medical_cost_forecast.ipynb

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  "metadata": {
    "colab": {
      "name": "medical-cost-forecast.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/LugoBlogger/MLCC-Assignment-05/blob/master/medical_cost_forecast.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bLMC3Zb-Cksh",
        "colab_type": "text"
      },
      "source": [
        "# Introduction\n",
        "\n",
        "In this notebook, we will predict health insurance cost that someone should pay annually by the given features, such as BMI, age, sex, etc."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gBCFS3gaE7wn",
        "colab_type": "code",
        "outputId": "86fa5ec4-67a3-46bc-8421-13218bb32188",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# Use seaborn for pairplot\n",
        "!pip install -q seaborn\n",
        "\n",
        "# Use some functions from tensorflow_docs\n",
        "!pip install -q git+https://github.com/tensorflow/docs"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "  Building wheel for tensorflow-docs (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZKKYz5BnFeAf",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Use tensorflow 2\n",
        "%tensorflow_version 2.x"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sPXvoENYBlC9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import time\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zBaTzo5YEHOz",
        "colab_type": "code",
        "outputId": "35b33725-7d96-48d6-ba3f-dcf408c6f82f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "import tensorflow as tf\n",
        "\n",
        "from tensorflow import keras\n",
        "from tensorflow.keras import layers\n",
        "\n",
        "print(tf.__version__)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2.2.0-rc1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vLwn9MsbEOfY",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "### this library is for callback functions\n",
        "import tensorflow_docs as tfdocs\n",
        "import tensorflow_docs.plots\n",
        "import tensorflow_docs.modeling"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "llvFDM09FyIu",
        "colab_type": "text"
      },
      "source": [
        "# Medical Cost Personal Datasets\n",
        "\n",
        "## Retrieve the dataset\n",
        "\n",
        "Manage the dataset into pandas' DataFrame."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ca59a6eCGMsA",
        "colab_type": "code",
        "outputId": "fbf3bddc-7c0a-4a16-e094-4406234edb01",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "source": [
        "dataset = pd.read_csv(\"https://raw.githubusercontent.com/LugoBlogger/MLCC-Assignment-05/master/datasets/insurance.csv\", header=0)\n",
        "dataset"
      ],
      "execution_count": 6,
      "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>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>bmi</th>\n",
              "      <th>children</th>\n",
              "      <th>smoker</th>\n",
              "      <th>region</th>\n",
              "      <th>charges</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>19</td>\n",
              "      <td>female</td>\n",
              "      <td>27.900</td>\n",
              "      <td>0</td>\n",
              "      <td>yes</td>\n",
              "      <td>southwest</td>\n",
              "      <td>16884.92400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>18</td>\n",
              "      <td>male</td>\n",
              "      <td>33.770</td>\n",
              "      <td>1</td>\n",
              "      <td>no</td>\n",
              "      <td>southeast</td>\n",
              "      <td>1725.55230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>28</td>\n",
              "      <td>male</td>\n",
              "      <td>33.000</td>\n",
              "      <td>3</td>\n",
              "      <td>no</td>\n",
              "      <td>southeast</td>\n",
              "      <td>4449.46200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>33</td>\n",
              "      <td>male</td>\n",
              "      <td>22.705</td>\n",
              "      <td>0</td>\n",
              "      <td>no</td>\n",
              "      <td>northwest</td>\n",
              "      <td>21984.47061</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>32</td>\n",
              "      <td>male</td>\n",
              "      <td>28.880</td>\n",
              "      <td>0</td>\n",
              "      <td>no</td>\n",
              "      <td>northwest</td>\n",
              "      <td>3866.85520</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1333</th>\n",
              "      <td>50</td>\n",
              "      <td>male</td>\n",
              "      <td>30.970</td>\n",
              "      <td>3</td>\n",
              "      <td>no</td>\n",
              "      <td>northwest</td>\n",
              "      <td>10600.54830</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1334</th>\n",
              "      <td>18</td>\n",
              "      <td>female</td>\n",
              "      <td>31.920</td>\n",
              "      <td>0</td>\n",
              "      <td>no</td>\n",
              "      <td>northeast</td>\n",
              "      <td>2205.98080</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1335</th>\n",
              "      <td>18</td>\n",
              "      <td>female</td>\n",
              "      <td>36.850</td>\n",
              "      <td>0</td>\n",
              "      <td>no</td>\n",
              "      <td>southeast</td>\n",
              "      <td>1629.83350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1336</th>\n",
              "      <td>21</td>\n",
              "      <td>female</td>\n",
              "      <td>25.800</td>\n",
              "      <td>0</td>\n",
              "      <td>no</td>\n",
              "      <td>southwest</td>\n",
              "      <td>2007.94500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1337</th>\n",
              "      <td>61</td>\n",
              "      <td>female</td>\n",
              "      <td>29.070</td>\n",
              "      <td>0</td>\n",
              "      <td>yes</td>\n",
              "      <td>northwest</td>\n",
              "      <td>29141.36030</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1338 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      age     sex     bmi  children smoker     region      charges\n",
              "0      19  female  27.900         0    yes  southwest  16884.92400\n",
              "1      18    male  33.770         1     no  southeast   1725.55230\n",
              "2      28    male  33.000         3     no  southeast   4449.46200\n",
              "3      33    male  22.705         0     no  northwest  21984.47061\n",
              "4      32    male  28.880         0     no  northwest   3866.85520\n",
              "...   ...     ...     ...       ...    ...        ...          ...\n",
              "1333   50    male  30.970         3     no  northwest  10600.54830\n",
              "1334   18  female  31.920         0     no  northeast   2205.98080\n",
              "1335   18  female  36.850         0     no  southeast   1629.83350\n",
              "1336   21  female  25.800         0     no  southwest   2007.94500\n",
              "1337   61  female  29.070         0    yes  northwest  29141.36030\n",
              "\n",
              "[1338 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QErQzKKxG3Ky",
        "colab_type": "text"
      },
      "source": [
        "The data consists of several columns:\n",
        "\n",
        "**age**: age of primary beneficiary\n",
        "\n",
        "**sex**: insurance contractor gender, female, male\n",
        "\n",
        "**bmi**: Body Mass Index, providing an understanding of body, weights that are relatively high or low relative to height, objective index of body weight (kg / m^2) using the ratio of height to weight, ideally 18.5 to 24.9\n",
        "\n",
        "**children**: Number of children covered by health insurance / Number of dependents\n",
        "\n",
        "**smoker**: whether or not the beneficiary smokes\n",
        "\n",
        "**region**: the beneficiary's residential area in the US, northeast, southeast, southwest, northwest.\n",
        "\n",
        "**charges**: Individual medical costs billed by health insurance"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iK2FmcfqH85U",
        "colab_type": "text"
      },
      "source": [
        "## Exploratory Data Analysis\n",
        "\n",
        "Some features have categorical data while the others are continuous data. The categorical ones include sex, smoker and region. The rest, which are age, bmi, children and charges are continuous data.\n",
        "We would like to see the correlation between each of these features.\n",
        "Thus, we will encode categorical features to convert them into continuous values."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DEElSgH4ICLv",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "\n",
        "data = dataset\n",
        "\n",
        "le = LabelEncoder()\n",
        "\n",
        "#sex\n",
        "le.fit(data.sex.drop_duplicates()) \n",
        "data.sex = le.transform(data.sex)\n",
        "\n",
        "# smoker or not\n",
        "le.fit(data.smoker.drop_duplicates()) \n",
        "data.smoker = le.transform(data.smoker)\n",
        "\n",
        "#region\n",
        "le.fit(data.region.drop_duplicates()) \n",
        "data.region = le.transform(data.region)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OCNjnj93IKF3",
        "colab_type": "text"
      },
      "source": [
        "Now, the all the data are continous. We can make correlations to see how each feature correlate to our target prediction, which is charges."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ONFkitE0ILlV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "outputId": "d09a8c73-c443-46d8-de79-30863f83dc78"
      },
      "source": [
        "data.corr()['charges'].sort_values()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "region     -0.006208\n",
              "sex         0.057292\n",
              "children    0.067998\n",
              "bmi         0.198341\n",
              "age         0.299008\n",
              "smoker      0.787251\n",
              "charges     1.000000\n",
              "Name: charges, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pd148RJLIOMs",
        "colab_type": "text"
      },
      "source": [
        "In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. In the broadest sense correlation is any statistical association, though it commonly refers to the degree to which a pair of variables are linearly related."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8JNDRty6IPvh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 504
        },
        "outputId": "8bb425d3-ce2f-4a42-defb-c69f25c561ea"
      },
      "source": [
        "import matplotlib.pyplot as pl\n",
        "\n",
        "f, ax = pl.subplots(figsize=(10, 8))\n",
        "corr = data.corr()\n",
        "sns.heatmap(corr, mask=np.zeros_like(corr, dtype=np.bool), \n",
        "            cmap=sns.diverging_palette(240,10,as_cmap=True),square=True, ax=ax)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f6fc06e2f28>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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S3wyoR8NEQ5KknvnpJht3st9NO9nrwhw6kSRJnTHRkCRJnTHRkCRJnTHRkCRJnTHRkCRJ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\nZAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CgmMvj5IIWpt",
        "colab_type": "text"
      },
      "source": [
        "A strong correlation is observed between smoker and charges and it is a positive correlation. It means that if someone smokes, the cost of health insurance will be higher as compared to those who do not smoke.\n",
        "\n",
        "On the other hand, we observe another interesting thing here, which is BMI. We can consider BMI as the indicator of how healthy someone is, according to their body weight and height. Thus, we might have expected that BMI would have strong correlations to health insurance cost/charges. However, the data shows that it is not.\n",
        "\n",
        "Since smoker feature has a strong correlation with charges. Let's investigate more on this."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Uo0ak40YIXGL",
        "colab_type": "text"
      },
      "source": [
        "Let's see the distribution charges for those who smoke and those who do not smoke."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bMjCEMmpIZjj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331
        },
        "outputId": "b9a97cc8-b4b7-4582-920e-c4d75dd89f28"
      },
      "source": [
        "f= pl.figure(figsize=(12,5))\n",
        "\n",
        "ax=f.add_subplot(121)\n",
        "sns.distplot(data[(data.smoker == 1)][\"charges\"],color='c',ax=ax)\n",
        "ax.set_title('Distribution of charges for smokers')\n",
        "\n",
        "ax=f.add_subplot(122)\n",
        "sns.distplot(data[(data.smoker == 0)]['charges'],color='b',ax=ax)\n",
        "ax.set_title('Distribution of charges for non-smokers')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Distribution of charges for non-smokers')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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684cCnxJsS3c3zeXlzJrk4MGJuGjGDKrM+KGWBBcpeNu3w4IFMJX30HV1QRK8\nZQt84hOZi01EoqFEOI892tXFoDtnZSgRXlZTQ4VZQSfCQ+483dvLiro6LAvTpg3XUF7OH8+YwW2H\nD2v2CJECNjQEO3bAsmVTb2vlSrjqKvjCF+Cee6benohER4lwHtsUzlZw1kSGN4+hIhbjhJqagl4k\nYmdfH32JBCfnoCwi6U9nzWJPfz+bOztz9pwikll79gQLY2QiEQb493+HpUvh3e8GXRpECpcS4Ty2\nqaODxVVVzK2qylibJ9XUsDcep6tA5//Z0t2NESwSkitvam6mXOURIgXtmWeCr8uXZ6a9+nr4zneC\nWSQ+8pHMtCkiuadEOI9t6ujIWFlE0klhAvl0gfYKb+3p4bjqauqyOG3acDMqKvijadP40eHDOXtO\nEcms556D5mbI5JjXc86B//N/grmFb7opc+2KSO4oEc5TLfE4u/r7M54IL6mupsqsIBPh9sFBnuvr\ny2lZRNKbmpvZ1tvL9gI8byISrAi3YEHm2/30p+E1rwlqhrdsyXz7IpJdSoTz1EMZrg9OKjNjWU0N\n23p7M9puLtzX3k4CIkmEL25uBuDnR4/m/LlFZGqGhqClBebNy3zb5eXwP/8TzCZx6aWghShFCosS\n4Ty1qaODMuCMDCfCEJRHHIjHaR8czHjb2bSxvZ0YsDSCiTuPr6nhZbW1/OzIkZw/t4hMzaFDQTI8\nf3522p8/H265JahDfsc7tASzSCFRIpynNnV2cmp9PbVZqIVN1gkX2uwR97a3c1x1NZURLQZy8YwZ\n/G9bG50F9gZCpNQdOBB8zUaPcNIf/RFcf32w6tw//mP2nkdEMksry2XZ+v37J3yMu3N/ezurGxom\ndfx4FlVVUR2Lsa23lzUZrkHOlr6hIR7q6OA1Ea7udnFzM/9v715+c+wYfzJrVmRxiMjE7N8frCiX\nzUQY4AMfgCeegOuuC6ZWe//7s/t8IjJ16hHOQ0cHB+lJJFiYwWnTUpWZcUJ1NdsLqE54c2cncXeW\n1dREFsM5TU00lpXxc5VHiBSUAweCGSMqK7P/XF/6ErzxjfDBD8KPf5z95xORqVEinIf29vcDQc9t\ntiyrqWF/PE53gRSzbWxvB4g0Ea6IxXjDjBncfvSoVpkTKSD792e/NzipvDyoF167Fi6/HH7729w8\nr4hMjhLhPLSnvx8DFmQxET4hTCh3FEiv8Mb2dk6uraU+h/MHj+TCGTM4EI/z++7uSOMQkfRkc8aI\n0dTWws9+BieeGPQOKxkWyV+qEc5De/v7mV1RQVUWB4Utra4mBmzv6+Pl9fVZe55MSLhzX0cHl2Wp\nLnciddjHBgYA+OedO3n9jN1aC2wAACAASURBVBmj7rcuW8PTRWRCWluzO2PEaJqb4c474bzzgmT4\nZz+D88/PbQwiMj71COehPf39WasPTqqMxVhcIHXCT3V30zY4yDlNTVGHwvSKCuZVVrKlwGbcEClV\nyfe5Ubw3nTkzSIaXL1fPsEi+UiKcZ3qHhjg8MJD1RBiCettdfX0MJBJZf66puDesDz43DxJhCBb0\neKa3N+/Pm4i8MHXa3LnRPP/wZPjXv44mDhEZmRLhPLMvHgeyO1Au6YTqagbc2R0OzstXG9vbmV9Z\nyZIIFtIYycm1tQy4s72vL+pQRGQc+/cHyWgOLqmjSibDJ50EF18Mt94aXSwi8mJKhPPMnjApzVWP\nMMCzeV4esbG9nXOamjCzqEMB4MTaWsqALRowJ5L3Dh6Mrjc41cyZcPfdcNZZwWwSX/ta1BGJCKSR\nCJvZIjO7y8y2mNlTZvaREfZ5rZm1m9lj4e2T2Qm3+O3t76cuFmNaefbHMTaWlzO7oiKv64R39fWx\np78/b8oiAKpjMY6vqWGr6oRF8po7HD4M+bL+zbRpcMcdQa/wBz8I114bxCgi0Ukn2xoEPubuj5pZ\nA/CImf3a3bcM2+9ed39j5kMsLXv7+lhYVZWz3s8Tamr4fXc37p43Pa6pkvMH58NAuVQn19ay4cgR\nOgcHacjBmxYRmbjubujrC3pj80VtLdx2G7zvffCpTwUlE29/O4w1M+S6dbmLT6TUjPsf3N0PAAfC\n+51mthVYAAxPhGWKEu7si8d5dQ6TvmU1NTzQ0cG23l5Oqq3N2fOma2N7O41lZXk3xVsyEd7W28uZ\nDQ1RhyMiIzh8OPiajUR4/frx9xktga2ogG9/G2bPhs9/Ho4cCRLjCNcLEilZE6oRNrMlwCpg0wgP\nv9LMHjezX5jZygzEVnJaBwYYcM9JfXDSCeEAtPvCntd8c29bG69qaqIsz3qrj6uupsqMp1UeIZK3\nkquhNzdHG8dIYjH493+Hd7wDtmyBf/u3FxJ3EcmdtD/TNbN64IfAX7t7x7CHHwWOc/cuM7sI+DGw\nfIQ21gHrABYvXjzpoIvV/nCg3PwcJsJzKyupi8XY2N7OX+Ry6aU0HB0Y4KmeHq6YMyfqUF6izIxl\nNTU8ncf11SKlLps9wulIp9f4Na8Jeoa//nX43OfgAx+AE07IfmwiEkirR9jMKgiS4P9299uGP+7u\nHe7eFd6/Hagws5dcetx9vbuvdvfVs/Jl9EIe2R9OnTa3sjJnz2lmnFBTk5c9wvfl2fzBw51UW8vB\neJz2wcGoQxGRERw+DHV1+V9ycPLJ8PGPQ3U1fOELcO+9GkQnkivj9ghbMILqm8BWd//CKPvMBVrc\n3c1sLUGCfSSjkZaAA/E4zeXlVGdxaeWRLKup4bbDhzkUjzM7h0n4eDa2t1Nhxpo8rcFN1lRv6+lh\nTWNjxNGIyHCHD+dnWcRI5s4NkuH/+i/47ndh2zb4sz8LkuN0jNf7rAF3IiNLJ+M6G/hz4LyU6dEu\nMrOrzOyqcJ9LgSfN7HHgeuByd72fnaj9/f05LYtIOiHsLrk/z3qFN7a3s7qhgZqxhlNHaFFVFdWx\nGNtUHiGSl44cyZ+p09JRXw9/9VdwySXw8MPwr/8Ke/dGHZVIcUtn1oiNwJgjldz9y8CXMxVUKRpy\np2VggJV1dTl/7uOqqqgyY2N7O2/Jk/8avUNDPNzZyd8sXBh1KKMqM2N5TY0GzInkoUQiSIRPOy3q\nSCYmFoOLLoJly4Le4c99DhYsCHp082zMsEhR0MpyeaJ1YIBBd+ZHUJpQEYuxuqGB+zqGj4GMzsOd\nnQy45938wcOdVFNDy8AAbaoTFskr7e0wOJhfcwhPxIknwic+AcuXw1VXwWWXwbFjUUclUnyUCOeJ\n5IwR8yIojYBgwYrNnZ30DA1F8vzDJRfSeFWeJ8InptQJi0j+iHrGiExobIQPfziYZu0nP4EzzoDH\nHos6KpHiokQ4TxwIZ4yYF9FgtXOamhh05+HOzkief7h729tZWVtLc0VF1KGMaWFYJ5zPy1RLfjGz\nC8zsaTPbbmYfH+HxKjO7JXx8Uzh/e/Kxa8LtT5vZG8Zr08yWhm1sD9usTHnsbWa2xcyeMrP/yd4r\njkYxJMIQlEr87d/CfffBwAC86lVw881RRyVSPJQI54nkjBFVOZ4xIinZ87oxDwbMDblzf3t73pdF\nQFAnvLS6mmeVCEsazKwM+ApwIbACuMLMVgzb7UrgmLsvA74IXBceuwK4HFgJXAB81czKxmnzOuCL\nYVvHwrYxs+XANcDZ7r4S+OssveTIHD4c1NTOmBF1JJmxdi088giceSZccUUw77CITJ0S4TwR1YwR\nSTMqKlhZW5sXifDvu7roGBoqiEQYglk39sXj9OZJWYnktbXAdnff4e5x4GbgkmH7XAJ8J7z/A+D8\ncBrLS4Cb3b3f3Z8DtoftjdhmeMx5YRuEbb4lvP+XwFfc/RiAux/KwmuN1JEj0NQULGdcLObMgd/8\nBi6+OKgb/trXoo5IpPApEc4DyRkjoiqLSDqnqYn729sZinjmu2Qyfu60aZHGka5lNTU4sKOvL+pQ\nJP8tAPakfL833DbiPu4+CLQDzWMcO9r2ZqAtbGP4c50InGhm95nZg2Z2wRRfV945fLjwyyJGUlUF\nP/whvOlN8MEPwo9/HHVEIoVNiXAeeH7GiAh7hCFIhDuGhniyuzvSODa2t7OwqorFEZ+PdC2triYG\nqhOWQlIOLAdeC1wBfMPMXvLO08zWmdlmM9vc2tqa4xCnplgTYQiS4e9/H1avhve8B3bsiDoikcKl\nRDgPHEjOGJEHPcIQbZ2wu3NvWB9sBTJpZnUsxsKqKtUJSzr2AYtSvl8YbhtxHzMrB5oIVuoc7djR\nth8BpoVtDH+uvcAGdx8Iyyy2ESTGL+Lu6919tbuvnpUnc4ynY2gI2toKZ1W5yaiqgltvDeqgL700\nGEgnIhOnRDgPtIRXsDkRF7MdV13NgsrKSBPhnX197I/HObdA6oOTltXU8FxfX+RlJZL3HgaWh7M5\nVBIMftswbJ8NwLvD+5cCd4YrdW4ALg9nlVhKkLg+NFqb4TF3hW0QtvmT8P6PCXqDMbOZBKUSRdOv\n2N4O7sUzUG40S5fCjTfC734Hv/xl1NGIFKZxV5aT7DsYj9NUVhb5UsJmxjlNTdzb1oa7R9Ije2+Y\nhBfKQLmkE2pquLOtjT39/Sypro46HMlT7j5oZh8C7gDKgG+5+1Nmdi2w2d03AN8EbjKz7cBRgsSW\ncL9bgS3AIHC1uw8BjNRm+JT/ANxsZv8C/C5sm3DfPzazLcAQ8HfufiTbrz9XkgtPFMgwg3GtXz/2\n42eeCXfcAeecA9On5yYmkWKhRDgPtMTjzIm4LCLpnKYmbmltZXd/P8dFkNBtbG+nqawskqWmp+KE\n8Fxt7+1VIixjcvfbgduHbftkyv0+4LJRjv0M8Jl02gy37yCYVWL4dgc+Gt6KTjIRLpWk8K1vhccf\nDwbOvfe9UUcjUlhUGpEHWuJx5uZRIgzR1QlvbG/n7KYmygqkPjhpekUFzeXlqhMWyQOllgjPnAnn\nnw8PPgg7d0YdjUhhUSIcsa6hIboTibzpEX55fT0NZWWRJMKH43G29vQUXFlE0gk1NWzv7cVVJywS\nqWPHgsFkNTVRR5I7F14IdXXwi19EHYlIYVEiHLGD4dLKUQ+USyoz41WNjZEkwvd1dAAU3EC5pGU1\nNXQMDXFYw7dFItXWFtQHF9gHS1NSUwOvfnVQIpFcXlpExqdEOGItYSKcL6UREJRHPNndzbEcJ3Qb\n29upNGN1Q0NOnzdTloXdT89qYQ2RSB07VjplEale85og+b/77qgjESkcSoQjdjAep9yM5jzpEYYX\n6oTvD3toc+XetjbWNDRQHfHsGZM1r7KSmlhMC2uIRKxUE+Hp02HVKrjvPginpxeRcSgRjlhLPM6s\nigpiefQZ3trGRsrNuC+H5RHdQ0M80tVVMMsqjyRmxgnV1RowJxKhRCKYR7iALyVTct550NMDmzZF\nHYlIYVAiHLGDeTR1WlJtWRln1tfntE74/vZ2Bt15bYH/9zqhpob98XjOy0pEJNDeHiTDpdgjDHDC\nCbBwIWzcGHUkIoVBiXCEhtxpHRjIq/rgpHOamnioo4P+RCInz3d3WxtlwKsaG3PyfNmSrBPOdVmJ\niATa2oKvpZoIm8HatbBrF7S2Rh2NSP5TIhyhwwMDJIC5eVQfnHROUxP97mzu7MzJ8/1vWxtnNjTQ\nUF7Ya7wsqa4mBjktKxGRF5TaHMIjWb06+PrII9HGIVIIlAhH6Pmp0/KwRzhZq3tX8r9KFvUMDfFQ\nZ2fBl0UAVMZiLK6uViIsEhElwtDcDEuXKhEWSYcS4Qi15HEi3FxRwen19dyZ/Jwxix7o6GDAndcU\nQSIMcHx1NZs7OxnMUVmJiLzg2DGoqAgWlyhlZ54Ju3fDoUNRRyKS35QIR6glHqehrIy6PJ0u7Lxp\n07i/vZ3eoaGsPs//trURg4JdUW64pdXV9CQSbOnpiToUkZLT1hb0BufRRDyROPPM4OvmzdHGIZLv\nlAhH6ODAQF72BiedN306/e48kOWBX//b1sYZDQ00Fnh9cNKS6moANmnAnEjOHTtWulOnpZoxI5hB\n4tFHo45EJL+Nmwib2SIzu8vMtpjZU2b2kRH2MTO73sy2m9kTZnZGdsItLi3xeN4srTySc5uaKAPu\nzGKdcO/QEJs6OnhNkfQGA8yqqKC5vFyJsEgESnUxjZGcdhrs2fPCTBoi8lLp9AgPAh9z9xXAK4Cr\nzWzFsH0uBJaHt3XA1zIaZRHqGRqic2gor3uEG8vLWdPYmNU64Y3t7fS7c14R/ecyM9Y2NrIpRzNu\niEggkXihNEJgRfifesuWaOMQyWfjJsLufsDdHw3vdwJbgQXDdrsEuNEDDwLTzGxexqMtIsmBcvk4\nh3Cq86dN46GODjoHB7PS/q+OHaPSrGgGyiWd1djIU93dWTtvIvJSXV0wNKTSiKQFC6CxUYmwyFgm\nVCNsZkuAVcDwxRsXAHtSvt/LS5NlSXEwXHksn3uEIagTHgLuzdJ0YL86epSzm5rydsDgZJ3V0IBD\nzuZhFhFNnTZcLBb0Cm/dGvSWi8hLpZ0Im1k98EPgr919UsWPZrbOzDab2ebWEl/y5mA8ToygnjSf\nvbKxkepYjDuOHs142wf6+3miu5s/LsL/WmvDFfIeUiIskjPJ9+tFNORgylasCHrKNWhOZGRpJcJm\nVkGQBP+3u982wi77gEUp3y8Mt72Iu69399XuvnrWrFmTibdotMTjzKqooCzP5/ipKSvjvGnTuD0L\nifBvwu6bP54xI+NtR21GRQXLa2o0YE4kh5LDGVQa8YKTTw6+3nFHtHGI5Kt0Zo0w4JvAVnf/wii7\nbQDeFc4e8Qqg3d0PZDDOotMSj+d9fXDSRc3NbO/tZVuG58X91bFjzAwX7ihGaxsalAiL5FB7ezB/\ncPiBjBCci0WLlAiLjCadHuGzgT8HzjOzx8LbRWZ2lZldFe5zO7AD2A58A/hgdsItDgl3DuX5HMKp\nLg57bH9+5EjG2ky48+ujR3n99OnE8rxXfLLOamxkfzzO3r6+qEMRKQnt7VBfD0U25GDKVq6EBx4A\nVWqJvNS4Kxi4+0ZgzEzF3R24OlNBFbsjAwMMuhdMIrykpoYVtbX8/MgR/mbRovEPSMMTXV20DAwU\nZX1w0llht9Smzk4WhotsiEj2tLWpLGIkJ50Ev/wlPPggvP71UUcjkl+0slwEWsIZIwqlNALg4uZm\n7mlvz9h0YD85cgQDLijC+uCk0+rrqTRTeYRIjrS3a6DcSI4/PphB4t57o45EJP8oEY7AwXAO4Xxe\nVW64i2bMYMD9+QFuU/Wj1lbObmpiblVVRtrLR1WxGKvq65UIi+SIEuGRVVfD6acrERYZiRLhCLTE\n49TGYtQXUCHb2U1NNJWV8dMM1Anv6O3l8e5u/mTmzAxElt/Oamxkc2cng5rEUySrBgeho0OlEaM5\n91zYtAnCfhgRCSkRjkBLPM6cykqsgAaJVcRivHnmTH50+DD9U0zqfnT4MEDJJMI9iQRbMjzjhoi8\n2KFD4K4e4dGcey709mo+YZHhlAhHoJCmTkt1xezZtA0O8sspzil8W2srq+rrWVpTk6HI8tfahgYA\nlUeIZNmBcMJOJcIjO+ec4KvKI0ReTIlwjvUlErQNDRXMjBGpXjd9Os3l5XyvpWXSbRzo7+f+jg7e\nWgK9wQAn1NTQXF6uRFgky/bvD76qNGJkc+bA8uWwcWPUkYjkFyXCOZYcKDe3gAbKJVXEYrxt9mw2\nHDlC1yRnj/hhuLT2n5TIyoJmxtrGRjZpAk+RrEomwuoRHt255waJsIYsiLxAiXCOtSRnjCjAHmEI\nyiN6Ewl+MolBc+7ONw4c4Iz6elbW1WUhuvx0VmMjT3V3Z2zqORF5qQMHtKrceM45B44eha1bo45E\nJH8oEc6xlngcA2YVYI8wBLNHLKyq4r8nUR7xUGcnT3R3s27+/CxElr/WNjTgwKNdXVGHIlK09u+H\nhgatKjeWV70q+LppU7RxiOQTJcI5djAeZ2ZFBRWxwjz1MTPeM3cuvzx6lG0TnAnh6/v3UxeL8Y7Z\ns7MUXX5aEw6Ye0h1wiJZs3+/yiLGs3x5UEOtRFjkBYWZjRWwloGBgi2LSPrQggVUmPHFvXvTPqZ9\ncJCbDx3iHXPm0FA+7sreRWVmZSVLq6t5WHXCIllz4IAS4fHEYrBmDTz0UNSRiOSP0spIIpZwpyUe\n56QCnzZsTmUl75o7lxsOHuTaJUuYlUZif9PBg/QmEry/xMoiktY0NPCQEmGRrNm/H5YtizqK/LV+\nffC1vByeeAK+/GUYfulety73cYlETT3COdQ2OMiAe0HOITzcRxcupC+R4KvJodpj6B4a4rO7d/OK\nxkbODMsESs3axkZ29vXRqmWdRDJucBBaWtQjnI6lS4NZI3bvjjoSkfygRDiHDhb4jBGpTq6r443N\nzXxp716ODAyMue+/797N/nicz59wQo6iyz/JOmGVR4hknlaVS9+SJcHXnTujjEIkfygRzqHk1GnF\n0CMM8C9Ll9IxNMTV27aNus/evj7+bc8e3jZrFmeX8H+pM+rriaEBcyLZoMU00tfUBDNmwHPPRR2J\nSH5QIpxDBwcGqI7FaCyS+X1Oq6/nU0uWcEtrK7ccOvSSx4fc+cj27STcue744yOIMH/Ul5ezoq5O\nPcIiWaDFNCZmyRL1CIskKRHOoZZ4nLkVFZhZ1KFkzD8sWsTahgY+uG0bG9vant8+mEjwrq1bue3w\nYf5l6VKWFPgAwUxIDphz96hDESkqBw4EX5UIp2fJEjh8GPS+XESJcE4djMeLoj44VXksxndPPpnG\n8nJe/dhj/NUzz/DZXbv44yee4H8OHeJfly7lbxcvjjrMvLC2oYHDAwPs6uuLOhSRorJ/v1aVm4il\nS4Ov6hUW0fRpOdOXSHBscLBo6oNTLa+t5ferV/P3O3bwpX37AJhfWcn1y5bx4YULI44uf6wJ/0s/\n3NmpHnKRDNq/H2bP1qpy6Vq8OHjjsHMnvPzlUUcjEi0lwjlyqMgGyg1XX17OV088kU8cdxz1ZWU0\nltiiGel4eV0dVWY81NnJZSW2up5INh04ACU6RfmkVFcHbxz27Ik6EpHoKVvJkYNFnggnza+qijqE\nvFUZi3F6fT0Pa+YIkYzav1+J8EQtWgQ7dkQdhUj0VCOcIwficWLArIqKqEORCK1pbGRzZydDGjBX\nsszsAjN72sy2m9nHR3i8ysxuCR/fZGZLUh67Jtz+tJm9Ybw2zWxp2Mb2sM3KYc/1p2bmZrY6O682\nN5QIT9zixXD0KHR1RR2