Exploratory_Data_Analysis.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Exploratory Data Analysis: The Superstore ! 🏪"
      ],
      "metadata": {
        "id": "gVCks02eqwhO"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![exploratory-data-analysis-900x615-1 (1) 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)"
      ],
      "metadata": {
        "id": "coXC-o34zOjR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from datetime import datetime\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "plt.style.use('fivethirtyeight')"
      ],
      "metadata": {
        "id": "6qr_ydu1zp1S"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%pip install kaggle"
      ],
      "metadata": {
        "id": "Jasl_d10rXMv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "outputId": "8e5c1cc4-0eab-4f1d-b12a-33e342137508"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: kaggle in /usr/local/lib/python3.10/dist-packages (1.6.17)\n",
            "Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.10/dist-packages (from kaggle) (1.16.0)\n",
            "Requirement already satisfied: certifi>=2023.7.22 in /usr/local/lib/python3.10/dist-packages (from kaggle) (2024.8.30)\n",
            "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.10/dist-packages (from kaggle) (2.8.2)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from kaggle) (2.32.3)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from kaggle) (4.66.5)\n",
            "Requirement already satisfied: python-slugify in /usr/local/lib/python3.10/dist-packages (from kaggle) (8.0.4)\n",
            "Requirement already satisfied: urllib3 in /usr/local/lib/python3.10/dist-packages (from kaggle) (2.2.3)\n",
            "Requirement already satisfied: bleach in /usr/local/lib/python3.10/dist-packages (from kaggle) (6.1.0)\n",
            "Requirement already satisfied: webencodings in /usr/local/lib/python3.10/dist-packages (from bleach->kaggle) (0.5.1)\n",
            "Requirement already satisfied: text-unidecode>=1.3 in /usr/local/lib/python3.10/dist-packages (from python-slugify->kaggle) (1.3)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->kaggle) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->kaggle) (3.10)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Collecting data :"
      ],
      "metadata": {
        "id": "A5hHl-DGq9U3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!kaggle datasets download -d vivek468/superstore-dataset-final -p /content/superstore_data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hcx_Rtjswvid",
        "outputId": "b6d83abd-558d-45f1-bf31-8f44ed25666c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset URL: https://www.kaggle.com/datasets/vivek468/superstore-dataset-final\n",
            "License(s): other\n",
            "Downloading superstore-dataset-final.zip to /content/superstore_data\n",
            "  0% 0.00/550k [00:00<?, ?B/s]\n",
            "100% 550k/550k [00:00<00:00, 76.2MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip /content/superstore_data/superstore-dataset-final.zip -d /content/superstore_data/"
      ],
      "metadata": {
        "id": "JtxvkOHvvRAC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2c287400-6850-4339-aa52-1b9a3c1a27fa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  /content/superstore_data/superstore-dataset-final.zip\n",
            "  inflating: /content/superstore_data/Sample - Superstore.csv  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%ls"
      ],
      "metadata": {
        "id": "6UOrbUQ8ZbrA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d8fb9e48-b120-4c7a-a74e-6b4ba667f9dd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[0m\u001b[01;34msample_data\u001b[0m/  \u001b[01;34msuperstore_data\u001b[0m/\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"superstore_data/Sample - Superstore.csv\", encoding='windows-1252')"
      ],
      "metadata": {
        "id": "qb1JLXBZp683"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head().style.set_properties(**{\"background-color\": \"#354a3d\",\"color\": \"white\",\"border-color\": \"black\",\"font-size\":\"9pt\",'width': 200})"
      ],
      "metadata": {
        "id": "vJqjpZa8rlMq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 275
        },
        "outputId": "9b33c035-aec7-417f-aa88-a59cd14aa9c3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x78f14037bbb0>"
            ],
            "text/html": [
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              "      <th id=\"T_dd70a_level0_col3\" class=\"col_heading level0 col3\" >Ship Date</th>\n",
              "      <th id=\"T_dd70a_level0_col4\" class=\"col_heading level0 col4\" >Ship Mode</th>\n",
              "      <th id=\"T_dd70a_level0_col5\" class=\"col_heading level0 col5\" >Customer ID</th>\n",
              "      <th id=\"T_dd70a_level0_col6\" class=\"col_heading level0 col6\" >Customer Name</th>\n",
              "      <th id=\"T_dd70a_level0_col7\" class=\"col_heading level0 col7\" >Segment</th>\n",
              "      <th id=\"T_dd70a_level0_col8\" class=\"col_heading level0 col8\" >Country</th>\n",
              "      <th id=\"T_dd70a_level0_col9\" class=\"col_heading level0 col9\" >City</th>\n",
              "      <th id=\"T_dd70a_level0_col10\" class=\"col_heading level0 col10\" >State</th>\n",
              "      <th id=\"T_dd70a_level0_col11\" class=\"col_heading level0 col11\" >Postal Code</th>\n",
              "      <th id=\"T_dd70a_level0_col12\" class=\"col_heading level0 col12\" >Region</th>\n",
              "      <th id=\"T_dd70a_level0_col13\" class=\"col_heading level0 col13\" >Product ID</th>\n",
              "      <th id=\"T_dd70a_level0_col14\" class=\"col_heading level0 col14\" >Category</th>\n",
              "      <th id=\"T_dd70a_level0_col15\" class=\"col_heading level0 col15\" >Sub-Category</th>\n",
              "      <th id=\"T_dd70a_level0_col16\" class=\"col_heading level0 col16\" >Product Name</th>\n",
              "      <th id=\"T_dd70a_level0_col17\" class=\"col_heading level0 col17\" >Sales</th>\n",
              "      <th id=\"T_dd70a_level0_col18\" class=\"col_heading level0 col18\" >Quantity</th>\n",
              "      <th id=\"T_dd70a_level0_col19\" class=\"col_heading level0 col19\" >Discount</th>\n",
              "      <th id=\"T_dd70a_level0_col20\" class=\"col_heading level0 col20\" >Profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_dd70a_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_dd70a_row0_col0\" class=\"data row0 col0\" >1</td>\n",
              "      <td id=\"T_dd70a_row0_col1\" class=\"data row0 col1\" >CA-2016-152156</td>\n",
              "      <td id=\"T_dd70a_row0_col2\" class=\"data row0 col2\" >11/8/2016</td>\n",
              "      <td id=\"T_dd70a_row0_col3\" class=\"data row0 col3\" >11/11/2016</td>\n",
              "      <td id=\"T_dd70a_row0_col4\" class=\"data row0 col4\" >Second Class</td>\n",
              "      <td id=\"T_dd70a_row0_col5\" class=\"data row0 col5\" >CG-12520</td>\n",
              "      <td id=\"T_dd70a_row0_col6\" class=\"data row0 col6\" >Claire Gute</td>\n",
              "      <td id=\"T_dd70a_row0_col7\" class=\"data row0 col7\" >Consumer</td>\n",
              "      <td id=\"T_dd70a_row0_col8\" class=\"data row0 col8\" >United States</td>\n",
              "      <td id=\"T_dd70a_row0_col9\" class=\"data row0 col9\" >Henderson</td>\n",
              "      <td id=\"T_dd70a_row0_col10\" class=\"data row0 col10\" >Kentucky</td>\n",
              "      <td id=\"T_dd70a_row0_col11\" class=\"data row0 col11\" >42420</td>\n",
              "      <td id=\"T_dd70a_row0_col12\" class=\"data row0 col12\" >South</td>\n",
              "      <td id=\"T_dd70a_row0_col13\" class=\"data row0 col13\" >FUR-BO-10001798</td>\n",
              "      <td id=\"T_dd70a_row0_col14\" class=\"data row0 col14\" >Furniture</td>\n",
              "      <td id=\"T_dd70a_row0_col15\" class=\"data row0 col15\" >Bookcases</td>\n",
              "      <td id=\"T_dd70a_row0_col16\" class=\"data row0 col16\" >Bush Somerset Collection Bookcase</td>\n",
              "      <td id=\"T_dd70a_row0_col17\" class=\"data row0 col17\" >261.960000</td>\n",
              "      <td id=\"T_dd70a_row0_col18\" class=\"data row0 col18\" >2</td>\n",
              "      <td id=\"T_dd70a_row0_col19\" class=\"data row0 col19\" >0.000000</td>\n",
              "      <td id=\"T_dd70a_row0_col20\" class=\"data row0 col20\" >41.913600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_dd70a_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_dd70a_row1_col0\" class=\"data row1 col0\" >2</td>\n",
              "      <td id=\"T_dd70a_row1_col1\" class=\"data row1 col1\" >CA-2016-152156</td>\n",
              "      <td id=\"T_dd70a_row1_col2\" class=\"data row1 col2\" >11/8/2016</td>\n",
              "      <td id=\"T_dd70a_row1_col3\" class=\"data row1 col3\" >11/11/2016</td>\n",
              "      <td id=\"T_dd70a_row1_col4\" class=\"data row1 col4\" >Second Class</td>\n",
              "      <td id=\"T_dd70a_row1_col5\" class=\"data row1 col5\" >CG-12520</td>\n",
              "      <td id=\"T_dd70a_row1_col6\" class=\"data row1 col6\" >Claire Gute</td>\n",
              "      <td id=\"T_dd70a_row1_col7\" class=\"data row1 col7\" >Consumer</td>\n",
              "      <td id=\"T_dd70a_row1_col8\" class=\"data row1 col8\" >United States</td>\n",
              "      <td id=\"T_dd70a_row1_col9\" class=\"data row1 col9\" >Henderson</td>\n",
              "      <td id=\"T_dd70a_row1_col10\" class=\"data row1 col10\" >Kentucky</td>\n",
              "      <td id=\"T_dd70a_row1_col11\" class=\"data row1 col11\" >42420</td>\n",
              "      <td id=\"T_dd70a_row1_col12\" class=\"data row1 col12\" >South</td>\n",
              "      <td id=\"T_dd70a_row1_col13\" class=\"data row1 col13\" >FUR-CH-10000454</td>\n",
              "      <td id=\"T_dd70a_row1_col14\" class=\"data row1 col14\" >Furniture</td>\n",
              "      <td id=\"T_dd70a_row1_col15\" class=\"data row1 col15\" >Chairs</td>\n",
              "      <td id=\"T_dd70a_row1_col16\" class=\"data row1 col16\" >Hon Deluxe Fabric Upholstered Stacking Chairs, Rounded Back</td>\n",
              "      <td id=\"T_dd70a_row1_col17\" class=\"data row1 col17\" >731.940000</td>\n",
              "      <td id=\"T_dd70a_row1_col18\" class=\"data row1 col18\" >3</td>\n",
              "      <td id=\"T_dd70a_row1_col19\" class=\"data row1 col19\" >0.000000</td>\n",
              "      <td id=\"T_dd70a_row1_col20\" class=\"data row1 col20\" >219.582000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_dd70a_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "      <td id=\"T_dd70a_row2_col0\" class=\"data row2 col0\" >3</td>\n",
              "      <td id=\"T_dd70a_row2_col1\" class=\"data row2 col1\" >CA-2016-138688</td>\n",
              "      <td id=\"T_dd70a_row2_col2\" class=\"data row2 col2\" >6/12/2016</td>\n",
              "      <td id=\"T_dd70a_row2_col3\" class=\"data row2 col3\" >6/16/2016</td>\n",
              "      <td id=\"T_dd70a_row2_col4\" class=\"data row2 col4\" >Second Class</td>\n",
              "      <td id=\"T_dd70a_row2_col5\" class=\"data row2 col5\" >DV-13045</td>\n",
              "      <td id=\"T_dd70a_row2_col6\" class=\"data row2 col6\" >Darrin Van Huff</td>\n",
              "      <td id=\"T_dd70a_row2_col7\" class=\"data row2 col7\" >Corporate</td>\n",
              "      <td id=\"T_dd70a_row2_col8\" class=\"data row2 col8\" >United States</td>\n",
