Data-Mining/Real-Estate-Pricing.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Real-Estate-Pricing.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "XVZF9F3F5Z94",
        "colab_type": "code",
        "outputId": "371e1d88-f3d7-44a8-eba8-d96808426943",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        }
      },
      "source": [
        "from google.colab import drive \n",
        "drive.mount('/mntDrive') \n",
        "!ls \"/mntDrive/My Drive/Colab Notebooks\""
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /mntDrive; to attempt to forcibly remount, call drive.mount(\"/mntDrive\", force_remount=True).\n",
            " ApacheSpark\t\t\t\t    Linear-Regression.ipynb\n",
            " Apriori-Algorithm.ipynb\t\t    Mean-Square-Method.ipynb\n",
            " Apriori-ARM-Assignment.ipynb\t\t    pima1.csv\n",
            "'car data.csv'\t\t\t\t    Real-Estate-Pricing.ipynb\n",
            " Cosmetics.xlsx\t\t\t\t    real.xlsx\n",
            " Introduction-To-Data-PreProcessing.ipynb   salary_data.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1en5gzxT6143",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LY9UF1o-7PWI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df = pd.read_excel('/mntDrive/My Drive/Colab Notebooks/real.xlsx')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h_UT3VMf7cUJ",
        "colab_type": "code",
        "outputId": "bdf55424-a888-43fb-d29c-be9306e3f26f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "source": [
        "df"
      ],
      "execution_count": 23,
      "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>street</th>\n",
              "      <th>city</th>\n",
              "      <th>zip</th>\n",
              "      <th>state</th>\n",
              "      <th>beds</th>\n",
              "      <th>baths</th>\n",
              "      <th>sq__ft</th>\n",
              "      <th>type</th>\n",
              "      <th>sale_date</th>\n",
              "      <th>price</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3526 HIGH ST</td>\n",
              "      <td>SACRAMENTO</td>\n",
              "      <td>95838</td>\n",
              "      <td>CA</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>836</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Wed May 21 00:00:00 EDT 2008</td>\n",
              "      <td>59222</td>\n",
              "      <td>38.631913</td>\n",
              "      <td>-121.434879</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>51 OMAHA CT</td>\n",
              "      <td>SACRAMENTO</td>\n",
              "      <td>95823</td>\n",
              "      <td>CA</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1167</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Wed May 21 00:00:00 EDT 2008</td>\n",
              "      <td>68212</td>\n",
              "      <td>38.478902</td>\n",
              "      <td>-121.431028</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2796 BRANCH ST</td>\n",
              "      <td>SACRAMENTO</td>\n",
              "      <td>95815</td>\n",
              "      <td>CA</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>796</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Wed May 21 00:00:00 EDT 2008</td>\n",
              "      <td>68880</td>\n",
              "      <td>38.618305</td>\n",
              "      <td>-121.443839</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2805 JANETTE WAY</td>\n",
              "      <td>SACRAMENTO</td>\n",
              "      <td>95815</td>\n",
              "      <td>CA</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>852</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Wed May 21 00:00:00 EDT 2008</td>\n",
              "      <td>69307</td>\n",
              "      <td>38.616835</td>\n",
              "      <td>-121.439146</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6001 MCMAHON DR</td>\n",
              "      <td>SACRAMENTO</td>\n",
              "      <td>95824</td>\n",
              "      <td>CA</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>797</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Wed May 21 00:00:00 EDT 2008</td>\n",
              "      <td>81900</td>\n",
              "      <td>38.519470</td>\n",
              "      <td>-121.435768</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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>980</th>\n",
              "      <td>9169 GARLINGTON CT</td>\n",
              "      <td>SACRAMENTO</td>\n",
              "      <td>95829</td>\n",
              "      <td>CA</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>2280</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Thu May 15 00:00:00 EDT 2008</td>\n",
              "      <td>232425</td>\n",
              "      <td>38.457679</td>\n",
              "      <td>-121.359620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>981</th>\n",
              "      <td>6932 RUSKUT WAY</td>\n",
              "      <td>SACRAMENTO</td>\n",
              "      <td>95823</td>\n",
              "      <td>CA</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>1477</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Thu May 15 00:00:00 EDT 2008</td>\n",
              "      <td>234000</td>\n",
              "      <td>38.499893</td>\n",
              "      <td>-121.458890</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>982</th>\n",
              "      <td>7933 DAFFODIL WAY</td>\n",
              "      <td>CITRUS HEIGHTS</td>\n",
              "      <td>95610</td>\n",
              "      <td>CA</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>1216</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Thu May 15 00:00:00 EDT 2008</td>\n",
              "      <td>235000</td>\n",
              "      <td>38.708824</td>\n",
              "      <td>-121.256803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>983</th>\n",
              "      <td>8304 RED FOX WAY</td>\n",
              "      <td>ELK GROVE</td>\n",
              "      <td>95758</td>\n",
              "      <td>CA</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1685</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Thu May 15 00:00:00 EDT 2008</td>\n",
              "      <td>235301</td>\n",
              "      <td>38.417000</td>\n",
              "      <td>-121.397424</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>984</th>\n",
              "      <td>3882 YELLOWSTONE LN</td>\n",
              "      <td>EL DORADO HILLS</td>\n",
              "      <td>95762</td>\n",
              "      <td>CA</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>1362</td>\n",
              "      <td>Residential</td>\n",
              "      <td>Thu May 15 00:00:00 EDT 2008</td>\n",
              "      <td>235738</td>\n",
              "      <td>38.655245</td>\n",
              "      <td>-121.075915</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>985 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                  street             city    zip  ...   price   latitude   longitude\n",
              "0           3526 HIGH ST       SACRAMENTO  95838  ...   59222  38.631913 -121.434879\n",
              "1            51 OMAHA CT       SACRAMENTO  95823  ...   68212  38.478902 -121.431028\n",
              "2         2796 BRANCH ST       SACRAMENTO  95815  ...   68880  38.618305 -121.443839\n",
              "3       2805 JANETTE WAY       SACRAMENTO  95815  ...   69307  38.616835 -121.439146\n",
              "4        6001 MCMAHON DR       SACRAMENTO  95824  ...   81900  38.519470 -121.435768\n",
              "..                   ...              ...    ...  ...     ...        ...         ...\n",
              "980   9169 GARLINGTON CT       SACRAMENTO  95829  ...  232425  38.457679 -121.359620\n",
              "981      6932 RUSKUT WAY       SACRAMENTO  95823  ...  234000  38.499893 -121.458890\n",
              "982    7933 DAFFODIL WAY   CITRUS HEIGHTS  95610  ...  235000  38.708824 -121.256803\n",
              "983     8304 RED FOX WAY        ELK GROVE  95758  ...  235301  38.417000 -121.397424\n",
              "984  3882 YELLOWSTONE LN  EL DORADO HILLS  95762  ...  235738  38.655245 -121.075915\n",
              "\n",
              "[985 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gAKu29Vg8kZg",
        "colab_type": "code",
        "outputId": "f7b14118-7cb1-440f-8d6d-424fab850316",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        }
      },
      "source": [
        "df.isnull().sum()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "street       0\n",
              "city         0\n",
              "zip          0\n",
              "state        0\n",
              "beds         0\n",
              "baths        0\n",
              "sq__ft       0\n",
              "type         0\n",
              "sale_date    0\n",
              "price        0\n",
              "latitude     0\n",
              "longitude    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AO10o5GN8oJ9",
        "colab_type": "code",
        "outputId": "990921e7-0779-4ec1-a91f-b5ce4c57217a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        }
      },
      "source": [
        "df.isna().sum()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "street       0\n",
              "city         0\n",
              "zip          0\n",
              "state        0\n",
              "beds         0\n",
              "baths        0\n",
              "sq__ft       0\n",
              "type         0\n",
              "sale_date    0\n",
              "price        0\n",
              "latitude     0\n",
              "longitude    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w5Hf4m0J8rxp",
        "colab_type": "code",
        "outputId": "ef32341b-8752-46b8-c28e-c77253bbb7b6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "df.isnull().values.any()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8pmciaok86ta",
        "colab_type": "code",
        "outputId": "a49eab15-9f7c-496a-acb4-6ee27da9e23d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "(df['beds'] == 0).sum(), (df['baths'] == 0).sum(), (df['sq__ft'] == 0).sum(), (df['price'] == 0).sum()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(108, 108, 171, 0)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g12zN1ox9F-W",
        "colab_type": "code",
        "outputId": "ca19a7aa-b1ef-407b-909c-33d6e1e35ecc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        }
      },
      "source": [
        "z_field = ['beds', 'baths', 'sq__ft']\n",
        "df.non_zero = df.copy()\n",
        "df[z_field] = df[z_field].replace(0, np.nan)"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:2: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n",
            "  \n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nOI8deg7_EEG",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df[z_field] = df[z_field].fillna(df.non_zero.mean())"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cr4CwcxuBkGH",
        "colab_type": "code",
        "outputId": "5f2153b6-3268-4457-b313-9983d10b7dc8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "(df['beds'] == 0).sum(), (df['baths'] == 0).sum(), (df['sq__ft'] == 0).sum(), (df['price'] == 0).sum()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(0, 0, 0, 0)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xu153JJ3Ss7G",
        "colab_type": "code",
        "outputId": "2ae17f8c-fe4f-4460-bb83-e6dad897ad18",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "df['street'].nunique()"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "981"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wGITTkBlTgIG",
        "colab_type": "code",
        "outputId": "76c3f523-fa96-4cc8-c142-2068ef450939",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "df['city'].nunique()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "39"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vCjUCRNkTpB_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "maxMin = df.groupby(['city']).agg({'price': [np.min,np.max]})"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ky6Wzd9rUCW4",
        "colab_type": "code",
        "outputId": "9e3c9254-e189-4903-99c3-e7b16cc20b4c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 731
        }
      },
      "source": [
        "print(maxMin)"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                  price        \n",
            "                   amin    amax\n",
            "city                           \n",
            "ANTELOPE         115000  408431\n",
            "AUBURN           260000  560000\n",
            "CAMERON PARK     119000  425000\n",
            "CARMICHAEL       139500  668365\n",
            "CITRUS HEIGHTS    30000  305000\n",
            "COOL             300000  300000\n",
            "DIAMOND SPRINGS  216033  216033\n",
            "EL DORADO        205000  289000\n",
            "EL DORADO HILLS  235738  879000\n",
            "ELK GROVE         71000  510000\n",
            "ELVERTA          126000  140000\n",
            "FAIR OAKS        142500  680000\n",
            "FOLSOM           200000  636000\n",
            "FORESTHILL       194818  194818\n",
            "GALT             106716  420000\n",
            "GARDEN VALLEY    490000  490000\n",
            "GOLD RIVER       299000  528000\n",
            "GRANITE BAY      600000  760000\n",
            "GREENWOOD        395000  395000\n",
            "LINCOLN            1551  512000\n",
            "LOOMIS           295000  839000\n",
            "MATHER           237800  237800\n",
            "MEADOW VISTA     230000  230000\n",
            "NORTH HIGHLANDS   63000  224252\n",
            "ORANGEVALE       183200  475000\n",
            "PENRYN           506688  506688\n",
            "PLACERVILLE      205000  677048\n",
            "POLLOCK PINES    175000  280908\n",
            "RANCHO CORDOVA    94905  430000\n",
            "RANCHO MURIETA    97750  425000\n",
            "RIO LINDA         30000  300000\n",
            "ROCKLIN          230095  600000\n",
            "ROSEVILLE        115000  614000\n",
            "SACRAMENTO        40000  699000\n",
            "SHINGLE SPRINGS  275000  275000\n",
            "SLOUGHHOUSE        2000    2000\n",
            "WALNUT GROVE     380000  380000\n",
            "WEST SACRAMENTO  147000  200100\n",
            "WILTON           372000  884790\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i1KBfk6tUQfW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import seaborn as sns"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ymxkiAbTVGIO",
