01w_bigdata_basic.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyM/leLz2LTyxmr+SVtZyC8t",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ai7dnn/2024-1-BDA/blob/main/01w_bigdata_basic.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 빅데이터분석프로그래밍\n",
        "## 01주 2024-03"
      ],
      "metadata": {
        "id": "pv0X9EaT3Aak"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import sys\n",
        "sys.version"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "gTYsevur2_5-",
        "outputId": "fae828ea-2953-41ee-b1b5-c79a48ca8571"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0]'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import site\n",
        "site.getsitepackages()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BUiw40B-3Xh0",
        "outputId": "3981a5cf-c4ce-4db8-8e18-74d15b5ac246"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['/usr/local/lib/python3.10/dist-packages',\n",
              " '/usr/lib/python3/dist-packages',\n",
              " '/usr/lib/python3.10/dist-packages']"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "print(np.__version__)\n",
        "print(pd.__version__)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d3UcHYav3dW_",
        "outputId": "189f76d1-0259-4b92-8550-096b4bad768d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1.23.5\n",
            "1.5.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 코랩에서 한글 처리"
      ],
      "metadata": {
        "id": "qZmAHerv2eug"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BQ3y3ZJO1OfY",
        "outputId": "3883bcf5-59d8-48c6-c52e-6af42b5abcdc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting koreanize-matplotlib\n",
            "  Downloading koreanize_matplotlib-0.1.1-py3-none-any.whl (7.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.9/7.9 MB\u001b[0m \u001b[31m16.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from koreanize-matplotlib) (3.7.1)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->koreanize-matplotlib) (1.2.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->koreanize-matplotlib) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->koreanize-matplotlib) (4.47.2)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->koreanize-matplotlib) (1.4.5)\n",
            "Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.10/dist-packages (from matplotlib->koreanize-matplotlib) (1.23.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->koreanize-matplotlib) (23.2)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->koreanize-matplotlib) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->koreanize-matplotlib) (3.1.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib->koreanize-matplotlib) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib->koreanize-matplotlib) (1.16.0)\n",
            "Installing collected packages: koreanize-matplotlib\n",
            "Successfully installed koreanize-matplotlib-0.1.1\n"
          ]
        }
      ],
      "source": [
        "!pip install koreanize-matplotlib"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%config InlineBackend.figure_format = 'retina'"
      ],
      "metadata": {
        "id": "FBxd0LlL2roF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import koreanize_matplotlib\n",
        "\n",
        "plt.plot([-1, 0, 1, 2])\n",
        "plt.title('그래프 제목', fontweight=\"bold\")\n",
        "plt.xlabel('간단한 그래프')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "FU9FaWCp4AMG",
        "outputId": "b17b6309-2218-45fb-c9d0-2357a8da3f31"
      },
      "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": {
            "image/png": {
              "width": 551,
              "height": 451
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(range(-20, 80), np.random.randn(100).cumsum(), 'r--')\n",
