYV1NfXo9PpyNmeQ2xsLKIIurEJWvsv5+naJ3iLxwmK7CHS/FnaBjQcP9fPyJyxvgCF7H0FPzsqfnHhgSiXM9b3ASEuLo7Ozk6XmztnLnN56lObyVhkmYvRaKSxsZGuri6ys7NZu3at127MDrYdBKSx9MVoNFJaWsr69esvCKduNpupqalhyxb7pfPvf//7oyMjI/dfdOrLx68idgBBEAo2bdq07/jx4/PG31xqpGsvhT9fBrc9BbnXuWzHzNn0FStWeGxEraSkhJiYGOcuprOi8Sk51uF263OKQKtuetImn0XjS0Wv11NTU8PY2Bi5ubmzUnil3aX813v/xeDEIN/a/C1uzr6ZkQmTNb0/o7Zv6+7vGNTTOzJbt14mQOycsb65oj5BAX51D+wR9Hr9tN6Cs7iyzMVsNtPc3DytTZGamur11PNn3/ksrcOtvH7D6z7N8pjNZo4dO0ZGRobbsoC+ZqGGuanxtvru7u5cURTNPjDvgsLvrlaiKJbExcW9/cwzz9z80Y9+dJb9giCwZs0aKisrF2+k0zVY/412fTa3vb2d+vp68vLyiIqaJ4rnNgRBYMOGDRw/fhyVSjW/f2CxaDxl64x942tA4Z+1aLVazfr16xkZGaG6upqGhgZyc3MJCwtjY+xGnrvuOf7n8P/wo6M/oqSrhO9v/T658WHkxttvXjQYzXQOGaab/GaO9JW2DPCv052Y5izhiQxSzpjfD5rn+CODlBd8ul+tVmOxWJiYmHAqgnylvJ2vP1dBbnwYj9+9iegQ++8RRZG2tjYaGhpITExcui7FMhkzjnGi84TPRypFUaS0tJTExMQLxqmPjY3R3d1td2RSFEX27t3b393dfedFp+4e/C5iBxAEIToxMbGqurraYSOdVqudrUk+l3d/DId+Cd/pBIVzaa6Zs+nr1q3zTmMb1pTcseKDrI2xEDFS935E7jAa3wShcQsf1I/p7++nuroatVrNypUrCQoKwiJa+PPpP/OHij+QEprCg7seZEXk0jZemS0iPSOG6Yh/Znd/x1QGYHxy9vUnKEA+S7VvrppfbFggchcU1aRKfX09AQEBpKYuvDTJtsxlc3oUf/6k/WUuoijS3d1NbW0t0dHRrFixYlG9B0/ydsvbfO3A1/jr1X9lU9wmn9ggiiKnT58mMDDQr9ewzkQURY4fP05WVhYxMfOnDF566SXz5z//+VcvNsy5D7907ADh4eFfuPPOO+//zW9+M8+zT05OUlxcTFFRkePI4rk7rcpoXz7l1PmGhoY4deoU6enppKSkeP6OflY0fhKxsxxhVqf6zH3ja/02Gl8q/7+9M4+Lslz7+O8eBhjWGbaZYQc3VFRkEVRQzFYrs9W0rDynxep02q2O1Wt1snIrT5u9p05lp05qvVlHO6dNxQVUFBBQEZQdhllgmA1mf+73D4FQhx0GGO7v5zMfxpnnuZ/rwWF+93Xd131dlFIolUqUlpYiICAAkyZNgqenJ3IbcvH8oedhsBiwJm0Nbp5w86D/X1FKoWm1Xib69ZpWyDQm1GuMULdcXMWPzyOQCn8P90d0SvILEwkQJvLqc9OT4aClpQVFRUW4tMRzO5RSvLfvPN7uoZlL++TM29sbcXFxI6KK2ppDa3Cw/iCylmaBzxueYObZs2dhNpsxY8YMl4kA1dTUoLm52WHp2NbWVsTFxanq6uqmUUqVw2CeSzJqhZ0QwpNIJKf37dt3WSIdcCH7sra2FrNmdTHz3poO+IcDd+/s9jrte9Pr6ur6VwSnN9jMQENRR031rrxxY8gM5Ct4mDnvuuHb4z7CoJSivr4e5eXl8Pf3x7hx42D1sOKFQy/gWMMx3DT+JryY9iK83Z0rHK2Wtm19Drb0yTQXqvhdEu1HsK/nJaJ/ce1+odfIaE978OBBzJkz57KIVU/NXDiOQ0NDAyorK+Hp6Ym4uDintYPtCRtnw4KdCzA/fD7emPfGsNhQWVmJxsZGpKSkuIyoG41GHD16FBkZGQ4jnKtXr9Z/8sknrzQ3N789DOa5LKNW2IGORLqfjx07FujoDyEvLw9SqfTykDzHAW+EArMeAK5d1+X4ZrMZJ0+ehLe3N6ZOnTqgvekXoZNdXFO94eTva+PCqN+LvzjwxjUaDU6ePOky218GC0opGhsbUVFRAZvNhujYaPxb+W98VPgRYoWx2Jy5GRMC+r8DYrCx2jnItabLRV/7+7/Ntou79fl58i9L7gvrFAEI9vXsUwOV/lJaWgpvb29ERkZ2vNa5mcsf0mPw8g2/N3Mxm82orq5GfX09xGIxYmNjR4SH3pkT8hP4w89/wObMzbgm5hqnX18mk6GqqgppaWmD9z0zzLSH4MePH++wkua5c+eQkZFxXqlUTmZr64PLqBZ2AJBKpdtee+21ZQ899NBlseguQ/LN1cDfZgA3bgFS/uBwXJVKhVOnTmHKlCmQSgewXn2ZN34C0NVdeK/DG0/5vQhML9bGVSoVSkpKMHv27GFdkxypGAyGDu9H7avGu+Xvwmg34sW0F7FkwpLhNq9XUErRaLBcFOa/8NPU0cRHZ7pkW58bD2EiwUVJfu3/jhB5QyoUwIM/8CxzvV6PM2fOIC0tDcDFzVyevnoS/rzwwgSqubkZ1dXV0Ol0iI6ORkRExLAkxfWGjcc34uuzX+PQskPwcXduNEwul6OsrMxhFGQ0U11dDY1G4zAEz3EcZs2apc7Pz7+eUnpsGMxzaUa9sBNCfCUSScnx48cjOnsQ7TgMyZ//DfjyNmDlj0DMxZW0OI7D2bNnodFokJiY2Pe96Zd544WAvW17VQ/eeF9oTzpi4t41VqsV9fX1KK4oxrambShtLcXN42/GmtlrRlTHrv6iN1kdtultf668ZFsfIYDET+DQ229/zcezd8KblZWF9PR0mOzAQ1/kdTRzWZ4Shrq6OtTW1sLX1xfR0dEICgoa0aFlSilu2HUDovyj8NFVHzn12q76d9xTCP7tt982rl+//nOFQvHoMJjn8ox6YQcANze3BbNnz/6/w4cPOwzJ5+fnQyKR/B6SP/oR8NPzwLPnAF9xx3EtLS0dGfUTJ07s+cvIZgbkxRdXcWv3xt08L3jjHULeO2+8L8jlcpw7dw6zZ892qZn+UNDU3IQtx7bgB8UPiPCKwPr09ZgWNm1EC85AMdvsaNCYLtvH3z4BaNAaYbVf/Pcv8nbvKOQT1imzv134A30uVPE7e/Ys7Hwv/OWnWpyW6bD22ljE+7ZCr9cjMjISkZGRo0aoKjQVWPLDEryU9hLunHyn066rVCpRUlKCOXPmjJrfVW/oKQR//vx5ZGRkVLXtWTcNg4kuz8iMi/URu92eJZFI9vz973+/c9WqVZctPE+bNg3Z2dkIDg6+EJJvOgd4CgGf3z90vdqb3pM3HpUGRPz59ypuQ5ypLpVKQSnF0aNHkZaW5lJfDoNNUEAQ/nrdX3FN7TV44dAL+MPeP+DOwDuxKGYRpFIpAgMDXaIOd2c8+W6ICfZBTLDj0LKdo1DpzZc17JFpjKhqakH2+Ua0XLKtz8vdDWEiAcQ+fJQrdWg2UTyW4InEQBvCw2MREBAw6iZL+2r3AQAyIzOdds12UXc1Tx24kAXv5eXlUNQ5jsPSpUvVCoXiTibqQ4dLeOwAQAjxkUgkZ3NzcyOioqIue18ul6OmpgazZs0C+WIJYDEAD+6DzWZDcXEx7HY7EhISfvd8bZYL2+GGyRvvC+1rdK74JTEUKFoUeO7gc8hX5uP6iOtxe+DtMGgM8Pf3h1QqhVgsZhEQXPC8tEZrh+hXyDUob1CjulGPRiMHs43Da0viceX03rcmHoms+M8KWDkrdty4wynXaw+/p6WluVwCrNFoxLFjx5CRkeEwn2Lz5s3G9evXf6pUKh8bBvPGDC4j7ADA5/MzU1NTv8vOznYYki8oKEBgYCCi/28REDMPmoXrcfLkSYwbNw6RQjeQ+hO/e+Syk5288ciLS7E6wRvvKwqFoqMOs6t9WQwFNs6GD05+gE+KP8GkgEnYlLkJATQAcrkcSqUSfD4fEokEUql0zG4t5DgOarUaCoUCKpUKXl5ekEqlkEgkEAgEOH36NAIDA0d1dbRGYyMW7lyIR2Y+gkcSHhny6zU0NHQsn7naJJxSipycHMTFxTksRNOWBV+lVCpZCH6IcSlhBwCJRPL5q6++uuzhhx++TN1sNhuOZP2KeYeXQT/uBijdQhFFFHCXF3TtjUfMAvxHxxeXSqXC6dOnMWvWrDErRn3lUN0hrDm8Bha7Ba/MfQWLYhcBuOB5yOVyyOVymM1mCIVCiEQiCIVCCIVCl9mS1BmTyQStVguNRgONRoPW1lYEBARAKpUiJCTksntubm5GRUWFw05do4Xvzn2HtTlr8e3ibxEXOLSV3mpqalBTU4PU1FSXE3XgQnEdAJg8efJl73Ech5SUlKaCgoLrKaW5zrZtrOFywt4Wki/Jzc2NdBSSby47goB/Xff7C6PAG+8LGo0GBQUFSEpKckqbS1dA3iLHcwefQ4GyAEsnLcVzqc/B0+33eaHdbodOp4NGo4FWq4VWqwUA+Pv7XyT4o0nsTSZTx/20i7inp2fH/YhEInh7e3cbYqeUIisrC/Pnzx9V996ZP+/7M0rVpfj5tp+HbDmBUorz589DrVYjOTl5xG75GwiNjY0oLS3F3LlzHf4eN23aZNy4ceM/FArFn4fBvDGHywk7APD5/PmzZs3alZ2dHdg5IUqlUuF0cSEmag7C4hmE2HlLR4033hfaezhPmzbNYUiMcTlWzor3Ct7DZ6c+w+TAydicuRlR/pdPDNtpF/t2YdTpdOA4Dv7+/h2iKBAI4OnpCU9Pz2FJzLPZbDCbzTCZTDCZTNDr9dBoNDAajfD09OwQcKFQ2KOId8WpU6cQEhICiWR0dArsjNFmxPzt83HLxFuwJm3NkFyDUopTp07BZrMhISHB5RI0gQsFiHJycrpsXV1WVoZ58+ZVtoXgzQ6GYAwyLinsACAWiz984okn7nvxxRe9O+9NT0pKgqenZ0dVuoiIiOE2dUgwmUzIzc3FhAkTLu8Kx+iSA7UHsObwGtipHa/OfRXXxlzb63M5jusQ+9bW1g5RNZvNoJSCENIh9AKBoOPh6ekJD48L28h4PB4IIR3PgQviQCkFx3Edz+12O8xm80XC3f7carUCANzc3DrGFwgE8PX1hUgkgpeX16B5p01NTaipqUFiYuKgjOdM9tfsx+P7H8ffr/475oQ5rn0/EDiOQ0FBAby8vDBlypRRnWDYFe27csaNG+dwcmcymTBz5sym0tLSayil+cNg4pjEZYWdEOIuFosLvv7663h3d3dIpVJMmDCh44/LarUiOzsbKSkp8PX1HWZrhwar1Yrc3FyEhYX1rp87AwDQYGjAswefRZGqCMvilmH1rNXwcBv48gzHcbBYLB1CfKkYdxbudiEHcJHQd37uaJIgEAjA5/OdJiLt4fjMzMxR542uzVmLX6p+wcE7D8LdbXB3QVitVpw4cQJisdhh/3FX4dy5c7BYLIiPj3f4/gMPPKD77rvv/qpWqzc52bQxjcsKOwAQQmKio6OL9+/f7+tI2DQaDYqKipCenj5q1wh7wm63Iz8/Hz4+Pi7rNQwFVrsVW/K34