              "      <td id=\"T_dd70a_row2_col9\" class=\"data row2 col9\" >Los Angeles</td>\n",
              "      <td id=\"T_dd70a_row2_col10\" class=\"data row2 col10\" >California</td>\n",
              "      <td id=\"T_dd70a_row2_col11\" class=\"data row2 col11\" >90036</td>\n",
              "      <td id=\"T_dd70a_row2_col12\" class=\"data row2 col12\" >West</td>\n",
              "      <td id=\"T_dd70a_row2_col13\" class=\"data row2 col13\" >OFF-LA-10000240</td>\n",
              "      <td id=\"T_dd70a_row2_col14\" class=\"data row2 col14\" >Office Supplies</td>\n",
              "      <td id=\"T_dd70a_row2_col15\" class=\"data row2 col15\" >Labels</td>\n",
              "      <td id=\"T_dd70a_row2_col16\" class=\"data row2 col16\" >Self-Adhesive Address Labels for Typewriters by Universal</td>\n",
              "      <td id=\"T_dd70a_row2_col17\" class=\"data row2 col17\" >14.620000</td>\n",
              "      <td id=\"T_dd70a_row2_col18\" class=\"data row2 col18\" >2</td>\n",
              "      <td id=\"T_dd70a_row2_col19\" class=\"data row2 col19\" >0.000000</td>\n",
              "      <td id=\"T_dd70a_row2_col20\" class=\"data row2 col20\" >6.871400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_dd70a_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_dd70a_row3_col0\" class=\"data row3 col0\" >4</td>\n",
              "      <td id=\"T_dd70a_row3_col1\" class=\"data row3 col1\" >US-2015-108966</td>\n",
              "      <td id=\"T_dd70a_row3_col2\" class=\"data row3 col2\" >10/11/2015</td>\n",
              "      <td id=\"T_dd70a_row3_col3\" class=\"data row3 col3\" >10/18/2015</td>\n",
              "      <td id=\"T_dd70a_row3_col4\" class=\"data row3 col4\" >Standard Class</td>\n",
              "      <td id=\"T_dd70a_row3_col5\" class=\"data row3 col5\" >SO-20335</td>\n",
              "      <td id=\"T_dd70a_row3_col6\" class=\"data row3 col6\" >Sean O'Donnell</td>\n",
              "      <td id=\"T_dd70a_row3_col7\" class=\"data row3 col7\" >Consumer</td>\n",
              "      <td id=\"T_dd70a_row3_col8\" class=\"data row3 col8\" >United States</td>\n",
              "      <td id=\"T_dd70a_row3_col9\" class=\"data row3 col9\" >Fort Lauderdale</td>\n",
              "      <td id=\"T_dd70a_row3_col10\" class=\"data row3 col10\" >Florida</td>\n",
              "      <td id=\"T_dd70a_row3_col11\" class=\"data row3 col11\" >33311</td>\n",
              "      <td id=\"T_dd70a_row3_col12\" class=\"data row3 col12\" >South</td>\n",
              "      <td id=\"T_dd70a_row3_col13\" class=\"data row3 col13\" >FUR-TA-10000577</td>\n",
              "      <td id=\"T_dd70a_row3_col14\" class=\"data row3 col14\" >Furniture</td>\n",
              "      <td id=\"T_dd70a_row3_col15\" class=\"data row3 col15\" >Tables</td>\n",
              "      <td id=\"T_dd70a_row3_col16\" class=\"data row3 col16\" >Bretford CR4500 Series Slim Rectangular Table</td>\n",
              "      <td id=\"T_dd70a_row3_col17\" class=\"data row3 col17\" >957.577500</td>\n",
              "      <td id=\"T_dd70a_row3_col18\" class=\"data row3 col18\" >5</td>\n",
              "      <td id=\"T_dd70a_row3_col19\" class=\"data row3 col19\" >0.450000</td>\n",
              "      <td id=\"T_dd70a_row3_col20\" class=\"data row3 col20\" >-383.031000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_dd70a_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "      <td id=\"T_dd70a_row4_col0\" class=\"data row4 col0\" >5</td>\n",
              "      <td id=\"T_dd70a_row4_col1\" class=\"data row4 col1\" >US-2015-108966</td>\n",
              "      <td id=\"T_dd70a_row4_col2\" class=\"data row4 col2\" >10/11/2015</td>\n",
              "      <td id=\"T_dd70a_row4_col3\" class=\"data row4 col3\" >10/18/2015</td>\n",
              "      <td id=\"T_dd70a_row4_col4\" class=\"data row4 col4\" >Standard Class</td>\n",
              "      <td id=\"T_dd70a_row4_col5\" class=\"data row4 col5\" >SO-20335</td>\n",
              "      <td id=\"T_dd70a_row4_col6\" class=\"data row4 col6\" >Sean O'Donnell</td>\n",
              "      <td id=\"T_dd70a_row4_col7\" class=\"data row4 col7\" >Consumer</td>\n",
              "      <td id=\"T_dd70a_row4_col8\" class=\"data row4 col8\" >United States</td>\n",
              "      <td id=\"T_dd70a_row4_col9\" class=\"data row4 col9\" >Fort Lauderdale</td>\n",
              "      <td id=\"T_dd70a_row4_col10\" class=\"data row4 col10\" >Florida</td>\n",
              "      <td id=\"T_dd70a_row4_col11\" class=\"data row4 col11\" >33311</td>\n",
              "      <td id=\"T_dd70a_row4_col12\" class=\"data row4 col12\" >South</td>\n",
              "      <td id=\"T_dd70a_row4_col13\" class=\"data row4 col13\" >OFF-ST-10000760</td>\n",
              "      <td id=\"T_dd70a_row4_col14\" class=\"data row4 col14\" >Office Supplies</td>\n",
              "      <td id=\"T_dd70a_row4_col15\" class=\"data row4 col15\" >Storage</td>\n",
              "      <td id=\"T_dd70a_row4_col16\" class=\"data row4 col16\" >Eldon Fold 'N Roll Cart System</td>\n",
              "      <td id=\"T_dd70a_row4_col17\" class=\"data row4 col17\" >22.368000</td>\n",
              "      <td id=\"T_dd70a_row4_col18\" class=\"data row4 col18\" >2</td>\n",
              "      <td id=\"T_dd70a_row4_col19\" class=\"data row4 col19\" >0.200000</td>\n",
              "      <td id=\"T_dd70a_row4_col20\" class=\"data row4 col20\" >2.516400</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "id": "D5gk75ZlDAS2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cc8ed374-7b9a-4e62-c50b-5a9cdca3cd1d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9994 entries, 0 to 9993\n",
            "Data columns (total 21 columns):\n",
            " #   Column         Non-Null Count  Dtype  \n",
            "---  ------         --------------  -----  \n",
            " 0   Row ID         9994 non-null   int64  \n",
            " 1   Order ID       9994 non-null   object \n",
            " 2   Order Date     9994 non-null   object \n",
            " 3   Ship Date      9994 non-null   object \n",
            " 4   Ship Mode      9994 non-null   object \n",
            " 5   Customer ID    9994 non-null   object \n",
            " 6   Customer Name  9994 non-null   object \n",
            " 7   Segment        9994 non-null   object \n",
            " 8   Country        9994 non-null   object \n",
            " 9   City           9994 non-null   object \n",
            " 10  State          9994 non-null   object \n",
            " 11  Postal Code    9994 non-null   int64  \n",
            " 12  Region         9994 non-null   object \n",
            " 13  Product ID     9994 non-null   object \n",
            " 14  Category       9994 non-null   object \n",
            " 15  Sub-Category   9994 non-null   object \n",
            " 16  Product Name   9994 non-null   object \n",
            " 17  Sales          9994 non-null   float64\n",
            " 18  Quantity       9994 non-null   int64  \n",
            " 19  Discount       9994 non-null   float64\n",
            " 20  Profit         9994 non-null   float64\n",
            "dtypes: float64(3), int64(3), object(15)\n",
            "memory usage: 1.6+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Visualization:"
      ],
      "metadata": {
        "id": "Fdm7lE1FCwau"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Categorical value Vs Numerical Value:** *Goal: Understand The Average Sales across different Regions.*"
      ],
      "metadata": {
        "id": "blwxRBJCDmC_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_bar=df[[\"Sales\",\"Region\"]]"
      ],
      "metadata": {
        "id": "zwRCRkRLy0C-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_bar=df_bar.groupby(\"Region\").mean().sort_values(by=\"Sales\",ascending=False)"
      ],
      "metadata": {
        "id": "0gvSgemH6Zo0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=[15,8])"
      ],
      "metadata": {
        "id": "ED3j1-3-7C4E",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "f05bdb10-9056-443f-9171-989489646502"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Figure size 1500x800 with 0 Axes>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x800 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.suptitle(\"Average Sales Across Different Regions\", size=20)"
      ],
      "metadata": {
        "id": "NjpHjGaG6-S0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "b9189208-9319-4e2c-fd29-8da950727e7f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0.98, 'Average Sales Across Different Regions')"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# BarChart\n",
        "plt.subplot(2,2,2)\n",
        "plt.bar(x=df_bar.index, height='Sales', color=['#380854','#612785','#874dab','#ab7bc9'], data=df_bar)"
      ],
      "metadata": {
        "id": "wLj4zT4w6fQG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 254
        },
        "outputId": "cd33717f-db99-4a66-8fc4-366a447e545f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<BarContainer object of 4 artists>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.subplot(2,2,2)\n",
        "plt.barh(y=df_bar.index, width='Sales', color=['#380854','#612785','#874dab','#ab7bc9'], data=df_bar)\n",
        "#plt.gca().invert_yaxis()\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "bPqrF0sg7nvz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "outputId": "35517494-44e3-44b8-d099-270a5db562d5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Check trend over period of time:** *Goal: Understand the trend for Average Profit and Sales across all these years.*"
      ],
      "metadata": {
        "id": "1KrGh6lKD1dG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_line = df[['Order Date','Sales','Profit']].sort_values('Order Date')\n",
        "df_line.head()"
      ],
      "metadata": {
        "id": "Q4YUpBUgCCvv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "d6f23c2c-b9d8-4515-8c08-1dcd16e80185"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Order Date    Sales   Profit\n",
              "8074   1/1/2017   13.748 -22.6842\n",
              "848    1/1/2017   48.896   8.5568\n",
              "8075   1/1/2017   15.224 -38.8212\n",
              "8073   1/1/2017    6.470  -9.7050\n",
              "8071   1/1/2017  310.744 -26.6352"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d5ffb5e5-097e-438a-bc7f-59c7b2daebe4\" class=\"colab-df-container\">\n",
              "    <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>Order Date</th>\n",
              "      <th>Sales</th>\n",
              "      <th>Profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>8074</th>\n",
              "      <td>1/1/2017</td>\n",
              "      <td>13.748</td>\n",
              "      <td>-22.6842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>848</th>\n",
              "      <td>1/1/2017</td>\n",
              "      <td>48.896</td>\n",
              "      <td>8.5568</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8075</th>\n",
              "      <td>1/1/2017</td>\n",
              "      <td>15.224</td>\n",
              "      <td>-38.8212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8073</th>\n",
              "      <td>1/1/2017</td>\n",
              "      <td>6.470</td>\n",
              "      <td>-9.7050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8071</th>\n",
              "      <td>1/1/2017</td>\n",
              "      <td>310.744</td>\n",