JSLSUCOfIwXicmRUVVMR0ykvZ2oYGuhMJ/tDTE3UoEgEzKwO+AlwIrACu\nMLMVw3a7Ejjm7suALwLXhceuAC4HVgIXAF81s7Jx2rwO+GLY1rGw7WQsDcBHgE3ZeK25MjgYLKgx\nb17UkRSWRYuCryqPkFKnrCxHDsbjRV8WIeNLrjCnhTVK1lpgu7vvcPc4cDNwybB9LgG+E97/AXC+\nBXMuXgLc7O797v4csD1sb8Q2w2POC9sgbPMtKc/zzwSJckFPY9LSEqwqpx7hiUlO5qNEWErduImw\nmX3LzA6Z2ZOjPP5aM2s3s8fC2yczH2ZhS7hzaGBAibBwYm0tjWVlWlijdC0AUlOPveG2Efdx90Gg\nHWge49jRtjcDbWEbL3ouMzsDWOTuPx8rWDNbZ2abzWxza2truq8xp5KLaSgRnpj6epg+XYmwSDqD\n5W4AvgzcOMY+97r7GzMSURE6MjDAoHteJ8Lrk/9NJKtiZqxuaFAiLJExsxjwBeA94+3r7uuB9QCr\nV6/Oy8L25KVr3rwXFtaQ9CxaBLt3Rx2FSLTG7RF293uAozmIpWgdKJEZIyQ9axsbebyri/5EIupQ\nJPf2AYtSvl8YbhtxHzMrB5qAI2McO9r2I8C0sI3U7Q3AKcDdZrYTeAWwoVAHzCWTX/UIT9yiRUFp\nSX9/1JGIRCdTNcKvNLPHzewXZrYyQ20WjVKZOk3Ss6ahgQF3Htdw7VL0MLA8nM2hkmDw24Zh+2wA\n3h3evxS404N1uTcAl4ezSiwFlgMPjdZmeMxdYRuEbf7E3dvdfaa7L3H3JcCDwJvdfXO2XnQ27d8P\nsVgwL65MzOLFQX313r1RRyISnUwkwo8Cx7n7acCXgB+PtmMh1Jtlw8F4nIayMuq07JGgAXOlLKzX\n/RBwB7AVuNXdnzKza83szeFu3wSazWw78FHg4+GxTwG3AluAXwJXu/vQaG2Gbf0D8NGwreaw7aKS\nXFVOa/hMnAbMiWRgQQ1370i5f7uZfdXMZrr74RH2zft6s2w4GI8zT73BElpYVcXcykrVCZcod78d\nuH3Ytk+m3O8DLhvl2M8An0mnzXD7DoJZJcaK57XpxJ2vtKrc5E2fDnV1SoSltE25R9jM5obT9GBm\na8M2j0y13WKiqdMklZmxpqGBh5QIi0yZFtOYPDMNmBNJZ/q07wEPACeZ2V4zu9LMrjKzq8JdLgWe\nNLPHgeuBy8PaNAE6BwfpTiSYo0RYUqxtaODpnh46BgfH31lERrV/vxbTmIpFi4JzODQUdSQi0Ri3\nNMLdrxjn8S8TTK8mI9BAORnJmsZGHHiks5M/mj496nBECtLAALS2qkd4KhYvDlbn0wyaUqq0slyW\nKRGWkaxODphTeYTIpGlVuanTUstS6pQIZ9nBgQEqzJihIc2SormighOqq3lYM0eITFrqYhoyOXPm\nQGWlEmEpXUqEsyw5UC4WjCcUed6axkb1CItMgRbTmLpYDBYs0IA5KV1KhLNMM0bIaNY2NLCnv5+D\nWtZJZFKSPcJKhKdm8eJgUQ0tdimlSIlwFvUODXFkYEAzRsiIkgtraD5hkcnRqnKZsXgx9PXBjh1R\nRyKSe0qEs+iZ3l4cDZSTka1qaKAMDZgTmax9+2DuXNCinVOTHDD36KPRxiESBSXCWfSHnh5AibCM\nrK6sjFPq6tikAXMik7JvX1DfKlMzf37Qs/6730UdiUjuKRHOoj/09GDAnIqKqEORPPXKpiY2dXSQ\n0Bo0IhOmRDgzKiqCZFiJsJQiJcJZ9IeeHporKqiM6TTLyF7Z2EjH0BBburujDkWk4CgRzpxFi+Cx\nx6KOQiT3NLltFm3t6WGueoNL0vo0l2lqCRdc+bc9ezinqWnMfddpaLzI83p6oK1NiXCmLFoEDzwQ\nTEmneZmllKirMksS7jzd06MZI2RMsysqqIvF2NHbG3UoIgVl377gqxLhzEgOmFN5hJQaJcJZsqe/\nn95EQgPlZExmxvE1Nezo64s6FJGCsndv8FWJcGYkE2GVR0ipUSKcJU+FNZ/zq6oijkTy3fHV1RyI\nx+keGoo6FJGCoR7hzKqpgeOPV4+wlB4lwlnyZDIRVo+wjOP4mhoAnlOvsEjalAhn3umnq0dYSo8S\n4Sx5srubBZWV1GqmdxnHkupqDFQnLDIB+/ZBQ0Nwk8xYtQq2bwdNbS6lRIlwljzZ3c0pdXVRhyEF\noDoWY0FVleqERSZg3z5YuDDqKIrL6acHXx9/PNo4RHJJiXAWDLmzRYmwTMDx1dU819enhTVE0qQ5\nhDNv1argq8ojpJQoEc6CZ3t76XdXIixpO76mhr5EggPhvMIiMjYlwpk3fz7MmqUBc1JalAhnQXKg\nnBJhSdfx1dWA6oRF0jE0FCz8oEQ4s8w0YE5KjxLhLHiyuxsDTlYiLGl6fmEN1QmLjOvQoSAZViKc\neatWwZNPgj6cklKhRDgLnuru5vjqauo0Y4SkSQtriKRPU6dlz6pVMDAAW7ZEHYlIbigRzgLNGCGT\ncXx1NQe1sIbIuJQIZ09y5giVR0ipUCKcYf2JBNt6e1mpRFgmSAtriKRHiXD2LF8OtbUaMCelQ4lw\nhm3r6WFQM0bIJGhhDZH07NsHZWUwe3bUkRSfsjI49VT1CEvpGDcRNrNvmdkhM3tylMfNzK43s+1m\n9oSZnZH5MAvH7zVjhEySFtYQSc/evTBvXpC0SeatWhUkwolE1JGIZF86PcI3ABeM8fiFwPLwtg74\n2tTDKlyPdXVRacbLamujDkUKkBbWEBnf3r1aVS6bVq0Klll+7rmoIxHJvnETYXe/Bzg6xi6XADd6\n4EFgmpnNy1SAheaxri5OqaujIqaqE5m45eHCGnv7+6MORSRv7d4Nxx0XdRTFSwPmpJRkIltbAOxJ\n+X5vuK3kuDuPdXVxen191KFIgVoeDpjbpjphkRElEkEivHhx1JEUr1NOCcpONGBOSkFOuy3NbJ2Z\nbTazza2trbl86pw4EI/TOjCgRFgmbXpFBTMrKnhGibDIiFpagsUe1COcPTU18LKXqUdYSkMmEuF9\nwKKU7xeG217C3de7+2p3Xz1r1qwMPHV+eayrC0CJsEzJ8poanunpwVUnLPISu3cHX5UIZ9eqVeoR\nltKQiUR4A/CucPaIa1TjlgAAIABJREFUVwDt7n4gA+0WnGQifKoSYZmC5TU1dCcSHNAapyIvsWtX\n8FWlEdm1ahXs3x8sZy1SzNKZPu17wAPASWa218yuNLOrzOyqcJfbgR3AduAbwAezFm2ee6yri+Or\nq2kqL486FClgJ4Z1wiqPEHmpZCKsHuHsOiOcCHXz5mjjEMm2cTM2d79inMcduDpjERUwDZSTTJhZ\nUcG08nK29fbymmnTog5HJK/s3g1NTcFNsufMM8EsSIQvuijqaESyR3N8ZUjX4CDbe3uVCMuUmZnq\nhEVGsWuXeoNzoaEhGDD38MNRRyKSXUqEM+T33d04GignmXFiTQ3tQ0McGhiIOhSRvKKp03JnzZog\nEdb7cSlmSoQzRDNGSCadFK5M+IeenogjEckv6hHOnTVrgunq9u6NOhKR7FEinCGbOztpLi9nYVVV\n1KFIEZhdUcGM8nIlwiIpOjqgrU2JcK6sWRN8VXmEFDMlwhnyUGcnaxsbMbOoQ5EiYGacXFvLH3p6\nSOhzSRHghTmEVRqRG6edBuXlmjlCipsS4QzoGhxkS3c3axoaog5FisjLamvpSSTY3d8fdSgieUFT\np+VWdTW8/OXqEZbipkQ4Ax7t6iIBrG1sjDoUKSIvU51wUTKzC8zsaTPbbmYfH+HxKjO7JXx8k5kt\nSXnsmnD702b2hvHaNLOlYRvbwzYrw+0fNbMtZvaEmf3WzAoitdSqcrm3Zk3QI6wPpqRYKRHOgIc7\nOwHUIywZ1VhezsLKSrYqES4aZlYGfAW4EFgBXGFmK4btdiVwzN2XAV8ErguPXQFcDqwELgC+amZl\n47R5HfDFsK1jYdsAvwNWu/upwA+Af8vG6820XbugshLmzIk6ktKxZk1Ql719e9SRiGSHEuEMeKij\ng+OqqphdWRl1KFJkXlZXx/beXuKJRNShSGasBba7+w53jwM3A5cM2+cS4Dvh/R8A51sw+OAS4GZ3\n73f35whW81w7WpvhMeeFbRC2+RYAd7/L3ZPvsB4EFmbhtWbcrl2waBHE9J8rZ9auDb5u2hRtHCLZ\nostJBjzc2ckalUVIFpxcW8ugO9u13HKxWADsSfl+b7htxH3cfRBoB5rHOHa07c1AW9jGaM8FQS/x\nLybxWnJu926VReTaypXB4hr33x91JCLZMe4SyzK21nic5/r6+MD8+VGHIkVoeU0N5WY82d0ddShS\nhMzsncBq4DWjPL4OWAewOA+mati5E97whnF3k0lav37k7QsXwk9/Cqf//+3deXwc1ZXo8d/RvrTQ\nbllewPKCV7yHzUDMlgBhbBgMNiEkwxIThjwyj08WmCQMQzAvDEkmYZIQjEOCgYcxfmAcAjEYmzXB\nYBvZwsb7Ii+ytUuWLGtp3ffHLaGW0NKWWl0l9fl+PvfT1berq091t6qObt+6dyosXBjemJTqa9oi\n3EsbtH+w6kPxUVGMS0ykQBPhgeIwMDzg/jCnrsN1RCQGSAXKunhuZ/VlQJqzjS+8lohcBvwYmGOM\n6XBoEmPMYmPMTGPMzOzs7FPYzdCrrYUjR2D0aFfDiEijRsHhw6A/TKmBSBPhXvro+HEEmKGJsOoj\nk3w+ihsb2akXzQ0EHwNjnNEc4rAXv61qt84q4FvO8jxgrTHGOPULnFEl8oAxwEedbdN5zjpnGzjb\nfAVARKYBT2CT4OI+2teQarlYa8wYd+OIRKNH21Ej9u1zOxKlQk8T4V5aX13NhKQkUmK0l4nqG2cl\nJwPwalmZy5Go3nL6634XWA18Biw3xmwVkQdFZI6z2h+BTBHZDdwD3Os8dyuwHNgG/A24yxjj72yb\nzrZ+BNzjbCvT2TbAo4APeFFE8kWkfTLuObt22VtNhMMvLw9EdOQINTBp9tYLfmP4oKqKBYMGuR2K\nGsCyYmMZEhfHX8vKuGf48O6foDzNGPMa8Fq7uvsDlk8C13fy3EXAomC26dTvxY4q0b7+slMO3GUt\nibB2jQi/hATbT3jPHrcjUSr0tEW4Fwpqaqj2+7kwNdXtUNQANyk5mXerqqhqaup+ZaUGoF27IDcX\nfD63I4lMo0bZrhF6CFIDjSbCvfBeVRUAF6aluRyJGugmJyfTZAxvlJe7HYpSrti1S7tFuGnUKKiv\nh4ICtyNRKrQ0Ee6F96qqGB4fzxkJCW6Hoga4kYmJZMTEsLK01O1QlHKFJsLuaumS8v777sahVKhp\nItxDxhjeq6rSbhEqLKJF+OfsbFaVlVHn97sdjlJhVV0Nx45p/2A3ZWRAZiasW+d2JEqFlibCPbSn\nro6jDQ2aCKuwuSE7mxq/n9XaPUJFGB06zRvGj4e1a7WfsBpYNBHuIe0frMLt4rQ0MmNiWF5S4nYo\nSoWVDp3mDePHQ1UVbNjgdiRKhY4mwj30XlUVGTExjE9KcjsUFSFioqJs94jSUu0eoSKKDp3mDePG\n2fGE16xxOxKlQkcT4R56p7KSC1JTiRJxOxQVQW7Izqa2uZm/afcIFUF27YKhQ0HbHdzl88G0afDm\nm25HolToaCLcA3vq6th78iSXpae7HYqKMLPT0siKjeX54n4xK65SIaEjRnjH5ZfDP/4BNTVuR6JU\naASVCIvIFSKyQ0R2i8i9HTz+LyJS4kzVmS8it4c+VO9ouVjpqxkZLkeiIk1MVBQ3DhrEK6WllDU2\nuh2OUmGhibB3XHYZNDbCu++6HYlSodFtIiwi0cDvgCuBCcCNIjKhg1VfMMZMdcqSEMfpKavLyxmR\nkMCYxES3Q1ER6LbcXBqM4bljx9wORak+V14OpaWaCHvFBRfYKZe1e4QaKIJpET4b2G2M2WuMaQCW\nAXP7NizvamhuZm1lJV9NT0e0f7BywRSfj5kpKSwpKsIY43Y4SvWpLVvs7eTJ7sahrIQEmD0bVq0C\nPfyogSCYRHgocDDg/iGnrr3rRGSLiKwQkeEhic6D/lFdTY3fr90ilKtuGzyYgtpaNhw/7nYoSvWp\n/Hx7O3Wqu3GoVvPmwd69rZ+NUv1ZqC6W+wswwhgzGXgTeLqjlURkoYhsEJENJf10LNTV5eVEA5fo\nhXLKRTfm5JAYFcUfi4rcDkWpPrV5M+Tk2KK8Ye5ciI6GFSvcjkSp3gsmET4MBLbwDnPqPmeMKTPG\n1Dt3lwAzOtqQMWaxMWamMWZmdnZ2T+J13erycs5LTSU1JsbtUFQES42J4YbsbJ49dowKvWhODWD5\n+doa7DVZWbZ7xIoV2j1C9X/BJMIfA2NEJE9E4oAFwKrAFUQkN+DuHOCz0IXoHUX19WyqqeGr2hqs\nPOB/Dx9ObXMzfzhyxO1QlOoTDQ2wbRtMmeJ2JKq9efNg507YutXtSJTqnW4TYWNME/BdYDU2wV1u\njNkqIg+KyBxntbtFZKuIbAbuBv6lrwJ200ulpQD8cz9tzVYDyxSfj6+kp/PY4cPUNze7HY5SIbd9\nu02GtUXYe6691s4yp90jVH8XVB9hY8xrxpgzjTGjjDGLnLr7jTGrnOX7jDETjTFTjDEXG2O292XQ\nbllRUsL4pCQmJCe7HYpSAPxg+HCONjTwrA6lpgagzZvtrbYIe09ODlx4ISxbpt0jVP+mM8sF6VhD\nA+9WVjJPW4OVh1yans40n49HCwvx69lIDTD5+Xa4rjPPdDsS1ZFbb4UdO2DtWrcjUarnNBEO0srS\nUpqB6zURVh4iItx3+unsqKtj6dGjboejVEht3gyTJoFem+xN8+fbC+d++1u3I1Gq5zQRDtKKkhLO\nTExkknaLUB4zLzubc1JS+Mm+fdT6/W6Ho1RIGKMjRnhdQgJ8+9t2co0DB9yORqme0UQ4CKUNDayr\nqGBedrbOJqc8R0T45ejRHGlo4FcHD3b/BKX6gSNHoKxM+wd73Z132tvf/97dOJTqKU2Eg/BccTF+\nYP6gQW6HolSHZqWmcl1WFo8UFnK4vr77JyjlcevX29vp092NQ3Vt+HC45hpYsgSqqtyORqlTp4lw\nN4wxLD5yhLNTUpjs87kdjlKdemTUKJqB23fswOiFc6qfW7cOkpJg5ky3I1Hd+fd/h4oKePBBtyNR\n6tRpItyNv1dXs+3ECRYOGeJ2KEp1aVRiIo+OGsXfystZrFMvq35u3Tq44AKIi3M7EtWdGTPg9tvh\nscfgswE5nZYayDQR7saTR46QEh3NfB0tQvUDdw4ZwuXp6dyzezc7T5xwOxyleqS42M5YdvHFbkei\ngrVoEfh8cPfdOq6w6l80Ee5CRWMjL5SUcFNODj4dv0f1A1EiPDV2LIlRUVxdUEBpQ4PbISl1yt55\nx95qItx/ZGfbrhFr1sAvf+l2NEoFT7O7Lvzp6FFONjfz7dxct0NRKmjDEhJ45ayzuDQ/n2s+/ZQ1\nU6aQEB3tdlhKBW3dOtu6qBfK9S933QXvvw8/+AHk5sJNN3W+7uLF3W9v4cLQxaZUZ7RFuBN1fj+P\nHjzIJWlpTE9JcTscpU7JrNRUnhk/ng+qq7l261ZqmprcDkmpoK1bZ6fvjY11OxJ1KqKiYOlSmD0b\nbrnFJrvNzW5HpVTXtEW4E0uKijja0MCyCRPcDkWpHrl+0CCebGrijp07mZ2fz18nTyan3ZVHi48c\nCfnr6oWlqjeKimD7djt9r+p/4uNh5Uq49lq44w547jn4j/+AWbPsY4FOnIDS0ralpsbW+/2wfLn9\nZSA3F844w06uMm0a5OS4s29qYNJEuAP1zc08UljIhampfDktze1wlOqx24cMYXBcHPO3bWPahg08\nOXYsX8vMdDsspTq1dq291f7B/VdqKrz1Fjz1FHz/+3DppXYovLFj7Wx09fX2n5321/MmJUFKir2N\niYGTJ+2Fkx98YJPkFkOG2G4z555rE+wvfQl00lfVU5oId+CPRUUcbmjgz+PGuR2KUr12dVYWH0yb\nxs3bt3N1QQHfyMnhP0eMYGRiotuhKfUFy5bB0KG25U/1XyJw220wfz68/TasXg3799vkNi3NJryZ\nmfYiu6wsu9xVMltXBwcPQmGhvd24EV591T4WE2Nbi2fNgvPPh3POgdNPtzEEK7DPcnOzTdJratqW\nc8+F6OjWkpBgv6stJSGhJ++Ucpsmwu2UNjTw0337uCg1lUvT090OR6mQmJqSwoYZM/jZ/v384uBB\nnj92jJsHD2ZQbCwjExJ06nDlCcXF8PrrthVRr+/0plO9yM3ng6uvtuVUtxMoMRHOPNOWFrW1sG8f\n7N4Ne/bYaZ5/8xv7WHy87UKRkWHHo25JvpuboaHBlvp6OH4cSkqgoKBt0tvREHDPPNN1jD6fTYhH\njLBdOUaMsK/f/vCqFwF6iybC7fxw716q/X5+f+aZmhyoASU+KoqHRo7kzqFDeaSwkCVFRdQ1NzMo\nNpbJPh8Tk5IYmZhIQpReQ6vc8fzztm/ozTe7HYnqD5KTYdIkW8B+d1pajYuK4OhROHbMJrDV1W2T\n2+hoO1mLz2dbpUVsX2Sfr21JSbG3ycn24s3m5tbS0GCnla6osKW83L72mjU2FoD0dJg8Gc46y3YN\n0QlivEcT4QDvVlbyp6NHuff005moHY7UADU0Pp7Hxozhobw8/teuXXx8/DhvV1aypqICAQbHxTEi\nIYEz4uM5PSGBYfHxxGtyrMJg6VI7S9nEiW5Hovqj6GjbCjtiRNv6hQtbuzu0JMDtf3E41RbqFh1d\nG9zYCIcO2a4g27fDhx/asbFjY2H8eDjtNJgzx/aFVu7TRNhR2djIrdu3c0Z8PD894wy3w1Gqz50W\nE8Os1FRmpaZS39zMrro69p08yYGTJ9laW8s/qqsBECAnLo7h8fGfl9MTEvDpb9cqhD79FDZtav1p\nW6lQioqyLbvhEBsLeXm2XHyxTYx37YItWyA/H2680cZy3XX214/Zs7UrkJs0EQaajeGmzz6jsL6e\nt6dOJUm/kSrCxEdFMSk5mUnOLyHGGCqamjhYX09hfT0HT55kT10dHx8//vlzcmJjGZOYyJikJMYk\nJpKpg76qXnjySXvR04IFbkeiequnrasDVWwsTJhgyw03wLhx8Oyz8OKL8PTTtlX561+Hb3zDdqPQ\nXpnhpYkw8MD+/bxWXs7vx4zh/NRUt8NRqkN9MeZvZ0SEjNhYMmJjmRLQjFLr93Owvp4DTmK8qaaG\n952W46zYWCYlJ3N6fDyz09J0NjsVtD174PHHbevYoEFuR6MGGi8l5lFRsHMnnH22HemioADWr4df\n/Qp+8QubFJ9zDvz613bkC9X3Ij4R/vmBA/zswAFuGTyY7+hEAEp1KTk6mnFJSYxzOrc1G8ORhgZ2\nnjjBthMn+KCqiisrK0mKiuLS9HTmZmXxT5mZDNIrRFQXfvhD229z0SK3I1EqfOLibJ/4GTPsSBUb\nN9qk+OWXbbnoIttKPG+evehO9Y2ITYSNMTywfz8PHjjA1wcNYrGOEqHUKYsSYVh8PMPi47kkPZ2G\n5mZGJSby17Iy/uIUwU75PDczk2uyshitV4ioAO+8Ay+9BD/7mb1qX6lI5PPBl79sS0kJfPSRTYoX\nLoQ777QjTkydartOpKfrEGyhJKajwfLCYObMmWbDhg2uvHaZc2HcqrIybhk8mCfHjiW6j5LgcP6c\nrZQXtEyxbIxhc00NK0tLeaWsjPyaGgAmJiUxNyuLa7KymJGSQlQ//QdURDYaY2a6HUe49MUxu6TE\njvFaVwc7dtixYnvDSz+BK9VbxsCBA7BhA2zebMfZBjtG8c03wyWXwHnn6UQewersmB1RLcLNxvBC\ncTE/2LOH4sZG/nvUKL43bJi2BCvVB0SEqSkpTE1J4YG8PPbX1fFKWRmvlJbySGEhDxcWMjQujjlZ\nWczJzOSC1FR8MRF1SIpox4/DlVfacVffeKP3SbBSA41I63Bw111nx0bevNmWhx+Ghx6yE4ecdx5c\neKGddnrqVJsoa1oTvKDOOiJyBfAbIBpYYoz5ebvH44GlwAygDJhvjNkf2lB7rs7v5+XSUh49eJD8\nmhqmJCez6qyzmJ6S4nZoSkWMEYmJfG/YML43bBhljY381UmKnz56lMePHCFGhLNTUrg4LY2L09OZ\nmZJC6gBMjHtzPBWR+4DbAD9wtzFmdVfbFJE8YBmQCWwEbjbGNLh9zN63z7Zo5efDypX2JK6U6pyI\nvZBuyBD7D2RdnR2SbccOW955p3XCkKQkGDbM9jEeObJ1KLfcXDvTXXJyz6ef7kx/7qrR7VlGRKKB\n3wGXA4eAj0VklTFmW8BqtwEVxpjRIrIAeASY3xcBB8MYQ1FDA+9UVvJGRQUrS0upbGpiVEICz44f\nz42DBvXbn2OVGggyY2P55uDBfHPwYOr8ft6rqmJdZSXrKir4eWEhiwoLARidmMh0n4/pKSlMTEpi\nVGIieQkJ/XZEit4cT0VkArAAmAgMAdaISMuEs51t8xHgv40xy0TkD862H+/sNfp2721XiCVLbH/g\n6Gh47rkvTr2rlOpeYqLtLzx5sr3f0ACHD9tfWA4etBN6rFrV2p0iUGysTYhPO81esBcXZ+taRsA0\npm05dqxtfYuEhNbyySd2hr6WZD03197m5NhhEb0smPDOBnYbY/YCiMgyYC4QeOCeCzzgLK8Afisi\nYkLcAbmisZGqpiZqm5up9fup9fup9vs5XF//eTlUX09BbS3FjY0ApMfE8LWMDG7NzWV2WpomwEp5\nTGJ0NF/JyOArGRkAVDc18feqKjbV1LDp+HE+Pn6c5SUln68v2Nnx8hISyImLY1BsLDlxcWTHxnJa\nTAxJUVEkR0fbEhVFUnQ0iVFRRIkgQBT2Ir+W26SoqHAm1j0+njr1y4wx9cA+EdntbI+OtikinwGX\nAF931nna2e7jnb1GqI/ZBw7YWbUKCuzt22/bqWfnzoX/+R8YPjyUr6ZU5IqLa235DVRfD2Vl9p/Q\n48ehttbOsFdba1uV/X5b6utbp4UWaW0xFrEtzO3rjLHPqaiAkydh7177Ou2PICJ2SMScHBg8+Iu3\naWm2hTopyd62LCcm2qHmWrYBNtmvq7P/RIdymMVgEuGhwMGA+4eAczpbxxjTJCJV2J/iSkMRZIsF\n27bxRkVFh49FA7nx8QyNi+OqzEym+Xyce9ppzEhJ6bML4ZRSoXdaTAxXZGZyRWbm53XljY3sOHGC\nPXV17HHGMD5w8iSf1tZS3NBAeVNTj1/vobw8fhy+2SR7czwdCnzY7rlDneWOtpkJVBpjmjpYPyzH\n7KVL4f777Ylr3Dj40Y9g/vzWViylVN+Kj29tpe1LCxdCU5NtgT5ypLUUFdnbY8ds2b7d3tbX9/y1\nrrwSXnstdLGHtcFaRBYCLT1JakRkR5BPzaKbA7Qfe5Q/BKwH/tzDGE9BtzG5QGMKjsYUnB7FdEcf\nBBIg5O/TT5zSAwN+LvZeHLPb8Pth61ZbHn6412F58W8lHCJ1vyFy973f7PcdoT3wd7nfr7/e44sB\nOzxmB5MIHwYCf8Aa5tR1tM4hEYkBUrEXYLRhjFkMnPIANyKywWvDFGlMwdGYgqMxBceLMZ2i3hxP\nu3puR/VlQJqIxDitwoHr9+kxuy8NgO9Aj0TqfkPk7rvud3hEBbHOx8AYEckTkTjsxRqr2q2zCviW\nszwPWBvqvmZKKTUA9OZ4ugpYICLxzmgQY4CPOtum85x1zjZwtvlKN6+hlFIRpdsWYaf/2HeB1diu\nuE8ZY7aKyIPABmPMKuCPwDPOxRvl2AOxUkqpAL05njrrLcdeWNcE3GWM8QN0tE3nJX8ELBORh4BP\nnG3T2WsopVSkCaqPsDHmNeC1dnX3ByyfBK4PbWhteOqnOYfGFByNKTgaU3C8GNMp6c3x1BizCFgU\nzDad+r20jiwRWN/Xx+y+1O+/Az0UqfsNkbvvut9h4NoUy0oppZRSSrkpmD7CSimllFJKDTieToRF\n5AoR2SEiu0Xk3j7Y/lMiUiwinwbUZYjImyKyy7lNd+pFRB5zYtkiItMDnvMtZ/1dIvKtgPoZIlLg\nPOcxZ1D87mIaLiLrRGSbiGwVke+5HZeIJIjIRyKy2YnpP536PBFZ72znBedCHZyLeV5w6teLyIiA\nbd3n1O8Qka8G1J/yZy0i0SLyiYi86oV4nOftd97bfBHZ4NS5/Z1KE5EVIrJdRD4TkfNc/j6Ndd6f\nllItIv/m9vukvK+nf5deIh4874SDePDcFg7i0fNnuIgHz9NfYIzxZMFe9LEHGAnEAZuBCSF+jYuA\n6cCnAXX/BdzrLN8LPOIsXwW8jp3Y6lxgvVOfAex1btOd5XTnsY+cdcV57pVBxJQLTHeWU4CdwAQ3\n43LW8znLsdihms8FlgMLnPo/AHc6y/8K/MFZXgC84CxPcD7HeCDP+Xyje/pZA/cA/xd41bnvajzO\nNvcDWe3q3P5OPQ3c7izHAWlux9Tu7/wodnxHT8SkxZulN3+XXip48LwTpv323LktTPvtyfNnGPff\nc+fpL8To9pvUxZt3HrA64P59wH198Doj2h2QdgC5znIusMNZfgK4sf16wI3AEwH1Tzh1ucD2gPo2\n651CfK8Al3slLiAJ2ISduaoUiGn/eWGvXj/PWY5x1pP2n2HLej35rLFjor6FnUL2VWf7rsUTsO5+\nvpgIu/bZYceH3YdzPYAXYmoXx1eAD7wUkxZvlt78XXqt4PHzTpjeA0+d28K0z544f4Zxfz15nm5f\nvNw1oqOpSId2sm4o5Rhjipzlo0BON/F0VX+og/qgOT8NTMP+B+lqXM7PG/lAMfAm9j+xoKZvBQKn\niD2VWLvya+CHQLNzP+jpZPsonhYGeENENoqdlQvc/ezygBLgT87PU0tEJNnlmAItAJ53lr0Sk/Im\nt84J4RBR330vndvCwYPnz3Dx6nm6DS8nwq4z9t8M48Zri4gP+H/Avxljqt2OyxjjN8ZMxf6HdzYw\nLpyvH0hErgaKjTEb3YqhCxcYY6YDVwJ3ichFgQ+68NnFYH+GfdwYMw2oxf786GZMADh9w+YAL7Z/\nzM2/PaXcNNC/+147t4WDl86f4eLx83QbXk6Eg5mKtC8cE5FcAOe2uJt4uqof1kF9t0QkFnugeM4Y\n85JX4gIwxlRiZ6s6D2f61g628/lrS3BTxJ7qZz0LmCMi+4Fl2J9dfuNiPJ8zxhx2bouBl7EHPTc/\nu0PAIWPMeuf+Cmxi7IXv05XAJmPMMee+F2JS3uXWOSEcIuK77+VzWzh45PwZLp49T3+B231Iuuhb\nEoPtBJ9Ha0foiX3wOiNo21frUdp23P8vZ/lrtO24/5FTn4Htg5nulH1AhvNY+477VwURjwBLgV+3\nq3ctLiAbSHOWE4H3gKuxLXmBnd7/1Vm+i7ad3pc7yxNp2+l9L7bDe48/a2A2rZ3wXY0HSAZSApb/\nDlzhge/Ue8BYZ/kBJx5XY3Ketwy4xQvfcS3eL705Tnit4LHzTpj22XPntjDtt2fPn2F8D2bjkfN0\nh/G5/QZ18+Zdhb2ydA/w4z7Y/vNAEdCIbTm7Ddsn5S1gF7Am4A9MgN85sRQAMwO2cyuw2ymBJ/aZ\nwKfOc35LuwuWOonpAuxPQ1uAfKdc5WZcwGTs9KxbnOfd79SPxB54djtf7ninPsG5v9t5fGTAtn7s\nvO4OAq7o7eln3e4PzNV4nNff7JStLc/zwHdqKrDB+fxWYk8ebseUjP1vPzWgztWYtHi/9PQ44aWC\nB887Ydpvz53bwrTfnj1/hvE9mI1HztMdFZ1ZTimllFJKRSQv9xFWSimllFKqz2girJRSSimlIpIm\nwkoppZRSKiJpIqyUUkoppSKSJsJKKaWUUioiaSKsPE1E/iwi89yOQymlVPf0mK36G02E1YAlln7H\nlVKqH9BjtnKDfuGUp4jIN0Vki4hsFpFnnOqLROTvIrK3paVBRHwi8paIbBKRAhGZ69SPEJEdIrIU\nO3j5cBH5qVP3vog8LyLfd9YdJSJ/E5GNIvKeiIxz6q8XkU+dGN514W1QSql+QY/Zqr/TCTWUZ4jI\nROBl4HxjTKmIZAC/ws5CNh8YB6wyxox25iJPMsZUi0gW8CEwBjgDO+3i+caYD0XkS8CT2Gk3Y4FN\nwBPGmF+IyFuARH7lAAAB1UlEQVTAd4wxu0TkHOD/GGMuEZEC4ApjzGERSTN2fnillFIB9JitBoIY\ntwNQKsAlwIvGmFIAY0y5iACsNMY0A9tEJMdZV4CHReQioBkYCrQ8dsAY86GzPAt4xRhzEjgpIn8B\n2zoBnA+86LwG2LnMAT4A/iwiy4GX+mZXlVKq39Njtur3NBFW/UF9wHLLEfAmIBuYYYxpFJH92LnK\nAWqD2GYUUGmMmdr+AWPMd5zWhq8BG0VkhjGmrMfRK6VUZNFjtuo3tI+w8pK1wPUikgng/MzWmVSg\n2DmgXoz9ea0jHwD/JCIJTovC1QDGmGpgn4hc77yWiMgUZ3mUMWa9MeZ+oAQYHoqdU0qpAUaP2arf\n0xZh5RnGmK0isgh4R0T8wCddrP4c8Benb9gGYHsn2/xYRFYBW4BjQAFQ5Tx8E/C4iPwE2xdtGbAZ\neFRExmBbMt5y6pRSSgXQY7YaCPRiOTXgiYjPGFMjIknAu8BCY8wmt+NSSin1RXrMVuGkLcIqEiwW\nkQnY/mhP6wFVKaU8TY/ZKmy0RVgppZRSSkUkvVhOKaWUUkpFJE2ElVJKKaVURNJEWCmllFJKRSRN\nhJVSSimlVETSRFgppZRSSkUkTYSVUkoppVRE+v+ZgCg0RpPWcAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RNt_2_JGIoUQ",
        "colab_type": "text"
      },
      "source": [
        "The distribution of charges for smokers and non-smokers above show that smokers will be charged more as compared to those who do not smoke. However, let's see how many of these people actually smoke."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZDaYT9VOJESz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "outputId": "b09cdec3-bfa3-49a5-ec74-3bf97ac4baec"
      },
      "source": [
        "sns.catplot(x=\"smoker\", kind=\"count\",hue ='sex', palette=\"pink\", data=data)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f6fbea03ef0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 402.375x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AegEgnh7JHC4",
        "colab_type": "text"
      },
      "source": [
        "The x axis shows \"0\" for non-smokers and \"1\" as smokers. The graph shows that there are more non-smokers than smokers. The graph also compared if the people are women or men, whereas women are coded as symbol \"1\" and men as \"0\". We can notice that there are more male smokers than women smokers."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZFydZNl3JJWV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 329
        },
        "outputId": "18f9e426-4ec1-41d0-ada6-b937c109a335"
      },
      "source": [
        "pl.figure(figsize=(12,5))\n",
        "pl.title(\"Box plot for charges of women\")\n",
        "sns.boxplot(y=\"smoker\", x=\"charges\", data =  data[(data.sex == 1)] , orient=\"h\", palette = 'colorblind')"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f6fbbacc3c8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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M/ie6MoP5eZ9LMpHks0n27n0rydv7GFyQ5PCh/bwsgw+4XJzkN4baD8/gzfOS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\nYII=\n",
            "text/plain": [
              "<Figure size 864x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kHiAqLIvJMeQ",
        "colab_type": "text"
      },
      "source": [
        "It is clear that smokers have higher range is charges as compared to the non-smokers."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GIfGB-vlJNEt",
        "colab_type": "text"
      },
      "source": [
        "Next, the second strongest correlated of feature towards charges is age. Let's investigate more on this in our dataset."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XgbKZVssJPj_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        },
        "outputId": "5c0c465c-8df8-4ba6-f71a-56f486fa539d"
      },
      "source": [
        "pl.figure(figsize=(12,5))\n",
        "pl.title(\"Distribution of age\")\n",
        "ax = sns.distplot(data[\"age\"], color = 'g')"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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1s1vKWB9hZtMD6xeaWVJg+clmttjMlgW+nlRim88C+1wSeDSuqA8lIiIiIlIZQssbYGY+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\nZBzHtDyGY1oec9D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RkVrMF+LjiqOvwGc+nv32WfIL872OJNWcyrNUuLWZa3nzhze5sveV\n1A2r63UcERGp5RrUacAlPS9h095NvLbyNa/jSDWn8iwV7vGFj+ML8XF1n6u9jiIiIgJA9ybdObnN\nyXy+4XNStqR4HUeqMZVnqVB7c/fy/HfPc06Xc0iol+B1HBERkWIjOo6gdVxrpnw/hR3ZO7yOI9WU\nyrNUqBe+e4F9efu4rp9uiiIiIlWLL8TH2N5jCbEQJi6eqPnP8puoPEuFKSwq5L8L/8uAlgPom9DX\n6zgiIiK/UHL+85ur3/Q6jlRDKs9SYd7+8W3W7V7HDf1v8DqKiIjIIfVo0oOBrQby0dqPWLVzlddx\npJpReZYKM37BeFrFtuKsjmd5HUVERORXnd35bJpGN2XSkklk52V7HUeqEZVnqRDfbv2WeRvmcW3f\nawkN0Y0rRUSkagv3hXNZr8vYl7uPqcum4pzzOpJUEyrPUiEeXfAoUWFRXHb0ZV5HERERCUpibCJn\nHnUm3279lgVpC7yOI9WEyrP8blv3bWXa8mlc2utS4iLjvI4jIiIStFPankL7Bu15dfmrpGenex1H\nqgGVZ/ndJiyaQEFRAdf2vdbrKCIiIoclxEK4tNelhFgILy55kcKiQq8jSRWn8iy/y4H8Azy9+GmG\ndRhG+4btvY4jIiJy2BrUacD53c5nTeYa3k993+s4UsUFVZ7NbKiZrTazVDO7pYz1EWY2PbB+oZkl\nBZY3NLNPzSzLzJ4otU1vM1sW2Oa/ZmYV8YHkyHp52cvs3L9Tl6cTEZFqrW9CX/o278s7P73Dusx1\nXseRKqzc8mxmPuBJ4FSgM3CemXUuNewyINM51w4YD9wfWJ4D3A78vYxdPwVcAbQPPIb+lg8g3ily\nRYxfMJ7uTbozKGmQ13FERER+l/O6nUdcZBwvfPcCOQU5XseRKiqYI899gVTn3FrnXB4wDRheasxw\n4KXA85nAYDMz51y2c+5L/CW6mJk1A+o55xY4/7VhJgO6OHA1M+enOaxMX8lNA25CPzgQEZHqrm5Y\nXcb0HEP6/nReW/Ga13GkigqmPCcAm0q8TgssK3OMc64A2AM0LGefaeXsU6q4B+Y/QMt6LTm3y7le\nRxEREakQHRp2YEjbIXy56UuWbFvidRypgqr8CYNmNtbMUswsJT1dl5CpKhakLeCLjV/wt2P+Rpgv\nzOs4IiIiFeaMo84gMTaRyUsns3XfVq/jSBUTTHneDLQs8bpFYFmZY8wsFIgFdpWzzxbl7BMA59xE\n51yycy45Pj4+iLhyJDz41YPUj6zP5Udf7nUUERGRChUaEsplvS4jrzCPMW+N0d0H5SDBlOdFQHsz\na21m4cAoYHapMbOB0YHnZwOfuF/5k+ac2wrsNbP+gatsXAy8ddjpxRM/7vqRWatm8ZfkvxAdHu11\nHBERkQrXNLopZ3c+m7lr5vJUylNex5EqJLS8Ac65AjO7BpgL+IAXnHMrzOxuIMU5Nxt4HphiZqlA\nBv6CDYCZrQfqAeFmdhZwinNuJXAVMAmoA7wXeEg18PBXDxPuC+fafropioiI1FwDWw0k40AGf//g\n7/yhzR/o0LCD15GkCii3PAM45+YAc0otG1fieQ4w8hDbJh1ieQrQNdigUjVsy9rGS0tfYnSP0TSN\nbup1HBERkUpjZrww/AW6TujKRbMuYv6l8wkNCao6SQ1W5U8YlKrl8YWPk1eYx40DbvQ6ioiISKVr\nHtOcZ4Y9wzebv+HfX/zb6zhSBag8S9Cy8rKYkDKBEZ1G6EdXIiJSa4zsMpILul3A3Z/fzaLNi7yO\nIx5TeZagPbv4WXbn7OYfA/7hdRQREZEj6onTnqBZTDMunHUh+/P3ex1HPKTyLEE5kH+AB756gEFJ\ng+jXop/XcURERI6ouMg4XjrrJX7c9SM3f3iz13HEQyrPEpTnvn2ObVnbuGPgHV5HERER8cRJrU/i\nhv438MSiJ/hgzQdexxGPqDxLuXIKcrhv/n0cn3g8A1sN9DqOiIiIZ/49+N90ju/MmLfGkHEgw+s4\n4gGVZynXC9+9wJZ9W7hj4B3472kjIiJSO0WGRjJ1xFTSs9P5y7t/0d0HayGVZ/lVuQW5/OfL/zCg\n5QBOan2S13FEREQ816tZL+4adBczVszg1eWveh1HjjCVZ/lVk5ZMIm1vmo46i4iIlPCPY//BgJYD\nuHrO1Wzas8nrOHIEqTzLIeUV5vHvL/9N/xb9ObnNyV7HERERqTJ8IT4mnzWZ/MJ8xrw1hiJX5HUk\nOUJUnuWQJi+dzMY9Gxl3wjgddRYRESmlbYO2PDr0UT5e9zGPLXjM6zhyhKg8S5nyC/P51xf/ok/z\nPgxtN9TrOCIiIlXSZb0u46yOZ3HzRzfz3dbvvI4jR4DKs5TpxSUvsn73esYN1FFnERGRQzEznjvj\nOeKj4jnv9fPIzsv2OpJUMpVn+YXsvGzu+OwOBrQcwOntT/c6joiISJXWsG5Dpo6Yyo+7fuT696/3\nOo5UMpVn+YVHvn6EbVnbePDkB3XUWUREJAgntj6RW467hee+e46ZK2d6HUcqkcqzHGRH9g4e+OoB\nRnQcwYCWA7yOIyIiUm3cNegu+ib05Yq3r2Djno1ex5FKovIsB7n787s5kH+A/wz+j9dRREREqpUw\nXxiv/PEVCooKuPCNCykoKvA6klQClWcp9tOun3hm8TOM7T2Woxod5XUcERGRaqdtg7ZMOG0CX2z8\ngjs/u9PrOFIJVJ6l2P998n9E+CK4Y+AdXkcRERGpti7qcRGX9ryUf33xL9776T2v40gFU3kWABak\nLWDmypncNOAmmkQ38TqOiIhItfbEaU/QvUl3Lpp1kW7fXcOoPAvOOf7x4T9oEtWEGwfc6HUcERGR\naq9OWB1eG/kaeYV5nDvzXPIL872OJBVE5VmYvmK6f27WoDuJDo/2Oo6IiEiN0KFhB5478zm+Tvua\nWz66xes4UkFUnmu53Tm7uWHuDSQ3T+aKo6/wOo6IiEiNck6Xc7imzzU8suARZq2a5XUcqQBBlWcz\nG2pmq80s1cx+8a2TmUWY2fTA+oVmllRi3a2B5avNbEiJ5evNbJmZLTGzlIr4MHL4bvvkNnZk7+Dp\n05/GF+LzOo6IiEiN89ApD9GneR8ueesSftj5g9dx5HcqtzybmQ94EjgV6AycZ2adSw27DMh0zrUD\nxgP3B7btDIwCugBDgQmB/f3sROdcT+dc8u/+JHLYFm1exIRFE7imzzX0bt7b6zgiIiI1UkRoBDPP\nmUlkaCTDpw0n80Cm15HkdwjmyHNfINU5t9Y5lwdMA4aXGjMceCnwfCYw2Pz3dR4OTHPO5Trn1gGp\ngf2JxwqKCrjynStpGt2Ue066x+s4IiIiNVpibCKvn/M66zLXcd7r51FYVOh1JPmNginPCUDJa6yk\nBZaVOcY5VwDsARqWs60DPjCzxWY29vCjy+8xYdEEvtv2HY8NfYx6EfW8jiMiIlLjHZd4HBNOn8Dc\nNXO5+aObvY4jv1Goh+99nHNus5k1Bj40sx+cc/NKDwoU67EAiYmJRzpjjbR572Zu++Q2hrYbytmd\nz/Y6joiISK1x+dGXs3TbUh7++mG6N+nOxT0u9jqSHKZgjjxvBlqWeN0isKzMMWYWCsQCu35tW+fc\nz193ALM4xHQO59xE51yycy45Pj4+iLjya5xzXPf+deQX5fPkaU/in10jIiIiR8ojQx7hpNYnccXb\nV7AgbYHXceQwBVOeFwHtzay1mYXjPwFwdqkxs4HRgednA58451xg+ajA1ThaA+2Bb8wsysxiAMws\nCjgFWP77P46UZ8r3U3h91evcMfAO2tRv43UcERGRWifMF8aMs2fQol4Lznz1TFIzUr2OJIeh3PIc\nmMN8DTAXWAXMcM6tMLO7zezMwLDngYZmlgr8DbglsO0KYAawEngfuNo5Vwg0Ab40s6XAN8C7zrn3\nK/ajSWmpGalcPedqBrYayE0DbvI6joiISK3VsG5D5pw/hyJXxNCpQ9metd3rSBIk8x8grh6Sk5Nd\nSoouCf1b5Bfmc+wLx5KakcrSPy+lZWzL8jeqIiYunuh1BBERqaXG9q7caxosTFvISZNPomOjjnw2\n+jNiImIq9f0kOGa2+FCXUtYdBmuJOz67g0VbFvHsGc9Wq+IsIiJSk/Vr0Y8ZZ89g6bal/GnGn8gr\nzPM6kpRD5bkW+HTdp9z35X1c3uty/tT5T17HERERkRJO73A6z57xLB+u/ZBL37qUIlfkdST5FV5e\nqk6OgIwDGVw06yLaN2zPo0Mf9TqOiIiIlGFMrzFszdrKPz/5J3GRcTx+6uO6IlYVpfJcgxUWFXLx\nrIvZkb2DBectICo8yutIIiIicgi3HncrGQcyePjrh3HO8fhpjxNimiRQ1ag812A3fnAj7/70LhNO\nm8DRzY72Oo6IiIj8CjPjwZMfJMRCePCrByl0hUw4fYIKdBWj8lxDPfHNEzy28DFu6H8Df+nzF6/j\niIiISBDMjPv/cD8+83Hf/PsockU8PexpFegqROW5Bnr3x3e57v3rOPOoM3nw5Ae9jiMiIiKHwcz4\n9+B/4wvx8a8v/kWRK2LiGRNVoKsIlecaZum2pYx6fRQ9m/bklT++gi/E53UkEREROUxmxj0n3kOI\nhXDPvHvIzMlkyogp1A2r63W0Wk/fwtQgm/duZtirw4iLjOPt897WCYIiIiLVmJlx94l3M37IeGat\nmsWJL52oOxFWASrPNcSG3RsYOGkgu3N2885579A8prnXkURERKQCXN//et449w2WbV9G/+f7szJ9\npdeRajWV5xrgp10/cfyLx7Nz/04+vOhDejTt4XUkERERqUBndTyLeWPmcSD/AAOeH8An6z7xOlKt\npfJczS3fsZwTJp3AgYIDfDr6U/q36O91JBEREakEyc2TWXj5QlrUa8GQqUN4YP4DuhuhB1Seq7HF\nWxYzaNIgDOPzSz6nV7NeXkcSERGRStQqrhXzL53PWR3P4uaPbubUl0/VPOgjTOW5mno/9X1OmnwS\n0eHRfDHmCzrHd/Y6koiIiBwBsZGxzDh7Bs8Me4Z5G+bR4+kefLjmQ69j1Roqz9VMYVEht31yG6e+\nfCpJcUl8MeYL2jZo63UsEREROYLMjLG9x7LoikU0rNuQU6aewk0f3MT+/P1eR6vxVJ6rkW1Z2zh5\nysn864t/cWnPS1lw2QJaxrb0OpaIiIh4pGvjriy6YhFjjx7LQ18/RJcJXXjnx3e8jlWjqTxXE/M2\nzKPXM71YkLaAF4e/yPPDn6dOWB2vY4mIiIjH6obV5ZkznuGz0Z9RJ7QOZ7x6BiOmj2Djno1eR6uR\nVJ6ruF37d/Hnd/7MoEmDqBdRj4WXL+SSnpd4HUtERESqmIFJA1ny5yXcN/g+PljzAZ2e7MQ9n9/D\n3ty9XkerUVSeq6jCokKeWvQU7R9vz3PfPsf1/a8n5YoUujXp5nU0ERERqaLCfeHcfNzNrLxqJUPa\nDmHcZ+NIejSJe+fdy56cPV7HqxFUnqsY5xyfr/+c5GeTuWrOVfRs2pOlf17KI0MeISYixut4IiIi\nUg20imvFG+e+QcoVKRzf6nhu//R2kh5L4p7P7yHjQIbX8ao1lecqoqCogNdWvMYxzx/DoJcGsXP/\nTqafPZ2PL/6YLo27eB1PREREqqHezXvz1qi3SLkihRNancC4z8bR/OHmXPjGhczbMA/nnNcRq51Q\nrwPUdntz9zJpySTGLxjP+t3raVu/LU+c+gRjeo2hblhdr+OJiIhIDfBzif5++/dMXDyRqd9P5eVl\nL3NUw6O4/OjLOafLOSTGJnods1qw6vQdR3JysktJSfE6xu+2L3cfb//4NjNWzOD91PfJLczl2JbH\ncuP/t3fvMVaUZxzHv7/dZRfLLiyXRZDlfl9EFzEICtZqbTU1YFOiNLQhhQSaaNVE0tT+U2tSo3/0\nYmLbhKqtbYpWoCDxD5CKVixREG9c1gsgugvCgtxBF4Gnf8wsrlTkdDl7zu7y+2wmZ9535kyefXIy\nec6cd+adcDeTh0+msKAw3yG2KvPWzct3CGZmdp6aPXZ2vkNoEUc/O8qCjQuY99o8VteuBqC6VzVT\nhk9hyvApVPeqRlKeo8wfSesi4vIv3ebiueWdjJPU7K7hxQ9eZPmW5acK5ovKLmLqyKlMv2Q64/qM\ny3eYrZaLZzMzy5f2Wjw39d7H7/H0O0+z5O0lrK5dTRBUdq7k6v5XM7HvRCb1n0RVRRUFOn9G+35V\n8ZzRsA1JNwAPAYXAIxHxwGnbS4C/AmOBj4FbI2Jbuu0eYBZwArgjIpZncsy2KiLYcWgHG3dv5K1d\nb/HShy+x6sNVpwbnV3auZM7YOdwy6hYm9J1wXn0QzczMrPUZ2n0oc6+cy9wr51J/pJ5n3n2GZZuX\nsfL9lcxfPx+A8o7lXNHnCkb3HM3FPS9m9IWjGdlj5Hk558RZi2dJhcDvgeuBOmCtpKURsanJbrOA\nfRExRNI04EHgVklVwDRgFHAR8C9Jw9L3nO2YrdKJkyfY/+l+dh7eSd3BOmoP1iavB2qp2VPDpt2b\nONDw+aNghnQbws3Db2ZS/0lM6jeJQV0Hndc/g5iZmVnr1bNTT2aOmcnMMTOJCLbu23rqQuC6j9bx\nwpoXaDjRAECBCujXpR8DygckS5cB9C/vT+/S3lR0qqBnp55UfK2CkqKSPP9X2ZXJledxwOaI2Aog\n6UlgCtC00J0C3JuuLwQeVlIhTgGejIgG4H1Jm9PjkcExW4X7V93PoppF7PtkH3s/2fuFwriREL1K\nezGs+zCmj57OqJ6jqKqoYlTFKCo6VeQhajMzM7NzI4nB3QYzuNtgZlTPAJKng23eu5kN9RtYv2s9\nW/ZtYdv+bazYsoIdh3YQ/O9w4LLiMjqXdKaspIyy4jLKSsooLS6luLCY4sJiOhR0oLiwmEIVcjJO\nEgQRQRBM7Dex1U0Ol0nx3AeobdKuA6440z4RcVzSAaB72v/yae/tk66f7ZitQklhCb1Ke1FVUUXX\njl2T5YKu9CrtRWXnSvp27kvvst4UFxbnO1QzMzOzFlVUUMSIHiMY0WMEU6umfmFbw/EGag/Wsuvw\nLnYf3c3uI7upP1LPnqN7ONhwkEPHDiVLwyH2frKXYyeOnVo+O/EZx08ep0AFSEKIAhVQ3rE8T//p\nmbX6R9VJmg00jtY/LOmdfMbTQnoAe/IdxHnAec4d5zo3nOfcca5zp1Xleg5z8h1CS2lVeT6TX6d/\nedD/TBsyKZ63A32btCvTvi/bp05SEdCF5MbBr3rv2Y4JQETMA9r14xYkvXqmOzote5zn3HGuc8N5\nzh3nOnec69xwnpsvk0c9rAWGShooqZjkBsClp+2zFJiRrk8FVkbyDLylwDRJJZIGAkOBNRke08zM\nzMysVTnrled0DPPtwHKSx8o9FhEbJd0HvBoRS4FHgb+lNwTuJSmGSfd7iuRGwOPAbRFxAuDLjpn9\nf8/MzMzMLHva1CQpp9voQAAABVFJREFU7ZWk2enwFGtBznPuONe54TznjnOdO851bjjPzefi2czM\nzMwsQ57ezszMzMwsQy6ec0jSY5LqJW1o0tdN0gpJ76WvXfMZY3shqa+k5yVtkrRR0p1pv/OdRZI6\nSloj6c00z79M+wdKekXSZkn/SG8MtiyQVCjpdUnPpG3nugVI2iZpvaQ3JL2a9vn8kWWSyiUtlPS2\npBpJE5zn7JM0PP0sNy4HJd3lXDePi+fc+gtww2l9PwOei4ihwHNp287dceDuiKgCxgO3pdPFO9/Z\n1QBcGxGXAtXADZLGAw8Cv42IIcA+YFYeY2xv7gRqmrSd65bzjYiobvI4L58/su8hYFlEjAAuJfls\nO89ZFhHvpJ/lamAscBRYjHPdLC6ecygiXiR5GklTU4DH0/XHgZtzGlQ7FREfRcRr6fohkhNyH5zv\nrIrE4bTZIV0CuBZYmPY7z1kiqRL4DvBI2hbOdS75/JFFkroAV5M8sYuIOBYR+3GeW9p1wJaI+ADn\nullcPOffhRHxUbq+E7gwn8G0R5IGAGOAV3C+sy4dRvAGUA+sALYA+yPieLpLHckXFzt3vwN+CpxM\n291xrltKAM9KWpfOdAs+f2TbQGA38Od0KNIjkjrhPLe0acAT6bpz3QwunluRdGIZP/4kiySVAouA\nuyLiYNNtznd2RMSJ9KfASmAcMCLPIbVLkm4C6iNiXb5jOU9MjIjLgBtJhn1d3XSjzx9ZUQRcBvwx\nIsYARzht2IDznF3pPRGTgQWnb3OuM+fiOf92SeoNkL7W5zmedkNSB5LC+e8R8c+02/luIenPrc8D\nE4BySY2TMFUC2/MWWPtxFTBZ0jbgSZLhGg/hXLeIiNievtaTjA0dh88f2VYH1EXEK2l7IUkx7Ty3\nnBuB1yJiV9p2rpvBxXP+NZ3afAbwdB5jaTfSsaCPAjUR8Zsmm5zvLJJUIak8Xb8AuJ5kfPnzwNR0\nN+c5CyLinoiojIgBJD+7royI6TjXWSepk6SyxnXgW8AGfP7IqojYCdRKGp52XUcyI7Hz3HK+z+dD\nNsC5bhZPkpJDkp4ArgF6ALuAXwBLgKeAfsAHwC0RcfpNhfZ/kjQRWAWs5/PxoT8nGffsfGeJpEtI\nbjIpJPky/lRE3CdpEMnV0W7A68APIqIhf5G2L5KuAeZGxE3OdfalOV2cNouA+RHxK0nd8fkjqyRV\nk9wAWwxsBX5Eei7Bec6q9Ivgh8CgiDiQ9vkz3Qwuns3MzMzMMuRhG2ZmZmZmGXLxbGZmZmaWIRfP\nZmZmZmYZcvFsZmZmZpYhF89mZmZmZhly8WxmZmZmliEXz2ZmZmZmGXLxbGbWxklaImmdpI2SZqd9\nsyS9K2mNpD9Jejjtr5C0SNLadLkqv9GbmbUtniTFzKyNk9QtIvamU6SvBb4N/Ae4DDgErATejIjb\nJc0H/hARL0nqByyPiJF5C97MrI0pyncAZmZ2zu6Q9N10vS/wQ+DfjdPsSloADEu3fxOoktT43s6S\nSiPicC4DNjNrq1w8m5m1YZKuISmIJ0TEUUkvAG8DZ7qaXACMj4hPcxOhmVn74jHPZmZtWxdgX1o4\njwDGA52Ar0vqKqkI+F6T/Z8FftLYkFSd02jNzNo4F89mZm3bMqBIUg3wAPAysB24H1hDMvZ5G3Ag\n3f8O4HJJb0naBPw45xGbmbVhvmHQzKwdahzHnF55Xgw8FhGL8x2XmVlb5yvPZmbt072S3gA2AO8D\nS/Icj5lZu+Arz2ZmZmZmGfKVZzMzMzOzDLl4NjMzMzPLkItnMzMzM7MMuXg2MzMzM8uQi2czMzMz\nswy5eDYzMzMzy9B/ARU43MAszYcVAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tlLJJOC8JTgw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "outputId": "f3ac2047-9175-4ac1-eb51-af4807803c66"
      },
      "source": [
        "g = sns.jointplot(x=\"age\", y=\"charges\", data = data[(data.smoker == 0)],kind=\"kde\", color=\"m\")\n",
        "g.plot_joint(pl.scatter, c=\"w\", s=30, linewidth=1, marker=\"+\")\n",
        "g.ax_joint.collections[0].set_alpha(0)\n",
        "g.set_axis_labels(\"$X$\", \"$Y$\")\n",
        "ax.set_title('Distribution of charges and age for non-smokers')"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Distribution of charges and age for non-smokers')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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JiEgBCs8PAxDpU41OREQKUKgiFgEKOhERKUih+bEIGD0xmuc7yS4FnYhIkVKN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\nzArtfyCh9MwpeCKsAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x432 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xI5G2oi9JYA5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "outputId": "9a11abf8-ed41-45e0-b17a-9324bd7e71cb"
      },
      "source": [
        "g = sns.jointplot(x=\"age\", y=\"charges\", data = data[(data.smoker == 1)],kind=\"kde\", color=\"c\")\n",
        "g.plot_joint(pl.scatter, c=\"w\", s=30, linewidth=1, marker=\"+\")\n",
        "g.ax_joint.collections[0].set_alpha(0)\n",
        "g.set_axis_labels(\"$X$\", \"$Y$\")\n",
        "ax.set_title('Distribution of charges and age for smokers')"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Distribution of charges and age for smokers')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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GBeFN1i6ic0BEl4AzkQi7BgfZdfZs7Osz/f08PziIBkqV4rLKSl4ybRqvnD6dOikyEQSB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\nUjwMAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x432 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WtiHZhXgJalT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 584
        },
        "outputId": "ec75d855-9feb-434d-8954-e42707c1dba6"
      },
      "source": [
        "sns.lmplot(x=\"age\", y=\"charges\", hue=\"smoker\", data=data, palette = 'inferno_r', size = 7)\n",
        "ax.set_title('Smokers and non-smokers')"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/regression.py:574: UserWarning: The `size` parameter has been renamed to `height`; please update your code.\n",
            "  warnings.warn(msg, UserWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Smokers and non-smokers')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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p0uuV/CgVTzJ8asgKMOxAY2ZkuuB961sb6N2+np7tffTYf1abSgwH+9+Bh5VS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s6EdFV+P+3EOC7uwR1ET16PiMSwTjiL5ItfJXvRlzA1llPYGZiJ4fLs8w3DLN5WamRrJZwD25GT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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 548.5x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ik_Ea7FMJc-K",
        "colab_type": "text"
      },
      "source": [
        "It can be observed that for non-smokers, the cost of treatment increases with age. However, for smoking people, we do not observe such dependence. I think that it is not only in smoking but also in the peculiarities of the dataset. Such a strong effect of smoking on the cost of treatment would be more logical to judge having a set of data with a large number of records and signs."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QmvEspCZJdrA",
        "colab_type": "text"
      },
      "source": [
        "Next, let's observe about BMI, eventhough it has relatively weak correlation with charges."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R6HINbY9JgQZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "d06b64e4-b599-4981-f696-452e0c724925"
      },
      "source": [
        "pl.figure(figsize=(12,5))\n",
        "pl.title(\"Distribution of bmi\")\n",
        "ax = sns.distplot(data[\"bmi\"], color = 'm')"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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pyToRObBIf4TWX7QSWhoi7XVpXscReQ0zo+iyIgDdGEVE5qy4JlA65x4DHhuz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\nTrYAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_z7FvnZ4Jjjt",
        "colab_type": "text"
      },
      "source": [
        "It appears that the average US citizens who are the beneficiary of health insurance have BMI of 30, whereas the ideal BMI is 18.5 to 24.9 BMI of 30 indicates obesity. Now, let's see the distribution of charges in people with BMI above 30 and less than 30."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9pkUjpKvJnB1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 318
        },
        "outputId": "a5475711-db58-4d99-fa3d-c5c4d999f6ef"
      },
      "source": [
        "pl.figure(figsize=(12,5))\n",
        "pl.title(\"Distribution of charges for patients with BMI less than 30\")\n",
        "ax = sns.distplot(data[(data.bmi < 30)]['charges'], color = 'b')"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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iiLGZM9OOSEREpHYoyZVKrVgR08Vuv71KFeqyTTaJRHflSvjXv2JiDxERkWKn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\nESk6SnJFREREpOj8P0o/Fhnd8PujAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "C6Cnj34xJp-S",
        "colab_type": "text"
      },
      "source": [
        "People who have BMI above 30 are charged more with their health insurance as compared to those people with BMI less than 30. It appears that eventhough BMI does not have strong correlation with the charges, severe obesity can make people pay more for their medical bills. Well, obese people tend to be more susceptible towards illnesses."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UT3E_tRqJqvb",
        "colab_type": "text"
      },
      "source": [
        "Now, let's observe if we compare smoker, bmi and charges."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LNUcs_nxJtGg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "84c3cb1c-83c4-45a6-b43a-5a79aa7e575d"
      },
      "source": [
        "pl.figure(figsize=(10,6))\n",
        "ax = sns.scatterplot(x='bmi',y='charges',data=data,palette='magma',hue='smoker')\n",
        "ax.set_title('Scatter plot of charges and bmi')\n",
        "\n",
        "sns.lmplot(x=\"bmi\", y=\"charges\", hue=\"smoker\", data=data, palette = 'magma', size = 8)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/regression.py:574: UserWarning: The `size` parameter has been renamed to `height`; please update your code.\n",
            "  warnings.warn(msg, UserWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f6fbb34d828>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9eqct4GjU9UtLSCxfjqmuxjd6XyQvr8HAz1RVOcOrtRaKKJVpIrKoxnakKfqn\niFKq3TCxGKay0hlC8/t3GDCZZBJTXo6JRJBgAAln1T8HrCltiEbTgjcAe923aQsA2opdXk7yixXY\nmzbi3Xc/QudfiPF4iPz9gTrHJpZ8QnLtGgLH/xhP79711Iaz8KEtg9BgEN+48cTnzd3Whtw8JJy+\nStbq3IXQZb9xeuo8FpKV7SzEyM3F04RFB3Z5OSQSTnqV3FysvE74Dzxox+cVFxP59+NOsLhnH4Ln\nX4DVvQeiw62qHdMATinVLtiRCInFi4g8/ihEo1i99yR8+W+x8vPrPd4YQ3Ldt1T/6S5nVaLfT+gX\nl+AdPqLOKsymkEAQyclJWyjg2XsQ7GDIrt42xmIYd76XhMNNCi7t6iqizzxF/N15ACQWLST5xQqC\nZ5+LZ8AAksuXpR1vFfQiNudNqu+/l/A112Ll5TW5vS3NCgYJnHQS+P3OKtqCAoJnnFVvENncXi97\nc6GzknX1aqzu3Qn94hKs3nvucKjVVFZS/a+HSS79DIDk16uouvMOsv54A5LXcJoSpTJNAzilVPtQ\nVUXknw+BO63DXr+OyBP/cXpD6pmXZcrKiDz4gBO8AcRiVP/9AbJvu6NuctsmkJwcQr+5ktj77+Lf\n/wAArC759U6K3x67opz4W28Rfe1VMAb/pCn4jz6m8YFKJEr8/ffSihKLFsLpZ+A/6hiSyz4nuXo1\niOA79DBMRQWmuNjZm7CRSW7bgpWbR/DkUzDHTUV8vjo56lqCXVFO9d8fdJ4HYH//PVV330XWjbds\nN1ccOHMek58vTS8rKcZEopD5GFipBmkAp5Rqc6ayEruslOTatXj69sPKy8XesiUVvG2V/PpriMag\nvon1to39/ab0skikSdtI1Uc8Hqw998Q3el+q/nSnU5/fT+jXv8E7ZMgOe3RSzVu3jugLz6Xex15+\nEe/AgVgj96n/+EgEohEIBJ1ks4LT61dz6NayQMDKyyN02W8x8RgkbYhFSX7zDdK5MxIMgbfpvYWt\nSfz+Zg9tb1ciSXLVyrQiU16enkakISJY3Xtgb9q4rczna932KtUCNIBTSrUpE4sSe28e0SefSJUF\nzjwb35ixTsBSo/fIM3QoNNTz5fXi2XvQtvxhgHTuDC0xOb+igshDD24LBmMxIn//W6N6dLaKL6q7\nWCq+4GO89QRwdkkJ0WefIfHlCjx7DyL4k1OQ7CwCU39E9IXnU8f5jj4WgiHnjcci/tY8Yq++Askk\nngEDCV96GQSDWLm7WdeRZWH13hN7/bptZcFgo34WrLw8ghf9nKq77nQWW3g8BM/9GdLAil6l2gsN\n4JRSbcpUVhF9/rm0suizT6Uc+6wAACAASURBVOPbbz9Cl15O9Kkn8Qzoj3Tvjv/Qwxrc+sjKySH0\n819Q/fBDJL/4AqtPH2cbqZwWmKTvLo5Ia3d5eZOGJr1DhhKf82ZamWfosDrH2RUVVD/4N5JffgFA\nYvNmqjZtJPybK/BNOBrP8BEkly/HM3gwVs8CrJATwJniYmIvvbityV+vIvbxRwQmTcFUVe1WAYiV\nm0vo4l9QdfddmOJiZyXrL35ZZ7jWjkbANqlnuJVnzz5k33o7pqoSCYWRUKhRq3RNMompcH5OJNS0\nOY5KNZcGcEqptmXsusOckQgY8AweTOjSS4m98TqmtAxiMUwijnjrX5Rg5ecT+uWlqZWHLZbmw+er\n06Nj7blnvZvEN8QzaDDe8fuT+PgjALz7jcE7vJ6d/2KxVPC2lb1mDcRiWPldsbIH4h0wsM5pyXXr\n6pTZq1YSf28eJhLBP2kKVivMN2uvrJ4FzlZZUWfIu+aWYiYexy78gehLL0KkGv+UqVh9+qTmVorX\n6/SsNrJ3FcCuqiL56adEnn7Ced4TjsY/aXKHTEFiV1djioqIz/8Qq2dPvCNGtotFMGr7NIBTSrUt\nf8DpVVr2earIO2o0BPyYUnf/ykQCgPi8uWTfcjvStWudarbuPtAaG69bubmEL7uc6of/SXLVKjwD\nBxI6/4ImBYhWbi7Bs8+BU08DAwQC9bfVctJmpBZjgDP8t4O5dp7+/euWDR5C8ttvSXz8Eb6DD3W2\nnOpAjDEN5rDbEbGsBleNmrJSKv/4B4jHAUh89hnha/+ANbBuYNzotpYUU/3QtnQusddexerZE9/B\nh+z0PTTp+tEopqKC5Pp1WN32QPJysbJ27v+F5KqVVP/5T6n3mcx7qBpPAzilVJuysrMJXfhzYm++\nTnLFCjzDh+OfcDQSziL64oup4A2AWIz4B+8TmHZ8qsgkEpjiLURnz4JEAv/ESVj5XVt8+Mrq2o3Q\nJW7vnte7U4GilZUNO/ilKtlZBM89j+q/3ecs4hAheObZdXKl1TkvJ5fgBRcRfeK/mOoqvGPH4R0x\n0ll4AZjNm6FHjya3ORNMVRXJjRuJz5uL1as3vv0PaNEeoPiSJangbavY7Jl4+vx8p39uEsuW1S1b\n8BHeseOavGK5qYwxJFd/TdXdd6WG9X2TpxCcOq3JQ+d2eVmdKQ32um+doWgN4No1DeCUUm3Oyssj\ncPyJmImTkWAQ8Xqd3hd/PUOUtYYtTWkJFdf9LjUMG3/vXbJuugVPz4KWb2cr9O7VJl4fnhEjyb7r\nz9ibC7G6doNG5IyzwmF8+x+Ad9hwTEUFicULqbr3r84vdI8Hq6Dln0drMMaQWL6M6vv/N1UWf+dt\nwv8zvcWCuPqGNSUvr1n7onr22qtuWb8BzcpB2FimrIzIY/9Km5MZnzWTwFHHNH3uo6H+uZ2Z2v9X\nNZqmmVZKZYS4vVpb96YUEfxHHpW26lSysvG5udi2in80P30OXTJJ7PXZmdtwvgVYwSBWfj7ewUOw\n8vPrTLJviHi9WJ07I3l52MXFYNtYPXoSvurqHW723l6Y8nJnbloN9nffYUqKW+wansFDsLrX6I0M\nhwlMmtKsfVGtngV4Dz5k2/u+/fAdOaHRaWaaxRjskpI6ZaZWL2NjSE4OgWnT0sqs7j2QLl2a00LV\nBrQHTinVbkjnzmTffBvxjz8CjwffuPFOT0lN9fVMuWV2WSlmyxZnw/fOXXabOTxWbi6B039K4IQf\ngyUdL41IfXPGWnAemZWXR3j6tSTXrsFEIngHDa77c9XUOnNyCJ7+UzjxJEwyiQSDbffzFgriO+gQ\n4m/PSRVJtz2QRgb+NYkI3mEjCF/7B+LvvI1V0AvfgQfpIoYOQAM4pVS7IR4Pkp9PYPKUBo/xjRlH\n7OWXtqX5CAYJHHMspryMqjtux974HYCzFdeV/7Pb/CKyAkEItO7cq9Zg5eYS+PFJVN/zl21le/Zp\n1m4a9V4nLw9r1OiWrbMRcxxbgxUIEjjhRKzcXOKLFmL16UPwxyft9M+6hMN4Bw7E07+/7v/agYip\nlfl8Vzd27FizcGHdBJtKqY7B2DamtJT4J4sgnkj10sXmvEn0if+kHRs873z8hx3e5m20S0uIL1iA\nvWkT/sMOQ7p1S6WsMLEYpqICu/AHZ4uurKzdKmdbfeyqKszmzcQ+eB9Pr1549xm12wTezWESCWev\nXb+/wXyJaufY0QhUR5z5pBlODSMii4wxY2uXaw+cUqpDEctCOncmMOHotHL7uw11jk1uWN/i1zeV\nlU47GkjRYZeWUnX7bamtmeJz3iB02W+IF27G07MH0rUblTf8wcl9BwROOQ3fEUc2et5bSzKVldil\nJSRXrcTTtx/SJb9NFm7UZoXD0KcPoT592vzaHZl4vchuMk2gLdllpUSfe474wo+x9uhO6NzzsHr1\nbtacydagfaVKqV1CfT1t/oMPbbH67UiExJdfUnXfvVTddy+JL7/Arq6ue9zmwvR9NYHYKy8DNlV3\n30Vs1kz8xxyb+iz63DMQqVtPazPxOPGP5lN57XQi/3qEyut/T+z1WfXe01Z2RQXJNauJvvqyc/+1\ndqtQqqMzsSjRl14kPm8uVFVhr11D5e23pnbcaE80gFNKtSi7uhq7qIjkmtXYxcU7tTKuISYex9TM\nE1eD1aMnoV/9GmvPPlh79SV0+RVIt7oJgLdbf2Ul9pYiJwirvZXW5s1U3XEryS9WkPxiBVV33IYp\n2tzYmlOv4u++g3fEyG0fJZOYWMs9o8YylZVEnn06rSz22owGg0kTixF/dx6VN/6R6HPPUnX7rURf\nfN4ZwtvZNkSj2CXF2MXF2w0clWorpqqaxOLF6YWRCPaWllsV3VLaV3+gUqpDM5EIiY8+JPL4Y05S\nWp+P8BVX4Rk0uFnZ6U0shl1YSGzmDLAs/FOOc5L31si5JeEw3v3G4Nl7EAhYTdwT1S4vI/rM08Tf\nexeMwTN4CKFfXJKaixWbN9e5p1SjDLF35hI646y0eqyu3bB69MDetClV5j/6WGJvzUmdB9uehXTb\no9UTv9bPQDSaXpRMNpj/y1RVEX05Pd1H/O23CBz3o52aw2dXlBN/aw7RV1+BZBLfwYcQOPmUJn/f\n0tpo25iyMpLrv0WCIaw9uu82K5FVC/H5sHr2IFkrjU17/DnSAE4p1WJMdTWR//x7W6ATj1P9z4fI\nuu767aZtsMvKSH75BYnVX+MbMw6rZ4+0bYHsLUVUXn9dKuFo/MMPyb71dqRbt7R6RGSn5wTZGzYQ\nf3de6n3yyy+If/A+/omTEMtyEuzWUm9ZXh7ha37nLmLYiG/ceBKfLyW5aiUA3oMOxlRWIN264dmz\nD8HTf5qRCfviDzh7tc7/MFXmGToU/A1t4m7q7GaAMelBbRPY339P9IXnU+/j787DM2gw/kN2ftjb\nFG+h8obrUyuUrb79CP/mtx0vrYrKGCsri+BZ51J1283Oz5EIgRNObJcLjTSAU0q1nHg8fSsswBQV\nbfeXvF1RTuRfD5NY8olTxayZBM46G/9hR6R2aIi9+WZ6tvhEnNj77xI84cct1vTk6tV1y1Z+BROO\ngkAA39hxePr1xxRtJjp7FqaivE6S4a2svE4Ejj7Gvb8KPGVl+A48CM8+o/EOH4YEgmRd+wfw+1Kr\nU9uahMMETz+D+F59SXy6BM/gIfiPnNDwirtgCN/hRxB/a1vuMe8+oyDQUMC3fTX3wt0qseQTfOP3\n36ntrUw8TnTGjG3pZQB77RqSa9di7TNqp9qodk9W9+5k3XQLpqICCYUhGNQATim1iwsEkG7dMIWF\nqSLvqFHb/4UciaaCt61iL76Ab8xYJK+T06sWqjvEKMGWXbXpHTGC6DNPpZeNHYcEAtiFhVQ9cD/2\nmtXOXLuLLoauXRuVXsDKzsYaNx7vmLFpObaas3fr1nmFzd22ycrNxX/Msc4CkEBgu7sIWEEn95hn\nwAASixbhGToU3/gDdnrVqmfw0Lplw0fW2TqtsUwyidlSVLe8njKltkcsC8nrBHmdMt2U7dJFDEqp\nFmPl5RG+6mo8I0YiuXl4DzqY4Dk/28Ffr3V752pvi+U/YgLUqENychrs/dpZVn5Xgmefi2Rlg8+H\nb9JkvCP3wS4vp/pBJ3gDsDdtpOqePyMNLKZoSEskSLWrq0lu3Ejk/x4j8ugjJDesx9Sex9ZE4vEg\n4XAjt4ASJDsHz+AhGKROb2tTWAUF+I6dCB4PiOAdOw7fmDE7PVfSCgbxH5WeWgavF++IfXa6jUq1\nZ5rIVynV4kxVFSYWg2BwhwlG7fJyqu//X5JffpEqC5x8Cv5jJ6XyLqWS9y75BPF48O6zD5Kb1+JZ\n400igamsAAMSCjm9b8XFVPz2sjrHZv3xRiS/a5vkTTPRKHbRZognqLz5Rki4c9E8HrJuugVPz53f\nuN4kk05OukBgu3muTCJBbNZMJ+2JS/K7kvX763d6Dp9dXe2sejVAIIDVQG69RtdXWUlyxXJis2dC\nMETw5FOweha0yQbzSrUWTeSrlGozEg43es6IlZND6Je/IrF4EcmVX+E74CCsfn3TgolU8t4jJ7RS\ni93reL3O0ElNHgurZ0Fqiy4AQmEnfYbZDG0QwNnFW4g+/xxW9+7bgjeAZJLYnDcJ/vTMnQpm7bIy\n4u/OI7H0U2cBwVHHNBiMmYoKYjX23gQwRZsx5WWwkwGcFQpBCyYwtrKysMaOwzNkCGJ52uW8JaVa\nigZwSqk2YeJxpxdt4QIn5cc+o7A6OcGSlZuL/4gjMYcd3u72YrRy8whd/Auq/nI3pqQEwmFC55xH\n7I3X8e6zD56+fXeq3q2jH7WHDO14HCorIZkArxfJySU2Zw4mGq133pwEQzu18bupqiLyxH9Sq1CT\nX35JcuVKQpf8Ciu7nrl9loVkZWG2bEkvb8ZcvtZSb/s7IGPb7e7/B9V+aACnlGoTdlERlX+4Fk/f\nfvgnTcYu/AHsJNK5SyqIac4vKxONgkizFgc0RAp6Ef7tlZjKKrCTxN58g8QniwmcdHLT25lIYIqL\nib31Jsa2CRx1DNLZ2bg9WVoCJaVUP/QgpvAHJD+f8KWXYfXuTfztOQRP+DGxt+ZgysqcysJh/EdO\n2Kl5YyYWJfHR/LSy5BcrIJl0khgbg+TkpOq2cnMJnn4mVX+6I5Urzjt2HBJu3rCnqsuuqMBeu4b4\n/A/xDNwb735j2mUeMpVZGsAppVqdiceJvfoynv79CUydRvWjj2CKirC6dyf068vxFPTa6brtSASz\naSPRGa+C309g6jSsrl1bdN6T5fVi53UiOnsWiQ8/gECQ4NnnpnoQm8KUlFBx3XSIxQAnGW7Wzbch\nlmDWrCH63LOYwh/A68NT0IvoG68TPPEkYsEQ1f9+nNCvL3dyyvkD+EaPRnY6x5lAMATV23ZS8E+a\nQnLdOqLPPwuJBIGp0/AOH5Ha99XTvz/Zt99F4qsvsXr0wNpjj4zsnborM4kE8XffIfq0syI6/v57\neOZ/SOiSSzO+qbpqXzSAU0q1PmMw8Tj+ycdR/fA/nKFInGSu1f97L+Hpv9vpZKvmhx+ovPGPqVxz\niQUfk33rHUjXpm2jtSNWbi7BM86Cn5wMCJKVhfh82GVl2OvXk9ywHu+IkUinTtvdmD7+/rup4M0p\niBN/ew5W/wFYObnY32/CM2gwwVNPI/7Zp6ndEcI330py6WfYGzfhO+gQJDu7WbtbSFYWwVNOIfLY\no877nBy848ZTdfMNqWdZ/cD9hKdfi3fQYOcYN02Mv1vdBMaqZZjKCmIzZqSVJb/8wlnsoQGcqkED\nOKVUqxO/n8CU4zDVkVTwtpW9aSMkkg2cuX0mmSD2+qz0RMHxOPEFHxOYPKU5Ta5X7Un3tZMQR0UI\n/fpyZNTohoMrq550HZYH8fkw5WVYvXoTPPU0Ku++C9x9RmNvvkH2TbfiP/SwFrsX8fnwjd8fz+Ah\nJFetwjNkaGobsZric9/GM2BgI9OMqBbhqWcqQTOCdbVr0tmRSqk2Id17IPldkFrDjlaPHk4usEYw\n0Sh2WWkqkS1IvatApZnpKBrLVFWlJyE2huhTT2ybo1YP38EHQ83dF4JB/EdOwLNXX6Jvv0Xo5xcT\nX7IkFbwBEInUWQHaEiSchadnAf5DD8PTrRtWj551jrEKCkAn0rcZycomcPyJaWWefUY5w91K1aA9\ncEqpNmEFgxifj9CvL6f6vnsxW7Yg3fYg9KvLGpVHzC4uJvri8yS/XoVn+AgCU6Zi5eUROPpYZw9T\nN+DxjN4X7/AR2EVFzirO3Ny03jC7vBxTXQ3irOBs1ryiehLZmkgUEgniCz7GLvwB735jnWFVNx+e\n5HUi++ZbiX/4Adg2voMOQjp1BhHCF/2cZNGWegMmk0hgjGnWsOmOeIcNw9prL+xvvnHausce+A45\nrM41TSzmpFHBQCiMtZPbabUHdnU1uCt820PaEfF68e5/AOG9+hJf8DHegQPxDBqscw1VHZrIVynV\nqoxtO7nCbAN+PxIKOe/jCfD56gRY9bHLyqj6693Ya9akyryjRxO64OcQDGLKykgs+xzp3BkrO4eq\n++/FFBY6iyR+dRlWr16ICHZZGdV/uy+VNNgzdCihiy/Z6RV+dmkpVXfclpYjLnDyqdjV1cRffdkp\nECF8ze9S88gaVe/mzVRce822uXJeH1m33Ipnj+471c6msMvKMMXFzgrhLvl1gmu7ooL43LeJvvoy\nJJP4jphAYNrxHXKCvV1cTOTJ/5JcsRxPv/4Ezzobq6vO71PtS0OJfDWAU0q1GhOLkVy1kup/PIQp\nKcYzfDihCy7C6tS5SfXYmwupuOqK9EIRsu/+K1bnbXXZpSVU3nhD2v6XVvfuhKdfh5WXR+zdeUQe\n+WdaNcGLLsZ/4EFNv7mt1ywpIfbWm9jffovvoEOw+vWj8pqrUqk2ADx7DyL068sb3YuyNdVIdM4b\nkLTxH30MVpcu7WJHgcSqlVTdclNaWejiS/Dtv3+GWrRz7IoKqv/2vyRXrEiVWT0LCF8zfacX1CjV\nGnQnBqVUmzOVlVT95c+p3QOSy5YReepJguect8MtttJ4vM4m5/FtuxBIdnbdid3xeJ3Ny+3vv08N\ndSZXrapTdfLrVdCMAM7q1InA8Sdi4nGsYJDEyq/SgjdwAlmMXe/5qR5KQLJznL1JvV6kWzeCp5zm\nlLfRHDSTTGJKionNfdtZNTzhKKzO6YFjYulndc6LL16Id8yY7W7F1e7E42nBG+D0pEZjDZygVPui\nM1OVUq3GlJSkb/0EJJcvd/bebAIJhwn85JQaBULwzHOQ2sN2Ph/SpUv6ud26pRZJ+A48sE7dvv0P\n2OH17YoKkmvXEJ09i+TaNdgVFenX8HhSAam1R3ekS37a54HjpmI8XuwtW7CLi7Hd+zeVlcTnf0jl\nzTdSedMNxN+bh125rW6xrDbNxG9KS6n4/bXEXn2F+OxZVF47HbvWzgv1DQV7hw7rWMEbOEmfa/cE\nBwLg62D3oXZbrf6TKiIeYCGwwRgzVUT6AU8C+cAi4CxjTExEAsDjwBigCDjVGLPWrWM6cD6QBH5t\njJntlk8C7gE8wD+NMbe39v0opRpP8nKdXjKv15n7VlaGp2/fJu+WIIEA/kMOxTt6X+xNG53Ev9nZ\ndVJbSE4u4Usvp+rev2CKi5H8fEIX/5LonDfx9u2LNWAggTPOIvbKyyAQmHaCs8pyO+xohNicN4i9\n+AIAUcB//In4J0/GCtTTi+j1knXtdcTmvo29aZPTi9WjB5G/P0Dis0/B68U/ZSr+Yydivv+eyD/+\nnjo18ui/CPfoiTV4SJOeD9RcWAASDiH+pi8siC/4CKqrtxUkEsRen03wjG17rVp9+uA7/Aji894B\nY/Duux/e/cY0+VqZJrm5hC68aFsPsWUROuc83VlCdRht8afGZcAKYOss4TuAvxhjnhSRB3ECswfc\n/xYbYwaKyGnucaeKyDDgNGA4UAC8KSKD3LruB44B1gMLRORlY8zyNrgnpVRjhLMIX3c9JJx9UK2u\nXaFTJ4zXiykuxt5c6Gx8n5u3w0nwEg7jCYfx7LFHw8dYFlafPmRdfwNEY9hbioj+9z8kv15FHPAf\n9yP8U3+Eb9w4ME7y2h3mN6usIvbqq2lFsRmv4j/sMKgRwNnV1SRXf030uWcACJ52BtbEyUgwSGzW\nTCd4AycoevlF/AcfQuyjD+tcLv7+e3gGDW5wYYddUYH93XcklizGM2gwnv4DwLKIv/M20VdfAdvG\nf8xE/BMnNX1hQX3XrFVk5eQSPOU0AtNOcHLGBQLteoWkqarC2HadNopl4Rm4N9l3/glTWork5kI4\n3CpbsaW1Jx7HVFRgF2125oKGw1jtYPWr6nhaNYATkd7AccAtwG/F+RdpAvBT95DHgD/iBHDHu68B\nngXuc48/HnjSGBMF1ojIKmC8e9wqY8xq91pPusdqAKdUe5FMEp//IfE3ZjvvAwGyfvd7TGUVVXfe\nhikvB5w8V6HzL3Q2Sy8tJb5oIXg8+PbdD8nLa9IwolgWktcJe/Nmqu64Le2z2BuznQUBTdkCy9jO\nxvJp95VwVtXWPKy4mOq770olwq267WbC1/wOq08fEivq/rOU+PYbPHv1I16r3OrXv8HgzcTjxOfN\nJfrM007BzNfwHTsJ3377EX32mW33OeMVPAMGYO27X+PvE/CNHU/05ZegstIt8OE/dlKd5y/hcLtI\nubE9JhbD3vgdkWefgWgU/3FT8e49KK3d4vc7AVvnpi2qaY7k2jVU3XVHaj5n4JTT8B1x5HZ371Cq\nPq09ueKvwP8AW2fv5gMlxpit/xquB7ZugtgLWAfgfl7qHp8qr3VOQ+V1iMhFIrJQRBYWFhY2956U\nUo1VVbUteAOIRkmsWEb0tRmp4A0g+dmn2IU/YMpKqbhuOtH//pvo/z1G5fXXYUpLd+7aVj1B0M7s\nJmB56gwRevcbU6e3KvHxR3V2MYjNfRt8Prwj96nblD264x0xAs+gQakyq/8AfNsZjjSVlURfeTm9\nbEtRejLhre1Z8DHGrrtwwsSi2CUl2CUlmFg07TPp1InsG28hcNLJ+KedQPatt6et8u1ITGkplTfd\nQPLzpSRXfkX1X/9Mct23GW2TXVbqrIKusRgn+uzT6cPWSjVSq/XAichU4AdjzCIROaK1rtMYxpiH\ngIfASSOSybYotTuwKyogkcBs7cmpSSzM5rp/SNmbN5P8+uu0X2amvJz4x/MJTJzc9EYEgngPPMjZ\nfH5r0Y+Ob/IuDRIOEzj+RDwD98bqmu/sVuAPOKtiax7Xs+4uBp6CAsTy4DvwIJKrvyax4GPw+Qic\neBKS3wUrK5vQry7DVFWCMUg4a8c56WoFZfb3m/AdeBDMmpl+7aFD6/Sc2eXlxF6fRWz2LBDBP3ES\n/mMmpoZaxbKQLl0ITP1RYx9PuxX/ZLGzj2wNsTffwNOvf6sPkzbIGOzNm9PLbBsT15Wvqulacwj1\nYGCaiEwBgjhz4O4BOomI1+1l6w1scI/fAOwJrBcRL5CHs5hha/lWNc9pqFwplQEmmXSGrf7vcezN\nhYQvvwLJysbUWFlpLAvvAQeSXPnVthO9XrwD9yY6e1bdSpu4YnUrEfBPONrZleHbb/AMGeps49XE\nnQwkEEA6dcI7dhyRxx8lufQz8HoJTP0RviMmpBIRe4cOxdqrL/Y3a53zuu2B79DDnaAoN5fQOedh\nTvupswNEOCsVRFg5OY3epFzCIfzHTCQ245VUmZXfFU//AXgPOIjEfCdY9Y7eF++ofeucb69dQ+zV\nbefGXnkZ76AhWCNGNOmZdASWuxpZsrLxHXkknr79nKA7k9uC+QN4x44jMX/b3EfJz0d0myy1E1ot\ngDPGTAemA7g