        "plt.title('한글 점검');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "45KoEA_A4XIz",
        "outputId": "a9501bfc-8ead-43a6-bca2-8f7f74c90948"
      },
      "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": {
            "image/png": {
              "width": 542,
              "height": 433
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x = np.random.randint(1, 100, 50)\n",
        "y = np.random.randint(50, 80, 50)\n",
        "s = np.random.randint(50, 300, 50)\n",
        "\n",
        "plt.scatter(x, y, s=s, alpha=.4)\n",
        "plt.title('산점도');"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "bdGw5i5F4XmU",
        "outputId": "0e53a7d1-fc18-48d7-ae28-b50b75761ddf"
      },
      "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": {
            "image/png": {
              "width": 551,
              "height": 433
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 데이터분석을 위한 샘플 데이터"
      ],
      "metadata": {
        "id": "_1O0OqNG5yOW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "8g5iM9oh5fHd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "titanic = sns.load_dataset('titanic')\n",
        "titanic"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 443
        },
        "id": "g0JxyVOi42t-",
        "outputId": "a0e2f3e2-0463-4d5b-f2cc-fc57869c5ff6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     survived  pclass     sex   age  sibsp  parch     fare embarked   class  \\\n",
              "0           0       3    male  22.0      1      0   7.2500        S   Third   \n",
              "1           1       1  female  38.0      1      0  71.2833        C   First   \n",
              "2           1       3  female  26.0      0      0   7.9250        S   Third   \n",
              "3           1       1  female  35.0      1      0  53.1000        S   First   \n",
              "4           0       3    male  35.0      0      0   8.0500        S   Third   \n",
              "..        ...     ...     ...   ...    ...    ...      ...      ...     ...   \n",
              "886         0       2    male  27.0      0      0  13.0000        S  Second   \n",
              "887         1       1  female  19.0      0      0  30.0000        S   First   \n",
              "888         0       3  female   NaN      1      2  23.4500        S   Third   \n",
              "889         1       1    male  26.0      0      0  30.0000        C   First   \n",
              "890         0       3    male  32.0      0      0   7.7500        Q   Third   \n",
              "\n",
              "       who  adult_male deck  embark_town alive  alone  \n",
              "0      man        True  NaN  Southampton    no  False  \n",
              "1    woman       False    C    Cherbourg   yes  False  \n",
              "2    woman       False  NaN  Southampton   yes   True  \n",
              "3    woman       False    C  Southampton   yes  False  \n",
              "4      man        True  NaN  Southampton    no   True  \n",
              "..     ...         ...  ...          ...   ...    ...  \n",
              "886    man        True  NaN  Southampton    no   True  \n",
              "887  woman       False    B  Southampton   yes   True  \n",
              "888  woman       False  NaN  Southampton    no  False  \n",
              "889    man        True    C    Cherbourg   yes   True  \n",
              "890    man        True  NaN   Queenstown    no   True  \n",
              "\n",
              "[891 rows x 15 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-174a528e-0436-4c44-b4c4-c8c5257f6313\" 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>survived</th>\n",
              "      <th>pclass</th>\n",