              "      <td>-26.6352</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d5ffb5e5-097e-438a-bc7f-59c7b2daebe4')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d5ffb5e5-097e-438a-bc7f-59c7b2daebe4 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-d5ffb5e5-097e-438a-bc7f-59c7b2daebe4');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-749715e6-9f96-4aac-b307-ffb039b7078a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-749715e6-9f96-4aac-b307-ffb039b7078a')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-749715e6-9f96-4aac-b307-ffb039b7078a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_line",
              "summary": "{\n  \"name\": \"df_line\",\n  \"rows\": 9994,\n  \"fields\": [\n    {\n      \"column\": \"Order Date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 1237,\n        \"samples\": [\n          \"4/1/2017\",\n          \"10/4/2015\",\n          \"6/21/2014\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sales\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 623.2451005086829,\n        \"min\": 0.444,\n        \"max\": 22638.48,\n        \"num_unique_values\": 5825,\n        \"samples\": [\n          33.45,\n          5.952,\n          254.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Profit\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 234.26010769095808,\n        \"min\": -6599.978,\n        \"max\": 8399.976,\n        \"num_unique_values\": 7287,\n        \"samples\": [\n          26.544,\n          19.41,\n          15.9936\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_line[\"Order Date\"]=pd.to_datetime(df_line['Order Date'])"
      ],
      "metadata": {
        "id": "LO4piftAE5B0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "type(df_line[\"Order Date\"][0])"
      ],
      "metadata": {
        "id": "qDYT0Rc-E-Ho",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fe390224-3d39-485e-e28c-5a648a02bf18"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas._libs.tslibs.timestamps.Timestamp"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_line = df_line.groupby('Order Date').mean()"
      ],
      "metadata": {
        "id": "XCVCofdIGQlS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=[8,4])\n",
        "plt.plot(df_line.index, 'Sales', data=df_line, color='#000ea8') # Avg Sales over Time\n",
        "plt.plot(df_line.index, 'Profit', data=df_line, color='#941818') # Avg Profit over Time\n",
        "plt.title(\"Average Sales and Profit over Time Period(2014-2018)\", size=10, pad=15)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "1oqSUswgGaeo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "outputId": "3b9a1eb5-78f9-4326-c725-25f9c19270a7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x400 with 1 Axes>"
            ],
            "image/png": 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gIKSY27x5MxQKhVYBlmEYuLi4ICsrC97e3hgyZAh69+6N9PR0nDhxAq6urujWrRsAaAZG7tixA4GBgVrHFovFWn8XLRCpu/ksWrQI1apVg5ubG0aPHm3STFESiQQBAQE4dOiQzmve3t563xsYGIjhw4dj+PDhmDNnDpo1a4Y//vgDs2fPxs8//4w1a9YgPDwcdevWhbu7O77++mvOtEkkEggEApw8eRICgUDrNXW3qdGjR6NLly44duwYoqKi8NNPP+Hbb7/F+PHjWY83cOBAdO3aFevWrUP58uWRnJyMgQMH6qSh8IBrdaFDHZxY4o8//kDt2rVRtmxZ1tYGRw2CNtagQYMwf/58XL9+HVKpFE+fPsXAgQMBvL1uV6xYoRMk8vnavYVt9TnZvjd936VEIsHXX3+tGedSmL5Ceo0aNbBt2zYIBAJUrFhR87t88uQJAPN+u7bg6+sLoKBFrXz58jqvz5w5E//++y8OHz6MoKAgzXY/Pz/IZDJkZmZqXafPnz+Hn5+f0ec/deoU/vnnH81YIIZhoFKp4Ovri+XLl2Pw4MFagbo6SLRX+tavXw8vLy8sXLhQs23dunWoV68eLl++rBXAvXr1ijUPCSmuKOAgpBhTKBTYvn07vv32W3Tp0kXrtffffx+7d+/Gxx9/jFatWiEoKAh79uzBf//9h/79+2v6DNeqVQsuLi5ITk42eV7+mJgYjBw5UlOAys3N1RSCgIKCkkKhwM2bN9G4cWMABS0qhWdKatSoEdLS0iAQCFC5cmUzcqGAj48P/P398fr1awDAhQsX0KtXL82c9iqVCg8ePECtWrVY39+wYUMolUqkp6ejbdu2nOcJDg7Gxx9/jI8//lgzYxBbwHH//n28fPkS8+fPR3BwMADg2rVrJn+uWrVq4cqVKxgxYoRmm7F9u4OCglC1alWj9vXy8kLFihURExOjdR3ExMSwdkHjoi7oGgqYatWqhZiYGK1tMTExqF69uibgCwoKQrt27bBz505IpVJ07txZU0j08/NDxYoVkZiYWGymgm7UqBHu37+v05pniEgkYn2PJb/dwoz57mvVqoUdO3ZouvoButdh1apV4eXlhdjYWFSvXl2znWEYzJo1C4cOHcKhQ4d0uiI2btwYIpEI0dHReO+99wAU/H6Sk5M1XcWMcfz4ca1Z6o4cOYIVK1bg33//RWBgINzc3Fjz0V7py8vL0wmG1dd64d/Lo0ePIJVKdVqpCCnOKOAgpBg7evQoMjMzMWrUKJ3WgH79+mHz5s34+OOPARQMwt2wYQMePHiAgwcPavbz9PTE1KlTMXv2bKhUKrRp0wZZWVmIiYmBp6enVl/4oqpVq4aDBw+iZ8+e4PF4WLx4sWawOlAwsLJTp06YNm0ali1bBqFQiLlz58LNzU1T+9upUye0bNkS77//PhYuXIjQ0FCkpqbi2LFj6NOnD2tXkA0bNuDWrVvo06cPqlatCqlUiu3btyM2NhZLly4FAISGhuLAgQOIiYmBj48Pfv31V6Snp3MGHNWrV8fQoUMxYcIEfPvtt2jYsCEyMjIQHR2NevXq4Z133sFXX32F7t27IzQ0FJmZmTh9+jTn8YKDgyEWi7Fu3Tp8/PHHuHv3LiIiIjjzksuECRMwadIkNG7cGK1bt8bff/+N2NhYi4IzLlOnTsWSJUtQtWpVNGjQAFu2bMGtW7ewfv16o48REhICHo+Ho0ePokePHnB1ddUar6I2efJkdOnSBUuXLsXAgQNx8eJFrF+/Xmew79ChQxEeHg6ZTIbvvvtO67Wvv/4aX375Jby8vNCtWzfk5+fj2rVryMzM1Bp47yxmzZqFYcOGITg4GO+99x74fD5u376Ne/fumTXNrSW/3aIMffeDBw/GokWL8Nlnn2HGjBl48uSJ1qxiQEHLUlhYGC5cuKCZkAIo6Ka0c+dObN26FR4eHkhLSwNQEOi4ubnB29sbo0aNwpw5c1C2bFl4eXlh1qxZaNmypVat/8OHD5Gbm4vnz59DKpVqZsmqXbs2xGKxzm/x2rVr4PF4mrEYXOyVvh49emDVqlX4/vvvMXjwYOTk5GDRokUICQnRCi7OnTuHKlWqGF1ZQEhxQAEHIcXY5s2b0alTJ9auR/369cOKFStw+/Zt1K9fH0OGDMEPP/yAkJAQtG7dWmvfOXPmwNfXFz/99BOmTZsGb29vNGrUSGtAKJvFixdjypQpeOedd+Dr64tp06YhJydHa581a9Zg6tSp6NWrF/z8/DB//nzExsZqakl5PB7+/vtvLFq0CJMnT8aLFy/g7++Ptm3b6nR5UGvatCnOnz+Pzz//HKmpqXB3d0ft2rWxZcsWTQ3tzJkzkZiYiEGDBsHNzQ1jxoxBr169NDPQsPn1118RERGBuXPn4tmzZ/D19UXz5s3xzjvvACjob//FF18gJSUFnp6e6Nq1K8LDw1mPVb58eaxatQoLFy7E2rVr0ahRIyxatEirpcIYAwcOxKNHjzB//nzk5+ejb9+++PjjjxEZGWnScYwxYcIEZGdnY+7cuZrgbNu2bQgNDTX6GIGBgfj666/xzTffYPLkyRg+fDhWr16ts1/jxo2xYcMGhIeHIyIiAv7+/pg9ezbef/99rf369euHmTNnQiAQoHfv3lqvjR49Gm5ubvj555/xv//9D2XKlEHdunX1TsXrSF27dsWOHTuwdOlSrFixAiKRCDVq1NBMCGAOc3+7RRn67j08PLB9+3Z8/vnn6NixI2rVqoUFCxbopH306NGYNm0aFi5cqKnNV48XKxyEAAW/N/X3/d1334HP52u6ZHbp0kVrrAtQEBQVnpmuY8eOAAqmm7UkALdX+sLCwvDbb79hxYoVmim8W7Rogd27d2uNLdu9ezfGjBlj9uchxBnxMjMzGcO7EUKIdTx9+hT16tXD/v37taaZJIQUfwzDoGvXrpg0aRIGDx7s6OQUO/fu3UO/fv1w+fJlg2PYCClOqIWDEGJT0dHRkEgkqFu3LtLS0jB//nxUqlRJ7zgJQkjxxOPxsHz5cty9e9fRSSmW0tLSsGbNGgo2SIlDLRyEEJuKjIzE3LlzkZiYCA8PD7Rs2RLh4eGoVKmSo5NGCCGEEDuggIMQQgghhBBiM3zDuxBCCCGEEEKIeSjgIIQQQgghhNgMBRyEEEIIIYQQm6GAgxBCCCGEEGIzFHAQQgghhBBCbIYCDkIIIYQQQojNUMBBCCGEEEIIsRkKOAghhBBCCCE2QwEHIYQQQgghxGYo4CCEEEIIIYTYDAUchBBCCCGEEJuhgIMQQgghhBBiMxRwEEIIIYQQQmyGAg5CCCGEEEKIzVDAQQghhBBCCLEZCjgIIYQQQgghNkMBByGEEEIIIcRmKOAghBBCCCGE2AwFHMWUVCrFw4cPIZVKHZ2UYofyzjKUf+ahfLMM5Z/5KO8sQ/lnPso7y5Sk/KOAoxhTKpWOTkKxRXlnGco/81C+WYbyz3yUd5ah/DMf5Z1lSkr+UcBBCCGEEEIIsRkKOAghhBBCCCE2QwEHIYQQQgghxGYo4CCEEEIIIYTYDAUchBBCCCGEEJuhgIMQQgghhBBiMxRwEEIIIYQQQmyGAg5CCCGEEEKIzVDAQQixidj4XLz/6VW07HIa/zfnDiSvFY5OEiGEEEIcQOjoBBBCSp7MLDn6Dr+I9BcyAED8AwlSUvOx7femDk4ZIYQQQuyNWjgIIVZ35NhzTbCh9s/x53j5SsbxDkIIIYSUVBRwEEKsbvnqh6zbr97IsnNKCCGEEOJoFHAQQqyO5+gEEEIIIcRpUMBBCLEbhnF0CgghhBBibxRwEEKsjsdjb+OggIMQQggpfSjgIIRYHUe8QQghhJBSiAIOQgghhBBCiM1QwEEIsTquFg6G+lQRQgghpQ4FHIQQ6+MMOOybDEIIIYQ4nlMEHMuXL4ePjw98fHxw6dIlndezs7Mxe/Zs1K9fH35+fmjQoAHmzZuH3Nxc1uOpVCqsXbsWbdu2RUBAAEJDQzF27FgkJiZypiEyMhK9evVCcHAwQkJC0KdPH0RHR1vrIxJCCCGEEFIqOTzguHv3LsLDw+Hu7s76ukQiQe/evbFq1SrUrFkTkyZNQo0aNbBy5Ur069cPUqlU5z3Tp0/Hl19+CYZhMH78eHTt2hUHDx5E586dkZCQoLP/jh07MGjQIMTHx2PEiBEYPnw4YmNj0b9/f+zfv9/qn5mQko5mqSKEEEKImtCRJ5fL5Zg4cSIaNGiAatWq4e+//9bZZ8WKFbh16xamT5+OBQsWaLYvWLAAy5cvx6pVqzBjxgzN9lOnTmHTpk1o27Yt9u3bB7FYDAAYMmQIhgwZgpkzZ2LPnj2a/TMzMzFr1iz4+voiOjoaQUFBAAqClo4dO2LGjBno0qULPD09bZQLhJQ83GM47JsOQgghhDieQ1s4fvjhB8TGxuKXX36BQCDQeZ1hGGzevBkeHh6YOXOm1mszZ86Eh4cHNm3apLVd/fecOXM0wQYAdO/eHe3bt0dUVBSSkpI02/ft24esrCyMGzdOE2wAQFBQED799FNkZGTg0KFDVvm8hBBCCCGElDYOCziuX7+OH3/8EV9++SVq167Nuk9CQgKePXuGVq1a6XS5cnd3R6tWrZCYmIjk5GTN9jNnzsDd3R2tW7fWOV7Xrl0BAGfPntXaHwC6dOli1P6EEMM4WzhATRyEEEJIaeOQLlX5+fmarlTTpk3j3E893qJatWqsr1erVg2RkZFISEhAcHAwJBIJUlNTUbduXdYWE/VxCo/jUP9/aGiozv7qbWzjPopiG0tiSzKZTOtfYjzKO8sYlX8cfadk+TK7/1acBV13lqH8Mx/lnWUo/8xHeWcZR+Sfq6urTY7rkIDju+++Q0JCAk6ePMkaGKhlZ2cDALy9vVlf9/Ly0tpP/a96u6H9Db1HPW6j8P5cUlJSoFQqDe5nbWlpaXY/Z0lBeWcZffnHdXN88SIDSUmlM+BQo+vOMpR/5qO8swzln/ko7yxjr/wTCASclfyWsnvAcfHiRaxcuRJfffUV6tata+/T20xgYKBdzyeTyZCWlgZ/f3+tsSrEMMo7yxiTf2JxGgDdoMPX1xchIRVsnELnRNedZSj/zEd5ZxnKP/NR3lmmJOWfXQMOhUKBiRMnol69evj8888N7q9udcjKymJ9vWjrBFsLhr79i76nXLlyWvvn5OTo7M/FVk1QhojFYoedu7ijvLOMvvzj89mHhwlFolKf53TdWYbyz3yUd5ah/DMf5Z1lSkL+2TXgyM3N1YyHqFCBvZaze/fuAIC//vpLM5j84cOHrPuqt6vHWri7uyMgIACPHz+GUqnU6a5VdH/1/1+7dg0JCQk6AYe+8R2EEG5cg8YJIYQQUvrYNeBwcXHBqFGjWF87d+4cEhIS8O6776J8+fKoVKkSQkNDUbFiRcTExEAikWjNVCWRSBATE4PKlSsjODhYs71du3bYvXs3Lly4gHbt2mmdIzIyEgDQtm1brf137dqFqKgotGjRgnX/oschhBBCCCGEGMeu0+K6ublh5cqVrP+1bNkSADBjxgysXLkSDRs2BI/Hw6hRo5Cbm4uIiAitY0VERCA3NxdjxozR2q7+e/HixVoDV48fP44zZ86gS5cuqFSpkmb7gAED4OXlhXXr1uHp06ea7U+fPsX69evh6+uLPn36WD0vCCnJaOE/QgghhKg5dKVxY0ybNg1HjhzB8uXLcfPmTTRq1Ag3btxAVFQUmjZtiokTJ2rt37FjR4wePRqbNm1CWFgYevTogdTUVOzduxdly5bF0qVLtfb38fFBREQExo8fj7CwMAwYMAAAsHfvXrx8+RIbNmygVcYJMRGPeyEOQgghhJQyDl1p3Bju7u44fPgwJk6ciPj4ePzyyy+Ij4/HlClTsH//fri5uem8Z/ny5ViyZAkAYM2aNTh+/Dj69OmDqKgoVK9eXWf/YcOGYdeuXahRowa2bt2Kbdu2oVatWti7dy/69+9v649ICCGEEEJIieU0LRyrV6/G6tWrWV/z9vZGeHg4wsPDjToWn8/HhAkTMGHCBKPP361bN3Tr1s3o/Qkh3KhLFSGEEELUnL6FgxBS/HAHHBRxEEIIIaUNBRyEEEIIIYQQm6GAgxBiddSlihBCCCFqFHAQQqyOa5YqijcIIYSQ0ocCDkIIIYQQQojNUMBBCLEbGjROCCGElD4UcBBCrI5jCAeN4SCEEEJKIQo4CCFWxzVonBBCCCGlDwUchBC7oRYOQgghpPShgIMQYnWcs1RRwEEIIYSUOhRwEEKsj7pUEUIIIeQNCjgIIXZDs1QRQgghpQ8FHIQQq6NB44QQQghRo4CDEGJ1XAEHNXAQQgghpQ8FHIQQu6GAgxBCCCl9KOAghFgd1yxVhBBCCCl9KOAghFgdZ5cqUBMHIYQQUtpQwEEIIYQQQgixGQo4CCF2Q2M4CCGEkNKHAg5CiNVxjeCggIMQQggpfSjgIIRYHQ0aJ4QQQogaBRyEELuhFg5CCCGk9KGAgxBiddTAQQghhBA1CjgIIVbHGXBQEwchhBBS6lDAQQixG4o3CCGEkNKHAg5CiNVRlypCCCGEqFHAQQixOq5ZqqiFgxBCCCl9KOAghNgNQxEHIYQQUupQwEEIsTrqUkUIIYQQNQo4CCF2Qw0chBBCSOlDAQchxOq4Wjgo3iCEEEJKHwo4CCFWxzVoXKWikIMQQggpbSjgIITYDXWpIoQQQkofuwccUqkUs2fPxrvvvovatWvD398fNWvWxDvvvIO//voLcrlc5z3Z2dmYPXs26tevDz8/PzRo0ADz5s1Dbm4u6zlUKhXWrl2Ltm3bIiAgAKGhoRg7diwSExM50xUZGYlevXohODgYISEh6NOnD6Kjo631sQkpVWihcUIIIYSo2T3gkEgk+OOPP8Dj8dCjRw9MnjwZffr0QUpKCqZMmYJhw4ZBpVJp7d+7d2+sWrUKNWvWxKRJk1CjRg2sXLkS/fr1g1Qq1TnH9OnT8eWXX4JhGIwfPx5du3bFwYMH0blzZyQkJOjsv2PHDgwaNAjx8fEYMWIEhg8fjtjYWPTv3x/79++3aX4QUiJxRBzUpYoQQggpfYT2PmHZsmXx5MkTiMVire0KhQL9+/dHVFQUjh8/jnfeeQcAsGLFCty6dQvTp0/HggULNPsvWLAAy5cvx6pVqzBjxgzN9lOnTmHTpk1o27Yt9u3bpznPkCFDMGTIEMycORN79uzR7J+ZmYlZs2bB19cX0dHRCAoKAlAQtHTs2BEzZsxAly5d4OnpaassIaTUoBYOQgghpPSxewsHn8/XCTYAQCgUok+fPgCAhw8fAihYJGzz5s3w8PDAzJkztfafOXMmPDw8sGnTJq3t6r/nzJmjdZ7u3bujffv2iIqKQlJSkmb7vn37kJWVhXHjxmmCDQAICgrCp59+ioyMDBw6dMjCT01I6UKzVBFCCCFEzWkGjatUKkRGRgIA6tatCwBISEjAs2fP0KpVK7i7u2vt7+7ujlatWiExMRHJycma7WfOnIG7uztat26tc46uXbsCAM6ePau1PwB06dLFqP0JIeajLlWEEEJI6WP3LlVqMpkMP/74IxiGwatXrxAdHY34+Hi8//77CAsLAwDNeItq1aqxHqNatWqIjIxEQkICgoODIZFIkJqairp160IgELDuX/i4hf8/NDRUZ3/1NrZxH0WxjSWxJZlMpvUvMR7lnWWMyT+GUbFul8vldv+tOAu67ixD+Wc+yjvLUP6Zj/LOMo7IP1dXV5sc16EBx/fff6/5m8fjYerUqZg/f75mW3Z2NgDA29ub9RheXl5a+6n/VW83tL+h96jHbRTen0tKSgqUSqXB/awtLS3N7ucsKSjvLKMv//Ly8li3Z77KRFIS1xxWpQNdd5ah/DMf5Z1lKP/MR3lnGXvln0Ag4Kzkt5TDAg4PDw9kZmZCpVLh2bNnOHr0KBYuXIhLly7h77//5gwanFVgYKBdzyeTyZCWlgZ/f3/WMTGEG+WdZYzJvzJumQBe62z38vZBSEiIbRPopOi6swzln/ko7yxD+Wc+yjvLlKT8c1jAocbn8xEUFISxY8fC19cXH374IX788Ud88803mqAjKyuL9b1FWyfYWjD07V/0PeXKldPaPycnR2d/LrZqgjJELBY77NzFHeWdZfTln0Co26URAAR8YanPc7ruLEP5Zz7KO8tQ/pmP8s4yJSH/nGbQOAB07twZwNuB3OoxFOpZq4pSb1fv5+7ujoCAADx+/Ji1e1PR/Qv/P9s4DX3jOwghpmNoXlxCCCGk1HGqgCM1NRUAIBKJABQU9CtWrIiYmBhIJBKtfSUSCWJiYlC5cmUEBwdrtrdr1w4SiQQXLlzQOb56Fqy2bdtq7Q8AUVFRnPur9yGEGIfHMS8uhRuEEEJI6WP3gCM2NhavX+v27X79+jXmzJkDoGDNDKCg0DJq1Cjk5uYiIiJCa/+IiAjk5uZizJgxWtvVfy9evFhrVP/x48dx5swZdOnSBZUqVdJsHzBgALy8vLBu3To8ffpUs/3p06dYv349fH19NeuDEEKMw7UOh4p98ipCCCGElGB2H8Oxd+9erFq1Cq1bt0alSpXg6emJlJQU/Pfff3j58iXatGmDSZMmafafNm0ajhw5guXLl+PmzZto1KgRbty4gaioKDRt2hQTJ07UOn7Hjh0xevRobNq0CWFhYejRowdSU1Oxd+9elC1bFkuXLtXa38fHBxERERg/fjzCwsIwYMAATTpfvnyJDRs20CrjhFgJdakihBBCSh+7Bxw9e/