        "colab_type": "code",
        "outputId": "f1c28ae7-7d0a-42da-c159-61ad1c329777",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "sns.lmplot(x='sq__ft', y='price', data=df)\n",
        "plt.show()\n",
        "sns.lmplot(x='beds', y='price', data=df)\n",
        "plt.show()\n",
        "sns.lmplot(x='baths', y='price', data=df)\n",
        "plt.show()"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWEAAAFgCAYAAABqo8hyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWAAAAFgCAYAAACFYaNMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0\ndHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nOzdeXRc1Z3o++8+NUilWZYly3jAli0j\nIGF0zOwY7CQmyYPcbpKQdCeETgLpEKa83Ibc9br7Pfr2WsnqvjHQ6RATQ0KGTkJIuqHThDTGOIaE\nyZgZjGXLxpY8aB5rPme/P84puSRXyRqq6hyVfp+1wNJWVZ1tS/rVPnv/9m8rrTVCCCEKz3C7A0II\nMVdJABZCCJdIABZCCJdIABZCCJdIABZCCJf43e6AV2zcuFE/8cQTbndDCFGcVKZGGQE7uru73e6C\nEGKOkQAshBAukQAshBAukQAshBAukQAshBAukQAshBAukQAshBAukQAshBAukQAshBAukQAshBAu\nka3IYk7YvruTzTvaONQXZkltGTeubWJdS4Pb3RJznIyARdHbvruTv3vsLTqHotSEAnQORfm7x95i\n++5Ot7sm5jgJwKLobd7RRsI0OToQ5d1jQxwdiJIwTTbvaHO7a2KOkykIUfRaO4cYCCcwDIXPUCQt\nTfdQnIQ55HbXxBwnAVgUvXjSAgWGsisCKgWW0na7EC6SKQhR9AI+O/BalkZrjWXZJ4EHfRlLtApR\nMBKARdFbtaCKuvIgfp/C1Bq/T1FXHqR5QZXbXRNznARgUfRuXNtE0O+jsbqU0xZU0lhdStDv48a1\nTW53TcxxEoBF0VvX0sBdV51JQ2UpA5EEDZWl3HXVmZIHLFwni3BiTljX0iABV3iOjICFEMIlEoCF\nEMIlEoCFEMIlEoCFEMIlEoCFEMIlkgUh5gQpRym8SEbAouhJOUrhVRKARdHbvKONgE9RFvSjlP1n\nwKekHKVwnUxBiKJ3qC9MTSgwpi0U8NHeF3apR94i0zPukRGwKHpLasuIJMwxbZGEyeLaMpd65B0y\nPeMuCcCi6N24tomEqQnHk2ht/5kwtRTjQaZn3CYBWBQ9KcaT3aG+MKGAb0ybTM8UjswBizlBivFk\ntqS2jM6hKGXB46FApmcKR0bAQsxhMj3jLgnAQsxhMj3jLpmCEGKOk+kZ98gIWAghXJLXAKyUul0p\n9ZZS6k2l1M+VUqVKqeVKqReUUnuVUr9USgWdx5Y4n+91vr4s7XW+6bS/q5T6SFr7Rqdtr1LqzrT2\njNcQQggvyVsAVkotAm4BVmut3wf4gGuBbwObtNYrgT7gi85Tvgj0Oe2bnMehlDrDed6ZwEbge0op\nn1LKB/wrcCVwBvAZ57FMcA0hhPCMfE9B+IGQUsoPlAFHgCuAR5yvPwR8wvn4audznK+vV0opp/0X\nWuuY1no/sBdY4/y3V2vdprWOA78Arnaek+0aQgjhGXkLwFrrDuCfgYPYgXcAeBno11onnYe1A4uc\njxcBh5znJp3H16W3j3tOtva6Ca4xhlLqBqXUTqXUzq6urun/ZYUQYhryOQVRiz16XQ6cApRjTyF4\nhtb6fq31aq316vr6ere7I4SYY/I5BbEB2K+17tJaJ4DfAJcANc6UBMBioMP5uANYAuB8vRroSW8f\n95xs7T0TXEMIITwjnwH4IHChUqrMmZddD7wNPA1c4zzmOuBR5+PHnM9xvr5Na62d9mudLInlQDPw\nIvAS0OxkPASxF+oec56T7RpCCOEZ+ZwDfgF7IWwX8IZzrfuBO4CvK6X2Ys/XPuA85QGgzmn/OnCn\n8zpvAQ9jB+8ngJu01qYzx/s14PfAO8DDzmOZ4BpCCOEZyh4witWrV+udO3e63Q0hRHFSmRplJ5wQ\nQrhEArAQQrhEArAQQrhEArAQQrhEylEKUWByCrFIkRGwEAUkpxCLdBKAhSggOYVYpJMALEQBySnE\nIp0EYCEKaEltGZGEOaZNTiGeuyQAC1FAcgqxSCcBWIgCklOIRTpJQxOiwOQUYpEiI2AhhHCJBGAh\nhHCJBGAhhHCJBGAhhHCJBGAhhHCJBGAhhHCJBGAhhHCJBGAhhHCJBGAhhHCJBGAhhHCJBGAhhHCJ\n1IIQosDkSCKRIiNgIQpIjiQS6SQAC1FAm3e0EU+aHB2I8u6xIY4ORIknTTmSaI6SKQghCmjPsUEG\no0kMFD6lSJqanpE4SXPQ7a4JF0gAFqKAEqYGwDAUAEqBZWniTruYW2QKQogCCvoN0GBpjUZjaQ3a\naRdzjoyARc7I6v7JNTdU8u7RQfojCSwNhoKaUIDmhkq3uyZcIAFY5ERqdT/gU9SEAhzoGebGn75M\nRYmPVQuqJBg7Lmqaxwv7e7CcGQdLQ38kwUVN89ztmHCF3PeInNi8o42AT1EW9DMcS9IznMDSmmjC\nklSrNI+/cQQ0KOdzBaCddjHnSAAWOXGoL0wo4AOgayiGUuBTirhpURb0E/ApSbUC9veE8fsUpQEf\noYCP0oAPv0+xvyfsdteEC2QKQuTEktoyOoeilAX9xE0Ln6HQFgR99nt8KOCjvc+9ICPz08KLZAQs\ncuLGtU0kTE04niRgKExLY6GZX1ECQCRhsri2zJW+eWn3WdP8cqxxWRCWttvF3CMBWOTEupYG7rrq\nTBoqSykrcW6stKajP0zrsSEGIwluXNvkSt/S56eVUq5OidyxsYXasgAKSJoWCqgtC3DHxpaC90W4\nTwKwyJl1LQ38/IYL+edrzqY6FMDnM1BKgQI3txmkz0+nuDUlsq6lgX+65mzOXVrLwuoQ5y6t5Z+u\nOVumQ+YomQMWObd5RxvVoQALq0OjbeF4ks072lwJNOnz0yluTomsa2mQgCsAGQGLPPDSiBPGzk9r\nbf+ZMLVrUyJCpEgAFjm3pLaMSMIc0+b2iDM1Pz0QSdBQWcpdV50po1DhOpmCEDl349om/u6xtwjH\nk4QCPiIJ0/URp9z2Cy+SEbDIORlxCjE5MgIWeSEjTiFOTgKwmBNkJ5zwIpmCEEXPSzvhhEgnAVgU\nPS/thBMinQRgUfS8lpcsRIrMAYuc8eo8q9d2wgmRIiNgkRNenmeVnXDCqyQAi5zw8jyr5CULr5IA\nLHLC6/Osr7f389bhAQ4PRHnr8ACvt/e73SUxSwxGE8STVl5eW+aARU54eZ713q17uGfbXgwFfsPu\n1z3b9gJwy4ZVBe+PV+fKxVimpekejjESS3JKTejkT5gGGQGLnPDyPOuWZ/c7wdfAUIbzp91eaF6e\nKxfHReImHX0RRmLJvF5HArDICS/Ps47ETdCaWNIkmjCJJe3PR+LmyZ+cY16eKxegtaZnOMaRgQhJ\nKz/TDunyGoCVUjVKqUeUUruVUu8opS5SSs1TSj2plGp1/qx1HquUUvcqpfYqpV5XSp2X9jrXOY9v\nVUpdl9Z+vlLqDec59yqllNOe8RqiMNw8/SKTEr9BwgJL232zNCQsu73QDvWFSZoWbV3D7D46SFvX\nMEnT8sxc+VwWT1p09EcYiCQKds18/wTeAzyhtW4BzgbeAe4EntJaNwNPOZ8DXAk0O//dANwHdjAF\n/h64AFgD/H1aQL0P+HLa8zY67dmuIfLEy7fWppl5pJutPZ8qS/y090UIx01nysakvS9CRYksx7hp\nIJKgoz+St8W2bPIWgJVS1cBa4AEArXVca90PXA085DzsIeATzsdXAz/WtueBGqXUQuAjwJNa616t\ndR/wJLDR+VqV1vp5rbUGfjzutTJdQ+SJl2+tY1nibLb2fBqKJjD18bsEDZjabheFZ1qaowNReoZj\n2GGksPI5Al4OdAE/VEq9opTaopQqBxZorY84jzkKLHA+XgQcSnt+u9M2UXt7hnYmuMYYSqkblFI7\nlVI7u7q6pvN3FA6vp6F5RddwHJ8Cwz6rFEOBT9ntorDC8STtfWHC8fwutE0knwHYD5wH3Ke1PhcY\nYdxUgDNyzevbzkTX0Frfr7VerbVeXV9fn89uFD2vHUOUzlBTa883n6Eo8fsoDfgo8fvwudWROUpr\nO73s6EAU03J3xSKfAbgdaNdav+B8/gh2QD7mTB/g/JmaJOwAlqQ9f7HTNlH74gztTHANkSc3rm1i\nMJKg9dgQ7xwZoPXYEIORhCfS0K4+e+GU2vNpeV0ZlgbL0mitsSyNpe12kX+xpD3nPljAhbaJ5C0A\na62PAoeUUqc5TeuBt4HHgFQmw3XAo87HjwGfd7IhLgQGnGmE3wMfVkrVOotvHwZ+73xtUCl1oZP9\n8Plxr5XpGiKPNIACpez7a69kQ2y69jwuWj42Eeai5bVsuva8LM/InzuvPJ2asgDKAFNrlAE1ZQHu\nvPL0gvdlrhmIJDjcHyVhFnahbSL5Xnq9GfiZUioItAHXYwf9h5VSXwTeAz7lPPZx4KPAXiDsPBat\nda9S6h+Al5zH3aW17nU+/irwIyAE/M75D+BbWa4h8mTzjjaqQwEWVh/fMRSOJ9m8o831XODtuzvp\nGIixor589JDQjoEY23d3Frxv61oa+PyFp7Ll2f2MmCYhn8HnLzzV9X+jYpa+o81r8hqAtdavAqsz\nfGl9hsdq4KYsr/Mg8GCG9p3A+zK092S6RrFzc4vrob4wNaHAmDavLMJt3tFGPGnSM5wkbloEfQaV\npX5X3hy27+7kkV0d1FeWsNR5M3hkVwdnLa6RIJwH0YRJ52CsIJsqpkN2whUJt/NwvbwIt+fYID0j\ncZKmxqcUSVPTMxKn9dhgwfuyeUcbCdPk6ECUd48NcXQgSsI0PZGuV2z6RuIc7i/MjrbpkgBcJNzO\nw/VyLYiEac9GG4ZCKYXhZB3EzcLPUrd2DtE9FCdpaXyGImlpuofitHYOFbwvxSppWhzuj9AX9n5q\nnwTgIuF2Hq6Xa0EE/QZosLRGo7G0vRMi6MJW5HjSAgWGUigUhrNgWegdWMUqHE/S0R8hmnBhl800\nyP7HIuGFcpDrWho8EXDHa26o5EDPMIOR43PAVeUBltVVFLwvAZ8ikrDT0JSC1OaroE9ygWdCa3ta\nySvpZZMlI+Ai4YUpgO27O/nM/c9z6be38Zn7n/dEHQiw/22SpsZ0cm9NS5N0aXpk1YIq6sqD+H0K\nU2v8PkVdeZDmBVUF70uxSBXRyVfwfelALzf/2yt5SV+TAFwk3J4CcHsR8GS8kqN849omgn4fjdWl\nnLagksbqUoJ+nyfmymejoWiCw3kqotMzHOMffvs2d/z6DZ585xg//GPu60fLFEQRcXMKIH0REKAs\n6PdMHrCXcpTXtTRwl9On9r4wi+VEjGmxLE33SIzhaO5ze01L89hrh3nw2f2jNaNXn1rLutNy/z2S\nACxywst5wF7rm1fnymeLaMKkayiWlymBPceG+M6Te9hzbBiAqlI/X/ngCq6/ZBmhYO7DpQRgkRNe\nWATMxst9E1MzEE7QG47nvHTkcCzJD/94gEdf7SBVn+ej72vky2ubqA4FcM56yDmZAxY5MX4RsGso\nSntfhNbOIdcX5LywQClmZrRu70hu6/Zqrdn+bifX//Al/v0VO/gun1/Ovdeewzc+chrV4+6cck1G\nwCIn1rU0cE17P1ue3c+QMy9XWxagsap0dEHuLudxbvRN5l1nr3A8SddQLOelIzv6I9z7VCsvHegD\noNRv8PmLl3HNeYvw+wozNpUALHIivcaBaWnipsVwzGQ4lqSyNOCZBTmvVGgTJ5ev3N540uKXOw/x\n0+ffG90lefGKOr52xUoaq0pzeq2TkQAsciI9CyJuWviUQgNdQzEqSwOuLnqlUuQCPjUmRc6tEbk4\nuXjSonMomvP0sl0H+7hnayuH+iIANFSWcPMVK7lk5fycXmeyJACLnEjPNAj6DJKmXes27qxUu7no\n5aVqaOLkBiIJekdyu9DWOxLn+3/Yx9Z37LUIQ8E15y/muouWEQr6TvLs/JEALHIiPdNgfkUJhwci\nYEHAUK4veu05Nkh/JIFl2VMQSdMkmjRJeqgwt8hP3V5La/7r9SP84Jn9DDuve8bCKm7/UDMr6gu/\nFX08CcAiJ25c28TfPfYW4XiSylI/5REfA9EkpqXpGorxpUuXuzbajMQtTLsGDqlkItOCcFwCsFdE\n4nZuby5LR+7tHGbT1j28c8SuNFdZ6ueGy5q48v2NdhEkD5AALHIiPdOg9dggkYRFY1UJdeUlrhcd\nH5OwrxhdifPS0TRzldaavnCC/hyWjgzHk/zoTwf4za7jOb0fOXMBN65toqYsmLPr5IIEYJEzqR1e\nn7n/+TEbH9zelmwYCj/24Zdag3KOgjdcOo3YzZNLvCRhWnQOxYjlqHSk1ppn9nbz3W176R62A/qp\n88q4bUMzZy+pyck1ck0CsMg5r239XV5Xxt6uEQKGGi0BaWrtyknEkpFhG4om6BmO27WZc+DoQJR7\nt7XyfJt9XGTQb5+198nViwkUKKd3OiQAFxGvjKy8tvX3zitP5xuPvMZwzJ6T9hmKmhJ3TiL2ctGi\nQrCchbbhHC20JUyLX+1s5yfPv0fMSVlbs3wet1yxklNqQid5tvskABcJL4ysUm8Ae44NMhwzmVce\nGJ0DdjMLYl1LA/98zdme2Al3qC+MT0Fb1/BoStz8iqAnihblW66L6Lze3s+mra2812P/29VVBPna\n5StZ2zw/b7Ubck0CcJFwe2SV/gawsDpER3+Yo4Mxjg3GqCjxu5oFAd6pQFZZ4ufdo0NoZyokaZkc\n6o1wWmOl213Lq76ReM7OaBsIJ9i8o40n3joK2Dm9/+PcRVx/ybIxd12zwezqrcjK7XnX9DeAoWiC\noag5etxOPGnxk+ffk6PXgaFIHAtGMzGc4+kYinj/AMnpSJgWXUOxnJzRZmnNE28e5f4dbQw69UZa\nGiu5bUMzqxbk7w1MKZW3tDUJwEXC7XnX9FvrVBFrsINLzLRIjMT59hO753wA7hpJ4DcYk5FhKLu9\n2ORyoa2ta5i7t7by5uFBAMpLfHz5siY+9v6F+PKYzVJR6qe2LJi3hTwJwEUifSNEKOAr+LxrZYmf\n1s7hzL8MGkzsxHhhn4ic/gtt5nDzgRfkcqEtkjD5yXPv8auX20eroa1vaeCv161gXnn+cnorSvzU\nlAXzfnK2BOAi4XbJxdF9+5kGO87mh2SOi2hPxb1b97DFOWKmPOjjS5cu55YNqwrej6b55bR2DqP0\n8VORLQ3N9eUF70s+RBMmnYO52dH2p33d3PvUXjqHYgAsrg1x2/pmzju1dsavnU1Z0E9teYASf2Hq\nQ0gALiJuLjQNx00W1ZTSPRwnNm66LxV33Tp5/d6te7j7qdbRXVGD0SR3P9UKUPAgfMfGFv7nI68x\nFE2SNC38hkFtWYA7NrYUtB+5lssdbccGo3x3217+uK8HgIBP8dk1S/nMmqV5G5GGgj5qy4KUBgpb\nmMe7GcpiVllSW4bfZ9BUX0G235FC11pN+f6ONizt1IKwD0XG0nZ7oa1raeBzF55K0G+gUQT9Bp+7\n8NRZPTceT1ocHojOOPgmTYuHdx7i+h+9NBp8zz+1lgeuW811Fy/LS/AtCfhYWB1iYXWo4MEXZARc\nVNzciJE+B23nYJ443eBWbmbYWRTUo/8b215I6YXrlzpz9W7WyZipQWehbaalI986PMCmra20dY0A\nMK88yFfXreDy0+rz8nMT9BvMKw+6nrYmAbhIuL0RI30Oep/zSzTe0YFo3vuRSea3g+OV0Qpp8442\nEubY2sRVodlXmzhXpSMHIwl+8Mx+/uuNI4D9PbnqnFP44qXLqSjJfXgK+AxqygJUlub3rLfJkgBc\nJNzeiAHH56CXf/O/RlOsUrSLi3B+AxIZ1oTyvMCdUWvnEAPhBIah8BmKpKXpHoqTMIcK35lpykXp\nSK01T759jPv+0MaAc+RQc0MFt3+omZbGqlx1dZTfMKguC1BV6vfULjkJwEXC7Y0Y6XwKkvr44lt6\nuxuqy4Kj1bHGtxdaPGkXJk4l9isFltI5P3onH7TW9I7ERwPmdL3XM8LdW1t5rX0AgLKgj7+6ZDlX\nn3NKznN6DaWoKQvk9Wj5mZAAXCTc3oiRrrGyhPaBWMZ2N8wvD9I7Eif9UF1D2e2FFvApRuKaaMJE\nY99yGwYE3Xp3mqRcnNEWTZj87IWD/PKlQySdb8blp9Xz1+tWML8itz8bSimqQwFqQgHXyo5OhgTg\nIuH2Rox0laEgaiA2Zt5VOe1uGImbo1kQKZZmzI69QmmoLKVvJHF8YlqBtqC+0p0MkcnIxRltL+zv\n4d6n9nLEWQdYWF3KreubWbN8Xq66CdiBt7LUT00oULCj5Wdi0gFYKXUq0Ky13qqUCgF+rfXsmbgq\ncm5vxEjXNRzDUByveaDsfMeu4RNHxYXQOeT0Z9wIOJXgX0haa3v+V42tTZzLAyhzJXWcVDg+/YW2\nrqEY/7p9Lzv2dAPgNxSfWbOEz65ZSkmO077yvW04HyYVgJVSXwZuAOYBK4DFwPeB9fnrmpgqr1T8\niictDEMRNI7/IiQty7V5TkvrMcHXbiNnxcCnIn3DSioLorGixJXR+ERmutBmWpr/eLWDB589QMQp\nxHPOkhpuW9/M0hwXwi/07rVcmuwI+CZgDfACgNa6VSnl/m+68KSATzEU1STM40FFAcFSd+bisl3V\njd4sqS3jQM/Ymhhx02JZnfsn9EJuFtreOTLIpq2to7U/akIB/nrdCjac3pDThbDSgI955YXfvZZL\nkw3AMa11XI2u3Co/mVMrhciYd+vmD0vSzHz1bO35dFHTPF480IvhVEGLmxadQ3E+84HczoVOx0zP\naBuOJtny7H7+87XDowuMHz9rIV+6bHlO8269sokiFyb7N/iDUup/ASGl1IeArwL/mb9uidmsN5x5\n9JStPd+y3US7MSHyXFsvlSU+BqNJEtoOwlWlfp5r6+UWF/qTMpPSkVprtu3u5Hvb99HnfI9X1Jdz\n+4ZVnHFK7nJ6Az6D2vJgXjZouGWyf5M7gS8CbwA3Ao8DW/LVKTG7jZ9vPVl7vnlpJ9yeY4OMxE0C\nhjG6CDcSN2k9NuhCb5zSkSMxhqPTW2g71Bvmnqda2XWwH4DSgMH1lyznz85dlLOcXr9hUFMeoLLE\nW5socmGyATgEPKi1/gGAUsrntBX/QVZiynyGwrT0CTvh8lk4e7ZIONMeqdxUpewgGHdhOmQmZ7TF\nkxb/9uJBfv7iwdG/02XN87lp3QoaclR0yWcoakJBqkLFF3hTJhuAnwI2AKnVgxDw38DF+eiUmB63\nT0VOXd9vaEzrxJ1wV53VWLC+pMsW2twYkAf9BsPRJEnLHN2urTQEQ4VNneoPx+kLJ6aV/vbye33c\nvbWVjv4IYFe5u/mKlVy0oi4nffMZ9iaKqlJvb6LIhckG4FKt9ejSrdZ6WCnlzhnjIiO3i/GkX7+5\noYq2rmHCTgEGn6G46qxGNl17Xt774XWpXXmj9eudIFyoXXlJ06JrOEZkGmlvPcMxvrd9H0+/2wXY\n39dPrV7M5y48NSeZCIaze63a47vXcmmyAXhEKXWe1noXgFLqfCCSv26JqXK7GM/4669oqCQcT9JQ\nWcrPb7gw79efLVK78tIValdeOJ6kayg2erTPZJmW5j9fO8wDzokiAO9fVM1tG5pZPn/mJ3kYSlHl\nBN65Nk012QB8G/ArpdRh7LWLRuDTeeuVmDK3i/Ec6gsTSyTZ3z2C5azu15UHZkWRmUI6nKUkZ7b2\nXJhJbu+eY0NserKVd4/Zm16rSv3c+MEVfOTMBTM+KVgpRVWpffbaXAu8KZMKwFrrl5RSLcBpTtO7\nWuviO8Z1FnO9GI9l0TV8/EfC0tA1nMAgwWfuf961bdEAoYBBJEM9ylCg8FtWs40+pzoqnazpFtEZ\niSX54R8P8B+vdoyO2K98XyM3rG2iOjSznN7ZVq8hnyYMwEqpK7TW25RSfzbuS6uUUmitf5PHvokp\nuHFtE9945DU6+iOYlsZnKCpK/Pztx84oyPV7I3YaU2oco9P+LPR89HhlQR+xpIXWo6UpUArKg7N3\nB9VkTCe3V2vNH/Z0869P76VnxC7huXx+ObdvaOZ9i6pn3KfZWK8hn042Av4gsA34vzJ8TQMSgD1E\nAWjnhGKtCprnGkta+BSMz6bSwP7uEapK3Tv1YdWCKna91zN6WKgGggY0L8h94e+TKURO8nSPhe/o\nj3DvU628dKAPgBK/wecvOpVPnr94xiPV2VyvIZ8mDMBa679XShnA77TWDxeoT2IaNu9ooyoUoLE6\nNNpWyEW4Er9BOG5mDDCWhv5Ikjc7+vLej4y0dcJJzTHTbi+0Er8imjwxBJf4cxOCp5PbG09a/HLn\nIX72wsHRqYoLm+ZxyxXNNFbPLKe3GOo15NNJ54C11pZS6m8ACcAe5vYi3LyQn3DczDy6c3Z8hRPu\nbIV7bn/mwJ+tPZ/yeWDpdHJ7Xzlo5/Qe6rOTmuorSrj5ipVcsrJuRn0qCfiYVxYkVOTTPDM12SyI\nrUqpbwC/BEZPXNRa9+alV2LKltSWsb97mKHo8cMeK0v9LJ9foCpbhkF9RYCekcQJaVbHc16lflNq\n11h6aNPMrDDQdHJ7+8Jxvv+HNp58+xhgZ61cc/5irrto2YyCZtBvUFsWpLyI6jXk02T/lT6N/XPy\n1XHthT9uQWSUqcpW13Ccz64pTJWt1BtAKODLmtMqCy/25gWtNZrjmzAMmPbGg6nm9lpa8/gbR/jB\nM/sZcuo/nLGwits/1MyK+um/WRdjoZxCmOy/1hnYwfdS7ED8DHZBduERz7X10lAZZDAy9rjzQlXZ\nSn8DyMaawSm6xaJpfjmtncP4jbQTMSxN0xQ3NEwnt3df5zCbtu7h7SN2Tm9lqZ8vX9bER9/fOO2c\n3oAvddqwN455n20mG4AfAgaBe53PP+u0fSofnRJTd6gvTF15CfMrji+aaK0LNgec/gaQXog9xQAs\nV+qP2cfPZ0qDdeNY+js2tvA/H3mNoWiSpGnhNwxqywLcsbFl0q8x1dzecDzJQ396j1/vah+dHvrw\nGQu48YNN1E7zZGivHvM+20w2AL9Pa52eUPq0UurtfHRITI/bGzHS3wDeOjww5hDM0oCPpGURcmkl\nPNvUsxtT0utaGvina86e9tl9g9EEvZPM7dVa8+zeHr67be/oeXxL55Vx24ZmzllSM63+pwrlePWY\n99lmsgF4l1LqQq318wBKqUJKkxkAACAASURBVAuAnZN5olO6cifQobX+uFJqOfALoA54Gficc9pG\nCfBj4HygB/i01vqA8xrfxK5HbAK3aK1/77RvBO4BfMAWrfW3nPaM15jk33VWcvtU5PRFwNFFN+dr\nqTPBbr58eUH6Mp7X6hNP5+w+08ntHZlkbu/RgSj3bmvl+TZ7nTzoN/jLC5by6Q8smdZc/FwslFMI\nkw3A5wN/UkoddD5fCryrlHoD0FrrsyZ47q3AO0Aq6/3bwCat9S+UUt/HDqz3OX/2aa1XKqWudR73\naaXUGcC1wJnAKdgZGauc1/pX4ENAO/CSUuoxrfXbE1yjaLl9KvJFTfN4YX/PhEFtf/dw9i/mkZfK\nUQLcu3UPW5zCNuVBH1+6dDm3bFiV9fFTOSAzaVr86uV2fvzce8ScKYo1y2q5ZX0zp9SETvLsE6m0\nwDtX6zXk02QD8MbpvLhSajHwMeAfga8r+57lCuw5ZLDnkf9f7OB4tfMxwCPAd53HXw38QmsdA/Yr\npfZiHxAKsFdr3eZc6xfA1Uqpdya4RlFz81Tk37151N7iS/bA9u+vHmHTtQXslAfdu3UP92zbi6Hs\nOehIwuSebXsBTgjCWmv6wgn6w5O7eXu9vZ+7t7ZyoMee96+rCHLz5Su5rHn+lKcLUvUaaudwoZxC\nmGwxnvem+fp3A38DVDqf1wH9WuvUfVQ7sMj5eBFwyLleUik14Dx+EfB82mumP+fQuPYLTnKNMZRS\nNwA3ACxdunQafz2R0tY9YqdWud0Rj9vy7H4n+NrTAIaCpGWx5dn9YwLwVA7IHAgn2LyjjSfeOjr6\nmp84dxHXX7xsyvm4Stk1RGrLpFBOIeQtaU8p9XGgU2v9slJqXb6uMxNa6/uB+wFWr14tsWMGkpZ2\nbU71ZAyVeb7XjYHdSNw8IfvCUGPrAU+2iI6lNb9/8yibd7Qx6OT0ntZYydc3NNO8oHLC52ZSUWKX\nhgy6kR4yR+Uza/oS4Cql1EeBUuw54HuAGqWU3xmhLgY6nMd3AEuAdufY+2rsxbhUe0r6czK190xw\nDZEnllejLxD0Za6/EPQVPgKXB32MxJNonXYkkYLyoH9KRXT2d49w99Y9vNFhH+ZZXuLjS5c28fGz\nFk55ykAK5bgnb291Wutvaq0Xa62XYS+ibdNa/wXwNHCN87DrgEedjx9zPsf5+jZt7119DLhWKVXi\nZDc0Ay8CLwHNSqnlSqmgc43HnOdku4bIE++GXzCMzD/m2drzaX1LPaZlj8g19p+mBetWzaejP3LS\n4BtJmNy/o40bfvLyaPBd39LAQ9ev4epzTplS8C0N+DilJkRjdakEX5e4sW/wDuAXSqn/DbwCPOC0\nPwD8xFlk68UOqGit31JKPQy8DSSBm7TWJoBS6mvA77HT0B7UWr91kmuIPEmdhOxF0Sxbo7O159Pu\no5kzQd46PHTSCmZ/2tfNv2zby7FBO6d3cW2IW9c3c/6ptVPqQ9BvMK88OCZnXLijIN8BrfV2YLvz\ncRvHsxjSHxMFPpnl+f+InUkxvv1x4PEM7RmvIfInFFAMx7wZgHWW1AztwhxwW/cIfsMe+aY2qxgK\nDk6wY/HYYJTvPr2XP+7tASDgU3x2zVI+s2bplOZrAz6DmrIAlbJt2DPkLbCIuHks/eKaMnYfcyfP\n92T8SpHIsKDld2Enl6X1mG3RGruIvcrQv6Rp8ZtXOvjRnw4QdY5UOn9pDbduaJ7SDsdUvYbKEtk2\n7DUSgIuE28fST+ZUX7d+9atDfrpHTixaUx0q/I+/zjZNM675rcMDbNraSluXXf21tizATZev5PLT\n6icdRCXwep8E4CLh9rH0Rydxqq9byU2DkcwLW9na8yVhWiddrByMJNjy7H5++/oRwH7TuursU/ji\npcupKJ3cr6vfMKgpl8A7G0gALhJun4iRnExxmAL0I5N4llFntvZ8SBXRMQyFNvXoppXU7kEU/Pdb\nR/n+H9rod0pMrmyo4OsfaqalcXJn10mFstlHAnCRcLsamtInD7DeXKLLr6Rp0T0cJxy3R9tLast4\nr2cEX3o9YFPj9xl864l3AfsU57+6ZBlXn7NoUmllPkNREwpSFZLAO9vIlpcicePaJhKmJhxPorX9\nZyGroZXK2V8nCMeTdPRHRoMvwA2XNVEVCqCAZFJjWhoLRhfZPriqnh9+4QP82XmLTxp8DaWoLQuy\npLaM6jIpDzkbyQi4SLhdDW0ym8rmyghYa03PSJzBDKdVrGmaxx0faeH+Z9p4r2eE1FFwC6tLuWX9\nSi5YXnfS1zeUokoqlBUFCcBFyI1Ap5Qara3g0f0YBRFLmnQOZj8Wvns4xvd37ButWAZw1qIqvv3n\nZ1FykoL1SimqSu16DRJ4i4NMQRSJVBpa51B0TBra9t2dBbl+wHd8TnOuGogkONwfzRh8TUvzm13t\n/MWWF8YEX4A3OgZ5+KVDJzwnxS4NGWBJbYi6ihIJvkVEAnCRSE9DU8r+M+BTbN7RVpDrN1SWoi3c\nS/Z1kWlpjg5E6RmOoTO8A+0+OshXf7aL7z69b/RY+nQa+PnOzAG4otTP4toQ9ZUlUh6yCMkURJFw\nOw1Naz0nR8ATHQs/HEvywLP7eezVwyedFkotwqWUl9jF0KU0ZHGT726RWFJbNnr2Wkoh09C6R+J2\n8J0jI2CtNT3DMY4ORE8Ivlprnnqnk+sefJFHneDbNL+ce68956SvWxb0s6g2xIKqUgm+c4CMgIvE\njWubuPWXrzAYGRlN8K8K+fnbj51xsqfmRDxpkcqCKvZB8ETHwrf3hblnaysvH+wHoDRgcP3Fy0bT\nyhZUBDg2fGJ2RGNlkFNqQpS6dHK0cIe8xRaJ19v7GYgkR4OfBgYiSV5v7y/I9S1tYeriz4AYjCbo\n6I+cEHzjSYuH/nSALz60czT4XrKyjh994QN8cvWS0YWz2z/UQnnAGL1RUEBF0OBbf362BN85SEbA\nReK7zsGOmdonOnE3VwxlACc/tXe2muhY+Jff6+Oep1pp74sAsKCqhJuvWMnFK+af8Ng1TfP41Ool\n/GpXO+G4SUWJny9duty1w1SFuyQAFwm36x1kWv0vFtmOhe8diXPf9n085aT6+QzFJ89fzOcuOpVQ\nltHsywf6eHJ3JwuqSgkFfEQSJo/s6uCsxTUShOcgCcAiJ1IbMYppCkJrTe9InIFxO9pMS/Pb1w+z\n5dn9jMTshc/3L6ritg2rWD6/PONrpYqh/+aVDvrDcYZjxxdMK0p8BataJ7xFAnCRKPEbxDIsCpUU\ncCU9dcJDMcTgbAtte44NsWlrK+8eHQKgqtTPjR9cwUfOXICRoRbD+Aplr7X3Ex5XO3k4ZvJagebq\nhbdIAC4SN61bwaatrWOCn3LaC+VkwXe2ZKgNRBL0jsTHTKuMxJL88E8H+I9XOkZH+Ve+r5EbLmui\nuuzEI36yVSgbH3xP1i6KmwTgIpFaaNvy7H5G4iblQR9funR5QRbgAGLJ5Kwf+Y4vHQn2NMSO1m6+\n+/ReeobjACyrK+P2Dat4/+LqE17DUIpqp1COIVuGxUlIAC4it2xYVbCAO17SOvnkg5cD9EgsSffw\n2B1th/sj3LttLy/u7wXs6ZzrLjqVa85ffMK2YLteg717TWo1iMmSACxywpqlq2+WpekeiTEcPT7q\njSctHt55iJ++cHB0DvjCpnncckUzjdWlJ7xGKOijrrxEdq6JKZMAXETcPBV5doZfaO+LjEkve/VQ\nP3dvbeVgr11Do77Czum9ZGXdCQXPAz6DuorgmFNIZiM3f27mutn9kyNGbd/d6WxFtudiO/oivH1k\ngHs+fa78Mk0gFXz7wnG+/4c2nnz7GACGgj8/bzHXXXzqCQG2mI4Acvs07blOAnCR+NtH32Qgkjx+\nyCP2VuS/ffRNnmm5Iu/Xn63pZ5bWPP7GEX7wzH6GnGmIMxZWcvuGVaxoqBjz2FRB9NqyYNEssLl9\nmvZcJwG4SKS2wY4Pgqn2fDMUZCh163m3/PxV3j4yCEBlqZ8vX9bER9/fOCanN7XAVhMKFF1NXrfL\nmM51EoCLRLbYV6iY6PcZ6KQ166pBpILvh85YwFc+2ERtWXD0a0opKkr81JYVX+BNcfs07bmuOH+q\n5qBsN8SFulFuml+OYaiC7rybjPHbiMdbUhvi/3zyLL55ZcuY4FtR4mdRTe5Posj27+PWv5vbp2nP\ndTICLhJBP2Qo1EVJgb7Dd2xs4X8+8troPKrbkqZF13CMyEl2mP3g86vHpI+Vl/ipKQtQ4s9Pacim\n+eW0dg7jM46foWdamqYsNSTyze3TtL0u3xkiEoCLhM/wAScGG8MoTI3ZdS0N/NM1Z7N5RxvPtfUU\n5JrZDMeSdA/FsLQmmeV04pRU8C0L2oE33zV579jYwi0/38Vw3MTS9tx5RdDHHRtb8nrdiaxraZCA\nm0EhMkS8db8opi3hbBhQaf+ltxfC6+39vHV4oGDXG8+0NJ2DUToHo1ha80b7ADf85OUJn1Ma8HFK\nTYjG6tKCFURXhho9O09r+3PhPYU46FZGwEXCMBR+NJZ2fqkV+BQFS5e6d+se7tm2F7diSTiepHso\nTtKyGIgkuH9HG7978+hJn3dKTagAvTvu20/sZiRmEvQbo1MQIzGTbz+xW0ahHlOIDBEJwEVieV0Z\ne7tGCKTPLWrN8rrCrGZveXY/pqUzTILkl2VpekbiDEUTWFrz+7eOsfkP+xh05qJPW1DJu8eGCtyr\n7Nq6RzAUo2luSoFWmrbuEZd7JsYrRIaITEEUiTuvPJ2asgDKsAOvMqCmLMCdV55ekOsPurD4Fk2Y\ndPRHGIom2N89wu2/fI1/+v27DEaTlAd93Lp+Jd/97LkF75coDoXIEJERcJFY19LAPzuLYMW+mp1+\nUkU0YfKT59/j4Z3to5XMLj+tnq+uW0FdRYnLPT1R6k5FWXr0TsXSsHK+5N16TSEyRCQAF6FZuCFt\n0qIJ+3y2hGnx3L4e7t3WyrHBGACLakLcun4lq5fNA+zMhnnlwYleruDuvPJ0vvHIawzHkpiWtutK\nlBTuTkVMTb4zRCQAF4liL6qitaY/nKA/kuDYQITvPr2PZ/d2AxDwKT67ZimfWbOUoN+gJOCjrjzo\nyWPe17U0cNnKOh57/SimZS+aXrayrii+R2LqJAAXiWIuqpIa9UYTJr95pYMf/fEAkYS93Hf+0hpu\nWd/MknllBHwGteVBKgq1+2Qa7t26h8deP4qhwO9XWBoee/0oy+fvca2YvnCPd39SxZQc6gvjU9DW\nNUzctAj6DOZXBAtWVCXboaAzYVma3nCcwUiCtw8PsmnrHvZ12dkCtWUBvrpuBVe0NOD3GbOmPOSW\nZ/fbwdew178NZZfE3PLsfgnAc5AE4CJRWeIf3eLqMxRJS9PRH6V5XEnF/F3fl9MAnMrr7QvH2PLM\nfn77+hE09gaTq84+hS9eupzKUGDWlYcciZuML/tgKLtdzD0SgIuE1hqtNfGkHg1UhmLMyb75lKsa\nEKal6RmOMRRNsPWdTu7bvo9+p6DOyoYKbt/QzOkLq+wqZeVBArOsSll50MdIPInW5uiGGaWgfJaf\nqiGmR77rRaJrODamHq/Grs/bPRwryPVjOSgGPBhN0DcSZ3/XCHc/1cqrh/oBe/fRX126jE+cs4gK\nZ8TrxQW2yVjfUs+/v3pk9HOtAW23i7lHAnCRCGe5hZ0Nt7axpEnPcJyBcJyfvXiQX7x4iKST0/vB\nVXZO7yk1oaI4f+2dI0MYMKZusuG0i7lndv80i1HJLKcSZ2v3Aq01feEEA5EEL7T1cM9TrRwZiAKw\nsLqUm69YycUr5lNTFqA6FPD8Attk7O8JYxhAWs0OQ9ntYu6RAFws3D4SY4pSqWVHBiJ87+l9bN/T\nBYDfUHz6A0v4iwuWUl9ZyrzyIL5ZssA2GZalSV+rTO2EU179Rom8kgBcLFw+EqMs6Ms6DZIulVrW\nNxLn0Vc7ePCPB0afd/biam7b0MxpjVXUVQTzVhTdTdkG8UUwuBfTIAG4SCSyLIJla8+1r6xt4jtb\nW0/6uPa+CG8e7mfTk620dg4DUBMK8JUPNvHR9y9kXkWJpzdSzFS2GaECJasIjynen3ThSf/nyXd5\n7NXDozfcHz9rIV++rIml88rsam5FPhT0GQrT0mMmHBSFq9ssvEUCsMiJ7//BPiVAMfG086OvHgbs\ns9Fu29DMBU11zJuF+bzTVVnqp3s4PqZNO+1i7pHvusiJsFOb4WR30qUBgy9cvIxPr15CY3WIULD4\n5nknMpLp5NQJ2kVxkwAscuJkI9+UH12/hpbGyqJJK5uquKnxG4w5OspQdruYeyQAz0C+j6yeTQKG\nIj6JnOPzT62dM9MNmZQHfUQSJiVp/wZJy6Jslu7sEzMzd38TZihVf7dzKDqm/u723Z1ud63gogmT\nspLJBZC5HHwBvnTpcixtB11LW86fdruYe+b2b8MMFOLIaq8zLU3XUIxDveHR8opiYrdsWMWtV6wk\nFPCRtOw6F7desVJKUc5ReZuCUEotAX4MLMCeHrxfa32PUmoe8EtgGXAA+JTWuk/ZE4L3AB8FwsAX\ntNa7nNe6Dvh/nJf+31rrh5z284EfASHgceBWrbXOdo1c/v0KcWS1lw1E7MI57x4dZNPWVrpH4id/\nkgDsICwBV0B+R8BJ4P/WWp8BXAjcpJQ6A7gTeEpr3Qw85XwOcCXQ7Px3A3AfgBNM/x64AFgD/L1S\nqtZ5zn3Al9Oet9Fpz3aNnFlSWzZ6KkNKro+s9qJI3KS9L8yh3hH+ZVsrf/2zXew+KoVkhJiOvAVg\nrfWR1AhWaz0EvAMsAq4GHnIe9hDwCefjq4Efa9vzQI1SaiHwEeBJrXWvM4p9EtjofK1Ka/28tove\n/njca2W6Rs4U4shqL0mYFscGoxzuD7P17WN84Ycv8etdHVgaTq0ro9RvYFCwnc9CFIWCZEEopZYB\n5wIvAAu01qmCqEexpyjADs6H0p7W7rRN1N6eoZ0JrjG+Xzdgj7ZZunTplP5OhTiyeir8CpIZkhD8\nM4yIlqXpj9gVyzr6wty7bS8v7u8F7GOIPnfhqXz6A0v4s+/9kWhSArAQU5H3AKyUqgB+DdymtR5M\nz/105mvzmgA50TW01vcD9wOsXr16yv3I95HVU7GwJsShvkjG9unQWjMYTdIfjhOJmzy88xA/feEg\ncaeU14VN87j5ipU01VdQX1GCUgpDZa91IIQ4UV4DsFIqgB18f6a1/o3TfEwptVBrfcSZRkjlbXUA\nS9Kevthp6wDWjWvf7rQvzvD4ia5RtDqHYhkT/DuHpn4ixkgsSe9InIRp8dqhfjZtbeVgr724WF9R\nwteuWMna5vnUVZZQVWovRFrakuArxBTlbQ7YyWp4AHhHa/2dtC89BlznfHwd8Gha++eV7UJgwJlG\n+D3wYaVUrbP49mHg987XBpVSFzrX+vy418p0jaKWqi2rOR6IpyKWNDkyEOHYYJSuoSjffmI3tz/8\nGgd7wxgKPnn+Yn54/Wo+fOYCFs8rGw2+AIYyMJygL4SYnHyOgC8BPge8oZR61Wn7X8C3gIeVUl8E\n3gM+5XztcewUtL3YaWjXA2ite5VS/wC85DzuLq11r/PxVzmehvY75z8muEbRqizx0T0y9lRiU0Pt\nJDZImJamdyTOUDSBpTW/e+Mo9z/TNnrQ5ukLK7l9wypWLaiktjxI9bj0O4Cg38AXVxiGyvnx9EIU\nq7wFYK31s2Rfk1mf4fEauCnLaz0IPJihfSfwvgztPZmuUcyynf020ZlwWmsGIgn6w3bg3dc1zKYn\nW3n7yCAAFSV+vnzZcj521kLKgn7qK0uy7mRrbqjkQM8wg5EkhTkGVIjZT2pBFIlsxVyytQ9GE/SP\nJEhaFpG4yUPPHeCRl9tH53E3nN7AX69bQV15SdZRb7ob1zbxd4+9RWO1n31dIzP5qwgxZ0gALhIG\nmkxjXWNcjbJowqR7ODaazfDHvd38y7a9o4t1S2pD3LahmXOX1hIK+phfkX3Umy49LU8C8MSkiJNI\nkQBcLFSWgpBO2l8sadI3kiAct+d1jw5G+e62vfxpXw8AAZ/iLy+wc3pLA75JjXrF1KWKOAV8akwR\np7tAgvAcJAG4SEx0JlznYJRhp+B30rR45OV2fvzce0SdUfDqU2u5dX0zi2pDUxr1pksPLCK79CJO\nAGVBP+F4ks072iQAz0ESgOeAVPB9o32Au59qZX+3PUVQVx7kpstX8MFV9fgMg3kVwTGpZVMxPrCI\nzLxYxEmmRNwjvy1zwEAkwQ92tPH4m0cBO1f3E+cs4guXLKOixE9JwEfDBBkOk5EpsIgTLakto3Mo\nOuaNys0iTjIl4i4p4joHfOGHL40G39MWVPK9vziPr12xksrSAPPKgyyqCc24UHqm6nDiRF4r4iR1\nrd0lI+AZ8Mqt28kOdByIJCgP+virS5dz1dmn4DMUAZ9BQ1UJJf7cHIWTSkNLLfKJzNa1NHBNez9b\nnt3PSNykPOjjS5cud2206cUpkblERsDT5IUjiaIJk8P99tbhiVx+Wj0/uv4D/I9zF+EzFNWhAItr\nQzkLvuAElvMW0TWN2hNzyfbdnTyyq4P6yhJOb6ykvrKER3Z1uHaU1Vyta+0VEoCnyc1bt3gyVZs3\nQnQSt/1/+/EzqHMyG06pCVHnVC/LpfTAIrLz2i2/16ZE5hqZgpgmN27dkqZFXzjBUDQxpn0yo87K\n0gB15UGMPFXLkSyIyfHaLb/X6lrPNfLbMk2FXM02LU1/OM5g1B6lpLf/5pUOfvTHAxM+v7G6NO+B\n8VBfGJ+Ctq7hvF5ntvNaFgR4q671XCNTENNUiFs3y9L0jcQ51BtmIJIYE3zfPjzIV376Mvdt33fS\n7INCjEorgj46+qMks2wIETa55RfpZAQ8Tfm8ddNaMxhJ0h+JY46rcj4UTbDl2f389rUjaOxyc1ed\nfQqPvnZ4xtedidE5ZQ9uhJtfEaR7+MRTm+dXBAveF7nlF+kkAM9APm7d0quUpdNa89TuTu7bvo++\nsD0HvLK+gts/1MzpC6tcD8BDsSSLakrpHo57rhxlLMsdQrb2fJNbfpEiAdgjhmNJ+pxjgMY72Bvm\nnqdaeeVgP2Av2lx/ybLRtDIvSM1tNtVX8EbHgNvdGWM4ljnQZmsXolAkALssHLfPX4tnOEUinrT4\ntxcO8vOXDo4W21nbPJ+bLl85Jt3Lb7g/le/ljRjZZqVltlq4TQKwS6IJk96ReNY83pcO9HLPU60c\n7rc3WTRWlXLL+pVc2FQ35nHlJX7mV7ife5u+w0sIMTkSgGdgOluRx9flHa9nOMb3tu/j6Xe7APAb\nik9/YAl/ccFSSgPHd64ZSs2oelmupW/EGIx6bxQshBdJAJ6mqVaRiict+sPx0dKQ45mW5tFXD/Pg\nH/cTds5xO2txNbdtaGZZXfmYxwb9Bg2VpQT97k89pMhGDCGmTn5bpmnzjjbiSZOe4SRx0yLoM6gs\n9Z9QWDu1e204NnYTRbp3jw6xaese9hyzNzFUhwJ85YNNfPiMBSdsGa4K2Tvacr2VeKakHKUQUycB\neJr2HBukP5LAsuzFnKRpEk2aJJ0shmy719INx5I88Ox+Hnv18OiC0Eff38iXL2s64Tggn6GYX1FC\neYk3v2WZdnh5RcCAxIlrnAS8cwMh5ijv/bbMEpGEhWnZ+w5Sx7GZln0MfN9InIGIfdR7Jlprnn63\ni+9t30fviL1BYPn8cm7f0Mz7FlWf8PhQ0Ed9RQn+GdbszScvZ0EEfD4S1omLnQFf7qrBCTEdEoCn\nKeGkjenR/x1v7wufuOsqpaMvwt1PtfLye30AlPoNPn/xMq45b9EJAVYpxbxZcjiml7MgYhlyqydq\nF6JQJABPUzLL6DZbKYR40uIXLx3kZy8cz+m9eEUdN1+xkgVVpSc83osLbRPxchaEZWX+pmRrF6JQ\nJABPU5b4mzG5f9fBPu7e2kp7XwSAhsoSbr5iJZesnJ/xNby60DYRL2dByEYM4VXe+20pIr0jcb7/\nh31sfcc+7cBnKK45bxGfv2gZoeCJ849+w2B+ZdCTQexkvJwF4Tcgw0ZDZsnNhShis+833SN8hjqh\nUhnYJw5bWvPb14/wg2faGHHqDbzvlCpu29BMU31FxtcrC/qpryzxTG2HqfJyFkRjVSnt/Sce29SY\nYepHiEKSMcA0XXVWY8b21afW8LV/e4W7t7YyEjOpKvXzjQ+v4u5rz8kYfJVS1FWU0FhdOmuDL4yt\nc+s1FSV+DI5XylTYP/gVHk3pE3OH/ARO06ZrzwN28djrRzEtjQIW14bY+V4/qYHxxjMbuXFtE9Vl\nmW/Nc30ysZvS69zu6xpxuztjDMdN6ioC9Iwk0NpOG6wrDzASl2powl0SgGdg07Xn8Z1Pa372wkHu\n3rqHQ84i26l1Zdy2oZmzF9dkfW5laYD5FbNroe1kUnVul935X253ZYyKoI+jA1EChoFS9gJqXzjJ\nynr3ixiJuU0C8Ax0DcX4m0deGy2cU+I3+NyFp/LJ1YsJZNk04fUdbcVozGkdqfc7TVG9+YnZSaLA\nDFSU+NnrHEJ5wfJ53LJ+JQurQ1kfXxrw0VDp7R1tuWAAmbY4uPW3HoolmVcWoHskjqXthdL55cGs\nhZGEKBQJwDMQCvr41p+dxf7uES5qmpd1RKWUorYsQE1Z4c8gc8OqBRXsPnbi6cirFmTOAMm3yhI/\nrQNRAr7jUxC94QTNDTIFIdxV3EOxArhk5Xwub2nIGnwDPoOF1aVzJvgCfPT9C8fc7ac+/uj7F7rS\nn9FiSDrtv/R2IVwiI+AZSBVk398zTGNliGs/sIQ1TfNGv15R6md+eQnGLE4vm47n2nqpDvmdSnB2\n1kFVqZ/n2nq5xYX+DMfN0QNDU6VDGytKJAtCuE5GwNOUKsjeORSlqiRAz0iMe7a18mJbL4ZS1FeW\n0FBZOueCL9ilOkfiJgHDoNRvEDAMRuImrccGXenPktoyYuO2wsWSFotry1zpjxApEoCnKb32gVKK\nUMCH31A8/PIhFtWGjAu5WgAACXtJREFUqPTIUUFuSBUbMgyFUmr0TSierVJRnl3UNI8uZ/RrKIib\nFl3DcS5Ku1sRwg0SgKfpUF+YUGDsBoryoI/OwWjWFLS5Iug3QNtbsjXarousca2y23NtvTRUBgn6\nDCwNQZ9BQ2WQ59p6XemPECkyBzxNS2rLONAzzGAkSSxpEvQZVJcFWFbnzkq/lzQ3VI7+26TmXKvK\n3fu3OdQXpq68hPkVx2s/aK1p7wu70h8hUub2UG0GLmqaR+eQfVvrMxQJS9M5JLe1YNeFCPh8NFaX\nctqCShqrSwn4fNy4tsmV/iypLSOSGLvgFkmYMgcsXCcBeJqea+ulvmLsbW19hXu3tac3Vk6pPZ/W\ntTRw11Vn0lBZykAkQUNlKXdddWbG06ILIb1QkNb2nwlTu/aGIESKTEFM06G+MPMrSqiv9MZt7R0b\nW7j1l68wGEmisfNuq0J+7tjY4kp/UnUhvCC9UFB7X5jFtWXcuLbJM/0Tc5cE4GnKVP/W7dvagM+g\nJGBgWhqfoeb8YmA6L70hCJEiv6HT5LXb2s072qgOBWhuqKSlsYrmhkqqQwE272hzpT9CiJOTEfA0\nee22NtORQKGAr6BTIqmdgYf6wlSW+NFaMxw3WSK3/EJkJAF4Brx0W+v2lEhqZ2DAp/ApaO20i/Es\nqimlcyjK3z32FneBZ/69hPACmYIoEm5PiaTvDOwejuMzFD6l6B6OUxb0E/ApmQ4RYhwJwEXC7dSv\n9J2BcdNCKbsIT9y0azAUejpEiNlApiCKiJtTIulTIEGfQdJyth87mRhuZ4gI4UUyAhY5kT4FMr8i\niGlpTK2ZXxF0PUNECK+SEbDIifFZIc0NFWitGYmbNFSWShaEEBlIABY546WsECFmAwnAImcyHUfv\nMxTlQR9funQ5t2xY5UKvbOk5ypKXLLyiaOeAlVIblVLvKqX2KqXudLs/xS5T8AUwLc1gNMl3trZy\n79Y9Be6VLf30kppQYDQvefvuTlf6I0RKUQZgpZQP+FfgSuAM4DNKqTPc7ZX4l22trlx3/Oklkpcs\nvKIoAzCwBtirtW7TWseBXwBXu9ynOS9hnfwx+ZDp9BLJSxZeUKwBeBFwKO3zdqdtDKXUDUqpnUqp\nnV1dXQXrnCgsKcguvKpYA/CkaK3v11qv1lqvrq+vd7s7Ra/EpTPh3N6mLUQ2xRqAO4AlaZ8vdtpE\nnhz41scm/LoCblq3ojCdGcftbdpCZKO0dueo8HxSSvmBPcB67MD7EvBZrfVb2Z6zevVqvXPnzgL1\nsPjdu3UPW57dz0jc9EQamhAuUxkbizEAAyilPgrcDfiAB7XW/zjR4yUACyHyKGMALtqNGFrrx4HH\n3e6HEEJkU6xzwEII4XkSgIUQwiUSgIUQwiUSgIUQwiUSgIUQwiUSgIUQwiUSgIUQwiUSgIUQwiVF\nuxNuqpRSXcB703z6fKA7h92ZKS/1x0t9AW/1x0t9AenPRGbal26t9cbxjRKAc0AptVNrvdrtfqR4\nqT9e6gt4qz9e6gtIfyaSr77IFIQQQrhEArAQQrhEAnBu3O92B8bxUn+81BfwVn+81BeQ/kwkL32R\nOWAhhHCJjICFEMIlEoCFEMIlEoBnQCn1oFKqUyn1pgf6skQp9bRS6m2l1FtKqVtd7k+pUupFpdRr\nTn/+Pzf74/TJp5R6RSn1Ww/05YBS6g2l1KtKKdePYlFK1SilHlFK7VZKvaOUusilfpzm/Juk/htU\nSt3mRl/S+nS78zP8plLq50qp0py9tswBT59Sai0wDPxYa/0+l/uyEFiotd6llKoEXgY+obV+26X+\nKKBcaz2slAoAzwK3aq2fd6M/Tp++DqwGqrTWH3erH05fDgCrtdae2GiglHoIeEZrvUUpFQTKtNb9\nLvfJh32m4wVa6+lukpppHxZh/+yeobWOKKUeBh7XWv8oF68vI+AZ0FrvAHrd7geA1vqI1nqX8/EQ\n8A6wyMX+aK31sPNpwPnPtXd7pdRi4GPAFrf64FVKqWpgLfAAgNY67nbwdawH9rkVfNP4gZBz2G8Z\ncDhXLywBuAgppZYB5wIvuNwPn1LqVaATeFJr7WZ/7gb+BrBc7EM6Dfy3UuplpdQNLvdlOdAF/NCZ\notmilCp3uU8A1wI/d7MDWusO4J+Bg8ARYEBr/d+5en0JwEVGKVUB/Bq4TWs96GZftNam1vocYDGw\nRinlyjSNUurjQKfW+mU3rp/FpVrr84ArgZuc6Sy3+IHzgPu01ucCI8CdLvYHZxrkKuBXLvejFrga\n+03qFKBcKfWXuXp9CcBFxJlr/TXwM631b9zuT4pzO/s0cEIxkgK5BLjKmXf9BXCFUuqnLvUFGB1Z\nobXuBP4dWONid9qB9rQ7lEewA7KbrgR2aa2PudyPDcB+rXWX1joB/Aa4OFcvLgG4SDiLXg8A72it\nv+OB/tQrpWqcj0PAh4DdbvRFa/1NrfVirf//9u7nReY4juP485V14cJBctGmNGkXW+ugONnswVkK\nOchFaf8BzpQj4khhuWzKgUiRIqK0u0hSDlZxFAfHt8P3PdlZpdix75m8HjU1ffvOp/c0zWs+3x+f\n98QgzWHt/Yjo2izmT0lamRdKyUP9caDsTpqI+AzMSWrlpjGg5OLtPPspPv2QPgDbJa3I79gYzfWV\nrnAAL4Kk68AToCXpo6QjheXsAA7RzO7at/DsKaxnHfBA0izwnOYccPntXz1iLfBI0gzwDLgVEXeK\na5oAJvPzGgFOVRWSP0q7aWabpfKoYAp4AbykycyuLUv2bWhmZkU8AzYzK+IANjMr4gA2MyviADYz\nK+IANjMr4gA2S5IG/7az3WJea/8vB7CZWREHsFmnAUmT2RN3KldAjUp6mI1z7mbrT3L7TC6oONYe\nQNJQ9kKeljQraWPZu7Ge5gA269QCLkTEJuArTbCeA/ZGxChwETiZ+14CJiJi64IxjgJnshHRNppe\nC2a/GKguwKzHzEXE43x+FTgODAP3mlYALAM+ZZ+LVdkTGuAKTQMZaJann8gexDci4t2SVW99xTNg\ns04L1+Z/A15HxEg+NkfE+G8HiLhG00rxO3Bb0q5/VKv1OQewWaf18/4P7QDwFFjT3iZpuaShbLH5\nRdLO3PdgewBJG4D3EXEWuAlsWbryrZ84gM06vaVpkP4GWE2e/wVO58W2aX72gz0MnM9//dC8MfYB\nr3L7MHB5qYq3/uJuaGZmRTwDNjMr4gA2MyviADYzK+IANjMr4gA2MyviADYzK+IANjMr8gORRSOn\nKoJVkwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWAAAAFgCAYAAACFYaNMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0\ndHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nO3deZxcV3Xo+9+qqedJUrfGbrVkZIQn\nGSHLliUcBQiRgdgMCthgPEHwfZALSR4EyOfzyHu+yf2Yl7wQuAnEvkbGgME2CoNDbBMH2ziWZdmy\njGzLki0htdStqaWep+oazn5/nNPV1a2qVlV1na7hrO/nI3f17qo657SrV+1ae++1xRiDUkqpuecr\n9AkopZRXaQBWSqkC0QCslFIFogFYKaUKRAOwUkoVSKDQJ1AstmzZYh5//PFCn4ZSqjxJqkbtATvO\nnj1b6FNQSnmMBmCllCoQDcBKKVUgGoCVUqpANAArpVSBaABWSqkC0QCslFIFogFYKaUKRAOwUkoV\niAZgpZQqEF2KrFQWnj7Qzd3PHKazb5TWpmruuGYlm1e3FPq0VInSHrBSGXr6QDdfe2Qf3UNhGquC\ndA+F+doj+3j6QHehT02VKA3ASmXo7mcOE43HOTUQ5o3TQ5waCBONx7n7mcOFPjVVojQFoVSGDnYP\nMTAaxecT/D4hZhnODkWIxocKfWqqRGkAVipDkZgFAj6xKwuKgCXGblcqB5qCUCpDQb8deC3LYIzB\nsuwdxUP+lKVelTovDcBKZejChfXMrwkR8AtxYwj4hfk1IVYtrC/0qakSpQFYqQzdcc1KQgE/ixoq\neevCOhY1VBIK+LnjmpWFPjVVojQAK5WhzatbuPO6i2mpq2RgLEpLXSV3XnexzgNWOdNBOKWysHl1\niwZclTfaA1ZKqQLRAKyUUgWiAVgppQpEA7BSShWIBmCllCoQnQWhlDovLcPpDu0BK6VmpGU43aMB\nWCk1o7ufOUzQL1SHAojYX4N+0TKceaApCKXUjDr7RmmsCk5pqwr66eobLdAZzR23Uy/aA1ZKzai1\nqZqxaHxK21g0zrKm6gKd0dyYi9SLBmCl1IzuuGYl0bhhNBLDGPtrNG7KvgjRXKReNAArpWbk1SJE\nnX2jVAX9U9rynXrRHLBS6ry8WISotama7qEw1aHJMJnv1Iv2gJVSKoW5SL1oAFZKqRTmIvWiKQil\nlErD7dSL9oCVUqpAXA3AIvLnIrJPRF4TkR+LSKWIrBCRXSJySEQeEpGQc98K5/tDzs/bk57nq077\nGyLyh0ntW5y2QyLylaT2lMdQSqli4loAFpGlwOeBdcaYSwA/cAPwdeAbxpi3AH3Ap5yHfAroc9q/\n4dwPEbnIedzFwBbg2yLiFxE/8M/AtcBFwI3OfZnhGEopVTTcTkEEgCoRCQDVwEngXcB25+f3Ax90\nbl/vfI/z83eLiDjtDxpjxo0xR4BDwHrn3yFjzGFjTAR4ELjeeUy6YyilVNFwLQAbY44Dfw8cww68\nA8BLQL8xJubcrQtY6txeCnQ6j40595+f3D7tMena589wjClE5DMisltEdp85cyb3i1VKqRy4mYJo\nwu69rgCWADXYKYSiYYy5xxizzhizrrm5udCno5TyGDdTEO8BjhhjzhhjosBPgY1Ao5OSAFgGHHdu\nHwdaAZyfNwA9ye3THpOuvWeGYyilVNFwMwAfA64SkWonL/tu4HXgKWCrc59bgF84tx9xvsf5+ZPG\nGOO03+DMklgBrAJeAF4EVjkzHkLYA3WPOI9JdwyllCoabuaAd2EPhO0BXnWOdQ/wZeAvROQQdr72\nu85DvgvMd9r/AviK8zz7gIexg/fjwOeMMXEnx/unwK+A/cDDzn2Z4RhKKVU0xO4wqnXr1pndu3cX\n+jSUUuVJUjXqSjillCoQDcBKKVUgGoCVUqpANAArpVSBaDlKpbLg9i65ylu0B6xUhuZil1zlLRqA\nlcrQXOySq7xFA7BSGZqLXXKVt2gAVipDrU3VjEXjU9ryvUuu8hYNwEplaC52yVXeogFYqQzNxS65\nylt0GppSWXB7l1zlLdoDVkqpAtEArJRSBaIBWCmlCkQDsFJKFYgGYKWUKhANwEopVSAagJVSqkA0\nACulVIFoAFZKqQLRAKyUUgWiAVgppQpEa0GorOm2PErlh/aAVVZ0Wx6l8kd7wCorydvyAFSHAoxG\nYtz9zGFP9IK196/ySXvAKite3pZHe/8q3zQAq6x4eVse3ZRT5ZsGYJUVL2/L4+Xev3KH5oA9Ltuc\n5ubVLdyJ3Rvs6htlmYfyoK1N1XQPhRP5b/BO79+r3M75aw/Yw2ab0zQun1+xueOalQyORTl4eoj9\nJwc4eHqIwbGoJ3r/XjQXOX8NwB6WS07T6wNRBkBAREC89ybkJXOR89cA7GG55DS9PBB19zOHaagK\nsqqljtWL6lnVUkdDVdAT1+5Fc5Hz1wDsYbnMaPDyQFRn3yixuMXhM8McODXI4TPDxOKWJ67di+Zi\nxo8GYA/LZUaDl6eh1VUEON4fJmYZ/D4hZhmO94eprdCx7HI0FzN+NAB72ObVLdx53cW01FUyMBal\npa6SO6+7eMZRXi9PQzPGYIwhErMIRy0iMSvRpspPLn8f2dK3bo/bvLolqxeUl6ehnR2JYAwg2KNv\nAsbY7ao8Zfv3kS0NwCprbr8oi1UkZuH3CwHf5AfHmGX3hJXKhaYglMpQ0C8AWJaddrAsO/UQctqV\nypYGYKUydOHCeubXhAj4hbgxBPzC/JoQqxbWF/rUVInSAKxUhu64ZiWhgJ9FDZW8dWEdixoqCQX8\nnhiAVO7QAKxUhuZiVFx5iw7CKZUFrw5AKndoAFYqC7ojhsonTUEolSGvFyJS+acBWKkMebkQkXKH\nBmClMuTlQkTKHZoD9jjNaWZOd8RQ+aY9YA/TnGZ2vFyISLlDA7CHaU4zOzoPWOWbpiA8rLNvlMaq\n4JS2THKamrbQrYhUfmgP2MNyKa7u5bTF0we6+eL2vbzc2cfpwTAvd/bxxe17PXHtyh0agD0sl5ym\nl9MWdz22n/7RKMYCvwjGgv7RKHc9tr/Qp6ZKlAZgD8slp+nlqVhHekYBQ9SyGI9ZRC0LME67Utlz\nNQCLSKOIbBeRAyKyX0Q2iMg8EXlCRA46X5uc+4qIfEtEDonIKyKyNul5bnHuf1BEbklqf4eIvOo8\n5lsiIk57ymOo9DLNaXp5TzjLMsQssIz9+7IM9veWZoRVbtzuAX8TeNwYsxpYA+wHvgL82hizCvi1\n8z3AtcAq599ngO+AHUyBvwauBNYDf50UUL8D/EnS47Y47emOoZLkks/18lSsWJpAm669nDx9oJsb\n73meTV9/khvveV7z3nniWgAWkQbgGuC7AMaYiDGmH7geuN+52/3AB53b1wPfN7bngUYRWQz8IfCE\nMabXGNMHPAFscX5Wb4x53ti7In5/2nOlOoZKkks+18tTsdKF2XIPv14eeHWbm9PQVgBngPtEZA3w\nEvAFYKEx5qRzn1PAQuf2UqAz6fFdTttM7V0p2pnhGFOIyGewe9u0tbVleXmlL9dpaFqS0VuS36gB\nqkMBRiMx7n7msL4OZsnNFEQAWAt8xxjzdmCEaakAp+fqagdipmMYY+4xxqwzxqxrbm528zSKkpfz\nuSpzXh54dZubAbgL6DLG7HK+344dkE876QOcrxOfY44DrUmPX+a0zdS+LEU7MxxDJbnjmpUMjkU5\neHqI/ScHOHh6iMGxqCfyubnYsCL1WG669nKhb9TucS0AG2NOAZ0i8lan6d3A68AjwMRMhluAXzi3\nHwFudmZDXAUMOGmEXwHvFZEmZ/DtvcCvnJ8NishVzuyHm6c9V6pjqGkMgICIgGT2ccSrAzI/vuPq\nc4LthhVN/PiOqwt0RnPDywOvbhP7E7pLTy5yOXAvEAIOA7dhB/2HgTbgKPBRY0yvE0T/CXsmwyhw\nmzFmt/M8twN/5Tzt3xpj7nPa1wHfA6qAx4D/bowxIjI/1TFmOtd169aZ3bt35+vSS8KN9zx/TnWv\n0UiMlrpKfvyZq1I+ZmI12PB4jLhl8PuE2ooAf791jeYDy9jE8vOuvlGWeWz5uTEGY8Dnk9k8TcoH\nuxqAS0kuAbjUayJs+vqTNFYFcaZPA/aLbWAsyn99+V0pH7PlG7/h0JkR/CKIgDEQN4a3NNfw+J//\n3lydesGU+v9zlZ3h8Rh9IxGa6yqonJYHz1LKAKwr4XJUDlNzcsntHekZxSd2b0BE8PkEn+CJ1WBP\nH+jmS9v38vKxPk4NjPHysT6+pLUgytJ4LM7JgTG6B8NE45Zrx9EAnKNyqImgub3sfP3xA/SNRjFA\nwO/DAH2jUb7++IFCn5rKk7hlODM0zvG+McYi8fM/YJY0AOeoHKbm5LKoYuWCGiwDljEYDJYxWMZu\nL3eHz47YvX8RBMEndu//8NmRQp+amiVjDAOjUTp7RxkKR+fsuFoPOEflsj1NtosqvrxlNV/avpeh\ncIxY3CLg89FUHeTLW1a7eJZKuWc0EqNnOOJqqiEd7QHnqFw+vmc7pWzz6hb+busa3t7WxOKGKt7e\n1sTfeWQGxIr51cQtQzgaZywaJxyNE7cMK+aX1puuskViFqcGwpwacDfPOxPtAedo8+oW7oSSnpoz\nMZAY9MuUgcQ7Ycbr8OpS5Pdduphv/OfBKW2WsdtV6bAsQ99ohMGw3XkqJA3As1DqgUjX+Gdn5+Fe\nFjVUMDgWIxK3CPl91FcF2Hm4l88X+uRURgbDUfpGIsSLpIKdBmAPy7UYj1d19o0yv6aCBbWViTZj\njP6+SkA4Gufs8DiRWGFSDeloDtjDdI1/dvT3VXqicYvTg2FO9I8VXfAFDcCzUuo1EcplIHGu6O+r\ndFiWoXckQlffGCPjsUKfTloagHNUDivhNq9uYevapZwZGmf/qSHODI2zde1Szf+m4eVi9KVkKByl\nq2+M/tFIwQfZzkdzwDkqhwGspw90s33PcZrrKmgL+hmLxtm+5ziXLWuc8Rq8XA+h1Adey1k4Gqdn\nJMJ4NL8r2F7p6uebvz7I//fHawj489tn1QCco3IYwMrlTSTXqWtKuSUWt+gdjTAczm+q4cCpQe7b\n0cGLHX0AbHrLAv54Xet5HpUdDcA5KoeVcLm8iZRDz382vNz7LzYTlfv6R6NYeUw1HD4zzH07Otjx\nu55E25plDbS7sNxeA3CO7rhmJV97ZB+jkRhVzsf3UhuQyeVNpLNvFL/YL9KJubALakMl1fPPlfb+\ni4cby4c7e0f53nMdPP3GmcTGBBc013D7xhV8eO1SqkL5D5cagHNUDivhcnkTqQ35efP0MBMb7cXi\ncTp7x7hwYe2cnXeheL33XwyicYvekUheZzacGgzzg51H+dW+U0ysz2ibV82tV7dzzYUL7OJLMqti\n7GlpAJ6FUh+QyeVNZHg8RnKfYyIQDxfxVJ98KYe8f6kyxtA/GqV/LJq3mQ1nh8d5YNcx/v2Vk8Sc\nyLu4oZKbNyznPW9biH92O2BkRAOwx2X7JnJmOELAZ9dAMAZEwCd2e7lrbaqmo2f4nKXI7fPLv/df\nSMPjMXqHI8Ss/KQb+kcjPPhiJz//7YnE4owFtSFuumo5116yiGCeZzrMRAOwyppPZMqLNJ6nP4xi\nt2HlPF7o6HVqAkMkbtE9FOHGK+YV+tTK0ngsTs9whHCeppUNj8f4ye5Otr90PLGisbEqyMevbOO6\nNUsIBeZ+WYQGYJWVlQtqePP0ENF4HIO90ZVP8EQOeOfhXpprQwyFJ3vAdZVajCff4s4qtnwVRh+L\nxPnZy8d5aHcnQ85UtdqKADdc0cqH3r6UqtCs9nqbFQ3AHpfttKprL1nEG6eHEqPEEzngay9ZNBen\nW1CdfaMsqK2guc57xXjmYvqdMYbBsRh9o5G8TCuLxCwe2XuCH79wjL5RO5hXBf1sfcdS/vgdrdRW\nFj78Ff4MVMHkMq1q5+FeGqoCDIzFsIzd+23wSEnGcpj7nYunD3Tzxe17GR6PEbcMZ4fH+eL2vfx9\nHgvxj4zH6B3Jz7SyaNzi8ddO8YPnj3LWGZsIBXx88PIl3HhFGw3VwfM8w9zRAOxhuUyrOtg9xHA4\nTtDvS2xLPxyOc7B7aC5PvSDuuGYlX9q+l+N9Y8QsezumusoA/9f7Lyr0qbnqrsf20z8axS+CXwRj\nQf9olLse2z/rAByJWfSMjOdlA8y4Zfj1/tPcv/MoJwfCAAR8wvsvW8wnrmxjQW3FrI+RbxqAPSyX\nRRWRmIWFIR43iVkQIhRlqT83GADBnhcqUNylXvLjSM+oPfDoTMsSAWMZjvTknnqJO7tSDOVhVwrL\nGJ558yzfe66DY732OfkE3nvRIm7esJxFDZXneYbC0QDsYXUVAQ52D+P3CX6fELMMx/vDrGpJP6Bm\njCH5U6JxksDFXnUqH+5+5jANVUEWN1Ql2nQhRnaMMQyGY/SPzn5XCmMMOw/3cN+ODn53xt6ZWoDf\nX93CLRuW0zqv+FNDGoA9LBE0k0fUmDmYplsR5NZKoWLi1WXYKxfUcLB7GDEmkXayDKxqzq42Qj6X\nD+852sd3dxxh/8nJ1NfGt8zntqvbWdlcOjNyNAB72HAkztLGSs4ORxIBZVFtBSMz5OMsk/qPx6Rp\nLyd1FQHePD1kL0LBXobd1TfGhQvrCn1qrvryltV8aftehsIxYnE7991UHeTLW1Zn9PhIzF4+PBqZ\n/WrJ144PsG1HB7/t7E+0rVvexO2b2lm9qH7Wzz/XNAB72MSofnKPYTQSo6Uufc7MslL3dONp2svJ\nUDhKPOnDgQHihrzNVy1Wm1e38Hdb12Rd9ySfuw+/eXqIbTs6eOFIb6Lt0qUNfGpTO5cta5zVc8/E\n7xPqKoOEXFodpwHYw3IpxpPu42M+q1IVqxP94azay0m2S9bztfvwkbMjfO+5Dv7r4NlE21sX1XH7\nxnbWLW9yLfUV9PtoqA5SVxFwNb2mAdjDcqrolu61WP4dYNK9xZT/W0/mxiJxekZmv/vw8b4x7t/Z\nwa/3dyeGKFYuqOG2je1cfcF814JidShAfVVgylxvN2kA9rhsezYBnxCNn9urCcxB5ShVvPJVJvL0\nYJgfPH+Ux1+bLA25rKmKW69uZ/Nbm/G5EHhFhNqKAA1VwTmvB6EBWGWlOuQnHLWmzH8VoKaA6+mV\n+9ItRbYsQ/9YlIFZlonsHYnwwK5j/PKVE4k3+IX1Fdy8oZ33XuROaciAz65mV1cZnJPSkynPoSBH\nVSWrubaCvhF70GmiGI9AUa4yUvmRbsn6V6NxLl7SMKsykQNjUR56sZOfvXyccSdtMb8mxE1XtfG+\nSxe7UhoyFPDRUBWk1uX8biY0AKusiIg9FxQQJwIL3pgHXBvyMRw5N9jUhua+jOFcmr5kvTLoJxaP\ncvdvDvMPH1uT03OOjMf4yUtdbH+pi1Fn2mNDVZAb17dy/ZolVATz/4mqOmSnGQpZ/Wy6jAOwiCwH\nVhlj/lNEqoCAMab8CwCoKc4Mj9s3zNQgnGgvY5ZJ/SaTrr1cTCxA+V33EJG4RdBvzwM+NTiW9XON\nReP8/OXjPPRiJ4NOaciaCj8fXdfKR9YuzfvgVyHzu5nI6GpF5E+AzwDzgAuAZcC/AO9279RUMYrE\nLHw+IeSbfDHHLMsTtSDG4xZ+YcpcYL/Y7eVsYgGK3yf4nCXrpwfHWT4/85VwkZjFL185wQO7JktD\nVgZ9fGTtMj66bhl1lfmtUOb3CfWVQeqrCpffzUSmbzefA9YDuwCMMQdFxPOL3724RXnQLwyPG6Lx\nydVyPoGQv3hf5PlSEfAlPi5PiBuoDhZfzypfxmNxIjH7mo1xZhsmlq6ff9AtFrd4fN9pfvj8UbqH\n7E9JQb/wwcuXcsP6VpqqQ3k937mav5svmQbgcWNMZOKCRCSANwpBpeXVLcqrgn56zNSVX5ax84Ll\nzpfmJZ+uvZQl70oxHImzsL6CvtEo0UQKIsToDFsFxS3Dkwe6uX9nR2Khit8nvP9SuzRkc11+B22r\nQn4aqoJzNn83XzI929+IyF8BVSLyB8BngX9z77SKn1e3KO91ZkAk9y1MUns5SzUAN1N7KUq1K8Xi\n+ip6RsZpTSo8PxaN01JzbhC1jOHZg2e577kOjvZMlob8g4sWcvOG5VMqyc2WiFBTYQfeikBpdgAy\nDcBfAT4FvArcATwK3OvWSZUCr25RPh63EDhnHnC550G9YCwS5+zw+DnLym+4opWv/+oAp4fCWJbB\n5xNqQgE+t/ktifsYY9h1pJdtOzo41D2caN98YTO3Xt1O2/z8lYb0iVBXaQ+sBeZwB2M3ZBqAq4Bt\nxpj/DSAifqetvKPNDLy6PU3AJ4xPW99v0JVwpSwat+gZzqBamZms/5zs5WN9bNvRwb4Tg4m2qy+w\nS0NeMENt6WwF/T7qK4PUVQYSxeFLXaYB+NfAe4CJt7Yq4D+Aq904qVJQLtvTZDuQaNIUV0nXXk58\nAqkus1RjQabVyh58sZPaigDNSYttxqJxvvvsER5+qZM9xyZLQ75jeRO3b2znbYvzVxqyIuhPLJwo\nN5leUaUxJvG5whgzLCLl3dXLQKlvT5PLQGIszR9quvZyEhAhkuI6AyUw2j7dUDhK30g0o1VsJwfH\nqE/aQTgcjdMzEpkyI+SSJfV8atMK1rTmrzRkjTN/t5wHeDMNwCMistYYswdARN4BZD8Lu4yUw/Y0\nuQwkirMlQnLMsfeGK70glK10Y/6z305y7kwEz/EZZjBMNzEI5xOhZ2Sc4fHJx164sJbbN67givb8\nlIaUpPyuG8uQi02mAfjPgJ+IyAnsMZdFwMdcO6sSUA6DcJ19o4xHYxw5O5LYYn5+TXDGRRXVQR9D\n4/FzpoCW81zYCelq28625u1ciMUtekcjDIezr1b2Bxct5J+eOshYdPJ1EfAJN1zRym0b2/MSeIuh\nME4hZBSAjTEvishq4K1O0xvGmPKfdzSDshiEsyzODE/+b7QMnBmOsqwhfTC9ZGkjr3b1TZl6VRvy\ncclS93YlULkzxjAwFqV/NJqYVpapM0Pj/PD5ozz62qnEm4zfJyxrrOKOa1Zy1QXzZ31+Qb+Pxuri\nKIxTCDMGYBF5lzHmSRH58LQfXSgiGGN+6uK5FbVcdpMoNr1jdm9IJv7j1HeYaE9lw8p5vNDRS9Av\niUGpsZhhw8p5c3HKKgsj4zF6R7LfBLNvNMKPdh3jkb2TpSFb6ir45FXL+cOLF+Zl6lepLpzIt/Nd\n/e8BTwJ/lOJnBvBsAN68uoWtXf3c++wRRiJxakJ+Pr1pRcnkfwHGY0m1DZzOkV9IlAVMZefhXgJi\nSEoDUuG32z/v7umqDI3H4vSORBibYXPVVAbHojy8u5Of7jlO2HkNzKsJ8Ykr23j/pYtnXcymHBZO\n5NuMAdgY89ci4gMeM8Y8PEfnVBKePtDN9j3Haa6roM3pAW/fc5zLljWWTBCeqG2Q3AM+X22D33b2\nTQm+AONxu10VlmUZekcjDI5llx0cGY/x0z3HefilTkac/7n1lQFuWN/GBy9fQmXQzwuHe3nwxU5O\nDo6xuL6KG65oZX2Gn3omNrasrwyU/MKJfDtv/98YY4nIXwIagJOUw1LkeVUBRiNxu/NrprankzwQ\nk0m7mhtD4Si9WW6CGY7G+flvT/DgC8cmS0OG7NKQH167lBpn3u0Lh3v55pMHCfiE+soAPSPjfPPJ\ng3yBVTMG4aDfR32VXRinXBZO5FumCZj/FJEvAg8BIxONxpje9A8pbxM1Ug+fGSYStwj5fSyoDZXU\nLAh8Ppprg/SMRKfMghCf9lJKxXgsztnh7KaVRWIWj756kh/uOkbvSASAyoCPD61dysfWtVI/bXbP\ngy92EvAJVc583Ikxjwdf7EwZgCudhRM1ZbhwIt8y/Q19DLuP9Nlp7aUz4pRndRUBDnYP4/cJfqdG\n6vH+MKvyuPTSba1N1Rw5O0xV0J94E/H7fKU1k8Ojckk3xC3Df+w7xf07p5aG/KM1S/j4+jbm1aQu\nDTl9IQbYtXyTC7KLCDUhP/VlvnAi3zINwBdhB99N2IH4v7ALsntWYulmojbqtPYSMDGjwSd27zcS\ntzgzHOHj69N/rJxeiCe5Xc2NbNMNljE8deAM9+/soKvPDpp+n7Dl4kV88qo2WuorZ3z8xEKMqqTA\nGo5aLKqvwidCfZXmd3OVaQC+HxgEvuV8/3Gn7aNunFQpGI7EWdpYydnhSKL3uKi2gpEsR54Laefh\nXlrqQgyOxRLXUF8VmHFGQyjgSzlLohi3e8m3Qr/5jMfi9AxHCGeYbjDGsONQD/c918GRs3bmUID3\nOKUhlzZmVhryhita+eaTBxmLxqkM+ghHLeKW4U/euYK2edWa352FTAPwJcaY5CozT4nI626cUKmY\nWIixsnky5TAaidFSN3Nvoph09o0yv6aCBbWT52yMmTGPvXJBDW+eHsKa2BMOu/e8ckHm29Oo7GSb\nbjDGsPtoH9ue7eCN05PbNv7ehc3ccvVy2rPYSghg/cp5fIFVPPhiJ6eHxmhtquGzmy8omcHmYpZp\nAN4jIlcZY54HEJErgd2ZPNApXbkbOG6M+YCIrAAeBOYDLwGfdHbbqAC+D7wD6AE+ZozpcJ7jq9j1\niOPA540xv3LatwDfBPzAvcaYu5z2lMfI8FozUg4LMSZywEPhyR5wXWWAFQvS57GvvWQR+09N/lEb\n7Klr116yaA7O2HuyTTfs7exn244jvHp8sjTkVSvncdvV7axaWJfzebzrbS18cO1Sze/mWaafG98B\nPCciHSLSAewErhCRV0XklfM89gvA/qTvvw58wxjzFqAPO7DifO1z2r/h3A8RuQi4AbgY2AJ8W0T8\nTmD/Z+Ba7Bz1jc59ZzpG3mxe3cKd111MS10lA2NRWuoqufO6i0uqV7Bh5Ty6h8YZidhvHiORON1D\n4zOuarvnmd9l1V5O0q2UdWMF7Xgszon+Mc4MjWcUfPefHORL21/hzx/emwi+l7c28q0bLud/fujS\nnIKvT4SGqiCt86ppqa/U4OuCTHvAW3J5chFZBrwf+FvgL8Re7P0u7Bwy2Hnk/xv4DnC9cxtgO/BP\nzv2vBx40xowDR0TkEPYGoQCHjDGHnWM9CFwvIvtnOEZebV7dUlIBd7rHXjuFMJnbnLj92Gun+Px7\nLkz5GC9sy5NWujiYx3HXbFTYUDMAACAASURBVNMNv+seZtuODnYe7km0XbS4jts3rWBtW1NO51CO\nhc+LVabFeI7m+Pz/CPwlMPH2Ox/oN8ZMFBvoApY6t5cCnc7xYiIy4Nx/KfB80nMmP6ZzWvuV5znG\nFCLyGeAzAG1tbTlcXmk7fHaE5A0OJm4fPjuS/kEelu4tJl9vPYPhKH0ZphuO9Y5y/3MdPPXGmUTb\nW5pruX1TO1eumJdTYZtyLnxerFz7TYvIB4BuY8xLIrLZrePMhjHmHuAegHXr1mXdjyn1beljljln\nhwfL2O1q7oxF4vSMjM9YBnTCyYExvr/zKE+8fjrx/275vGpu3djOO1ctwJdD4PVC4fNi5eZb3Ubg\nOhF5H1AJ1GMPmDWKSMDpoS4Djjv3Pw60Al3OtvcN2INxE+0Tkh+Tqr1nhmPkTTlsS2+lCbTp2lV+\nReMWfSMRhsfPX6P3zNA4D+w6xqOvnky8QS5uqOSWq9t59+qWrGvoTmxsWZ9h4fNS72wUK9cCsDHm\nq8BXAZwe8BeNMZ8QkZ8AW7FnKdwC/MJ5yCPO9zudnz9pjDEi8gjwIxH5B2AJsAp4ATtducqZ8XAc\ne6Du485jnkpzjLy5+5nDRGJxeoanziAopVoQuaQ0Az5I1VHzwDRgfKRON2R76ZZl6B+LMjAWPe/C\nnb7RCA++0Mkv9p5I9JCbayv45IblbMmhNGTA56OhKrv8bjl0NopVIZI9XwYeFJG/AV4Gvuu0fxf4\ngTPI1osdUDHG7BORh4HXgRjwOWNMHEBE/hT4FfY0tG3GmH3nOUbevHl6kMFwDB+CX4RY3NAzEiEW\nHzz/g4uE3ycp840z9abSfUrO4NNzyVvSWElXfzhle6Yy3YttKBzl4d1d/OueLsJOoaOm6iAfv7KN\nP7psSdYLX0IBXyK/m21+uBwKTxWrOQnAxpingaed24eZnMWQfJ8w8MdpHv+32DMpprc/Cjyaoj3l\nMfJpolD1RC9CxO7ZROKl8/G9KigMj597vtVBHflOpbYicM5qOHHazycctWv0nm8V22jEKQ25uyuR\nmqirDPCxda186O1LqQpll6etCvlprApl/bhk5bD9VrHS4c4chQI+xiJxLGeDSuNMISilJbnLGqs5\ncHr4nPaljVqMJ5WzI5Fz0jPGaU8nbhl6RyIMhWeeVjYejfPI3hP86IVOBpwpaNUhP1vXLmPrumVZ\nzUyYKIzTUJ2fwudlsf1WkdIAnKNVLXV09AxPraNQE6R9fulUQ0tXt6KU6lnMpXRzc9O1D4zZ08pm\n2ostGrd49NVT/HDXUXqG7UBeEfDxwcuXcMMVbTRUB9M+djpf0o7C+SyMUw6rPouVBuAc3XHNSr60\nfS9xy2CMIW4ZYiX2ojw1cG4+c6Z2r0uXXprensnW73HL8MTrp/n+zqOcGrR/3wGf8IHLFvOJK9uY\nX1uR8XnlMrCWjc2rW7gTOxfc1TfKMp0FkTcagGfBAIj9kQ/J64KoORFL0zNL165mlkm6wTKG37xx\nhu8910GnUxrSJ7Dl4kXctGE5i85TGjLZbAbWslXqqz6LlQbgHN39zGEaqoIsbpgs6VdqI8Ni0pRX\n1Pib0kzlKO2t39OvYjPG8Nzv7NKQh89MloZ899tauHnD8qzyqdUhO80wm4E1VRw0AOeoHEaGK0N+\nRlPkeyv1DzulZU1ViV5rskX1FfQMj6d8jDGGl472sW1HBweSqshtessCbtvYzooMy3jqjsLlSQNw\njsphZNif5lNrunav+x/XX8Jnf7RnyptWZdDHF96dunDRq10DbNtxhL1dA4m29e1N3LZxBW9dlFl1\nMt1RuLxpAM5ROYwMiwgTYzbGTJZVdDufWMoi0wbWYilWoLxxaohtO47wYkdfom3NsgZu37iCS5c1\nZHQc3VHYGzQA56gcRoaDfnEWkJDYmt7ng5B2gVP6i4f2EJuW4o0ZuOux1/np5zZx5OwI9+3o4NlD\nZxM/X72ojk9tWsHatsaM3ti0Ipm36P/lWSj1keGWukr6RqJTCgIbC5pLaFuluTAes1ex9Y6lnlbW\nH47zN/++n6cOdCcG6S5oruG2je1sWDk/o8CrFcm8SQPwLJR6hSiTvIoPwElDlNLOzm6yLEPfaITB\ncOy8v5MnD3QD0NpUxW0b27nmwubzloYUEWqdwFtKKyhV/mgAzlE5VIg6OxKxg29yD9jMvLTWKwbD\nUfozKJozYVF9JbdcvZz3vG3heUtD+n1CfWWQ+qpg1mUkVXnRAJyju585zHA4Sv9YFMvYk+kbq4Il\nNQ84ErOm7Gcm2D3gTAqDl6twNM7Z4cyKoye7//YrzltXN+Dz0VBtz2jQgU4FGoBztu/EAIPh2OSe\nagZ6R6PsOzFwvocWDctYJK+infiUbYz3AnAsbtGbpjj6cDjGT17qTPGoSTMF37lcsaZKiwbgHCUK\n1iT/PZnSKmTjk9QlxkW8k480xtA/an+SmZ7nHYvG+dme4zy0u5Oh8Pl3rZhOV6yp89EAnKOJbXum\nj82U0nY+6QaWvDIINzweo28kQjQ+9U0oErP4t1dO8KNdx+gbtes6TMz1Pp+JgbX6qoCuWFPnpQE4\nR3WVgcTH1eRFDKU0f3NiIUbye4ZPyn8hxsS0srFpn1ZicYvHXjvFD54/ylmnNGQo4OP6NUu4cX0r\nH/7OzrTPWe4Da6U+46dYlU60KDKf3rSCbz55CJ+QCGKWsdtLiWWmZlFKqAOftfjEtLJp9XvjluHX\n+09z/86jnByYLA35vksXc9NVbSzIoDRk27zqsn3jKocZP8VKA3COPv8ee/3/vc8eYSQSpybk59Ob\nViTaS0WqLXbKUapqZZYxPPPmWb73XAfHeu0iSj6B9160iJs3LGdRQ+YLUso1+ILuCecmDcCz8Pn3\nXFhyATfZeCyWcoudSCz7AadilWpamTGG5w/3ct+ODg6dmdyS6fff2swtV7fTNq90CirNhXKo/Fes\nNAB7WMxKXeE2apV+by7dtLI9R/vYtuMIr5+cLA258YL53LqxnQuaU28nNZHf9apyqPxXrDQAe1i6\nGRulNJNjOssydrph2rSy144PsG1HB7/t7E+0vWN5E7dvbOdti+tTPlfQby+cqPP4/N1yqPxXrDQA\nz0KpjwynC7OlGn5T5XnfPD3Eth0dvHCkN9F26dIGbt/UzppljSmfpypkVyRL7vF5WTlU/itW+grL\n0dMHuvni9r0Mj8eIW4azw+N8cfte/n7rGn1hzrHRSIye4anzeY+cHeH+5zp45uBkaci3Lqzj9k3t\nrFvedE6PVnecmNkrXf3sOzHASCTOwFiUV7r69XWeBxqAc3TXY/vpH43iF8EvgrGgfzTKXY/tL5kX\n5kx7nJWCSMzO845GJvO8x/vHuP+5Dn69f7I05MoFdmnIqy84tzSk7jhxft/6zzcTUy4DPjv/+80n\nDwGU9CB0MdAAnKMjPaOAIWqZxEIMn0y0lwafQKqd1ot9HUGqMpHdg2F+8PwxHnvtZGIu87KmKm7Z\n0M7vrz63NKTuOJG5e5894gRf+w3KJxCzLO599ogG4FnSAJwjyzLELKe36JRxjBmQEsqgBvw+TMya\nUg3C57QXq6FwlL6kMpG9IxEe2HWMX75ygqjzbrKwvoKbr1rOey9edM6qtFDAR2N1qKRWLBbaSCTO\n9HLFPimtuifFSl+FOQr6fUQt5wVopraXipULajjYPUzQJ4nC7HHLsDLDnXrn0ngsTs9whLBTj2Fg\nLMpDL3by85ePE3bm+M6vCXHTVW1ce8nicwqcV4X8NFaFtDBODmpC9syH5Pcyy9jtanY0AOeoKuRj\nPB5P7KcmgN8H1aHSCcBf3rKaL23fy1A4RixuEfD5aKoO8uUtqwt9agmxuEXfaJShsL18eGQ8xk9e\n6mL7S12J3YnrKwN8/Mo2rluzZMqWPiJCTchPQ3V+BtYqAj7GU9QJrijz3Sw+vWkF//jrg0Tjkz1e\nn5TesvtipAE4RxcurOfI2WGGwjEicYuQ30ddZYAVC1JP5i9Gm1e38Hdb1xTl9KKJMpEDY1EsYxiL\nxvnFy8d58MVOBp3SkDUVfj66rpWPrF06ZcqYT4S6SrsUZD7TKbF46jrJ6drLxWXLGqkJ+RmJxBOb\nD9SE/FyWZhqfypwG4BxNTE5f1BAo6cnpxTi9aHg8Ru9whJhlEYlZ/PKVkzyw62iiNGRl0MeH376U\nj65rpT5piazbFclSDVjO1F4u7n7mMC31lVPe5LQWRH5oAM7R5tUtbO3qP6cYTym9IIttelFymchY\n3OJX+07zg+eP0j00DkDQL1y3Zgkfv7KNpupQ4nG61Y+7tBaEezQA5+jpA91s33Oc5roK2pwe8PY9\nx7lsWWPJBOF7nz1C3DJMH8ue6+lFccvQOxJhKBwlbhmePNDN/Ts7ONFvl4b0+4T3XbqIm65cTnPd\nZGlI3epnbmgtCPdoAM7R3c8cJhKL0zM8NQdcSh/LBtNss5OuPd+Mceo2jEaJWxb/degs9+3o4GjP\nZGnIP7hoIZ+8ajlLGqsSj9MZDXNLa0G4RwNwjt48PchgOIYPeyVcLG7oGYkQiw8W+tRKwsS279F4\nnBc6etn2bAcHuydLQ/7ehc3cevVyls+fnBJXWxHI24wGlTmtBeEeDcA5isYNljHEzeRKOBGIlPuI\nzCyNReL0jNj1eV8+1se2HR3sOzH5pnXVynncvnEFb2mxZ5NM7LHWWB0sqTnW5Wbz6hYNuC7QADwL\ncWuyboIx5b2dz2wl1214/cQg23YcYc+xpNKQbY3ctnEFFy2xS0P6RKivKq4aDdP3z0tuL3elXvmv\nWGkAngWvbOczG3HL0O/UbTh4eohtO47w/OHJ0pCXLKnn9k0ruLzVnlPq9wkNVUHqK4NFV6Mh6E+9\nEKPce+a6J5x7NADnyDJWyu18jCmdSfluruxKHmDrODvCfc918Js3zyR+vqqllts3tbO+fR4ikiiO\nU8xTycqxgH0mdE8492gAzpGVZtueeAlt51NX4U8ZgOsqZjfINTHAdqx3hO/vPMp/7j+d+Oi+fH41\nt21s551vWYCIUBm0a/DWlEBxHJ9PEMuc86mn2Hrq+abzgN1T/K/6IhVNs/w0XXsxGkoz3Sxd+/lM\nFEY/0T/GD58/yqOvnUrsTrGksZJbNrTzrtUt+H1CTYW9VDi5dkOxqw356Jn2hmWc9nKm84DdowE4\nR+nCbOmEXxhPM2MjXfv5vH5ikB+/cIxH9k6Whmypq+CTVy3nDy9eSDDgt6eSVQXPqVZWCgbHU5df\nTNdeLnQesHs0AOfIq/nAmdx0765Eacim6iCfuHI5H7hsMZVBvyvFceZaNM0bU7r2cqHzgN2jAVjl\nTThmUV8Z4IYrWvng25cm0gzFOKNB5aa832rmngbgHAV9QiRFbzdYxoHmfL37WzYsZ+s7ltFQFbID\nb1XxzmhQmdNpaO4p3c+DBVYOOeDqNLUUprdbzlze350ZTnn/CZ9+50qWL6ihdV4VDdVBDb5lInka\nmoj9NegX7n7mcKFPreRpAM5RLE1vMF17MfpvaQZRJtqNMQyMRjnSM8wDzx/lpu/umvH5WudVU1+p\ngbfcdPaNUjVttopOQ8sPTUGocxhjGAxH6R2O8MTrp7l/ZwddfWOFPi1VIDoNzT0agD3sX35jf4RM\n7q8a4NtP/46mmgrue66DI2dHEvd5z0ULeeL103N+nqqwdBqaezQAe9ios8Pw9KTJeNzwtUf2Jb6/\nZtUCbt3YzkWLGzQAe5BOQ3OPBmAPm15MaLorV8zjto3tXN7aRGN1aa1aU/ml5SjdoQHYo0bGYwQE\noikisADfvOFy1q+Yr4E3id8niaXV09uVyoUGYI8ZHo/RPxph/8lBjIhdyHiaxqoAf3jJIt15Yprq\noI+hFMuOq4M6mUjlRgOwR0wE3t91D/O95zp46o0zKe8nwKKGKg2+KVQEUgfgfJTvVN7k2itHRFpF\n5CkReV1E9onIF5z2eSLyhIgcdL42Oe0iIt8SkUMi8oqIrE16rluc+x8UkVuS2t8hIq86j/mWOBNQ\n0x3Di4bHY3T1jfJKZz9/88v93Pa9FxPBN+if+tFZnH8mRa9YQe9oNKt2pc7HzbfuGPB/GmMuAq4C\nPiciFwFfAX5tjFkF