              "      <th>sex</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>fare</th>\n",
              "      <th>embarked</th>\n",
              "      <th>class</th>\n",
              "      <th>who</th>\n",
              "      <th>adult_male</th>\n",
              "      <th>deck</th>\n",
              "      <th>embark_town</th>\n",
              "      <th>alive</th>\n",
              "      <th>alone</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>male</td>\n",
              "      <td>22.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7.2500</td>\n",
              "      <td>S</td>\n",
              "      <td>Third</td>\n",
              "      <td>man</td>\n",
              "      <td>True</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>no</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>female</td>\n",
              "      <td>38.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>71.2833</td>\n",
              "      <td>C</td>\n",
              "      <td>First</td>\n",
              "      <td>woman</td>\n",
              "      <td>False</td>\n",
              "      <td>C</td>\n",
              "      <td>Cherbourg</td>\n",
              "      <td>yes</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>female</td>\n",
              "      <td>26.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7.9250</td>\n",
              "      <td>S</td>\n",
              "      <td>Third</td>\n",
              "      <td>woman</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>yes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>female</td>\n",
              "      <td>35.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>53.1000</td>\n",
              "      <td>S</td>\n",
              "      <td>First</td>\n",
              "      <td>woman</td>\n",
              "      <td>False</td>\n",
              "      <td>C</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>yes</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>male</td>\n",
              "      <td>35.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>8.0500</td>\n",
              "      <td>S</td>\n",
              "      <td>Third</td>\n",
              "      <td>man</td>\n",
              "      <td>True</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>no</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>886</th>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>male</td>\n",
              "      <td>27.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>13.0000</td>\n",
              "      <td>S</td>\n",
              "      <td>Second</td>\n",
              "      <td>man</td>\n",
              "      <td>True</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>no</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>887</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>female</td>\n",
              "      <td>19.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>S</td>\n",
              "      <td>First</td>\n",
              "      <td>woman</td>\n",
              "      <td>False</td>\n",
              "      <td>B</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>yes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>888</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>female</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>23.4500</td>\n",
              "      <td>S</td>\n",
              "      <td>Third</td>\n",
              "      <td>woman</td>\n",
              "      <td>False</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Southampton</td>\n",
              "      <td>no</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>889</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>male</td>\n",
              "      <td>26.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>C</td>\n",