IszX2Bq0FRsytyESL/LKxsygMLCQoSFhTnctzxS4SiHK3ZegVRpKjZmbhzUsY1GI44fP45x48a5bEQQuNCh7/Tp00hPT3c4qfv2229tf/rTnw4qlcqrqCsLzQhkdE2x+wiltKqxsfGPq1atanb0uRKJRAgPD8eZM2eGwTrn4Obm1tEtKjc3tyNMy+gedzd3rJ61Gn+74m+o1dfizt134rfq34bbrBFJWFgYZDLZcJvRJ4pURVCb1Lgi8opBHVetVuPo0aOIj493aVG3WCwoLCxEcnKyQ1GvrKzEn//8Z4VSqbydibrzcWlhBwCDwfBNYWHh7i1bthgdvT9u3Di0traivr7e2aY5DUIIpkyZgvDwcOTk5KClpWW4TRo1LIxaiG8Wf4MYYQyeynoKb+W+BaudTY46ExQUBLVajdH0/Z1VmwU+4SM9PH3QxqypqcGpU6eQlpaGoKCgQRt3pEEpRUFBAeLi4hx26bNarViyZIlaLpffTiltHgYTxzwuL+wAoFQqV7311lu1+fmX524QQpCUlITz589Do9E43zgnEhERgYSEBOTm5kKlUg23OaOGcN9wbLtuG1ZMWYGvSr7Cvf+9F/UG150I9hUej4eAgACo1erhNqXXZNVmIVmSDKHnwLeEUkpx+vRpKBQKzJ07d8S1pB1sSkpK4O/v32VS7jPPPKOXyWR/o5QedbJpjDaGTNgJITcTQigh5PJqBd2f9zkh5HYHr6cQQt7tjy2UUpNSqbzxtttua9TpdJe97+7ujuTkZBQUFMBkcu2CSCKRCHPmzEFpaSkqKytHlZc1nLi7ueP51OexZcEWVOuqccfuO7CvZt9wmzViCA0NHTXh+BpdDcq15bgiauBheKvVimPHjoHP5yMlJcUl96h3pq6uDnq93mERGgD48ccf7Tt27DjV1NT0upNNY3RiKD325QAOt/0cMJTSE5TSxwdw/jm1Wv3MPffco3EkZr6+voiPj8eJEyc6spFdFYFAgDlz5qC5uRmFhYWw2+09n8QAAFwZfSV2LN6BSL9IPLH/CWw4voGF5gGEhISgsbFxVEwU99fuBwBkRgys6YtOp0N2djaioqIQFxfn8ompGo0G5eXlSEpKcnivdXV1ePDBB5VKpXIJpdS1v0RHOEMi7IQQXwAZAO4HsKzttQWEkAOEkB8IIRWEkLcIIXcTQnIJIcWEkM57Qq4ihJwghJQRQm7sdP6etuephJAjhJACQkgOISSu7fWVhJDvCCE/EULOEUI2dLLpOp1O9+SePXvIpEmTOOBCm9Y//vGPSE1NRWJiIo4cOYLQ0FAUFhaOii+ogeDm5obExEQIhUJkZ2dDr9cPt0mjhki/SPxz0T+xfPJy/PPMP7Hyp5WQGUaHtzpU8Hg8+Pv7o7l55C+pZtVmYWLARET49S+5jVKK6upq5OfnIykpaUzUiTCZTCgoKEBKSorDBklmsxmLFy9WK5XK5ZRSts43zAyVx74EwE+U0jIATYSQ9mLSCQAeBjAFwD0AJlFKUwF8AqBzqcEYAKkAbgDwESFEcMn4ZwHMo5QmAvgfAG90em8mgDsBTAdwJyEkkhASAuBjALdxHCdtbm4u27t3L7du3TosXLgQubm52L9/P1avXt1RZKGysnJwfhMjGEIIYmNjkZCQgLy8PNTW1g63SaMGDzcPrElbg02Zm1CuLccdu+/AgdoDw23WsBIWFoaGhobhNqNbNCYNCpQF/c6Gt1qtyM/Ph1qtRkZGBvz9/QfZwpGH3W7vqGTpqAcFpRQrV67U1tTUvGWz2cb2H8EIYaiEfTmA7W3Pt+P3cPxxSmlDW1nBcgC/tL1ejAti3s5OSilHKT0HoALApQs6QgDfEEJOAXgHQOfqCHsppdq27kFnAEQDmA3gIKW0klJqampqumLFihWK3bt346233sLMmTOxYMECmEwm1NbWYsaMGZDJZFAqlYPyyxjpCIVCpKenQ6lUoqCgADabbbhNGjVcG3Mtdt64E2G+YXhs32N4+8TbsHJjMzQvFouhVCpHdLTrUP0h2Km9X8Ku1WqRnZ0NsViMxMREl19PBy6IdmFhIcLDw7usU/DOO+8Y9+3b9zMrQjNyGPRPJiEkEMBCANMJIRSAGwAK4EcAnesEc53+zV1iy6XfDJf++68A9lNKbyGExADI6vRe52vY4eAeKaVyQshitVp9NCcnh++oO1VKSgqOHDkCb29vl61M1xl3d3ckJSWhpqYG2dnZSExMHBPeyGAQ5R+FL6//EhuPb8Rnpz9DgbIAGzM3QuojHW7TnIqbmxv8/Pyg0+lGbAOi/bX7EeIVgqlBU3t9DqUUVVVVqK2tRXJyMvz8/IbQwpFFeXk53Nzcuqxc+csvv3BvvfVWmUqluoftVx85DIXHfjuAf1JKoymlMZTSSACVAOb1YYw7CCG8tnX3cQBKL3lfCKB9v9HKXox3FMB8QkgscGHyQSnNs9vt/1myZIm5PXmsoKCg4wSBQIDExEScOHECFoulD6aPXgghiI6ORmJiIgoKCljWfB/wdPPES7Nfwob5G1DWXIY7dt+BQ3WHhtsspzOSs+Mtdguy67OxIHIBeKR3X31msxnHjx+HTqdDenr6mBJ1uVwOhUKB6dOnO3z/3LlzuO+++xpUKtU1lNKx8SU5ShgKYV8OYNclr/0f+pYdXwMgF8B/ATzcFlbvzAYAbxJCCtCLqENbMsdDAL4jhBQC2AEAdrt9mVKpPCeRSLj4+Hi8/PLLF50nEokwefJk5ObmjqnwtL+/P9LT09HS0oIjR46gtbV1uE0aNSyKXYQdN+6A2FuMR/c+ii15W2Djxs5nRyKRQKFQDLcZDsmV56LV1ooFkQt6dbxMJkNOTg4iIyORkJDgsmWnHaFWq1FaWopZs2Y5rCyn1WqxaNGiRrlcfiOldGysWY4iXLpWfG8ghPBCQkL2v/POO3Puvvtuh50gampqIJPJkJqaOuoaXQyUpqYmFBcXIyYmBtHR0S6/pWewMNlMWH98Pb4t+xZJ4iRsmL8BEp/R19q0Pxw7dgxTpkwZcUs5rx99Hf8u/zcOLTsETzfPLo8zm80oLi4GIQTTp0+Hh8fAGwCNJnQ6HfLy8rpsw2q327Fw4cLmgoKCR3Q63Y5hMJHRA2NLpRxAKeVUKtWNTz/9dG1eXp7DY6KiohAUFISTJ0+OudB0UFAQMjIyoNfrmffeBwR8AdbOWYs3572JEnUJ7th9B7Lrs4fbLKcwErPjKaXYX7sf6WHp3Yp6u5ceHh6O5OTkMSfqRqMReXl5SElJcSjqAPD000/rS0pKPmWiPnIZ88IOAJRSvVKpvHrJkiXKuro6h8dMmDABHh4eKCkpcbJ1ww+fz8f06dMRFxeH3NxcVFVVjbkJTn+5cdyN2H7jdgR5BeGR3x7Bu/nvunxoXiqVQi6XD7cZF3FGfQbKVmWXYXiLxYITJ06goaEB6enpCA0Nda6BIwCLxYLc3FwkJCR0mUvw6aefWrZv335cpVI952TzGH2ACXsblNIKuVx+68KFC5scFdkghCA+Ph5GoxHl5eXDYOHw09l7z8nJgaPyvIzLGScch3/d8C/cPOFmfFz8MR785UGoWl23hoe7uzs8PT1HVLOhrNos8AgP8yPmX/R6e7GZ7OzsMeulA4DNZkNubi4mT56MwMBAh8f8+OOP9hdeeOGcUqm8iVWWG9mM+TX2S/H19b150qRJn2ZnZwc4CkVxHIdjx44hMjLSpdsy9oRGo8GpU6cgFAoxefJkh9WoGJfz7/J/4/Wjr8OL74X189djdujs4TZpSKiurobFYsHEiROH2xQAwB2774A33xvbFm3reK39MywSiRAXFzdmP8McxyE3NxdhYWGIiopyeMzRo0exZMmSKqVSmUIpbXKyiYw+wjz2SzAYDN9XVVW9eOONN2ocZcLzeDzMmjULlZWVY6aAjSNEIhHS09Ph7++Pw4cPo7a2loXne8FN42/C1zd8jQDPADz0y0P48OSHsHOuV6s/NDR0xKyzywwynFWf7ShK095L/PTp05gxYwamTZs2ZkWdUoqTJ08iKCioS1EvKSnBLbfc0qBUKjOZqI8OmLA7QK1Wby0uLv7g3nvv1ToSKz6fj9TUVJSUlKCpaex+ztv3vaenp6O5uZmF53vJeNF4/OuGf2Hx+MXYWrgVq35dhUZj43CbNah4eHiAz+ePiGTLrNosAEBmZGZH2D0oKAhz584dcZn7zoRSilOnTsHT0xMTJkxweEx9fT2uueYalVwuv5pSWuNkExn9hIXiu4AQQsRi8T/uu+++OzZs2OCw9JzJZMLRo0cxffp0BAUFOdvEEUd7aNPf3x+TJk2CQHBpiX/Gpew6twtvHHsDvh6+WD9vPVJDU4fbpEGjsrISHMdh/PjxPR88hDz0y0Oo19XjBckLCAgIGNNh93bae8hzHIfp06c73Mba3NyMtLS0poqKiiU2m21sbOlwEZjH3gWUUqpUKh/4/PPPD2/ZssXo6BiBQIC0tDQUFxdDrVY728QRR3t4PigoCEePHkVJSQms1rFZN7233DLxFvzrhn/B190XD/76ID4q/MhlQvMjIRxf31iP3IZcxAviMXPmzDEddm+HUoozZ87Abrd3KepGoxFXXXWVWiaTPcBEffTBhL0b2va43/zGG2+c2r59u0OF8vLyQlpaGoqKikZFy8qhhhCC8PBwzJ8/HwKBAIcPH0Z5eTnr+d4NEwMmYseNO7AodhE+OPkBHvntETQZR/8ST3vExmS6tHDk0NPS0oK8vDx8m/ct7LBjeeryMVUOtisopR0T7hkzZjgUdZvNhsWLF2sqKytfMhgM3zvfSsZAYcLeA5RSs0qluvKJJ54o/+mnnxyqk5eXF1JTU1FYWMg89zZ4PB5iY2Mxb9482O12HDx4EDU1NSzBrgu83b3xZsabWDtnLfIUebhj9x04Lj8+3GYNGGd77WazGUVFRcjLy0NkZCRkXjIECgIxI3iG02wYqbR76haLBQkJCQ5FneM4rFixQltUVPSBWq3eOgxmMgYBJuy9oK2Azbx777238tdff3W4f9Pb27vDcx/LCXWXwufzMWnSJKSnp0Ov1+PAgQOora0Fx7FtsJdCCMHtk27Hv274F7zdvfHALw/g46KPwY3iLcNhYWFOaQpjMplw+vRpHDlyBIGBgZg3bx4CggNwqP4Q5kfMhxtv7NR5d0T7mrrNZutW1O+9917tvn37tqlUqpcdDMMYJTBh7yWU0kaVSjV3xYoVVfv27XP4Tdseli8uLkZjo2tlOQ8UDw8PxMfHY/bs2dDpdDhw4AAqKytZiN4BcYFx2HHjDlwbfS3eLXgXj+59FM2m0bnM4+XlBY7jYDabez64H7S0tKCwsBDHjh2DUCjE/PnzERERAUII8hX50Fv0vW764qq0Z79zHNdl+J1Sivvvv1/3yy+/fKVSqZ5kLVhHNywrvo8QQiRisfjIzp07ozMzMx1OjNqz5adOnQqxWOxsE0cFVqsVlZWVqK+vR0REBGJiYsZ8UtOlUErxTdk3WJ+7HiKBCJsyNyFRnDjcZvWZc+fOwcPDA9HR0YM2pk6nw7lz52A0GjFhwgRIJJLLBGt97np8U/YNDt55EN7u3oN27dEEpRRFRUXg8XiYNm1