/Nr5HuBaYJXz7zPAd8AOpsBfA1cC64G/Tgqo3wH+JOlxW5z2dMfwjKFwlM7e\nUV4/McD/+/gb3LztBR7fdwrLwOKGSr5y7Wqqgz58MnUamvjg7PB4wc67mKVbY1NCa29UkXEtBWGM\nOQmcdG4Pich+YClwPbDZudv9wNPAl5327xu7+/W8iDSKyGLnvk8YY3oBROQJYIuIPA3UG2Oed9q/\nD3wQeGyGY5Q1Y4yTaohyZijMj1/o5Bd7TxBxKpQ111bwyQ1t/NFlS2iur+TbTx2yg68zHUKcr7qx\naGpeHoTTPeHcMSc5YBFpB94O7AIWOsEZ4BSw0Lm9FOhMeliX0zZTe1eKdmY4xvTz+gx2b5u2trYs\nr6p42CvXYgyORekbifDQ7k7+dU8X4ehkacgb17fxobcvZWFDJfWVk7sbxM20jUULcP6lYv3yRnYe\n6UvZXs60GI97XA/AIlIL/CvwZ8aYweQ6AcYYIyKudrdmOoYx5h7gHoB169aVXLfPsuwlwwNjUYbD\nMf51TxcP7+5ieNze0aK2wi4N+eG1S1nSWEVD1bl1Gqbv9OuBzlzO+tLketO1lwvdE849rgZgEQli\nB98HjDE/dZpPi8hiY8xJJ8XQ7bQfB1qTHr7MaTvOZDphov1pp31ZivvPdIyyELcMg2NRBsNRRsdj\nPLL3BD96oZOBMTsQVAX9bH3HUj66rpXFjVU0VYdSfky2jHVO/tIypbWx6Fw60jNKyC/4fZNDJ3HL\n4khPeRel0T3h3ONaAHZmJHwX2G+M+YekHz0C3ALc5Xz9RVL7n4rIg9gDbgNOAP0V8D+TBt7eC3zV\nGNMrIoMichV2auNm4H+d5xglLRq3GBiLMhSOEYnFefTVU/xw11F6hiOAPR3q+suXcOMVbSxurGJe\nTWjGrX984sMndrA1EzlgQESnVaVjGUMsFk/8vnwC/jKv/qbFeNzjZg94I/BJ4FUR+a3T9lfYQfFh\nEfkUcBT4qPOzR4H3AYeAUeA2ACfQ/g/gRed+d04MyAGfBb4HVGEPvj3mtKc7RkkKR+MMjEUZGY8R\ntwxPvH6a7+88yqnBMAABn/D+yxZz05VtLG2qZl5NKKPVa6GAD39E7N1+nTUZlmVKcr+2udBSV0Fn\n39iUnHnMwOKGioKel9u0GI973JwF8SxTZzgle3eK+xvgc2meaxuwLUX7buCSFO09qY5RakYjMQbG\nooxF4ljG8MybZ7hvRwedTmlIn8CWixdx04bltDqBN5vt3Ve11NHRM8zgWIxI3CLk91FfE6R9fq1b\nl1TSakJ+/E7O3GC/uP1it5czLcbjHl0JV2QmppINjEWJxCyMMew83MN9Ozr43ZnJ0pDvWt3CLVcv\nZ/n8GhqrQjlt/zPRs1nUENCeTQaGI3GWNVVxdjiSeMNaUBtiJFLeuyKDFuNxiwbgHAV9EE0xVpVr\nWYC4ZRgKRxkcixGz7MC751g/23YcYf/JocT93rlqAbde3c7K5lrqKwM0phlgy4T2bLIzkQtd2Tz5\nCWE0EqOlrrKAZ6VKmQbgHMXSTFpL157OxMDacDiG5SwBfrVrgG07jrC3ayBxv/XtTdy+aQUXLqyj\nOhQ47wBbtkpuDl4BaC5U5ZsG4BylK5eQaRmFcDTO4Fg0MWcX4I1TQ9y34wgvdExO9l+zrIHbN67g\n0mUNBP0+5teGpoxGz4ZOsM+OfmJQ+aYBeI6NReL0jUYIRyfzhkfOjnDfjg6ePXQ20bZ6UR2f2rSC\ntW2N+H0+mqpzy/PORCfYZ8+ruVBdiuwODcBzwBjDSMSeSjaeFHi7+ka5/7mjPHmgO5ECuKC5hts2\ntrNh5XxEhLrKIPNqcs/zzkQn2KtM6Ccl92gAdtHEUuGJgbUJpwbD/HDn0UR1MoDWpipu29jONRc2\n4xOhKuRnXk3I1bq8OsFeZUI/KblHA7AL4pZhYCzK4Fg0MbAG0DM8zgO7jvHvr54k6lQcW1RfyS1X\nL+c9b1uI3ycE/b6s5/PmSgeVVCb0k5J7NAC74Fjv6JSi5gNjUR584Rg//+0Jxp3SkPNrQ9x05XLe\nd+kign4ffp/kPJ83V5tXt7C1q597nz3CSCROTcjPpzet0F6NmkI/KblHA7ALJoLv8HiM7bu72L6n\ni1Fnsn5jVZAb17dy3ZolVDjLheurgmkL5rjp6QPdbN9znOa6CtqcHvD2Pce5bFmjBmGVoJ+U3KMB\n2AVj0Tg/23Och3Z3MhS2p5nVVPj52LpWPrJ2GVXO0tW5yPPORHN7KhM6/c49GoBdcNO9uxI1YiuD\nPj6ydhkfXbeMOqcQetDvo6kmRO0c5Hln0tk3il/g8JnhKUtrNbeXnlenY3l1+p3bNAC7oG80Sijg\n4/o1S7hxfSuN1SEAfCI0VgdTFkYvhNqQn0NnRvCL4BchFjcc7w/zluaaQp9aUdLpWCrfNAC74Po1\nS/j4lW00102WKaytDDCvOkTAXzylHhNvAhPbIYOzN1zh3xyKkaZsVL5pAHbBF96zKnG7MujPuD7v\nXBsaj7G0sXJKda9F9RVTlkerSTodS+WbBmCXBHw+5tUWPs87E63ulR2djqXyrXg+D5eRpuoQrfOq\nijr4gj29KBo3jEZiGGN/1elF6Xn59/X0gW5uvOd5Nn39SW6853mePlBW2ywWjAZgFzTVhEoij7p5\ndQtb1y7lzNA4+08NcWZonK1rl2o+M43Nq1u487qLaamrZGAsSktdJXded3HZ/74mBh+7h8JTBh81\nCM9ecXfRlKt0IUb2vDgdSwcf3aM9YA9L/sMSsb8G/cLdzxwu9KmpItLZN0rVtEFkHXzMDw3AHqZ/\nWCoTrU3VjEWn7nung4/5oQHYw/QPS2XCy4OPbtMA7GH6h6Uy4dXBx7mgg3AepuUoVaa8OPg4F7QH\n7GHJsyDetqiO5roKtu85rtOLlJojGoA9TGdBKFVYGoA9TGdBKFVYGoA9TGdBKFVYGoA9TGdBKFVY\nGoA9TKcXKVVYOg3N43R6kVKFoz1glZWgP3WVt3TtSqn0NACrrNRXBpgeagVoqNQPU0plSwOwykq6\n3TKadRcNpbKmAVhlZWgsgpnWZpx2pVR29HOjysqZkSh+sYOuMSBipyDOjEQLfWpKlRztASulVIFo\nAFZZaa4NETdgGbsXbBmIG7tdKZUdDcAqK3WVQfxO2gHsr36x25VS2dEcsMrK0HiMZU1VnB2OEIlb\nhPw+FtSGGB6PFfrUlCo5GoBVVlqbqukeCrOyuTbRNhqJpZ2eppRKT1MQOaoO+bNqLxdawEep/NEA\nnKOqoA/ftCVhPoHqYHn/SrWAj1L5oymIHLXUVdI3EkVkcj4sxhsrwrSAj1L5oQE4R8YYfD7BL5II\nwnFjMGb6OjGllEpNA3COhiNxljZWTpkNsKi2gpFI/PwPLiJPH+jm7mcO09k3SmtTNXdcs/K8vdtc\nHqOUOld5Jyxd1NpUTcDvY2VzLasX1bOyuZaA31dS2/k8faCbrz2yj+6hMI1VQbqHwnztkX0z7oqc\ny2OUUqlpAM5ROcwGyGVXZN1JWan80QCco3KYDZDLrsi6k7JS+aM54Fko9dkAE4sqqkOTL4Pz7Yqc\ny2OUUqlpD9jDckmjlEPqRalioQHYw3JJo5RD6kWpYiE6b9W2bt06s3v37kKfhlKqPKXctVZzwB7X\n/pV/P6et4673z/iYP39wD4+8coq4ZfD7hOsuW8Q3bljr1ikqVbbKNgCLyBbgm4AfuNcYc1eBT6no\npAq+E+3pgvCfP7iHn/32ZOL7uGWc7/d4Igh7dRGKV6/bbWWZAxYRP/DPwLXARcCNInJRYc+qPDzy\nyinA2QvO+ZfcXs68ugjFq9c9F8oyAAPrgUPGmMPGmAjwIHB9gc+pLMSt1GMG6drLiVcXoXj1uudC\nuQbgpUBn0vddTtsUIvIZEdktIrvPnDkzZydXyvzTa3Cep72ceHURilevey6UawDOiDHmHmPMOmPM\nuubm5kKfTkm47rJFgF39beJfcns5a22qZiw6tdiSFxahePW650K5BuDjQGvS98ucNpUk3UDbTLMg\nvnHDWj50+eJEj9fvEz50+WJPDMB5dRGKV697LpTlPGARCQBvAu/GDrwvAh83xuxL9xidB6wyMTEb\noKtvlGUemg3g1evOo5Q5urIMwAAi8j7gH7GnoW0zxvztTPfXAKyUcpG3FmIYYx4FHi30eSilVDrl\nmgNWSqmipwFYKaUKRAOwUkoViAZgpZQqEA3ASilVIBqAlVKqQDQAK6VUgWgAVkqpAinblXDZEpEz\nwNEcH74AOJvH09FjF//x9dh67GycNcZsmd6oATgPRGS3MWadHts7x9dj67HzQVMQSilVIBqAlVKq\nQDQA58c9emzPHV+PrceeNc0BK6VUgWgPWCmlCkQDsFJKFYgG4AyJyDYR6RaR19L8XETkWyJySERe\nEZG8bZKWwbE3i8iAiPzW+fe1PB67VUSeEpHXRWSfiHwhxX1cufYMj+3mtVeKyAsistc5/v+T4j4V\nIvKQc+27RKR9Do99q4icSbr2T+fj2EnP7xeRl0Xklyl+5sp1Z3hs165bRDpE5FXnec/ZIifvr3Vj\njP7L4B9wDbAWeC3Nz98HPIa99chVwK45PPZm4JcuXfdiYK1zuw57r72L5uLaMzy2m9cuQK1zOwjs\nAq6adp/PAv/i3L4BeGgOj30r8E9uXLvz/H8B/CjV79et687w2K5dN9ABLJjh53l9rWsPOEPGmGeA\n3hnucj3wfWN7HmgUkcVzdGzXGGNOGmP2OLeHgP3A0ml3c+XaMzy2a5zrGXa+DTr/po9aXw/c79ze\nDrxbRFLu/+XCsV0jIsuA9wP3prmLK9ed4bELKa+vdQ3A+bMU6Ez6vos5DBbABufj6mMicrEbB3A+\nZr4duzeWzPVrn+HYFOiewwAAA/VJREFU4OK1Ox+Ffwt0A08YY9JeuzEmBgwA8+fo2AAfcT4KbxeR\n1nwc1/GPwF8CVpqfu3bdGRwb3LtuA/yHiLwkIp9J8fO8vtY1AJeHPcByY8wa4H8BP8/3AUSkFvhX\n4M+MMYP5fv5ZHNvVazfGxI0xlwPLgPUickk+n3+Wx/43oN0YcxnwBJM90lkRkQ8A3caYl/LxfC4c\n25XrdmwyxqwFrgU+JyLX5PG5z6EBOH+OA8nvxMucNtcZYwYnPq4aezfooIgsyNfzi0gQOwA+YIz5\naYq7uHbt5zu229eedJx+4ClgekGVxLWLSABoAHrm4tjGmB5jzLjz7b3AO/J0yI3AdSLSATwIvEtE\nfjjtPm5d93mP7eJ1Y4w57nztBn4GrJ92l7y+1jUA588jwM3OKOlVwIAx5uRcHFhEFk3k30RkPfb/\n17wEAed5vwvsN8b8Q5q7uXLtmRzb5WtvFpFG53YV8AfAgWl3ewS4xbm9FXjSOKM1bh97Wu7xOuwc\n+awZY75qjFlmjGnHHmB70hhz07S7uXLdmRzbresWkRoRqZu4DbwXmD7zKK+v9UDOZ+sxIvJj7BH3\nBSLSBfw19sAIxph/AR7FHiE9BIwCt83hsbcC/4eIxIAx4IZ8/DE4NgKfBF518pEAfwW0JR3frWvP\n5NhuXvti4H4R8WMH9oeNMb8UkTuB3caYR7DfIH4gIoewB0pvmMNjf15ErgNizrFvzdOxU5qj687k\n2G5d90LgZ877eQD4kTHmcRH5b+DOa12XIiulVIFoCkIppQpEA7BSShWIBmCllCoQDcBKKVUgGoCV\nUqpANAArzxORdklTaS7N/W8VkSVJ33e4sfhDlT8NwEpl71ZgyfnupNT5aABWyhYQkQdEZL9T4KVa\nRL4mIi+KyGsico+z+mkrsA54QOyasVXO4/+7iOwRu5bsagAR+T2ZrFn78sQqK6UmaABWyvZW4NvG\nmLcBg9j1bv/JGHOFMeYSoAr4gDFmO7Ab+IQx5nJjzJjz+LNOEZfvAF902r4IfM4pqPNO7JV6SiVo\nAFbK1mmM2eHc/iGwCfh9sXd7eBV4FzBTqcuJQkEvAe3O7R3AP4jI54FGp2yjUgkagJWyTV+Tb4Bv\nA1uNMZcC/xuonOHxE9W54jg1VowxdwGfxu4975hITSg1QQOwUrY2Edng3P448Kxz+6xTj3hr0n2H\nsLdImpGIXGCMedUY83XgRUADsJpCq6EpZXsDuwD3NuB17FxuE3Y5wlPYAXTC94B/EZExYAPp/ZmI\n/D72zg77sPcSUypBq6EppVSBaApCKaUKRAOwUkoViAZgpZQqEA3ASilVIBqAlVKqQDQAK6VUgWgA\nVkqpAvn/AV6R1kIlMXxAAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o0K5PriZVY72",
        "colab_type": "code",
        "outputId": "e63f7a95-2eac-4e84-9c85-9252a9c972e1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        }
      },
      "source": [
        "df.corr(method ='kendall')"
      ],
      "execution_count": 39,
      "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>zip</th>\n",
              "      <th>beds</th>\n",
              "      <th>baths</th>\n",
              "      <th>sq__ft</th>\n",
              "      <th>price</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>zip</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.018953</td>\n",
              "      <td>-0.005025</td>\n",
              "      <td>-0.016095</td>\n",
              "      <td>-0.067694</td>\n",
              "      <td>-0.080830</td>\n",
              "      <td>-0.364485</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>beds</th>\n",
              "      <td>0.018953</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.615725</td>\n",
              "      <td>0.528635</td>\n",
              "      <td>0.322866</td>\n",
              "      <td>-0.115128</td>\n",
              "      <td>0.018372</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>baths</th>\n",
              "      <td>-0.005025</td>\n",
              "      <td>0.615725</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.535217</td>\n",
              "      <td>0.366823</td>\n",
              "      <td>-0.073400</td>\n",
              "      <td>0.068689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sq__ft</th>\n",
              "      <td>-0.016095</td>\n",
              "      <td>0.528635</td>\n",
              "      <td>0.535217</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.415124</td>\n",
              "      <td>-0.083057</td>\n",
              "      <td>0.051609</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>price</th>\n",
              "      <td>-0.067694</td>\n",
              "      <td>0.322866</td>\n",
              "      <td>0.366823</td>\n",
              "      <td>0.415124</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.018218</td>\n",
              "      <td>0.129167</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>latitude</th>\n",
              "      <td>-0.080830</td>\n",
              "      <td>-0.115128</td>\n",
              "      <td>-0.073400</td>\n",
              "      <td>-0.083057</td>\n",
              "      <td>-0.018218</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.281511</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>longitude</th>\n",
              "      <td>-0.364485</td>\n",
              "      <td>0.018372</td>\n",
              "      <td>0.068689</td>\n",
              "      <td>0.051609</td>\n",
              "      <td>0.129167</td>\n",
              "      <td>0.281511</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                zip      beds     baths  ...     price  latitude  longitude\n",
              "zip        1.000000  0.018953 -0.005025  ... -0.067694 -0.080830  -0.364485\n",
              "beds       0.018953  1.000000  0.615725  ...  0.322866 -0.115128   0.018372\n",
              "baths     -0.005025  0.615725  1.000000  ...  0.366823 -0.073400   0.068689\n",
              "sq__ft    -0.016095  0.528635  0.535217  ...  0.415124 -0.083057   0.051609\n",
              "price     -0.067694  0.322866  0.366823  ...  1.000000 -0.018218   0.129167\n",
              "latitude  -0.080830 -0.115128 -0.073400  ... -0.018218  1.000000   0.281511\n",
              "longitude -0.364485  0.018372  0.068689  ...  0.129167  0.281511   1.000000\n",
              "\n",
              "[7 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B1-NPEkHWEWd",
        "colab_type": "code",
        "outputId": "c7f7ebe9-2c8b-4745-b37f-d4995dfd707f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 408
        }
      },
      "source": [
        "df.corr().unstack().sort_values(ascending = False).drop_duplicates()"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "longitude  longitude    1.000000\n",
              "sq__ft     baths        0.666713\n",
              "beds       baths        0.664115\n",
              "sq__ft     beds         0.650869\n",
              "price      sq__ft       0.525367\n",
              "baths      price        0.475334\n",
              "price      beds         0.412636\n",
              "latitude   longitude    0.387925\n",
              "price      longitude    0.284485\n",
              "baths      longitude    0.132186\n",
              "beds       longitude    0.054626\n",
              "longitude  sq__ft       0.044055\n",
              "beds       zip         -0.038355\n",
              "baths      latitude    -0.039411\n",
              "price      latitude    -0.039573\n",
              "zip        sq__ft      -0.043852\n",
              "baths      zip         -0.088795\n",
              "beds       latitude    -0.093180\n",
              "price      zip         -0.093353\n",
              "sq__ft     latitude    -0.159076\n",
              "latitude   zip         -0.290389\n",
              "zip        longitude   -0.539904\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l7x-9q-SW6sP",
        "colab_type": "code",
        "outputId": "33c6fdd9-b0cb-463b-c82c-947922f801fb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "covariance = np.cov(df['sq__ft'], df['price'])\n",
        "print(covariance)"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[3.75061406e+05 4.45187121e+07]\n",
            " [4.45187121e+07 1.91451054e+10]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UKK5G7ccYAlb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X = df['sq__ft'].values.reshape(-1,1)\n",
        "Y = df['price']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L_POgPjlYWIP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size = 1/3, random_state = 0)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Aq98rKwgY0dS",
        "colab_type": "code",
        "outputId": "2026abff-7aa2-4c91-ceab-67d7bb962896",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "regressor = LinearRegression()\n",
        "regressor.fit(x_train, y_train)"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SQCh0UeIe2I3",
        "colab_type": "code",
        "outputId": "83ef3579-6ce2-4238-f828-3a4b174c5a6c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        }
      },
      "source": [
        "train = plt\n",
        "train.scatter(x_train, y_train, color = 'red')\n",
        "train.plot(x_train, regressor.predict(x_train), color = 'blue')\n",
        "train.title('Price vs Area (Training Set)')\n",
        "train.xlabel('Area in sq. ft.')\n",
        "train.ylabel('Price')\n",
        "train.show()"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZ8AAAEWCAYAAAC5XZqEAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGInz/wFl1YtftV6EggAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xl0X_8SNoi_3",
        "colab_type": "code",
        "outputId": "be4d8aa1-96a1-43d4-9aa1-6adaeb933e6a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        }
      },
      "source": [
        "test = plt\n",
        "test.scatter(x_test, y_test, color = 'red')\n",
        "test.plot(x_test, regressor.predict(x_test), color = 'green')\n",
        "test.title('Price vs Area (Testing Set)')\n",
        "test.xlabel('Area in sq. ft.')\n",
        "test.ylabel('Price')\n",
        "test.show()"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAAEWCAYAAACqitpwAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nw0gcExfDMAwjcf4/XyRUe8bmaXEAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4pVoCQ7ViMOn",
        "colab_type": "code",
        "outputId": "1e569637-8daa-4fac-d10f-97d5d61b7fcc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "y_pred = regressor.predict(x_test)\n",
        "print('Actual values' + '\\tPredicted Values' +'\\tError')\n",
        "err = y_test - y_pred\n",
        "for i in zip(y_test, y_pred, err):\n",
        "  print(i)"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Actual values\tPredicted Values\tError\n",
            "(211500, 166719.38113072014, 44780.61886927986)\n",