ZEamoqLl68iIsXL0IikcDLywv16tXDoEGD8MEHH0AofJssd3d3HD58GEuWLMHBgwdx+vRp+Pv7Y8qUKfjyyy/h5uamc47ly5ejbt26+PPPP7FmzRq4u7ujT58+mDdvHqpWraqz/7Bhw+Dr64sff/wRW7duBY/HQ6NGjTBz5kx06tTJltlBSInENfEtxRuEEEJI6WP3gKNJkyZo0qSJSe/x9vZGeHg4wsPDjdqfz+djwoQJmDBhgtHn6NatG7p162ZSuggh7Li7VFHEQQghhJQ2TjVonBBSslELByGEEFL6UMBBCLE6mqWKEEIIIWoUcBBCrI6rSxW1cBBCCCGlDwUchBC7YWgMByGEEFLqUMBBCLE6auEghBBCiJrdZ6kihJR83AEHRRyEEG13YnNw6Uom6tXxRPMm3pxjwAghxRcFHIQQu6GVxgkhha3b+Biz/ndP8/eUcVXw7dzaDkwRIcQWqEsVIcTqOGepogYOQsgbUqkS/1scp7Xtl3WJSHzy2kEpIoTYCgUchBCr4+xSRRPjEkLeOHzsOaT5us2ea/547IDUEEJsibpUEbOkPc/HvsOpyMySo/c7/qhfx9PRSSLFAHWpIoSovciQsW5Peppn55QQQmyNAg5ismepUvQcFIPHSQUPhWW/PsSOP5qiU4fyDk4ZcXY0aJwQQggpfahLFTHZjj0pmmADAPLzVVix5pEDU0ScDU2LSwghhBA1CjiIyRYsidfZduJ0hgNSQpwVV2BBAQchhBBS+lDAQQixOq7AQkUrjRNCCCGlDgUchBC7oXCDEEIIKX0o4CCEWB3n4HCKOAghhJBShwIOQojVUZcqQoi5aKxX6ZOaJoVCQfOml2QUcBBC7IYKEoQQNa7Z7Ejp8SjxNdp0O4PaLU6iWqMobNmZ7OgkERuhgIMQYnU0SxUhhBBDPp5yHfficwEA2TkKTPniNh48lDg4VcQWKOAghFgddakihBCiz7NUKa7dzNbaxjDA2g2PHZQiYksUcBBC7IZaOAghhADAs7R81u0HjqTZOSXEHijgIIRYHdcsVRRvEEIIIaUPBRyEEKvjHsNBIQchhBBS2lDAQQixGxXNekgIIYSUOhRwEEKsjqsdg1o4CCGEkNKHAg5CiNXRtLiEEEIIUaOAgxBiN9SlihBCCCl9KOAghFgdd9cpauIghOhHLaGElDwUcBBCrI66VBFCCCFEjQIOQojdUMBBCFHj8RydAkKIvVDAQQixOq7AQqWiiIMQUoAqIAgpPSjgIIRYHedK41TAIIQQQkodCjgIIVZHYzgIIYQQomb3gCMlJQWrVq3CgAEDUL9+fVSoUAE1a9bEqFGjcPnyZdb3ZGdnY/bs2ahfvz78/PzQoEEDzJs3D7m5uaz7q1QqrF27Fm3btkVAQABCQ0MxduxYJCYmcqYrMjISvXr1QnBwMEJCQtCnTx9ER0db4yMTQt6gLlWEEEJI6WP3gGPdunWYPXs2EhMT0blzZ0yZMgWtW7fGkSNH0KNHD+zZs0drf4lEgt69e2PVqlWoWbMmJk2ahBo1amDlypXo168fpFKpzjmmT5+OL7/8EgzDYPz48ejatSsOHjyIzp07IyEhQWf/HTt2YNCgQYiPj8eIESMwfPhwxMbGon///ti/f7/N8oKQEourhcO+qSCEEEKIExDa+4RNmzbFoUOH0L59e63t586dw3vvvYcZM2agd+/ecHFxAQCsWLECt27dwvTp07FgwQLN/gsWLMDy5cuxatUqzJgxQ7P91KlT2LRpE9q2bYt9+/ZBLBYDAIYMGYIhQ4Zg5syZWkFNZmYmZs2aBV9fX0RHRyMoKAhAQdDSsWNHzJgxA126dIGnp6etsoSQEodzFQ6KOAghhJBSx+4tHP369dMJNgCgbdu26NChAzIzM3H37l0ABQNPN2/eDA8PD8ycOVNr/5kzZ8LDwwObNm3S2q7+e86cOZpgAwC6d++O9u3bIyoqCklJSZrt+/btQ1ZWFsaNG6cJNgAgKCgIn376KTIyMnDo0CHLPzghhLpUEUIIIaWQUw0aF4lEAACBQAAASEhIwLNnz9CqVSu4u7tr7evu7o5WrVohMTERycnJmu1nzpyBu7s7WrdurXP8rl27AgDOnj2rtT8AdOnSxaj9CTfu1aVJaUOzVBFCCCFEze5dqrgkJSXh5MmTCAgIQL169QBAM96iWrVqrO+pVq0aIiMjkZCQgODgYEgkEqSmpqJu3bqaoKXo/oWPW/j/Q0NDdfZXb2Mb91EU21gSW5LJZFr/OoO8PCn4fOdfyckZ8644MSb/FAoV63alUmn334qzoOvOMpR/5nPWvJPL5azbVSrnuk84a/4VB/ryLj8/n/U9DBin+v4dyRHXnqurq02O6xQBh1wux/jx45Gfn48FCxZogoXs7GwAgLe3N+v7vLy8tPZT/6vebmh/Q+9Rj9sovD+XlJQUKJVKg/tZW1pamt3PyeXJkyQIBM4fcKg5U94VR/ryTyrNY93++nWeVpfG0oiuO8tQ/pnP2fIuMzOLdXtennPeJ5wt/4oTtrxLS2MPKpRKpVN+/45kr2tPIBBwVvJbyuEBh0qlwqRJk3Du3DmMGTMGw4cPd3SSzBIYGGjX88lkMqSlpcHf319rrIp9sLf4BAcHQyh0ql56rBybd8WfMfnn6voSgG7Q4eLiipCQEBun0DnRdWcZyj/zOWvelS3LB/BCZ7ubm5tT3SecNf+KA3159+JVNoCnOu8RCARO9f07Ukm69hwacKhUKkyePBk7d+7E0KFD8dNPP2m9rm51yMpirwUp2jrB1oKhb/+i7ylXrpzW/jk5OTr7c7FVE5QhYrHYYecuysXFFSKR8wccas6Ud8WRvvzj8divAz6fX+rznK47y1D+mc/Z8k4kYi+C8PkCp0qnmrPlX3HClncuLuxdqnjgUT4XURKuPYeVDtUtG9u2bcPgwYOxevVq8PnayVGPoXj48CHrMdTb1fu5u7sjICAAjx8/Zu3eVHT/wv/PNk5D3/gOQojpaNA4IYQQUvo4JOBQBxvbt2/HwIEDsXbtWtZB3qGhoahYsSJiYmIgkUi0XpNIJIiJiUHlypURHBys2d6uXTtIJBJcuHBB53iRkZEACqbgLbw/AERFRXHur96H6EeFSaLGdS3QtLiEEGKe6LMZeGfABdRpcQLTv7oNqdT+40YJMZfdAw51N6rt27ejf//+WLduHWuwAQA8Hg+jRo1Cbm4uIiIitF6LiIhAbm4uxowZo7Vd/ffixYu1RvUfP34cZ86cQZcuXVCpUiXN9gEDBsDLywvr1q3D06dv+xI+ffoU69evh6+vL/r06WPx5y4NKOAgalzXAl0jhBBiuoeJEgz78ApirmTiWVo+Nm5NxvSv7zg6WYQYze5jOL7//nts27YNHh4eqF69uk4gAQC9e/dGw4YNAQDTpk3DkSNHsHz5cty8eRONGjXCjRs3EBUVhaZNm2LixIla7+3YsSNGjx6NTZs2ISwsDD169EBqair27t2LsmXLYunSpVr7+/j4ICIiAuPHj0dYWBgGDBgAANi7dy9evnyJDRs20CrjRrLGOhxyuQqnzmXg8ZM8hLX3RWhVd8NvIsUGBRzEnnJyFYg+mwG5TIXOHcrDx0fk6CQRYpbN25Mhzdeebnz77hSsXFq/WI2dJKWX3QOOJ0+eAAByc3Pxww8/sO5TqVIlTcDh7u6Ow4cPY8mSJTh48CBOnz4Nf39/TJkyBV9++SXc3Nx03r98+XLUrVsXf/75J9asWQN3d3f06dMH8+bNQ9WqVXX2HzZsGHx9ffHjjz9i69at4PF4aNSoEWbOnIlOnTpZ78OXcJaWJWUyFUZPuIaj/6UDAEQiHv5c3QS9evhZnjhiV9Slijha2vN89B1+EfEPCrrjBge64tCOlqhSuYyDU0aI6X5a9Yh1e65EgbI+xXP2IlosuHSxe8CxevVqrF692qT3eHt7Izw8HOHh4Ubtz+fzMWHCBEyYMMHoc3Tr1g3dunUzKV1Em6X3juizGZpgAwDkcgb/+y6WAo5iiHOlcTung5Re6zY+1gQbAJCcIsWKNY/wU3g9B6aKEOviofisfVUUxRulC7XDEauxtLZi3rdxOtsePHyN5+nsU+eR4oceMMRefvxFd3bDDVtoMTGiS6Vi8PfeFHwx9y42/PWkWA3G5piBvFig50Hp4vCF/0jJYenNI/Z+Lut2mVzFup04L65LgZrQCSHO5ssF97B+4xPN30eOP8ffG5uBxyu+rQfFAT0PSpdiHBsTZ0P3DqLGPYbDvukghBB9srLl+GOzdsvX8RMvcCeWvQLM2RTn525xTjsxHQUcxGpsdfNwVC3T6zwldeeyNnrAEEIMsGfN9/4jaVAqdc+3YjX7gsPOpji3EhTjpBMzUMBBrKY43/gKYxgGC8LjUKXBf6jZ7AR6D41BZqbc0ckqVjgHjZeQa4QQYjln6LKUn88+XiMnV2HnlJinON9Si3Paieko4CBWU1JuHgePpmH56keQyQo+0NkLr/D1wnsOTlXxwtmlqoRcI4QQ4gyKczdVqoAqXSjgINZTQu4d4T8+0Nm2bVeKA1JSfHGvNF5CLhJCCHECxfmeWnxTTsxBAQexGqaE3D7uxRePwYLFUTF+NhJCSiCubl3F5V5VXNLJpjinnZiOAg5iNXTzIBo0SxUhhNicqhj3Uy3OrTPEdBRwEKuhewdRo0HjhBBie8X5llqc005MRwEHcXpUSC056KskhDgTJ5goyyLF+ZZKz4PShVYaJ1Zjq5sH3ZSKH+5B4/ZNByHFWa5EgcP/PsfTlDx07VQBjep7OTpJxMkU5y5VxTpaIiajgINYja1aIqiQWvxwfWUq+jIJMUquRIEB71/CpatZAIDFPz7AH780wnu9AxycMuJMivMtlXovlC7UpYpYja3uHcW6BodooecLIcb5NzJdE2wAgFLJYMlPulN2ExspJveq4vx8pOdB6UIBB7Eam9086KZU7HAPGrdzQgixg7/+TkabbmdQv81JfPvDfasUAj//+o7OtnvxuXidx74ydnFENdyWK85ZWIyTTsxAXaqI1VCXKqLGOYajGNfGEcLmv5PpmPLFbc3fP/ycAHc3AT6fXM2i42bnKFi3l4ZCein4iNZTjPOqNFzL5C1q4SBWY7MuVXRTKjHoqyQlza/rE3W2RfycYLPzcS1UVxw5w2fhSkFxuVUV5+djMU46MQMFHMRqbNajykluSlQbYzyapYqUFidOZ+hss2W3p5J0HypJn8VRinMWFue0E9NRwEGsxnbT4jrHXemHlQ+hUNBS2cbg+sqKc20cKRmK8yBbAFCVoFsQ3Q4sV5yvZ/r+SxcKOIjV2CowcJYH7OIf7uOLuXcdnYxijR4wxNGUSvtehHlSJZ6n51vteCXpN+QMn8UJenVZxBny0FzOUplI7IMCDmI1pWHhvx17UpCf7yQRkBPjnqXKib5MUirZqwKDYRgs/vE+qjSIRM1mJ/Du4Bi8ypRZfNziXKNdFN0PLFecs7A4p52YjgIOYjUlvUsVAORJVbgXl+PoZDg9U8dw5EoUiIxOx53YHKf6vknJo7RTgf3fyHRErEjQVFCcv/gKs/53z+LjlqTfRwn6KA5TnANQ+v5LFwo4iNXYrEsV3ZRKDLba5Vt3s9GwbTQGjbqCdj3O4pOpN2isDLEZe3WpGv7xVZ1tO/c9s/i4JamQ5syfpbgEdsUjleyKSRYTK6GAg1hNaehSRYzD3cKh+8JXC+7h5Su55u/dB1Lxz3/ptkoaKeX01QjnShTYfeAZVv2WiPsJuXZMlfGcZUybNRT+JsSw3jiX0qQ4Px8ZJw+XGIbB6t8T8d6IS5j0f7dwl3o3WIQW/iPWUwq6VBHjcH1jbF/l2QuvdLb9b3Ec+vb0t26iCAF3wJGdo0D/kZdw9UYWAOCb7/nY+lsTdA2rYM/kGVScu9AUxTAM/Hmp+MhlE4L5KUhX+eIv2UgAzpXnbJ6n52PaV3dw/uIr1Knpge8X1kHDel52T0dxvh6c/dG++McH+KHQmjpH/3uOU/+0RXCgmwNTVXxRCwexGpst/FeCavRKu6LT4nIFk48ev7ZHckgppORYImP/kVRNsAEA+fkqLPnpgZ1SZTxnL6SZglExmOiyDsH8FABABX4GJrmshUCZZ7c0cC0+aCifR35yFf8cf47MLDnOX3qFfsMvISeXfXV4WyrO14Mzp51hGGzckqS17eUrOQ4dTXNQioo/CjiI1diqeZRaOIof7lmqtP+mYJLYG1eNMNuU15euZrHs6VjFuUa7KMGzWJTnv9Ta5sKTISj9vINSZJzEx69x+Zr2tZGZJceBf1LtnpbifD0487Ndmq/CiwzdWeW+WhDrgNSUDBRwEOfnvPckwoHzOaITcNCXS+yLa9A413TXznaNOldqLCNMjWfd7pd5w84pMc2la5ms2zdvS7ZvQoBifUE4cbxBbIACDmI1NutS5WQ3JWdLjzMydlpcauEg9mbqtLhyuXP94J0tALKEM3wScxb+y8tj75ensPOikkAxL7Q7cdpL0u/MWVDAQaymNKzDAdh/peKSpOhNvOiYDkJszdQgN+WZFI8SX1vtPmTpcUpUkF4Mf/6S1wp89uUd1tccEZwW53uoMye9RP3OnATNUkWsxlaBgbPdlCjgMMz4MRyUl8S+VCb+fpt0PAUAaNHUG39vbIayPmKLzs8w5tWqv31/yfnNcH0SnhNHIidOZ3C+Ri0cpnHma5meTdZHLRzEamw3S5Vz/fAd8VApdqhLFXFS5q40fulqFhaEs485MIWl9zOmBP1mnLi8yZm2r+ZzrxavkNv/y3G256MpnPr7L0G/M2dBAQexmtKy8B+1cJivaPN/cX5YkuLJkmvuTysMCrY0yC7OXWickamtTeksMxepUQuHaZw56eZWTBBudg84duzYgenTp6NTp07w8/ODj48PtmzZwrl/dnY2Zs+ejfr168PPzw8NGjTAvHnzkJvLvgqsSqXC2rVr0bZtWwQEBCA0NBRjx45FYmIi5zkiIyPRq1cvBAcHIyQkBH369EF0dLSlH7XUoYDDdM7cpGwJYweNUy0SsTeudTjsxeIWjhJ0yyiO9z99aVYoKOAwhTN//1QZZn12Dzi+/fZbbNy4EUlJSfD317+SsEQiQe/evbFq1SrUrFkTkyZNQo0aNbBy5Ur069cPUqlU5z3Tp0/Hl19+CYZhMH78eHTt2hUHDx5E586dkZCQoLP/jh07MGjQIMTHx2PEiBEYPnw4YmNj0b9/f+zfv99qn7s0sNXNw9l++NYIOO7F5eCdARcQWOs4eg+NwaPE4rvQ3WuWGVu4Aw4aNE4cy9E1l5ae3tnuhyWVOc8zRwQcxfl6cObbP3X3tT67BxwrV67EzZs3kZCQgI8//ljvvitWrMCtW7cwffp07NmzBwsWLMCePXswffp0XL16FatWrdLa/9SpU9i0aRPatm2L6OhofPPNN1i3bh22bNmCV69eYebMmVr7Z2ZmYtasWfD19UV0dDQiIiIQERGB6OholCtXDjNmzEBOTo7V86CkstW9w573JGNu3pY+VGQyFd4beQkxVzKRJ1Xh7IVX6P/+pWL34Ih7IEGHd88isNZxtOh8GpeuZhp8T9GbON3Uib05ukukpb/zkvSbceYCpznkCvt/OcU5C7m+f2eoiHJ0xURJZPeAo1OnTqhUqZLB/RiGwebNm+Hh4aETKMycORMeHh7YtGmT1nb133PmzIFY/HYmke7du6N9+/aIiopCUtLbper37duHrKwsjBs3DkFBQZrtQUFB+PTTT5GRkYFDhw6Z9TlLo5LQpcqYYMLSG9F/J1/gebp2P+DHSXm4eCXTouPak0rFYOTYm7h1pyAgv58gwaBRl5EnLWjtoFmqiLNy9DVn6f3MCcpiJYo1Azhq4TAN17Wc/oJ7nIy9FOd8dVZOO2g8ISEBz549Q6tWreDu7q71mru7O1q1aoXExEQkJ78dxHfmzBm4u7ujdevWOsfr2rUrAODs2bNa+wNAly5djNqf6FcSZqkyJphQWvhQOfRvGuv2k2e4p1t0NjduS/H0Wb7WtuwcBQ4cKfhsnAuNF8NB43fjchDxcwLW//kY6S/yDb+BODWuAibfTk9Di1s4SlDE4QwfxZpdgWkMh2n05f3jJMd2My5JLYnOwmnX4VCPt6hWrRrr69WqVUNkZCQSEhIQHBwMiUSC1NRU1K1bFwKBgHX/wsct/P+hoaE6+6u3sY37YMM2nsSWZDKZ1r/OIF+aD6lUZPXjyvJlVs1ffXknyVUYfH+e1LL0yOXs51CpFCYfl2EYxD14jXI+QvhVcDE7TaaQyWS4dZc9nf8cT8V7vcqB4ShUMQyj9Rnz8rgL8Pb+TbE5c/4VPhh3C9L8gqfPL+se4cC2JvD3Mz2vnfE3W5xYK//y8qSQSnW/P6GAB5kRwYCl12VenhQuYvNHrkvzTL/POuu1p1Kx50PR+4Qt5cvkrNtVKpUmDYXzT18BX65Q2b8sYOXno7Xpu/ZkHHkPAKt+e4hvvq5us3QZkveaO0/tmd+O+O26urra5LhOG3BkZ2cDALy9vVlf9/Ly0tpP/a96u6H9Db3H09NTZ399UlJSoHTA9Cdpaey15Y7wLDUVXh7WL/SmPX+OpCT2WcksOi5L3uXkGv4Onz9/gaQk82u6JRIJ6/acnGytLn+GpL9QYMqXKXiYWHDTfu9dT3z9eQUIBBasKmYkHp/9HLm5EiQlJUEmZ3+QKJUqrc+Y+pw7wDMlL2wl4ucUTbABAI+TpPjtzziMHl7W7GM602+2OLI0/56lPkdSku59nS8AwF3+0bD0ukxKeoqcbN1KMWM9S02Fp7t591lnu/byOApuSpXSbr//ly+zWLfn5Ul10pCWlmZgliqVTdKt75ypabZ5Plob27WXkcFdvkp8nKk3L/NlKtyNzUdQRRH8Kli/KPs0hftm4Ihnk71+uwKBgLOi31JOG3AUN4GBgXY9n0wmQ1paGvz9/bXGq9gHe6uPv78/goM9wDN7GV3245YvXwEhIeXMPKYufXn38pUcQKLe9/v4lENISIDZ5y/jlgtA9wHh4+2NkJAQo4+z6Ic7mmADAPb/k4N3uwejfx/9s79ZSiaTQcDPZH3NxdUNISEhEApTwFp64/G1PiPDywPwmPVYpuSFrcRc0b0mV65/iTkzG5p8LMf+Zos/0/OP437iWwEhIT4624WCRACGKxx0r0vjWsHVKgYGonw589Pv5+ePkBBPk87prNeei4sb63YBX2C337+3Nw/AC53trq6umjQUzj+lkvv7Vihsc98qmOjgIetrFSpY9/lobfquvbLlngFIZ32fu3sZzry8cTsHwz66gcysggqrKZ+GYM4X1Swoe7CkW/EawBPW1+z5bHLW3645nDbgULc6ZGWx1z4UbZ1ga8HQt3/R95Qrp/2DVc9OxdViUpStmqAMEYvFDjt3UYt/SMS9uFyUKSPAlHFVMHaU4ckBjCES2eYzsuWdUGj4hsXjCy1KD4+js/iyVY/xxWc1jW6hOPCP7o168bJHGD64subvY1HpWLvhMXJzFRg2MBAfW+k74e7vzoerqyv3jZ/R/q2IRdwdZZ3lumZjSdqc6TdbHFmafwKhiPX9xv7uLP3uxCIXuLqa3xJszP3wXlwONmxJQmaWHAP6VETnDgXPMWe79vgcNxIej2e3dAqF7N3T+Hy+VhoYhsGvv6Xo7VLFMLa5b8lk3PdJWz0frY39ecvdNZDPF3B+rhlzrmiCDQD4ZX0S+vUKRMtm5rc8FyUScbe+OyK/ne23aw6nHTSuHkPx8CF7VK/ert7P3d0dAQEBePz4MWvXpqL7F/5/tnEa+sZ3EHYnz2QgLT0fjx6/xv/NuYt/jj+3ynHtuTiQMVNmqgrtwzAMEh+/1szOZAyuQaP5+Sos/D7e6OOwSUp+20XhXMxLjBh7FZHRLxBzJRMz5tzFhr/Ya2wKMya/+RxdqtT5xzndYZHPXpIGwJLigWswqDGVDdY5v4UL/xkYzPrgoQTvDr6IdRuf4O+9zzBi7FXs2p9q0TlLMmOfLyfPSvD98kTbJoZD4clM+FDCE2+n6y8OE29wMef2n/Y8H3fu6S5XsOxX9rKiucyZPlupZHD9ZhZiLr+CwgFTJDs7pw44KlasiJiYGJ0+7xKJBDExMahcuTKCg4M129u1aweJRIILFy7oHC8yMhIA0LZtW639ASAqKopzf/U+xHSrf0+0ynHsOVuEMbNUKd7ciB4lvkaLzqfRuMMpVG0QiTV/JBp1Dn032V9/M+4Yxti8I1nnprn+T+6AQyZT4fOv7yC0cRRadTmNXftTOPdlmZcBwNvvytiVxmkmEGJvKo6ChFBgn8ehpTG2oSB91/5nyMzS7s64YQv3b9mRuD6KPddK4boHFU3bhi2ZNk8LF3V+hAlPIcLta4SXmYdZLj/Cm5dVzGepKvg3lJ+AXqJ/0EJwGSLoHxydlc0+tuLU2ZdWTZupcVxOrgJ9hl5Epz7n8c7AGHR89xzNaliE0wYcPB4Po0aNQm5uLiIiIrRei4iIQG5uLsaMGaO1Xf334sWLtUb0Hz9+HGfOnEGXLl201gAZMGAAvLy8sG7dOjx9+lSz/enTp1i/fj18fX3Rp08fW3y8UuHUOevcAJxuHY43N//xn9/Eg4cFU/dJ81X4akEsbt4xPMmAvkK2NadV3LZLt5BxN457cOGcb2OxYUsSXr6SI+6BBJ9+dpNzMT9DLRxcBYaiWx1dO2dKy1RpJJersPjH++jS9zw+nnwdd+OK/0KoXJUKdmvhsPE6HEt+eqCz7cp14yY/sT/2D5Px0n4z8hj7ddyLd1zhUalkUIn/BEPEe+DCK8ibSoIkfCDe6vB7qEUYBh2EZ/C560r0Ev2LMS5/YYLLegjA3Z3JXuUBU/N13cbHOH/plebvu3G5WLrCtPFdJZ3dx3Bs2rQJ58+fBwDcvXsXALB582bNmhht2rTB6NGjAQDTpk3DkSNHsHz5cty8eRONGjXCjRs3EBUVhaZNm2LixIlax+7YsSNGjx6NTZs2ISwsDD169EBqair27t2LsmXLYunSpVr7+/j4ICIiAuPHj0dYWBgGDBgAANi7dy9evnyJDRs2aGarIo5jzy5Vxq40/ipTxrpQ3y/rErFuhf4BxYbOoVIxnAV6W1q/Ubv1g2EKbqItmvro7MuVPE3AwfEZdbpUOaiF4+KVV5j8xW3cT5CgUX0vrP+5IWpW93BMYpzYzHl3sXFrwVpHV29kIfpsBs4fb2+3KZhtgeuaExgZcFj6+yz6G4i5/AqLIu4j8clrdAsrj+/m10EZN+5ZrIp1AbMIfbf21DQpAvxt32e9OOSnSsWgm1C3J0YdQRxU+QWBUEqqFJu3JyM1LR+93/FDt04V7J1MkzEqFXqJjmptqyW4j+r8BACOnTTE1Fa2RUvv62xb/+cTRCyqa60kFXt2b+E4f/48tm3bhm3btuHGjRsAgAsXLmi2qYMRoGBcxuHDhzFx4kTEx8fjl19+QXx8PKZMmYL9+/fDzU13hovly5djyZIlAIA1a9bg+PHj6NOnD6KiolC9uu6czsOGDcOuXbtQo0YNbN26Fdu2bUOtWrWwd+9e9O/f3zaZQExiz0KpsSuNF8xmpevAEcN9pQ0934xJg72CsJ37nrFu5xo0rn54c3Vb0elSpedzyOUq7NyXggXhcThy7DnnZ36WKkXc/Vyj8+R1nhKDRl3G/YSCrpo3bmdj8JgrZuWpQqEqFgUWc8hkKk2woZbxUo6jkeyzyhQXXAUJoZGDxi1euK/Q+58+k2LQqMs4c/4lkp9KsXFrMqbOvGXg/Rad3rnoycp9h7Xvpa8yZZgy8xZadjmNsVOuIzklz+ZpcBZKJdBUeJ31NZUsH8/T89FzUAzClz3Ahi1JGDz6CjbvSGbd35kwaYnw5Om2ur8nPmjysaw4QRUAw2OliOns3sKxevVqrF692uj9vb29ER4ejvDwcKP25/P5mDBhAiZMmGD0Obp164Zu3boZvT+xL3t2qTKmVsPSlcYNFWyNWu3cjn2c2XDN6KNOO9eSNKaM4Rg75QYO/KOee/wRpk+sigVf19K8LperMPmLW/h7b0FQ1Ki+F/b81Ry+BqYc3Xvomc56K0+S8nDlehaaN/HR+141pZLBV9/cw47dKRAKefh0TCV89Xl1q07L6GhcK/1++b+7GD08mPW14sDSLlWWFvgLF2R27k1BrkT7Wtx9IBUrI7i7+sXG56J1C+vNxuNI+u5iiiL3uOEfXUXMm1bl+AcSXLmehcsnO0AotKzetDhUGOi736sAHPgnDU+StAOwVesTMWqYk/9O5ezd1Lx5ju8CSBOaWJ/TjuEgRI2xYxWU0ojChDEBgT6G7mPGtHBYc6yHOThbON6UkxQcGVk02NL3sH8bbBT49bdE5BRaCX7b7hRNsAEUtFTMD4/Tl2wAwOF/2WdPu3wt0+B71Vasfoj1G58gO0eBl6/k+H55Arbvtu7A3EtXMzF49GW06nIa8xbH6p0a0xa4CtaO6O5nTZa2cFj6+y9ckGEbbwEAKc+4VzKe/vUd3Ljt+AKZVejJysKLkD9MlGiCDbXEJ3k4c97ycYLGTnDhSPquOUbF4Iu5d3W234s3vBigUsngyvVM7D+Sipev7L8KvTl5zPUea9f16Avybt/LwYVLryCXUzOIKZx2HQ5C1OzbpcrwySwt7BuqUTOqlcXKtXLW6qKlMtDCUfS7NKV2US5nUKNJFLy8hAgMcMX1W7qFrr92PMUvEQ30Hofr+xOJtKMofXkS8bPuYMAfViZgxOAgvec21uOk1xjw/iVN7XfcAwlychRYvqS+VY5vDK5rzB4r2VtK33fH1VXClDEclij8G+BcrsbA73HjliT8FF7PonQ4A32fsvB98AjHFOt//JWETh3KW5YGJwosuOht4eC62UL/eCO5XKXViuzpIcDuzc2tupaFIeZkvbWffVz0lTvav3MWABBatQwObG+JoIrFe30Me6EWDuL0zC0MS14rTH6vMcGNpd2ZDPUNNSrgsPLkSqZ+Jq58Uj8MjC2UmdpPVpqvwvN0GWuwYSyuWilRkQKnvmshT6r7YsIj9i5I5jj873OdrjYbtybbtUaN6/MXh15j+n72coWKtbXI+DEc5qaqQOF7ElcXPEO3rQ1bkiw6r7NjoF2wFHDNimeFwqcxXWckEu5Zk4qaMfuO1Vsj9d2fGT0PA673yWQq7NibotWKnJOrxOyFseYn0gwMuH9zXNcr12ey9n3JmGdYwqPX+DbCsrWzShMKOIjTM/U5mfQ0D937n0dwnf/QoE20SQsQGlfYZyyqFTP0VuPSYO0Hmmn7c92MDU2LW/S9jugnK+do4SjaF9ySwPJ1nhJ//Z2Mhd/HI/pshsnv53rwp2fYr9sD1+cvHi0c3K99+tlN+FU/hncHxSDp6dt+78Z2FSv4/TP45/hzzFlkegHNUYO+nXKwOVf3GGjfJ7i+G2M/U/qLfM41EdTXCg8qlOelg48i47uS89C572XjToSCVhdzrgt99BZ+9WRC0XEwALB81UNUbRiJKV/c1nnt8rUsu1ZqMGaMzOYaQ2nt8XPGxrJs088TdtSlijg9U+9JYyZcx9UbWQCA5BQpRk+4hmunOyI4UHdWs6KMXYeD6wFgzD3KUM0J20NCNw1GnMgEptYUcrdwFPyr7zMUbuZXH0eMfFTjJyKT8UIqEwDoqfmyFNcDq+igYXO7zshkKgz98Iqmf/myXx9iyYLa+HBkgNHH4PPZ81hfzSnDMLh6Iwt37uWgZbOyqF3Tsml+GY7Pb+8xHPn5KkRGv8DDxGzUrCZDiBGzZRpTm3/+0iu8/+k1nDrS9s17jEsPwzBY8tMDfL/cvDn2C19X3F2qzDq0gfNa/5iWYvRcSoUDXq4gl2s2PDWZTIXx029i76GCGa96v+OH9T830pp2WKViUIWfiHEuv8OLl4M8xgV/yUaCYToDAJb9koAnydxjathYezpUvRU4CuNbOKLPZGDBEv018kolA5HItPSZzYTrXCpV4sTpDBz4x/BMkNbg6IlZSiIKOIjTM6bwkJ+vwpXrmeDzeZpgQ00uZ/DXjqf46nPdaZGLMnalcUtuRtYYw2HMWBNTGFO4zsyUw8WVDx64B9cb08KhVAJC4dvzBvJSMNV1lWZ6xEuKZtgsGwkVuNcisIScI++Kdqkyt7vGuZiXOoNZI35OwKhh/kYfQyziQ5qvm059tY9zv43Dr+sTNX8vW1wXH4+qxLm/IVxBI9eEAbaQn6/CiLFXEHWqoJVIIADWLffCoPf0Rx3GFq5v3s5GwiMJQqu6Gx1gvs5T4ec1j4w7AVvaCp3GngGHvfq+m0Lf5yx8j+GKcQ21kP66PlETbAAFXRVXrn2EL6e/fRYwKhU+dfkDXryCRS3dePn4WPwnDiqaA4DO1NCOoO96ZvS1cBSpXPlp1UOD5zKmwstaOL++Ittf5ykx7KMrOG2lxYSNwVXhQsxHXaqI0zP08L19Lwf1Wp9EryEX0XNQDOs+f+81rtnTmClvFQrGqNmsuBgqDBk3aNyS8+seX985Ja8VGP7xFVRtFIkqDSKxYMkDzsKZyoiAo/AMVioVMES8W2su9hbCK6gvuGPwc5hLLudo4SgyaNzcGuGFLAtAZbyU613lvSixmP3WzBaEAMCjxNdawQZQEIDkc+xvDK7WFL6NBnGcv/gK3yyJw2+bniAzs2Cdm6hTLzTBBlAQrH63zHChyZQC+53YgoKmseWLk2desI7hMZYxLRy26GrojC0c+mq4lYUqBjin4TZwr1y5TjcwDF+mPTOY6OltnWlYBTwVqrw8o/fYhlhzul19waKhQeOFnTxjuHunPWdANPZMR48/t2uwARh/PwCAHXuoW5UxqIWDOD1DD9/Pv76NF1bq227UGhgqy1o4DJUljB1HwsXQSshKpe7r+h6Oi5bex9H/ChZ7y89XYc0fyWhYj31WDpWqoLuZ3prLQs9HpUqFGgLdrin9RIdwU6l/xXZzcdXgFS38mfsdP0tl737BFeiw4Qo48vLYCxdrNjzW2fY6T4l/o56j37vGd+UqjGusiy3GcOzYk4IJn9/UXDcbtiThyM6W+N93utMcJzzKQ/qLfFQor73auVSqxK27OSjrI0JwoPGzxqjPaXQLx2vL+jMaU/C3RaHPUPcjR9DXel34PsHnDDj0H59rgdbChC+fsG6vkGvZOAyFgoFYbJ3fit5B4yruTDDnOrJnVyLOVoQi2TZr/j3DB7PybcmUsSwz5+lOS0x0UcBBTOKImU70nVLyWoFLV7O4dzCRsQv/WfLwNrjwn4WLD+bLVHBz5e6OxNZHV9+De80fuoXZm3fYC9XGBGOF846rdi6Ab/xAf1MpOB4kRdNtzrW+5KcHeJbGNTjVhIBDxP70zMtjT/vDRAnr9hcvzA/EuR64vCKxkFSqRHaOAj7eIs5AyZAfViZo/c7v3MvB0f/SNavBFyUrErzdT8jF4NFX8PjN4mfvdvczOQ3GBhyWz1JXuIXDvLEJ5rB0ngmGYRAbn4u7cblo3sQblUPKWJ4oPQP0Clf+cHXjs0Y3MVs90ZQqBgqFCmcvvELik9cIa+eLKpXNyzO915yePDDnWrXrGk9GDtC0VoWisWYvvIdVv+k+97hk53DPYva/xXHYdyQVFXzFmDGlGnr3ML5rbUlDAQcxiSNmVtQ7xaXMuAQZ2wvE2EHjlvRzNfSMNGrQuJ6D5EsNBBwmdqkyhVJp+FiFP59KbuXR7ygoGOmbsaRoYVXzPp01Qkw/N9dCbqbiKri/5mjhsAWuFpnCU5RGn8nAlFm3kJQsRXlfMdavaIjOHU1bF0EqVbIGFtO/0p1FR61o8DY/PF4TbADQzExXlf8IbYQxEECJGEULxKtqch/TyO/b8oJ7oT84LlNb9KO3tEvV4h/u44eVBd3Z+Hxg1Y8NMHyQhevOcNzcedCuuOBxZJS59y2tewRHGl6+lGHE2KtmHR8ouK4/mXlbs9CoWMzDpjVN0LObOcGwntf01BaZcx3ZdwwHx7kY08sa1mjgyHgpQ2jjKCsc6a2f1xZ063uSlIfR46/j+L7WaNrI26rnKC5oDAcxiSMCDn01j8bWcBUtfzIMg8QneXierl0bbatB4ydPv8C8xbH4Y/MT5OipDQEs71KVb2AO+N37n+lsO3PBOv1jlSrGYB4WTru+GVbMZahgxTVovGi6HTlLSdFFCNWkUvsFHDKOFg51d7z8fBUmzriJpDcz+LzIkGHMpOsmjxvhul70jZMofB9iGAZHjum2iFXhJ2Kqyyq0FV5AK+ElTHZZgzp8lq4ZJnapmmPhWgWFu4hyFZJsUctsyfWc+OS1JtgACn5jM+fdtXy9CSNbOLiuEXNbgiSFusXpe6YZmlKdDyUq8p5BBN0a+KhTGZpgAwBkMgbzFut2ETSG/nU49OShWS0cdpwWV093MGu7n5CLlWsfYdP2ZLzKZG8xsfZ0xkUplQw2mrGGTklBLRzEJM7WpcqcOcNfZcox9rOnuHW34AE6bGAgfv2hPoRCvtGFfVOa8tdtfIxZ/zOiD6r6+MYMXLcg4Fi5LhGjR2jP8rPqt0Sj0maISskY7FetMKJLlSWUSkbvOAOu/C363Vtz0KepRBxdql6zBBzZOQocP/GCdX+2cSlXb2QhJ1eBVs194F6G+xHA9dsSvGk8238kFSmp2gF7drYC5y++5Fz9WaVisP7PJ4g69QJVK5fBZxOqwr2M6bORFf6uuLpbtBFegJj3tg+/gKdCe+E53JPV0dpPM4bDTl+39krj7N+zLWqZLWmZWcsyRignV4moUy/MqrFXM3ZFeK7frDp4YxgGz9Ly4VderLOeDpusbAU83Auufc4UGKgyr8JPxHiX9fDkSSBnBNgmG4aLypaa18dOuaHznvsJEqSmSRHgb9rK1PqeS7k57F04i77P2ODQrhUtei5KU+em0NeqfebCSwwZfVlTifHLOncc/rulzjiw7bttP/h70/Zk/Ly0vs3P44yohaMYe5wkw7SvYtFrSAx+/CXBLjcKZ+tSZc6DOXzZQ9y6+/YmvWNPCv7a8RSAcYV9pZ4WjqK3PJWKwQ8rTZuv36iB63o+t6EHC1v3lSvXrTMOpiBv9J9fu4XD+BV8jU6DgfzjGgxdNE+tvLaiSVw4B43rJmrC5zeNOqbktQLvjbyE7v0vYOAHl9G62xk8SuReHZ2rS5W6hYOr9veUntlk5iyKxZfz7+HfyHSs+eMxeg6KQWYW98BerjJE4e/qaQr7eKJ2wgs62xoJb3Gey14BpjHnkVt5pWpjz8slNp59hrWiLcQm03Nzl8tV2L77KTr2OofpX7PPWqdSAXH3c9Es7DTqtjyJ6k1OYOc+w4XGrOy315x5zzQGY8Ub4MkruJeKeEp8IN4GLxi+j0qLtNzFXH6FX39LxOnzGdyra+v57n5hmYlL875CvxNjW7HtOoZDT3O0Ncsay35J0GoxjX8gwXaaWcruqIWjmMp4KcP4GSnIeFlQ43ku5hVS0/I5FxvKkyqxZNkDXLj0CnVqeeDL6dVRMcC0WhbAQV2qWE6aK1Fg1v/uYevOp0Ydo3Dtx6btul2KFi6Nx4fvhxhd2Odqyi86bWnik9d4nm7agDeuG37hmntDg8YNuXojC7+uf4T0FzL0723eLEZsVCrDM8cUzjul3PoBh6EHJlfNfdHv3toFUFP60Is5ulQVnaUqO0fB2p2Izejx17XWB0lKluK7Zfex/udGrPtztnC8CTiSU/JYXw+syH5fkclU2Lxde02DJ0l5erut8Hjs95zC3/FTjlnBjKUu5Km/Hx5UEEIBOcQWHZeLdgsH+z4//mp46l9TWdKYaKOZkPV2qTpy/Dn+3KZ/DYwr17PQquvb6Wszs+SY8PktVK/qjiZ6+skX7tZqzjMthJeMsnzt4ILPY9BBdBaH5b30vrfw+ZaueIDvfnw77mvi2MoIn19H5z36Kpj4MG6l8W8MLPjH9p7CUlKluHg5E6HVyqB+HU/rrOxtxbma9SWn8NTaavO+jcPUcVULJcVxLdqlBbVwFFNRp15qgg217bufchYSPp58AyvWPELMlUxs3JqMPsMumtX/NuER+6wxtsT2QJg445bRwYYx1NMnGlO7U7AOB/d+W3a+fUiacz8t+nCJOvUCLbucRsVaxzB49GW8yJDpPf/S5Q8Mfrf9hl/E7gOpOHXuJWbMsd6UfsbMUqXVpcoGYzgMnp+re0bRFg4rtxhytawABYPBCz/wRFwtHEW6VCU+4W6hAN7+djbvSEZktG63q537dINvADjwTyo++5K9Vlk9S1VmFnuw+MXcu/hy/j2d/HvwSIJcie73/dUC0/tNF85LrhYOU6lUDNoLz+A7t/8hwu1rjBP/BldY59iFKZQqPEp8DaWS4SwkFV040ho+nJSM6LPGHffajSwsX/UQG/56onPNWRNPT2k/3cwZ1pRKBt98r79wrT0+yfTfeXk++3oWddnGCBWhrkDLypbrrFa/+vfHrIG8vrEq+gKOwr9BrgqCotjuj/8cf47G7aPx4aTr6NDzHGbOu6fTGpOdozC5y7WhMRz5+QUrxdtSZqYcS356gJGfmD9BADEOBRzF1Kz5ujfUnFwlHj3WLYCkPc/XqUVMePQa5y+9Mvm8XAUUU1y/lYVFS+Px4y8JSHpq+CbIMAX9xYd/fAVhvc7Bp9JRHPwnzeJ0sDF+HQ7u12fOvacZ3GtOJdDHk2/g+s2C2rOnz6QY/vEVxD+QQCZj8N/JF/h48nW9heH9R9Iwdqpu/+HC2Ap+1mDM+Babd6kyIeDR9z5jZy0yFlur1IsMGfqPvITgOsdRq/kJbHrTAiDkGINSNJA09vm+2oQxOqfPZ+DDidc5X9e3xova2g2P0f/9S1rbBEa8ryiugL3wwFZLAw51HgbK4jFcvAuevFwIeUo0FN7GEPEui47Npu+wS2jS8RRCG0cZtU4EF4ZhcPxEOuZ/F4fNO5INVjJk5agwatwtg5VG+w6lovuAC1iwJB6fz76LFp1OI+kpex5b3OJtoybzk2cyMGjUZc7XC3cX5EoCT08gIufoHCLiGf4+1QX6vQdTWe9VG/7SHVSs756qL52F7znGZnXR+xTDMG8mCHi7/bdNT3D9ZsFiiQ8eStDh3bOoVO8/1G15Ev+dLFiz6WzMS/QeGoOWXS7gh19esLe8G6iR27Q9yaaL6slkKvQbeQlLfnqgWWvKHuw5+YczoYCjFDhyjL1wvvr3RJOPtczEpv7eQ2Ow/3Cq5u+Tp1/gnYEx+PGXh1i09D4atInG8RPpemtGdu9/hjETruPof+m4cTubcz99jC34GzPryelzL7H4B93VpNVe5ynxb2TBzcvQYm9ueI02gvPoKTyKYF7Bgyb1eT76Dr+IBw8l2LrzqdaNHijoI//cQO2frQIyQwrmnjcQcBR6eKpsMFDCUMDB3aWq6N/WLQwVDXSep+ejepMonDyTAZWqoEb3s1m3cf1mFuegd2O6yxVW0CWJ0bvKedHf3p4DqXrLAeqAw9Bv6vS5l4h/8Pa81uyWo9Wl6pmFAcebf5tIo3VeayXkLrRaSt/YFWP8sPIhhoy5ghVrHmHqzNsY+uEVgzXMMjljsO/6j78maOVvcoqUcz2UQ/+mYfmqh7h2w/QxYAzD4EmS7VrM2Vr01AoHZ+bEPHJGxLpdBMMVKOrWlXSOyQ6SWQJofRVcels4Ct9rjbx1FL1P3b6Xw5qm1X88BsMwGPnJVdy6kwMAeJaWj5GfXMXVG1kY9MFlnL3wCk+SpdixNwtzFuo+MxmOWh3mzWjIed8aP6uXOfeX85de4aaZZQpL6FvxnWGYEtu9iwKOEobt5ll0XIE9nb3wCh9Ouo7I6IIC+Io1j3SmzRwy5grrisJq0We5f5zGMvZeZEyXquwchcHA58mblhuuqUWBgmBjmusveN9lB/qIj2Km609oKChoPs7JVWLf4VTW2WEA4KEDurYZQ6VnfIta4Tx2RAuHSgWIIEMX4QmMEv+F9sIz4ENp81mq5AoVzl96jR9WJuLg0TR0fe886357Dqaybgd0f8vGdGEwNE1t0YB2g4FpGwVvnhrG/KZ2FZqCmWv9E3NkZcuR8mbshqUtHOrrsa6cPbjg6SnQqbkiD80EV9BOcA7evEyL0mOsopNRnDyTYdTA4IgV3JNYyOUqTeHRGMdPvMCCJfHo3Pc8Nu/QHW+RJ1Xi5zWP0Lb7GdRrdRJbdiYjT6oEwzCY/tUdvHjBMejcVmNG3ih8X2bMOJmKo+gkguEgUl0JxbWYIdtvWt89TW8LR+HWZCMjq6LPQK6ubdduZuHR49eIf6D9LJLJGAwadVnnXrX/yHPdz6GnS9XjpDyrlF305d3SFYbXTfLjPUdH4Wk0FNxknf5YFwND3fTCl2mf90lyHtb8kYg23c7Av8YxVG0Yif+bc8esWTidGQ0aLwW4mtq5ZsKxNoYBNm9/iq5hFXDiNHvwsHJtop3Swn0jePlK/9gI004E3IvLwZd6psNtLLiJYP7b2kYBT4WeomO4qWwIAPg24j7K+rDXpDkrlcpwy0DhgIQxYwyHNy8TEsYdCrDnjeGZyxiMd/kNtQUF3RJb4TKq8h9j36EpuHI9CwF+Lvj4gxCrj+FY9P1D3H+o7vKYyLnfz2sfoVN7X9bXZEUfwAaSuPqPx3jPwKQAr/MUcHExfoC0eqYsY2aI27b7KT56PwQVA1ytOvPSoFFXAAAtmnrj9l3jC8gFGBQu0SoMtLKJIIcMLpyveyIH01xXIoBf0G1VwpTBSukkJDPBmn14UIGxcv0eWyCpL5gwhr61TwxZtDQe7w8J0rSAMQyDoR9ewelCs5ZN/r/b2LglCd9/Uxd/bktGLxH7NdRAwD5+yFoUhYLf2PgcBJr4fgHY71vGdKlSP4/5HFXy7JMkcFfM6B00XrhLlZHPtqK/B64KC7GYz9ly+ipTNx9ycpXIyVXAx/vtfZurhQMwfeZErhYOfYX216/1P3/q8e/gE5c/IOIV7BevrI7V+eM4JpRg0E0YiU7C0xDwlLigaIkD8j6sv/vCY+9u3slGv+GXtFo8ZTIFft+cBG8vEWZNq6Q3jcUJBRwlDFthj6sbhouL6fPfm2vfYfb+qvamr4tTaOMoq3Upvhefi4iVCcjO5n5QDBf/rbOtEj8ZhQtEXIX3+eHGzThib6YPGje+hcObl4XxLutRiZ8MOSPEP/J3cEzRXTcNRc6fn6/C+k2P8d+JFwgKdEUQ76km2FBrIbiMvZeScP6SBwBg574U/PKDdedKfxts6OfiwucszBf9LesbiA4UTP947qL+sVrhyx5g6UL22e3YxN7PRXJKns70nmySkqWo0/Kk0cc21aWrpnflEUIJRaFHn8JAy4sYMr0BRxvhBU2wAQDuvNf4yu0H/N/rJWgiuIGeomNw5+XihrIRtsuGcAbK1qBvSmJjFJ0FzRTP02W4F5+LerU9AQA3bmdrBRtql65m4d3BMQD01867QgopTJ9J0RjpGTI8T8+HXwWXgu6pJk5IxhlwGNHCoa/VG2APOJQy7uPqCziu3sxC21blOI/LZv3GJ2jXqpzWAp9sxCIePExcQ+dczCv06lFo3RaOfl4+fNN/11z0tawa6qLaV3xYE2wAQE3BA9QX3MU1ZWOdfZsLrqK/+JDm7+6iKOQwnohSdNbZVyh8Gx39su4RZ/fK5asflqiAg7pUlTAdep7DgvA4rZsEVwuHq4t9v/5pX9226/kKU0/hp+9mb83xi1t3PtUbbAAFLRpsCj9AjFkXxJkolYzBmm+tZn6l8QHHCPGONwEZIOIp0E98GNX5uk3iRQOOuYtjMXdRHE6eycCWv5+ii+ikznv4PAYNBW/XaHiWlo+9h7i7NtmSp4eQ83sv+ls2VHgBgMUR3OONAGDdxic4FmXagMlf1yfitQWFU0cSFulnb+h6FfP0d6PoJz7Muv3HMl/hA5dtKM/PgBsvH62FFzFAtN+0xNpZ6nPL1tUoHLCs//MJ537q55O+gEPdvdQWvpx/DzWbnYBPpaNmvV/AY7/2xUa0cMjlKhw+lsY5kxZbV06V3oCDOw/nLorD6t8TceCfVKMnCjnwTxo+L7TuCdc9xtVFYHI3yZGfXNW6bzB6Bpa4wbgKGrWMl2+7WRamr4Xjbiz32DYh5Fo9ENQGivay7t9FeFJnW3dRJOu+GS/lGPD+JVy9kYW/93JPxGPFWYOdAgUcxZS+BbGWr36EqbPeFp64+kG6uNr361cvrudIxaFPZOECkTO0CplC36KIhfdRM3bQOA8q1BfoTt/bTRSl9/ivMmXYWGRMgjuP/UEm5GkXRB11vb7IkHHOICeRKLUWLTOmm9I9jkXbCtt/xLTgavXvj1m7TRQHOgGHgaDemFprY4WJzhjeyQ7Y7oOR0ekI63XO4mNLXiuQkio1agYufQFHGZ5x07haypzhIgIjxvVwefwkD2MmXOd8nW0Ml1Kub3HMomnRztOvv4nF6PHc52OzZedTvMosCLS5WgHEYr7BLklsDv9baEITPWM4Wgkvcb7GpUuf8zrdps195nO1YhVdf0WtkkB37Jsnj/vee+J0Bnq9aekrLahLVQm173Aqln1XDx7uQu4uVXYaw+EMYu/nYtHSeEjMuEHaW+EbnbVnSrI1hjHcKhNzORP16njC20sExsguVVw3f7YgpHCN9fETL3S60XEdS8E4/+3w36h0VGkQiS4dy+P3XxoZ7FJlrC1/P8WvPzSwyrGcnZCn0CqTyRX6CyRiKwYczqJC6DFUKC/Gz9/Xx7vd/aBSMZj8f5a3QH85/55Jfe/1BRzmrI9hDj7H/UAfrnuIMTZtTzYY5DZsF413u/nh5p1syGQqePOyMJBjX3WLeFPBVfQSHYUXLwc3lQ2wQzbY7MUrFQoGP/36COM+qsTZzU4s5pnVyrl151M8fyFDapoUGfey0ZZjv8p87hYyLqnP81G1YRSunuqAcmXFyM9XaS0MaYqiFRO2YMygeFPXNnFmzv+EJWaRyRjci8tFi6Y+ugNN3zB1GrniVtte1I+/mL56b3leOnqJ/kV53gvEqWriH/k7UMG2Y1+0Ag4H5HlZ3kvkMWXM7j9t6Cb6zffx+G3TE/y5pjFURi5/bMrNX93KcuhoGuvqulyFBaWNv1drYZiCKT+rNGBvrif6Fb2WlAoGaXq6Eol5MquWfW0xgNwc6S9kGDX+Gu5d7IT0DJnF3akAMwb66slYG09UpaGvSxIXSwKO67cMT8P6JClPa4bCcrwMDHRj35cPBiG8JHwo