al6K+atUq3Q8//LBDqVSuYqI++mHC3g8IIaFisThn586dUV2Ju9lsRm5uLmJjY8d0hbqesNlsqKmpQXV1NSQSCcaNG8e2yV1CSVMJnjnwDGQGGR5Pehwr41f2up/4SKClpQVFRUWYM2fOgMahlEKtVuP8+fPgOA4TJ05EUFBQl2K16LtFmCCagPevfH9A1x2t2O125OXlQSgUYtKkSV3+nh5++GH9999//61SqbyfibprwIS9n7SL+9dffx21cOFCh9+yNpsNx48fh1gsHva9vCMdjuNQV1eHqqoq+Pj4IDY2FgEBAaxNbBsGiwFrc9bil+pfMD9iPtalr4NIIBpus3rNgQMHMHfu3H5FZex2O+rq6lBdXQ0fHx+MHz8eIpGo23PKmstw279vw9o5a3H7pNv7afXoxWq1Ijc3F+Hh4YiJiXF4DMdxeOCBB3Q//vjjN0ql8kEm6q4DE/YB0BaWz/nyyy9jrr76aofiznEcCgoKIBAIMHXqVCZUPUApRXNzMyoqKtDa2oro6GiEh4eDz+cPt2nDDqUU20u3Y+PxjQjyCsLG+RsxUzxzuM3qFaWlpfD29kZkZGSvzzEYDKiuroZSqURYWBiio6N7Hc35e9Hf8V7Be9i/dD+CvYL7a/aoxGQyITc3FxMmTEBYWJjDYziOw8qVK3U///zz10ql8hEm6q4FE/YBQggRh4SEZG/btm3cokWLHIp7e0aqxWLBzJkzweONnjDqcGIymVBTU4P6+noEBQUhJiZmTJcAbed042k8c+AZKFoUeDL5Sdw79d4RP2HU6/U4c+YM0tLSuj2O4zjI5XJUVVUBAGJiYiCVSvv8N7N8z3LwCA9f3fBVf00elRgMBpw4cQLTpk1DcLDjCY3dbsc999yj/e233/6pUqkeZ6LuejBhHwQIIcEhISGH33333XHLli1zGGuklOL8+fNQq9VITk5mHmgfoJRCqVSiqqoKZrMZYWFhCA8Ph6Pue2MFnUWH/8n+H+yt2YsFkQvwevrrEHoKh9usbsnKykJGRsZln/32KE1tbS3UajXEYjGio6Ph6+uwknOPKFuVuPKbK/F44uN4cMaDg2H6qKC5uRknT55EUlIShELHnwWz2YzbbrtNk5ub+w+VSrWaibprwoR9kCCE+IWEhOz9y1/+Mu2pp57qUnFqampQU1OD1NTUMdn3eaBYLBbIZDLU1dWBx+MhIiICoaGhYzKjnlKKr0q+wua8zRB7ibEpcxOmh0wfbrO6pKSkBP7+/ggPDwdwwYuvq6uDXC6HUChEREQEQkJCBhx9+KbsG7x25DXsumkXJgQ4bm7iaiiVSpw5cwapqanw9na8A0Cn0+Gaa65pPnfu3OtNTU1vO9lEhhNhwj6IEEI8Q0JCvr/vvvsyNmzY4NvVF5RcLsfZs2eRkpLSb6+EAbS2tqKurg4ymQw+Pj4dwjDWoiHFqmI8e+BZKI1KPJ38NFZMWTEiQ/NarRZnzpyBWCxGfX09PDw8EBkZCYlEMqj/Z4/+9igqtZX4z63/GZG/h8GmfVdJamoqPD09HR6jUChwxRVXqOvq6v6k0+m2O9lEhpNhwj7IEEJ4ISEh/7jqqqtu+eKLL4RdfWFpNBqcPHkS8fHxCAkJcbKVrgWlFFqtFvX19VCpVBAIBJBKpZBKpWNm65zWrMXL2S9jf+1+XBl1JV5Lfw3+HsOfj0AphUajgVwuh1KphMFgwOTJkxEREdGlCA2EVmsr5m2fh6VxS/F86vODPv5IguM4nDlzBkajEYmJiV1OjsrLy3HllVc2ymSyOy0Wyz4nm8kYBpiwDwGEEBIcHPxaQkLCY7t37xZ1tRZsMplw4sQJhIWFITY2dkx4F87AYDBALpdDoVDAbrdDIpFAKpXC39/fpX/HlFJ8ceYLbMnbAomPBJszNyM+ON7pdtjtdqhUKsjlcqjVagiFQkilUojFYpSVlSEwMBChoaFDcu291XvxZNaT+PTaTzFLOmtIrjESsFgsyMvLQ2BgYJd71AGgoKAAN954o1wmk11PKS1wspmMYYIJ+xASGBj4SExMzLq9e/cGBAQEODzGbrejqKgIhBDMmDGDZcwPMhaLBQqFAgqFAnq9Hv7+/ggODkZwcDC8vb1dUugLVYV49sCzaDQ24tmUZ3HX5LuG9D45joNGo0FjYyMaGxthsVgQEhICiUSCwMDAiz7T7VsZk5OTh8SWFw+/iKzaLGTdmQV3nmvmXej1euTl5SEuLq7bCdLevXu5u+++u06hUFxBKa1woomMYYYJ+xDj4+NzS3h4+Mf79+8Pak8auhRKKSorK9HQ0ICUlJQhCVEyfg/ZNzY2oqmpCa2trS4r9BqTBi9mv4iDdQdxdfTVeHXuq/DzGJy2pY6EXCQSITg4GEFBQd3uVqCUIisrC5mZmYM+ibVzdizYuQDp4el4a95bgzr2SEGhUKCkpARJSUndbv3cvn279fHHH69QqVSZlFKFE01kjACYsDsBPp+fLpVKv/vhhx/E3Xkq7ZmtiYmJXW5XYQwejoTe29sbIpEIIpEIQqFwVK/Rc5TDttPb8Lf8vyHMNwybMjdhatDUPo1BKYVer4dWq4VGo4FWq4XNZuu1kDuiuLgYYrEYEomkT+f1RL4iH/f9dB82Zm7EdTHXDerYww2lFOXl5VAoFN1O/imlWLduXcu77757WqVSXUUp1TvZVMYIgAm7kyCEjA8JCflly5YtkXfddVeXMUKDwYC8vDxMmDABXXn4jKGBUorW1lZoNJoOETObzfD29oZQKIRIJIKvry+8vb1H1ZJJgbIAzx54Fs2mZjw/63ksjVvqMDJhtVphMBig1+s77t9ut8PX17fj/kUi0YC3FjY1NaGmpgaJiYPb0Gbzic34suRLHLrzEHw9XGe3id1ux8mTJ8Hn8zF9+vQuP3tGoxHLly/X5OTkfK9SqR6ilFqdbCpjhMCE3Ym07XXffe+99yZv2LDBt6s/UKvVivz8fHh7e2Pq1KlwcxvbvaSHE0opjEZjh9AZDAa0traCUgqBQABfX1/4+vrCx8cHvr6+EAgEIzKc32xqxl8O/wXZ9dm4MuJKPDbpMVATRUtLCwwGA2w2G/h8Pnx8fODn59cRsRiK+gCUUuzfvx8LFiwY1AnS4l2LEeYbhv+9+n8HbczhRq/XIz8/H9HR0V3WfAeA+vp6XHvttWqZTLZWrVaPza43jA6YsDsZQghPLBa/PX369Ht37doV4OfneN2zfd29rq4OSUlJbL/7CINSCpPJBIPBAIPB0CGQZrMZlFIQQuDp6QmBQNDxUyAQwN3dHXw+/6KHm5tbvyYDHMfBbrfDZrPBarV2PDebzTCZTDCZTB3PrVYrOMphn2Efdqt3QyKQ4KUZL2G6dDp8fX2dXuCnsLAQYWFhg7bVs1JbiZu+vwlr0tZg+eTlgzLmcFNbW4vy8vIel+aOHTuGW2+9VaFQKO6w2WyHnGgiY4TChH2YEAqF90gkknd++umnoHHjxnV5XPt+9wkTJrD2r6MIjuNgNpsvEtl2gbXZbB2PdjHuD4SQyyYJfD4fHh4eHROJ9kmFu7t7x+QhT5GH5w48B41ZgxfSXsDtE293epRBpVJBJpMhISFhUMb79NSneCfvHfx6+6+Q+kgHZczhwmazoaioCJRSJCQkdFu857PPPrO88MIL1Uql8mpKabUTzWSMYJiwDyOEkGSpVLr7q6++knTV+hW4EJovLCwEn8/HtGnTxlxlNcbg02RswprDa5Ajy8H1sddj7Zy18HZ3XIp0KOA4DgcOHMCCBQsGZVJx73/vhclmws7FOwfBuuFDq9WioKAA48aNQ1RUVJfH2e12PPnkk/qdO3ceVSqVt1BKW5xoJmOEM3oygFwQSmmeXC5PWrZs2ZktW7aYuppkubu7Izk5GQEBAcjOzoZOp3OypQxXI8grCFuv2orHZj6Gn6p+wp177kRZc5nTrs/j8SASiaBWqwc8ltqkxknlSSyIXDBww4YJSimqqqpw8uRJJCcndyvqGo0GV1xxRfOOHTs+VCqV1zJRZ1wKE/ZhhlIqV6lUKW+++ea/lyxZoulKtAkhiI6ORmJiIgoKClBdXQ0WbWEMBB7hYVXCKnx89ccwWA2468e78N2575z2uQoLC4NMJhvwOAdqD4CC4orIKwbBKudjtVqRl5cHrVaLjIwMdJV3A1xYT09ISFAVFBSsUiqVL7DubAxHMGEfAVBKzQqF4s4DBw48MWPGjMa8vLwuj/X390d6ejrUajWOHz8Os9nsREsZrkhqaCq+WfwNZopnYm3OWrx4+EW0WluH/LohISFobGwc8EQiqzYLEm8JJgdOHhzDnIhSqcThw4chlUqRkJDQ5Q4YjuPw1ltvGW+66aaSmpqa2Xq9/hsnm8oYRTBhH0Fotdovqqur5y5atKjs7bffNnb1hcfn85GYmIioqCjk5OSgvr7eyZYyXI1gr2D871X/i0cTHsWeij1Y/uNynG8+P6TX5PF48Pf3h0aj6fcYJpsJRxqOYEHk4KzVO4v2vJmKigrMnj2728TYxsZGLFy4sPmdd975UqlUzmTlYRk9wYR9hEEpPadSqWasX79+5zXXXNPc3RqkVCpFeno6FAoF894ZA8aN54ZHZj6Cv1/zd2jMGtz1n7vww/kfhvSaAw3HH2s4BqPNiIWRCwfRqqFFpVIhOzsbAQEBSEtL67Zy38GDB+nMmTOVubm5KxUKxUOUUosTTWWMUpiwj0DaQvMrc3JyHkpISFDl5OR0Gav08PBAUlISIiMjmffOGBRmh87Gt4u/xbTgaXgp+yW8nP0yjDbjkFxLLBZDpVL1Oxy/v3Y/fNx9kCJNGWTLBh+bzYbCwkKUl5cjLS0NUVFRXUYZ7HY71q5d23L77bcX19fXp7S2tv7byeYyRjFM2EcwLS0t39bV1aXefPPNJevWrWvlOK7LY9u9d7lczrx3xoAJ8Q7Bx1d/jFUzVuGH8z/grh/vQoVm8CPAbm5u8PHx6ddOD45yOFB3AOlh6fBw8xh02wYTlUqFw4cPQyQS9eily+VyZGRkqLdu3fqJSqVKppTWOtFUhgvAhH2EQymtUqlUM999991t6enp6urqrmtQeHh4IDk5+SLvnSXNMvqLG88NjyU+ho+u+ghqkxrLflyG3eW7B/06/Q3Hn2o8hUZjI66IGrnZ8O1r6efPn0daWhqio6O7zQXYtWuXLSkpSZ6Xl7dcqVQ+SSntX/UixpiGCfsogFJqVSgUjx4/fvzmtLS02o8++sjcnWC3e+9KpRJHjx6FwWBworUMV2Nu+FzsvHEnpgROwZrDa/BKzisw2UyDNr5EIoFC0ffOolm1WXAjbpgXPm/QbBksKKWoq6vr8NJnz57drZfe1NSEJUuWND/yyCO/NjQ0TLNYLL840VyGi8Eqz40yCCE+YrH4/fHjx9+0ffv2wO4KWQCAWq3GqVOnEBwcjEmTJrGqdYx+Y+Ns+ODkB/ik+BNMDJiIzZmbESuMHZSxjx07hqlTp3a7h/tSbvnhFgQIAvDptZ8Oig2DhU6nQ3FxMXx9fTFlyhR4eHS/TLBr1y7bn/70pyatVvtYS0vLt04yk+HCMI99lEEpbVEoFH/Izc29JTU1tUfvPTAwEPPmzYOXlxcOHToEmUzGwvOMfsHn8fFE0hP48MoPoWpVYdmeZfhPxX8GZey+huNr9bU4rzk/oorSWK1WnDp1CkVFRYiPj0dCQkK3ot7U1ISbb75Z88gjj/zW0NAwjYk6Y7Bgwj5KsdlsBxUKxZRXXnlle0ZGhrqmpqbLYwkhiI2Nxdy5c6FUKnHkyBHo9XonWstwJeZFzMM3i79BXGAcnj/0PP565K8w2weWrCmVSvsUjs+qzQIALIhYMKDrDgaUUtTW1uLw4cPw8/NDeno6RCJRt+d8//339unTpyt+/fXXh+Ry+SJKaaNzrGWMBVgo3gVwc3NbEBIS8s9XX31V/NBDD3n0VKijPTwfFBSEuLg4Fp5n9AsrZ8V7Be/hs1OfYXLgZGzO3Iwo/+6XhrrjyJEjmDFjBnx8fHo89v6f74fapMauJbv6fb3BoD3s7ufnh8mTJ/cYdler1bj//vs1R44cyVUoFHczQWcMBUzYXQRCiK9EIvkwMjLyhm3btgVOnTq12+MppaiurkZlZSViY2MRFRUFHo8FcBh950DtAbyY/SJsnA2vzn0V18Zc269xqqurYbFYMHHixG6P05q1yNyRiT9O+yMeT3q8X9caKEajEaWlpTAYDJg2bVqPHjqlFNu2bbOuWbNGrdPpnjAYDDucYyljLMKE3cUghMwSi8X/XLp0adgbb7zh11MyktVqxfnz56FQKDBx4kSEhYWNqtKcjJFBg6EBzx58FkWqIiyLW4bVs1b3eW+52WxGbm4u5s3rPst9T8Ue/OXQX/DV9V9hRsiMgZjdZywWC86dO4fGxkZMmjQJUqm0x7+XwsJCrFy5sqmhoWG3QqF4ilKqcY61jLEKE3YXhBDC8/f3f8TX1/d/Nm7cGLh8+XJ+T18+JpMJZWVl0Gg0mDx5MsRisZOsZbgKVrsVW/K34IszX2BK4BRsztyMSP/IPo2Rk5ODxMTEbreGPXvgWeQp8rD3jr3gEedEmWw2GyorK1FXV4fx48cjMjKyR0HXaDRYvXq1bvfu3TUKhWIFpbTQKcYyxjxM2F0YQkiQRCJ5LzIy8prPP/88KD4+vsdzWlpaUFJSAovFgqlTp/YYYmQwLmVfzT68lP0SKKV4Lf01XB19da/PraysBMdxGD9+vMP3rXYr5u2Yh+tirsMrc18ZJIu7huM41NTUoLKyEpGRkYiNje2yA1vnc7Zt22Z98cUX1QaD4UW9Xv8pa6/KcCZM2McAhJCUTuF5/97sFdZoNCgpKQGfz8eUKVPg6+vrBEsZrkK9oR6rD6xGcWMx7p5yN55OfrpXoXmTyYQTJ04gIyPD4fs59TlY9dsqvL/wfWRGZg622R1QStHQ0ICysjJIJBJMmDAB7u7uPZ5XWFiI++67r6mhoWG3UqlkYXfGsMCEfYzQFp5/2NfXd+0bb7wRcM8997j3JllOpVKhtLQUAoEAEydOhFAodIK1DFfAarfi7by38WXJl5gWNA0bMzciwq/r9qTtHD58GCkpKRAIBJe9t+7oOvxQ/gMO3nkQAv7l7w8UjuMgk8lQXl4OkUiEuLg4h3ZcSmNjI1544QXd7t27a5RKJQu7M4YVJuxjDEJIoFgsfksoFN7yzjvvBF5//fW83iTLNTU1oaysDIQQTJw4EUFBQU6wluEK7K3ei5ezXwYI8Hr661gY1X2L1fLycvB4PMTGXlzVjlKKa/7vGkwNnIq/LfzboNpot9tRU1OD6upqhISEYPz48b0SdIPBgPXr17d8/PHHzXq9/i+tra1fsbA7Y7hhwj5GIYRESaXSd0NDQzM++OCDoDlz5vTqPI1Gg3PnzsFisWDChAkQi8Usi57RI7X6Wjx74FmcaTqDe6beg6eSnoK7m+PQdmtrK06ePIm5c+de9HpJUwmW7lmK1+a+hlsm3jIodlmtVlRVVaGurg5hYWEYN25cr0LuFosFH374oWnDhg3a1tbW9Vqt9gPWK50xUmDCPsYhhMRLpdIPp0yZMu3999/vcf97OwaDAefPn4dOp8P48ePZNjlGj1jsFmw6sQlfn/0aM4JnYGPmRoT5hjk89tChQ0hLS7uo4MvWk1uxtXAr9i/djyCvgUWMzGYzKioqIJfLER0djaioqF4VauI4Dl999ZXtpZdeam5tbf1HY2PjOkop67LEGFEwYWcAAAghcyUSyUeZmZmRmzZtEkVG9m6bktFoRHl5ORobGxEVFYXIyMheeTyMscvPVT9jbc5auBE3vJHxhsMkuHPnzsHDwwPR0dEdry3dvRQCvgBfLPqi39fW6/WorKyEWq3GuHHjEBER0avCTJRS/Pe//+WefPLJZp1O94NCoXiBUqrqtyEMxhDChJ3RASGE8Pn8G4KCgt697bbbgl9++WU/qVTaq3MtFgtqampQW1uLoKAgxMbG9qlTF2NsUaOrwTMHnsFZ9VmsjF+Jx5Mehzvv9wlhS0sLiouLMXv2bACAvEWOq7+9Gk8lP4U/Tvtjn65FKYVcLkdlZWVH3wSJRNKrCBOlFIcOHcJTTz3VJJPJcuRy+Z8ppdV9u1sGw7kwYWdcBiHETSAQ3CUUCl+99tprA9auXSsaN25cr86llEKhUKCyshIAEBMTA4lEwsrVMi7DbDdj4/GN2FG6AzNDZmJj5kZIfX6fSB44cABz586Fu7s7tp/djnXH1uGHm3/AOGHvPotmsxk1NTWoq6tDcHAwYmNje71tk1KKPXv20JdeeqlJpVLlNTQ0PEspPdWvG2UwnAwTdkaXEEJ4fD7/xuDg4LdSU1Mlr7/+euD06dN7fb7BYEBVVRVUKhVCQ0MRHR3dbUUxxtjkv5X/xSs5r8DDzQPrMtZhfsR8AEBpaSm8vb0RGRmJh399GPWGeuy+ZXe3Y1FK0djYiOrqarS2tiIqKgrh4eG9Xh6y2WzYsWOH/ZVXXmk2GAx75XL5i5TS8gHfJIPhRJiwM3qEXIhZzg8NDd04ceLEcW+++WbQpRnL3WG32yGTyVBdXQ0+n4/IyEhIpdIeK3gxxg5V2io8c+AZlDWX4f5p9+OxxMdgbDHizJkziE+Mx7wd87Biygo8k/KMw/NbW1tRV1cHmUwGoVCImJgYiESiXid0mkwmfPrpp5b169drTSbTd0ql8jVKae8bxDMYIwgm7Iw+QQhJCg0N3SCVShPeeOONoGuvvZb0JRter9ejrq4OcrkcQqEQERERCAkJYRn1DJhsJqw/vh7fln2LJHESNszfgJLjJTBGGvHc4efw+XWfI1mS3HG8xWKBTCZDXV0deDweIiIiEBoa2qfkTb1ej/fff9/43nvv6a1W66eNjY0bKKXNQ3F/DIazYMLO6BeEkEmhoaFv+vj4zF+9erVwxYoV7t7e3r0+n1KK5uZm1NbWQq1WIyQkBBERERAKhUzkxzh7KvbgtSOvQeAmwCPRj+Co7ijym/ORtTQLoIBCoUBtbS3MZjPCwsIQHh7e5yWeiooKvP3227pvv/22xWKxbGlubv6AUtoyNHfEYDgXJuyMAUEIkQQFBT3B5/P/sHTpUu+nnnrK/9KKYT3BcRyUSiXq6upgMBg6vqx9fHyGyGrGSKdCW4Fnsp5BuaYcbsQNV4ZdibuD7oZGo4FEIkFERAT8/f37NCbHcfj111+xbt26xvPnz8uamppet1gsuyiltiG6DQZjWGDCzhgUCCHu7u7utwYFBb00adIk6erVq4MWLVpE+rqObrVa0dDQAJlMBpPJBLFYDKlUioCAAObJjyGsVitqGmqwuWAzDmkO4ZnYZ7A4fjECAwP7/DloamrCP/7xD9OHH36oN5vN++Vy+euU0uIhMp3BGHaYsDMGnbZqds+5ubkteuCBB3xWrVrlHRoa2udxbDYbVCoV5HI5NBoNRCIRpFIpQkJCelUljDG6aGlpgVwuh0KhgM1m65jUFVUUYWLoRPTlM0QpRU5ODjZt2tR05MgRvdFofFen031KKdUO4S0wGCMCJuyMIYMQ4u3t7X23v7//s5MnTw589NFHAxcvXszrTXONS2lfk5fL5VCpVPD09IREIoFEIkFf1vYZIweO46DRaDr+Tz08PCCVSiGVSi9aM29ubkZFRQWSk5O7Ge0CtbW1+OKLL4yffvqpwWQy5cpksjcAHGGNWRhjCSbsDKdACIkXi8WrCCG3Z2Zmeq5atSowMzOz31ve2r07lUoFo9EIkUiEoKAgBAcHM6EfobQLeVNTExobG2E2myEUCiGRSCAWi7uMwlBKkZWVhczMTIeFjjQaDXbu3GnbunVrs0KhkGu12g9aW1t3sF7ojLEKE3aGUyGE8ACkh4WFPQbgiltvvdXzgQce8J8xY0a/19A5joNWq+0QDCb0I4P2/5fGxsaLhDw4OBjBwcF9ymQvLi6GWCyGRCIBcKGq3J49e+jWrVubTp8+bTCbzZ81Nzd/RimtHar7YTBGC0zYGcMGIcSTx+NdFxoa+qSnp2f8ypUrfVesWOHV16z6S+ksKE1NTTAajfD394dIJIJIJIJQKGRr9IMMpRQmkwkajabjYTKZIBKJEBwcjKCgoAFNsJqamlBRUYGWlhZ8/PHHzfv27TNRSncpFIqPWCIcg3ExTNgZIwJCiNDLy2tpQEDAKk9Pz+hbb71VcMcdd/jOmjVrwHXmOY6DXq/vEBydTge73Q4/P78OoRcKhawrXS+hlMJoNHb8PrVaLUwmE7y8vCAUCjsmUINRPlin0+Hnn3+mX331lfr48eN8AL/KZLL3ARyilHIDvgCD4YIwYWeMOAghfjwe7+rQ0NA/2O321MzMTLe77ror6Kqrrhq0sHq72Gu12g5xstvt8PHxga+v70WPsSr47QJuMBjQ0tICg8EAvV4Ps9kMLy+viyIgg9kDoKamBt9//731yy+/1NTW1rZwHLdLqVR+DSCPiTmD0TNM2BkjGkKIG4DZEonkbkLIDRMmTPC6++67AxYvXswPDw8f1GtxHIeWlpYOEWsXNKvVCjc3N/j6+nYIv4+PD7y8vODu7j6q99dzHAez2YzW1taLBLy1tRUA4OXlddF9+/r6oj+7GnqyIS8vD998843hu+++MxqNxlqtVvvPlpaWXaxFKoPRd5iwM0YVhJAJQqHwdh8fnzv5fH74vHnzeDfccEPgggULSH/2yvcWm812kfC1tLTAZDLBYrEAAHg8HgQCATw9PSEQCC56uLu7g8/nw83Nbcgb31BKYbfbYbPZYLPZYLFYYDKZLnqYzWaYzWYAACGkw87OUQovL68ha7XLcRyKioqwd+9ey+7duzWlpaUcn8/Pl8lkn3Ec9wulVDckF2YwxghM2BmjFkKIB4BZgYGBiwQCwWJ3d/fQjIwMtxtuuCFgqIX+Uux2O8xms0MRtVqtHULLcRdHknk83kWi3+79E0IuigRQStH+t0op7RjPZru8Giqfz+8Y08PD47KJhkAggIeHh9MiDZcIuba0tNTu7u5eqFQqvzObzXsBVLB95gzG4MGEneEydCH0vIULFwakpKTwpkyZMuLWyzmO6xBou91+kXi3/+ws8u3P3dzcOgR8pC0FaDQa5Ofn49ixY+ZffvlFe/bsWY4JOYPhPJiwM1wWQogngBRfX9+5AQEBV1qt1qlCoVCQmprqNn/+fFFKSgovPj5+xIn9aKK5ubldxE0HDx7UnzlzhtpsNjWPx8uVyWS/UUqPAjjPhJzBcB5M2BljCkKIL4CZPj4+swMCAhbabLZp/v7+gtTUVN7cuXMD4uLieJMmTUJ4ePiI84SHE7PZjPLycpSVlaG4uNh06NAhXUlJCbHb7Y2EkGMNDQ17KaV5AMoopfbhtpfBGMswYWeMeQghPgBmuru7zxSLxcmEkGk2my3My8vLY8KECTQhIcFr2rRpvnFxcWTSpEkIDAwcbpOHBLvdjtraWpSVleHs2bO2wsJC3alTp2wymQw2m63F3d293GQynVSpVPkACnBBxNn2MwZjhMGEncHoAkKIO4BYAJP8/PziRSJRMsdxUyilQZ6envyQkBAaGRnJi4mJ8YiJifENCwvjhYWFITQ0FFKpFJ6ensN9CwAurNPrdDrIZDI0NDSgoaEBdXV15srKytbq6mprfX09NBoNsVqtJnd391q73V6sUChO2O32UgBlAJS9CaUTQm4GsAvAFErpWUJICIA9ADwAPA5ACuA1AHJK6RX9uRdCSBaAZymlJ7o5pgpACqW08ZLXHwbQSin9ghDyOYA9lNJvCSGfAHibUnqGELKGUvpGf2xjMEYKTNgZjH7Qtr8+BEAogDBCSGhQUNB4Ly+vcQAirFarlMfjCfh8vruHhwf8/Pyon59fe5U7N5FI5CYSidyFQqG7SCTyaN8fzuPxLnoQQsBx3EUPu92O1tZW6HQ6qtFozFqt1trc3GzVarWcVqvldDod1ev1pKWlhWez2exWq9XG4/G0bm5uMrvdXqPX68v1en0VgIZOD91A18EJITsAhAHYRyldSwhZBuAqSukDbe//BOB1SunhXo7Hp5TaLnktC/0U9kuO+Rxtwn7J6wZKqW9v7GMwRiqsYDaD0Q/a1pHlbY+C7o5t8/x9Afh1+tnxnMfj+fv5+QV5eHh4E0LcCCG8tp9uANwA2DiOs1NK7ZRSO8dxdrPZrDEYDM0A9AAMbT8vfd7qrFB5W+5CBoArAOwmhOwCsAGAFyEkBRc8+QwA/yCE/BvAywC2AkgBYAPwNKV0PyFkJYBb2343boSQ6wB8BiABwFkAXp2uuRXArLbXvqWUru1k0nOEkEUAjADuopSeJ4S8AsBAKd10ie1ZAJ4FcHubvScBnAZQDkBNKd3Sdtw6XIhe/G3AvzAGYwhhws5gDDGUUiuA5raHq7IEwE+U0jJCSBMuTEj+Bxc858cAgBByBdq8bULIMwAopXQ6IWQygF8IIZPaxkoCMINSqiaEPI0LE5QphJAZAPI7XfPFtmPcAOwlhMyglBa1vadtG/teAFsA3NjTDVBKXyCEPEYpndlmbwyA7wBsaetKuAxAar9/QwyGkxia0lIMBmOssRzA9rbn29v+3R0ZAL4EAErpWQDVANqF/VdKqbrt+fxOxxUBKOo0xlJCSHsiXzyAqZ3e+7rTzzl9vZm261UBaCKEJAK4BkABpbSpP2MxGM6EeewMBmNAEEICASwEMJ0QQnHBW6e4EM7uDy29uGYsLoTPZ1FKm9vWzDsXsaddPO8rnwBYiQuJf58OYBwGw2kwj53BYAyU2wH8k1IaTSmNoZRGAqgEENnNOYcA3A0AbSH4KAClDo47COCutuOmAZjR9ro/LkwAtIQQCYBFl5x3Z6efR/pwL9a2nIh2dgG4DhfW8n/uwzgMxrDBPHYGgzFQlgNYf8lr/9f22j+6OOdDAFsJIcW4kDy3klJqdlAUaCuAzwghJQBKAOQBAKW0kBBSgAsJdbUAsi85L4AQUgTAjJ6XBTrzdwBFhJB8SundlFILIWQ/AA0rvMMYLbDtbgwGg9EFbUlz+QDuoJSeG257GIzewELxDAaD4QBCyFQA5wHsZaLOGE0wj53BYDAYDBeCeewMBoPBYLgQTNgZDAaDwXAhmLAzGAwGg+FCMGFnMBgMBsOFYMLOYDAYDIYLwYSdwWAwGAwX4v8BYrihXMJpsv8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "metropolitan-laser"
      },
      "source": [
        "Crear un grafico en html"
      ],
      "id": "metropolitan-laser"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pleased-familiar",
        "outputId": "ccc3cb70-0c58-4aad-e39e-10a8a2b71517"
      },
      "source": [
        "categories = ['Food Quality', 'Food Variety', 'Service Quality', 'Ambience', 'Affordability']\n",
        "categories = [*categories, categories[0]]\n",
        "\n",
        "restaurant_1 = [4, 4, 5, 4, 3]\n",
        "restaurant_2 = [5, 5, 4, 5, 2]\n",
        "restaurant_3 = [3, 4, 5, 3, 5]\n",
        "restaurant_1 = [*restaurant_1, restaurant_1[0]]\n",
        "restaurant_2 = [*restaurant_2, restaurant_2[0]]\n",
        "restaurant_3 = [*restaurant_3, restaurant_3[0]]\n",
        "\n",
        "\n",
        "fig = go.Figure(\n",
        "    data=[\n",
        "        go.Scatterpolar(r=restaurant_1, theta=categories, name='Restaurant 1'),\n",
        "        go.Scatterpolar(r=restaurant_2, theta=categories, name='Restaurant 2'),\n",
        "        go.Scatterpolar(r=restaurant_3, theta=categories, name='Restaurant 3')\n",
        "    ],\n",
        "    layout=go.Layout(\n",
        "        title=go.layout.Title(text='Restaurant comparison'),\n",
        "        polar={'radialaxis': {'visible': True}},\n",
        "        showlegend=True\n",
        "    )\n",
        ")\n",
        "\n",
        "pyo.plot(fig)"
      ],
      "id": "pleased-familiar",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'temp-plot.html'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fuzzy-absence"
      },
      "source": [
        "Creando poligonos (html):"
      ],
      "id": "fuzzy-absence"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "delayed-damage",
        "outputId": "ad0d2b50-24c1-4ba8-d9b5-9ae7f5e68ad4"
      },
      "source": [
        "\n",
        "categories = ['Food Quality', 'Food Variety', 'Service Quality', 'Ambiance', 'Affordability']\n",
        "categories = [*categories, categories[0]]\n",
        "\n",
        "restaurant_1 = [4, 4, 5, 4, 3]\n",
        "restaurant_2 = [5, 5, 4, 5, 2]\n",
        "restaurant_3 = [3, 4, 5, 3, 5]\n",
        "restaurant_1 = [*restaurant_1, restaurant_1[0]]\n",
        "restaurant_2 = [*restaurant_2, restaurant_2[0]]\n",
        "restaurant_3 = [*restaurant_3, restaurant_3[0]]\n",
        "\n",
        "\n",
        "fig = go.Figure(\n",
        "    data=[\n",
        "        go.Scatterpolar(r=restaurant_1, theta=categories, fill='toself', name='Restaurant 1'),\n",
        "        go.Scatterpolar(r=restaurant_2, theta=categories, fill='toself', name='Restaurant 2'),\n",
        "        go.Scatterpolar(r=restaurant_3, theta=categories, fill='toself', name='Restaurant 3')\n",
        "    ],\n",
        "    layout=go.Layout(\n",
        "        template='plotly_dark',\n",
        "        title=go.layout.Title(text='Restaurant comparison'),\n",
        "        polar={'radialaxis': {'visible': True}},\n",
        "        showlegend=True\n",
        "    )\n",
        ")\n",
        "\n",
        "pyo.plot(fig)"
      ],
      "id": "delayed-damage",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'temp-plot.html'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "minor-marijuana"
      },
      "source": [
        ""
      ],
      "id": "minor-marijuana",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "subjective-radical"
      },
      "source": [
        ""
      ],
      "id": "subjective-radical",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "generic-enclosure"
      },