            "(395100, 436144.0921005355, -41044.09210053552)\n",
            "(129000, 186467.18463515153, -57467.18463515153)\n",
            "(124000, 187391.05848331208, -63391.05848331208)\n",
            "(176850, 227810.53934033538, -50960.53934033538)\n",
            "(480000, 209092.47999940577, 270907.5200005942)\n",
            "(220000, 166950.34959276026, 53049.65040723974)\n",
            "(610000, 470558.3929445154, 139441.6070554846)\n",
            "(362305, 265111.9459598169, 97193.05404018308)\n",
            "(325000, 328281.8203277933, -3281.820327793306)\n",
            "(130000, 196860.7654269575, -66860.76542695751)\n",
            "(215000, 216146.63200730865, -1146.6320073086536)\n",
            "(339000, 241437.67860070322, 97562.32139929678)\n",
            "(270000, 291673.31909443217, -21673.31909443217)\n",
            "(300567, 239358.96244234202, 61208.03755765798)\n",
            "(108750, 175265.21422620508, -66515.21422620508)\n",
            "(145846, 235432.49858765976, -89586.49858765976)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(460000, 518253.3803558029, -58253.38035580289)\n",
            "(339000, 185196.85809393082, 153803.14190606918)\n",
            "(271742, 169837.45536826193, 101904.54463173807)\n",
            "(137721, 275505.5267516229, -137784.5267516229)\n",
            "(164000, 186582.6688661716, -22582.66886617159)\n",
            "(257200, 358076.7519309705, -100876.75193097052)\n",
            "(134555, 190278.16425881372, -55723.16425881372)\n",
            "(220000, 186005.24771107128, 33994.75228892872)\n",
            "(115000, 184272.98424577026, -69272.98424577026)\n",
            "(261800, 209092.47999940577, 52707.52000059423)\n",
            "(306000, 209092.47999940577, 96907.52000059423)\n",
            "(225000, 223653.10702361297, 1346.8929763870256)\n",
            "(218000, 304607.5529686797, -86607.5529686797)\n",
            "(371086, 209092.47999940577, 161993.52000059423)\n",
            "(276500, 247789.3113068069, 28710.688693193108)\n",
            "(334000, 312691.4491400843, 21308.550859915675)\n",
            "(210000, 209092.47999940577, 907.5200005942315)\n",
            "(221000, 212104.6839216063, 8895.316078393691)\n",
            "(178760, 219611.15893791063, -40851.15893791063)\n",
            "(97500, 168567.1288270412, -71067.12882704119)\n",
            "(116100, 192818.8173412552, -76718.8173412552)\n",
            "(471750, 505434.63071257545, -33684.630712575454)\n",
            "(361745, 276660.3690618236, 85084.63093817641)\n",
            "(185000, 168105.19190296094, 16894.80809703906)\n",
            "(181000, 241206.7101386631, -60206.7101386631)\n",
            "(282400, 474369.3725681776, -191969.37256817758)\n",
            "(330000, 209092.47999940577, 120907.52000059423)\n",
            "(115620, 220073.0958619909, -104453.0958619909)\n",
            "(120000, 287631.3710087299, -167631.3710087299)\n",
            "(156000, 186929.12155923177, -30929.121559231775)\n",
            "(236250, 206330.47237060298, 29919.527629397024)\n",
            "(85500, 183349.11039760974, -97849.11039760974)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(247480, 193742.69118941572, 53737.308810584276)\n",
            "(127059, 183464.5946286298, -56405.5946286298)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(61500, 169260.03421316162, -107760.03421316162)\n",
            "(180000, 224807.94933381365, -44807.94933381365)\n",
            "(65000, 181963.29962536893, -116963.29962536893)\n",
            "(380000, 256681.59709535202, 123318.40290464798)\n",
            "(250000, 209092.47999940577, 40907.52000059423)\n",
            "(258000, 379441.33466968284, -121441.33466968284)\n",
            "(680000, 385908.45160680654, 294091.54839319346)\n",
            "(234000, 227810.53934033538, 6189.460659664619)\n",
            "(225000, 226424.72856809458, -1424.7285680945788)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(75000, 156672.25303197434, -81672.25303197434)\n",
            "(205878, 222382.78048239223, -16504.780482392234)\n",
            "(236000, 332323.7684134956, -96323.76841349562)\n",
            "(668365, 444920.8936580606, 223444.10634193942)\n",
            "(92000, 167643.25497888066, -75643.25497888066)\n",
            "(114800, 191317.52233799433, -76517.52233799433)\n",
            "(151087, 197784.63927511807, -46697.63927511807)\n",
            "(150000, 226540.21279911464, -76540.21279911464)\n",
            "(311328, 313384.35452620476, -2056.3545262047555)\n",
            "(511000, 209092.47999940577, 301907.5200005942)\n",
            "(150000, 217994.3797036297, -67994.3797036297)\n",
            "(230522, 144546.40877486736, 85975.59122513264)\n",
            "(164000, 203327.88236408125, -39327.88236408125)\n",
            "(68000, 153554.17879443255, -85554.17879443255)\n",
            "(297500, 209092.47999940577, 88407.52000059423)\n",
            "(122000, 203789.81928816153, -81789.81928816153)\n",
            "(275336, 226771.18126115476, 48564.818738845235)\n",
            "(188335, 210603.38891834544, -22268.388918345445)\n",
            "(200345, 189354.2904106532, 10990.709589346807)\n",
            "(300000, 209092.47999940577, 90907.52000059423)\n",
            "(193500, 231967.97165705776, -38467.97165705776)\n",
            "(255000, 232776.36127419822, 22223.63872580178)\n",
            "(192067, 205060.14582938224, -12993.145829382236)\n",
            "(229500, 210718.8731493655, 18781.126850634493)\n",
            "(286013, 224692.46510279356, 61320.53489720644)\n",
            "(165000, 236125.40397378016, -71125.40397378016)\n",
            "(220000, 221112.4539411715, -1112.453941171494)\n",
            "(200000, 189354.2904106532, 10645.709589346807)\n",
            "(167293, 200440.77658857958, -33147.77658857958)\n",
            "(207744, 282781.0333058871, -75037.03330588707)\n",
            "(395000, 385908.45160680654, 9091.548393193458)\n",
            "(116000, 186005.24771107128, -70005.24771107128)\n",
            "(207000, 261185.4821051346, -54185.48210513461)\n",
            "(275000, 294675.90910095396, -19675.909100953955)\n",
            "(170000, 191086.55387595418, -21086.55387595418)\n",
            "(288000, 257605.47094351254, 30394.52905648746)\n",
            "(277980, 351725.11922486685, -73745.11922486685)\n",
            "(182716, 197553.67081307792, -14837.670813077915)\n",
            "(412500, 209092.47999940577, 203407.52000059423)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(280000, 345258.0022877431, -65258.00228774309)\n",
            "(148750, 174918.76153314486, -26168.76153314486)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(328360, 278277.1482961045, 50082.85170389549)\n",
            "(109000, 180115.55192904786, -71115.55192904786)\n",
            "(146000, 193858.1754204358, -47858.175420435786)\n",
            "(247000, 250791.90131332862, -3791.9013133286207)\n",
            "(613401, 500468.80877871264, 112932.19122128736)\n",
            "(394470, 454506.0848327261, -60036.084832726105)\n",
            "(111000, 177228.44615354622, -66228.44615354622)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(228000, 242592.5209109039, -14592.520910903899)\n",
            "(156000, 184734.9211698505, -28734.92116985051)\n",
            "(190000, 182194.26808740906, 7805.731912590942)\n",
            "(174250, 196283.34427185718, -22033.344271857175)\n",
            "(266000, 255064.8178610711, 10935.18213892891)\n",
            "(94905, 165910.99151357968, -71005.99151357968)\n",
            "(368500, 209092.47999940577, 159407.52000059423)\n",
            "(170000, 209092.47999940577, -39092.47999940577)\n",
            "(265000, 250329.96438924837, 14670.035610751627)\n",
            "(115000, 153785.14725647267, -38785.14725647267)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(131750, 186351.70040413146, -54601.700404131465)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(204750, 243054.45783498418, -38304.457834984176)\n",
            "(225000, 225385.37048891396, -385.3704889139626)\n",
            "(245000, 203789.81928816153, 41210.180711838475)\n",
            "(159900, 343063.8018983618, -183163.80189836182)\n",
            "(274500, 209092.47999940577, 65407.52000059423)\n",
            "(178480, 194089.1438824759, -15609.14388247591)\n",
            "(141000, 177228.44615354622, -36228.44615354622)\n",
            "(127000, 147318.03031934897, -20318.030319348967)\n",
            "(133000, 177228.44615354622, -44228.44615354622)\n",
            "(360000, 209092.47999940577, 150907.52000059423)\n",
            "(250000, 209092.47999940577, 40907.52000059423)\n",
            "(120000, 150089.65186383054, -30089.651863830542)\n",
            "(250000, 246172.53207252597, 3827.467927474034)\n",
            "(201528, 214067.91584894745, -12539.91584894745)\n",
            "(170725, 246403.5005345661, -75678.50053456609)\n",
            "(315000, 288670.7290879105, 26329.2709120895)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(460000, 209092.47999940577, 250907.52000059423)\n",
            "(142000, 196514.31273389733, -54514.31273389733)\n",
            "(200000, 220766.0012481113, -20766.001248111308)\n",
            "(450000, 294329.45640789374, 155670.54359210626)\n",
            "(102750, 186582.6688661716, -83832.66886617159)\n",
            "(438700, 209092.47999940577, 229607.52000059423)\n",
            "(475000, 209092.47999940577, 265907.5200005942)\n",
            "(180400, 255411.27055413128, -75011.27055413128)\n",
            "(378000, 193396.23849635554, 184603.76150364446)\n",
            "(303000, 356575.45692770963, -53575.45692770963)\n",
            "(425000, 453697.69521558564, -28697.69521558564)\n",
            "(423000, 209092.47999940577, 213907.52000059423)\n",
            "(129500, 183002.65770454955, -53502.65770454955)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(261000, 238204.12013214137, 22795.87986785863)\n",
            "(228750, 302759.8052723586, -74009.80527235859)\n",
            "(170000, 232776.36127419822, -62776.36127419822)\n",
            "(415000, 294213.9721768737, 120786.0278231263)\n",
            "(267750, 209092.47999940577, 58657.52000059423)\n",
            "(238000, 251022.86977536874, -13022.869775368745)\n",
            "(433500, 209092.47999940577, 224407.52000059423)\n",
            "(356000, 269500.34673857945, 86499.65326142055)\n",
            "(265000, 261416.45056717476, 3583.549432825239)\n",
            "(170000, 199516.90274041906, -29516.902740419056)\n",
            "(212500, 209092.47999940577, 3407.5200005942315)\n",
            "(614000, 209092.47999940577, 404907.5200005942)\n",
            "(294173, 255988.6917092316, 38184.308290768386)\n",
            "(160000, 215800.17931424844, -55800.17931424844)\n",
            "(140000, 220766.0012481113, -80766.00124811131)\n",
            "(223000, 245133.17399334535, -22133.17399334535)\n",
            "(89921, 186813.63732821174, -96892.63732821174)\n",
            "(331200, 344103.1599775424, -12903.159977542411)\n",
            "(178000, 195705.92311675687, -17705.923116756865)\n",
            "(255000, 231159.5820399173, 23840.417960082705)\n",
            "(185074, 223075.68586851264, -38001.685868512635)\n",
            "(145000, 187968.4796384124, -42968.47963841239)\n",
            "(489332, 454506.0848327261, 34825.915167273895)\n",
            "(350000, 209092.47999940577, 140907.52000059423)\n",
            "(295000, 402769.1493357363, -107769.14933573629)\n",
            "(305000, 271001.6417418403, 33998.358258159715)\n",
            "(192700, 210718.8731493655, -18018.873149365507)\n",
            "(122000, 181963.29962536893, -59963.299625368934)\n",
            "(436746, 209092.47999940577, 227653.52000059423)\n",
            "(180000, 173532.95076090406, 6467.049239095941)\n",
            "(105000, 178614.25692578702, -73614.25692578702)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(110000, 199170.45004735884, -89170.45004735884)\n",
            "(297000, 312806.9333711044, -15806.933371104416)\n",
            "(224000, 177343.93038456625, 46656.06961543375)\n",
            "(148750, 227233.11818523504, -78483.11818523504)\n",
            "(158000, 214067.91584894745, -56067.91584894745)\n",
            "(107666, 136000.57567938243, -28334.575679382426)\n",
            "(128687, 168336.16036500107, -39649.160365001066)\n",
            "(69000, 149050.29378464996, -80050.29378464996)\n",
            "(600000, 209092.47999940577, 390907.5200005942)\n",
            "(152000, 207831.76737386384, -55831.76737386384)\n",
            "(315000, 214298.88431098757, 100701.11568901243)\n",
            "(294000, 209092.47999940577, 84907.52000059423)\n",
            "(225000, 209092.47999940577, 15907.520000594232)\n",
            "(245000, 344911.54959468293, -99911.54959468293)\n",
            "(145000, 186582.6688661716, -41582.66886617159)\n",
            "(289000, 299295.2783417566, -10295.27834175661)\n",
            "(55422, 154016.1157185128, -98594.1157185128)\n",
            "(120000, 125145.05796349616, -5145.057963496161)\n",
            "(284686, 279201.022144265, 5484.977855734993)\n",
            "(346375, 358192.23616199056, -11817.236161990557)\n",
            "(400000, 209092.47999940577, 190907.52000059423)\n",
            "(241000, 270193.2521246998, -29193.252124699822)\n",
            "(242000, 209092.47999940577, 32907.52000059423)\n",
            "(183200, 242361.55244886377, -59161.552448863775)\n",
            "(227887, 243862.84745212464, -15975.847452124639)\n",
            "(179000, 252986.1017027099, -73986.10170270989)\n",
            "(145000, 140619.94492018508, 4380.05507981492)\n",
            "(125000, 159790.32726951613, -34790.32726951613)\n",
            "(406026, 371819.3754223584, 34206.6245776416)\n",
            "(195000, 239474.4466733621, -44474.44667336211)\n",
            "(150000, 208524.67275998424, -58524.67275998424)\n",
            "(167293, 205060.14582938224, -37767.145829382236)\n",
            "(229027, 214067.91584894745, 14959.08415105255)\n",
            "(210944, 170876.81344744255, 40067.186552557454)\n",
            "(425000, 209092.47999940577, 215907.52000059423)\n",
            "(68880, 149165.77801567002, -80285.77801567002)\n",
            "(240000, 266959.6936561379, -26959.69365613791)\n",
            "(197654, 231044.09780889723, -33390.09780889723)\n",
            "(220000, 238088.6359011213, -18088.635901121306)\n",
            "(441000, 379094.8819766226, 61905.11802337738)\n",