3gw+r+CztBZehBICbJMNMzudP699hJ/XPuJ83cVFYFbAceJ0hmbymDaCXLTlGB6lPxjllpklR42mJ3DnQhgatz9l9kxXQo5uc/ZmaGr94oQCjmKKZ0S0oF48jGulWJmMQfyDXIhFfFSpXEbvsW7dzcbQMVdMT6iJgnnJ6CU6inL8l7irrIND8l5GFfDd8BqDxPtQnZ+ANKYC9sgGQAYxshgvswMEN7zGDNef4cUrmAWnmiAR3rwsbJWNMOt4xhLylJoCjj37cHoiBxNd1qGSIAlKho8oRSfsl/eFqY9+YxY1evpMinmL4/B+C+5AwhVSdBaeRBA/BelMeaPPf/+BBB16cncNKe4Bh618GxGPmZ9Vd3QybE5YpMVifng85ofH4xeOW6A1u1QBBdefwgkCDqCgJrtG0xMOO7/+gMNeLRyGb7KBvBQ0F16BAkJcVDTX+56PxBuxRTZC70QDphLqCXD4UKGN8IIm2FBrJzxvUcBhyKGjaTh01LL1nswJ9oyhVDKo3eKkRcewRwuHMT4YdwsLvvR2dDKsggKOYsqYIqB63u2c3IKblQgyBPJT8FzlhzyUwdoNjzW1KIPfq4ifl9ZHGbeCQld+vgpzF8fi38h0lPUWmb3gnim8eZmY5voL3HgFA7+C+Skog9fYLjd80/zEZQNqCQoGx5ZHBuq5hQMA8hkx/pYNRoyypcnpqS+4qwk21FoIrmAXBlr1YVKUwEE3uiHi3Zp+qAKeCt1FUUhQVcNtpWmzNRlbo3T+4iu8V1sGD47XJ7usRlUB+zok+nw8Rf8q687yIHE2P6x8iJt3csDnawe6DQU3UZd/Dy8YX5xXtIEE7o5LpBWY+v0bGjRu+vmVWjNVVeU/Qj/RIfjyXuKusjZ2yweY3RWmuHHmgEN9/mr8h5jislozILyT8BQuKppzHq+Z8DpkEGOLbKTV0qivRYUHFTqKzrK+xodSb4WbC6RoIrgBH14mbivrIpkJsTitptAdf1KYY2v2neU5cercKyz4Ph9/b6zi6KRYjAKOEkw9p3quRIGa/HiMc/kdrrx8qBgedsgH46yinWbfXfufoUObchgzsuCGM3PeXWzaXjAj0JMk+wzeayC4rQk21JoLr+Jv+WC9N01PZGuCjaJceDKMctmKB3mhyGDY1zbg0kv0j842EU8Bf95zJNnwxqyvNsuWmgqv62zrLow0PeAwYS7/P/96jMkcPbfMCTaMwTXDjOWBHoN2wnOoz7+Ll0xZ/KfoildMWQuPaV9FZ6vqJoxEf/FBzd8thVfwg3S6TQNu6+AurIiKjOFQUzE8nVpiwPpjOAoXZHx4mZjishoub4Ka9vzzcOVJsVE2Rus9ztINy9oMBRx+vOdoKbwEMWS4omyCx6oqVk+DoRaOTsJordmnyvDy0El0Wu972ggvWjng4L436ctDEeTI53h2ipGPaa6/aGb+e5f5Fxtlo1mnfDWkPO8FqvIfIY3xxxNVCIxtFbdVC4c1WNJtztpOnXsNiUQBV9vMEm03FHCUYOquLbnZMnzosgmuvII+unwegxHinbitrI8s5m1T3fpNTzBmZAjkchV27NWdDs7Whot36Wxz5eXDi5cND0jQVHgNMkaES8rmyCjUxSaEr7vCbVFthRdwUN7bpPRwzZJSdNCptZl7o+NDiXK8l8hgfM0onLB/oFABdx9eLlxd+NgY053B2rjy19JAr4/oCHqKjmv+biy4iW+lXyEP+rsrOiseVOgq0u5uE8h/hnqCe2YVSuxJXyGMq+ZSBT7rAGLjVhc2XuH7R2PBDU2wodZceA1bZCMghxiNBTfQV3QIPrws3FbWw1bZMOTbaG0KR9D3PQXwU9FdFKmZVa6j8AzW5I9DrKqWzr71BbfRXVgwpum8ohUuKFvB+EKv/ntQU6H+FlPu4+pvXTCFvvEE+tJfEHCwXy+NBTc0wQZQ0KrdS3TU5N92C8EljBJv1QTrJ+QdsVvONcRdm76022sMT1H+vFQ0ENxBed4LKx1Re6FRc6U+l8HXtDpTp0MBRzHmCilaCS/Cl5eBe8rauKeqo/X64NFXMGZEMJB0G14s07O1EZzHUUVPzd/qFXvTM2Sci/04Qi1+PIaJd2lqmcKY0/hJ+hleMOURyHum0yrCpongmskBBxd3lvnBxchHGd5rSBh3i7tDmBPQNBDcwmjxFrjxpMhhPLA+/2M8VFWDDy8TA0V70VR4A7HKmtgrew9PmSCd91uzn/qM2cavEszX26RunCkuq+AKKS4pmyFa0RGGbu5cAQdXy4cxeFChg1C7W4M3PxtNBddxVsk1D4v18aGEL+8lXpgVdGorx3vJOq3je6IDrIWSQF4KqvAfIweeuKWsB8cVGfQH7WKOAEIJAWvQaczaCqYoHPD0Fx1g3acs7xUEUOFj8UZNQa6Z8BpcePlYkz/OqulxJH013K2LTIsq5CnRSRSN2HztgKMq/xEmuPym+TtU8AjIBy4oWxuXBivcg9joa10wlb7rWd8UvfomPBgg1r32KvJTIYLM6GcYH0oMFu/VahnsLDqFs4q2SGUCjHi/85QzAKAmPx4TXNZb9TdfdKFRc1myKKezoICjmBIxMkwq1BzaRRSNXbIBOKkI09rvz23JaC1IBVsPiBqCBBwtUtl3JzbH4JR99tZTdFzrBuDJk2CoeDfK816gPN+ylXXNUYYn0fq7seAGRoq3owwvDy9VPvhLNhLxqppmH9+UFg535KKB4DY+cNmu2ebJy8WnLn/gR+k0LHBbrNleWxCPr90i8H3e/+l0CTOm20hBtw4eDBUk80zoUmXJfPZq6lXDqwiegAfo/AaK4mrJsKTPrgckrOt7DBXvwtk88wMOPpTwQC6yYXjQYGPBdXwg3gZXXj6yGU+sz/8Yj1RVLTg3+33Ah6c7E1EzwRWMEm/V1MTeVtbFmvxP4YigQwiF/oCDY0yGkiNAY2/hYNBacBE1BLoLTxqTvrdHYc8fHhi0EF7W6eJVX3AXH4o3YbNsJJQGHt9CyOECmVOMuWksuI76gjt4zZTBMXk35KJgNXJTx2mwTYPNtuBaa+FF4wMOGxV6awnicVPZ0CrH0ndvGumyg/M1fRVJXGtEuCDf6IAjlP+Q9b7XQXgWO+WDDL7fmGmRy/JeoYPwDBjwcEXRFClMoFFpM0dP0TGrVzAIoLBKwJGV4xxjSixBAUcxVYt3V6s5FAB6iI4jWtHBoprNrxbcw7QJ5hdSbKECX7dpU13INFdd/l00F16BjHHBGUVbJDPBRr+38A3WBVKMEm/RdIsox8/E++Jt+EY6FyrwUZ6XATFkeMYEGP296D5cGNTmx8GTl4PHqkp4zvgDACrxn2C8y2/w5ukO6Pfk5WKM+C/W43cQndGZaUuk5ybLhxKDRXvQQngZbrx83FbWxR/5Y4zux18GEnjycvGcqaCTB+bMga9PK+ElzoCDBxV8eFkox2dfVK+z8CTqCu4hm/HCf/IumgebDy8TtfhxUEKAq8omrN0kRByF2KKryfOhhAhyyCEy2N0iTHgK74kOQsyTI0kVjLX5nyCT8WHdN4j3FJ+4bNT87cXLwf+5rsCCvLl48ab7oRByVOInQcq4GvXQ5ux6ptMSxKCP6IjW9vqCu+gh/A/HFN0NnsdYhgJeT+RgjMtm1OA/4CzIA/pbONi0F56HhHHHLWV9CHkKCKBCF+FJhBnox8/FmIBDBDl6cKxS3Fx4FU9UIYhSdGZ9nQcV+oiOoIvwBEQ8JWKVNfG3bDByGA+HdO/rIjyBgeK3K6w3E17DN3lzIIMLeFYo7Ddh6fJUXfB2CnQXSBEmPI0g/lM8VlXGSUVHrd+erQKOcW8qfSwJ+tXM7WZrTsu1K0+KXMZTa5sPLxODRXtQSxCPTMYb22VDkaAKZX32AAXPJmMY6lJVjpeBOa7fa56v74j+K7iOGTe8YHzxt2wQXjAVjDpXM8FVNBVcRR7K4KS8g2aAvD8vFZX4SXiqCkJNMyoQRJDBn/ec83UhFLB8wmkgO5sCDuIg3ZQHddaJ9+LlvulOYfwUokWdPvcSg/pWNGrfIF4yBon3wY+XjmQmCNtkQ5HFUSDiVjDQtqHA8kWn9Hv7YG8iuI6PxH9qag+bC69gmXSaTiGMqzA8SLwPPrxMXFI0QwD/uU4fbF/+K9QX3EErwUU0EhZ8riRVEFZJxyMHXvBEtt5VdLUfLgw+FG9Cc+E1AICcEeIv2UhcUTZFT+Exzhs+wD3ouq0wRjfg0PNgelf0r9YsKPUFd7GszJf4Lm+W3oJrAC8V411+0wSMaaoKWJ0/TusBYe2HPdd4nir8RHzhulzve8vys1AWBbX3DQS38Z10Frx52Zjosk4TZL6jOo4I6QzI4AIfXiaaCa6CAQ+PVZUMpq0q/xE+EG+FPz8dmSpvbJaNRBxLf3QACOYlYYh4j9bn+kC8Fb/kT9LZt77gtlaXksIWuH2Ln6WTkMN4YpzL75rv4qKiOTbLRuoNgvVdE768DGQwvvDmZUEIOSrwM3T26Sc+jBOKMNTgP8AA8X5U5KchUVkJm2XvI+1N0MymOv8B/PlpSFUFIEEViiaCaxgq3gVPngS3lXXxj/wdNBVcfxOAh+C8ojVkcMEYl81GVUSMFO9Ac9VVxCtr4ISik6b2kSsALM/PwPsuOwBw1ySbwpguk0XvKUV1FZ3gDDgaCm7hHdF/mr9rC+LxP7fvkM+I8Y+8B/5TdDMpvXwo0VxwBWV4r3FPWRtperrK1BfcRi/RUZTlvUKCMhTbZEPRu8jkG968bLQVXsBJRZhZ7V8eyIUUrlBACHdI9O7LgwoTXNajhiABANAM11FPcBfPVRVQjv8SccpacOEco2N5S38bYQweyXQDjgq8dAwU74MPLwtZjBcuKFohRRWgqUwqSsgzr7Ap5slN/hidhdHYJR+odW8YLv5b07rkxpNiistqzMn7BpbmkaEWjr6iIzq/BU9eLjx5ufBDOha4LcZuWX+cUHTSe542gvNvfsMFmgiuI0I6Ax2EZ82qOBgo2gsxZHjFlEWY6BRrl3U1V14+lIzQiHWtGHQRnkQv0VGIIMcFZSvskb2nGYOTSQEHcQSZTAU/Xjrrax+KN+G+qjrOK1ppbl6m3tTjHnD/eNSEkGO8y++a2mIfZGG8y29YKv0CjQQ3EMp/iFzGA09UlZAHF2QxPpAwZTRNtcG8JHjxclBHEIvOolMmptAyYcJTWl0VXHn5aC2MwR75AM22TsKTcONx10t0FZ1EZ2E066w2QEHtVmEh/KfoLfoHL5ly6CU6qncQYOEuP9X4jzTBBlAww85HLpvwJC8EDYXmB2lV+Y/wf64rNH+flHfg3Pdd0THW7QPE+/Fr/kTW14rObgQA/vyCB4SMESGb8cTfssEoz9MtqFpOPUiPQSDvGVoLY9BFFG3SEdx4UrQQXEEV/mOtFq2K/DQsdFsID57+gk5RfCgxWvyXpmDuw8/Cxy5/Yl7efCgg1CnsdmZJb21BPOrw70EAFR6pqkACd/Cg4hwHoNZXdBgSuGu1FLYUXoY3LwsyRoyagvt4zvjhkbIKDsp7aWrB9bV69RcdQKggQe+DFgB+KjNL6+8qgieY5xYOFcPDAXlvnFJ0gBhySFAGDPjoKzqkVVguqr7grla3mpa4jCaCG1ifP9boVk8BT4U6gjjUEcShi+gkvs5bBIBnt2lYg/lP4cPLRIqKO1h3MVAn6s3LRiAvBR68XKSoApFbaHLpTkL2+6kLT4b+4kNoILiDW8p6OKNoDylcIYIM1fkJEECFOFUNePAkyGXcIYcIfKgw13UJ/PgFzxsFI8BG2WhcVzbSOX7RsRSNhTfRWHiTNS2DxXsLAg6O+6c+S8rMRQ7jjq2yEZAw3C02YcJT8OelaYINtVqC+5pZDesJYjnfX08Qi69cl5qcvsLaCi9gu2yI5vfNhxLV+Qn4zHWVZp8QaHcVy2Hckct44IyiLe4q6yKdqWB2C0djwQ08VFUz6T1hojPw4WXib/lgZDE+KMt7pdOVTcRToJHgJmeQ7sdPR1/RYZSBBHUEsQB4SGfK42/ZYKQXqnDS97mEUBo1YH+QeB9kjBjZ8EQX4Ukw4OGcog0uK5uhDCToIzqiM22wC0+Gma7LDAb2XEx5nnzjtghyRoDzitbYKR/EWclTmx+n1RLYTnge2YwnDst7ASgZLRy8zMxM5+qw7yBXr15FeHg4YmJioFAoULduXUyePBkDBgww/GY7++f4c2RM7Whwv7X5n+CWsj46CM9gGMsMUHHKGliZP1lnu18FMZ6nF/wQvXmZGCjah+A3zdFnFG1RWxCHnsJjrIXtm4r6FhWEbWnK658A8PBLmemsrx+S9cQxRXfU5sdhkus6u6atsGeqAPwsnYwceGKCyzrWfsvOYurrZeBDhSr8x5AyrnjKBMGHl4n5rt8WTD/qAFvyh4MHRm/fZnt6riqPFFUgZ+FL7ZS8PWJVNaFkBJjoul7vvlmMF37L/whyRoSv3H6wWlrV94Q6/Hv4yOVPlDFiQgZriZR3RpjwlFkr/D5TBaAiP9Xsc2eoysKXo6tdcSJhyrD2qeeyMO9rTHZZY9JnT1X54Zf8ieglOoqKvFQkq4JwVPEORov/4pyenM0FRQsAPLQWXjT6PcXRlvzhyGY84crLxyDxXp21nQzJUnkhVlULrYoMojfWYVlP/FNochigYFzBijJfGHzvc1V53FXWYZ0GOFFZCZeUzTBEvNek9LxSeeOxqjIq8ZM4u7eWVDtlAxGt6IAa/AeoIXiA5yo/XFE2QQXeC/zP7TvW95xVtMZ+WV8cPdIJDesX72mqKOAAcOrUKQwaNAiurq4YOHAgPDw8cODAASQlJWHRokWYOnWqo5OoZdhHV9D3/PtG7XtHWRuA/poctX2yvjihCNMMRuRBhTmuSxDA5+6fWNKclHcwOMc64XZD0QCpTADeKTQ9LCGEEMeJU9ZAGd5rpKsq4KGqKqryE9GsUMs5cW7PA9ti0pFVcC3mC3GU+oBDoVCgRYsWSElJwfHjx9GwYcGsEllZWejatSuePHmCy5cvo1Ilw3207WXA+5cw6MooRyeDEEIIIYTYEo+HvlFR8K5o3PhaZ1Xyli410alTp/Do0SMMHjxYE2wAgLe3N2bMmAGZTIZt27Y5MIW6eI6b3p4QQgghhNgLwyDjhnkLUDqTUj9o/MyZMwCALl266LzWtWtXAMDZs2d1XitKKrVfX+dpE0KQ9IndTkcIIYQQQhzEp0kTu5UzbdV1q9QHHAkJBTNYhIaG6rzm7+8PDw8PPHz4UOe1olJSUqBU2mclyLKKp0iyy5kIIYQQQoijVBw0CBnZ2cjI5p4G31oEAgGqVTNtZjNjlfqAI/vNF+jl5cX6uqenp2YffQIDbbf6ZVGxx2lALiGEEEJISVeuTRv4+/tDLDZuBXhnVerHcFiLq6ur3f6rMXAg+C7GrfLsaG5+fkbtV2vUKIR07w5BcZiFwc6DaMoEcC+0VdyFdO+OGsOHo+aIEXAp5wt+xapQuXk7OllGafbVV45OAqvQgQPx7u7dJr2n0fTpqNC0qY1SZB0qnhD8wCpwraC9sjBfLEaFJk3gbmGlT7Ovv7bo/bbgVqECWi9ejCp9+8KrqmUrVvs0b272ext+9hkC2ra16PwAENSpk8XHqD50KBpMmoSKRdJTrl491PnoI1Ro1szoY1Xp0wc+NWtanCZ7K1unDqr174+Atm2NfsZazMTnHo9v/+KlpfcAZ+TXqhXca9aEWCy2WxnTVkp9C4e6ZYOrFSMnJwc+Pj52TJFh7gEBaLloES7MmmV45zdG3rmjdQPg8Xi48/vvuL5sGZgiXcE8QkIgy86GLCtL5zihgwcjYZfumh5cgsLC8GDnTs7XeXw+Bp89C5eyZQEADMPgQM+eyHnMvkq2KYRlyqB848aoPmgQ/Jo3h5ufH3g8HqRSKe5FRiJtyxZIkpIQ0KYN6o4di9QLFyB98QJ3N2wAo2BfQ6JKnz6o9t57kGZk4JwNCpyNpk9HSNeuyHnyBD7Vq8OzcmUAAKNS4f6OHXhy7Bgybt9Go88+Q9W+feHi4wOFVIrshw9xf8eOgvfVqIHM+/eR/egR3Pz8oJBIkJ+VBWV+PgI7dICLtzcC2rRBcNeu4AsEkGVnQ56bC7lEgkN9+2rSwheJ0C4iAmIvL0R+/LFVPp/IwwNdf/8dsuxs+LdqBUGhGpuW8+dr/j8/Kwv/jhiB7DfdGcvVr4/Oq1fDtXx5MEol+EIhGJUKyVFRSIqMxMO9ps0FX5RPrVrIjIsz6T3VhwzB3T/+QN7zt9NGB3XujMbTpyP1/Hnc+PlnKF7rronQdO5c1Hn/fURPmYLkyEit12qNGoUGEybgakQEHu7bx3reLuvXI7BDB6jkcryKj0f6lSvIz8yEX/Pm8G/RAnyRCAAw8vZtvLxzBzlPnsCvWTM82LULt1atYj2me8WKeGfrVmQnJuJAz56s+7DptGoVri9fjsx43UX3wlatgkomQ+b9+8h/9Qr+LVuiUo8e4PH5SDl9GsknToDH58OzUiVc/o59DvoPYmPBMAzkEgmUAgGSk5MREhLC+VBUKZV4tG8fbq5aBcnTp1qvufj4wKVcOTT67DMEtG6Np9HRkGVno3LPnnB7E8SEDhqEvy0omFuLa/ny6H/8OASuruDxeKg+aJDmNYZhkPP4Me6sW4eEPXu03lfnww/R7KuvIElNxYXZs/Hy3j14VqqEhl98AYmPD66NGgVZZqbO+bpt3Ih7f/6JpydOsKan4aSCFe5znjzB0+hoCN3cUPnddyEsUwYquRzPL11C5NixnJ+nzscfo8n//R/4AgFiN2/G5cWLzciVgoJ2y/nzwRcULDinksuR/egR+GIxvKpU0dpX8uwZ9nZmX41drf0PBWvYMCoVDvXti6yEt4sEBnbsiC7r1uHmqlW4vXo1VHLuhTBdfHww5MKFgmMxDOS5uRB7egIA/qpd2+DnarVoEVy8vRHYvj2eX7kCSWoqkv/7Dxl37sDV1xeS5GTIJQWLjXrXqIFOq1fDvVBF1OGBA/Hqrm3Wa6o5YgTqfPih5lkEACqFAnKJBJcXL8bTkyfBd3FBnQ8/RJVevSB0dUXeixdwKVsWmXFxrNdF2dq18SqWfap+7xo1kHX/zXouPB54fL5OGaUokacnBp89C4FYjL9btWItuwAFZYJa77+v+f3HbtpkZC5YgMdD/+PHkRoTgwtz5rDuInJ313y/QMHzjlEo4NuwIWpPmIB0iWkLzTqrUj8t7sKFC7Fs2TL8/vvvGFTopg4AaWlpqFWrFjp27IgDB/Sv5mtvUqkUiXFxeLlzJ7Li4pBx6xbnvnU/+QRNv2Bf5Od1Whokz56hbK1aELq5abYrZTLs7dwZ0gztlaB779+P6KlTkfvkiVHp7Pbnn/hvzBjW13h8PprMnIm6H32ktT3x8GGc+b//M3hsnkDAeSPqc/AgvKtXB4+lVkYqlSIpKYmz4BK/fTsuLligs71CkyZ4582MZY+PHsXp6dMNptEUzWfPRu3Ro616TFMppFI8PXkSr1NTEdCmDcrWqgUAyLhzB/8U+X2YQ+ztjaExMUbtq1IqkXbhAgSurvCtXx8CPa16ucnJSD5xwqSCTO0xY9C8UK32vyNGIP3a27npeUIh+hw4gIO9eum8N6BtW3T74w9IX77E3T/+QH5mJoI7dUJIt26afeQSCWQ5OUg6dgz3d+4ETyhE+ffeQ+Phw+Hq6or069dxYtw4yN5UdngEB6PXvn0Qe3gg/9Ur7GzTRue8lXv1Qodly4z+jIXlpadjdwf2FeXbhIcj9M0ip/999BFSz59n3a/hZ5/Bu1o1yCUSBHXsCLcKFZB84gROTtRecb5s7drozREwFZV+7Rr+HTGC9bUPChVKDP1ui8pJSkJKdDTKBAYiqEMHTSBmiFImw7ZCMxYCgE/Nmqj36afwrV8fmfHxODVtmuY1vliMdt9/j9Off856PM/KlVkrUGqPGQOxtzde3rkDoZsb8l+9QtbDh/AICkLzOXNQrk4dvemU5ebizIwZSDlVsLK4b8OGCFu5EmX8/XX2Vefdq927Eb9xo9ZrFZo2xTtbt+LRoUM4y/Gc+ICjcFjY88uXceyDD3S2d1y5EpW6d9f8rZBKcXLSJKSeO2fwmIUFhYWh7ZIlmsopQ14/f449HfUvkKt1fb18iWvLliHn8WP41q+PBpMmaYKGV0lJOPPVV8i6coX1OG5+fhh0in2F98vh4Yj980+tbd6hoQgdNAg+NWogkOM3WRjDMHh5+zaUMhnKN2oEvlC7rvjZ2bOInjqVtYLDEJGnJ6oPHox7GzZobXerUAHv/fsvhGW4V3MvnD62Zy2jUuFgnz6aiiMACOnWDY1nzMDRoUMhz83V2t5u6VLwRSKkX7uG/FevENC2LZ4cO8ZZUAeAwA4d0G7pUs11oczPx7ZGjbQ/o4cHOq5cCb+mTTXPEZVSiStLluD+9u16g8miBG5uUObl6WxvPns2pC9f4vaaNVrb2/3wA6r26aP39zUgKgqPDhwATyBA9cGDta5xU+97zqzUt3C0a9cOy5YtQ1RUlE7AEfmm9rFdu3aOSJpBgjJl0HTuXM1FmBwVhZu//oqXd+5o9nHz80PN4cM5j1HG35/1ASUQi9Fo+nRc/OYbTW1/9SFDULZWLTScPBnnvvzSqDT6t2ihXWOBgi5CTf7v/+BTowbKstT+VOndG9KMDMRt3Qq+QIDQgQNRd+xYvH7+HOdmzULapUtwDwxEi3nzcCU8HNmPHumm/03NoDk4C7aFjsfV9Uvg4gKP4GCtmrLaY8agQpMmeBodjTJ+fnh89ChrAcSYG7utCV1dUZmlhtu3Xj2rHJ/3pmbSGHyBABWN/O15BAej9qhRePzPP0i/etWo9zAqldbfrRYuxNmZM/EqNhZiLy80nzsX3tWqoVy9elq/KQCo96bWzrVcOc5gXuTuDpG7O2qPHo3ao0drHhxqFRo3Ru99+5By+jR4AgGq9u2rufZcypZF2bp1dWot6+qpRTbErUIF+NSsydoagUJ5UYaji0btMWM0Nd2FBXbsiEo9euDJsWMACh7IpnRPErm7G72vKTxDQlCLpQBsiEAsxpDz53Fj5Uq8TkuDX9OmqD16tCZg8apaFcOvXcPDffugyMtDxXbtULZWLXhVq4bD772nc7ymM2fiaXS0Tktv6MCBmoDeHGIPD3ReuxYv794Fo1CgXP36mpp/LlUHDEDi3r1va4B5PDT67DMAgEdQkNlpAQC/5s3xQWws4rdtw4NduwAeD7Xef18r2AAK7jFdf/8dL27cgEouR/lGjbC3SxdIX7zQOWa3jRsR0Lq1WekxNsBUcy1XDm2+/Zb1NbcKFVCuTRvOgEOgp299g4kTkXLqlOY55R0aii7r15vU/YfH48G3QQPO1yu2a4c+Bw4gNSYGbuXL4/Tnn7MGH34tWuBVbCzkOW9XO2/8+eeoNXIkms6ahfs7diD1/Hm4lC2L+hMmGP1M4nrW8vh8hP3xB2K+/x687GxUaNCg4Liurui9fz/it26FMj8fNYYO1era5t+ypeb/gziCRjc/P/T/7z+dvBe4uGDEzZuI37oVr2Jj4VW1Kup89JHOfnyBAC3mzEGTGTOgkssh9vJC1sOHrBVMasOvXkXU+PF4fkl31XeBqyvqfPQRshMT8eToUYDHQ+3Ro1GpR4+C1/VcI+6Bgag/YQLn6yVFqQ84wsLCUKVKFezatQvjx4/XWvhv2bJlEIvFGK6nwO5Mgrt0QXCXLnidloZHBw+CLxSiWv/+cDGzS1iNIUNQoVEjvLx7F2UCAjQ3/ip9+iDlzBkkHjwIoKD57+Xt26zH4PH5eGfLFlxfvhy5T5/Ct3591B83Tm9tNQBNIa2wMn5+6LZxI5QymebHq3j9WqelwcXHB+4WLJBTtPao8GdRE3LVNPD56LljB26vW4e89HT4NWuG0EGDwOPxNAX5FzdusAYcKo5uXCWJrfv1KvPzjd+5SMDhU6MG3t21C3KJBAIXF8133GLuXESNG6d5SIcOHAh/MwtBRbkHBqLGsGGsr7UND0fkJ59Amp4OAGg4dSrK1a1r0flCunVjDTjcCxU2Q7p3x8P9+3X2CWzfnvWYfIEAHZYvx4vr1yFJTUVA69ZwLVfO6DQJbRRwWMKlbFm0/N//OF8XurmhZpFWmbK1aqHF//6HSwsXarb5NmyIwA4dUKFJE8glEjw5ehRib280+/pri4INNR6PZ1JlgGflyui9dy/it22D4vVrVB86VJMOa/V/rzlihE7eFMXj8VChcWPN31wt1YVb3U1lKPgyFU9PAKPveebi44M+Bw/i6alT4PH5CGjVyqLPxcUjOBjVg4ML0uPqyhpwlK1VC+0iInB7zRoo8vJQqXt3Tassj8dDzeHD9VZQmsPFxwdVJ03SqaH3CApC05kzDb7frUIFtPnuO5yfPVtre+3RozkL8QKxGHU+/NCo9And3IA334e3ntmZmnzxRUEAxrB3CuKLRHDx9kbH5cuRn5kJnlAIsYfH2zQVk3G3tlTqAw6hUIiff/4ZgwYNQu/evTFw4EB4eHjgwIEDSEpKwqJFi1C5UN/F4qCMvz/qfWKdhTp8atbUGVTHFwjQPiICDSdPBqNUwrNSJWzVU/si9vLS+/A2VeGbTHDnzjr97+t++iln0GAMhuOGUhjnA4NhIPLwQJMZMzjfKyp0EypM7uT9NCv17FlQc2NAcJcuSDl9mrWZ2tYBhylN42zfM18ohIu39qD1Ck2aYEBUFNKvXYN7xYqcXfWsrWytWhh44gRexcXBIzDQ6K4k+lQfMkRnHIeLjw/8Co1bCAoLg3tQkNYYCLGXl1atY1E8Ph8VmjZFBc49uNmqhcMRao0cCe9q1fDs7Fm4BwVpWq0ELi7osGwZmB9/tMu1o497YCCasHRZdatgzrdnHVwBh6mtFIUZak1tOHWqScfj66mh1vcaUHBfCWFZ68tWCrdgFFbG3x/uAQFoxdJl2JmFDhwIv+bNcff33wu6r3bpgmosrYm2ZGwAA4C1kpcCDgo4AAAdO3bE0aNHER4ejr1790Iul6Nu3br45ptvMHDgQEcnz2kVHqRXpXdvJB4+rPU620PN2gQuLuixZQse7NyJ3KQkBLZvj2BLb+xFar41jOhSxVX7UZhf8+ZI+u8/ne3eFs5CY2tV3n3XYMBRJiAAnVatwsG+fbW60anZvIVDJjN636JdqvQRe3pyNu3bEl8otFp3NqBgcHizr77ClSVLCo4vFqNNeLhWgM4XidDu++9xfu5c5CQmwrVCBbSPiLDZA5Mr4LD4d+wgAa1bc3YDcnSwoQ+Pz4d39erIevBAa3uoFcZuGcIVcJjSBbMoQ5VOld9917Tj6WvhcLLpSrkqXuw2o5UNeFaqhFbffOOw81tSiQkYDkpLAwo43mjWrBl2mTD7EtHWYNIkpF28iLw33T/K1q2L6oMH2+XcYg8PnYHnluBq4ShcWOZ6+BjTOlLtvfdw7ccftR4KAldXq0w7aUsh3buj6cyZuLVmDWcNmjpf9PXptSWVjQKOkqTOhx+iSu/eyEpIQLl69TQDYwvza94cfQ8ehEIqhbBMGat3TymMLxIhoE0bnYHqjp5AoTQKHTAAVyMitLZV0dOn3Vqqvvce4rdu1dnuVr682cfUF6x0Wr1ab/cZ1uPpCTgsaYmxp+IccNhL3bFjcff337W2eVSqZPB9hioTnC0odQRah4NYhXdoKPocOIAOP/2EzmvX4p0tW6zSBcQhOAqi1qqddClbFi3nz9c8EHlCIdqGh3OPC3ESPD4fdceOxXunT6MKy+BhoNCD10EBh0ndc4wIDksqtwoVENC6NWuwocYXiSD29LRpsKHWauFCzbSbPD4f9cePh3+rVjY/L9FW56OP0GjaNHhWqYKydeqg7dKlRk/cYAm2cUzlGzWCq6+v2cfUF3AEhYWZfDx9NdTFpTDJNkEM0Vb53XfBK9KaoZ7BD4DZ63BRlypq4SBW5FK2rMnN1M5I7M2+8Jz7mwF5ALTmQC/M2Jkmqg8ejOAuXZAZH49ydetCzLHSvbPiepirH7ycwZmNA44GkyZxTk9alDGtUcQ+PENC0O/oUWQ/fAi3ChWK3e+hpODx+WgwcSIaFJnm2NbK1qqFFnPn4uoPP0AplcKzShW0W7rUomPqqyAyp+JDWAKuSWrhMMz3zZpP6vEilXv2RL3x4zWvl2/YkHWWKkML9FLAQQEHIToqtm8PgasrlFKp1vY6hdYTEZYpg+CuXbUWbuOLRKjWr5/R53EtV87sKR8drWgNkJqmFpDjgW7rPuwVO3SAe2AgJCkphnemgMOp8Hg8eIeGOjoZxEFqffABqg8Zgrz0dLgHBTndeBe3kBC4BQQgLzVV5zWu+6GzEXNMWEK0BXbowLk+Ss0RI3S6XLn4+MCvRQu9x6QxHNSlihAdQldXnRlMqr33HryrV9fa1nbJElR+912IPDxQtk4ddFq9Gh6FWkFKMq7CgGYMB9f7bNw9R+zhgR5//YWaI0eiYvv2aDpzJprOmsW6L9dsYYQQx1CvY+RswQZQcM+rx9HyY8o00PbQgKXLa+GZ6Ij5PIKD0bjQVPx8kQitv/3WYNdTe3RNdXbFIywnxM7qjR0Lv6ZN8fzq1YLVYNu313kIij090eGnnzhXWS3JuGaVETh4DAdQMO1n4WmY8168KBgIW6RFw9rzzRNCSrbKffvi0e7dyLh5U2u7v4HabXurNmAA7u/YAWlGBoCCFhhLFg0l2upPmIAqffsi68ED+DZsCFcjxqtyzWzp+2btt9KAAg5COFRo0gQVmjQxuF9pCzYA7mkXNc3GXAGHA/LKrXx5hA4ahIRCs9CFdO8Oz0LTOhNCiCE8Ph8df/4Z/40Zo1m8tVLPnqjSt6+DU6bNMyQE72zfjod790IukaDyO++gQtOmjk5WieIRFASPQgumGiL29ETZ2rXxKjZWa3sjE9eDKc4o4CCEmIzhCjjUXaq4xnA4qFm59cKF8G/eHC9u3kTZ2rVRrX//UhkoEkIs4x4QgL5HjuDlnTtw8fGBR0iIU95LPENC0OizzxydDFJIs6+/xsmJEzWrwFfu1QsBbdo4OFX2QwEHIcRkKoWCdbuhdThsPUsVFx6fj2r9+6Na//4OOT8hpOTgCwQoX4q6whDrCGjVCu8dO4bnly7BPTAQ5erXL1VjO2jQOCHEZD4czfNVDczSZY8xHIQQQogzcitfHpXffRflGzUqVcEGQAEHIcQMbpUrw6vISr2uFSogsH17AHq6VFHAQQghhJQ69PQnhJiMx+Oh/apVCAwLg9jbG/6tWqH7n3++XXHXiQaNE0IIIcSxaAwHIcQsZQIC0GXtWvYXuQKOUtaETAghhBBq4SCE2ABXSwZ1qSKEEEJKH3r6E0Ksj6vrFHWpIoQQQkodCjgIIVbH1cJR2mblIIQQQggFHIQQW3CydTgIIaWPZ+XKOtvcKlRwQEoIIfT0J4RYHee0uNSlihBiJ/XGjdPZVn/CBAekhBBCs1QRQqyPZqkihDhY6MCByHv+HPFbt4JhGFQfMgQ1R450dLIIKZUo4CCEWB1XOwa1cBBC7IXH46HBxImaVg26/xDiOBRwEEKsj1o4CPn/9u4/Loo6/wP4C4RVYwM0bZFYQMAISjLFn2h+BdQSIgUkzcQjuU7SIvXOTLvDH3TkhZqn5sO61CxOLZEDxIeJoBFoSpli1yUI/gDR1SxAMAVlvn/obrvuLuxPdnFfz8djH9XMZ3ZmX312hvfOfGbISrDQILI8juEgIpPTOoaDg8aJiIhsDo/+RGR6fA4HERER3cWCg4hMj5dUERER0V0sOIjI5LRdM81LqoiIiGwPj/5EZHraCg5eUkVERGRzWHAQkclpPcPBS6qIiIhsDgsOIjI9nuEgIiKiu1hwEJHJaR2rwTEcRERENodHfyLqMLykioiIyPaw4CAik9M6hoOXVBEREdkcFhxEZHocNE5ERER3seAgIpPTNoaDz+EgIiKyPR169C8rK8OyZcsQHR0NX19fuLq6IiIiot3lPv/8c4SGhsLd3R1eXl544YUXcPz4ca3tjx07hsmTJ8PT0xPu7u4IDw9HVlaW1vaXLl3CnDlz4O/vD4lEguDgYKSnp6OlpcWQj0lEvKSKiIiI7nLoyJXl5eVh1apVEIlE8PPzw9WrV9tdJj09HampqZBKpUhISEBjYyN27dqF8ePHIzs7G8OGDVNpX1RUhJiYGHTr1g3R0dEQi8XIyclBQkICampq8Nprr6m0l8lkCA8Px4ULFxAZGQlfX1+UlJQgNTUV3333Hf7973/zjyQiE+ElVURERLanQwuOiRMn4tlnn8Xjjz+OX375Bf7+/m22r6ysxLvvvgs/Pz8UFBTAxcUFADBz5kyMHTsWycnJOHz4MOzvXqZx69YtJCcnw97eHnl5eQgKCgIALFiwAGFhYVi+fDmef/55eHp6KtaRkpKCmpoarFq1Ci+//DIAQBAEJCYmIjMzE5mZmYiNjTVHHET3La1FOot3IiIim9Ohl1QFBARgwIABcHR01Kl9RkYGbt26hfnz5yuKDQAICgpCTEwMTp06hcOHDyumFxUV4cyZM4iNjVUUGwDg4uKCefPmobm5Gdu2bVNMv3btGrKysuDt7Y2EhATFdDs7O6SkpAAAPvnkE4M/L5GtEgRB43SO4SAiIrI9Vn30Ly4uBgCEhoaqzQsLCwMAlJSUGNy+tLQUN2/exJgxY9R+kfX09ES/fv1w5MgR3L5928hPQkQAL6kiIiKyRR16SZW+KisrIRaLIZFI1Ob5+voq2ii3V56nTCKRQCwWo6qqSq29j4+PxvX7+PigoqIC1dXV8Pb2bnNbb9y40faHMbHm5maVf5LumJ1xdMnv9q1bmqe3tnb4d8VasN8Zh/kZjtkZh/kZjtkZxxL5devWzSzva9UFR0NDA3r37q1x3oMPPqhoo9weAJydnbUuo6m98uVayuTvU19f3+621tbWWuRMiEwm6/B13i+YnXHayu96U5PG6dcaG1FdXW2uTeoU2O+Mw/wMx+yMw/wMx+yM01H5denSReuP8MbSu+BYvHixXpXWrFmzNJ5xuN+4u7t36Pqam5shk8kgkUggEok6dN2dHbMzji751XTvrnG6i6srpFKpOTfParHfGYf5GY7ZGYf5GY7ZGed+yk/vgmPLli1o0vLrpSZRUVEGFxzOzs4qZySUXbt2TdFGuT2ANpdxdXVVa6/tDEZ7Z0CUmesUVHtEIpHF1t3ZMTvjtJVfFy2Dwx0cHW0+c/Y74zA/wzE74zA/wzE749wP+eldcFy4cMEc26GRr68vjh49qqjulGkar6E8rmPAgAEq7WUyGRobGzFw4EC19srjOpRVVVVBJBLBw8PD6M9CZEu03qWKg8aJiIhsjlXfpSokJAQAUFhYqDavoKBApY0h7YODgyESiXDgwAG1P5DOnz+PiooKDB06FA4OVj3UhajT4G1xiYiIbI9VH/2nTZsGBwcHrFy5UuWyp7KyMmRmZsLf3x/Dhw9XTB89ejS8vb2xc+dOlJWVKabX19crnnA+ZcoUxXRnZ2dER0fj7Nmz2Lx5s2K6IAhYtmwZAGDGjBnm/IhE9ydtZzj44D8iIiKb06E/3ZeXl2P16tUAfr+NbEVFBZKSkhRtNmzYoPh3Pz8/LFy4EKmpqRg5ciSioqLQ2NiIXbt2AQDWrFmjeMo4ADg4OOCf//wnYmJiEBERgejoaIjFYuTk5KC6uhrLly+Hl5eXyjYtWbIExcXFmD9/Pg4ePAgfHx+UlJSgtLQUzzzzDGJiYsyWB9H9Smht1Tidl1QRERHZng4tOGQymcqTvgHg8uXLKtOUCw4A+POf/wxPT09s2LABmzZtgqOjI4YPH45FixapjdMAgKeffhp79+5FWloasrKy0NLSgsDAQCxduhTR0dFq7d3c3LB//36kpqZi37592Lt3L6RSKRYvXozk5GT+IktkAK1jOPh9IiIisjkdWnCMGjUKdXV1ei8XFxeHuLg4ndsPGjQIO3fu1Lm9m5sb1q1bp/d2EZEWWgoOcAwHERGRzeHRn4hMT0vBYc9LqoiIiGwOCw4iMjkt5zcAXlJFRERkc1hwEJHp8TkcREREdBcLDiIyPW0FB8dwEBER2Rwe/YnI5HiXKiIiIpJjwUFEpse7VBEREdFdPPoTkenxDAcRERHdxYKDiEyOd6kiIiIiORYcRGR6ra0aJ7PcICIisj0sOIjI5LQNGucZDiIiItvDgoOITI8FBxEREd3FgoOITI63xSUiIiI5FhxEZHq8LS4RERHdxaM/EXUYnuEgIiKyPSw4iMjktA4aJyIiIpvDgoOITI+DxomIiOguFhxEZHocNE5ERER3seAgIpPjJVVEREQkx4KDiExP2xkO3qWKiIjI5vDoT0Qdh5dUERER2RwWHERkcrykioiIiORYcBCRyQmtrRqnc9A4ERGR7WHBQUSmx9viEhER0V0sOIjI9FhwEBER0V0sOIjI5LSN4OAlVURERLaHBQcRmR7PcBAREdFdLDiIyPRYcBAREdFdLDiIyOS03RaX5QYREZHtYcFBRKbHMxxERER0FwsOIjI9bWc47LnLISIisjU8+hORyWl9zjjPcBAREdkcFhxEZHraLqkiIiIim8OCg4hM7pH/+z+N08UeHh27IURERGRxHVZwtLS0IDs7G7NmzcKQIUPwyCOPwMPDA2FhYfj4449x+/Ztrct+/vnnCA0Nhbu7O7y8vPDCCy/g+PHjWtsfO3YMkydPhqenJ9zd3REeHo6srCyt7S9duoQ5c+bA398fEokEwcHBSE9PR0tLizEfmchmPTplitrlUy6+vnDx8bHQFhEREZGldFjBcebMGcyYMQO7d++Gn58fEhMTMXnyZNTW1mL+/Pl48cUXNd5KMz09Ha+88gquXLmChIQETJw4EYcOHcL48ePxzTffqLUvKipSzJs0aRISEhIgk8mQkJCAtWvXqrWXyWQIDw9HRkYGhgwZgqSkJPTo0QOpqamIj4/XentPItJO7OGBEStWwFEsvvPfUilGrVlj4a0iIiIiS3DoqBWJxWKkp6dj6tSpcHJyUkxPTU1FZGQkvvzyS2RnZ2PixImKeZWVlXj33Xfh5+eHgoICuLi4AABmzpyJsWPHIjk5GYcPH4b93Tvf3Lp1C8nJybC3t0deXh6CgoIAAAsWLEBYWBiWL1+O559/Hp6enop1pKSkoKamBqtWrcLLL78M4M4zBBITE5GZmYnMzEzExsaaOx6i+45PVBS8J0zAb5cv44E+fWDHAeNEREQ2qcPOcLi7uyMxMVGl2AAAJycnzJ49GwBQUlKiMi8jIwO3bt3C/PnzFcUGAAQFBSEmJganTp3C4cOHFdOLiopw5swZxMbGKooNAHBxccG8efPQ3NyMbdu2KaZfu3YNWVlZ8Pb2RkJCgmK6nZ0dUlJSAACffPKJCT49kW2yd3CAk7s7iw0iIiIbZhWDxh0dHQEAXbp0UZleXFwMAAgNDVVbJiwsDIBqkaJv+9LSUty8eRNjxoxR+4PI09MT/fr1w5EjR9ocX0JERERERNp12CVVbfnss88AqBcKlZWVEIvFkEgkasv4+voq2ii3V56nTCKRQCwWo6qqSq29j5aBrD4+PqioqEB1dTW8vb3b/Aw3btxoc76pNTc3q/yTdMfsjMP8DMPcjMP8DMfsjMP8DMfsjGOJ/Lp162aW97V4wbFlyxbk5+fj6aefxrhx41TmNTQ0oHfv3hqXe/DBBxVtlNsDgLOzs9ZlNLVXvlxLmfx96uvr2/0ctbW1FjkTIpPJOnyd9wtmZxzmZxjmZhzmZzhmZxzmZzhmZ5yOyq9Lly5af4Q3lt4Fx+LFi/WqtGbNmqXxjAMA7N27F3/5y18glUrx4Ycf6rspVsXd3b1D19fc3AyZTAaJRAKRSNSh6+7smJ1xmJ9hmJtxmJ/hmJ1xmJ/hmJ1x7qf89C44tmzZgqamJp3bR0VFaSw49u3bhxkzZuDhhx9Gbm4u3Nzc1No4OzurnJFQdu3aNUUb5fYA2lzG1dVVrb22MxjtnQFRZq5TUO0RiUQWW3dnx+yMw/wMw9yMw/wMx+yMw/wMx+yMcz/kp3fBceHCBaNX+uWXXyI+Ph4PPfQQcnNztY6P8PX1xdGjRxXVnTJN4zWUx3UMGDBApb1MJkNjYyMGDhyo1l55XIeyqqoqiEQiePDpyEREREREBunwu1TJi40ePXogNze3zWvFQkJCAACFhYVq8woKClTaGNI+ODgYIpEIBw4cUHvA3/nz51FRUYGhQ4fCwcHiQ12IiIiIiDqlDi048vPzER8fD1dXV+Tm5mod2yE3bdo0ODg4YOXKlSqXPZWVlSEzMxP+/v4YPny4Yvro0aPh7e2NnTt3oqysTDG9vr4eq1atgkgkwpQpUxTTnZ2dER0djbNnz2Lz5s2K6YIgYNmyZQCAGTNmGP25zeXe2wiT7pidcZifYZibcZif4ZidcZif4Zidce6X/Ozq6uqE9psZr7y8HKNGjcLNmzcRExMDPz8/tTaenp6YNm2ayrT09HSkpqZCKpUiKioKjY2N2LVrF5qbm5GdnY1hw4aptC8qKkJMTAy6deuG6OhoiMVi5OTkoLq6GsuXL8drr72m0v7SpUsIDw/HhQsX8Nxzz8HHxwclJSUoLS3FM888g23btvGhZUREREREBuqwguPrr7/Gc88912abkJAQ5OXlqU3//PPPsWHDBvz0009wdHTEsGHDsGjRIrVxGnLfffcd0tLScPToUbS0tCAwMBCzZ89GdHS0xvaXLl1Camoq9u3bh7q6OkilUkyZMgXJycmd/q4ARERERESW1GEFBxERERER2Z4OHzRORERERES2gwUHERERERGZDQsOIiIiIiIyGxYcRERERERkNiw4iIiIiIjIbFhwEBERERGR2bDgaEdtbS0++OADTJo0CU888QR69+6NRx99FNOnT8e3336rcZmGhgYsWrQITzzxBB5++GH0798ff/3rX9HY2KjW9sqVK1i1ahXi4+MRFBQEV1dXuLq66rWN77//vmK50tJSvT/jzZs3sWLFCgwcOBASiQSPPfYYkpOTceXKFbW2169fx9q1a5GYmIjBgwejR48ecHV1xblz59TaMjtVSUlJinVpe/3jH/8AYJ3Z9e/fX+t2R0RE6J1da2srNm7ciBEjRsDNzQ2+vr6YOXMmzp49q7H9xo0b8eqrr2LEiBF46KGH4Orqiq+//lqtHbNTlZaW1m6/mzNnjqK9NeYnl5ubi4kTJ6Jv376QSCQICgrCzJkzUVNTo9Pycra4z7NEdvrs8wDryy8jI6Pd7Y+KijJbfp2571k6u85+vBUEATk5OYiMjIS/vz/69OmD4OBgvPHGG1qPkabKTp9+pw8+h6MdS5Yswfvvv4++ffti5MiR6NWrFyorK5GXlwdBEPCvf/1L5YGCTU1NeOaZZ3Dy5EmEhoYiKCgIZWVlKCwsxMCBA7Fnzx5069ZN0V7+QEQ7Ozv4+vqitrYW169fR11dnU7b9+OPP2LMmDFwcHBAU1MT8vPzMXjwYJ0/X2trKyZPnoyCggIMHjwYISEhqKysxO7du+Hl5YX9+/ejV69eivbnzp3Dk08+CQCQSqVobGzEr7/+ihMnTsDLy4vZtZHd7t27cfLkSY3vtW7dOjQ1NaGgoACDBg2yyuz69++P+vp6JCUlqc3z9PTEtGnTdM4OAF5//XVs3boVAQEBGDduHC5evIj//Oc/cHJywv79++Hr66vSXr6DdnNzgyAIkMlkyM3NxahRo1TaMTvV7L7++msUFxdrfJ9PP/0UtbW12Lx5MyZNmmS1+QmCgLlz52LLli3o27cvwsLCIBaLcfHiRZSUlOCjjz7C8OHDdcrO1vZ5lsxOn32eNeZXVlam8WHEAJCTk4P//e9/WLp0KZKTk82SX2fue5bOrrMfbxcvXoz169fDzc0NEyZMwIMPPogffvgBhYWFEIvF+PLLLxEYGGiW7PTpd3qpq6sT+NL+2rp1q7B792616Xv27BEcHR0FV1dXQSaTKaYvWLBAACC88cYbKu3feOMNAYDwt7/9TWV6eXm5kJeXJ1RXVwt1dXVCv379BAA6bduVK1eEJ598UggODhbi4uIEAEJ+fr5en2/dunUCACE2Nlb49ddfFdNXrVolABD+8Ic/qLSvqakRsrKyhDNnzgh1dXVCWFiYAEA4ceIEs2snO22vgwcPCgCEwMBAq85OKpUKUqnUJN+rnJwcAYAwYsQI4fLly4rpX3zxhQBACA0NVVtmx44dwqlTp4S6ujohISFBACDk5uZ2in5n6ew0vcrLywUHBwehZ8+eKu9jjfmlpaUJAITExETh6tWravN//vlnnfOztX2eJbPT9tK0z7PW/DS9Ll++LPTs2VNwcHAQysvL2fesMDt9+p61ZXfq1CnB3t5ekEqlwrlz51TmvfPOOwIAYdq0aVbR7/R58QyHEaKjo1FYWIgDBw7gqaeegiAICAwMxLVr13Dq1Ck4OTkp2jY1NcHf3x+9evXC8ePHtb7n4MGDUVFRgTodfqVPS0vD+++/j6+++gpr1qzBtm3b9P6Vfty4cTh69CjKysrg6empmC4IAp566ilcuXIFp0+fRvfu3TUuHxMTg4KCAr0rX2b3u/nz5+Pjjz9GWlqaxl/A72Wp7Pr37w8AWn810kdiYiJ27tyJvLw8hISEqMyLjIxEcXExTp48CalUqnH5uXPnYvPmzRrPcLSF2f1uzZo1SElJQVJSEtLS0nRatyXy++233xAQEABXV1d8++23cHBw0GlbtbGlfZ61ZSen7z4PsPwxQ1lWVhYSEhIQERGBjIwMnZezpb6njaWyk+sMx9vS0lKMHTsWkydPxkcffaQyr7KyEoMGDcL48eOxY8eOdrcfsFy/uxfHcBjB0dERANClSxcAdzrCxYsXMXToUJVOCABOTk4YOnQozp49q/c1s5ocP34cK1euxJtvvonHHnvMoPe4ceMGvv32W/Tr10+lEwKAnZ0dxowZg6amJnz//fdGb++9mN0dv/32G7744gt07doVU6ZM0WndlsyuubkZGRkZWLlyJT788EOt17e2p7i4GE5OThg2bJjavLCwMABASUmJUduqCbP73aeffgoAiI+P13ndlsivsLAQdXV1iIiIwO3bt5GTk4PVq1dj06ZNqKqq0uu9bG2fZ43ZGbLPAyz73b3X1q1bAej33bG1vqeNJbPrLMdbX19fiEQifPPNN2hoaFCZt3fvXgDA6NGjdXovS/a