      "source": [
        ""
      ],
      "id": "generic-enclosure",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tested-lodge"
      },
      "source": [
        ""
      ],
      "id": "tested-lodge",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "thousand-consolidation"
      },
      "source": [
        ""
      ],
      "id": "thousand-consolidation",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fitted-label"
      },
      "source": [
        "# Reportes"
      ],
      "id": "fitted-label"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "intermediate-status"
      },
      "source": [
        "import os\n",
        "import shutil\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import calendar\n",
        "from datetime import datetime\n",
        "from fpdf import FPDF\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib import rcParams\n",
        "rcParams['axes.spines.top'] = False\n",
        "rcParams['axes.spines.right'] = False"
      ],
      "id": "intermediate-status",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sixth-description"
      },
      "source": [
        "Generación de datos\n",
        "\n",
        "generate_sales_data() funciones devuelve un Pandas DataFrame con datos ficticios para un mes determinado\n",
        "\n",
        "El mes se pasa como entero"
      ],
      "id": "sixth-description"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "formal-fleece"
      },
      "source": [
        "def generate_sales_data(month: int) -> pd.DataFrame:\n",
        "    # Date range from first day of month until last\n",
        "    # Use ```calendar.monthrange(year, month)``` to get the last date\n",
        "    dates = pd.date_range(\n",
        "        start=datetime(year=2020, month=month, day=1),\n",
        "        end=datetime(year=2020, month=month, day=calendar.monthrange(2020, month)[1])\n",
        "    )\n",
        "    \n",
        "    # Sales numbers as a random integer between 1000 and 2000\n",
        "    sales = np.random.randint(low=1000, high=2000, size=len(dates))\n",
        "    \n",
        "    # Combine into a single dataframe\n",
        "    return pd.DataFrame({\n",
        "        'Date': dates,\n",
        "        'ItemsSold': sales\n",
        "    })"
      ],
      "id": "formal-fleece",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "moral-sector"
      },
      "source": [
        "generate_sales_data(month=3)"
      ],
      "id": "moral-sector",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "natural-detection"
      },
      "source": [
        "Visualización de datos de ventas"
      ],
      "id": "natural-detection"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "metric-gather"
      },
      "source": [
        "plot() La función visualiza un solo mes de ventas (serie temporal).\n",
        "\n",
        "En lugar de mostrar la figura, la función la guarda en un archivo.\n",
        "\n",
        "El nombre de archivo se especifica mediante un parámetro"
      ],
      "id": "metric-gather"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "prepared-injury"
      },
      "source": [
        "def plot(data: pd.DataFrame, filename: str) -> None:\n",
        "    plt.figure(figsize=(12, 4))\n",
        "    plt.grid(color='#F2F2F2', alpha=1, zorder=0)\n",
        "    plt.plot(data['Date'], data['ItemsSold'], color='#087E8B', lw=3, zorder=5)\n",
        "    plt.title(f'Sales 2020/{data[\"Date\"].dt.month[0]}', fontsize=17)\n",
        "    plt.xlabel('Period', fontsize=13)\n",
        "    plt.xticks(fontsize=9)\n",
        "    plt.ylabel('Number of items sold', fontsize=13)\n",
        "    plt.yticks(fontsize=9)\n",
        "    plt.savefig(filename, dpi=300, bbox_inches='tight', pad_inches=0)\n",
        "    plt.close()\n",
        "    return"
      ],
      "id": "prepared-injury",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hispanic-institute"
      },
      "source": [
        "december = generate_sales_data(month=12)\n",
        "plot(data=december, filename='december.png')"
      ],
      "id": "hispanic-institute",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "loving-composite"
      },
      "source": [
        "Construir elementos de la pagina\n",
        "\n",
        "construct() La función crea un directorio para las parcelas y luego crea un gráfico de ventas para cada mes en 2020 excepto enero\n",
        "\n",
        "    Se excluyó enero porque queremos mostrar cómo puede tener un número diferente de elementos en la página de informes.\n",
        "\n",
        "    No dudes en incluirlo\n",
        "        Cambiar for i in range(2, 13)afor i in range(1, 13)\n",
        "\n",
        "Una vez que se guardan las visualizaciones, se agregan a una lista de estructura de lista (matriz)\n",
        "\n",
        "    Máximo de 3 elementos por fila\n",
        "\n",
        "    Puede ser menor\n",
        "    \n",
        "    Una sola fila en esta matriz representa una sola página\n",
        "\n",
        "        Si la fila tiene 3 elementos, la página del informe tendrá 3 visualizaciones"
      ],
      "id": "loving-composite"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "innocent-lloyd"
      },
      "source": [
        "PLOT_DIR = 'plots'\n",
        "\n",
        "def construct():\n",
        "    # Delete folder if exists and create it again\n",
        "    try:\n",
        "        shutil.rmtree(PLOT_DIR)\n",
        "        os.mkdir(PLOT_DIR)\n",
        "    except FileNotFoundError:\n",
        "        os.mkdir(PLOT_DIR)\n",