            "(237800, 298948.8256486964, -61148.825648696395)\n",
            "(452000, 547586.3750348998, -95586.3750348998)\n",
            "(212864, 240860.2574456029, -27996.25744560291)\n",
            "(298000, 286130.076005469, 11869.923994530982)\n",
            "(188700, 222151.8120203521, -33451.81202035211)\n",
            "(233641, 179422.64654292748, 54218.35345707252)\n",
            "(285000, 237280.24628398084, 47719.75371601916)\n",
            "(236073, 222036.32778933205, 14036.672210667952)\n",
            "(300500, 277815.2113720242, 22684.788627975795)\n",
            "(68212, 192010.42772411474, -123798.42772411474)\n",
            "(190000, 149165.77801567002, 40834.22198432998)\n",
            "(180000, 220073.0958619909, -40073.09586199091)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(174000, 211989.19969058625, -37989.19969058625)\n",
            "(220000, 176420.05653640575, 43579.943463594245)\n",
            "(250000, 225385.37048891396, 24614.629511086037)\n",
            "(228327, 197207.21812001773, 31119.78187998227)\n",
            "(391000, 245133.17399334535, 145866.82600665465)\n",
            "(70000, 173994.88768498434, -103994.88768498434)\n",
            "(284893, 212335.65238364643, 72557.34761635357)\n",
            "(150000, 232314.42435011797, -82314.42435011797)\n",
            "(399000, 290056.53986015124, 108943.46013984876)\n",
            "(520000, 209092.47999940577, 310907.5200005942)\n",
            "(30000, 209092.47999940577, -179092.47999940577)\n",
            "(307000, 209092.47999940577, 97907.52000059423)\n",
            "(158000, 213259.526231807, -55259.52623180699)\n",
            "(224252, 168105.19190296094, 56146.80809703906)\n",
            "(91000, 163254.85420011813, -72254.85420011813)\n",
            "(170000, 194435.59657553612, -24435.596575536125)\n",
            "(78400, 143391.56646466668, -64991.566464666685)\n",
            "(208000, 281279.7383026262, -73279.73830262618)\n",
            "(270000, 234046.68781541896, 35953.31218458104)\n",
            "(95000, 182194.26808740906, -87194.26808740906)\n",
            "(575000, 430138.91208749206, 144861.08791250794)\n",
            "(61000, 158404.51649727533, -97404.51649727533)\n",
            "(99000, 246980.92168966643, -147980.92168966643)\n",
            "(156142, 222151.8120203521, -66009.81202035211)\n",
            "(276000, 345258.0022877431, -69258.00228774309)\n",
            "(221000, 258067.40786759282, -37067.40786759282)\n",
            "(350000, 308072.07989928167, 41927.92010071833)\n",
            "(266510, 235086.04589459958, 31423.954105400422)\n",
            "(150000, 145008.3456989476, 4991.654301052389)\n",
            "(113000, 174341.34037804452, -61341.34037804452)\n",
            "(660000, 325741.1672453518, 334258.8327546482)\n",
            "(200000, 218109.86393464977, -18109.863934649766)\n",
            "(169000, 191086.55387595418, -22086.55387595418)\n",
            "(242000, 219611.15893791063, 22388.84106208937)\n",
            "(200000, 192934.30157227526, 7065.698427724739)\n",
            "(92000, 163947.75958623854, -71947.75958623854)\n",
            "(528000, 407965.9397316393, 120034.06026836071)\n",
            "(326951, 209092.47999940577, 117858.52000059423)\n",
            "(30000, 191894.94349309464, -161894.94349309464)\n",
            "(100309, 162215.49612093755, -61906.49612093755)\n",
            "(275086, 224230.5281787133, 50855.47182128669)\n",
            "(195000, 306917.237589081, -111917.23758908099)\n",
            "(240000, 412469.82474142185, -172469.82474142185)\n",
            "(545000, 212913.07353874677, 332086.9264612532)\n",
            "(180000, 246403.5005345661, -66403.50053456609)\n",
            "(256054, 298024.9518005359, -41970.9518005359)\n",
            "(760000, 481067.4579673414, 278932.5420326586)\n",
            "(140800, 207369.8304497836, -66569.83044978359)\n",
            "(195500, 250907.38554434868, -55407.38554434868)\n",
            "(170000, 271925.5155900008, -101925.51559000078)\n",
            "(190000, 275159.0740585627, -85159.07405856269)\n",
            "(313138, 218225.34816566986, 94912.65183433014)\n",
            "(122000, 186351.70040413146, -64351.700404131465)\n",
            "(123675, 194435.59657553612, -70760.59657553612)\n",
            "(400000, 253217.07016475, 146782.92983525)\n",
            "(164000, 191433.0065690144, -27433.006569014397)\n",
            "(306500, 209092.47999940577, 97407.52000059423)\n",
            "(200000, 267421.6305802182, -67421.63058021822)\n",
            "(168000, 227810.53934033538, -59810.53934033538)\n",
            "(172000, 239936.38359744236, -67936.38359744236)\n",
            "(198000, 181154.91000822847, 16845.08999177153)\n",
            "(423000, 281164.25407160615, 141835.74592839385)\n",
            "(299000, 232776.36127419822, 66223.63872580178)\n",
            "(336000, 312229.5122160041, 23770.487783995923)\n",
            "(221000, 241553.16283172328, -20553.162831723283)\n",
            "(166357, 248482.2166929273, -82125.2166929273)\n",
            "(328578, 248828.66938598748, 79749.33061401252)\n",
            "(264469, 201942.07159184045, 62526.928408159554)\n",
            "(315000, 209092.47999940577, 105907.52000059423)\n",
            "(194818, 209092.47999940577, -14274.479999405768)\n",
            "(254172, 268576.4728904189, -14404.472890418896)\n",
            "(189000, 221227.93817219159, -32227.938172191585)\n",
            "(310000, 230697.64511583705, 79302.35488416295)\n",
            "(174250, 226193.76010605443, -51943.760106054426)\n",
            "(258000, 256335.14440229183, 1664.8555977081705)\n",
            "(335750, 371934.8596533785, -36184.85965337849)\n",
            "(247000, 209092.47999940577, 37907.52000059423)\n",
            "(160000, 229080.8658815561, -69080.86588155609)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(189000, 233815.71935337884, -44815.71935337884)\n",
            "(4897, 209092.47999940577, -204195.47999940577)\n",
            "(311000, 323893.4195490308, -12893.419549030776)\n",
            "(106852, 157827.09534217502, -50975.09534217502)\n",
            "(830000, 209092.47999940577, 620907.5200005942)\n",
            "(344250, 309573.37490254256, 34676.625097457436)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fcSkE1qWnirb",
        "colab_type": "code",
        "outputId": "17521997-87b6-4f11-d294-725e58eb8c14",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "regressor.score(x_test,y_test)"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.32739641886802984"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mcauqu7foypr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "xM = df[['sq__ft', 'beds', 'baths']]\n",
        "yM = df['price']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0gNSLgGfo_MM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "xM_train, xM_test, yM_train, yM_test = train_test_split(xM, yM, test_size = 1/3, random_state = 0)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fPD-iGj1qiSi",
        "colab_type": "code",
        "outputId": "7b5fa6d1-2b87-46b1-b35f-40d729367d67",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "regressor = LinearRegression()\n",
        "regressor.fit(xM_train, yM_train)"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xQ03BZjZt5Hu",
        "colab_type": "code",
        "outputId": "651e23a1-9d61-4055-987c-b7c489dc55dc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "yM_pred = regressor.predict(xM_test)\n",
        "print('Actual values' + '\\tPredicted Values' +'\\tError')\n",
        "errM = yM_test - yM_pred\n",
        "for i in zip(yM_test, yM_pred, errM):\n",
        "  print(i)"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Actual values\tPredicted Values\tError\n",
            "(211500, 135354.45636553367, 76145.54363446633)\n",
            "(395100, 430460.3625492493, -35360.362549249316)\n",
            "(129000, 204109.8992577062, -75109.89925770619)\n",
            "(124000, 210920.30936645318, -86920.30936645318)\n",
            "(176850, 237533.83110206499, -60683.831102064985)\n",
            "(480000, 280962.0789088955, 199037.9210911045)\n",
            "(220000, 135506.5336325943, 84493.4663674057)\n",
            "(610000, 453119.87534128444, 156880.12465871556)\n",
            "(362305, 255892.20869185374, 106412.79130814626)\n",
            "(325000, 359440.27883193083, -34440.27883193083)\n",
            "(130000, 210953.37627543494, -80953.37627543494)\n",
            "(215000, 180303.19359751928, 34696.806402480725)\n",
            "(339000, 246506.3898586427, 92493.61014135729)\n",
            "(270000, 329133.9309623152, -59133.93096231518)\n",
            "(300567, 238935.5934145925, 61631.4065854075)\n",
            "(108750, 190532.05076476076, -81782.05076476076)\n",
            "(145846, 236350.27987456165, -90504.27987456165)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(460000, 478321.72994880204, -18321.729948802036)\n",
            "(339000, 153722.7387708892, 185277.2612291108)\n",
            "(271742, 143609.6005113567, 128132.3994886433)\n",
            "(137721, 318488.5222680704, -180767.52226807037)\n",
            "(164000, 160837.30341375747, 3162.6965862425277)\n",
            "(257200, 323305.40972426534, -66105.40972426534)\n",
            "(134555, 206619.17416420672, -72064.17416420672)\n",
            "(220000, 148052.90816509703, 71947.09183490297)\n",
            "(115000, 196463.0641801257, -81463.06418012569)\n",
            "(261800, 225209.24235040756, 36590.757649592444)\n",
            "(306000, 225209.24235040756, 80790.75764959244)\n",
            "(225000, 228594.33925446906, -3594.339254469058)\n",
            "(218000, 281897.42135922296, -63897.421359222964)\n",
            "(371086, 225209.24235040756, 145876.75764959244)\n",
            "(276500, 244486.41366230583, 32013.58633769417)\n",
            "(334000, 336770.86122432887, -2770.8612243288662)\n",
            "(210000, 212805.04026939868, -2805.0402693986834)\n",
            "(221000, 214788.37486093267, 6211.625139067328)\n",
            "(178760, 225932.9870809079, -47172.987080907886)\n",
            "(97500, 136571.07450201878, -39071.074502018775)\n",
            "(116100, 158741.28858389027, -42641.28858389027)\n",
            "(471750, 476083.54266744095, -4333.542667440954)\n",
            "(361745, 269698.1730853901, 92046.82691460988)\n",
            "(185000, 142469.0210084019, 42530.978991598095)\n",
            "(181000, 240152.21155107763, -59152.211551077635)\n",
            "(282400, 523786.1888872818, -241386.1888872818)\n",
            "(330000, 212805.04026939868, 117194.95973060132)\n",
            "(115620, 226237.14161502916, -110617.14161502916)\n",
            "(120000, 376023.3143067374, -256023.3143067374)\n",
            "(156000, 198211.95275132303, -42211.95275132303)\n",
            "(236250, 167637.80870693768, 68612.19129306232)\n",
            "(85500, 202056.85615238754, -116556.85615238754)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(247480, 215102.43421062073, 32377.565789379267)\n",
            "(127059, 202132.89478591786, -75073.89478591786)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(61500, 143229.4073437051, -81729.4073437051)\n",
            "(180000, 229354.72558977225, -49354.72558977225)\n",
            "(65000, 145391.55599153583, -80391.55599153583)\n",
            "(380000, 200790.65292615697, 179209.34707384303)\n",
            "(250000, 207392.17216829883, 42607.82783170117)\n",
            "(258000, 393125.3934858624, -135125.3934858624)\n",
            "(680000, 496485.02799952717, 183514.97200047283)\n",
            "(234000, 231331.73006156055, 2668.269938439451)\n",
            "(225000, 230419.26645919672, -5419.266459196719)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(75000, 128739.09524839585, -53739.09524839585)\n",
            "(205878, 227757.91428563555, -21879.914285635547)\n",
            "(236000, 411652.3665234755, -175652.3665234755)\n",
            "(668365, 430037.19765704917, 238327.80234295083)\n",
            "(92000, 135962.76543377622, -43962.76543377622)\n",
            "(114800, 207303.5218659796, -92503.5218659796)\n",
            "(151087, 211561.6853436775, -60474.6853436775)\n",
            "(150000, 230495.30509272704, -80495.30509272704)\n",
            "(311328, 293878.45854803175, 17449.541451968253)\n",
            "(511000, 207392.17216829883, 303607.82783170114)\n",
            "(150000, 231070.54725198782, -81070.54725198782)\n",
            "(230522, 120755.03872771231, 109766.96127228769)\n",
            "(164000, 215211.53975313282, -51211.53975313282)\n",
            "(68000, 126686.05214307724, -58686.052143077235)\n",
            "(297500, 324310.7133863744, -26810.71338637441)\n",
            "(122000, 215515.6942872541, -93515.6942872541)\n",
            "(275336, 230647.38235978768, 44688.617640212324)\n",
            "(188335, 220001.97366554296, -31666.97366554296)\n",
            "(200345, 206010.86509596417, -5665.865095964167)\n",
            "(300000, 207392.17216829883, 92607.82783170117)\n",
            "(193500, 234069.12086865207, -40569.12086865207)\n",
            "(255000, 185050.65578538083, 69949.34421461917)\n",
            "(192067, 216352.1192560876, -24285.119256087608)\n",
            "(229500, 226280.1133395777, 3219.886660422286)\n",
            "(286013, 229278.68695624193, 56734.31304375807)\n",
            "(165000, 243008.612716248, -78008.612716248)\n",
            "(220000, 233123.59035730647, -13123.590357306472)\n",
            "(200000, 156460.1295779807, 43539.8704220193)\n",
            "(167293, 213310.57391487484, -46017.57391487484)\n",
            "(207744, 273728.2206624971, -65984.2206624971)\n",
            "(395000, 335428.6193645679, 59571.380635432084)\n",
            "(116000, 203805.7447235849, -87805.74472358491)\n",
            "(207000, 259508.99619232732, -52508.99619232732)\n",
            "(275000, 281560.1999161199, -6560.19991611992)\n",
            "(170000, 207151.44459891896, -37151.444598918955)\n",
            "(288000, 250949.697512383, 37050.30248761701)\n",
            "(277980, 368674.0203980813, -90694.02039808128)\n",
            "(182716, 211409.60807661686, -28693.60807661686)\n",
            "(412500, 274759.97786839097, 137740.02213160903)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(280000, 364415.8569203834, -84415.8569203834)\n",