              "      <td>First</td>\n",
              "      <td>man</td>\n",
              "      <td>True</td>\n",
              "      <td>C</td>\n",
              "      <td>Cherbourg</td>\n",
              "      <td>yes</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>890</th>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>male</td>\n",
              "      <td>32.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7.7500</td>\n",
              "      <td>Q</td>\n",
              "      <td>Third</td>\n",
              "      <td>man</td>\n",
              "      <td>True</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Queenstown</td>\n",
              "      <td>no</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>891 rows × 15 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-174a528e-0436-4c44-b4c4-c8c5257f6313')\"\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",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </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-174a528e-0436-4c44-b4c4-c8c5257f6313 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-174a528e-0436-4c44-b4c4-c8c5257f6313');\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-9d1bbf88-b2de-431c-8ece-32a626af67fe\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9d1bbf88-b2de-431c-8ece-32a626af67fe')\"\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-9d1bbf88-b2de-431c-8ece-32a626af67fe button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_68b88666-1668-4e47-8a18-b194286fe03e\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('titanic')\"\n",
              "            title=\"Generate code using this dataframe.\"\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",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_68b88666-1668-4e47-8a18-b194286fe03e button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('titanic');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "titanic.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OXS-0Pam6LoV",
        "outputId": "d03e7e11-2d0f-4cb9-dfff-8ea274ee7e7f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 891 entries, 0 to 890\n",
            "Data columns (total 15 columns):\n",
            " #   Column       Non-Null Count  Dtype   \n",
            "---  ------       --------------  -----   \n",
            " 0   survived     891 non-null    int64   \n",
            " 1   pclass       891 non-null    int64   \n",
            " 2   sex          891 non-null    object  \n",
            " 3   age          714 non-null    float64 \n",
            " 4   sibsp        891 non-null    int64   \n",
            " 5   parch        891 non-null    int64   \n",
            " 6   fare         891 non-null    float64 \n",
            " 7   embarked     889 non-null    object  \n",
            " 8   class        891 non-null    category\n",
            " 9   who          891 non-null    object  \n",
            " 10  adult_male   891 non-null    bool    \n",
            " 11  deck         203 non-null    category\n",
            " 12  embark_town  889 non-null    object  \n",
            " 13  alive        891 non-null    object  \n",
            " 14  alone        891 non-null    bool    \n",
            "dtypes: bool(2), category(2), float64(2), int64(4), object(5)\n",
            "memory usage: 80.7+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "titanic.groupby('sex').count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "id": "n0pBG4sL6Onb",
        "outputId": "8a19d034-54fa-4d70-92cf-3bab2bc1dee5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        survived  pclass  age  sibsp  parch  fare  embarked  class  who  \\\n",
              "sex                                                                       \n",