        "        \n",
        "    # Iterate over all months in 2020 except January\n",
        "    for i in range(2, 13):\n",
        "        # Save visualization\n",
        "        plot(data=generate_sales_data(month=i), filename=f'{PLOT_DIR}/{i}.png')\n",
        "        \n",
        "    # Construct data shown in document\n",
        "    counter = 0\n",
        "    pages_data = []\n",
        "    temp = []\n",
        "    # Get all plots\n",
        "    files = os.listdir(PLOT_DIR)\n",
        "    # Sort them by month - a bit tricky because the file names are strings\n",
        "    files = sorted(os.listdir(PLOT_DIR), key=lambda x: int(x.split('.')[0]))\n",
        "    # Iterate over all created visualization\n",
        "    for fname in files:\n",
        "        # We want 3 per page\n",
        "        if counter == 3:\n",
        "            pages_data.append(temp)\n",
        "            temp = []\n",
        "            counter = 0\n",
        "\n",
        "        temp.append(f'{PLOT_DIR}/{fname}')\n",
        "        counter += 1\n",
        "\n",
        "    return [*pages_data, temp]"
      ],
      "id": "innocent-lloyd",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "early-patrol"
      },
      "source": [
        "plots_per_page = construct()"
      ],
      "id": "early-patrol",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "acceptable-defeat"
      },
      "source": [
        "4 páginas en total\n",
        "\n",
        "Los primeros 3 tienen 3 parcelas por página\n",
        "\n",
        "El último tiene solo 2"
      ],
      "id": "acceptable-defeat"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "closed-scottish"
      },
      "source": [
        "plots_per_page"
      ],
      "id": "closed-scottish",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "unusual-engineer"
      },
      "source": [
        "PDF class\n",
        "\n",
        "Hereda de PDF\n",
        "\n",
        "    Todos los métodos y propiedades se heredan\n",
        "\n",
        "    No olvides llamar super()al constructor\n",
        "\n",
        "La clase se usa para generar un informe a partir de la plots_per_pagematriz."
      ],
      "id": "unusual-engineer"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "immediate-partition"
      },
      "source": [
        "class PDF(FPDF):\n",
        "    def __init__(self):\n",
        "        super().__init__()\n",
        "        self.WIDTH = 210\n",
        "        self.HEIGHT = 297\n",
        "        \n",
        "    def header(self):\n",
        "        # Custom logo and positioning\n",
        "        # Create an `assets` folder and put any wide and short image inside\n",
        "        # Name the image `logo.png`\n",
        "        self.image('assets/logo.png', 10, 8, 33)\n",
        "        self.set_font('Arial', 'B', 11)\n",
        "        self.cell(self.WIDTH - 80)\n",
        "        self.cell(60, 1, 'Sales report', 0, 0, 'R')\n",
        "        self.ln(20)\n",
        "        \n",
        "    def footer(self):\n",
        "        # Page numbers in the footer\n",
        "        self.set_y(-15)\n",
        "        self.set_font('Arial', 'I', 8)\n",
        "        self.set_text_color(128)\n",
        "        self.cell(0, 10, 'Page ' + str(self.page_no()), 0, 0, 'C')\n",
        "\n",
        "    def page_body(self, images):\n",
        "        # Determine how many plots there are per page and set positions\n",
        "        # and margins accordingly\n",
        "        if len(images) == 3:\n",
        "            self.image(images[0], 15, 25, self.WIDTH - 30)\n",
        "            self.image(images[1], 15, self.WIDTH / 2 + 5, self.WIDTH - 30)\n",
        "            self.image(images[2], 15, self.WIDTH / 2 + 90, self.WIDTH - 30)\n",
        "        elif len(images) == 2:\n",
        "            self.image(images[0], 15, 25, self.WIDTH - 30)\n",
        "            self.image(images[1], 15, self.WIDTH / 2 + 5, self.WIDTH - 30)\n",
        "        else:\n",
        "            self.image(images[0], 15, 25, self.WIDTH - 30)\n",
        "            \n",
        "    def print_page(self, images):\n",
        "        # Generates the report\n",
        "        self.add_page()\n",
        "        self.page_body(images)"
      ],
      "id": "immediate-partition",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "downtown-posting"
      },
      "source": [
        "Cree una instancia y cree un informe:"
      ],
      "id": "downtown-posting"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "adaptive-slovak"
      },
      "source": [
        "pdf = PDF()\n",
        "\n",
        "for elem in plots_per_page:\n",
        "    pdf.print_page(elem)\n",
        "    \n",
        "pdf.output('SalesRepot.pdf', 'F')"
      ],
      "id": "adaptive-slovak",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "incident-migration"
      },
      "source": [
        "# Crear documentos PDF en Python con ReportLab"
      ],
      "id": "incident-migration"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mineral-better"
      },
      "source": [
        "ReportLab es un toolkit de código abierto para crear documentos PDF desde Python. Se trata de una librería muy extensa y con muchas funcionalidades, desde pequeños textos y figuras geométricas a grandes gráficos e ilustraciones, todo ello puede ser incluido dentro de un PDF. En este artículo estaremos sopesando sus características generales y sus principales funciones para crear este tipo de documentos."