9cFcaY84QkWeAn+CsRD0HeMk95WX3/Yfu528ZY4yIvAz8V0T+jLOIYW/gY5yptXu7\nq1o34Cx02Dq3TimVAaa8nMpbbkoFXZF/P074yquIPPcs9vff4xs/Hu9ee2G2bCHwk5OJf/A+kp1D\n8PSfIrm5+CccRfytN7f1nPh8+A4+ZOfaUh2h6tabsAoKsPboTnzRIohEyLr51jr7se6IhMPE577t\nBG8AiQTRF1/AM2gIyaVL8Y0ahZWbR/i3V9bZxcCuqMDetMnJ9j9kCFaPno3uAUqdu/xzPIOHYBX0\nwj9xEp5hwzAbNyKdu+AZOBArN5fgmWfBT052TmxgYUF8Ud0k5vHFC/HuggGcZ+9BeAYPIfCTU4i9\nMZv43Lex+uyF1aMHVrc9WnVLsoZYoRDB035KNBwmsWQJnt69CZxxlrOAQqkmykTCm6uBJ0XkZuAT\n4GG3/GHg/9xFCltwAjKMMctE5GmcxQkJ4BJjTBJARH4FzMZJI/KIMWZZm96JUiqNvbkwrccs+dWX\nVD/xH8IXXwKWhYTDmOoqkpEI1l59Ce9/IPj9qWFDq0sXsm66hdismeDx4p80CclrWrCVYmxnyGrD\nBuwNbue8t+5OBqayEhONOn8SBoL1rgg00Ui9CxGSq1eRWPIJ9ldfEDj9DOc+avwyNtEo8TdfJ/rS\ni6ky/5Sp+H80bYeJjE00SnzOG0Td9CUAvomTCEw+DhEhsfE7vDW2ubKysmAHw8PeYcOJvzO3TllL\nMMY4Pa0eb7uYkG/l5RH6+S+IPPYvEp8uASC5fBlVd95B1u+vRxqx/25rtSt46mmYHx3fbvZfVR1T\nmwRwxpi5wFz39Wq2rSKteUwEOLmB82/BWclau/w14LUWbKpSrc4uLcVs2QI+L5KXh5Wz6/z1XV9P\ngni8zi8qN7gQXx5WPZP6wVkV6OlZQPCsc5xEqzuz6GCrQBDPoMEkv/oyVeQ7/HAI1Uj9UV5G5P8e\nJ7FwAYjgO3ICgeNPrJN+QwJBvCP3IVkriPP07Uds1kySa9YQOPEkqBW4mKoqojNmpJXFZs/Ef/Qx\nzh6uxmBKS0l8vhRsG+/IfVKrbk11FdEZ6elLiMWJvfM2sReeByA+50284/cneNY5jUrl4Rk6FO/4\n/Z0FFyJ4x++PZ3DjNWhOVwAAIABJREFU92htiF1RQfLzpcTefAPJySHwk1OwundvMLmvHYkg9v+z\nd95hUlTp275PVecweciSQTJIRhAwgBgAQREToq4BV91dXePnz7TrrmsOa86rIu6aEwiiglkkg6Lk\nDAMzTOrcXXW+P2qmZ5oeYAYY4rmvay6p06eqTnc702+/532fx6z/4EWIKvmWCmRRIUQjWFU6Bwfh\ncO6VTp9CUR0lOa1QHEDM4mKC992LrOiG1tu1x33tdUeM96LwerEPP5X4jIrOU48H10UT6t44sB9U\n/TW/H/cfryX+zWyMFcux9eyNrWevFPHdxMIFVmMBgJTEv5iJvWcvtJ2yUkLXsQ8chLF2jTXf4cB5\n+pkY69cjAwFwudL00ioumi5BYprJblVZUkLw7juQZRVWWl4f3r/da7lJSNKK8O29ehH69+MpY4k5\nP8G550EtAjjNn4H74kuQ555nBchOZ53fm5owlv1C+Llnqtb06y/47nsgzRVDxmKYBQVE338XGYvh\nPHMUWovmaO56CuSEQOTlI7dvqxqz2cF+kJoYFIr9iArgFIoDhDQMYl/OTAZvAMaK5RirV6P1SC84\n3xvMSAQCAYytW9AbNgKv94CKhGpeH85RZ+E8ZRgyEEBk56TbXe0HZDBo2WbtoZZMy8zEcdoZyJOH\nIVyulLonaSRILF2adk5ixfIatxW1ykaE8echAwFiX35huREAztFn1ajgLyo7Yb//Ljlm690H4bSy\nL/GffkwGb9bzChCbPQvXmLHgcmEfOIj4N19XXdDtTpMqqSvC690vQVslMhgg9sXM1MFYDGPVSrSc\n1M0Ws6SE4D13JgPT0C9L8d5xN7Ruvd/WU52k28JDD0AsBpqGa8IEtW2pOCJQAZxCcaAwEphbtqQN\nm1u37pfLy0QCY+ECws8/m/yQd11yGfYBxx9Q2YRkLVb+rh0T9hYzECCxdAnx2bPQ8vNxjjrL6uLb\nTUG60HVEDTVZQrdhO66nlcHCyn65LpqA1rQpxvr11vb2TnVSlQK2pqZh79cfkZmFrV07cLuR8Vja\n6yw8HlznnU/i2A4kFi1E79INe69eVdvJ/gzsg4dirFhuGalT4RwgJZrbjXPcuejtj7XO7dQFLS8f\nx4jTiX1UVVNn69nL8vDEqpuTyJotvuoJabMhsnPSxmuqMUvM/Tktqxj9fDruyy5H2NPrE/cVIQR6\ny1b47n8QWVpmfZnweJIBtEJxOKMCOIXiACEcThyDh5Co3gkoBLb9lH2TgQDhN15LydBEpkzG1r37\nwdO92gUyHrfsjerwQSpNk8Tcn4n85xUAjN+WkVi0EO8999a5q7QSW+cu2E88mfjXs3BdNYnYp59g\n/P4bAFrDhpaTws6G54C5fTvhF19Aa9iQ+OyvkKWleG67Ha0Go3fNn4H9hMHY+w+wsoYVwaZZWooM\nlEEijvOsMcjyMiJT3sRx0snJOZo/A8egE7D37Zc813HKMGxt2xL/eQ56x07YOndBOBwYmzZaLgqG\ngXPkKETDRntslNgfaE4XzrPGkli0CMKWF6verr2ll7cTNb1PWnb23gks1xJht1um9TW8jwrF4YwK\n4BSKA4jWug2uyy4n9tlUcDhxjTt3r4OPNEyzygKpkmgUjHQ1/oOFNE3kjh1Ep32K3LEDxynD0Vu1\nrJWBuCwvJzZzRupYWRnmtm11s8aqhub34zz3XJyjz8JYszoZvAGYBQXEvvwC5+gxac0U8Z9+RO4o\nwthRVDX2w/fYagjgwMoEUS2INstKCT38IGaFM0D8++9wXnAR3vvuR8vIxCwttTJVum7pzFU7V/P7\n0bp2S3F3MLZtI3jXHcnsVmL+PLx//wc0bWa9TokEMhBARiLWVrLXu18zXlpeHr5//gtj3VqEz4eW\n36BGQWJb5y5oDRthFlhZZ+H34zhlWJ2s0hQKhYUK4BSKA4jm82EfOAhbt+6gif3bgepwoHfqjPFr\nlZqO3roNOPb/1tTeIsvKCN5zp1X4j9VE4P7TX7DXxrNT1xHe9EJ94dmp8zMYRMbjYLPVqjNTOF3I\naBRj3bq0x8xNm6wmhJ0COL1V6zQPU711GxKxBKESy0nC5XfhcKe+9tJIWE4U5eXJ4K2S2IzPsPft\nh7mjiPCTT2Bu3ozWsCHua/6E1rTpboOcxPffpm5NSkls5udWNy9grF1L6JGHrAyZ04n7j9dh69QR\nUYOsyt4gdB2RlYWW1WO387TMTDy33Y65YT0yFkNv3UZpoCkUe4n62qNQHGCEpqHVg3yI5vPhvuIq\n7CeehNaoMfYTBuO+9k+HlEyJsW5tMnirJDZtqmW9tQc0nw/n+RdAtQ5VvXPnlFors6iI0LNPE7jl\nRsJPPoGxbVtNl0pBBsoJv/IKtmM7pLk02AcPqVHuwda1G/qxHarW0b498Q49+GHyPO4/5WnuG/Ik\nM5/8hmCxtaVoRiIY69cRefkljA3rkTW4SwjdBokE4Scex9xs1cOZBQWEHnsEWV6WNj8FX3qjiPBn\ngBDIsjLCzz6V3N4kGiX83NNp78OBQsvMxNalq9Xtm5Wlsm8KxV6iMnAKxRGElpWF67wLkOGwtVV2\niBVr19hM4PGAXrsPcb1JU3z/epDE8t/QcvMtVf2KANUsLyP01L8x16wGwPj9N8KPPYLnltvSmhEq\nKdsWYN28jdB8EG3dftyT/kj0k48gFrMcD9q0rfE8LSMD9zXXISt8W4XHw5Z1AdbO20Dj9g1YM3cD\nXzz1Lc26NKbbaR0xt2wm9Pd70Fq2RF+9GuF2o7drn2In5hx7NtJmw9ya2ugidxSlmJ/XhL13H2JT\nP7FcIKjYmhx6IkIIa9u6qCj1hFAI4okarqRQKA4XVACnUBxhCIfjkGtaqERr1AiteQvM9RXblTYb\nzrPPqbUOmHA4ELm5OAYMTH8wnkgGb5WYWzbDLozCSwvKeWzUi4RKrMyUN9vD9W+dh/OkUxB+P1qH\njlZH7a6ei9+P9Hot0d1QiGxKGdM3TCK3GeHbBvPcpA9YNPVXOg5tRfzTT0BKtPwGGBs2kJg7B/ek\nP2Ju2YJZUICtVy+0ZsdAIoHIb5CiWyaysiwPz929Ln4/3jvuxli5HGkY2Dp0qtqatNvQWrXCXLOm\nan5+g5SaPBkKISNhS3tuFzZcCoXi0EIFcAqF4oBR6RdqrFmNLC5OOg/sCbOkmPiPP2KWFOMYPBQt\nJwexc4elriGyspAlJVVjHg/oNsySEmt71DCsAMXrZcn0ZVx47ynkNXCCgO0FEZZ8uZoe5QtxnDES\nfTfBmxkox1i5ksScn7D1Px4ZDJB4/lnrOQL+1m244N4xbN8WQ9c14hXBkrluLc6zxxH/6gtCD95v\n1YBlZ1vBndeLlBLPtddZ26bFxYiMTNzX/RlRwxYpgFlWBrEosW++xli+HPugE7B175ESgGn+DDx/\nvI7wi89jLP8dvVUrXFdMSgZ4Znk50Xf+Z+nNSYmtZ09cEy+rsQlBoVAcOgi5j6KQhxu9e/eWc+em\nGzorFIpDE7O0hOA9dyW3BxEC7x13o7dqlTJPGgbGiuWEHn3YEm2123FffQ1mWRnxr75Ab9sOe7/+\nxGZ9hevCCQS2lqC9/hzmWiszpbVsjTnhSnwNMnabxZSxGNGpnxCr8Dd1XX4lsY8/SnZWViJuvhsa\nNMSf68XYspngnXdAIo5r4iXI0lKi0z8DKXGefoZVt1gRpEnTtGreYnFLOsTvr9FSzCwtIbF0KfHv\nv0tpXLH164/74kvSxGrNQAASCdC1lLrIxJIlhB55MGWu69I/4Bg8ZFdviUKhOIAIIeZJKXvvPK4y\ncAqF4qAi43FL3sLtrtFCy1izpip4A5CS6Ifv45p0NZqrqqZO6Dp6m7aWaGsojHA5iX37LbH33wXA\nXLfO2q7s0pXEsmU4SkqIra3aVjTXrsaxfjla66G7X28oROyzaVUDmkDKdKkWt9+JLdfK4ml5+fju\nu5/4z3NAt2E/8WTsQ0+ypF+czhS3DKFpiMw9y6IkFiywRIerBW9gWWvJ8eenBXC72hZNVJNOSY79\n+gv2gYP2zYtWoVDUK3Vu/xFCZAshanaiVigUij1gRiKYO3ZgrF+PuWMHkXfeJvToQ0Q/fB+zrDT9\nhJp2CaS06rV2QtjtaFnZ6E2aACSDt0qMpUvQW7VCbt2C3Lg+7fyaxtJvAmhVgU3i558tc/pqaC1a\noGVUbXsKux0tLw/naafjOGEwOBzWc3/9P0RefhFjwwZkrOZavV1hFhZar8HOQZbTmdZNuzts3bun\njdl79VHBm0JxiFOrAE4IMUsIkSGEyAHmAy8IIR6p36UpFIpoMEY8Uj/dgtIwLF2yA4iMxTAWLSRw\n0w0Yq1cRfvZp4jM+w1yzhtgnHxN59RXL57QaeqvWlpJ+JULgGD0GrYaO1hSEllKoD1im8/EEVOjx\n7Yzj+BqaI3a+rMeLc/RZyePEgvloObl4brsd++AhOCdMxHP9jbutIZOFhYT+fjeJBfNJzJtL8J47\nMYt37PHe1bEPHERiwTwcw05NGXeeM65OXqda4yY4x55jBX42O/bhp6J36LDnExUKxUGltluomVLK\nMiHE5cBrUsq7hBCL63NhCkVtkfE4MhhAFpdYBfFu954/3A9xwmURtvxWwFfP/YAny8Ww6waT3TQT\n3b7vWRFpGJYbwozPIBLBceoItPwGB0RyRAaDhF99GUwTrUnTFBkNsIR9ZSyWEoBoWVl477yb+I/f\nYxYXW/IYObl7vJfweHCeex7RN15LjjnPGouxaaNla6XruC6/kuhHHyCEwDl6DFrDRnu+rt2OfeAg\n9DZtSMyfh97+WPQ2bdD8Gejt2u/WlxWsGrfYlzNTM4uGQfy779DHnr3H+yfXkZ2NrXcfzB078Nx8\nK8aWLdjaH4uWnV0nlwXN58Nx6gjsJwy2BlyuA2LBpVAo9o3aBnA2IURj4Fzg9npcj0JRJ6RpYqxe\nRejhBy2tLCFwTbwUe/8Bh5wGWl3YvKyAp8f/J3m8eNoybvniGrIa73tnoCwtIXDn7VAhJhv/7lu8\nf7sXvdkx+3ztPWIkkvcFCTY7JKppnLncgMQsKUFGIwiHE+HxoGVn4zztjDrdSjidOAYcj61LF8wN\nGyyZDocDzelMBoj2Acdj69LVmu/311pUVvP50Nq2w9a2XeoDUmKUlyPi8YqOVwfCn5FyXaFpNboP\n1NWRQHO50Nq0RTYOWd2jHTvV6fyUex/C0jMKhaJmalsD9zdgOrBKSvmzEKI1sKL+lqVQ1A5ZXkb4\nxeerhE6lJPLG68hQ6OAubB+IBmPMfuGHlLFYKM6K71bv4oy6EZ8/v1oQhWW79Nk0y36qvnE40ZpZ\n/pzxOXNwnnFmysPOs8aQWL6cxG/LCN56M4FbbsLYuAFj82Zic37CKNiKWYf3Vng86A0bYe/dB71R\nI/ScnJTsXtIVIzMTGQhgFm7HLN6BWYNTwp4wQ0ESK5Zj/v4bgTtvJ3DLjQTvucvSotv5ZRg8NCVg\nEzk52Hv3qfM9K59jXbZMFQrFkUGtMnBSyreBt6sdrwZqn+tXKOoLSbrKfCK+R+X6QxlNF7gz07ew\nPFn7Z1u4xkyLo26F73uLlpGB5y9/JfLGayTmzsH1hyvx3nMvxsaNaE0ak5g/j+iUybivvgatYSP0\nzp0xli4h+sH7yWu4LrkM+/ED97hNaJaXY24rwFy/Hr1DB0RmFprHg1lWhiwtBQEiIxMtIwOzuJjQ\nE49ZkiI2G84xZ+MYMrROgZEsKkKYJqFXXoIKhwZZXEz4mafw3HxbSk2cyM62nveK5aBp6G3botWi\n81ShUCgqqVUAJ4RoDzwDNJRSdqnoQh0lpby3XlenUOwBYbdj69adxKKFVWP5DayC7MMUu8vOsOsG\ns3jaMmIhKxBt0CaX5t2b7pfr27p1TxW8dThwjjitRgmP+kDLzcV9xVVW16Xbjdy6BTSBuXYttm49\nMNavB5cb96Srweki8tqrKedH/jsFW/fuqY0NOyGDQaLvvUN81lfJMfeVk5BduhJ+8H7MjRustTRv\ngeevNxH96IOkHhyJBNG3/4utZ8/divnuTHzuXGsbsyJ4q8TctMmSC6mGEMIyf+/Tt9bXVygUiurU\n9i/2C8BNwHMAUsrFQog3ARXAKQ4qwuvFdcllRN7+L8bSJWjNW+C6eOIuvS8PF7KbZnLLl9ew4ts1\nuDNdtOjRFH/+/rE3EpmZeO/6G4lFC5HRiCUZsZ9fLxmLWVlQj8fy3YTUrUuPB+HxYJaWEn72maT/\np/D58NxxF5Epb2IsXIDIb4DrgouIO51VQXokAka67lrK/aMR4rNnpYxF3pqC+8ZmyeANwFy/DnPb\nNoxVK9OuYW7Zgt6oca2fs96iOSTiCL8fWV5eNd6mbbrUh0KhUOwjtQ3gPFLKOTt1VyknZMUhgZaV\nhWvCRIhErGJsT+18NQ9ldLtOVqMM+pyTrtG1r1RmfxxDhu73a0spkUVFVkaroAD7gOMReXnEpn2K\nc9RZaM1bpHQIJ35blmLeLgMBYjOmo3m9GIDcvo3wc0/juf6vyQDO1r07CDBLSnbpUoBhpOnHyUgY\nUUPgZ2wrwNa1O7ENVYEdQtS5qUNv257opx/jvnISkTdewywoQGvVCvdVV6P5a7bCUigUir2ltgFc\noRCiDRXSmUKIc4Atuz9FoThwaC6XpfGlOKjIslKC995j1ZgBxvLfcY45G+H1Ebr/Prz33IuZlwea\nhuZ0IktL0q9RXp6qoRaJgG5Da90WW9u22E8YjLllC+Hnn8U18VL0Tp3TZS+cLrSWraq2RQH7kKHg\nSt9atzVtiujcBbNgK4n58xA+H66LJkIdDd21jAycZ47CjMVw//VmhCasrlf/wfcUjUcTJGIJ3H71\nO6JQHCnUNoC7Bnge6CCE2ASsAS6qt1UpFIrDDhmLYRYWJoO3SuLff4vjzFEkfp5DbPZXiOwcy9R9\nzFjsx/Ui+vb/LI/OCuwDBxF9c3LVBXQd4XRg790bc+MGgn+7C+fI0eitWhN+8gl8Dz6SFrxbzRLX\nE/tiJsaqVdh698He23IXcF99DdEPPwBh6cJp+Q0QHg/uyy5HXjQBhED4dpHZ2wOa3193e5t6REpJ\nyeZSvnj6O4rWFzPggl60GdAS735qiFEoFAeP2nahrgZOEUJ4AU1KWb6ncxQKxdGDWV5O9LOp2Lum\nu+wJnx9ZUdiv+fwYy38jsXgxiYUL8P3rQbx33UP0/feQ0SjOM0ci8vKQldpwDgeuiycS+2JmSkNC\nYukSbF26kFi0ELNgK1puurCvlpmFc9RZljCwy5XUYrP16Yt+bAerC9WfkRTerazLO5Io3x7k8bNe\nony75W6x/JvVjH9gJL3P6YGm1X/XsUKhqD9q24V6w07HAKXAPCnlwhpPUigURwXSMIh//x3xqZ+i\nN25idQUvXmQ9qOs4Ro4i+t67iNw8bF27Ef3kI+uxeJzEooU4TjwJ1xVXIUwT4fEgpcR7x90QjYLD\njgyHibz4Qso9tSZNMAst+RitQYNdrk3YbGndtUKI/d60cahSuLYoGbxV8vUrc+h0cnt8uUo7TqE4\nnKntFmrvip+PK47PBBYDk4QQb0spH6iPxSlSkYk4MhBEhkMIl9vKGBzGchmKA4sZCCC3bSOxcjm2\n9h0QeXlodazzqgkZDpGY8xMAkcmv4770D9iHnogMBLB16IgZCuI69zyE30f42WesBoMKKsVsq9ew\n7RxgmboN+9ATkxk4rUlTHIMGE3z8EVwXTwQlYrtLnL70vw/uDBeafiht9CoUir2htgFcM6CnlDIA\nIIS4C/gUGAzMA1QAV89IKTHWriP08ANWUbfNhvuKSdh69FAWOIo9YkYixGZ8RuxjK/sVBZxnj8Mx\nfDjCsW9fAoTDida8OcbqVRCJEH7mKUR2Nu4bbsIMBtByc9FatLRcDqo1LWhNmqDvbEVVA5rfj+uc\nc3GeOQqZSCQFfH333IvwevZ5/UcymQ39tOnXglU/rQNAt2uM/H+n7DdRaIVCcfCobQDXAOtvfiVx\nLFHfsBAiuotzFPsRWVZG+PlnqyyQEgnCL7+A774HVACn2DPhMLGpn6YMRT/+EPugQfshgHPgHDka\nY9kyzIKtANi6dMVctZLIqy+jNWuG58ZbENk5+O69D2PlCnC50Ju3qLVen/B6lV3UXuDL9XLxU+ew\nZcU2ijeU0Pb4Vvjy1OuoUBwJ1DaAmwz8JIT4sOJ4JPBmRVPDr/WyMkUq0kRu35Y6Fo1CPHZw1qM4\nvJAyZesSsIR2d9JKqwvlhQFCJWE0XcOT7cZz2+1Ws4JpkFi4kMgbrwFgbtxIYukSHAMHIbKzlfvA\nAcaX56VdXisYcLBXolAo9id7DOCE1bHwKjANGFgxPElKObfi3xfWz9IUKdjs6B06Yvy2LDkkcvPA\nqXSdFLXA6cTWsxeJ+fOSQ7Z+/RF7+f9P2bYAz130OluXbweg3aBWXPT4WLwNGhB5+UXi332bMt8s\nKNj7tSsUCoUijT0GcFJKKYSYKqXsCszd03xF/aD5fLivuIrIa6+SWPYreouWuC67PFkErlDsDs3r\nxTXxUuLtj8X4dSl61+7Y+/bbK9kM0zCZ8/aCZPAGsOLbNaxbsInOp7THfuJJqQGcENj7q/RPfWCa\nkkBREKTE5XfhcNsP9pIUCsUBorZbqPOFEH2klD/X62oUu0XLybEMuWMxsNn2Sweh4uhBy8jAMWw4\ncshQy3JM27tORCNhsumXrWnjW34roPMp7dEbN8b9p78Q/fhDhK7jHDsOkZOzr8tX7EQ0GGXlj+v4\n4K7PCBaH6Df+OE6+dhC+HFXjplAcDdQ2gOsHXCiEWAcEAYGVnEtX7VTUK0ei2KjiwCE0DbGPlmN2\np42+43qweOqylPHOw4+17uHxYj+up9VhKoT6olFPBHaEeOXyt5JljF+//BPZzTIZNLGvkglRKI4C\nahvAnVqvq1AoFIcVzXs0Zcw9I5j1/A/YXTZOv/lksvLcSMNIWlApA/f6Zd28jWk9KIs+XUbvMd3x\nZCuZEIXiSKe2VlrrAIQQDQBVNa9QHOV4sz0cf2Fvup3eCZFI4Fi+kMSz7xDr2g37kKGpZvSKeqFB\nu7y0saZdGmH3qDo4heJooFZ5diHEKCHECiwT+9nAWqyuVIVCcZSi2TR8Lon2n6eJvvoyxorlRN97\nh8jk15Gh0MFe3hFPduNMjp/QO3ncsG0eJ/9xIHZnbTdWFArF4Uxtf9P/DvQHZkopjxNCnAhcVH/L\nUigOT6SUmAkT3a4f7KUcGGJRjN9/SxlK/DwHed4FqlaznvHmeDj9xpM4+eqBJOIGTq8Df56qN1Qo\njhZqG8DFpZRFQghNCKFJKb8SQjxWrytTKA4h4tEEoZIw0jSxu+x4s9ODk7JtAea+u4jNywrof/5x\nNOnY6JC2LAoUBdm4ZAsbFm+m0yntyWmaiTuzjusVGuh6qkiwyw1C7N/FKmrEnenCnamqWhSKo5Ha\nBnAlQggf8DUwWQixDasbdZcIIVwV850V93lHSnmXEKIV8BaQi+WjOkFKGRNCOIHXgF5AETBeSrm2\n4lq3AX8ADOBPUsrpFeMjgMcBHXhRSvmvWj9zhaKWRMojLJ62jA/+Np1oIEb7Qa04/9ExZORXZTvK\nCwM8e8FrFKwsBGDBR0s576FR9BrT7ZDsCAwWh3j3/z5l8TQre/bZI7MY/+Aoeo3pim6rXfZQBoMY\nGzfgOPU0YlM/SY67xp+HUJ2nhxyRYIzSzaX88OY8Mhtl0POsrmQ2VI0mCsXhSm0/WUYDYeB64DNg\nFZad1u6IAidJKbsDPYARQoj+wP3Ao1LKtkAxVmBGxX+LK8YfrZiHEKITcB7QGRgBPC2E0IUQOvAU\ncBrQCTi/Yq5CsV8JFof5780fEw1YtmXLv13Dl099SzwST84p3x5MBm+VzHzqW4I7Ds1asGgolgze\nKpn6wJcEi8O1voYZCBB+7BFEZiaeG2/Ged4FeO64G71nT4RN1WEdahSs2M6Dpz7LN6/M4ZP7ZvL4\n6Bcp2x442MtSKBR7Sa0COCllUEppSCkTUsr/SCmfkFIW7eEcKaWs/Otgr/iRwEnAOxXj/wHOqvj3\n6IpjKh4/ucLGazTwlpQyKqVcA6wE+lb8rJRSrpZSxrCyeqNr83wUirpQ3XGgkpU/riUarPKh1Wzp\nv0o2u37AtxLNYBCzuBiztAS5s/dpNaSR7oGaiCbqdq+CrSAl0SmTCT/zNPEfviPyxmsIc+/9VRX1\nQ6Q8wozHZiOrvTelW8vZsHjzQVyVQqHYF2rbhTpWCLFCCFEqhCgTQpQLIcpqcZ4uhFgIbAM+x8rc\nlUgpKz8pNgJNK/7dFNgAUPF4KdY2a3J8p3N2NV7TOq4UQswVQszdvj39w1ih2B0Na5BraN23OU6v\nI3nsy/HQsmezlDmn33QSvtx9K+SXoRDmjh2YO3Ygg7utWsAsKSH89JMEbvgzwbvvIrHsV8u1owac\nXgctjkv9dRlyeX/cGbWvp9KbNksGqDIYwFy3Dr1DB9W8cCiyiy8SqlRRoTh8qe0+xwPASCnlsj3O\nrIaU0gB6CCGygPeBDnVc335BSvk88DxA7969VXpAUSe8OR7O+ecZfHTvDGKhOG36t+CU6wZjd1Xp\nbflyvVzy/HhW/bSOrcu30f30TmQ3yUDswyekWV5O9L13iM+eBYCtT19cF11co0CuGYkQ+d9bGL/+\nAoAsKSb8+KP4HngY4XCkzfflern0+fHM/3AJa+dvpOforrTu2zwpQWGWliIjEYRNB5cLzVtDTZvX\ni/tPfyHyn1eQZWXYevfBeeppCPuB1SEzTUlge4A1czdgc9k4pluTlPpEBbh8Tk69fgi/f70qmYXL\napxBs65NDvLKFArF3lLbAK6grsFbdaSUJUKIr4ABQJYQwlaRZWsGbKqYtgk4BtgohLABmVjNDJXj\nlVQ/Z1fjCsV+w+130XtsNzqd3B5pmNjdNXeh+vO89DijE5yRXopZvj1ANBTD5rTh8jpx+Z17vK+5\ndg3xWV8ljxMf1ZqOAAAgAElEQVRzfiLRrRv2fgPSa8wiEYxlv6aOJRKYxTvQsrOrrhkMQDyBsNvx\n5/s44bL+HD/BSNEOM4uLCT30AOZm69fJfsJgnOPGpwWOmsuF6NoN791/AwnC6US4D3zXbdnWMh45\n4/lk/V5u82yuffdSFcTtRMO2+dw0YxI/vbWAjIZ+eo7uol4jheIwZrcBnBBibMU/5woh/gt8gNWc\nAICU8r3dnJuPJT9SIoRwA8OwGhO+As7BqlmbCHxYccpHFcc/VDz+pZRSCiE+At4UQjwCNAHaAXOw\n/FjbVXS1bsJqdLigDs9doag1dpedTNfeZZZKNpfy7EVvsH11EZouOOW6wZxwaV88e5DsSOwckAHG\nL7+gtWuPrUHDlHHhcKC3bEVi4YJqgwItKyt5aBZuJ/zKyxirVqK3a4/7ksvQcnPRqgVvMh4nOn1a\nMngDiH/zNfahJ9aY+RO6jsjMShs/UJiGyTevzklpvihaX8zvs1fR55zuB21dhyJOr4OGbfMZ9X/D\nD/ZSFArFfmBPNXAjK378QAgYXm3szD2c2xj4SgixGPgZ+FxK+QlwC3CDEGIlVo3bSxXzXwJyK8Zv\nAG4FkFL+AvwP+BWrA/aayoYK4FpgOrAM+F/FXIXikCEaijH1wS/Zvtrq+TENyYzHZteqO9XWLT0A\n0du3J/bhB5jlqSWowuPBddHF2Pr0BZcLHA5cl10OHq9137IyQo89Ym2xRqMYS5cQevKJtOsQj2Gu\nW5d2X3PTxto+5QOKNCXl29NrAwOFR3Z3ZaAoSMmWMsq3B5A7G6IeBRiGSdm2coo3l1JeuPvaUIXi\nSGW3GTgp5aUAQoj/AH+WUpZUHGcDD+/h3MXAcTWMr8bqIN15PAKM28W1/gH8o4bxqcDU3a1DoTiY\nxEIxNv2yNW28cF0x+a1yd3uu1uwYHCNHEftsGpgm9hMGIzIyMRYtgnHjU+YGi0MUb42xOW8grW4c\njzfDjj3TU1X/FothbkqtMDDXroFYPGUMlxtb334Yv1WrmBAC/diDUr66R3S7zuDL+jHv/cVVYw6d\nbjVsYx/uGHGDcGmYcHmU1699l02/bCW3eTYXP3U2jTs2rLV+3+FOImawftEmXr/mHcq2BWjUPp/L\nXjiP3BbZez5ZoTiCqG0NXLfK4A1ASlkshEgLzhQKRSruDBedTmmfIkWi6YJG7fN3eY4ZDkMohFm8\nA8eQE7H17guhEIkliwk/8xT2IUMRnqrt13BZhJlPfsPXL/2UHLvwibF0P70jyY90mw28XqjWySoy\nMi0XhWoITcPeuw+ysJDYV18ivB5cF1yE8B+65vR5rXK49p1L+eKpb7G7bQz/yxAy8o8sgVrTMNmw\nZDPbVhXx/Rtzk18KitYX88Ilb/LXaZPIaHB01LOFikO89IcpRMqsap6ty7fzxl/e4/KXzsebozqg\nFUcPtQ3gNCFEtpSyGEAIkVOHcxWKoxabw8bgy/pTti3Agg+XkNHAz7j7zkxabMlEAhkIgBAIvx/i\ncRI//0Tk1VdAStB13H/6C8bKFcR/noNj+Agcp45AOKqaIKLBGN+8Miflvh/+bTptB7RMFqkLnxf3\nFVcRfurfEI9bW6xXTrLuuROa349z9Fk4hg1Prktoh56bRCUun5NWvY/hon+PRWgCpye96/ZwIhqM\nUbq1jPkfLiW7WSYdT2yHEPD6te9ywaNj2LAoVbstUBQiFq5ZLuZIJBqKJYO3StYv2ISR2LXuoUJx\nJFLbIOxh4AchxNsVx+OoYUtToVCk48/zMvaeEZxx88kIAd5cL5omMAMB4t98TWzGZ1ZAde556K1a\nEZn8hhW8ARgGkVdewnvH3ThOHobweNJkOoy4kSLQClZWjmq1UcJmx9axE777H0KGQwi3B+HzIfSa\nt92Ew1Gj/EhNSNO0Ar2DLCrm8u25s/dgYRom5dsDLP18OUhJ52HH4s/3odcgAL3ltwKeHPdq8j1t\n0CaXq96YQMnmMoo3ltCofX5KRteV4cSxlw02hyNOrwOX30mkvCqIO6Z7k6NmC1mhqKS2TgyvAWOB\ngoqfsVLK1+tzYQpFTQSKgpQXBjAM82AvpU44vU4yGvjw5/vQNCvQMX7/jej/3kKWlCC3bSP85BPI\nWBx2Et+VJSVWR2lmZo0aaw6vg2ZdG6eM9R3XA6c3NaARDgdadjZ6k6Zo2dn7rNcmYzGMggIib04m\n+vZ/MQsLd+v+UBeiwRjR0K6zSqZ5eL3/ZdsDPDTiOd67Yyrv3TmNh059lvJt5WnzQqVhpj30VUpA\nvm1VEYXrdnDskDbMfulHxvztNLKaWFvaniw3lz57Lp4aZG2OVDxZHi578Tz8+VaDToM2eVz0+Fi1\nfao46qj1NqiU8lesTlCF4oATDcZYv3ATH//zc6KhGEMu70/30zvVqMdW30gpScQN7I69ryKQsSjx\n779LHw+H0Jo0wdxctU2md+kKu8mG+XO9/OGl8/n6pR9Zt3ATXYYfS6+zuqY4RdR6XaaJLC+zmhvs\nNoQ/Y5dZOnPHDoJ3/D9IWMYqsa++xHfvfYjc3Tdn7I5oMEbByu3M/Pc3aDaN4X8eQl7LHBxuK9gM\nFAVZ/s1qfpu9ks6nHEubAS3xHQYf3PPfX0yopErqJFwW4ce3FjDihqGpEyUYifTgVBqScf88kzf+\n9B6f/usLxj84iuwmmTg9Drw5HnT70ZN9sjl0WvZqxg2fXokRN7A5bfjzjo76P4WiOqqOTXFYULat\nnOcmvJHMTLx7+1QyG/jpPOzY5ByztBQZKAe7HeHxoPl2Xcgu43GIRcHtqVN9V3lhkIUfL2X1z+vp\ncWYX2g5osXdBpG5Db96CxPx5aevyXH8jkSmTMdauwdaxM85zxqF5vbu9XEYDHyNuHEosFMflc6Lp\ne1ezZm7eTOjRh5E7ihB+P+5r/oTetm1aECdNk9jn05PBGwCRCPE5P+E87fS9ujfAjo0lPDHm5eT7\n/MvM5dw842ryWuUQKY/w0b0zmPf+EgDmvb+E4yf05oxbTj6kt08BoqF4+lgwmjbmyXIz7LoTeP7i\nycmxrMYZNGyfT0a+j8teGI+RMNBsGr6c3f8/cSSj23QyGhxZjSoKRV1RAZzisOC3WSvT6rx++u8C\n2g5shdPjsNwD7v8nZkEBALbjeuK65DK0jPTuSbOkmOi0qZhr1mDr3Qf7gONrFKndmcCOEK9f+w6r\nfrR00hZPXcbJ1wxi2HUnpNhq1Qah69iHDiU+dw7mRktjTe/WHb1RY7SMDFyXXwHRmGVj5aqdP6nN\nbsOWufe/0mZpKeGnn0TusDTrZHk54X8/jvfefyKyahDrrSkzt5eBI1iWWN+99nPK+2wmTH58az4D\nJ/bB5rAx/4MlKef8OGU+p1x7wiEfwPU9tweznv+eRNTaYtbtGgMn9KlxbvPjmvKXjy7nu9d/JueY\nLPqNPy7ZjKK2CRUKRSUqgFMcFuS3Tt+Wa9A2D5vDhkwkiH4+PRm8ASQWzMccPiItgDNLSwk98hDm\nhg0AGCuWY24rwDVuPMK5+yAgFowmg7dKvnn5JwZN7FvnAA5Ay8zCc9Otlkm9riPc7mQgqbk94D7A\nH9amibkltcNRBgNpNXlgyY04hw23fForHhdeH/Y+aRKPtUbTRLKuqTruDBfTH5nFiL+eiNAE0qgK\n8DT98HBjz2jg58bpVzP7hR8wTZOhVwwgs1HN0ixuv4tjujXh3PtGIvSD3xyiUCgOTQ5dbQCFohrN\nujSm7YCWyeOcY7I44dK+6DYNGY8nA7LqVLeDqkRGo2lz41/PRkbCaXN3pqatVt2hW6Zue4mWkYHe\nuDF6gwa1ygLWK7qO1rxFypDIzARnzbV0IjsH3z//hXPsOTjHn4/37/fus61W//N64surCuKymmTQ\nbmArK/MmJf0v6JUy/4RL+9XKV/ZgY3fayG+Zw5h7TuPsv51Og9Z52F2p35/DZRFKNpeyfU0R5dsD\naDZtl8FbLBxn+5odTH3wS2a/9COlBekNEQqF4shGZeAUhwW+XC8TnjqbYFGIeDRBZkM//optJc3t\nxj5wEMbSattrQqB37pJ2HaHrIESqxIbXhxE3WfjhEoy4SfsTWlvXDgbAMCxJDY8Hp9dBz9FdmP/h\n0uS5p9144h49TfcGGQoh4zFwVm2hxsKxpHSCO8O1V1m/3aFlZOD+47WEn3oCc8MGRH4DPNdch9hF\nLaGw2RC5eThHjtpva8ho6Of6j69g2ZcrQECj9g343y0fk9siB5vTxqnXD6HLsGNZ/s1qOpzYliYd\nGh5Wum81yYYABEvCfPHUN3z94o9IaYkTXz15AllNMmucX7huB4+e+QJmRcPDrOd/4PqPrzhqxHwV\nCgWIo81Hr3fv3nLu3LkHexmK/YxZXk7826+Jzfwc4XLjPO989Lbt0NypwZUMhYi89w7xL2ZaA0Lg\nuvpa3nlzY7I4vuPQNlzy9yFEXnkBc8NGbF0647r4UrTsbAJFQTb9spV1CzbS8aR25B6TnRTl3VvC\nZRHCpWGKN5eR3zoXL2GiUyZjrFmD3qkTrnHjCZkOZj3/Pd+8MgdNF5x09UCOv6h3vXThmmVlVnOC\nriMyMg74Fp5pmBSuLeL9e6az/OvV5LXM4dLnx+/WvaImyrcH2Lh0C6HSCG37t8CX5z1ktcK2Lt/O\ng8OfSRnrc24Pxt4zAoc7NUCNheO8deOHLPo0VRTg4qfOofsRaCGmUBztCCHmSSl77zyuMnCKIwLN\n78cx7FTsxw8EodXYvACA243zjJHYB56AuXkTert2bFhZxrz3pyWnjJjUm/DD9yNLSwFILFxI2HgJ\nz1VX48v1cuzgNhw7uM1+WXc0GOPndxbx4d+mA3D1C2NoNGtyUkYk8f13RF1u1jbsy1fPfp8877OH\nZ9G6bwuadGqIw+3YZWZnb9jla3eA0HSNvFZ5nP/wWRgxA5tDT9lWrQ3l2wM8c/5rFKwsBMDpc3DD\np1eS1yKnPpa8zxSuLUob2/zLVmKheFoAh5SYNeggmubR9WVcoTjaUTVwiiMGYbOhZWbtMgCRwSCJ\neT8TeuwRYu+/i9aoESIzi99+TK2V83q0ZPBWibF0CTKRLgVRE+WFQYo3l1K2PVDjB211IuURPrnv\n8+RxTkN3igYcWNIii6ct2/lUlkz/jdkv/siXT39LeWEw7fHDGU0TZOT7yG6aiT/fV+cs4PpFm5LB\nG0A0EGPmU98Sj9buPTzQNO3cOK0ho+uIjrhr2J53eBwMu+4EhFY135froU2/5vW+ToVCceigMnCK\nowZj8ybCTz0JgAkkli7Be+999Dm7O18++x1GzJJ4MIQN3W63PEMr0Bo3AZH6fUdGIsjychLLf0dr\n1AitYSN2FMZ45cr/snX5djIb+bn46XM4pmuTXQqtJmIGRrwqyEuYApvDkdr5GQrS7vieyS3eSpp0\naMDXr8xhy7IC1szbwIWPj8GbdWA7V81ARZeqEJbN1x46efcnlidmhFgojtPnwJfrTerfBXekN6UE\ni0KYCQmHYM+DJ9vN5a9ewLv/N5XybQF6n92NARf03GVmNa9VLjfNmMR3r8/Fl+Oh3/jjkjWhCoXi\n6EAFcIojkmgwlhRK9WR50HWIz/oqdZKUxH/6gYzTRvPXqVcy88lvMRMmtkwfrksuI/LKS1YtmNeL\n+8qr0jJ7iVWrCD/8QLIhQl5zM2/8/cekT2Xp1nJevHQKN39+9S5FRx0eO/mtc9m+2tpC+/a/Szn1\n7PMx3notaWZvH3oiHRu1osupx7J0+u8IAT1GdsaT5WbLMks65ffZq4iH4rBvTaB1wiwtJfzi81bz\niMOBc9x4HMcfj/DUv8BsNBhl4ce/8u6dUzFiBv58H1dPuZiGbfMAaD+oFQ63nVi4KggfemX/vXKn\nOBA4PQ7aD2rNde9cipTg8juT7hO7mt+wbT5j7h6hZEYUiqMUFcApDkvMQMDKkGkawu9PkfgI7Ajy\n2cOzmPO/BTg8Ds689RR6jOqM1rhx2nW0Ro2xu2w0bJvPuf8aiURi10FmdMb3rweRsahl/L6TxIdZ\nVkb0zTdSulmlw8mGRanbn+HSSI0q/JX483xc9fpFfPzPz9mweDPSZkfv1Rt3rx6YxcVouTmWvprD\nwfj7R3HWXTGkKVk8bRmT//x+8jo2p56ypbYzMhi0MoaJOMLlRsusubuxtshEgtiM6VWdv7EY0cmv\nY+vSBf0ABHCR8ijv3P4JZoUmXPn2AP+7+SMue+k8vNke/Pk+bph6JTMe/5pQSZgTJx1Pk46N6n1d\n+4IQos5ZtP0RvAWLQ0QDMaSUVibzKHZ4UCgOJ1QApzjsMEuKCb/wPMavvyCys3FfcRV6m7YIhwPT\nlCyeuowfJlsWVeHSCG/f9gktezWjwaDBxL7+Grl9GwDaMc2xdeqcvK7dZcMMlBP7YhbRTz4G08Qx\n/FQcw0ek+4GapiVya7MhPF60hg0RPg/NujRm49ItyWnuDNduMykA2U0zOff+kcTClg1W5XxtJ09R\nT5YbT5abeCSOpouU7NLwPw3G5rYRj8TT5EXMQDnRD95Pdt5qDRvhuflWtJy9L+iPl5STWJZujWys\nX4feKD1Q3t+EyyLJ4K2SLcu3YcQrnQ508lvlMu6+MzANecg7NRwsAkVB3rz+fX7/ejUArfs25+Kn\nx+GvY9OIQqE48KgATnFYYUbCRN6agvHrLwDI4mJCjzyM74GHEA4HsVCMpTN+Tztv5Q9raTSxL97b\n78AsLEToOiInJ92pYfNmou+8nTyOffIxepu2aD2OS5knvF7ExKuI2rzEIgnyMyH27htccO84Xr5+\nKoVrduDL83LxU+fUSurD5XPWOsiwu+z0Prs77Qe1Zt38jbTudww5fg25fTPG5k0Y7dpDRia611Px\nGpVUyaYAZsFWoh9/iOv8CxGOum8p7thYwty3F9C/VTtYszrlMa1pc0oKynB5a/989gZPlhuX35nU\nxQPoMKQtjp004dI6OBUprPxhbTJ4A1g9Zz2/fP47/c/vefAWpVAoaoUK4BSHF5FoMnhLkogjS0sg\nOxuHy06rPsfw+9erUqYc060JAFpm5m63D+ML5qeNJeb8hK1b95Rt2mjUZO7PZXz8z/e48e3ziTzx\nKDIYwFNezqR7x2Bm5WHLycKX70tqj8lQCKlptfY23R0uEUNbMYesRl5snqbEpk0l/uUX1toA11VX\no/Xpi9B1zK1b0s431q1DRqN1DuBCJWHeuukj1s3fSI+3z8dbsBnjlyXgdKKdOZbvP/idjx/9jmHX\nncCgiX33WSNvV3izPVz95gSm/PVDtq0qpONJ7TnrrlNVpq2OrF+Q7laydt4G+o4/Dm03W/KHMkbC\nIFQcRkpwZzj3u+C1QnGooAI4xWGFcDjQW7UmsXhR1aCmITKsoEyzafQ/vyfLv1nN6jnrEZpg0MQ+\nafpfZiiEDJRjrluH1rQZWmYmwuvF1qUr8ZmfW80LFeidOiWDN2kYEAljRCWfPTYbAJezwjMUkBvW\no7/4ODrge/QJNJuOGQphrltL9NNPEE4nzjFj0Ro2Qtj37oNFBoNEXn2FxIL52G+4FRGNEP/qy5Q5\n0SmTsXXsiMjMQm/VOs19wt6nL8JT947VRMxg7bwNGDGDpy59lzP+PJDWw8/G38DPJ4//wPdTfgZg\n+qOz6XZap2QAZxomgaIgsVAcu9uOJ9OdZiVVF3S7TrOuTZg05WKkIbG7bLgz9j0wPtrodkZHZr/0\nY8pYrzHdDtvgLVwaYennv/Hp/V8QC8c54ZJ+DL6sH96cA+wrrFAcAFQApzisEB4PrgkXE3r4Qcyt\nW8HhwDVhIlQLRvx5PiY+ey6xUAxN13D6HLj9VR/uMpEgsWABkRefq7iowHPjzYicXEgk8N5xF7HZ\ns4h/+QW2Hsdh69YDALOslPjsWSSWLkXr0JEbppzHk5e8Q8zQcLtcEIkk76G1aAkVQZ+5aROhB/6V\nfCyxeDG+++5H5OXt1WsgY1ESCxdY99Gs58NOjioyFIKKIeHz4b7hRqJvvIZZWor9hMHYBw1Kr+ur\nBbpdo0WPpqyes55AUYj/3jkTh9vOH9+ayPdTFqbM3fL7tqR7QsGK7Tw3YTLl2wM4PHYufGws7Qe3\nxrGP2RF/rqrV2hcatM7j7H+czozHvkaaJif9cRBNOjU82Mvaa0q2lPLWjR8lj2c++Q2N2udz3Kh0\nWz2F4nBHBXCKww4tLx/PbbdDNAo2u1WPttNWoC/HA7v41i0DASJT3kgeO04ZhrFiOdEPKro6hcD9\nx2txjBxtiQP7fClZLwBj+e94uqxi5A0Dmf78XM6acCXizZeRwQAiPx/3VZPQMjKQsRixGZ+lLiAR\nJ75gPs5hw/fuBRACnE6IRDDmfI9+4iloLVpirlubnGI/fhC4XFb3aSKB3qEjntv+D6REeNwIx95t\nNXqzPZz30GheumwKBSsL8Wa7ueCxMRSu35E295huVjNDoDDI5L+8T/l2K0sZC8WZ/Of3uHXWtfsc\nwB1IYuE40UAUp89xxNTWebLc9Bvfky7DO1jHmW5sjkPTbqw2LJu1Mm1swcdL6Tzs2D02EykUhxsq\ngFMclmgZ+yCDISWEQslDW+++hB78V8rjkdf/g/eee9F8lqyDjFZlvSoxl//OsWedz4zn5/LL6lb0\nuedeNNMAhwNR0RwhpUxu76auPwOztNQKqPz+OmXDhNeHc9x4oq//h8Q332AfNAT3pKuJzZyJuX4d\ntuN6Yj9+IHJHEeE3XkfuKMJ+/CDsJ56E5q9Zj64u5DbP5uq3JhKPxLE5dLzZHkJlEY4b1YVFn/6C\nO8PF6LtOTcpRmKbJlt+2pVwjFo4TC8VquvwhSdm2cqY/NpvVP62jdb8WnPrnIWQ03PfX8lBAt2lk\nHCEiwJW1rtVp2fOYwzooVSh2hQrgFIc9MhRCBoOYxTvQ8hvUmJGrjnA6sfXqTWLuz1WD1WreAGR5\nOeGyMPGwqLJystst1wGvF/PcS4h480iENK753yV4st3YqmWTzPJyEr8tI/HrLziGn0ripx+TdXJa\n4yaI/HwCf7kOkZmJ+8pJ6G3b1bqhQNjtOPr3x9axE8baNWheDyIjE+fos8AwEH4/MhQk/OormCuW\nAxB9/13QBI4RpyNs+/5rv7PMhD/Xyzn/OIORtw9DCCtTV+k+oTtstBnQklU/rE3O9+V6DllR3Z0J\nFod4/br3WP3TOgC2rSpi28pCLnnu3Fp1GCsOHI07NKDn6C7M/3ApAM17NKXPuO5Jhw6F4khCSHl0\nGSD37t1bzp0792AvQ7GfMMNh4l/OrJL+sNnx3HQzerv2uxU5NctKic38nMTSJbjOu5DIG69hblif\nfFzv0ZP5juOY9tQP3DR9Eln5HmKzviI6ZTLyjzfy5iMLWPmD9YGe0yyLa9+5hMxGFVm3sCV1Ev96\nlnWttu1wTbwEY/16hNOJyM4h/MyTyMIKr067Hd/9D6FlZ+/z6yENA1lWRmLJIkgYaMccQ+TVlzE3\nb0Zr1AjPrbfvs4jv3lC8uZQpN3zAqh/X0bBdPpc+fy5CE2xdvp3GxzbAm+3G5a//JoRYOE5ZQTlz\n31+MP99H1+HH7tIlo5KSzaX8/fjH08bv+P7PZDU58K+lYvcES8LEglFMU+L0WBZrCsXhjBBinpSy\n987jKgOnOLwJh4m+927VcSJO5JWX8Nx6O2I3gYqWkYlz1Fk4hp2KcLnwXH8D0fffw1i1Ctm+E8Ee\ng5gx8R2igRjfvT6XM245GcfAQdi692DF0uJk8AaWLto3r8zhtBtPRLfryEiE+LdfJx83Vq4gePed\neP7vTmQoTOih+yFczaszHreyc/sjgCsuJnDX/yW3iEVuLu5J1xD6598Refn7Jfu2N2Q3yWTiM+Mw\n4gZC01gyfRnv3j41+fj4B0Zy3Oiu2J31u77CtUU8OvJFzITlP/vVM9/xpw/+sNstRFHRCBMNVG35\nOn0OhMrqHJJ4s9x460m+RqE4lFB/gRSHNTIeA9NMGTMLC9O6MmtC2Gxofj/CbkfLzsF14QQCZ1/O\nV+vzeGLC24RKrCArHo4jpSXeqzdsSOGGsrRrFawsJBEzql08Pfun+XzojRqht26d+oDNhvCmBhDS\nNDHDYeROz62SaChGqCRM9Qy6NAyin09Pqe+TRUUYq1aid+5iCfd66y8bsau1VuLN9pDRwI9pmHz8\nj89THvvw7zOSr3d9EQ3GmPHY7GTwBlC8qZT1C9O10KrjyXIz9p7Tkm+pEDDm7hH1pnGnUCgUtUFl\n4BR7xAwEkGVlmFu3oLdogfD6EPtBjHZ/IFxuRG4usqgoOWbr088SZ6sjps2Os1EebQYYdB3RmfWL\nN/PZw18y6JK+KbpYHYa2RWgCaVYFT/3G96iq6XK7sJ90MvHPZyQft598Cvh8aC437ksuI/ToI5ib\nN4Hbg/vyK1I02cyyMuJzfsRYshi9c1fs/QckHSNMw2THhhKmPfIVpZvLGHBhLzoMbWvVYkkJgUAN\nT8zAfcVVYBrIRGK/Z+HM8nKM338jsWA+etdu2Dp3RvNn7Hq+YRLbyR82Uh5NeT3rB4mRSL9Hpf3W\nrrA7bXQZ3oH/900Ltq8uIr9VLp5sV71nCxUKhWJ3qL9Ait1ihkLEpk8j9snH1oAQuP9yA7YuXVOc\nCQ4WIiMD7y23EXlzMsbGDdiO64njzFEQDhObNw/h8aK3br3Luq9QWZhQcZhAYRCX38mT414lXGrp\nuQ24sBc3Tr86zWDcl+9j0hsX8dE/PicajDHk8v607ts8+bjmcuMcORp7127Ely7B3qUrWstWaC4r\nY6Pl5eO55VarIaJSBqVC1FeGQkQmv05izk+ApRlnLP8d96V/QHi9BIqCPDbqRcJl1hrXzN3A+AdG\n0vucHmg2G45TRxD/4fuqDKTdjq1LNwK33YLQBM5x52Hv3QuxnwznzUiY6AfvJV0g4t9/h+3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wd/ZPTrg9g6f1f4e1dUDm8+RstBTcr5tP44THYT3W7rwOIpKwFtmtad72XUG0P56cX5eAu9NO5d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NSexam897uD/g41pXJ7pRBHcv5NBmXBPsVgfmsgrC6wRzZPlpAqL9UOmUXN5zndPrL/DWoemi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\nKaWUUhHm/wEeU5NfthsVoQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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dwZZzKDy0d9FRqGax1FSs53IkX/QiMu/cMbOIetvbFy2ivFgkt2c3hYd+CID1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\nhAozERERkZT4fyYXuRPgtif0AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 620.5x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j5e67HQtJz1G",