              "female       314     314  261    314    314   314       312    314  314   \n",
              "male         577     577  453    577    577   577       577    577  577   \n",
              "\n",
              "        adult_male  deck  embark_town  alive  alone  \n",
              "sex                                                  \n",
              "female         314    97          312    314    314  \n",
              "male           577   106          577    577    577  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7fccbb2c-3d69-4551-8601-765afb1acc1b\" 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>survived</th>\n",
              "      <th>pclass</th>\n",
              "      <th>age</th>\n",
              "      <th>sibsp</th>\n",
              "      <th>parch</th>\n",
              "      <th>fare</th>\n",
              "      <th>embarked</th>\n",
              "      <th>class</th>\n",
              "      <th>who</th>\n",
              "      <th>adult_male</th>\n",
              "      <th>deck</th>\n",
              "      <th>embark_town</th>\n",
              "      <th>alive</th>\n",
              "      <th>alone</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>female</th>\n",
              "      <td>314</td>\n",
              "      <td>314</td>\n",
              "      <td>261</td>\n",
              "      <td>314</td>\n",
              "      <td>314</td>\n",
              "      <td>314</td>\n",
              "      <td>312</td>\n",
              "      <td>314</td>\n",
              "      <td>314</td>\n",
              "      <td>314</td>\n",
              "      <td>97</td>\n",
              "      <td>312</td>\n",
              "      <td>314</td>\n",
              "      <td>314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>male</th>\n",
              "      <td>577</td>\n",
              "      <td>577</td>\n",
              "      <td>453</td>\n",
              "      <td>577</td>\n",
              "      <td>577</td>\n",
              "      <td>577</td>\n",
              "      <td>577</td>\n",
              "      <td>577</td>\n",
              "      <td>577</td>\n",
              "      <td>577</td>\n",
              "      <td>106</td>\n",
              "      <td>577</td>\n",
              "      <td>577</td>\n",
              "      <td>577</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-7fccbb2c-3d69-4551-8601-765afb1acc1b')\"\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",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </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-7fccbb2c-3d69-4551-8601-765afb1acc1b 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-7fccbb2c-3d69-4551-8601-765afb1acc1b');\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-4312d3f2-6fa6-401b-8ede-48158f795252\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4312d3f2-6fa6-401b-8ede-48158f795252')\"\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-4312d3f2-6fa6-401b-8ede-48158f795252 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.barplot(x=\"sex\", y=\"survived\", data=titanic);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "PVXz923o6t2K",
        "outputId": "1c43cbde-a095-4aa2-9117-0ed392667f1a"
      },
      "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": {
            "image/png": {
              "width": 565,
              "height": 430
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.barplot(x=\"pclass\", y=\"survived\", data=titanic);"
      ],
      "metadata": {
        "id": "VQ7ghRAI-ZQP",