      ],
      "id": "mineral-better"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "legendary-southwest"
      },
      "source": [
        "from reportlab.pdfgen import canvas\n",
        "c = canvas.Canvas(\"hola-mundo.pdf\")\n",
        "c.save()"
      ],
      "id": "legendary-southwest",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "brief-carroll"
      },
      "source": [
        "c.drawString(50, 50, \"¡Hola, mundo!\")\n"
      ],
      "id": "brief-carroll",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pacific-expense"
      },
      "source": [
        "from reportlab.lib.pagesizes import A4, letter"
      ],
      "id": "pacific-expense",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "welcome-fitting"
      },
      "source": [
        "from reportlab.lib.pagesizes import letter\n",
        "c = canvas.Canvas(\"hola-mundo.pdf\", pagesize=letter)"
      ],
      "id": "welcome-fitting",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "located-disclosure"
      },
      "source": [
        "from reportlab.lib.pagesizes import A4\n",
        "c = canvas.Canvas(\"hola-mundo.pdf\", pagesize=A4)"
      ],
      "id": "located-disclosure",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "standing-rebate"
      },
      "source": [
        "from reportlab.lib.pagesizes import A4\n",
        "from reportlab.pdfgen import canvas\n",
        "w, h = A4\n",
        "c = canvas.Canvas(\"hola-mundo.pdf\", pagesize=A4)\n",
        "c.drawString(50, h - 50, \"¡Hola, mundo!\")\n",
        "c.showPage()\n",
        "c.save()"
      ],
      "id": "standing-rebate",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "medical-canada"
      },
      "source": [
        "Líneas y figuras geométricas\n"
      ],
      "id": "medical-canada"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "universal-cutting"
      },
      "source": [
        "# Dibujar una línea horizontal.\n",
        "x = 50\n",
        "y = h - 50\n",
        "c.line(x, y, x + 200, y)"
      ],
      "id": "universal-cutting",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "familiar-franchise"
      },
      "source": [
        "# Rectángulo.\n",
        "c.rect(50, h - 300, 300, 200)"
      ],
      "id": "familiar-franchise",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "driven-gambling"
      },
      "source": [
        "# Rectángulo con extremos curvos.\n",
        "c.roundRect(50, h - 300, 300, 200, 10)"
      ],
      "id": "driven-gambling",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "unlikely-commerce"
      },
      "source": [
        "# Círculo: posición (x, y) del centro y el radio.\n",
        "c.circle(100, h - 100, 50)"
      ],
      "id": "unlikely-commerce",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "accessible-snapshot"
      },
      "source": [
        "c.ellipse(50, h - 50, x + 150, y - 50)"
      ],
      "id": "accessible-snapshot",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "composite-nerve"
      },
      "source": [
        "from reportlab.lib.pagesizes import A4\n",
        "from reportlab.pdfgen import canvas\n",
        "w, h = A4\n",
        "c = canvas.Canvas(\"figuras.pdf\", pagesize=A4)\n",
        "c.drawString(30, h - 50, \"Línea\")\n",
        "x = 120\n",
        "y = h - 45\n",
        "c.line(x, y, x + 100, y)\n",
        "c.drawString(30, h - 100, \"Rectángulo\")\n",
        "c.rect(x, h - 120, 100, 50)\n",
        "c.drawString(30, h - 170, \"Círculo\")\n",
        "c.circle(170, h - 165, 20)\n",
        "c.drawString(30, h - 240, \"Elipse\")\n",
        "c.ellipse(x, y - 170, x + 100, y - 220)\n",
        "c.showPage()\n",
        "c.save()"
      ],
      "id": "composite-nerve",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "comprehensive-genealogy"
      },
      "source": [
        "Estilos"
      ],
      "id": "comprehensive-genealogy"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "advance-tobago"
      },
      "source": [
        "# Valores RGB entre 0.0 y 1.0.\n",
        "c.setFillColorRGB(1, 0, 0)\n",
        "c.drawString(50, h - 50, \"¡Hola, mundo!\")\n",
        "c.rect(50, h - 150, 50, 50, fill=True)"
      ],
      "id": "advance-tobago",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "junior-clothing"
      },
      "source": [
        "c.setStrokeColorRGB(0.7, 0, 0.7)"
      ],
      "id": "junior-clothing",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "known-appeal"
      },
      "source": [
        "c.setFont(\"Helvetica\", 10)\n",
        "c.drawString(50, h - 50, \"¡Hola, mundo!\")\n",
        "c.setFont(\"Times-Roman\", 20)\n",
        "c.drawString(130, h - 50, \"¡Hola, mundo!\")"
      ],
      "id": "known-appeal",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "turkish-infection"
      },
      "source": [
        "Textos"
      ],
      "id": "turkish-infection"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "quantitative-latest"
      },
      "source": [
        "text = c.beginText(50, h - 50)\n"
      ],
      "id": "quantitative-latest",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "distinct-acquisition"
      },
      "source": [
        "text.setFont(\"Times-Roman\", 12)\n"
      ],
      "id": "distinct-acquisition",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "historical-shower"
      },
      "source": [
        "# Las dos frases aparecen en dos líneas diferentes.\n",
        "text.textLine(\"¡Hola, mundo!\")\n",
        "text.textLine(\"¡Desde ReportLab y Python!\")"
      ],
      "id": "historical-shower",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "outer-latino"
      },
      "source": [
        "# El método textLines() soporta el carácter de salto de línea.\n",
        "text.textLines(\"¡Hola, mundo!\\n¡Desde ReportLab y Python!\")"
      ],
      "id": "outer-latino",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "declared-tractor"
      },
      "source": [
        "c.drawText(text)\n"
      ],
      "id": "declared-tractor",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "unsigned-trading"
      },
      "source": [
        "Imágenes"
      ],
      "id": "unsigned-trading"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "excited-treasurer",
        "outputId": "04f1ab50-0bc2-49b5-810c-6bf329b5bbff"
      },
      "source": [
        "c.drawImage(\"assets/logo.png\", 50, h - 200)\n"
      ],
      "id": "excited-treasurer",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(526, 469)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "consecutive-helicopter",
        "outputId": "964410a8-ade1-4f1b-9c5f-5e42e4108ba7"
      },
      "source": [
        "c.drawImage(\"assets/logo.png\", 50, h - 200, width=50, height=50)\n"
      ],
      "id": "consecutive-helicopter",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(526, 469)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "significant-complaint"
      },
      "source": [
        "Grillas\n"
      ],
      "id": "significant-complaint"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tropical-organization"
      },
      "source": [
        "xlist = [10, 60, 110, 160]\n",
        "ylist = [h - 10, h - 60, h - 110, h - 160]\n",
        "c.grid(xlist, ylist)"
      ],
      "id": "tropical-organization",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "removable-vehicle"
      },
      "source": [
        "import itertools\n",
        "from random import randint\n",
        "from statistics import mean\n",
        "from reportlab.lib.pagesizes import A4\n",
        "from reportlab.pdfgen import canvas\n",
        "def grouper(iterable, n):\n",
        "    args = [iter(iterable)] * n\n",
        "    return itertools.zip_longest(*args)\n",
        "def export_to_pdf(data):\n",
        "    c = canvas.Canvas(\"grilla-alumnos.pdf\", pagesize=A4)\n",
        "    w, h = A4\n",
        "    max_rows_per_page = 45\n",
        "    # Margin.\n",
        "    x_offset = 50\n",
        "    y_offset = 50\n",
        "    # Space between rows.\n",
        "    padding = 15\n",
        "    \n",
        "    xlist = [x + x_offset for x in [0, 200, 250, 300, 350, 400, 480]]\n",
        "    ylist = [h - y_offset - i*padding for i in range(max_rows_per_page + 1)]\n",
        "    \n",
        "    for rows in grouper(data, max_rows_per_page):\n",
        "        rows = tuple(filter(bool, rows))\n",
        "        c.grid(xlist, ylist[:len(rows) + 1])\n",
        "        for y, row in zip(ylist[:-1], rows):\n",
        "            for x, cell in zip(xlist, row):\n",
        "                c.drawString(x + 2, y - padding + 3, str(cell))\n",
        "        c.showPage()\n",
        "    \n",
        "    c.save()\n",
        "data = [(\"NOMBRE\", \"NOTA 1\", \"NOTA 2\", \"NOTA 3\", \"PROM.\", \"ESTADO\")]\n",
        "for i in range(1, 101):\n",
        "    exams = [randint(0, 10) for _ in range(3)]\n",
        "    avg = round(mean(exams), 2)\n",
        "    state = \"Aprobado\" if avg >= 4 else \"Desaprobado\"\n",
        "    data.append((f\"Alumno {i}\", *exams, avg, state))\n",
        "export_to_pdf(data)"
      ],
      "id": "removable-vehicle",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "greatest-vegetarian"
      },
      "source": [
        ""
      ],
      "id": "greatest-vegetarian",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "minimal-stone"
      },
      "source": [
        ""
      ],
      "id": "minimal-stone",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "finnish-survival"
      },
      "source": [
        ""
      ],
      "id": "finnish-survival",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "finnish-trick"
      },
      "source": [
        ""
      ],
      "id": "finnish-trick",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "unlimited-noise"
      },
      "source": [
        "# Bibliografia"
      ],
      "id": "unlimited-noise"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hawaiian-worship"
      },
      "source": [
        "## Visualizaciones"
      ],
      "id": "hawaiian-worship"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "novel-rhythm"
      },
      "source": [
        "https://stackabuse.com/matplotlib-histogram-plot-tutorial-and-examples/"
      ],
      "id": "novel-rhythm"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "simple-native"
      },
      "source": [
        "https://relopezbriega.github.io/blog/2016/09/18/visualizaciones-de-datos-con-python/"
      ],
      "id": "simple-native"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "short-tamil"
      },
      "source": [
        "https://towardsdatascience.com/how-to-make-stunning-radar-charts-with-python-implemented-in-matplotlib-and-plotly-91e21801d8ca#_=_"
      ],
      "id": "short-tamil"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sharp-header"
      },
      "source": [
        "https://www.pluralsight.com/guides/map-visualizations-in-python-using-folium"
      ],
      "id": "sharp-header"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "incorporated-garage"
      },
      "source": [
        "https://machinelearningknowledge.ai/seaborn-countplot-tutorial-for-beginners/"
      ],
      "id": "incorporated-garage"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "destroyed-tobago"
      },
      "source": [
        "https://machinelearningknowledge.ai/11-python-data-visualization-libraries-data-scientists-should-know/"
      ],
      "id": "destroyed-tobago"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "opponent-delivery"
      },
      "source": [
        "https://machinelearningknowledge.ai/seaborn-distplot-explained-for-beginners/"
      ],
      "id": "opponent-delivery"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wicked-dimension"
      },
      "source": [
        "https://machinelearningknowledge.ai/seaborn-histogram-plot-using-histplot-tutorial-for-beginners/"
      ],
      "id": "wicked-dimension"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "acoustic-nowhere"
      },
      "source": [
        "Libro: https://gumroad.com/l/data-visualization-in-python"
      ],
      "id": "acoustic-nowhere"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ethical-sentence"
      },
      "source": [
        "## Reportes"
      ],
      "id": "ethical-sentence"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "flexible-dispute"
      },
      "source": [
        "https://recursospython.com/guias-y-manuales/crear-documentos-pdf-en-python-con-reportlab/"
      ],
      "id": "flexible-dispute"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "selective-peoples"
      },
      "source": [
        ""
      ],
      "id": "selective-peoples"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "trying-linux"
      },
      "source": [
        ""
      ],
      "id": "trying-linux"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "atlantic-conducting"
      },
      "source": [
        ""
      ],
      "id": "atlantic-conducting"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "happy-letters"
      },
      "source": [
        ""
      ],
      "id": "happy-letters"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "olympic-monte"
      },
      "source": [
        ""
      ],
      "id": "olympic-monte"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "noted-glucose"
      },
      "source": [
        ""
      ],
      "id": "noted-glucose"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "efficient-southwest"
      },
      "source": [
        ""
      ],
      "id": "efficient-southwest",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "brutal-sleep"
      },
      "source": [
        ""
      ],
      "id": "brutal-sleep",
      "execution_count": null,
      "outputs": []
    }
  ]
}