7e7HgMFB1dTUOHjwINzc3PP744wDudEQA8PHx0biMfLq8naFu3ryJpKQk9O/fX+frHzU5c+YMWltbzb6992J2v8vOzkZDQwMiIyPRo0ePdtdryewAQCaTYfbs2Vi+fDkWLFiA8PBwhIaG4syZMzq/R1NTEy5dugQvLy/FTtxc26uM2f3u0KFDOH36NAYPHoyAgACd1m2p/OS/FHbp0gUhISGIj4/H0qVLMW/ePAQHB+Ptt9/W+b1sbZ9njdnpu88DLP/dVXb+/Hl89dVXeOSRRxAeHq7zcrbW9zSxdHad5Xjbs2dPpKSkoKamBkOGDMG8efOQkpKCmJgYLFmyBImJiXjllVd0ei9L9TtNWHAYoKWlBX/6059w8+ZNLFmyRHHgl1eiLi4uGpdzdnZWaWeov//976isrMT69es1/tGhq47aXmXMTpU+vzJbOrtp06YhOzsbFRUVqK2tRVFREV544QUcO3YMUVFRuHbtmk7vI98O+XaZa3uVMTtV8n43ffp0ndZryfx+/vlnAMD69evh7OyMwsJC1NTUYM+ePfDz88O6devw8ccf6/RetrbPs8bs9D2zZunv7r0yMjLQ2tqKqVOn6nUMsbW+p4mls+tMx9vZs2dj06ZNaGpqwqZNm7BmzRoUFBQgODgYsbGxOl8eaan/15oYd0GnDWptbcWrr76KQ4cOYcaMGXqdEjaFo0ePYu3atVi4cKFOdyjQdKeGkSNH6nXdu6kwO1VVVVU4dOgQvLy88PTTT7fZ1tLZAcDChQtV/jsoKAgbN24EAOzYsQOffPKJ4vaqmu6M1L9/f0RGRnbMxiphdqoaGhqQnZ0NsViscucVbSydX2trKwBAJBIhIyMDffr0AQCMGDECW7ZswciRI7Fu3TrMnDkTAPd5964fsJ7s9Nnnybff0t/de7cnIyMDdnZ2eOmll9Tms++1vT2WzK6zHW9XrFiB9PR0LFq0CHFxcXBxccHJkyexaNEiREZGYuvWrZgwYQIA6+p3bWHBoYfW1lbMnj0bX3zxBeLi4rB69WqV+fJKsb6+XuPy7f062Z5bt24hKSkJjz/+OObOnavTMnl5edi2bZva9FGjRpl9e5UxO3WfffYZBEHASy+9BDs7O63tLJ1dexISErBjxw4cOXJE8UdzcXExVqxYodJu6tSpiIyMbPcXlfup37XHEtnt2rUL169fx/Tp0yEWi9vcPmvIT77sgAEDFH8wywUGBsLb2xtVVVWoq6uDq6sr93ka1mEt2em6zwOsI797HTx4EDU1NRg9ejS8vb3V5rPvaWfp7DrT8fbgwYNIS0vDq6++qvL3yvDhw7F9+3YMGDAAb7/9tqLgsJZ+1x4WHDqSV7zbt29HbGwsNmzYAHt71SvS5Pe+1zYYTz793ucL6KqxsVFxnV3v3r01thk7diyAO1+uyMhIbNiwARs2bNDY1tvbG/b29mbbXjlmp+727dvYtm0bunTp0uYzGKwhu/Y89NBDAO48LEjurbfewltvvaWxvZOTE9zc3HDu3Dncvn1b7dT6/dTv2mOJ7HQdtGkt+fXr1w+A9ksC5NNv3LgBANznKbGm7HTd5wHWk9+92vvusO9pZ8nsOtvxNj8/HwA0nqGQSCTo168fysrK0NjYCLFYbBX9ThcsOHSg3Amjo6OxceNGjdcf+vr6ok+fPjhy5AiamprUbpd25MgReHl5wcPDw6Dt6Nq1q9Zrrg8dOoTKyko8++yz6NWrl9rdCDTp3r07Bg0ahNLSUpw/f17tdmkHDhyAk5MTnnrqKYO2F2B22rLbt28fLl68iPHjx8Pd3V1jG2vJrj3yuy3pkptcSEgIMjMz8c0336jd2rWgoADAncs+DMXsNGf33//+F8eOHUNAQECbt4C2pvzkB93y8nK1eS0tLaiqqoKTk5PKg6u0saV9HmBd2emyzwOsKz9lv/zyC/bs2YMePXoYdHmjrfU9ZZbOrrMdb5ubmwH8PgbrXlevXoW9vb3iDlpt6Yh+pysOGm+H/PTa9u3bMXHiRHz44YdaBzvZ2dlh+vTpaGxsxHvvvacy77333kNjYyNmzJhh8LZ0794da9eu1fgaMmQIAGDevHlYu3YtgoKCdHpP+fYsW7YMgvD7I1k2b96Ms2fPYvLkye3e11obZqc9O/ngNU3XsgLWlR1w5w8W5V/hlacvWbIEABAbG6vz+8m355133lHsXIE7v+wUFxcjNDRUrz/ClTE77dm11+8A68uvb9++CA0NRVVVleJXUrnVq1ejvr4eEREROg+itJV9HmBd2XXGvqds+/btaG5uRlxcHLp27WrQe9hS31Nm6ew62/FWfsvzDz74QO1SqE2bNuHChQsYMmSIzlmas9/pgw/+a0daWhpWrFgBsViMWbNmaeyEERERij9Sm5qaMH78ePzwww8IDQ3Fk08+iRMnTigeeZ+Xl6f2P1b54TN5eXloaGjA1KlTFdPmzp2LRx99tM3tTEpKMujhdZoeeV9VVYXc3Fx4enqioKBA7devt99+G1evXgVw51rDixcvIioqSlHpx8fHY/jw4cxOQ3YAcPnyZQQGBqJnz5748ccfNR7srS27tLQ0fPDBBxgxYgSkUikeeOABnD59Gvn5+WhpacG8efPwt7/9TefsAOD111/H1q1bERAQgHHjxuHSpUvIysqCk5MT8vPz4efnp9J+9erVil9qS0tLcfr0aYSFheHhhx9W5BEZGcnsNGQH3PnV7LHHHkNjYyN++ukn9OzZU+N7W1t+wJ1bO44bNw5XrlzB+PHjFZcUFBUVQSqVYv/+/ZBIJDplZ2v7PEtnB+i2zwOss+/JjRgxAj/++CNKSkoUt0jVl631PUtnB3TO4+3t27fx3HPP4dChQ+jduzeeffZZuLi44MSJEygqKkL37t2xe/duDBo0yGzZ6drv9GLMY8pt4TV16lQBQJuv9evXqyxz7tw5ISkpSfDw8BAcHR0FDw8PYc6cOYrH2t/7au/9c3Nzdd7O/Px8vT+jTCYTFi5cKPTt21cQiUSCRCIR4uPjhfLyco3tpVKpTnkwO83LLF26VAAgJCcnd5p+t3v3bmHSpEmCr6+v4OzsLDg4OAgSiUSYMGGCsGvXLoO+W7/88ovw7rvvCgEBAULXrl2Fnj17CtHR0cL333+vsX1ISEib2/vmm28yOy3Z1dXVCZs3bxYACJMmTdLp+2At+clfP/zwg/Diiy8KEolEsY4//vGPQkVFhdm/t519n2fJ7OrqdNvnWXN+BQUFAgBh0KBBBn1fbbnvWTI7XfueNWYnk8mElJQUISgoSHjggQcEBwcHwd3dXYiLixOOHDliNf1OnxfPcBARERERkdlwDAcREREREZkNCw4iIiIiIjIbFhxERERERGQ2LDiIiIiIiMhsWHAQEREREZHZsOAgIiIiIiKzYcFBRERERERmw4KDiIiIiIjMhgUHERERERGZDQsOIiIiIiIyGxYcRERERERkNiw4iIiIiIjIbP4fFPR7Y1F1h7sAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Check Distribution:** *Goal:understand the distribution of Profit and Sales.*"
      ],
      "metadata": {
        "id": "GvMKk6DFL4nO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_hist=df[['Sales','Profit']]"
      ],
      "metadata": {
        "id": "a4mlsa0oGhoI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_hist.head()"
      ],
      "metadata": {
        "id": "UlftcJkzNNVF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "84c1f03e-0229-4502-f2d7-cf5334efc4f2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Sales    Profit\n",
              "0  261.9600   41.9136\n",
              "1  731.9400  219.5820\n",
              "2   14.6200    6.8714\n",
              "3  957.5775 -383.0310\n",
              "4   22.3680    2.5164"
            ],
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              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-8e20ab8f-c6a8-4c7c-822e-2681e2eff607 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-8e20ab8f-c6a8-4c7c-822e-2681e2eff607');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-1bd47b23-a0bb-42b2-b8f0-ffa816ccc380\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1bd47b23-a0bb-42b2-b8f0-ffa816ccc380')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-1bd47b23-a0bb-42b2-b8f0-ffa816ccc380 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_hist",
              "summary": "{\n  \"name\": \"df_hist\",\n  \"rows\": 9994,\n  \"fields\": [\n    {\n      \"column\": \"Sales\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 623.2451005086818,\n        \"min\": 0.444,\n        \"max\": 22638.48,\n        \"num_unique_values\": 5825,\n        \"samples\": [\n          2624.985,\n          84.416,\n          30.28\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Profit\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 234.26010769095757,\n        \"min\": -6599.978,\n        \"max\": 8399.976,\n        \"num_unique_values\": 7287,\n        \"samples\": [\n          -183.6324,\n          1.926,\n          144.3546\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_hist = df_hist[df_hist['Sales'] <= 2000]\n",
        "df_hist = df_hist[df_hist['Profit'] <= 2000]\n",
        "df_hist = df_hist[df_hist['Profit'] >= -200]"
      ],
      "metadata": {
        "id": "3Ymr5IEiSFIe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=[5,5])\n",
        "plt.suptitle(\"Checking Distribution and Outliers \\nfor Sales and Profit\", size=9)\n",
        "plt.subplot(2,1,1)\n",
        "plt.hist(df_hist['Sales'], bins=200, color='blue')\n",
        "plt.xlim(0,650)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "qhrg41GoNgMG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 294
        },
        "outputId": "194960ba-8fb2-4ab1-af1d-450bc41ad430"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Boxplot of  for Sales\n",
        "plt.subplot(2,3,3)\n",
        "sns.boxplot(df_hist['Sales'])"
      ],
      "metadata": {
        "id": "XGnjILenQOeY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 234
        },
        "outputId": "0f971461-39c6-4a20-db02-7e81b58ddc3d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: ylabel='Sales'>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# KDEPlot for Sales\n",
        "plt.subplot(2,3,3)\n",
        "sns.kdeplot(x=df_hist['Sales'], color='blue')"
      ],
      "metadata": {
        "id": "1fRMxINNRyUT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "outputId": "0ecfeb0e-5f9c-4cac-e04d-a421bf1daf13"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Sales', ylabel='Density'>"
            ]
          },
          "metadata": {},
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_hist['Sales'].describe()"
      ],
      "metadata": {
        "id": "NdYWVz8QP-sX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 335
        },
        "outputId": "7c7d9cdc-f174-486c-f862-0d5c43036d76"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    9718.000000\n",
              "mean      169.878281\n",
              "std       284.298010\n",
              "min         0.444000\n",
              "25%        16.606500\n",
              "50%        50.226000\n",
              "75%       191.073750\n",
              "max      1999.960000\n",
              "Name: Sales, dtype: float64"
            ],
            "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>Sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>9718.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>169.878281</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>284.298010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.444000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>16.606500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>50.226000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>191.073750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1999.960000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> float64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Histogram for Profit\n",
        "plt.subplot(2,3,4)\n",
        "plt.hist(df_hist['Profit'], bins=200, color='#30475E')\n",
        "plt.xlim(-250,300)\n",
        "\n",
        "# Boxplot of  for Profit\n",
        "plt.subplot(2,3,5)\n",
        "sns.boxplot(df_hist['Profit'], color='#30475E')\n",
        "\n",
        "# KDEPlot for Profit\n",
        "plt.subplot(2,3,6)\n",
        "sns.kdeplot(x=df_hist['Profit'], color='#30475E')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "wbMalnr2R_ON",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "outputId": "2868c79f-a003-4170-fce6-0fdc415f4b41"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_hist['Profit'].describe()"
      ],
      "metadata": {
        "id": "YWL3DcTBTeKL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 335
        },
        "outputId": "9ad3f294-f340-406c-e05e-3eb4c640cf86"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    9718.000000\n",
              "mean       26.316213\n",
              "std        75.912677\n",
              "min      -199.770000\n",
              "25%         1.962225\n",
              "50%         8.709500\n",
              "75%        28.706400\n",
              "max       899.982000\n",
              "Name: Profit, dtype: float64"
            ],
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>9718.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>26.316213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>75.912677</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-199.770000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.962225</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>8.709500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>28.706400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>899.982000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> float64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Relationship between numerical columns**:*Goal: understand how the Sales impact Profit for different Customer Segments.*"
      ],
      "metadata": {
        "id": "p8vCnZhoWB32"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_scatter = df[['Sales','Profit','Segment']]\n",
        "\n",
        "# Visualizing the ScatterPlot\n",
        "plt.figure(figsize=[8,5])\n",
        "# Profit in the Y axis, and Sales in the X. Hue will classify the dots according to Segment.\n",
        "# The size of the dots are according to the volumen of \"Sales\".\n",
        "sns.scatterplot(x=df_scatter['Sales'], y=df_scatter['Profit'], hue=df_scatter['Segment'], palette=['#a86f8f','#65856d','#d18b00'], size=df_scatter[\"Sales\"], sizes=(100,1000), legend='auto')\n",
        "plt.title(\"Sales vs Profit Across Different Customer Segments\", size=10, pad=10)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "c9yFfFaUStgn",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "outputId": "4ec69749-02c5-4110-9255-24d491c39109"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "2XO11kMWYXTk"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}