        "colab_type": "text"
      },
      "source": [
        "It appears that for non smokers, the increase of bmi does not really affect the increase of charges. However, for those who smoke, the increase of bmi indicates higher charges. That means, a smoker who is obese will have a really high amount of health insurance cost."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i_o-MQJPQmEY",
        "colab_type": "text"
      },
      "source": [
        "## Clean the data\n",
        "\n",
        "Checking the dataset whether is clean or not."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UKBu_VRVKUSE",
        "colab_type": "code",
        "outputId": "602c1f73-9eed-4205-b68c-049d9c5fb7df",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 162
        }
      },
      "source": [
        "dataset.isna().sum()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "age         0\n",
              "sex         0\n",
              "bmi         0\n",
              "children    0\n",
              "smoker      0\n",
              "region      0\n",
              "charges     0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LzSz-tvQQ9L7",
        "colab_type": "text"
      },
      "source": [
        "Convert categorical columns into numeric with the following convention:\n",
        "\n",
        "* `sex`: male = 1, female = 2,\n",
        "\n",
        "* `smoker`: yes = 1, no = 0,\n",
        "\n",
        "* `region`: northeast = $\\displaystyle\\frac{\\pi}{4}$, northwest = $\\displaystyle\\frac{3\\pi}{4}$, southwest = $\\displaystyle\\frac{5\\pi}{4}$, southeast = $\\displaystyle\\frac{7\\pi}{4}$. We use the representation of direction by their angle on unit circle. If we compute the method `.mean`, it will make a sense (where is the region whose citizens are the most recorded)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "epUomxKVQiJu",
        "colab_type": "code",
        "outputId": "335abec1-2f90-4be3-f54d-7d06f14b42e1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "source": [
        "dataset.loc[dataset['sex'] == 'male', 'sex'] = 1\n",
        "dataset.loc[dataset['sex'] == 'female', 'sex'] = 2\n",
        "\n",
        "dataset.loc[dataset['smoker'] == 'yes', 'smoker'] = 1\n",
        "dataset.loc[dataset['smoker'] == 'no', 'smoker'] = 0\n",
        "\n",
        "dataset.loc[dataset['region'] == 'northeast', 'region'] = np.pi/4\n",
        "dataset.loc[dataset['region'] == 'northwest', 'region'] = 3*np.pi/4\n",
        "dataset.loc[dataset['region'] == 'southwest', 'region'] = 5*np.pi/4\n",
        "dataset.loc[dataset['region'] == 'southeast', 'region'] = 7*np.pi/4\n",
        "\n",
        "dataset['region'] = pd.to_numeric(dataset['region'])\n",
        "\n",
        "dataset"
      ],
      "execution_count": 0,
      "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>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>bmi</th>\n",
              "      <th>children</th>\n",
              "      <th>smoker</th>\n",
              "      <th>region</th>\n",
              "      <th>charges</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>19</td>\n",
              "      <td>2</td>\n",
              "      <td>27.900</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3.926991</td>\n",
              "      <td>16884.92400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>18</td>\n",
              "      <td>1</td>\n",
              "      <td>33.770</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5.497787</td>\n",
              "      <td>1725.55230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>33.000</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>5.497787</td>\n",
              "      <td>4449.46200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>33</td>\n",
              "      <td>1</td>\n",
              "      <td>22.705</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2.356194</td>\n",
              "      <td>21984.47061</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>32</td>\n",
              "      <td>1</td>\n",
              "      <td>28.880</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2.356194</td>\n",
              "      <td>3866.85520</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1333</th>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>30.970</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2.356194</td>\n",
              "      <td>10600.54830</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1334</th>\n",
              "      <td>18</td>\n",
              "      <td>2</td>\n",
              "      <td>31.920</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.785398</td>\n",
              "      <td>2205.98080</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1335</th>\n",
              "      <td>18</td>\n",
              "      <td>2</td>\n",
              "      <td>36.850</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>5.497787</td>\n",
              "      <td>1629.83350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1336</th>\n",
              "      <td>21</td>\n",
              "      <td>2</td>\n",
              "      <td>25.800</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3.926991</td>\n",
              "      <td>2007.94500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1337</th>\n",
              "      <td>61</td>\n",
              "      <td>2</td>\n",
              "      <td>29.070</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2.356194</td>\n",
              "      <td>29141.36030</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1338 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      age  sex     bmi  children  smoker    region      charges\n",
              "0      19    2  27.900         0       1  3.926991  16884.92400\n",
              "1      18    1  33.770         1       0  5.497787   1725.55230\n",
              "2      28    1  33.000         3       0  5.497787   4449.46200\n",
              "3      33    1  22.705         0       0  2.356194  21984.47061\n",
              "4      32    1  28.880         0       0  2.356194   3866.85520\n",
              "...   ...  ...     ...       ...     ...       ...          ...\n",
              "1333   50    1  30.970         3       0  2.356194  10600.54830\n",
              "1334   18    2  31.920         0       0  0.785398   2205.98080\n",
              "1335   18    2  36.850         0       0  5.497787   1629.83350\n",
              "1336   21    2  25.800         0       0  3.926991   2007.94500\n",
              "1337   61    2  29.070         0       1  2.356194  29141.36030\n",
              "\n",
              "[1338 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1k5TfULDV6f4",
        "colab_type": "text"
      },
      "source": [
        "## Split the data into a training set and a test set."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2YLF4K7CVUQ-",
        "colab_type": "code",
        "outputId": "daa5e3ea-edab-499b-bfa4-e434c0a5f21e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "train_dataset = dataset.sample(frac=0.8, random_state=2020)\n",
        "test_dataset = dataset.drop(train_dataset.index)\n",
        "\n",
        "N_train = len(train_dataset)\n",
        "N_test = len(test_dataset)\n",
        "print('N_train:', N_train)\n",
        "print('N_test:', N_test)\n",
        "print('N_train/N_dataset:', N_train/len(dataset))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "N_train: 1070\n",
            "N_test: 268\n",
            "N_train/N_dataset: 0.7997010463378177\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZwYyBYWEW7eU",
        "colab_type": "text"
      },
      "source": [
        "## Inspect the data\n",
        "\n",
        "We look at the joint distribution of a few pairs of columns from the training set. The diagonal elements represent kerned density estimation (kde) for univariate variables for given columns. We include all the columns to inspect which variable has a correlation to another variable"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iK4789xEWxtj",
        "colab_type": "code",
        "outputId": "24d1b8cd-3f4e-4eca-b043-825286b2abdd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "sns.pairplot(train_dataset[['age', 'sex', 'bmi', 'children', 'smoker', \n",
        "                            'region', 'charges']], \n",
        "             diag_kind='kde', height=2);"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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TnRlCgGfnFKDGKygueS6HqdvvaGm5swPQ/JtfEPHMvlNYPTNfGWD3FJdi3dzR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64y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Bk0BVx29nDU7T+MO/74GV6++TyMKsudrQ+J4rLZr9+X9FUlHhk/u2BM3IRjSXda2eNht21N\n1fSEzs+EVLD2UXmZ9a5SRAG6zmPGEEtmVSdl5ZVIPU53QDnnlumkeRJU8zRuHTWbqPDo8ZBTkGkh\nFzF8nImVxbj/0vH4n3Z/zPtnyawalObLeObjvVj2t32mHzOk0GVmPTN0AeyExnUOy2c1vNiDj+/+\nblIWJzNycjcN0JsjSRiDiGgqSjzY/nUHPqs/gnnPxs4+LXi2DnmKiGZfEEcDqun4G5/PW7UJWndH\niF7xX7vwXKxZcK4ZthI9s2W15ybVqphWiv8jS/PijpE6Z++ENR23rN6CuSs3mvuablm9BeEEB9JO\nhdtEzDhkTJR0dn7dgc8ajuA7Y8pzVvRQFgXcdsEYAMDVT23AlgNtaa5R5qHbhLL2xZk47A9ZCs4e\n9ocSOt9IXxaNIeyUKL1lkxkIrN5fmfiuCqp63Bjhpuc3I6hm9/shWzDC5qNJVtj8QKBzWKaTTsZ7\nWtdtxgBJGgS4bbRJ3H3QtSKO+TgLp4xCW2c47v1z0/N1OHDYj2V/22cem7dqE1SdmzZ26Qe7sWhG\nlblAGI2x5cvKHg8tdJ/QO8LOL8u0yd10QCv/ScIYRESHMD40vQqPvL0T9/xwnPXsk6bjoelVcEmC\n5eecc7PMniv+RgeIntmKniQ4fWgBPIqU8pUUu9UbAGld0XEamSB+lQ4o1V8sL/zjACSB4ZunDU53\nVdLK0CI37v3R6XjknZ2YvmQ9Zk8eiTu+PxZFeYmtSmc7ybAXgbD1qoiR5vV4uCQBi2dVm+lnjVS2\nyRLqGggyIfogEVSblWM1V2dJHUZZvstyW19ZvjNCj1MpSGyvPdLvogFEFPlL810xUZWl+a6sU+RP\nNaVeBcvm1MAf0o6bXjz6WFjVY2ysRxHBwbFsdg0WRPUHY8vXYK8rafbYyi/LxMnddEDOfxIw9ucP\nypPNdHrbv+4wRffsUmAUuCT87r+/xJ0/GGcbejh2iKfXjtAzbNGYJBjIPS122wZyfU9NX8gE8at0\nkOo0P06irTOElzbW49xTS1GYYOh1NlM5KA+/vfwsrNlUj+c27Mdrn/0Pbv/eGMyePLJPq8vZiMvG\nXrj6YC/s+l6iW244GN747CBWXH8ORIFB0znWbjqAn3z7tITrkAk4QbBLotBlRyNJAsYNKTDHh5Io\noDzfBckhE2WiTftLhh1Ohi3rjf7qWhERBIFhTFk+mnxBfNnos3xmXT1U+A0/xsrGlnjsnfxk2WOn\nTO6mA2dYngwmOlXQN/7fe7hy2SfoCKpYV1ePLfXtAGCGuvQMZRle5MFvLq9CoVvCsjk1lqGHxwuL\ndErYItE7gzwKls6ObQNLZ9dgUJbPTntdIhb3SPOzeFY1vK7cC8v6w8d74Q9ruGTC8HRXJWPwuiTM\nPf8U/PbyszCi2IP7X/sCVy37BA1tuZ0KMBn2wqOIce+lvqR5LfUq+JfqSsxduRFTH/0r5q7ciH+p\nrqR3Twoo8IhY0uN5L5ldgwJP7tlJpyJJgplueXixxzGOPwDku63bX767/+3PEP7sOYZNpvBnurcX\nZQO6zvFVSyd+9acvUOKV494dT82pwcjSvIR9kYF6JvTsrWHJEOxwErW1tXzTpk1JK6+5I4jLF38c\nNwO2+iffMHNUVpR4sOqGSch3SwiruuXskxE9cCKzU/05N8vp101IdlvpjeaOIO59ZWuc4u1vLq/K\n+FWp/qDrHAfbuxBUuZnmxyUxjCjOG+g2fMI/lox20nQ0gO8s+gBnVxbjZxeM7ldZ2QrnHB991YIV\nH++DJDI8fvVEfHdcWjIipLWtAMmxF7rOsa+1MyYLzcjSvD7lqaZ3z3FJSltp6gjg6Q93Y0btSTFR\nFjd+exTKC9xJqyyRNjJ6rNLUEcC/vfLPeEX+y89KSvsjO9In0tJWon2diZXFuGvaWAwtcoMxBpEx\nDOvejkzPMaOwvfkU9t9P7NQkRYH1KdSkP6GHTghbJHonpGp4Z1sT3tnWFHP8/kuyW5VUECKOfq6/\nMH71+jaENR1XnVOZ7qpkLIwxfGt0GcYOKcB/vLsLN6zciJ//YCxunjIq58QRk2EvkhEOS++egSGs\n6lj2t32mmJbBteedkp4KETlFWNVt7E1yBCfJjmQ+PfXFrln+dwDAh3d9FyOKPUkP2SdSi3PijjKU\n3tQkKdSESJRcViXN9bCsVz89iDe2HsLlE0dgSCGt4h2P8kI37r9kPM4dVYpFb+/Erau3oCukprta\nA0qy7EWu9z2nkMvvByL9UPsj7NqARxbpveFAyPnvJ7TnnkgG1I5yk7r9bbhn3T8xbmgBLj2b9von\niksScet3T8PMSSfhz/88hAsf+xDv72g6/olZAtmL3IKeN5FOqP0R1AayCwr77yekJkkkA2pHucfb\nX3yN/73mUxR5ZNx2wWhIAs3F9gXGGC6ZMByjyvPxh4/2Yu7KjThzeCGm11SgZmQJxgwpgFvOzpUp\nshe5BT1vIp1Q+yOoDWQX5PwnAdqvRCQDakfZz9FAGJ/sbsVL/ziA93Y249TBXtxx4VgU59Hs+Yky\nflghHvzxWXhvZxPe39GEX/1pm/lZSZ6MYcUeDC/yYESxG8OKPRhW5Mbw7v8OKXRDFp056UL2Ireg\n502kE2p/BLWB7IGcf4IgiCSz5IPdqNvfhpCmI6RqCIR1NB4NoPFoADoHCt0SrjqnEhedNcyxzmcm\nIYkCLhw/FBeOH4rGowHsa+nEwXY/DneG0NoZws6vj2L97pa4PMQMwCCvgrICF7wuCW5ZgEsSIYsM\nY4YU4I4Lx6bnggiCIAiCIFJAzqX6Y4w1A9g/QD83GEDLAP1WJv5+uuvQwjmfdqInD3BbiSad9yxX\nf/uE20qO2ZT+kg3135FhbSUT7mm665Du37erQyrsSiZcayrJxetL51glE+831cmedLWVTLn+aDKt\nTplWH9u2knPO/0DCGNvEOa/N1d/PlDo4jXTes1z9bafg9HtE9U8+mVCndNch3b8/kHXIhGtNJXR9\nA0um1QegOmUimXj9mVanTKtPb1C8KUEQBEEQBEEQBEFkOeT8EwRBEARBEARBEESWQ85/ankqx38f\nyIw6OI103rNc/W2n4PR7RPVPPplQp3TXId2/DwxcHTLhWlMJXd/Akmn1AahOmUgmXn+m1SnT6mML\n7fknCIIgCIIgCIIgiCyHVv4JgiAIgiAIgiAIIssh558gCIIgCIIgCIIgshxy/gmCIAiCIAiCIAgi\nyyHnnyAIgiAIgiAIgiCynJxz/qdNm8YB0L/c+NcvqK3k1L8ThtpJzv07Yait5Ny/E4baSk796xfU\nVnLqX7+gtpJT/2zJOee/paUl3VUgHAK1FSIRqJ0QiUJthUgUaitEolBbIRKF2goBAFK6K9BfGGP7\nAHQA0AConPPa9NaIIAiCIAiCIAiCIDILxzv/3XyXc5726Sxd52jtDCGkamCMQWSAIAgo9SoQBGb5\nPUUSUepVAKDXY25FQCjMEdJ0yKKA8nwXJCk+cENVdTT5ggh3fy9PEdAZ1OBRRKg6R1jVoUgiSjwy\n2vzhmN8TBJZw3aKvh0gOgYCKVn8Iqs4hCQylHgVud7Z0UXuCQRUtXceue3CeApcr+6+7N6z6YSJ9\nTtc52vxB+EM6dJ1DFBgkgVnaoWhbIQkMssQQVjk8iohiT2y/lyUBksAQVnVoHOCcJ8UWJHqdJ3o/\nCCJbyNX3Q7bgdBsWDmto8gXN9lee74Isi+muVkKksu/k8vhF1zlafEEEwhrcsghV0xHWOdySADCG\noKpBYAxuSUBY49A4h9DtG8mSEOOT9OaDOKmfOIXcaKEDgK5z7GzswLxVm9DQ5kdFiQcPTa/CM+v3\n4vbvj8XYIQVmw+75vVU3TEJQ1W2PleW7cNe0sbhz7Vbz86WzazBuSEHMBICq6tjR2IGFz9WZ31s8\nqxp/3dGE2lMGxZ3/+Ltf4p1tTago8WD5tbUYXZaPXc2+mHosv7YWLknAtX/4R8wx43qI5BAIqNjV\n2ombop7dktk1GF3qzeoBXjCo4suW+OseM9ibMy/QnljZiET6nK5z7GvtROPRQExft7JDdrbijc8O\nYsq4Iago8cAX1GLq8OTMiQiEddzxx8+SYgsSvc4TvR8EkS3k6vshW3C6DQuHNexo8sW1v3Hl+Rk/\nAZDKvpPL4xdd59j5dQfmPRvro1j5K4tnVeOJ93aZ/sajV0yAWxZwy+otMf3BzgdxSj9xEtmw558D\neIcxVscYm5+uSrR2hswGCwANbX7cvW4rptdUYt6qTWjtDNl+b39rV6/HFk4ZZXYk4/OFz9WhyReM\nqUOTL2gO5o3v3fz8ZlxWXWF5/vSaSvPveas2ockXjKvHvFWbsL+1K+6YcT1Ecmj1h8wXCBC5zzc9\nV4dWf3bf55Yu6+tu6cru6+4NKxuRSJ9r7Qxhf2tXXF+3skN2tmJG7Um4c+1WBFUeV4fDnWHT8e9L\nvfp7nSd6P3KB5o4g1tY1YG9LZ7qrQqSQXH0/ZAtOt2FNvqBl++s5Bs1EUtl3cnn80toZwrxn430U\nK3/l5uc3x/gbd/zxMxzuDMf1BzsfxCn9xElkg/P/Tc55NYAfAriFMfbtnl9gjM1njG1ijG1qbm5O\nSSVCqmY2WIOGNj+KPTIa2vwIqZrt9/IUsddjRhk9y1Y1PeZYWNMtv8c5t61b9N925+cpYtwx43qy\njYFoK1aouvUzUvV+i7tmNE697lS2Eztbcrw+F1I1S1tiZYfs+rooMDS0+SEwJGSn+mMLEr3OE70f\nmUIq28rNz9fh53/8DL967YuklkukB7u24lQ7SURIhQ0byLGKk9tfKuvulPuSirYS3aajfRQ7f6Wn\nv2HlV9iNS5zyrncSjnf+OecHu//bBOAVAJMsvvMU57yWc15bVlaWknookoiKEk/MsYoSD9r9YVSU\neKBIou33ukJar8eMMnqWLYmxj08WBcvvMcZs6xb9t935XSEt7phxPdnGQLQVKyTB+hlJWR7q5NTr\nTmU7sbMlx+tziiRa2hIrO2TX1zWdo6LEA50jITvVH1uQ6HWe6P3IFFLVVrpCKrYcaAcAbNjTikCY\nBkhOx66tONVOEhFSYcMGcqzi5PaXyro75b6koq1Et+loH8XOX+npb1j5FXbjEqe8652Eo51/xpiX\nMVZg/D+ACwF8no66lHoVLL+21my4xl7bdXX1WH5trSmcZ/W9kaV5vR5b+sFuLJpRFfP50tk1KM93\nxdShPN+FpbNrYr63eFY1Xt3cYHn+urp68+/l19aiPN8VV4/l19ZiZGle3DHjeojkUOpRsKTHs1sy\nuwalnuy+z4PzrK97cF52X3dvWNmIRPpcqVfByNK8uL5uZYfsbMXaTQewaEYVXBKLq8Mgr4xHr5iQ\nNFuQ6HWe6P3Idj490A5V5/jBGUMRUHVs3Hc43VUiUkSuvh+yBafbsPJ8l2X76zkGzURS2XdyefxS\n6lWwfE68j2LlryyeVR3jbzx6xQQM8spx/cHOB3FKP3ESjPPMCk/pC4yxUxFZ7Qci4oWrOee/6e2c\n2tpavmnTppTUZyDU/sOaDikBtX+1+3s5rvbfr0qmsq1YkatqzhmilnvCbSUV7WQg1f5VTYcoMMiS\ngLCqk9r/8cmItvLYX77E79/bhSdnVuPWF7Zg4XdOxZ0/GJeUsomkkbS2kqvvh2zhODYs48cqpPZv\nTRrGLxnTVky1f1WDWzq+2r/Ouekbkdr/gGB74xz95uCc7wEwId31MBAEhrKC48+E2n0v0WO9IUkC\nhhfHhs0U51l/16rsvtSNSC5ut4QROTiYc7kkjMhyZdy+kqgtsTqv1OsGvMf/rpWt6Emq+31/bWYu\n88X/HMWIYg+K8xSUF7iwr6Ur3VUiUkiuvh+yBafbMFkWMaLEZjCZ4aSy7+Ty+EUQGMoL3Ukv08n9\nxCk4OuyfIAiCIHKR+sNdKCuIDLyGFLpJ8Z8gCIIgiONCzj9BEARBOAjOOerbulBeGFkhGVroxr7W\nTjh5Gx9BEARBEKmHnH+CIAiCcBBtXWF0hTSUd4dHDi1yoyukodkBebcJgiAIgkgf5PwTBEEQhIOo\nPxzZ32/sjRzSve+S9v0TBEEQBNEb5PwTBEEQhIM40O38l3fv+R9W1O38t9K+f4IgCIIg7CHnnyAI\ngiAcRH2b4fxHVv4HdadkbTwSSFudCIIgCILIfMj5JwiCIAgH0XgkAK9LhLs7z7YsCihwS/j6KDn/\nBEEQBEHYQ84/QRAEQTiIZl8QJXlKzLFBXgWNR0nwjyAIgiAIe8j5JwiCIAgH0dwRRKFbjjlW7JHx\n9VF/mmpEEARBEIQTIOefIAiCIBxEc0cQRXmxzv8gr4LGI7TyTxAEQRCEPeT8EwRBEISDaPYFUeyJ\ndf5L8hS0+IJQNT1NtSIIgiAIItMh558gCIIgHEJXSEVnUIt3/r0KOCITAwRBEARBEFaQ808QBEEQ\nDqGlIwQAKOoh+GcIAJLoH0EQBEEQdpDzTxAEQRAOodkXSefXc+W/uFsDoJHS/REEQRAEYQM5/wRB\nEAThEJo7Iiv7xXnxav8A0OoLDXidCIIgCIJwBlnh/DPGRMbYFsbY6+muC0EQBEGkiuZu576wx8p/\noen8U9g/QRAEQRDWSOmuQJK4DcB2AIXp+HFd52jtDCGkalAkEaXeyN5Lu2O6rkPjgM45BMYgMkAQ\nBJR6FQgCS7hsoxyRARoHOOfwKCI45/CHdWg6hyIKKMt3QZLs53mM32Dg0HSOsM6h6xySKJhl29XR\nqn49r4FIjEBARas/BFXnkASGUo8Ctztbuqg9uXrdqSK6T3oUEarOEVb1mP6pqjqafEGENR2KKEBg\nQEDV4ZYEgDEEVQ0iY/AoIoo9kXNCIRXNnceeU75bgFdW0OYP99r/e9qIEo+Mo8Ew/CENGudwyyIG\ne11kNxKkrTPi/Bf06COyKMCriGgh5z8rITvpbMJhDU2+oPn8yvNdkGUx3dVKmFS2v57vljKvAkVJ\nXtsOBlW0dB0rf3CeApfLGXXPZKLHEbIoYHCejPaAipAW8T88sohit4SWrjDCmg5RYFAEBkli0HRm\n+jMtnUEEwhokxiCJAkKabvpGsiTEjGFKPPJxxxwnSi75M45voYyxCgAXAfgNgP890L+v6xw7Gzsw\nb9UmNLT5UVHiwaobJiGo6jHHll9bm0SyDQAAIABJREFUC5ck4ME3t+O6807B3eu2mp89NL0Kz6zf\ni9u/PxZjhxSYjc2q7J7lPLN+r1leWb4Lv/6XM3A0oOLOtcfKXzq7BuOGFFhOABi/8V+b6zG9thKt\nvlDMuUbdjN+KrqNd/aKvgUiMQEDFrtZO3PRcnXkvl8yuwehSb1YP8HL1ulNFdJ8sy3fhrmljY/rz\n8mtrcdpgL3Y2+bAw6p4vmlGFVzYfxOXVI2K+v2hGFYYUujGi0I0vW+KfU5FHw8zlf7ft/z1txIXj\ny3HXtHFo7gjG1YvsRmIc7gzBq4iQhHh7XuSR0UJh/1kH2UlnEw5r2NHki3t+48rzHTEBkMr2Fwqp\n2NkcX/bYMm9SnOhgULV8d40Z7O33BECq657JqKqOHY0dMeOIFXPPQXtnCLev+Szmfvz+3S/xzrYm\nc0xRVuDCR1824dtjhyAY1jHv2U0xY46H39qJZl8QT8yciLCqx5S3dHYNHo8qL1ljh1zzZ7Ih7P8/\nANwFIC3JjVs7Q2ZjAYCGNj/2t3bFHZu3ahP2t3Zhek2l6fgbn929bium11Ri3qpNaO0M9Vp2z3Ki\ny1s4ZRSaOo4578Y5C5+rQ5PNapDxGzNqT8LBtkDcudG/0bOOdvWLvgYiMVr9IfMFAkTu5U3P1aHV\nn933MlevO1VE98mFU0bF9ed5qzahyRc0X9jG8TvXbsW8b58a9/07127F/tYutHRZP6eQynvt/z1t\nxPSaStQf9lvWi+xGYrR1hVDgli0/K/DItPKfhZCddDZNvqDl87Mbl2UaqWx/zZ3WZTcn6X1g9+5q\n6cr8umcyVuOIhsN+01E3jt30XB2m11Saf9+5divqD/sxdfywiK/07Ka4McfCKaPQ0OZHW2c4rryF\nPcpL1tgh1/wZRzv/jLGLATRxzuuO8735jLFNjLFNzc3NSa1DSNXMxmKQp4hxxxra/MhTRBR7ZMvP\njOMhVeu17J7lRJdX7JFtf1vVrOdGjN8QBWZ7bs/fMupoV7/oa3AaqWwrvaHq3Pq56XzA6pAOnHrd\n6WonxyO6T9rZGrt7LgrM1t7YndNzQvx4Nqw3G+Vku9EbyW4rhztDyLdZbSvyyGh2iENBxGPXVpxq\nJ4kIqXh+A/kOSmX7S3XbdnLdk0Uq2kpY0xP2faIz0xhjCs75cb+faHnJGDtkoz/TG452/gGcD+BS\nxtg+AC8CmMoYe67nlzjnT3HOaznntWVlZUmtgCKJqCjxxBzrCmlxxypKPOgKaWj3hy0/M44r0rEQ\nMKuye5YTXV67P2z725Jo/aiN39B0bntuz98y6mhXv+hrcBqpbCu9IQnM+rllYbhRNE697nS1k+MR\n3SftbI3dPdd0bmtv7M7pOcY5ng3rzUY52W70RrLbSltXCPk24apFHpnU/h2MXVtxqp0kIqTi+Q3k\nOyiV7S/VbdvJdU8WqWgrsigk7Pu0+8Mxf3eFNDDGjvv9RMtLxtghG/2Z3nC08885/1fOeQXn/GQA\nVwN4j3M+eyDrUOpVsPzaWrPRVJR4MLI0L+7Y8mtrMbI0D+vq6vHQ9KqYzx6aXoV1dfVYfm2tKYBh\nV3bPcqLLW/rBbpQXKFg0I7b8pbNrUJ7v6rX+azcdwIgSd9y50b/Rs4529Yu+BiIxSj0KlsyuibmX\nS2bXoNST3fcyV687VUT3yaUf7I7rz8uvrUV5vgtLe9zzRTOqsPzDPXHfXzSjCiNL8zA4z/o5KRLr\ntf/3tBHr6upROchjWS+yG4lxuDMUJ/ZnUOiWccQfEVcisgeyk86mPN9l+fzsxmWZRirbX5nXuuyy\nJL0P7N5dg/Myv+6ZjNU4omKQB49dOSHufqyrqzf/XjSjCpWDPHhv26GIrzSnNm7MsfSD3ago8aDE\nK8eVt7RHeckaO+SaP8M4z6zwlBOFMTYFwM855xf39r3a2lq+adOmpP72iar9c87BUqj2r+sc8omq\n/XMOSXC82n+/KpKKttIbuarmnCHXfcJtZaDbyfHoi9q/2q3SG6/2r0NkGAC1f8AtC05T+09rWzn9\nF2/hu2PLMWfyyLjP/rKtEX/4eC82/OsFGFrk7tfvEEkhaW0lQ+wkcYIcR+0/48cqpPZvTRrU/jOm\nrUSPI6Qeav+6Hsnkk7javw6JAZIoIKzppm9Eav/9wrbyWfPm4Jx/AOCDdPy2IDCUFcTP4CZ6LFll\nnyh2v5Hqc4lY3G4JI3JwMJer150qEumTkiRgeLGn1+/0RFEkjLAY1Bzvt6zqM0hyAd4+/TwBIBDW\n4A9ptiv/Rd17IVt8QXL+swyyk85GlkWMKMlLdzVOmFS2P7t3S7JwuSSMSJKz35NU1z2TsRpHlFvc\ni+HHuT/lBX17V6XK58glf8bRYf8EQRAEkSu0dStUJ+L8EwRBEARB9IScf4IgCIJwAIe70w4VuqxT\n/RnOP4n+EQRBEARhBTn/BEEQBOEA2jojKsd2qf4KPZHjtPJPEARBEIQV5PwTBEEQhANo90dW9O1S\n/XlkEYoooLWTVv4JgiAIgoiHnH+CIAiCcADtXb2v/DPGUJQno6WDVv4JgiAIgoiHnH+CIAiCcABH\n/BHn39uLenKhW0Izhf0TBEEQBGEBOf8EQRAE4QDau0JwSQIUyf7VXeSRSfCPIAiCIAhLyPknCIIg\nCAfQ3hW23e9vUOiWSfCPIAiCIAhLyPknCIIgCAfQ7g/b7vc3KMqTcbgzBF3nA1QrgiAIgiCcAjn/\nBEEQBOEA2rtCyFPEXr9T5JGh6tzUByAIgiAIgjAg558gCIIgHMARf2Jh/wAo9J8gCIIgiDjI+ScI\ngiAIB5DInv8ij+H8k+gfQRAEQRCxkPNPEARBEA7giD8Mb8LOP638EwRBEAQRS++jiAGEMeYCMB3A\nyYiqF+f8/6arTgRBEASRCQTCGoKqnvDKfys5/wRBEARB9CBjnH8ArwI4AqAOAI1aCIIgCKKb9q6I\ngN/xnP98twSBUdg/QRAEQRDxZJLzX8E5n9aXExhjbgAfAnAhci1rOef3p6JyvaGqOpp8QaiaDlFg\nEAUGzgGBAUwAwiqHqnPIAoMkMKicg3NA5xwuSYSq6QADOAc0nUPs/l5Q1eGSBGgcCGs6JIFBEACR\nCVA1HWGdR44xgINBYoBf1eGWBGicQ9UiZQkMEBiDqh+rR55LQEgFQpoOrfuYSxYQCOsxddU4h95d\nL0WK7BIJqpHrlAVmXp+mc0iigPJ8F3RdR3NnCGp3/dyygJCmQ9ePXZ9bFqBqHIIgoNSrQBDYQD+2\njCMQUNHqP3bfSj0K3MdJ65UN5Op1J4JpW3QdImNgDBAZg95tE0QhckzngNRteyQB6ApF+rFbEsAY\nM/u5RxGhaty0J7LIoOmAyICAqkPo7vcMgCwxcD1y3Hg2HkVAIBSxPW5JgA4g1G0P8l0CuoKRz0SB\nQREF6JwjqOqQu88Na0BQ1SAwBlliAGcIa902RxQgCZG/FUmMsQu6ztHaGUJI1eI+yxXa/RFn/njO\nv8AYCj0yhf1nGWQnnY3Tn18q65/qe+Pkumcius7hC4UQVjlCGkeo21fROaBqkXGE3O0/MER8kICq\nI98lmj6GMf5QtYjvEAhrZhk9xzaKKGBQngJJEqDrHM2+IIJhLeKHiAxhjUPnHAJj8LpEhFQeM85Q\nNYBzDkUSUeKR0eYPI6RqkKXImMMf0sAYgyQCXAfCOjf9IsM3c0kCOBiKXCJausJmHRVRMH2wExmX\npGtsk0ktdD1j7CzO+T/7cE4QwFTOuY8xJgP4iDH2Jud8Q4rqGIeq6tjR2IGFz9Whoc2PihIPHppe\nhWfW78VtF4yGzoGbnt9sfvbYlRMgSwJuXb0FZfku3DVtLFZ8vBfXnXcK7l631fzeohlVeGXzQVxe\nPQJ3rj12/NErJsAtC7hl9Za435t7/ikJnXPh+HLcOW0cWjqCMd9bOrsGj7/7Jd7Z1mRb1+jvP3bl\nBBTlybhh5Sbz2LI5NVAkAXNXbDSPLZlVDSD2PiyeVQ1FYvj3d77E7d8fi7FDCnJuMB9NIKBiV2sn\nbopqR0tm12B0qTerXyS5et2JYGVbnpg5EWFVx+1rPrPs/yNKPDjqV7HwuTqU5bvwy0vHoyuk4c61\nWy378OJZ1Xjjs4OYMm4IHn5rJ5p9QSyaUYU8RURZoQutHaGYfrtkdg1e/7QB/9jXHlPWhePL8dML\nxsQ8R6OcX762Dc2+YJx9+cP1tTjSFY65lseunIDf/nkHmn1BLL+2FmOHFAAAdjZ2YN6qY3bG+CyX\nbIax8n+8Pf8AUOyRaeU/iyA76Wyc/vxSWf9U3xsn1z0T0XWOls4AAmEdHX4VC7rHGj3HFotmVMGj\niFj8/ldY8J1RWL+rBd8ZV46be/gBxvjjlc0HcdWkStz24qeWY5ujBS6MLMnDV80+zHu2LqaMJ97b\nhXe2NUXGIVNHm2OWC8eX49apo2N+s+c4ZNGMKjz81k6UFSj4+Q/GotUXivOfnv5oD26dOhr7Wzpw\nSllhzJhs0YwqDM5XsPb/s/fu0XFUV77/95yqru5WS7ZasmTAkvzCmHiCZKsFZEiGEHIvIRmSzIyE\nB7Agw80lsZ0wGX5chztzZ92Z3/3dmzXEw/UQwDJ48iJ2HkbKJDMZkiHhGSAPJIFNYvwAGywZY8lS\ny9ajW9VVdX5/dFepuru61ZK61dXS/qylJfWp89jn1D679u6q2uruw58018/ILzEMUTTfxk0J/z4E\noIcxdpQxdogx9jpj7FC2BiLOWOKjJ/EjCi2onYGxSUsRAKA/HMF9XYfQGqrHgM1xNo/dc+AgwuMx\n9Icj2HrdWuzojNc1A3+z3o7OQ7jr2jWWEprl9z5xEMOJ9qnj5dqmNVSP/uFIWr2t+3rQGqrPKmvq\nXE6Ho0lln/9OD/qHI0ll2/b34tyYmlS2fX8vZC6hNVSPux7vxtD44nZUhyKqdQEBEuu2rwdDkYW9\nLot13rngZFvC41PBsllm3/+qJqw2W69bi+HxmLVvnfbw9v29aGtpwI7OQ9h63VrL9gyPx6DrSLNf\n2/b1oK2lIa2v1lB92nk0+zH7TbUvp8PRtLncc+CgVd+0C0PjqnVxNOstRpthPfafg1NZ4aM7/wsJ\nspOlTamfv0LKX+i1KWXZ3Uj8LrWAqgl83uZrpPoWOzoPITweQ2soHtB/urnOCsLNOnb/465r11iB\nv3nc7tv0DUcwMDZpBf72Pky/ojVUn+SztIbq08ZM9UNM36c1VI/T4ahj/GT2s2lldZpPFq8fRVtL\nw4z9kmL6Nm76aurjs2nEGJMQzxNwKYBHhBC/cajzOQCfA4CGhoa5yJhGTDesE2fSH46gMpF0yelY\nmSIBiN+dMes61ZM4y9o+dbxc22STzTyWSdZcZMm1jLOpflVNhxsopK5kQzOE4/pqxrx+lzXvlOq8\n50NPnGxLmSJl3LfmnjKPp+7z6eyMvX6ZIkEXzudG4iytr2z2oQxSkpy5zMX827QLTvXcYjOmI1+6\ncj7Hx/4BYInfg1ND47MeiygOmXSlVO0kEacQ528+fZVC6l+hdbuUZc8X+dQVVdOhGyLN18h2/e8P\nRyCy+BPZYhez7zJFyrjeps+Qq1+SGuekfs4kg55h/DJFsuSfiV+ianrRfBvX3PkXQrwDoB7xx/jf\nATCBHOQTQuhCiI0A6gBcxRh7v0Odx4QQLUKIlpqamrzK7ZE46oL+pLK6oB8jkRgmVN3x2IQaP7Ej\nkZhV16mebois7VPHy7VNNtlGIrGssuYiS65lhpjqV5GTvxwoFoXUlWzInDmur7zAH2su1XnPh544\n2ZZs+9bcU+bx1H0+nZ0x9765XyXmfG50Q6T1lc0+2Pu125fpbJBpFxRZcqznFpsxHfnSlVwT/gHx\njP/02H/pkUlXStVOEnEKcf7m01cppP4VWrdLWfZ8kU9dUeR4oJvqa2S7/tcF/WBZ/IlssYvZfkLV\nM6636TPk6pekxjkjkdi0cVFd0A8pw/gTqm7JPxO/pJi+jWuCf8bY3wG4D8BfJ4o8APbl2l4IMQLg\nWQAzSho4V2rLvdjTHrJOoPmeSldPH2orFHRsaU46tmtzE4IBT/zdk+fews62eN37WxuT6u1sa8Te\nF05gZ1ty+QM3N6Eq0T51vFzbdPX0oa7Kn1ZvT3sIXT19WWVNncuKoC+p7NHbQ6ir8ieVdWxpxrJy\nJals95ZmaIaOrp4+7L2jBdUBpYBnyf1U+xV0pOhRR3sI1f6FvS6Ldd654GRbggEPdm1uyrj/FZlZ\nbfY89xaqAh5r3zrt4d1bmtHZfQo72xqx57m3LNtTFfBAkpBmvzraQ+jsPpXWV1dPX9p5NPsx+021\nLyuCvrS57NrcZNU37UJ1QMHeO1qS6i1GmzESiUHmDF55+sv2Up+MSEzH+KQ2D5IRhYbsZGlT6uev\nkPIXem1KWXY3Uh1QoMgMiszwqM3XSPUtdrY1IhjwoKunDw/eshE/7u3H7hR/wu5/7H3hBB68ZWNG\n36a+yo/aci/23h5K68P0K7p6+pJ8lq6evrQxU/0Q0/fp6unDiqDPMX4y+3n1naE0nyxe34fO7lMz\n9kuK6dswIdzxeApj7DUAmwD0CiE2JcoOCSEas7SpARATQowwxvwAngJwvxDiJ5natLS0iO7u7rzK\nnprtX058KzarbP9CQGLp2f7Nvu3Z/rVEVm3OASGyZPvnAEfmbP9GIvNmrtn+VW0qm6fLs/3PqdNC\n6Eo2FmPWWMA18561rhRST3LJ9s8ZoOeQ7d8wBHwFyPYfS7TLlO1f1QyrbTzbvwHOAI/MgcQ8TPtR\nItn+i6Irf/Mvr+PfD53BnvbQtHWfPzaAPc+fwAs7PoKG6rJZjUfkhbzpikvsJDFLpjl/rvdVSjlj\nfinL7kDRdSU1239MM6A4ZPs3hAAS2f4nNQOBGWb7N32b3LL9x2OuqWz/U36Gposcs/0zCEMgZggr\nLirxbP8ZO3LTlUMVQgjGmAAAxlgghzYXA/h24r1/DuBAtsC/UMgyxyWV/ukrLho4VihuUq3SwOeT\nsWIROnOLdd65MFvbEszFes6WLH1XFijO5JyhpsJbmM5LhPMTsZwe+QeAJb74O4yDY5MU/C8QyE6W\nNqV+/gopf6HXppRldyOcMyzxFed6zDnD8iW+OfWR5kvM0F+6JI/xTbF8Gzdp7AHG2KMAKhljdwH4\nLwD2ZmsghDiE+NMCBEEQBLFgGYmoCHhzexdwaSKB0RBl/CcIgiAIwoYrgn/GGAPwAwCXA7gAYD2A\n/ymE+HlRBSMIgiAIFxAez/3Ovxn8U9I/giAIgiDsuCL4Tzzu/6QQ4goAFPATBEEQhI2RiIq15eU5\n1V1iBf90558gCIIgiClck+0fQC9j7MpiC0EQBEEQbuN8JPc7/x6JI+CV6LF/giAIgiCScMWd/wRX\nA9jCGHsHwDjiWQpFtmz/BEEQBLHQiekGxif1nIN/AFjqV+ixf4IgCIIgknBT8P+xYgtAEARBEG5j\nZCIGADMK/pf4ZAxOc+df0w0c7B/B5RctQWAGfRMEQRAEUZoU/WrPGKtK/DlaVEEIgiAIwoWMTMTv\n4JfP4F9KBcsUnB6JZDyu6Qb+dPfLeP30eXxkfQ2+8RdXIp57lyAIgiCIhYob3vnvAdCd+D0I4BiA\n44m/e4ooF0EQBEEUnfAs7vwvK1dw5nwEhiEcj//w1dN4/fR51Af9ePboIJ58/b28yEoQBEEQhHsp\nevAvhFgthFgD4BcAPimEWCaEqAZwE4CniisdQRAEQRSXcOLOf4XPk3ObZRVexHSR8dH/f/7lCaxe\nFsA//FkjqgIK/vXg6bzIShAEQRCEeyl68G/jA0KIJ80PQoifArimiPIQBEEQRNGxHvuf0Z1/LwCg\nP5z+6P/Jc+M4dnYM165bBs4ZWlYG8dzRQYxPavkRmCAIgiAIV+Km4P9dxtjfMsZWJX7+B4B3iy0U\nQRAEQRQT87H/ihm881+TCP6d3vv/j9/HH/FvWRVPuXPlqipMagZ+9dbQXEUlCIIgCMLFuCn4vxVA\nDYB/SfzUJsoIgiAIYtESnlAhcwavnPsl27zzf9rhzv8zRwawelnAqnPZ8gpInKHnVDg/AhMEQRAE\n4UqKnu3fRAgxDOBLxZaDIAiCINzEyHgMFT55Rtn4/YqEcq+M0yMTSeXjkxp63wnjE1dcbJUpMseq\n6jL0vkPBP0EQBEEsZIoe/DPG/g2AczpiAEKIT82jOARBEAThKsIT6owe+TeprfDinaHk4P+3bw9D\nMwTev2JpUvm62go8f2wQMd2AR3LTQ4EEQRAEQeSLogf/AP6x2AIQBEEQhFsZmYjNKNmfyYqgH0ff\nG00qe+n4OXgkhvXLK5LKL60tx89+/x6Onx3DhkuWzElegiAIgiDcSdGDfyHE88WWgSAIgiDcSnhC\nRbBMmXG7+mAZfnn8HEYmVFQm2r/45jmsv6gCSkr+gFXLAgCAN85coOCfIAiCIBYoRQ/+GWMHhBCb\nGWOvw+HxfyFEY5a29QAeB7A80fYxIcSDBRM2A7GYjoGxSRhCgDMGxgAhgHIvRyQmYAhAlgBhADFD\nQDcEFImjTGEYVwViugGZM8icYVKb+luHgGEAmiEgcwafzAEOaJpI6meJj2FscqrMK3MwANFEX+U+\njqgaP65IDDE9Xk/iU7L6ZI4xVUdAkTCpGdZxzgEJDJohoNnaQCAur25Yc5YYgyEA3RBgDPF6YJAl\nBk03IBLHJPtcJY7aci/kGSSyWqhEoxqGIqp1vqv9CnyzeNS31Fis83bCMAQuRFWMT+rQEvvbpzBE\nHOyExBl8Hg5dj+9tn4dDCGBSM6y19Cscmh63QZohYCTsg2ZM2QCesAGcMwgRr2vaBd0Q4JzBwxkk\nzjCu6pA5Q8DLMT5pJPVhCMCvcERUI6m9zE0bEP87osUfK/d7GNSELTMMAVniYIiPzzmgSByqLqBq\nBrwyT8zBgMTidskw4u+1V/oVcJ77u/ClSHhCRX1V2YzbmW2OvjeKq9dUY3B0EkfeG8UtV9an1b14\niQ+KzHH4zAW0zlliIt+QnSxtSv38FVL+Qq9NKcvuNjTNwOikCkMA0Vjc1/AlfArNEPB7JGhG3F+R\nOIPCGcCAWOL6byR8DEPE/RuznenbyDLDZGyqvYczKDLDhGpY8Y29jSJzxDQDuhDwyhJkiSU+T40B\nIaAaAvE/mRWrcRb3lzycwadwRGMCmm5YPk+Zl2M0olv+Syzh7ygShyGErW3p+SFu0FAzyd9Ns2ir\nAbhXCNHLGKsA0MMY+7kQ4nD+xMtOLKbjyMAYtu3rQX84grqgH/e3NuLbL5/E3R+9DDXlHnz7pZNo\nbanH0JiKHZ2HrHod7SE89PQxPHV4AHVBP3a2NeKrPzuKwbFJPHLbJkRjBu594uBU/S3NWFrmwelw\nJKmfPe0h6IaBL3z3VavM3tc377wSI+MqfnH4Pfxx0wps39+bJusXr1+HI++ex+WXLE06/sDNTfB5\neFLfZps7P7jaGuPh2zYhphm458DBtHpf+MilaXOxy7enPYTLl1cs6i8AolENx4fGk/Sooz2EddWB\nBX0hWazzdsIwBE6PTCA8EbP24A0banH39euwzbYn7XunY0szOANeOTmEj2y4COdtbc21LPdyvHd+\nEjs6D6Gm3Isv37g+yX6k7tOvv3gCn7lmNe7rOpQ0ZnW5gn9+4SRGIiru/uhlGW3eT17rx7Xrlye1\n79jSjJ8cPI3rLl+Or/7sKGoqFPy3j61Ps4kP3NyEr794Ats/cqllT7LJfOcHV2P5Eh9WVQdK6sI7\nE4QQs37svz7oBwAcOxsP/l968xwApL3vD8S//KkP+vHGmQtzE5jIO2QnS5tSP3+FlL/Qa1PKsrsN\nTTMwOB5FTI9fk7bv7026Pjtdq3e2NWJZuYLO7j78pw0XwSNzfPG7rzrWffCWjVjq9+AvvvlKUtkS\nvwd3fvMVxzYdW5rx0DPHrTjqwVs2QuLMGuPvP7UBE6qOb7500tGvMf2RVJ9m1+YmVAYUdL5yCjc1\nrUjzwZb4ZPztj36PwbFJ7NrchOpyb0n5IUWPtoQQZxK/33H6ma6tEKI38fcogDcArCi81FMMjE1a\nCgMA/eEI7us6hNZQPbbt64FuAG0tDTgdjloKa9bbtq8HraF66/OOzkPYet1a9IcjGB6PWcGyVX9/\nL1RNpPWzdV8PhsdjSWX2vvqHI7jnwEG0tTRYgUGqrNv39+KadTVpx+994mBa32Yb+xjh8ZgV+KfW\nc5qLve3WfT0YGJss+LlyM0MRNU2Ptu3rwVBELbJkhWWxztuJoXEVk5pI2oOtoXrrogOk751t+3sx\nMKri+g0XI5bS1lxLmUuWzdh63do0+5G6T1tD9dYF0j7m6XAUd127xrJtmWxeW0tDWvtt+3vR1tJg\nyd4aqne0ieb4dnuSTeYdnYfwztAEhsYXrr6MTWrQDDGrhH9VAQUVPhm9p0YAAE++fgbBMg9WVwcc\n66+sDuD3716AEBlz8BJFgOxkaVPq56+Q8hd6bUpZdrcxMDYJTQdUm69hvz47Xavjn6Noa2nAPQcO\nIpyIJ5zqfun7r6FvOJJW1p8oc2qzbX9vUhz1pe+/ljTG8HgMOzoPZfRrTH8k9Tzec+Ag+ocjaGtp\ncPTBBkZVyw+758DBkvNDih78mzDG/owxdpwxdp4xdoExNsoYy/kWBGNsFYBNAH7jcOxzjLFuxlj3\n4OBg/oRG/FFaUylM+sMRVPo96A9HrEflyxQpYz2nz5nqcwbH8jJFyti32ZfEWVZZ9QxzydR3LvJW\n+j3Tzr0/HIGmG3ADhdSVbGTSI81Y2E54qc67EHqianra/jb3mZ3UvVOmSInH2JxtgyGm1jhbf+Y+\nzVSnTJEgcZa1j2x2xiyv9HumtQv2Y9ONV6ZIUDU988IWmbnqyshEDABmdeefMYZN9ZV4+o2zCI+r\neO7oIK5eXZ3x7sTKqjKcj8Tw3oXojMci5k4mXSlVO0nEKcT5m09fpZD6V2jdLmXZ80W+dCWmxx+v\nt/sa9uvzdL6DPZ7IVjdT2XRBq5YAAAAgAElEQVT+kFP96fwa0x+ZTm6nY6l+mJv9kFRcE/wD+CqA\nTwkhlgohlgghKoQQOWUdYoyVA+gC8FdCiLQvDIQQjwkhWoQQLTU1NXkVWuYMdYlHK03qgn6MRGKo\nC/rj7+4bAhOqnrGe0+dM9Q0Bx/IJVU8rS+1LN0RWWaUMc8nUdy7yjkRi0869LuiH7JJ/LVVIXclG\nJj2SS+QRotlSqvMuhJ4ospS2v819Zid170yoOngi34ZTXc6m1jhbf+Y+zVRnQtWhGyJrH9nsjFk+\nEolNaxfsx6Ybb0LVocjJDoObmKuuhCfidxPKZ/kY6ZWrqnAhquEL3+2Fqhu4Zm11xroN1fEcAbk+\n+n9ubBL3dR5CV08/PS2QBzLpSqnaSSJOIc7ffPoqhdS/Qut2KcueL/KlKx6JW7m9nK7P0/kO9ngi\nW91MZdP5Q071p/NrTH9kOrmdjqX6YW72Q1JxR8QV56wQ4o2ZNmKMeRAP/PcLIX6Yf7GyU1vuRUd7\nyFIO833Urp4+dLSHIHGgs/sUVgR92NnWmFSvoz2Erp4+6/POtkbsee4t1AX9qAp48MDNTcn1tzRD\nkVlaP3vaQ6gKeJLK7H3VVcXfX+nsPoXdW5odZd29pRkvHx9MO/7AzU1pfZtt7GMEAx7s2tzkWM9p\nLva2e9pDqC33FvxcuZlqv5KmRx3tIVT7Z57hu5RYrPN2ojqgwCuzpD3Y1dOHjpQ9ad87HVuaUVuh\n4JnDZ+BJaWuupWbols3Y89xbafYjdZ929fTh/tbGtDFXBH3Y+8IJy7Zlsnmd3afS2ndsaUZn9ylL\n9q6ePkebaI5vtyfZZN7Z1oiV1WWoDixcfQkn7vxXeD3T1HSmsa4Slyz14eW3hvBHly7DupR/8Wen\nIZEg8PC70wf/Md1A+z//Bj/o7sO9TxxEZ0//rOQjpofsZGlT6uevkPIXem1KWXa3UVvuhSwBis3X\nsF+fna7V8c8+dHafwq7NTQgm4gmnug/eshH1Vf60srpEmVObji3NSXHUg7dsTBqjKuDBzrbGjH6N\n6Y+knsddm5tQV+VHZ/cpRx+stkKx/LBdm5tKzg9hxf62njH2Z4k/PwzgIgA/AmC9AJ4toGeMMQDf\nBjAshPirXMZraWkR3d3dsxfYgZlm+zcMAY8t27+WyGqZKdu/mVE7Ndu/2Y89279hCCgzyPZvZun2\nyRzjqo6yHLL9m9nBZ5LtX9cN69g8Zvuf09evhdCVbCy2rLEmLpn3rHUln3qSLdt/kp3Q41nv85Lt\nn8dtE+cMImFzTLuQmu1/QtUh5ZDt394+p2z/QkDmztn+Y5oBxV3Z/udVV3782ml86fuv4R9vbsKK\nSv/0DRyIxnT85uQwrl5dBZ8n+92Jv/rBq2hZWYVHtjTnJNdfXr8OT/7uDMaiGp7/8nXwltDdj3kg\nb7riEjtJzJJpzp/rfZVSzphfyrI7UFRdSc32r6f4FL7psv0nfAx7tn97XGBm+7dn3XfK9m+2mcr2\nD3hlnpTtX4h4jFSobP9qIsZycbb/jAK54crxycRvAWACwA22YwJAtrv5HwRwO4DXGWOvJcr+Rgjx\nZN6lzILHI2FF0PnfMKXnVE45PvP/3uRIwDfNODn4jJkfBiXmA59PxopF6Mwt1nk7wTlDZZkXlSl2\nIYN5KSqpMlo455IjZkk4kUSoYhbv/Jv4PBI+fFluj3s2VJXhcA6P/X/jxZO4pNKHq9dUwevh2Pkf\nR/Hi8XP46PuWz1pOIjNkJ0ubUj9/hZS/0GtTyrK7DVnmCMrTBBwFIFgkv6Ji/qc6LxRdY4UQdwIA\nY+zbAL4khBhJfA4CeGCati9ijt+CEQRBEIRbMR/7D8wh+J8JK6sD6H4njAlVQ5niPGbf8AQO9p/H\nlqsbwBlD44qlCCgSfva79yj4JwiCIAgX46Z3/hvNwB8AhBBhxLP3EwRBEMSiZGRCRcAbzzo8H6ys\nKoMQwJH3RjPWeerwWQDxZIIAIEscmxqCeOrwWeguy3RNEARBEMQUbgr+eeJuPwCAMVYFFzyZQBAE\nQRDFIjwRm3Wyv9mwsnr6pH8/P/we6qv8WL5k6pnIjfWVOB+J5fyfAgiCIAiCmH/cFFw/AOBXjLEn\nEp9vBvB/iigPQRAEQRSV8ISKcu/8JdFbVu5FQJEyBvHjkxq63w7j4++/KKn8fRfH/zPvr08M4f0r\npst2QxAEQRBEMXDNnX8hxOMA/gzA2cTPnwkhvlNcqQiCIAiieIQnVJT75u/OP2MMK6vLMgb/v317\nGJoh0gL8qoCCi5Z48ZuTw/MhJkEQBEEQs8BNd/4hhDgM4HCx5SAIgiAINzA0pmJdbfm8jllfFcAv\njw/CSPyrRzsvHj8Hj8Rw+UVL0tqtv2gJfntyGEIIxP8TL0EQBEEQbsI1d/4JgiAIgphCCIGhMRVL\n/PN35x+Iv/c/oep4Z3gi7diLx89h/UUVUOR09+Gy5RU4H4nh7aH0dgRBEARBFB8K/gmCIAjChYxO\nalB1A0vnO/iviif9S330f2A0iqNnR3HFJc7v9JtPKLx6KlxYAQmCIAiCmBUU/BMEQRCECxkaUwFg\n3oP/umAZOEvP+P/ym0MAkDGh34pKP/weCa+eGnE8ThAEQRBEcaHgnyAIgiBcyLmxSQDzH/wrMkdd\nsAyv9iXfwX/u6AAqfDJWLQs4tuOcYW1tAL10558gCIIgXAkF/wRBEAThQoYSwf98v/MPAH9wyRJ0\nvx1GNKYDAGK6gWeODGBTfSV4lmR+l9ZU4MiZUUyo2nyJShAEQRBEjlDwTxAEQRAuZLBIj/0DQGPd\nUkxqBl55O/6v+145OYwLUQ0tK6uytlu3vBy6EHi9//x8iEkQBEEQxAyg4J8gCIIgXIh557/CN///\nlffyi5ZA5gxP/f4sAOCJnn74PRxX1Dm/729yqZn0r4/e+ycIgiAIt0HBP0EQBEG4kHNjk6jwyZD5\n/F+qfR4J16ytRmdPP37/7nn828F38eH1tfB5pKztlvg8uHipjzL+EwRBEIQLoeCfIAiCIFzIuVG1\nKI/8m9zUeAmiMR2fevglSJzhxj+4KKd2a2vK0fvOCIQQWesdOzuKL+zvxZc7D2JkQs2HyARBEARB\nZKGkg3/G2DcYYwOMsd8VWxaCIAiCyCcDo1FUFjH4r68qw46PrccfXLIEf/3x92H5El9O7dbVlmNw\nbBKnRyIZ65w5H0Fbx8t4/tggfth7Gu1f/w003ciX6ARBEARBODD/LxLml28BeBjA48UUIhrVMBRR\n4ZEYYrqAZgjInIFzQDcAReIAE4hp8WM+mcMAIHFA0wRiifoyZ5jUDAS8EqIxw+qnTOGI6SKpb3Os\nCh9HNCYgBBAzBHRDwO+RoOmG1W+ZwqEmxjEMAYkzMAZIjMEQgGYY4IzB5+FJ4/pkjomYDs7i9T0S\nh8yBCXWqTrk3Pr5mxH88nKHMy6HpwKRmgDFACMAQAorEoSVkNGUQAqgt98IzzaOkiwFTj8y1rfYr\n8BXhXd/5ZrHOOxXDEBiJqIioOnQh4JMlSBIwMRnfg5wBnDHoQoAB1p6XOIOHM/g8DJoORDXDsjO6\nADTdgMST93e5Iln1TBsxoRrW3jR/hABUPV7u4QzxgRH/jbgdmtSmjgd8HFFVWLZIkTgCXobR6NRY\nFT6O0agBXQhIiXkZAmCJPn0elrBpAoosIej34MJkzFoXj8TBAUzqBnweCcsCXnDOYBgCQ+MqVE2H\nIkuoDigAkFbGeeZM9W7jvfNRrK0pL6oMmxqC2NQQnFGbdcsrAACvnhpBXbDMsc4jz76JCVXHV9sa\n8fa5cXztmTfR2dOPW65qmLPMCxGyk6VNqZ+/Qspf6LUpZdndRDSqIRyNIebgU8iJz+OTOiQ+dV1P\njYvKFA7diPsVMT3ub/hkDlWLxyw+mcMQsMaQOcOkbkBKiVE8nMHr4YjEpvwPZo3JIYSAR47HHDHN\ncLz+a5qB81EV0diU75Mqty4EfBKHlpDJI3HUlnshhMDwhAoBQEvEVh6ZQ5EZoqrzeHac/JX59E1K\nWkOFEC8wxlYVU4ZoVMPxoXH85LV+/HHTCmzf34v+cAR1QT/ub23Et18+iTs/uBo1FV589WdHMDiq\n4ss3rsdzR87ipqYV2Garv7OtEd0nh/Hhy2uT+vnWnVciEjOwbV+PVbZ7SzP+/eBp3LSxDpdUenHs\nvTHs6DyEmnIvvnzjeuzoPGTV/eadV2JkXMU9Bw5aZQ/c3ASfh+ML333VKutoD+Ghp4/hqcMD1hj7\nfvUOXj4xhI4tzVhWoeC9C7EkOTraQ1hWLuPPH/uNVbanPQSvzLDzP47iM9esxn1dznKZ63P3Ry/D\n5bXli/oLAFOPUtd2XXVgwV5IgMU771QMQ+DtoXGcvRBN2iM72xrx1Z8dxeDYJB6+bRN0Q+DR59/C\nZz+0Bvc+cTCp3splZRgaVbFtf2/afvv8H63CTRvrsG1fD65ZU432P1yZZGM62kP4yWv9ePSXb6Mu\n6MeDt2xEdbmCMyPJ8jxwcxO+/uIJfPZDa/D1F0/g7uvX4aFnjuOpwwP4/B+tQtuVDTg3Omm1uWFD\nLe7+6GVp59c+lmkHPnPNarxw9Kwlp92e6IaRZKt2bW7CV548gsGxSey9owXraspxfHAMdz3ebdV5\n/L9chUnNSCrbe0cL1i+vKIkvAAxDYGB0Ei2rsmfXdyP1VX54ZY7ut4fxyaZL0o6/OxLBD17pw4cv\nq8HFS/24aIkPT/7uPTz8zJvY3FJfEudnPiE7WdqU+vkrpPyFXptSlt1NRKMa3hoex+e/05PmU9jj\nEjNmuL+1ES8cPZsWF3W0h1Ad8GDzo7+2fIQvXr8O2x38FrsPVFOhpPkSu7c04+GE/2H3T+784GqU\ne2UYQiT5Dfbrv6YZePdCBCMTsbS4zS63k0x72kOoKvdg8MIkJlQ96Viqb+LkbxiGwNGzo0X1TUr6\nsX83MBRRsW1fD9paGiwFAoD+cAT3dR1Ca6geOzoPoW84gtZQPbZetxY7Og+hraXBCvzN+js6D+HT\nzXVp/fQNRyyFN8u27++N97GvB1HVsJTP7N9et384YgX+Ztm9TxzE8HgsqWzbvh60huqTxrjr2jXo\nD0dwbkyFpiNNjm37eqAbLKls674e9IejaA3V476uzHKZ67NtXw8GElmtFyumHqWu7VBkYb8Hu1jn\nncrQuIp3hibS9siOzkPYet1a9IcjCI/H8KXvv4bWUL0V+Nvr6Tosm5K630xb0R+O4K5r16TZGNOG\nmZ+/9P3XoOlIk+feJw5a47eG6rFtf69lM9paGtA/HElqY+7vbGOZduC+rkNJcprHt+7rSbNV9xw4\naK3LXY93Y2Bs0rqQmnXeGZpIK7vr8W4MjZeGbg1PxO8mVSWeYCglZM5x+cUV+OXxc47Hdz/3JoQA\nPr1xBQCAsXg+gf6RCH59cmg+RS0JyE6WNqV+/gopf6HXppRldxNDEdUK/AE4XqvtMYN5PXfyNXQD\nST7C9gx+i90HcvIlttv8D7t/sqPzEM6NqWl+g/36PzA2CVUTjnGbXW4nmbbu64GuA8PjsbRjqb6J\nk78xNK4W3TdZFME/Y+xzjLFuxlj34OBgXvvWDIH+cAQSnwqATfrDEVT6PegPR1CmSKj0e6zPmeob\nQqSVlymSY12zD1MGAFb/ubQvU6S0Mvv7peYYZh+6g2z94Qh0Q6SVmfPNJpd9fTQje2Ko+aKQupIN\n+zk0cdO6FIpSnXe+9UTV9Iz71NyT5vFMe8m+P1Pr2O1NJtsj2b5x7g9HwBmy7ln7b7Pf1DlkkjV1\nrOnsYjZb1R+OQNONnO2equmYT2arK++djwIAgmWlF/wDQOOKSpw4N5723v+Z81N3/WsqvFb5lauq\nUKZI6Oo5Pd+iuoZMulKqdpKIU4jzN5++SiH1r9C6Xcqy54t86ErqXKfzI6aLc0xyjROyHUv9bPoM\nTn6Def2P6UZGH8cud6ZxDSGm9dky+RuqphfdN1kUwb8Q4jEhRIsQoqWmpiavfcucoS7oh24I1AX9\nScfqgn6MRGKoC/oxoeoYicSsz5nqc8bSyidU3bGu2YcpAwCr/1zaT6h6WtlIJJY2htmH5CBbXdCf\n5Mjb+7bL4iSXfX1klzzmWUhdyYb9HJq4aV0KRanOO996oshSxn1q7knzeKa9ZN+fqXXs9iaT7bF/\niVcX9MMQyLpn7b/NflPnkEnW1LGms4vZbFVd0A9Z4jnbPUWe39eLZqsrA6Px4L8qULyEf3PhihVL\nAQDPHhlIKu947i0Ytrv+JorMEVoZxC/eOJv2hfJiIZOulKqdJOIU4vzNp69SSP0rtG6Xsuz5Ih+6\nkjrX6fyI6eIck1zjhGzHUj+bPoOT32Be/z0Sz+jj2OXONC5nbFqfLZO/ochS0X2TRRH8F5Jqv4KO\n9hA6u09h95Zm64Sa74509fRhZ1sj6qv86Orpw57n3sLOtkZ0dp9CR0r9nW2N+HFvf1o/9VXx92Ts\nZbu3NMf7aA/Bp3DsbGuMv4uS6N9et64q/h6KveyBm5tQFfAklXW0h9DV05c0xt4XTqAu6MeycgWy\nhDQ5OtpDkLhIKtvTHkJd0Ieunj7c35pZLnN9OtpDqC2fugO0GDH1KHVtq/2ledcvVxbrvFOpDihY\nWV2Wtkd2tjViz3NvoS7oRzDgwYO3bERXTx8euLkprZ4kwbIpqfvNtBV1QT/2vnAizcaYNsz8/OAt\nGyFLSJPngZubrPG7evrQsaXZshmd3adQV+VPamPu72xjmXbg/tbGJDnN43vaQ2m2atfmJmtd9t7R\ngtpyL/be0ZJUZ2V1WVrZ3jtarESAbue98/FXoUr1zn9d0I8VlX786NWpO/lnzkfwvd+eSrvrb7Kp\nPojzkRhePRWeT1FdD9nJ0qbUz18h5S/02pSy7G6i2q/g0dun5up0rbbHDOb13MnXkDiSfITdGfwW\nuw/k5Evstvkfdv9kZ1sjlpUraX6D/fpfW+6FIjPHuM0ut5NMe9pDkKT4F/Opx1J9Eyd/ozqgFN03\nYdP9H143wxj7HoDrACwDcBbA3wkhvp6tTUtLi+ju7s6rHKnZ/q2skQ7Z/nVDwJst279uIKDMPtu/\nYQj4csj2b2YOX+DZ/uf09WshdCUbiylrrB2XzHvWupIvPUnO9g/4ZJ7I9m8k9mt6tn/NEODzkO3f\nSNQz9yxjgLBl+zeP27P9G0Y8M39atn8/x2gkH9n+BXweXoxs//OiK7t+fgxfe/o4Hv/sVZB5aX5P\n/+PXTuP7r/ThmXs/jDU15fjrH76OA9192LW5CTUV6f82cHxSw+e+041t163Fjo9dXgSJ807edMUl\ndpKYJdOcP9f7KqWcMb+UZXegaLoyq2z/MrNiHykl27+mx/0Xx2z/RjzDv8wZVD09RrFn+7f7J3PO\n9s8Bw5jK9m8IAW8i27+mG5BLK9t/xg5L+sohhLi12DIAgM8nY0URL8JL/NPXmS3VDmXBQPLnpYUb\nflFRbD0qFot13qlwzlAV8AIp+6s64Fw/36Tu69my1MEepdqoHP9dvEWVnL4uqXDOHO8mO5WVAu+O\nRFBZ5inZwB8Arr2sBj967TT+/l9/j9uubsD3fnsKH3//RY6BPwAEvDLWX1SBp98YWCjBf94gO1na\nlPr5K6T8hV6bUpbdTfh8Mi6eZq7Vxf3PtDNCljmqy2fojNhY7uTsANP6KkBmf2W+KF2vgiAIgiAW\nKP3hSMl+cWESLFNwy5UNeOH4OWzd14v6oB9/fmV91jYb64M48t4ozpyPZK1HEARBEMTMWRxfVxEE\nQRBECXFqeAKrls3TYx8F5IYNy3HxUh/eOx/FtZfVwDtNUqNN9ZX43m9P4dkjg7jt6oZ5kpIgCIIg\nFgd0558gCIIgXISmG3jvfBQ1CyARKmMMjXWVuOEPLoIvh9wuZoLZ548NTFuXIAiCIIiZQcE/QRAE\nQbiIM+ej0IVAbYk/9j8bGGO4YkUlXnpzCDHdKLY4BEEQBLGgoOCfIAiCIFxEX3gCQOkmK5wrTfVL\nMTap4bW+kWKLQhAEQRALCgr+CYIgCMJF9A/Hk90t1uD//ZcsBWfAC8cGiy0KQRAEQSwoKPgnCIIg\nCBdxcmg8/j+jy5Vii1IUAl4Zl9aW43kK/gmCIAgir1DwTxAEQRAu4vjZMVy81AeZL95LdGNdJV7v\nP4/hcbXYohAEQRDEgmHxehYEQRAE4UKOD4zikkp/scUoKhvrKyEAPHeUsv4TBEEQRL6g4J8gCIIg\nXEI0pqNveAJ1wcUd/K9eFkBVQMFTvz9bbFEIgiAIYsFAwT9BEARBuIQTg+MwBLCisqzYohQVzhia\nG4J4/tggIqpebHEIgiAIYkFAwT9BEARBuISjZy8AwKK/8w8AV6+uQiSm4xdv0N1/giAIgsgHFPwT\nBEEQhEt47dQIfB6+6N/5B4ANFy9BdUDBD3v7iy0KQRAEQSwIKPgnCIIgCJfwat8IVi8LQOKs2KIU\nHc4ZPrRuGZ4/Noj+8ESxxSEIgiCIkoeCf4IgCIJwAdGYjsPvXsClNeXFFsU1/Of3LQdjDF9/8WSx\nRSEIgiCIkqfkg3/G2I2MsaOMsTcZY/+92PIQBEEQxGw41H8emiGwrrai2KK4hupyL65ZW43v/eYU\n+obp7j9BEARBzAW52ALMBcaYBOARAP8ZQD+AVxhj/yqEODyfckSjGoYiKjRDQOYMHokhpgt4JAYh\nAEMAqm5A5gxemWNC1SFxBp/CEVUNaIZAuVeCpgvEDAHdEFAkDsXDrOP2tjJn4JzBEAJCALoQkNlU\nGcAQS4wncwZVN6BIHJohoBkCHs4Q8HKMTcb79skchgDABCTGoeoG9ES9ch9HRLXJJXNwAFHNgEfi\nCHgZYhowqU3JyTlgGABjgBCAT+bgHIjGBFTdgMQZPJxBlhiiMQPVfgU+X0mrYl5I1aPFsi6Ldd4m\nhiEwNK5C1XT4lbgdiMbiNsLcQ2UKRzQmACZgGPE9L7H4cY/EE7bDgMQYfB6eZEvM/R0zDMtOTCb2\nb5nCMD5pgDFAYsxq45EYFIlb+9ojcSjSlM0xbYmUsDFyok/zHMoJW8QYgyEAPSGbR473qSfq+WSO\naKKdInH4FQ5dCERVA7oQ8HkkVPkVhCOxqfUxBGKaAUWWEPR7rGOKLKE6oICnPC5vX99MddzCs0cH\nIHGGDZcsKbYoruLPW+rxytvD+Osfvo5v3XklZKnk71vMmMVuJ0udUj9/hZS/0GtTyrK7hWhUwwVV\ng6ob4DZ/gTMAAtASPokZ/+g2/8CAgIfzJB/BJ8ev9WaMZPovnAGMxWOnmG6AJ2KfmBb3CRSJQzcE\ntETcI0sMkdhUXOGRGSbURAwjcfg8HBWKjIgWg2YAEdWw/CpdCMicQ+YMkYTP5eEMDIDEGaJasm/E\nbe0kFo91OJglj88jYVnACwBJPkcufoqJ6a8YhgFdAEKIgvgtpa6hVwF4UwhxAgAYY98H8GkA8xb8\nR6Majg+NY9u+HvSHI6gL+rF7SzP+/eBp3NS0AorM8NlvJx/b96t3ECyTcdPGOmzb14Nr1lTjv167\nGkNjKnZ0HrLqdrSH8NDTx/DU4YGkti+fGMIjt21CNGbg3icOWvV3bW6CzyNh2/5eq2xnWyP+pfc0\n/rR5RVLfe9pD6D55Dj8++B6+fON6fPOlk/jSf7oMFyKxtHq6YeAL333VKnvo1k34X/92GFetqsRt\nf7gK5ydi2G4b8/7WRnz75ZP4zDWr8e2XT+K/fWw9YrrA57/TkyTXsgovXjo2gNDqZVhXHViQBjNX\nnPSooz204Ndlsc7bxDAEjp4dxV2Pd6Om3Iu/+cTluOfAwaS99MLRs/jkxjp87elj+Mw1q3Ffl81G\nbGkGYwxbbetn37M15V58+cb1SXt6Z1sjvvqzo6ipUHD3Ry/DQ08fw/aPXIqIqme1P3vaQwgGZLwb\njibJuLOtEdXlCv7xP45adXdtbkKFX8ZoREuqu3tLMx5+5jieOjyAGzbU4u7r1yXZKyd7s6c9hK89\nfQyDo2raXMxj5rh772jB+uUV1kXSvr5mm9Q6buLpN87i8osqEPAufN2fCdXlXtz+gVXY+8sT+NIP\nXsNX/uQKLC3zFFuseWOx28lSp9TPXyHlL/TalLLsbiEa1dB/IYLB0Ul886WTlr/wzZdOJvkkN2yo\nxRevX5cUD+za3IRlFQrORdWka/3uLc2oLPNgNBLD5/dNlT982ybENMPRb3DyAUx/ZnBsEo/ctgkS\n50n+0IO3bERNhRceieHcWAwPOfhRuzY34StPHsHg2CR2tjWipkJBJCaSfKPUudYF/Xjg5ib4PDzJ\nX9l7ewu8Ho47vvHbnP0UE9Nf2fXzo2lj5dtvKfWvz1cA6LN97k+UzRtDEdXa+ADQH45g+/5etLU0\nYNv+XkhcSjt217Vr4scT7e66dg1Oh6OWQpt1t+3rQWuoPq1tfziC4fGYFfibx+85cBDnxtSksh2d\nh3DXtWvS+t66rwfXb7gYW69bix2dh9AaqsfAhUnHesPjsaSyu7/3KrZetxZtLQ2IacLa6Obx+7ri\n/Zm/T4ejVuBvl6t/OILrN1yMbft6MBRRC36u3IyTHi2GdVms8zYZGletwHTrdWutCx4wtZfaWhqw\nNWELzIuBefzcmGpd6Mwy+54193fq3tt63Vq0huotGxMej01rf7bu64FhsDQZd3QewulwNKnuPQcO\nQuZSWt3t+3uteq2hessZcJLdXtYaqnecy9YUGe96vBtD41O6Y1/fTHXcwluDYzh2dgyb6oPFFsWV\nXH95LW69qgE/ff0Mrv7KL/Anj7yEL363F//zx7/Dw88cxy+PD2J8Uiu2mAVhsdvJUqfUz18h5S/0\n2pSy7G5hKKKibzhixQqmv5Dqk7SG6tPiAdMXSL3Wb9/fC1UTGBhNjlnC47GMfkM2f8aMi1L9oS99\n/zWomoCmw/JpUv2oew4ctPrY0XkIAE/zjZza3fvEwTR/5a7vdOOdoYkZ+SnWOif8Faex8u23LJyv\nprLAGPscgM8BQENDQ3Ajff4AACAASURBVF771gxhnSCT/nAEEmfoD0eQ+iWNecz8G4g/XlKmSI79\nVPo9jm0z1S9TpIyypJYLIVDp9ySNk2uflX5P2jxSj+fSrxDx9dMMATdQSF3JRiY9csu6FIpSnXe+\n9ETVdGv+5p6xY9+/TsenswOZ+rTvy2x7NNX+GML5fJUpEsogJZVxlr3PTLJlsje5yqhquvXZvr6Z\n6hSaXHXlO796BzJn+OCl1fMlWsnxqaZL0FS3FM8eHcTpkQn0vBPGWFTDaCLo9ysSPtV4CW7/w5V4\n/4qlRZZ25mTSlVK1k0ScQpy/+fRVCql/hdbtUpY9X8xVVzRDWL5Gqu9gn3+ma3omv4EzpF3vp4uF\nsh3L1Jaz+KP6mfyo1P5N3yXbXM1yJ38lmw9jfnbyQUx/JdNY+fRbSv3O/2kA9bbPdYmyJIQQjwkh\nWoQQLTU1NXkVQOYMdcHk/8dcF/RDNwTqgn6k2gDzmHkcAHRDYELVHfsZicTS2gLIWH9C1dPK7GPZ\nyxljGInErHFm0udIJAbdEDAEMsqdS7+MxddPdskjuIXUlWxk0iO3rEuhKNV550tPFFmy5m/uGTv2\n/et0fLo9m6nPkUgspz2aan84cz5fE6qeVjebbcgmWyZ7k20u9s+KPHXhta9vpjqFJhddGRiN4ome\nPly9ugqVZcq8yVaKrKwO4C+uWYX/8YkN+L+bN+KxO1rw9c+04K8/fjmuXlWFH712Gjc99CI2P/or\n/PT1M2lPA4xGY/jl8UH8358fw217f40PfOVpbPpfT+G6f3wW2/f34AevnMJ5m07NJ5l0pVTtJBGn\nEOdvPn2VQupfoXW7lGXPF3PVFZkzy0ew+wup1+RM1+hMfoMhkHa9z+aLTOcDZGpriPh7+5n8KHsf\ndt8l21zNuk7+SiYfxv7ZyQcx/ZVMY+XTbyn14P8VAOsYY6sZYwqAWwD863wKUO1X0NEesk6U+X5K\nZ/cpdGxphm7oacf2vnAifjzRbu8LJ7Ai6MPOtsakuh3tIXT19KW1rQv6URXw4IGbm5Lq79rchGXl\nSlLZzrZG7H3hRFrfe9pDeObwGex57i3sbGtEV08fapd4HetVBTxJZQ/dugl7nnsLnd2n4JEZdm9p\nTjp+f2u8P/P3iqAPj94eSpOrrsqPZw6fQUd7CNX+xe3wOunRYliXxTpvk+qAgr13tMT32nNvYdfm\nprS91Nl9CnsStuD+1uT9uaxcwZ6U9bPvWXN/p+69Pc+9ha6ePsvGBAOeae3PnvYQOBdpMu5sa8SK\noC+p7q7NTdAMPa3u7i3NVr2unj50pNgOJ3tjzt1pLntSZNx7RwuqA1O6Y1/fTHWKjWEI/N2Pf4/J\nmIHW5rpii1OSlCkyGusq8fkPr8UjtzWj/eqVOHluHNv296Lp/30KH/unF/Cnu1/Ch+5/Blf8/VO4\n/eu/xcPPHMe7IxFctrwcoZVVqC334bcnh3Ff1+u48n//An/5vVfxq7eGIETx7+ItdjtZ6pT6+Suk\n/IVem1KW3S1U+xXUV/mtWMH0F1J9kq6evrR4wPQFUq/1u7c0Q5EZaiuSY5ZgwJPRb8jmz5hxUao/\n9OAtG6HIDLIEy6dJ9aN2bW6y+tjZ1gjASPONnNo9cHNTmr+y9/YWrKwum5GfYq1zwl9xGivffgtz\nw4VtLjDGPgHgnwBIAL4hhPg/2eq3tLSI7u7uvMqQ72z/hplde5ps/0LE77wbVubJqWz/WiKrvszj\nmf89qdn+fRxj0Zll+zcMAU8i2/+kZkBOyfZvZvd0zPYvAVFVWNk75ynb/5y+fi2ErmRjsWSNTcUl\n8561rsxVTxyz/Wu6lfnWcMj2bwgBnkO2f8MQ8Cb2t2Zm03XI9s8ZwBMZbQ1DQM4h279uCPCUbP+p\nGX4ZnLP9G4l6ZrZ/MzNvcrZ/wOfhbsz2nzddEULg//vJG/jGSydx65X1+NTGeU1Zs6DRDYHDZy7g\n9f4RvHs+ClUzUO6TUVfpx6W15bi0thxlSrKdEULgxLlxvHBsEC+9dQ7jkzpWVZfhlqsa8MmmS7Ci\n0p82zvC4ivCEirU15U5i5E1XXGIniVkyzflzva9SyhnzS1l2B4qiK5my/UsJP7+Y2f6jsam4wsz2\nH/dj5p7t3+4bSQl/zDnbf9xfcVm2/4wNSv7KIYR4EsCTxZTB55OxYrabPTDH43Ngabof48iSHOtN\nS1me+lmgzEmPSpjFOm8TzhlqKrxFG7/Sjfsyxe5lW5/p1q7Y6zsdEgdufP9F+GTTJcUWZUEhcYYr\nVizFFTN4958xhrU15VhbU44tV6/Eb04O4dkjA/iHnx7BP/z0COoq/Vi3vBzLl/igGQJnL0Tx6xND\n+MCaanzns1cXcDZkJ0udUj9/hZS/0GtTyrK7BZ9PLpkvG6sc4iaPJ/HIfAFjKjupPkeuPsh8+Sul\ncSYJgiAIYoHBGMPffOJ96BueAGPuek+UANbUBHDrVQ04NTSB3749jIP9Izg9EsGh/vPwSBwVPhl/\numkFPvuhNcUWlSAIgiByouQf+58pjLFBAO/M03DLAJybp7HcOH6xZTgnhLhxto3nWVfsFHPNFuvY\ns9aVRWZT5spCkP+Iy3TFDWtabBmKPX4mGQphV9ww10KyGOdXTF/FjetNMmWmWLrilvnbcZtMbpMn\no64suuB/PmGMdQshWhbr+G6RodQo5pot1rFLhVJfI5I//7hBpmLLUOzx51MGN8y1kND85he3yQOQ\nTG7EjfN3m0xukycbpZ7tnyAIgiAIgiAIgiCIaaDgnyAIgiAIgiAIgiAWOBT8F5bHFvn4gDtkKDWK\nuWaLdexSodTXiOTPP26QqdgyFHt8YP5kcMNcCwnNb35xmzwAyeRG3Dh/t8nkNnkyQu/8EwRBEARB\nEARBEMQCh+78EwRBEARBEARBEMQCh4J/giAIgiAIgiAIgljgUPBPEARBEARBEARBEAscCv4JgiAI\ngiAIgiAIYoGz6IL/G2+8UQCgn8XxMydIVxbVz6whPVl0P7OGdGXR/cwa0pVF9TMnSFcW1c+cIF1Z\nVD8ZWXTB/7lz54otAlEikK4QuUB6QuQK6QqRK6QrRK6QrhC5QrpCAIBcbAEywRj7BoCbAAwIId7v\ncJwBeBDAJwBMAPgLIUTv/EoZJxrVMBRRoRkCMmfwKRxR1bA++xWOsagOWeKQGKALASEAQwhInIOz\nxN+MIWYI6IaAhzPIMoOmAzHdgFfmMAwBzRCQOANjgCEAD2fweRiiMYGYISCEgFfi0Iz4Z5kzVPg5\nYjEgqk3JVOblUGMCuoiPxxmDz8MRjU3V8ckcuhAAGFTdgCEEZMbAOcOkZsAjcXg9DJOqgVhCLkXi\nWKLIGItpmLSN5/NwqJqAqhuQOIMnMYeYLrCsTIHX61pVnDdS9ajar8DnW/jrsljnnQlNMzA4Nmnt\nFUXi8MjAxOTUfuIc4GDQhUBMj+89n8yhaoZlG/REXa/MEdEMKBKDbiBpD0qcwRCAxIHJxN7nnKFM\n4YjYbJiSsD9A3FYJAWvPe3hcDgYGbrNveuK4V+ZgDJjUBGK2sf0KQ0QVls1TJA6JMwghwDlH0O9B\nOBKDYRjQBSCEgE+J2y1Vj9uf2nIvZDnzd9iGITA0rkLVdCiyhOqAAs7ZfJ3KgpKPfTPXPordPhbT\nMTA2abWvLffC45Fybg8sbB0hiHxRyOt0oX2AUpZ9IaJpBgbHJyEScY9mi218MoeqG5Zfo3AGMIZI\nTIdX5uAsHo9M+QxAJJbs00Q1IymOimkChhAo90qYUJP9KIi43xLVDCtWicYM6AnZGAPkhIxgSIrT\nzPjO9JU8nMFvxVZxn0WRJcuXsV9jAGBoXE3yb+x1U8vzfV1ys4Z+C8DDAB7PcPzjANYlfq4G0JH4\nPa9EoxqOD41j274e9IcjqAv60dEewkNPH8NThwesz8+9cRY/6OnHrs1N8MgcX/zuq1b9R27bBM4Y\nxiY17Og8NNXPlmY89MxxDI6q+PKN65OO3d/aiG+/fBJ3fnA1llV4IXPg9q+/gppyb1Ldz//RKtz2\nh6twfiKG7ft7rfbfvPNKTEzq+MJ3ezPKvXtLM5aVe3A6HMU9Bw5a9Xa2NeKrPzuKwbHJtDY72xqx\nIujH+YkYtiXGu2FDLf7yo5dhq22NdrY1orpcQVd3H27aWIfLlgUW9RcAmfRoXXVgQV9IFuu8M6Fp\nBo6cHU3aK4/dEYJhIKnsgZub4PNwfCFhR27YUIsvXr8ODz9zHJ+5ZjXu65qyFbu3NKP37SG0rF6W\ntgeXlSvwejguRHTr2A0banH3Ry9LOie7tzTDK8cvPKNRHX/1g9eS+vErEnY/+ya+8JFLEY0ZuPeJ\ng0ltl5Z58N1fvY1Hf/k26oJ+fOvOFlyYZDg3Oplk1x66dRMYA3Y/+yb+8qOX4d9e68e165fjvq5D\nabatLujHnvYQLl9e4fgFgGEIHD07irse77bq772jBeuXV5R8cJePfTPXPordPhbTcWRgLK395bXl\nOX8BsJB1hCDyRSGv04X2AUpZ9oWIphk4enYUDz59DNs/cilimmHFFzdsqMXd16+zYgfTvyhTJOz/\n9Sls+UADJlQ9yQfYtbkJX3nyCAbHJq1Yyt7ejKOuuGQprnvf8qRzZcZRd/3RGnzlySOoqVDSfB/T\n13rk2Tex/SOXIpIy/p72EL5mi4H2tIcghEiSIbXO3jta4JU5/uGnb6T5a3vaQ0l+T6GuS6597F8I\n8QKA4SxVPg3gcRHn1wAqGWMXz490UwxFVEtRAKA/HMG2fT1oDdUnff50cx36wxHcc+AgwuOxpPrD\n4zGcG1MthbLa7e9Fa6geW69bm3bsvq5DaA3Vx8uHI5C5hP5wJK1uW0sDYpqwAn+zff9wxAr8M8m9\nfX8vdINZG9Ms39F5CFuvW+vYZkfnIajalOIDiM8hZY12dB7C6XAUbS0N2LavB+cm1AKeJfeTSY+G\nIgt7XRbrvDMxMDaZtlfOnk8vu/eJgxi22ZHWUD22J+yFecEw627f34vrN1zsuAf7w1Ew8KRjraH6\ntHOyfX8vJC5B4pIV+Nv7CY/H0Bqqx/B4zAr87W1jmkBbS4NVBnD0D0fS7Nrd33vV6mvrvh60tTRY\n83Gyg1v39WBgbNJxLYfGVSuoM+vf9Xg3hsZLX7fysW/m2kex2w+MTTq2z6QPjjIsYB0h3MekpkPT\njWKLMWMKeZ0utA9QyrIvRAbGJvH5RNwQHo8lxRetofqk2MH0L4bHY7jr2jUYHo+l+QD3HDhoxSPD\n47G09mYc9enmurRzZcZRZh9Ovo/pa5nyOvkg9hho674enBtTs9a56/FuvDM04eivpfo99jb5vC65\nNvjPgRUA+myf+xNlaTDGPscY62aMdQ8ODuZVCM0Q1gmyBAlHUOn3JH0WQlh/lynJdyXKFAllipSx\nn0q/J+Mxsz8j0X9qXYnHH2lJbZ9tPPtnXWSfn1Ob1PEyyV+mSJA4Q384En+kxgUUUleykUmP3LIu\nhaJU510oPYnpRs571W5HzD2Waa8ZGfZxmSKl7fFMfXAGR1ti9lPp92SUlbO4LTLhLPu8TBlM+5BN\nrkzOtKrpjvVVTXesXygKoSv52Ddz7aPU2wPu0RGTYl1/iPnhY7tewP9z4GBe+ppPXSnkdbrQPkAp\ny54v3GRXTB/HyV+YLlaYLm7JdjyTD2T3nbKNn82/SY2BUmO8THUyjWf3e+zl+bwulXLwnzNCiMeE\nEC1CiJaampq89i1zhrqgP6msLujHSCSW9DmeoiD+94SafAInVB0Tqp6xn5FILOMxsz+e6D+1rm4I\nGAJp7bONZ/8ssezzc2qTOl4m+SdUHbohUBf0Q3bJI5aF1JVsZNIjt6xLoSjVeRdKTzwSz3mv2u2I\nuccy7TWeYR9PqHraHs/UhyHgaEvMfkYisYyymjkITAyRfV6mDKZ9yCaXLDlfxhRZcqyvyDN7J3yu\nFEJX8rFv5tpHqbcH3KMjJsW6/hDzgxDxLz7z09f86Uohr9OF9gFKWfZ84Sa7Yvo4Tv7CdLHCdHFL\ntuOZfCC775Rt/Gz+TWoMlBrjZaqTaTy732Mvz+d1qZSD/9MA6m2f6xJl80q1X0FHe8g6UeY7P109\nfUmff9zbb72fEgx4kupXBTxYVq5gZ1tjcj9bmtHV04c9z72Vduz+1kZ09fTFy6v80Iy4UqbW7ew+\nBY/MsHtLc1L7uio/HrmtOavcu7c0Q+ICuzY3JdXb2daIPc+95dhmZ1sjFJmhwzZeV08f9qSsUTw3\ngA+d3afQ0R7CsjKlgGfJ/WTSo2r/wl6XxTrvTNSWe9P2yvKl6WUP3NyEKpsd6erpw+6Evbi/NdlW\n7N7SjGcOn3Hcg3VBHwSMpGNdPX1p52T3lmbohg7d0PFPf74xrZ9gwIOunj5UBTx44OamtLYemaGz\n+5RVBhioq/Kn2bWHbt1k9bWnPYTO7lPWfJzs4J72EGrLvY5rWR1QsPeOlqT6e+9osZLtlDL52Ddz\n7aPY7WvLvY7tM+mDowwLWEcI92EIYd2oKSUKeZ0utA9QyrIvRGrLvXg0ETcEA56k+KKrpy8pdjD9\ni6qAB3tfOIGqgCfNB9i1ucmKR6oCnrT2Zhz1497+tHNlxlFmH06+j+lrmfI6+SD2GGhPewjLypWs\ndfbe0YKV1WWO/lqq32Nvk8/rEjMfR3cjjLFVAH6SIdv/HwP4IuLZ/q8G8DUhxFXT9dnS0iK6u7vz\nKqeZ7dPMbu2Y7X9Sh8xzy/ZvJNqZ2f413bCybWuJevGs2ols/wpDVJ3fbP+qZkCeRbb/mG6Az1+2\n/zldZQuhK9lYrFljXTLvWetKvvXEzPZv7hV7tn/Txtiz/Wt6PEN/rtn+7XtwLtn+zboezhKvHTHL\nlpnjp2b712xj27P9G4aAZwbZ/mN63P4UKdu/K3SFsv2XRLZ/V+gK4Q4++A/P4ANrqvHA5qbUQ673\nVUo5Y34py+6A63VlOsxs/0h8GaYlsudbfoxuWH6Nme0/GtOhZMj2H40l+zRRzUiKo1Kz/dv9qEzZ\n/s0v6ngiw39qtn8j0YfLs/1nbODayIIx9j0A1wFYxhjrB/B3ADwAIITYA+BJxAP/NxH/V393FkdS\nwOeTsSJ1sweSP1alfM43S/3TVPAVcHCHuS2GoDXfOOrRImCxzjsTssxxcWX6hg6WzbMgBbZZALBk\nGrtVU5H7XVwnOGdz7sOt5GPfzLWPYrf3eCSsmOPGWMg6QriLeEBRbClmRyGv04X2AUpZ9oWILHNc\nPG3QUhiChfBrcujT6RqT6bozH9cj12qsEOLWaY4LAF+YJ3EIgiAIgiAIYlYIAZTgU/8EQSwwSvmd\nf4IgCIIgCIJwPQKl+c4/QRALCwr+CYIgCIIgCKKAGALWf34iCIIoFhT8EwRBEARBEEQBMYzSfeef\nIIiFAwX/BEEQBEEQBFFASvVf/REEsbCg4J8gCIIgCIIgCogQoDv/BEEUHQr+CYIgCIIgCKKAGELQ\nO/8EQRQdCv4JgiAIgiAIooAI0L/6Iwii+FDwTxAEQRAEQRAFhN75JwjCDVDwTxAEQRAEQRAFhN75\nJwjCDVDwTxAEQRAEQRAFhO78EwThBij4JwiCIAiCIIgCYggAFPsTBFFkKPgnCIIgCIIgiAIi6M4/\nQRAugIJ/giAIgiAIgigg9M4/QRBugIJ/giAIgiAIgigg9M4/QRBugIJ/giAIgiAIgigghgAYBf8E\nQRQZ1wb/jLEbGWNHGWNvMsb+u8PxBsbYs4yxVxljhxhjnyiGnARBEARBEASRCSEEAMr3RxBE8XFl\n8M8YkwA8AuDjADYAuJUxtiGl2t8COCCE2ATgFgC751dKgiAIgiAIgsiOEY/96bF/giCKjiuDfwBX\nAXhTCHFCCKEC+D6AT6fUEQCWJP5eCuDdeZSPIAiCIAiCIKbFvPNPCf8Igig2bg3+VwDos33uT5TZ\n+XsA7YyxfgBPArg7U2eMsc8xxroZY92Dg4P5lpVYQJCuELlAekLkCukKkSukKwsX685/nqJ/0hUi\nV0hXiFTcGvznwq0AviWEqAPwCQDfYYw5zkcI8ZgQokUI0VJT8/+zd+9hclT3nfC/v6q+z4zmphnd\nRgJJCBzWkUAanBjHN5w4JM7ayUoQHCnYxIuNCI4Xs8Tx7j6O4/dNNl5els3aRhi9vgYcByR7jWN8\nicGY2BjMjEAyCHQbIc2MhOauufWtqs7+0V01fZ3p7ulL9cz38zx6NF2XU6e6T1WfX5+qX3VUtZJU\nX9hWqBBsJ1QothUqFNvK0mXZ9/yXaeSfbYUKxbZCmdwa/A8CWJ/yuis5LdWHADwCAEqpXwAIAFhZ\nldoRERERERVA8Z5/InIJtwb/zwPYIiIbRcSHREK/xzKWOQvgXQAgIr+GRPDP61mIiIiIyDUsZvsn\nIpdwZfCvlDIA3AHghwBeQSKr/8si8hkReW9ysbsA3CoihwH8E4APKjujChERERGRC9idU478E1Gt\neWpdgXyUUo8jkcgvddqnUv4+CuAt1a4XEREREVGhyn3PPxFRqVw58k9EREREtBQoK/E/R/6JqNYY\n/BMRERERVYg98l+mJ/0REZWMwT8RERERUYXMXfbP6J+IaovBPxERERFRhcwl/KtpNYiIGPwTERER\nEVUKR/6JyC0Y/BMRERERVYj9IGom/COiWmPwT0RERERUIUz4R0RuweCfiIiIiKhCLI78E5FLMPgn\nIiIiIqoQy47+GfsTUY0x+CciIiIiqjCO/BNRrTH4JyIiIiKqEN7zT0RuweCfiIiIiKhCeM8/EbkF\ng38iIiIiogqxR/4Z+xNRrVU0+BcRXUTurOQ2iIiIiIjcSjnBP6N/Iqqtigb/SikTwPtLWVdErheR\nYyJyUkT+Ks8yN4rIURF5WUS+sajKEhERERGVmXIu+69tPYiIPFXYxs9F5PMA/hnAjD1RKXUo3woi\nogP4AoDfATAA4HkReUwpdTRlmS0APgngLUqpcRHprNQOEBERERGVgvf8E5FbVCP4vyr5/2dSpikA\n182zzpsAnFRK9QGAiHwTwPsAHE1Z5lYAX1BKjQOAUmqobDUmIiIiIioDZvsnIreoePCvlHpnCaut\nA9Cf8noAwG9kLHM5AIjIzwHoAD6tlPpBSZUkIiIiIqoAi/f8E5FLVDzbv4isEpEvicj3k6+vFJEP\nlaFoD4AtAN6BRF6B/SLSkqcOHxaRHhHpGR4eLsOmaaliW6FCsJ1QodhWqFBsK0uXKvNl/2wrVCi2\nFcpUjUf9fRXADwGsTb4+DuA/LbDOIID1Ka+7ktNSDQB4TCkVV0qdTpa7JVdhSqkHlVLdSqnujo6O\nIqtPywnbChWC7YQKxbZChWJbWbqckf8ylce2QoViW6FM1Qj+VyqlHgFgAYBSygBgLrDO8wC2iMhG\nEfEBuAnAYxnL/B8kRv0hIiuRuA2gr4z1JiIiIiJaFGfkvxq9biKieVTjNDQjIu1IJPmDiPwmgIvz\nrZD8geAOJK4YeAXAI0qpl0XkMyLy3uRiPwQwKiJHAfwEwN1KqdFK7QQRERERUbF4zz8RuUU1sv1/\nHIlR+83J5HwdAHYttJJS6nEAj2dM+1TK3ypZ9sfLWlsiIiIiojLho/6IyC2qEfyPA3g7gCuQuN3p\nGOYe/0dEREREtGQpPuqPiFyiGpf9HwCwSin1slLqJQBvBvDlKmyXiIiIiKim7JF/KVvKPyKi0lQj\n+L8NwP8RkdUi8vsAPgfg96uwXSIiIiKimuLIPxG5RcUv+1dKPS8ifwHgRwAiAH5bKcUHTRIRERHR\nkueM/POefyKqsYoF/yLyXSQz/CeFkMjy/yURgVLqvbnXJCIiIiJaGjjyT0RuUcmR//+vgmUTERER\nEbmek+2f0T8R1VjFgn+l1E/tv0VkFYBrki9/qZQaqtR2iYiIiIjcwuLIPxG5RMUT/onIjQB+CeAG\nADcCeE5EdlV6u0REREREtWYH/2C2fyKqsYon/APwXwFcY4/2i0gHgB8j8QhAIiIiIqIlyw79OfJP\nRLVWjUf9aRmX+Y9WabtERERERDU1l/CP0T8R1VY1Rv5/ICI/BPBPydd/DOD7VdguEREREVFNWVbi\nfwb/RFRrFQ/+lVJ3i8hOAG9JTnpQKfXtSm+XiIiIiKjW7Hv+GfsTUa1VY+QfSqmDIvKv9vZEpE0p\nNVaNbRMRERER1Yr9qD8G/0RUaxUP/kXkIwD+BkAEgIVEqlMFYFOlt01EREREVFu855+I3KEaI///\nGcAblVIjVdgWEREREZFr2CP/DP6JqNaqkXX/FIDZYlcSketF5JiInBSRv5pnuZ0iokSke1G1JCIi\nIiIqM8vJ9l/jihDRsleNkf9PAnhGRJ4DELUnKqX+It8KIqID+AKA3wEwAOB5EXlMKXU0Y7kmAB8D\n8FwlKk5EREREtBhz9/wz+iei2qpG8P9FAE8C+BUS9/wX4k0ATiql+gBARL4J4H0AjmYs9/8A+CyA\nu8tTVSIiIiKi8lEc+Scil6hG8O9VSn28yHXWAehPeT0A4DdSFxCR7QDWK6W+JyIM/omIiIjIdeYe\n9cfon4hqqxr3/H9fRD4sImtEpM3+t5gCRUQD8D8B3FXg8h8WkR4R6RkeHl7MpmmJY1uhQrCdUKHY\nVqhQbCtLl3IS/pWnPLYVKhTbCmWqRvD/fiTv+wfQk/JvPoMA1qe87kpOszUBeCOAp0TkNQC/CeCx\nfEn/lFIPKqW6lVLdHR0dJe0ELQ9sK1QIthMqFNsKFYptZekqd7Z/thUqFNsKZapG8P8JANuUUhsB\nfAXAYQC7FljneQBbRGSjiPgA3ATgMXumUuqiUmqlUupSpdSlAJ4F8F6l1EI/KhARERERVc3cZf81\nrggRLXvVCP7/m1JqUkR+C8B1AP5/APvmW0EpZQC4A8APAbwC4BGl1Msi8hkReW/Fa0xEREREVAZz\nCf8Y/RNRbVUj4Z+Z/P89APYnE/T9vwutpJR6HMDjGdM+lWfZdyy2kkRERERE5Tb3qL/a1oOIqBoj\n/4Mi8kUAfwzgGWL2lAAAIABJREFUcRHxV2m7REREREQ1pcp8zz8RUamqEYTfiMTl+7+rlJoA0AaA\nj+YjIiIioiWP9/wTkVtU/LJ/pdQsgG+lvD4P4Hylt0tEREREVGu855+I3IKX3xMRERERVUi5H/VH\nRFQqBv9ERERERBXiXPZf43oQETH4JyIiIiKqEI78E5FbMPgnIiIiIqoQ+55/Ya+biGqMpyEiIiIi\nogrho/6IyC0Y/BMRERERVYjlZPuvcUWIaNlj8E9EREREVCG855+I3ILBPxERERFRhdgj/0REtcbg\nn4iIiIiowjjyT0S1xuCfiIiIiKhCLIv3/BOROzD4JyIiIiKqEN7zT0RuweCfiIiIiKhC7Hv+GfsT\nUa25NvgXketF5JiInBSRv8ox/+MiclREjojIEyJySS3qSURERESUj3KCf0b/RFRbrgz+RUQH8AUA\nvwfgSgDvF5ErMxZ7AUC3UmorgAMA/kd1a0lEREREND8F3u9PRO7gyuAfwJsAnFRK9SmlYgC+CeB9\nqQsopX6ilJpNvnwWQFeV60hERERENC9LKY76E5EruDX4XwegP+X1QHJaPh8C8P18M0XkwyLSIyI9\nw8PDZaoiLUVsK1QIthMqFNsKFYptZemyVHlH/tlWqFBsK5TJrcF/wURkD4BuAPfkW0Yp9aBSqlsp\n1d3R0VG9ylHdYVuhQrCdUKHYVqhQbCtLl6UUBOWL/tlWqFBsK5TJU+sK5DEIYH3K667ktDQi8tsA\n/iuAtyulolWqGxERERFRQZRipn8icge3jvw/D2CLiGwUER+AmwA8lrqAiFwN4IsA3quUGqpBHYmI\niIiI5mVZisE/EbmCK4N/pZQB4A4APwTwCoBHlFIvi8hnROS9ycXuAdAI4FEReVFEHstTHBERERFR\nTSSy/TP6J6Lac+tl/1BKPQ7g8Yxpn0r5+7erXikiIiIioiIk7vknIqo9V478ExEREREtBYl7/hn+\nE1HtMfgnIiIiqgNf+tlpPNc3WutqUBGeOTmCrz7zWlkf9UdEVCoG/0RERER14B9+fBzfOpT18CNy\nsUd7B2pdBSIiB4N/IiIiojoQjpsIx81aV4OKEI4lPi8m/CMiN2DwT0RERORyhmkhbioG/3XG/rwY\n+xORGzD4JyIiInI5O4iMMPivK/bIv2mpGteEiIjBPxEREZHr2cH/bIzBfz2ZjRsAgLjJ4J+Iao/B\nPxEREZHLRWIWAGA2ZtS4JlQMe+Q/Zlo1rgkREYN/IiIiItezR5AjcQaR9YSX/RORmzD4JyIiInI5\nO4jkyH99YYJGInITBv9ERERELmcHkQwm6wuv1CAiN2HwT0RERORy9si/fe8/uZ9l8dGMROQuDP6J\niIiIXM4OImOmhd4zYzCYQM7V4qaF506P1boaRERpGPwTERERuVw45RF/O/f9Aj86eqGGtaGF/MuR\nc3j//mdrXQ0iojSuDf5F5HoROSYiJ0Xkr3LM94vIPyfnPycil1a/lkRERESVl3n5+LmJcI1qQoU4\nNxGpdRWIiLJ4al2BXEREB/AFAL8DYADA8yLymFLqaMpiHwIwrpS6TERuAvBZAH9c/doCkYiB0XAM\nIoBSice56Jog4NUABUQMC4al4NEEQZ+GqYgJjyZoCmiYiiTmBTwaLJW4nC/1b48mEAE0EViWgqkU\ndBFomsBSClCAoRQ8mgZdADP5d8y0YFoKXk0gGuD3aAjHrLk6JssRASwF+DSBrgsMUyFuqcS6uoam\ngGAqbCGe3KcGn4bZ2Nz+tAQ1hONA1LCc/dY0wLLgbCvo06AUEI3PlePTBBAgbiq0B30IBFzZFKvK\nbkf2e7tc3pflut82y1IYnYkhZpgIeDVE4nPHV8inIWbMHZM+XYNXF0SSx5tX1+DRAcMETMtCyKun\nnW98Hg1x00o75jUB/N7E+SDfdry6wKfPnYfsbQW9gtmYBa8uiJvKWd+rC5QCDCsxLejREmUpBb+u\nOdO9euI8FTESZQS96eeTkE+DAtLq5vUIPJqkTbPPoz5dQ9CnYSZqIujTYVgKccOCz6OjvcGXOE+m\nvL+p0+tdOY6bxZZR7+uXq4xqSR35B4DRmViNakKFGJ1eOp9PJY+TSh+D9Vx3t4hEDMwYhtM/8WqC\ngE9DJJber9d1SevDNPo1zEQtGCkxh1JAwKNBtET+ElMp6JoGQMHvSe8DBX1aIi5J9jfs+AhQ0ESc\nPotHE3g1AUQQjpvQ7dcALChYFqAA+JN9AABLsl9QKLe20DcBOKmU6gMAEfkmgPcBSA3+3wfg08m/\nDwD4vIiIUqqqD1KNRAycGJ3B5544jg9cuxGfOHgEA+NhdLUG8cCeHQh4NXzwK8870/bt2YGnXrmA\npoCOHRtXYu9Dveho9OMvr78Cdx84kva3vc7n/+RqxA0Ldz5y2Jl2343b4PVouOMbL6RNa2/04cLk\nbNr6X73lGoxMx3PW8bM7t+Jrz5zGLW/ZiLWtQQxdjKRt54E9O/C/nziOHx0dwkfeein+4Kou7H2o\nN22+3yO45as9WWV+4NqN+Nozp3H39W9AzLDwkX+cW++eXVuxstGHAz39+IOrurClvWFJnjALZbej\n1Pd2354dS/59Wa77bbMshWMXpnDr13tw7aZ2/OmbL8Hehw+lHV+mZeHPk8f5u6/sxB3XbcHtKcvs\n270dn3vyBFqCPux58yVZ8wCklfmVD3ZjZEZlHcep25lvWs/pEWy/tD1rOz6P4ENfW/h8dt+N2/B3\nj7+KjiYfPvquy7M++/ZGL/74wWfTyl4R8mL3/ueyzqP/3DuAfbu346lXh9C9sS1tO/tv7saWjkac\nGJ7GrV/vSZt+xaqmuv6iL8dxs9gy6n39cpVRTZkj/6PT0RrVhAoxOrM0Pp9KHieVPgbrue5uEYkY\nGJqNYmI27nzvf+Stl+LfX9WF21L2/b4bt6GlwYdbMmKezyVjiNT44KPXbUHQp6fFR5//k6sR8un4\ns5R44oE9O+D3arjlK887/Ymv/Pw0bn/nZQjHzKy+hc+j4dOPHcXwdBT37NqKtgYvJmYN3PXo4bQ+\ngN+j4eYv/3JJ9QuK4dbL/tcB6E95PZCclnMZpZQB4CKA9qrULsVoOIa9D/Vi5471TlANAAPjYdz2\nUC/6x8Jp0/Y+1Iv3be/CdVeucU4Yt71js9OAU/+21xmfiTsBuT3tzkcOY3wmnjXNUpK1PiB56/iJ\ng0ewc8d63H3gCOKGytrObcn1AGBX9wanzqnzB8YjOcu0/x8YCzuBv71Moo4Rp8zR8NL5hbwUdjvK\nbCtL/X1ZrvttG52JOYHprW/b5ATpwNzxNZZynO/csd758rWX2fvwIezcsR63vm1Tznkj07G0aSJa\nzuN4LON8km/adVeuybkdXdMLOp/d+chh3PaOzdi5Y33Oz940kVV23FA5z6P2/Pdt78razq1f78HQ\ndNR5f1On1/uIaTmOm8WWUe/rl6uMasoc+f/2C4P49b/+ISZm3Vnf5WpkOop/96kf4HtHzte6KmVR\nyeOk0sdgPdfdLUbDMcQMlfa9v6t7gxP4A3Pf7QM5Yh47hkiND/Y+fCgrPrrjGy9gMCOeuO2hXqdM\nuz+xc8d6jM/Ec/YtxmbiuO0dm504Q9d0J/C3l7v16z04Mzq75PoFxXBr8F9WIvJhEekRkZ7h4eGy\nlm1YiU5pS9DrNCTbwHgYIZ+eNU0pBUvNdWZT181VTsinF1y2Jsha1p6Wr4729Fzr2vMBQNek4HrY\nZbYEvfPW3y7TsKp6wUZelWwr87HbUSo3vS+VUq/7Xa52EjNMZ/8LOb7mO4YLPT7zHee5juN8569c\n69s/mC90PrPrm2+elXHxVmrZmfVYqE5x08o5PWZU79FblTinlOO4WWwZ9b5+ucoop4XaSubIf9xU\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wDP1j4bTv0p071md9f9994AgGxsJZfYnrrlzjvL7r0cNp/YTMvoQ9L7Ofs6t7AwbGwvPG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\nb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s28iMVvfKX4fs28aErjiTcgRsjP3rNpH7wBc+RhAzo+bsAERaGeosLR4A8F/04TK/+Z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\n",
            "text/plain": [
              "<Figure size 1008x1008 with 56 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T2UJIGH7kFxp",
        "colab_type": "code",
        "outputId": "08ec0ede-19a7-4f89-8779-d9f365bd1405",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "source": [
        "train_dataset"
      ],
      "execution_count": 0,
      "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>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>bmi</th>\n",
              "      <th>children</th>\n",
              "      <th>smoker</th>\n",
              "      <th>region</th>\n",
              "      <th>charges</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1293</th>\n",
              "      <td>46</td>\n",
              "      <td>1</td>\n",
              "      <td>25.745</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2.356194</td>\n",
              "      <td>9301.89355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>361</th>\n",
              "      <td>35</td>\n",
              "      <td>1</td>\n",
              "      <td>30.500</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3.926991</td>\n",
              "      <td>4751.07000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>802</th>\n",
              "      <td>21</td>\n",
              "      <td>1</td>\n",
              "      <td>22.300</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3.926991</td>\n",
              "      <td>2103.08000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>623</th>\n",
              "      <td>18</td>\n",
              "      <td>1</td>\n",
              "      <td>33.535</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.785398</td>\n",
              "      <td>34617.84065</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>735</th>\n",
              "      <td>49</td>\n",
              "      <td>2</td>\n",
              "      <td>34.770</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2.356194</td>\n",
              "      <td>9583.89330</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>979</th>\n",
              "      <td>36</td>\n",
              "      <td>2</td>\n",
              "      <td>29.920</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>5.497787</td>\n",
              "      <td>4889.03680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>54</td>\n",
              "      <td>1</td>\n",
              "      <td>39.600</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3.926991</td>\n",
              "      <td>10450.55200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>171</th>\n",
              "      <td>49</td>\n",
              "      <td>1</td>\n",
              "      <td>30.300</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3.926991</td>\n",
              "      <td>8116.68000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>265</th>\n",
              "      <td>46</td>\n",
              "      <td>1</td>\n",
              "      <td>42.350</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>5.497787</td>\n",
              "      <td>46151.12450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>585</th>\n",
              "      <td>33</td>\n",
              "      <td>2</td>\n",
              "      <td>28.270</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5.497787</td>\n",
              "      <td>4779.60230</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1070 rows × 7 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      age  sex     bmi  children  smoker    region      charges\n",
              "1293   46    1  25.745         3       0  2.356194   9301.89355\n",
              "361    35    1  30.500         1       0  3.926991   4751.07000\n",
              "802    21    1  22.300         1       0  3.926991   2103.08000\n",
              "623    18    1  33.535         0       1  0.785398  34617.84065\n",
              "735    49    2  34.770         1       0  2.356194   9583.89330\n",
              "...   ...  ...     ...       ...     ...       ...          ...\n",
              "979    36    2  29.920         0       0  5.497787   4889.03680\n",
              "162    54    1  39.600         1       0  3.926991  10450.55200\n",
              "171    49    1  30.300         0       0  3.926991   8116.68000\n",
              "265    46    1  42.350         3       1  5.497787  46151.12450\n",
              "585    33    2  28.270         1       0  5.497787   4779.60230\n",
              "\n",
              "[1070 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZPzyen-Vd0Io",
        "colab_type": "text"
      },
      "source": [
        "If we look at the above table, we see that BMI and charges have an intriguing pattern.\n",
        "\n",
        "We also inspect at their statistical description:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q7FTmLoaXx4g",
        "colab_type": "code",
        "outputId": "e7246bee-b1ff-461f-e4eb-09cece044256",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        }
      },
      "source": [
        "train_stats = train_dataset.describe()\n",
        "train_stats.pop('charges')\n",
        "\n",
        "# for pretty output\n",
        "train_stats = train_stats.transpose()\n",
        "train_stats"
      ],
      "execution_count": 0,
      "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>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>age</th>\n",
              "      <td>1070.0</td>\n",
              "      <td>38.943925</td>\n",
              "      <td>14.062091</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>26.000000</td>\n",
              "      <td>39.000000</td>\n",
              "      <td>51.000000</td>\n",
              "      <td>64.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <td>1070.0</td>\n",
              "      <td>1.495327</td>\n",
              "      <td>0.500212</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bmi</th>\n",
              "      <td>1070.0</td>\n",
              "      <td>30.696785</td>\n",
              "      <td>6.157567</td>\n",
              "      <td>15.960000</td>\n",
              "      <td>26.237500</td>\n",
              "      <td>30.400000</td>\n",
              "      <td>34.700000</td>\n",
              "      <td>53.130000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>children</th>\n",
              "      <td>1070.0</td>\n",
              "      <td>1.080374</td>\n",
              "      <td>1.206890</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>smoker</th>\n",
              "      <td>1070.0</td>\n",
              "      <td>0.203738</td>\n",
              "      <td>0.402965</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>region</th>\n",
              "      <td>1070.0</td>\n",
              "      <td>3.182698</td>\n",
              "      <td>1.799384</td>\n",
              "      <td>0.785398</td>\n",
              "      <td>0.785398</td>\n",
              "      <td>3.926991</td>\n",
              "      <td>5.497787</td>\n",
              "      <td>5.497787</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           count       mean        std  ...        50%        75%        max\n",
              "age       1070.0  38.943925  14.062091  ...  39.000000  51.000000  64.000000\n",
              "sex       1070.0   1.495327   0.500212  ...   1.000000   2.000000   2.000000\n",
              "bmi       1070.0  30.696785   6.157567  ...  30.400000  34.700000  53.130000\n",
              "children  1070.0   1.080374   1.206890  ...   1.000000   2.000000   5.000000\n",
              "smoker    1070.0   0.203738   0.402965  ...   0.000000   0.000000   1.000000\n",
              "region    1070.0   3.182698   1.799384  ...   3.926991   5.497787   5.497787\n",
              "\n",
              "[6 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mtyJH96doYzP",
        "colab_type": "text"
      },
      "source": [
        "### Split features from labels\n",
        "\n",
        "Separate the target value, or \"label\", from features. In this case, we assume our target value is `charges`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zjjp8sK6jG6a",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Remember that .pop method will extract the value not the labels!\n",
        "\n",
        "train_labels = train_dataset.pop('charges')\n",
        "test_labels = test_dataset.pop('charges')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M3fL6Fa-Ek7l",
        "colab_type": "code",
        "outputId": "58bbe25b-0a4f-4bcf-f640-d342c7c11688",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "source": [
        "test_labels"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       16884.92400\n",
              "6        8240.58960\n",
              "7        7281.50560\n",
              "24       6203.90175\n",
              "29      38711.00000\n",
              "           ...     \n",
              "1305     2464.61880\n",
              "1306    16115.30450\n",
              "1327     9377.90470\n",
              "1331    10795.93733\n",
              "1332    11411.68500\n",
              "Name: charges, Length: 268, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2DjgkfdYpr9b",
        "colab_type": "text"
      },
      "source": [
        "### Normalize the data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XJjXQ4wFpzTC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def normalize(x_val):\n",
        "    return (x_val - train_stats['mean']) / train_stats['std']\n",
        "\n",
        "normed_train_data = normalize(train_dataset)\n",
        "normed_test_data = normalize(test_dataset)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jm9U0OUw7saq",
        "colab_type": "code",
        "outputId": "d1cfedd2-95a5-40fc-9aaa-a789b8456982",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "source": [
        "normed_train_data"
      ],
      "execution_count": 0,
      "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>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>bmi</th>\n",
              "      <th>children</th>\n",
              "      <th>smoker</th>\n",
              "      <th>region</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1293</th>\n",
              "      <td>0.501780</td>\n",
              "      <td>-0.990234</td>\n",
              "      <td>-0.804179</td>\n",
              "      <td>1.590556</td>\n",
              "      <td>-0.505598</td>\n",
              "      <td>-0.459326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>361</th>\n",
              "      <td>-0.280465</td>\n",
              "      <td>-0.990234</td>\n",
              "      <td>-0.031958</td>\n",
              "      <td>-0.066596</td>\n",
              "      <td>-0.505598</td>\n",
              "      <td>0.413638</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>802</th>\n",
              "      <td>-1.276050</td>\n",
              "      <td>-0.990234</td>\n",
              "      <td>-1.363653</td>\n",
              "      <td>-0.066596</td>\n",
              "      <td>-0.505598</td>\n",
              "      <td>0.413638</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>623</th>\n",
              "      <td>-1.489389</td>\n",
              "      <td>-0.990234</td>\n",
              "      <td>0.460931</td>\n",
              "      <td>-0.895172</td>\n",
              "      <td>1.976007</td>\n",
              "      <td>-1.332289</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>735</th>\n",
              "      <td>0.715119</td>\n",
              "      <td>1.008918</td>\n",
              "      <td>0.661497</td>\n",
              "      <td>-0.066596</td>\n",
              "      <td>-0.505598</td>\n",
              "      <td>-0.459326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>979</th>\n",
              "      <td>-0.209352</td>\n",
              "      <td>1.008918</td>\n",
              "      <td>-0.126151</td>\n",
              "      <td>-0.895172</td>\n",
              "      <td>-0.505598</td>\n",
              "      <td>1.286601</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>1.070685</td>\n",
              "      <td>-0.990234</td>\n",
              "      <td>1.445898</td>\n",
              "      <td>-0.066596</td>\n",
              "      <td>-0.505598</td>\n",
              "      <td>0.413638</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>171</th>\n",
              "      <td>0.715119</td>\n",
              "      <td>-0.990234</td>\n",
              "      <td>-0.064439</td>\n",
              "      <td>-0.895172</td>\n",
              "      <td>-0.505598</td>\n",
              "      <td>0.413638</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>265</th>\n",
              "      <td>0.501780</td>\n",
              "      <td>-0.990234</td>\n",
              "      <td>1.892503</td>\n",
              "      <td>1.590556</td>\n",
              "      <td>1.976007</td>\n",
              "      <td>1.286601</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>585</th>\n",
              "      <td>-0.422691</td>\n",
              "      <td>1.008918</td>\n",
              "      <td>-0.394114</td>\n",
              "      <td>-0.066596</td>\n",
              "      <td>-0.505598</td>\n",
              "      <td>1.286601</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1070 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "           age       sex       bmi  children    smoker    region\n",