            "(148750, 146955.3003866908, 1794.6996133092034)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(328360, 320313.44947279803, 8046.550527201965)\n",
            "(109000, 206129.87545404304, -97129.87545404304)\n",
            "(146000, 215178.47284415105, -69178.47284415105)\n",
            "(247000, 246463.41813409413, 536.5818659058714)\n",
            "(613401, 466611.7803851329, 146789.21961486712)\n",
            "(394470, 436348.4042400656, -41878.4042400656)\n",
            "(111000, 148476.07305729718, -37476.07305729718)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(228000, 247266.7761939459, -19266.7761939459)\n",
            "(156000, 202969.3197547514, -46969.3197547514)\n",
            "(190000, 151745.7342991009, 38254.265700899094)\n",
            "(174250, 210573.18310778335, -36323.18310778335)\n",
            "(266000, 199726.1120567325, 66273.8879432675)\n",
            "(94905, 184372.92144880487, -89467.92144880487)\n",
            "(368500, 207392.17216829883, 161107.82783170117)\n",
            "(170000, 212805.04026939868, -42805.04026939868)\n",
            "(265000, 246159.26359997285, 18840.73640002715)\n",
            "(115000, 176388.86492812133, -61388.86492812133)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(131750, 197831.75958367143, -66081.75958367143)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(204750, 247570.93072806718, -42820.93072806718)\n",
            "(225000, 180184.1832394404, 44815.816760559595)\n",
            "(245000, 159762.85772876622, 85237.14227123378)\n",
            "(159900, 424926.06048229965, -265026.06048229965)\n",
            "(274500, 207392.17216829883, 67107.82783170117)\n",
            "(178480, 209128.44907070725, -30648.449070707255)\n",
            "(141000, 191824.7075347762, -50824.707534776186)\n",
            "(127000, 122579.96593243998, 4420.034067560016)\n",
            "(133000, 191824.7075347762, -58824.707534776186)\n",
            "(360000, 207392.17216829883, 152607.82783170117)\n",
            "(250000, 207392.17216829883, 42607.82783170117)\n",
            "(120000, 124404.89313716766, -4404.893137167659)\n",
            "(250000, 243421.87279288136, 6578.1272071186395)\n",
            "(201528, 222283.13267145253, -20755.132671452535)\n",
            "(170725, 194023.21454195856, -23298.214541958558)\n",
            "(315000, 277606.1909725433, 37393.80902745668)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(460000, 219007.14130990312, 240992.85869009688)\n",
            "(142000, 210725.260374844, -68725.26037484399)\n",
            "(200000, 226693.37341621108, -26693.373416211078)\n",
            "(450000, 281332.084015529, 168667.91598447098)\n",
            "(102750, 210388.03893174094, -107638.03893174094)\n",
            "(438700, 280962.0789088955, 157737.9210911045)\n",
            "(475000, 219007.14130990312, 255992.85869009688)\n",
            "(180400, 249504.96347530693, -69104.96347530693)\n",
            "(378000, 208672.21726952534, 169327.78273047466)\n",
            "(303000, 378069.7440468591, -75069.7440468591)\n",
            "(425000, 442018.23484585783, -17018.234845857834)\n",
            "(423000, 225209.24235040756, 197790.75764959244)\n",
            "(129500, 201828.74025179658, -72328.74025179658)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(261000, 238175.2070792893, 22824.792920710694)\n",
            "(228750, 336433.6397812258, -107683.63978122582)\n",
            "(170000, 234601.3913033643, -64601.391303364304)\n",
            "(415000, 324604.6798594777, 90395.32014052232)\n",
            "(267750, 225209.24235040756, 42540.757649592444)\n",
            "(238000, 246615.49540115477, -8615.495401154767)\n",
            "(433500, 207392.17216829883, 226107.82783170117)\n",
            "(356000, 258781.6767660059, 97218.3232339941)\n",
            "(265000, 309211.80897737143, -44211.80897737143)\n",
            "(170000, 212702.2648466323, -42702.264846632286)\n",
            "(212500, 219007.14130990312, -6507.14130990312)\n",
            "(614000, 225209.24235040756, 388790.7576495925)\n",
            "(294173, 256087.25768346293, 38085.74231653707)\n",
            "(160000, 223423.71217440732, -63423.71217440732)\n",
            "(140000, 226693.37341621108, -86693.37341621108)\n",
            "(223000, 248939.62613161292, -25939.626131612924)\n",
            "(89921, 154787.27964031367, -64866.279640313674)\n",
            "(331200, 314104.73506709666, 17095.264932903345)\n",
            "(178000, 210192.98994013175, -32192.989940131753)\n",
            "(255000, 233536.85043393984, 21463.149566060165)\n",
            "(185074, 234416.2471273219, -49342.2471273219)\n",
            "(145000, 198896.3004530959, -53896.3004530959)\n",
            "(489332, 436348.4042400656, 52983.5957599344)\n",
            "(350000, 212805.04026939868, 137194.95973060132)\n",
            "(295000, 408485.1974589869, -113485.19745898689)\n",
            "(305000, 315523.015560388, -10523.015560387983)\n",
            "(192700, 220078.01229907328, -27378.012299073278)\n",
            "(122000, 201144.3925500237, -79144.39255002371)\n",
            "(436746, 274759.97786839097, 161986.02213160903)\n",
            "(180000, 189391.47126180597, -9391.471261805971)\n",
            "(105000, 149388.536659661, -44388.53665966101)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(110000, 162923.4134280579, -52923.41342805789)\n",
            "(297000, 392599.7364163471, -95599.73641634709)\n",
            "(224000, 148552.1116908275, 75447.8883091725)\n",
            "(148750, 237153.6379344134, -88403.63793441339)\n",
            "(158000, 228485.23371195697, -70485.23371195697)\n",
            "(107666, 108926.07880596424, -1260.0788059642364)\n",
            "(128687, 142621.09827546254, -13934.098275462544)\n",
            "(69000, 123720.54543539479, -54720.545435394786)\n",
            "(600000, 274759.97786839097, 325240.02213160903)\n",
            "(152000, 211974.94542031086, -59974.94542031086)\n",
            "(315000, 222435.20993851317, 92564.79006148683)\n",
            "(294000, 219007.14130990312, 74992.85869009688)\n",
            "(225000, 207392.17216829883, 17607.82783170117)\n",
            "(245000, 364187.7410197924, -119187.74101979239)\n",
            "(145000, 204185.9378912365, -59185.93789123651)\n",
            "(289000, 334152.48077531625, -45152.480775316246)\n",
            "(55422, 126990.20667719851, -71568.20667719851)\n",
            "(120000, 107980.54829461864, 12019.451705381362)\n",
            "(284686, 314719.6575005362, -30033.65750053618)\n",
            "(346375, 379134.28491628356, -32759.284916283563)\n",
            "(400000, 219007.14130990312, 180992.85869009688)\n",
            "(241000, 265440.00960769225, -24440.00960769225)\n",
            "(242000, 207392.17216829883, 34607.82783170117)\n",
            "(183200, 247114.69892688526, -63914.69892688526)\n",
            "(227887, 248103.2011627794, -20216.201162779413)\n",
            "(179000, 254110.25321167463, -75110.25321167463)\n",
            "(145000, 118169.72518768146, 26830.274812318545)\n",
            "(125000, 136994.23939421892, -11994.239394218923)\n",
            "(406026, 381904.7426323568, 24121.25736764318)\n",
            "(195000, 245213.73308862725, -50213.733088627254)\n",
            "(150000, 224835.37930250165, -74835.37930250165)\n",
            "(167293, 222554.22029659204, -55261.220296592044)\n",
            "(229027, 222283.13267145253, 6743.867328547465)\n",
            "(210944, 131889.74613212072, 79054.25386787928)\n",
            "(425000, 207392.17216829883, 217607.82783170117)\n",
            "(68880, 123796.5840689251, -54916.584068925105)\n",
            "(240000, 263310.9278688433, -23310.92786884331)\n",
            "(197654, 233460.81180040952, -35806.811800409516)\n",
            "(220000, 244301.26948626342, -24301.269486263423)\n",
            "(441000, 392897.2775852714, 48102.7224147286)\n",
            "(237800, 278171.5283162374, -40371.52831623738)\n",
            "(452000, 503837.64390600764, -51837.64390600764)\n",
            "(212864, 246126.1966909911, -33262.19669099111)\n",
            "(298000, 275933.3410348763, 22066.6589651237)\n",
            "(188700, 227605.8370185749, -38905.83701857491)\n",
            "(233641, 149920.80709437325, 83720.19290562675)\n",
            "(285000, 243768.9990515512, 41231.00094844881)\n",
            "(236073, 227529.7983850446, 8543.201614955411)\n",
            "(300500, 270458.5594206933, 30041.440579306684)\n",
            "(68212, 158209.01814917804, -89997.01814917804)\n",
            "(190000, 123796.5840689251, 66203.4159310749)\n",
            "(180000, 226237.14161502916, -46237.14161502916)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(174000, 220914.4372679068, -46914.43726790679)\n",
            "(220000, 141741.70158208048, 78258.29841791952)\n",
            "(250000, 235937.01979792828, 14062.980202071718)\n",
            "(228327, 211181.4921760259, 17145.507823974098)\n",
            "(391000, 292288.26060909196, 98711.73939090804)\n",
            "(70000, 140144.89027794378, -70144.89027794378)\n",
            "(284893, 221142.55316849775, 63750.44683150225)\n",
            "(150000, 246701.43885025187, -96701.43885025187)\n",
            "(399000, 272316.55353440274, 126683.44646559726)\n",
            "(520000, 280962.0789088955, 239037.9210911045)\n",
            "(30000, 207392.17216829883, -177392.17216829883)\n",
            "(307000, 207392.17216829883, 99607.82783170117)\n",
            "(158000, 227952.96327724474, -69952.96327724474)\n",
            "(224252, 142469.0210084019, 81782.9789915981)\n",
            "(91000, 182624.03287760753, -91624.03287760753)\n",
            "(170000, 209356.5649712982, -39356.56497129821)\n",
            "(78400, 119994.65239240912, -41594.652392409116)\n",
            "(208000, 322290.45394458633, -114290.45394458633)\n",
            "(270000, 235437.81627219782, 34562.183727802185)\n",
            "(95000, 151745.7342991009, -56745.734299100906)\n",
            "(575000, 420304.2525651682, 154695.7474348318)\n",
            "(61000, 129879.67475135066, -68879.67475135066)\n",
            "(99000, 194403.40770961015, -95403.40770961015)\n",
            "(156142, 227605.8370185749, -71463.83701857491)\n",
            "(276000, 370617.9579608878, -94617.95796088781)\n",
            "(221000, 307006.6886049921, -86006.68860499212)\n",
            "(350000, 284178.58036513254, 65821.41963486746)\n",
            "(266510, 236122.1639739707, 30387.836026029312)\n",
            "(150000, 114857.09222132916, 35142.90777867084)\n",
            "(113000, 146575.1072190392, -33575.1072190392)\n",
            "(660000, 345363.226813255, 314636.773186745)\n",
            "(200000, 224944.48484501374, -24944.484845013736)\n",
            "(169000, 207151.44459891896, -38151.444598918955)\n",
            "(242000, 219730.88604040345, 22269.11395959655)\n",
            "(200000, 208368.06273540406, -8368.062735404063)\n",
            "(92000, 139731.6302013104, -47731.630201310414)\n",
            "(528000, 356154.09940936335, 171845.90059063665)\n",
            "(326951, 219007.14130990312, 107943.85869009688)\n",
            "(30000, 207683.7150336312, -177683.7150336312)\n",
            "(100309, 188141.7862163391, -87832.7862163391)\n",
            "(275086, 228974.53242212065, 46111.467577879346)\n",
            "(195000, 388721.76610630075, -193721.76610630075)\n",
            "(240000, 414872.4426755338, -174872.44267553382)\n",
            "(545000, 171972.01081816587, 373027.98918183416)\n",
            "(180000, 249776.05110044644, -69776.05110044644)\n",
            "(256054, 389068.8923649705, -133014.89236497052)\n",
            "(760000, 460039.39099254354, 299960.60900745646)\n",
            "(140800, 217872.89192669402, -77072.89192669402)\n",
            "(195500, 246539.45676762445, -51039.45676762445)\n",
            "(170000, 266580.589110647, -96580.58911064698)\n",
            "(190000, 268709.6708494959, -78709.67084949592)\n",
            "(313138, 225020.52347854406, 88117.47652145594)\n",
            "(122000, 204033.86062417587, -82033.86062417587)\n",
            "(123675, 203154.46393079378, -79479.46393079378)\n",
            "(400000, 248060.22943823086, 151939.77056176914)\n",
            "(164000, 201177.45945900548, -37177.45945900548)\n",
            "(306500, 207392.17216829883, 99107.82783170117)\n",
            "(200000, 257412.98136246015, -57412.98136246015)\n",
            "(168000, 231331.73006156055, -63331.73006156055)\n",
            "(172000, 239315.7865822441, -67315.7865822441)\n",
            "(198000, 151061.38659732803, 46938.61340267197)\n",
            "(423000, 322214.4153110561, 100785.58468894393)\n",
            "(299000, 228399.29026285987, 70600.70973714013)\n",
            "(336000, 342668.807730712, -6668.807730711997)\n",
            "(221000, 246582.42849217303, -25582.42849217303)\n",
            "(166357, 251144.74650399218, -84787.74650399218)\n",
            "(328578, 251372.86240458314, 77205.13759541686)\n",
            "(264469, 220501.17719127343, 43967.822808726574)\n",
            "(315000, 225209.24235040756, 89790.75764959244)\n",
            "(194818, 207392.17216829883, -12574.172168298828)\n",
            "(254172, 258173.36769776334, -4001.367697763344)\n",
            "(189000, 226997.52795033235, -37997.527950332355)\n",
            "(310000, 233232.69589981856, 76767.30410018144)\n",
            "(174250, 230267.18919213608, -56017.18919213608)\n",
            "(258000, 256315.37358405392, 1684.6264159460843)\n",
            "(335750, 375778.6802253828, -40028.68022538279)\n",
            "(247000, 207392.17216829883, 39607.82783170117)\n",
            "(160000, 232168.1550303941, -72168.15503039409)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(189000, 185735.0034871537, 3264.9965128462936)\n",
            "(4897, 207392.17216829883, -202495.17216829883)\n",
            "(311000, 300797.97419929085, 10202.025800709147)\n",
            "(106852, 123297.38054319464, -16445.38054319464)\n",
            "(830000, 386265.6509853668, 443734.3490146332)\n",
            "(344250, 285167.08260102675, 59082.91739897325)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZYloO8s7uLPy",
        "colab_type": "code",
        "outputId": "5f800845-32b5-444f-d569-a48f67073e6e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "regressor.score(xM_test,yM_test)"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.3532101742163726"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        }
      ]
    }
  ]
}