              "1293  0.501780 -0.990234 -0.804179  1.590556 -0.505598 -0.459326\n",
              "361  -0.280465 -0.990234 -0.031958 -0.066596 -0.505598  0.413638\n",
              "802  -1.276050 -0.990234 -1.363653 -0.066596 -0.505598  0.413638\n",
              "623  -1.489389 -0.990234  0.460931 -0.895172  1.976007 -1.332289\n",
              "735   0.715119  1.008918  0.661497 -0.066596 -0.505598 -0.459326\n",
              "...        ...       ...       ...       ...       ...       ...\n",
              "979  -0.209352  1.008918 -0.126151 -0.895172 -0.505598  1.286601\n",
              "162   1.070685 -0.990234  1.445898 -0.066596 -0.505598  0.413638\n",
              "171   0.715119 -0.990234 -0.064439 -0.895172 -0.505598  0.413638\n",
              "265   0.501780 -0.990234  1.892503  1.590556  1.976007  1.286601\n",
              "585  -0.422691  1.008918 -0.394114 -0.066596 -0.505598  1.286601\n",
              "\n",
              "[1070 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-FkTXsNvzxnH",
        "colab_type": "text"
      },
      "source": [
        "## Regression model\n",
        "\n",
        "### Construct the model\n",
        "\n",
        "In this model we use the model with two densely connected hidden layars (`layer.Dense(64)`), and an output layer that returns a single continous value (`layer.Dense(1)`)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U911cB9VqFZl",
        "colab_type": "code",
        "outputId": "523eb409-2e4e-409b-d76c-a57b9cfb76ba",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "train_dataset.keys()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['age', 'sex', 'bmi', 'children', 'smoker', 'region'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZSftOajG0uEi",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# relu = rectifier linear unit activation function\n",
        "# The first argument of RMSprop algorithm is learning rate.\n",
        "# You can check the creator of RMSprop (Root Mean Square propagation) in \n",
        "# his lecture. Hinton is known as a \"Godfather of AI\"\n",
        "# https://www.youtube.com/watch?v=XhZahXzEuNo\n",
        "\n",
        "# mse and mae are metrics\n",
        "# mse = mean squared error\n",
        "# mae = mean absoulte error\n",
        "\n",
        "def construct_model():\n",
        "    reg_model = keras.Sequential([\n",
        "        layers.Dense(64, activation='relu', \n",
        "                     input_shape=[len(train_dataset.keys())]),\n",
        "        layers.Dense(64, activation='relu'),\n",
        "        layers.Dense(1)\n",
        "    ])\n",
        "\n",
        "    optimizer = tf.keras.optimizers.RMSprop(.001)\n",
        "\n",
        "    reg_model.compile(loss='mse', optimizer=optimizer,\n",
        "                  metrics=['mae', 'mse'])\n",
        "    \n",
        "    return reg_model"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6eFVr16E3q4S",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "reg_model = construct_model()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gOZfcxTx35HX",
        "colab_type": "text"
      },
      "source": [
        "### Inspect the regression model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZBopaN9c30uY",
        "colab_type": "code",
        "outputId": "ddb1c891-d9f2-4fca-caac-6e0eb98b45e0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        }
      },
      "source": [
        "reg_model.summary()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential_2\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense_6 (Dense)              (None, 64)                448       \n",
            "_________________________________________________________________\n",
            "dense_7 (Dense)              (None, 64)                4160      \n",
            "_________________________________________________________________\n",
            "dense_8 (Dense)              (None, 1)                 65        \n",
            "=================================================================\n",
            "Total params: 4,673\n",
            "Trainable params: 4,673\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_5ymap9w4IFt",
        "colab_type": "text"
      },
      "source": [
        "Now we try out the regression model by taking a batch of 5 samples from the training data and call `reg_model.predict()`.\n",
        "\n",
        "> **Note**\n",
        ">\n",
        ">In offline platform, we have to cast the format of `normed_train_data` into numpy array."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8yzpnang4BtY",
        "colab_type": "code",
        "outputId": "1b426496-3b05-4344-fad3-e136907c246e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        }
      },
      "source": [
        "example_batch = normed_train_data[:5]\n",
        "example_result = reg_model.predict(example_batch)\n",
        "example_result"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-0.33743232],\n",
              "       [-0.15567961],\n",
              "       [-0.3412    ],\n",
              "       [-0.44432744],\n",
              "       [-0.00998501]], dtype=float32)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4AXmJiq742cI",
        "colab_type": "text"
      },
      "source": [
        "Quick check on the shape and data type shows that the regression model seems to be working. \n",
        "\n",
        "### Train the regression model\n",
        "\n",
        "We will train the regression model for 2000 epochs, and record the training and validation accuracy in the `history` object.\n",
        "\n",
        "> **Note**\n",
        ">\n",
        ">In offline platform, we have to cast the format of `normed_train_data` and `train_label` into numpy array.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eCh0Rv7R4roj",
        "colab_type": "code",
        "outputId": "06d8104d-afab-44b2-ad17-cc6208211450",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "EPOCHS = 4000\n",
        "\n",
        "# the validation_split will split for the data for validation\n",
        "# from the last samples of normed_train_data. This smaller\n",
        "# splitted data will be used in the validation process.\n",
        "\n",
        "start_compute = time.time()\n",
        "\n",
        "history = reg_model.fit(\n",
        "    normed_train_data, train_labels, epochs=EPOCHS,\n",
        "    validation_split=0.2, verbose=0,\n",
        "    callbacks=[tfdocs.modeling.EpochDots()]\n",
        ")\n",
        "\n",
        "print('Approximation computational time: {:.2f} s'.format(time.time() \n",
        "                                                         - start_compute))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Epoch: 0, loss:328287425.7944,  mae:13307.9336,  mse:328287392.0000,  val_loss:323582397.9065,  val_mae:12969.2461,  val_mse:323582400.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 100, loss:34385614.2804,  mae:3895.6562,  mse:34385616.0000,  val_loss:30368397.3458,  val_mae:3667.2400,  val_mse:30368400.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 200, loss:31212977.5327,  mae:3586.3752,  mse:31212978.0000,  val_loss:28467005.7850,  val_mae:3474.4321,  val_mse:28467006.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 300, loss:27162034.5421,  mae:3136.7605,  mse:27162034.0000,  val_loss:25866958.2430,  val_mae:3163.5667,  val_mse:25866960.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 400, loss:24536018.6168,  mae:2954.8369,  mse:24536016.0000,  val_loss:23725177.6822,  val_mae:2996.3418,  val_mse:23725178.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 500, loss:23361817.0280,  mae:2872.4424,  mse:23361816.0000,  val_loss:22510921.4486,  val_mae:2895.5059,  val_mse:22510922.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 600, loss:22710738.9907,  mae:2808.1741,  mse:22710740.0000,  val_loss:21898630.8785,  val_mae:2862.7458,  val_mse:21898630.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 700, loss:22250374.6822,  mae:2769.4536,  mse:22250374.0000,  val_loss:21481235.1869,  val_mae:2829.6416,  val_mse:21481236.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 800, loss:21776203.7103,  mae:2714.8120,  mse:21776202.0000,  val_loss:21144195.5607,  val_mae:2796.5569,  val_mse:21144194.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 900, loss:21289030.0374,  mae:2671.2063,  mse:21289030.0000,  val_loss:20813708.7103,  val_mae:2757.8987,  val_mse:20813710.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1000, loss:20751779.9556,  mae:2609.1023,  mse:20751778.0000,  val_loss:20457120.6636,  val_mae:2721.0422,  val_mse:20457120.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1100, loss:20160778.3084,  mae:2539.2859,  mse:20160778.0000,  val_loss:19966589.1963,  val_mae:2639.5549,  val_mse:19966590.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1200, loss:19648886.6449,  mae:2489.8770,  mse:19648886.0000,  val_loss:19534519.9720,  val_mae:2593.3379,  val_mse:19534520.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1300, loss:19266097.1121,  mae:2443.5264,  mse:19266098.0000,  val_loss:19229086.8972,  val_mae:2535.4612,  val_mse:19229086.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1400, loss:18992581.6636,  mae:2404.8352,  mse:18992584.0000,  val_loss:19091228.5327,  val_mae:2505.6855,  val_mse:19091228.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1500, loss:18802998.5514,  mae:2423.6201,  mse:18803000.0000,  val_loss:18983147.8037,  val_mae:2501.4067,  val_mse:18983148.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1600, loss:18632925.3738,  mae:2371.8284,  mse:18632928.0000,  val_loss:18941376.4486,  val_mae:2486.6875,  val_mse:18941376.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1700, loss:18457482.8084,  mae:2413.6177,  mse:18457484.0000,  val_loss:18954866.0467,  val_mae:2461.7332,  val_mse:18954868.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1800, loss:18338544.4159,  mae:2361.0369,  mse:18338544.0000,  val_loss:19016880.4019,  val_mae:2446.0442,  val_mse:19016882.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 1900, loss:18212548.5607,  mae:2328.9983,  mse:18212546.0000,  val_loss:19122816.5607,  val_mae:2467.9187,  val_mse:19122818.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2000, loss:18105904.4299,  mae:2316.5117,  mse:18105906.0000,  val_loss:19169922.2617,  val_mae:2460.3420,  val_mse:19169922.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2100, loss:17944330.4860,  mae:2322.0259,  mse:17944330.0000,  val_loss:19207765.6542,  val_mae:2469.2324,  val_mse:19207764.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2200, loss:17825433.2991,  mae:2305.2905,  mse:17825432.0000,  val_loss:19306943.6916,  val_mae:2468.4380,  val_mse:19306944.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2300, loss:17719520.5701,  mae:2290.4485,  mse:17719522.0000,  val_loss:19442293.6822,  val_mae:2490.1182,  val_mse:19442294.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2400, loss:17608070.2243,  mae:2279.3352,  mse:17608068.0000,  val_loss:19452415.4206,  val_mae:2481.7607,  val_mse:19452416.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2500, loss:17494353.5981,  mae:2273.4966,  mse:17494354.0000,  val_loss:19483299.5607,  val_mae:2494.6799,  val_mse:19483300.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2600, loss:17377484.4766,  mae:2272.2615,  mse:17377484.0000,  val_loss:19487659.8879,  val_mae:2457.3650,  val_mse:19487660.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2700, loss:17234043.2617,  mae:2245.2039,  mse:17234044.0000,  val_loss:19542602.1495,  val_mae:2488.1006,  val_mse:19542602.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2800, loss:17108733.4907,  mae:2250.2200,  mse:17108734.0000,  val_loss:19574478.6355,  val_mae:2474.1016,  val_mse:19574478.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 2900, loss:16978221.2150,  mae:2236.6204,  mse:16978220.0000,  val_loss:19603899.8505,  val_mae:2488.0879,  val_mse:19603900.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3000, loss:16843776.2103,  mae:2261.5110,  mse:16843778.0000,  val_loss:19652600.4112,  val_mae:2468.8450,  val_mse:19652600.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3100, loss:16732596.5654,  mae:2222.6074,  mse:16732595.0000,  val_loss:19712152.8131,  val_mae:2493.1843,  val_mse:19712154.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3200, loss:16642363.1495,  mae:2213.6038,  mse:16642364.0000,  val_loss:19736033.1589,  val_mae:2500.3313,  val_mse:19736032.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3300, loss:16533796.0467,  mae:2232.2131,  mse:16533795.0000,  val_loss:19776054.6262,  val_mae:2451.6262,  val_mse:19776054.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3400, loss:16452338.1939,  mae:2216.9385,  mse:16452338.0000,  val_loss:19839954.1215,  val_mae:2469.8625,  val_mse:19839954.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3500, loss:16361555.4299,  mae:2200.2368,  mse:16361557.0000,  val_loss:19920953.2056,  val_mae:2488.3228,  val_mse:19920954.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3600, loss:16238422.8879,  mae:2195.3567,  mse:16238421.0000,  val_loss:20045249.9720,  val_mae:2511.7295,  val_mse:20045250.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3700, loss:16137134.3458,  mae:2215.5752,  mse:16137135.0000,  val_loss:20136071.0748,  val_mae:2505.5808,  val_mse:20136070.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3800, loss:16034859.8505,  mae:2202.9016,  mse:16034861.0000,  val_loss:20281287.3271,  val_mae:2496.6379,  val_mse:20281286.0000,  \n",
            "....................................................................................................\n",
            "Epoch: 3900, loss:15941434.7290,  mae:2172.8674,  mse:15941435.0000,  val_loss:20365889.1028,  val_mae:2514.4890,  val_mse:20365890.0000,  \n",
            "....................................................................................................Approximation computational time: 211.41 s\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r7kvjvqn8neK",
        "colab_type": "text"
      },
      "source": [
        "We visualize the regression model's training progress using the progress that stored in the `history` object."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xqa9cs1o80On",
        "colab_type": "code",
        "outputId": "f37c992f-e0cb-4412-8f30-18fb533c689f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        }
      },
      "source": [
        "hist = pd.DataFrame(history.history)\n",
        "hist['epoch'] = history.epoch\n",
        "hist.tail()"
      ],
      "execution_count": 0,
      "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>loss</th>\n",
              "      <th>mae</th>\n",
              "      <th>mse</th>\n",
              "      <th>val_loss</th>\n",
              "      <th>val_mae</th>\n",
              "      <th>val_mse</th>\n",
              "      <th>epoch</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3995</th>\n",
              "      <td>1.585593e+07</td>\n",
              "      <td>2172.849121</td>\n",
              "      <td>15855931.0</td>\n",
              "      <td>2.043693e+07</td>\n",
              "      <td>2506.919678</td>\n",
              "      <td>20436928.0</td>\n",
              "      <td>3995</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3996</th>\n",
              "      <td>1.586093e+07</td>\n",
              "      <td>2175.238281</td>\n",
              "      <td>15860937.0</td>\n",
              "      <td>2.044698e+07</td>\n",
              "      <td>2523.964844</td>\n",
              "      <td>20446984.0</td>\n",
              "      <td>3996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3997</th>\n",
              "      <td>1.584793e+07</td>\n",
              "      <td>2183.042969</td>\n",
              "      <td>15847924.0</td>\n",
              "      <td>2.046164e+07</td>\n",
              "      <td>2531.564209</td>\n",
              "      <td>20461640.0</td>\n",
              "      <td>3997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>1.585962e+07</td>\n",
              "      <td>2178.803711</td>\n",
              "      <td>15859617.0</td>\n",
              "      <td>2.045297e+07</td>\n",
              "      <td>2529.616455</td>\n",
              "      <td>20452974.0</td>\n",
              "      <td>3998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3999</th>\n",
              "      <td>1.584975e+07</td>\n",
              "      <td>2194.208008</td>\n",
              "      <td>15849754.0</td>\n",
              "      <td>2.043116e+07</td>\n",
              "      <td>2509.615967</td>\n",
              "      <td>20431160.0</td>\n",
              "      <td>3999</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              loss          mae         mse  ...      val_mae     val_mse  epoch\n",
              "3995  1.585593e+07  2172.849121  15855931.0  ...  2506.919678  20436928.0   3995\n",
              "3996  1.586093e+07  2175.238281  15860937.0  ...  2523.964844  20446984.0   3996\n",
              "3997  1.584793e+07  2183.042969  15847924.0  ...  2531.564209  20461640.0   3997\n",
              "3998  1.585962e+07  2178.803711  15859617.0  ...  2529.616455  20452974.0   3998\n",
              "3999  1.584975e+07  2194.208008  15849754.0  ...  2509.615967  20431160.0   3999\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VswpdL3G8-CW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "plotter = tfdocs.plots.HistoryPlotter(smoothing_std=2)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tA4Exe-l9GgP",
        "colab_type": "code",
        "outputId": "35b3fa95-2a92-41d9-e4bd-c1914d937ed3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        }
      },
      "source": [
        "plotter.plot({'Basic': history}, metric='mae')\n",
        "plt.ylim([2e3, 3e3])\n",
        "plt.ylabel('MAE [charges]');"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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QQY0Uj9KCXBfZBgdrLd9sPXFZ5XxdbHlxfDgFZVW8szqB2ZuT1BwMRWnmzOmz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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KkbE7Kqz9S59",
        "colab_type": "code",
        "outputId": "a875aa4c-7186-48ca-eadb-c753652ed50c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        }
      },
      "source": [
        "plotter.plot({'Basic': history}, metric='mse')\n",
        "plt.ylim([1.5e7, 4e7])\n",
        "plt.ylabel('MSE [charges^2]')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'MSE [charges^2]')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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e1u4v44pxOeSnx/GruVto8PnDHZpSSnWKQG0Edzfb/0OLc/+vvRcWq+7kOWCz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\nRK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vHD0cA4v-u25",
        "colab_type": "text"
      },
      "source": [
        "In the graphs above, we can notice that there is a little decreasing on the long run of epochs. Since we are constrained by time. We conclude that \n",
        "MSE might not be converge. From two metrics above we also easily notice that their value is really big numbers even though we have normalize the datasets.\n",
        "\n",
        "The next step, we want to see how well that regression model generalizes the `test` set.\n",
        "\n",
        "> **Note**\n",
        ">\n",
        ">Sometimes, we have to cast the format of `normed_test_data` and `test_label` into numpy array. The correct procure is\n",
        ">\n",
        "> `x_array = np.asarray(x_list)`\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ld6pvqJM9yJp",
        "colab_type": "code",
        "outputId": "230543db-754d-489b-b7a7-c2de595fc7ed",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        }
      },
      "source": [
        "normed_test_data_np_arr = np.asarray(normed_test_data, dtype=float)\n",
        "test_labels_np_arr = np.asarray(test_labels, dtype=float)\n",
        "\n",
        "loss, mae, mse = reg_model.evaluate(normed_test_data_np_arr, test_labels_np_arr, \n",
        "                                    verbose=2)\n",
        "\n",
        "print(\"Testing set Mean Abs Error: {:5.2f} (charges)\".format(mae))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "268/268 - 0s - loss: 23027157.4254 - mae: 2711.8274 - mse: 23027156.0000\n",
            "Testing set Mean Abs Error: 2711.83 (charges)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rBHc2nAwIyP_",
        "colab_type": "text"
      },
      "source": [
        "### Make prediction\n",
        "\n",
        "Finally, we predict the charges of medical cost using data in the testing set."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fds06mu-Dr23",
        "colab_type": "code",
        "outputId": "becac38a-4a0b-4c27-dfc7-b71b591cc51a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        }
      },
      "source": [
        "test_predictions = reg_model.predict(normed_test_data_np_arr).flatten()\n",
        "\n",
        "a = plt.axes(aspect='equal')\n",
        "\n",
        "plt.scatter(test_labels, test_predictions)\n",
        "\n",
        "plt.xlabel('True Values [charges]')\n",
        "plt.ylabel('Predictions [charges]')\n",
        "lims = [0, 6e4]\n",
        "plt.xlim(lims)\n",
        "plt.ylim(lims)\n",
        "\n",
        "_ = plt.plot(lims, lims)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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yUsxONkkoNZg0X2yXLyh2BoKLVUIK/WAH6iROK2dUS4rhJWkEk/ryH2cguFgN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\n/wFtgebLBFbcaAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0FGdqjnbJ4Nu",
        "colab_type": "text"
      },
      "source": [
        "We see on the graph there are some points are not align with the diagonal line. It means the regression model has a big error on predicting that data.\n",
        "\n",
        "The next step is taking an inspection at the error distribution."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w8mXWtfmJw8R",
        "colab_type": "code",
        "outputId": "5094980b-efe1-475a-a01a-e467f62c990f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "error = test_predictions - test_labels\n",
        "\n",
        "plt.hist(error, bins=25)\n",
        "plt.xlabel('Prediction Error [charges]')\n",
        "_ = plt.ylabel('Count')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YI6MyHCiKmhs",
        "colab_type": "text"
      },
      "source": [
        "This error is not quite gaussian, because our number of data is relatively small.\n",
        "\n",
        "## Conclusion"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J0HRN5XPKbdw",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}