        "outputId": "9d9dd093-9620-4bcb-868a-c4206f7fecaf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABGoAAANdCAYAAADMb5qdAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAB7CAAAewgFu0HU+AABa+UlEQVR4nO3debRXdb3/8dcXEA+DQAwieFTAxFJARQaNTG0SATWcIBWHjHLIq3XD9FaWt65RSbMpUFlkpRhqKCI2OCFkDkiYiAZZDAdFAfEAisL5/dGCe/mJyHA4Z8P38ViLlZ392Z/9/lrrrHy29/6WampqagIAAABAvWtQ3wMAAAAA8G9CDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABREo/oegNr32muvZdasWUmSdu3apVEj/zEDAABAbXvzzTezZMmSJEn37t1TUVGx3Xv6J/hd0KxZs9KnT5/6HgMAAADKxl/+8pf07t17u/fx6BMAAABAQbijZhfUrl27DX/9l7/8JR06dKjHaQAAAGDXVFVVteGJlv/7z+LbQ6jZBf3fd9J06NAhlZWV9TgNAAAA7Ppq6/2wHn0CAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCKOtQ88ADD2TIkCHp3LlzKioqUllZmQEDBuT222/f5j0HDBiQUqm0xX+6d+9ei58IAAAA2Jk1qu8B6suVV16ZkSNHJkl69eqVww8/PIsXL86UKVMyefLknHXWWfnpT3+axo0bb9W+H/nIR9K6det3XLds2bLcfffdWbt27TbNDwAAAOx6yjLU3HDDDRk5cmQ6deqUCRMmpGfPnhuOzZ07N6eeempuuummdOjQId/61re2au/PfvazW7Tu6quvzt13352hQ4du1f4AAADArqtUU1NTU99D1KVly5Zl3333zZo1a/LYY49t8tGjRYsWpXv37lm+fHmeeuqpvPe9763VGV5//fXsu+++eeWVVzJ//vy0a9euVvdfsGBB9tlnnyTJ/PnzU1lZWav7AwAAADvmn7/L7h0148aNS3V1dYYOHfq274fp2LFjLrrooqxbty5jx46t9Rl++ctf5sUXX8wZZ5xR65EGAAAA2HmVXaiZNGlSkuT000/f7Lr1x+++++5avX5NTU2++93vJkkuu+yyWt0bAAAA2LmV3Ttqpk+fniTp16/fZtd169YtLVu2zJw5c7J06dItekHwlrjnnnvy9NNP59hjj02PHj22aY8FCxZs9nhVVdU27QsAAADUr7IKNVVVVamurk6bNm3SqlWrza4tlUrp0qVLZsyYkeeeey59+/atlRm+853vJNm+u2nWP/8GAAAA7FrK6tGnF154IUmy5557btH69u3bJ0kWL15cK9f/61//mj/84Q9597vfnUGDBtXKngAAAMCuo6zuqFm5cmWSpGnTplu0fv269edtr/V301xyySVp0GDbG9n8+fM3e7yqqip9+vTZ5v2htqxduzZLlizZ5LF27dqlYcOGdTwRAABAsZVVqCmVSlu1vja/ubyqqiq/+c1v0qJFi5x33nnbtZev22ZnsWTJkpx55pmbPParX/0qe+21Vx1PBAAAUGxl9ehTs2bNkiSrVq3aovWrV69OkjRv3ny7r/3DH/4wa9asyfnnn5899thju/cDAAAAdj1lFWrWf3PT+nfVvJP176Zp06bNdl131apVGT16dBo0aJBLLrlku/YCAAAAdl1lFWoqKyvTtGnTLF26NMuXL9/s2pqamsybNy9J0rVr1+267o033pilS5fmpJNOSufOnbdrLwAAAGDXVVahplQq5ZBDDkmSTJ06dbNrZ82alRUrVqRjx45p167dNl9z3bp1+d73vpdk+76SGwAAANj1lVWoSbLha7HHjx+/2XW33nrrRuu31cSJE/P3v/89PXv2zAc+8IHt2gsAAADYtZVdqDnnnHNSUVGRm2++ObNmzdrkmkWLFuW6665LkgwfPny7rrf+K7kvvfTS7doHAAAA2PWVXajZe++9c8UVV+SNN97IiSeemCeeeGKj43Pnzs3AgQOzbNmyDBs2LL169drmaz366KN56KGHstdee2Xo0KHbOzoAAACwi2tU3wPUh6uuuioLFy7M2LFjc/jhh6d3797Zb7/9snjx4kyfPj1r167NcccdlzFjxmzy/BEjRmTatGkZPXp0unXr9rbXWX83zYUXXpjGjRvvkM8CAAAA7DrK7o6a5N8vFR4zZkwmT56cwYMHZ+HChZk4cWKeffbZHHvssRk3blwmT56cioqKt5z70ksv5dprr90Qat7Oyy+/nN/+9rd517velQsvvHBHfhwAAABgF1GWd9Ss179///Tv33+rzmnTpk0GDRqUadOmZfDgwZtd98Ybb2zviAAAAEAZKetQsy1KpVLuvPPO+h4DAAAA2AWV5aNPAAAAAEUk1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAF0ai+B2DXdviIcfU9AvWowevVafE2x0645ras2715nc5DsTz+7bPrewQAACgcd9QAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABREWYeaBx54IEOGDEnnzp1TUVGRysrKDBgwILfffnutXWPt2rW544478olPfCIHH3xw2rZtm8aNG2fPPffMUUcdlZ/97Ge1di0AAABg51a2oebKK6/MMccck/Hjx6dt27YZNGhQOnXqlClTpuTkk0/OsGHDsmbNmu26xp///OccfvjhGTx4cH7+85+nUaNGOeKII/Kxj30s3bp1yzPPPJM77rijdj4QAAAAsNNrVN8D1IcbbrghI0eOTKdOnTJhwoT07Nlzw7G5c+fm1FNPzU033ZQOHTrkW9/61jZd449//GNOOOGEvPnmm7n88stz2WWXpUOHDhutqampyauvvrpdnwUAAADYdZTdHTXLli3LiBEj0rhx40ycOHGjSJMk+++/fyZNmpTWrVtn1KhRmT179lZfY+HChfnYxz6WtWvX5q677so3v/nNt0SaJCmVSmnRosU2fxYAAABg11J2oWbcuHGprq7O0KFD0717902u6dixYy666KKsW7cuY8eO3eprfOELX0h1dXVGjhyZj370o9s7MgAAAFAmyi7UTJo0KUly+umnb3bd+uN33333Vu2/dOnSjB8/Ph06dMgll1yybUMCAAAAZans3lEzffr0JEm/fv02u65bt25p2bJl5syZk6VLl6Z169ZbtP/EiRPzxhtv5NRTT02jRjvmb++CBQs2e7yqqmqHXBcAAADYscoq1FRVVaW6ujpt2rRJq1atNru2VCqlS5cumTFjRp577rn07dt3i67x2GOPJcmG9XfeeWd+8IMfZNasWVm+fHk6duyYD3zgA7n44ovTu3fvbfoc++yzzzadBwAAABRbWT369MILLyRJ9txzzy1a3759+yTJ4sWLt/gaTz/99IZzTz755Jx44ol57rnncsQRR2TgwIHZfffd84tf/CJ9+/bNl7/85a38BAAAAMCurKzuqFm5cmWSpGnTplu0fv269edtiaVLlyZJvvjFL+af//xnJk6cmBNOOGGjNffee2/OOOOMfP3rX0/79u3zmc98Zov3T5L58+dv9nhVVVX69OmzVXsCAAAA9a+sQk2pVNqq9TU1NVt9jerq6iTJjBkz8thjj6VHjx5vWfPRj340v/nNb/LRj340X/7yl/PJT34yFRUVW3yNysrKrZ4LAAAAKL6yevSpWbNmSZJVq1Zt0frVq1cnSZo3b77F19htt92SJB//+Mc3GWnW+8hHPpKePXtm+fLleeCBB7Z4fwAAAGDXVVahZv03N61/V807Wf9umjZt2mzxNfbYY48kyTHHHPOOa4888sgkybPPPrvF+wMAAAC7rrIKNZWVlWnatGmWLl2a5cuXb3ZtTU1N5s2blyTp2rXrFl9j3333TbJld+G0bNkyyf8+LgUAAACUt7IKNaVSKYccckiSZOrUqZtdO2vWrKxYsSIdO3ZMu3bttvga3bp1S5L885//fMe1L774YpJs1f4AAADArqusQk2SDBo0KEkyfvz4za679dZbN1q/pT760Y8mSe64447Nrlu3bl3++Mc/JvnfR6AAAACA8lZ2oeacc85JRUVFbr755syaNWuTaxYtWpTrrrsuSTJ8+PCt2v/II49M165d8/DDD+eWW25523WjR4/OP/7xjxx55JE5+OCDt+oaAAAAwK6p7ELN3nvvnSuuuCJvvPFGTjzxxDzxxBMbHZ87d24GDhyYZcuWZdiwYenVq9dW7V8qlTJq1KgkyXnnnfeWWLN27dp873vfy3/8x3+kSZMm+fGPf7x9HwgAAADYZZRdqEmSq666KsOHD8/zzz+fww8/PH369Mlpp52Wo446KgceeGCefPLJHHfccRkzZswmzx8xYkT69euXp556apPHBw0alFGjRuX111/P0KFDc8ABB+TUU0/NCSeckA4dOuSzn/1smjdvnokTJ+bQQw/dgZ8UAAAA2JmUZagplUoZM2ZMJk+enMGDB2fhwoWZOHFinn322Rx77LEZN25cJk+enIqKirec+9JLL+Xaa6/NtGnTMnr06Le9xuc+97k88sgjOfvss/PGG2/krrvuyoMPPpjKysp8+ctfznPPPZcPf/jDO/JjAgAAADuZRvU9QH3q379/+vfvv1XntGnTJoMGDcq0adMyePDgza7t1atXfvGLX2zPiAAAAEAZKetQsy1KpVLuvPPO+h4DAAAA2AWV5aNPAAAAAEUk1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAXRqL4HAHZd6xo3zYqDT3nbYwAAAGxMqAF2nFKDrNu9eX1PAQAAsNPw6BMAAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQjep7AACAcrZ27dosWbJkk8fatWuXhg0b1vFEAEB9EmoAAOrRkiVLcuaZZ27y2K9+9avstddedTwRAFCfPPoEAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABVHWoeaBBx7IkCFD0rlz51RUVKSysjIDBgzI7bffvl37fuYzn0mpVHrHP40aNcqSJUtq6dMAAAAAO7tG9T1AfbnyyiszcuTIJEmvXr1y+OGHZ/HixZkyZUomT56cs846Kz/96U/TuHHjrd67uro6SfLhD3847du3f9t1jRo1StOmTbftAwAAAAC7nLIMNTfccENGjhyZTp06ZcKECenZs+eGY3Pnzs2pp56am266KR06dMi3vvWtbb7OF7/4xRxzzDG1MDEAAABQDsru0adly5ZlxIgRady4cSZOnLhRpEmS/fffP5MmTUrr1q0zatSozJ49u54mBQAAAMpN2YWacePGpbq6OkOHDk337t03uaZjx4656KKLsm7duowdO7aOJwQAAADKVdmFmkmTJiVJTj/99M2uW3/87rvv3uEzAQAAACRl+I6a6dOnJ0n69eu32XXdunVLy5YtM2fOnCxdujStW7eui/G2yIIFCzZ7vKqqqo4mAQAAAGpTWYWaqqqqVFdXp02bNmnVqtVm15ZKpXTp0iUzZszIc889l759+2719Z5++uk8+eSTef755/PKK6+kRYsWOfjggzNw4MDsvffe2/gpkn322WebzwUAAACKq6xCzQsvvJAk2XPPPbdo/fqv1l68ePFWXadUKiVJLr744k0e32233XLhhRfmm9/8ZioqKrZqbwAAAGDXVVahZuXKlUmSpk2bbtH69evWn7elPvGJT6Rv377p3bt39ttvv7Rs2TJr1qzJP//5z9x777259tpr84Mf/CB///vfc+edd6ZBg617VdD8+fM3e7yqqip9+vTZqj0BAACA+ldWoWb9nS5bqqamZpuuc9RRR+Woo47a6Ge77bZbDjrooBx00EE5++yz8/73vz933313fvGLX+S8887bqv0rKyu3aS4AAACg2MrqW5+aNWuWJFm1atUWrV+9enWSpHnz5rU6R+vWrfPd7343SXLjjTfW6t4AAADAzqusQs36b25a/66ad7L+3TRt2rSp9Vk++MEPZvfdd8+sWbNqfW8AAABg51RWoaaysjJNmzbN0qVLs3z58s2urampybx585IkXbt2rfVZdtttt7Rp02bDXTsAAAAAZRVqSqVSDjnkkCTJ1KlTN7t21qxZWbFiRTp27Jh27drV+izr1q3LsmXLNnyzFAAAAEBZhZokGTRoUJJk/Pjxm1136623brS+tj344INZvXp1jjzyyB2yPwAAALDzKbtQc84556SioiI333zz274fZtGiRbnuuuuSJMOHD6/1GV599dV89rOfTZKcf/75tb4/AAAAsHMqu1Cz995754orrsgbb7yRE088MU888cRGx+fOnZuBAwdm2bJlGTZsWHr16rXV1/jpT3+64UXE/7/77rsv73vf+/Lkk0/m7LPPzkc+8pFt+hwAAADArqdRfQ9QH6666qosXLgwY8eOzeGHH57evXtnv/32y+LFizN9+vSsXbs2xx13XMaMGbPJ80eMGJFp06Zl9OjR6dat21uOf/7zn8/w4cPz3ve+N3vvvXdat26dV199NTNnzszChQuTJBdeeGG+//3v79DPCQAAAOxcyjLUlEqljBkzJieffHLGjBmTRx55JDNnzkyrVq1y7LHH5uyzz85ZZ52VUqn0lnNfeumlXHvttUmS0aNH54c//OFb1vzoRz/KHXfckUceeSQPPvhg3njjjbRo0SKdOnXKySefnPPPP3/DS40BAAAA1ivLULNe//79079//606p02bNhk0aFCmTZuWwYMHb3LNmWeemTPPPLM2RgQAAADKSFmHmm1RKpVy55131vcYAAAAwC6o7F4mDAAAAFBUQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQjep7AAAoZ4ePGFffI1DPGrxenRZvc+yEa27Lut2b1+k8FMvj3z67vkcAoI65owYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIJoVNsbPvroo1m9enWt7tmkSZP07t27VvcEAAAAKJpaDzV9+/ZNqVSq7W2zdu3aWt8TAAAAoEhqPdRccMEF73hHzR133JFXXnklSfLud787Bx98cJo3b56XX345M2bMyAsvvJAk6d27dw466KA0a9astscEAAAAKJxaDzU//vGPN3v8ggsuyCuvvJKPfexjueaaa/Ke97znLWt+//vf5/LLL8+sWbNy8cUX5+yzz67tMZMkDzzwQH784x/nL3/5S6qqqtK2bdv06NEjw4cPz+DBg2v9eitXrkzv3r0ze/bsNGvWLNXV1bV+DQAAAGDnVacvE77nnnsyduzYXHjhhbnttts2GWmS5CMf+Uj+/Oc/5+ijj87w4cPz+OOP1/osV155ZY455piMHz8+bdu2zaBBg9KpU6dMmTIlJ598coYNG5Y1a9bU6jUvu+yyzJkzJxUVFVm5cmWt7g0AAADs/Oo01IwePTotWrTIqFGj3nHt7rvvnl/+8pfZbbfdtmj91rjhhhsycuTIdOrUKY8//ngeffTR/Pa3v83UqVPz7LPP5tBDD81NN92UL33pS7V2zd/97nf5yU9+khEjRqR9+/a1ti8AAACw66jTUPPoo4+mX79+qaio2KL1bdu2zVFHHZWpU6fW2gzLli3LiBEj0rhx40ycODE9e/bc6Pj++++fSZMmpXXr1hk1alRmz5693ddcvHhxPvnJT+bQQw/Nf//3f2/3fgAAAMCuqU5DzUsvvZTdd999q85p2rRplixZUmszjBs3LtXV1Rk6dGi6d+++yTUdO3bMRRddlHXr1mXs2LHbdb2ampqcd955qa6uzk033ZTGjRtv134AAADArqtOQ02rVq0ya9asrTrnqaeeSps2bWpthkmTJiVJTj/99M2uW3/87rvv3q7r/ehHP8o999yTb3zjGzn44IO3ay8AAABg11br3/q0OT179syUKVNy++23b9G3Kt1+++157rnnMnTo0FqbYfr06UmSfv36bXZdt27d0rJly8yZMydLly5N69att/paTz/9dC6//PJ86EMfyqWXXrpN827KggULNnu8qqqq1q4FAAAA1J06DTXnnHNO7rnnnpx77rlZt25dTjnllLdde8stt+STn/xkGjZsmM997nO1cv2qqqpUV1enTZs2adWq1WbXlkqldOnSJTNmzMhzzz2Xvn37btW11qxZkzPOOCNNmjTJz3/+85RKpe2YfGP77LNPre0FAAAAFEedhpohQ4bkt7/9bSZMmJDTTz89Xbt2zTHHHJOOHTumdevWWbp0aRYtWpT77rsvzz33XGpqavLd7343vXr1qpXrv/DCC0mSPffcc4vWr/92psWLF2/1tb74xS9m5syZufnmm1NZWbnV5wMAAADlp05DTZL85je/yTXXXJPvfOc7mTNnTubMmbPR3SY1NTVJkgMPPDCjRo3KgAEDau3aK1euTPLvFxRvifXr1p+3pf70pz9l1KhROeusszJkyJCtG3ILzJ8/f7PHq6qq0qdPn1q/LgAAALBj1XmoadSoUa666qqMGDEif/rTn/Lkk0/mhRdeyOrVq9O8efN06tQp73vf+9K7d+9av/bWPn60PhptjWXLluWcc87Jvvvum+uuu26rz98S7tABAACAXVOdh5r1mjRpkoEDB2bgwIF1ds1mzZolSVatWrVF61evXp0kad68+RZf44ILLsiiRYty//33p0WLFls/JAAAAFC26vTruevb+m9uWv+umney/t00W/r14L/85S8zfvz4XH755TnqqKO2bUgAAACgbNXbHTVJ8q9//SszZ87Myy+/nIMOOmiHv1elsrIyTZs2zdKlS7N8+fLNfvNTTU1N5s2blyTp2rXrFu3//e9/P0ny7LPPbvYrxZcsWZIkG9Y0bNgw119/vTtwAAAAoMzVS6i555578uUvfzlPPPHEhp+deeaZGTdu3Ebr/vGPf+Tvf/973v/+96dJkybbfd1SqZRDDjkk06dPz9SpUzNo0KC3XTtr1qysWLEiHTt2TLt27bZo/4qKiiTJbbfdtkXrb7nlliRJgwYNcu211wo1AFCG1jVumhUHn/K2xwCA8lLnjz5de+21GThwYB5//PEccMABGTRo0Nu+tHfmzJnp379/brzxxlq7/vo4M378+M2uu/XWWzdavyWmTp2ampqad/yz3377JcmGf7927dp06NBhGz8RALBTKzXIut2bb/JPSmX1lDoAkDoONY888ki+8IUvpEOHDnnwwQfzzDPP5He/+93brj/hhBPSsmXLTJ48udZmOOecc1JRUZGbb745s2bN2uSaRYsWbfjGpuHDh9fatQEAAAA2p05Dzfe///00aNAgd999d97//ve/4/qGDRvmPe95T/72t7/V2gx77713rrjiirzxxhs58cQTN3r8Kknmzp2bgQMHZtmyZRk2bFh69epVa9cGAAAA2Jw6DTUPPfRQ+vTpkx49emzxOR06dMhLL71Uq3NcddVVGT58eJ5//vkcfvjh6dOnT0477bQcddRROfDAA/Pkk0/muOOOy5gxYzZ5/ogRI9KvX7889dRTtToXAAAAUN7qNNQsWbIk++yzz1ads27durz55pu1OkepVMqYMWMyefLkDB48OAsXLszEiRPz7LPP5thjj824ceMyefLkDS8H/r9eeumlXHvttZk2bVpGjx69Tddv2rRprbwcGQAAANi11Om3PrVq1SqLFy/eqnNmzpy5xd+6tLX69++f/v37b9U5bdq0yaBBgzJt2rQMHjx4m6779NNPb9N5AAAAwK6tTkNN3759M2XKlFRVVW3RtxxNnjw5zz//fE4++eQ6mG7LlEql3HnnnfU9BgAAALALqtNHny688MKsWbMm55xzTlavXr3ZtXPmzMknPvGJlEqlnHnmmXU0IQAAAED9qdNQ079//3zqU5/KH/7wh7z3ve/Nz3/+81RVVSVJ1q5dm5deeikPP/xwRowYkV69euWFF17Ihz70oW1+xAgAAABgZ1Knjz4lyfXXX59WrVrl2muvzfnnn5/k348T3Xzzzbn55ps3rKupqcmgQYPyy1/+sq5HBAAAAKgXdXpHTfLvKDNy5Mg8/fTTueyyy3LYYYelZcuWadCgQVq0aJGDDjoo5513Xv74xz9m4sSJadmyZV2PCAAAAFAv6vyOmvW6du2aUaNG1dflAQAAAAqnTu+oWf8+GgAAAADeqk5Dzd57750+ffrkBz/4QV544YW6vDQAAABA4dVpqOnZs2cee+yxfPazn01lZWX69++fX/7yl6murq7LMQAAAAAKqU5DzWOPPZa//vWvufLKK9OlS5fce++9Offcc9O+fft8/OMfz1133ZU333yzLkcCAAAAKIw6/9anbt265etf/3rmzJmTGTNm5Atf+EL23nvv3HLLLTnppJPSoUOHXHzxxXn44YfrejQAAACAelXnoeb/OuSQQ3LNNdfk2WefzeOPP57Pf/7zadGiRa6//vp84AMfSOfOnfOlL30pc+bMqc8xAQAAAOpEvYaa/+uwww7LN7/5zcydOzePPPJI/vM//zNJ8o1vfCM9e/as5+kAAAAAdrzChJr/q1OnTjnggANywAEHpKamJq+//np9jwQAAACwwzWq7wHWW7hwYW677bZMmDAhDz/8cNatW5eGDRvmuOOOy7nnnlvf4wEAAADscPUaaubNm5cJEyZkwoQJeeyxx7Ju3bo0aNAgRx99dIYMGZJTTjklbdq0qc8RAQAAAOpMnYeap59+ekOcmTVrVmpqalIqlXLkkUdm6NChOe2009K+ffu6HgsAAACg3tVpqOnZs2dmzpyZmpqaJEmvXr0yZMiQDBkyJJWVlXU5CgAAAEDh1GmoefLJJ9O9e/cMHTo0Q4YMSZcuXery8gAAAACFVqeh5p///Gf22WefurwkAAAAwE6jTr+eW6QBAAAAeHu1HmrWrFmTGTNmbHgPDQAAAABbptYfffrwhz+chx9+OOeff37GjBmz0bFu3bpl1apVW71ns2bNMmvWrNoaEQAAAKCQaj3UzJs3LzU1NZk3b95bjs2ePXub7rRp2LBhbYwGAAAAUGi1HmruvffeTJ48OUOGDHnLsXnz5uW1117b6j0rKipqYzQAAACAQqv1UHPQQQfloIMO2uSx/fbbr7YvBwAAALDLqNNvfQIAAADg7dVpqDnwwANz+eWXZ+bMmXV5WQAAAICdQp2GmoULF+baa69Nz549071794wcOTL//Oc/63IEAAAAgMKq01Azd+7cfP/738+RRx6Zp59+Ov/1X/+VLl265AMf+EBGjx6dpUuX1uU4AAAAAIVSp6Gmffv2ueSSSzJ16tTMnz8/3/nOd9K3b988/PDDueiii9KhQ4ecdNJJufXWW7fp26EAAAAAdmb19jLhjh075rLLLsu0adPyz3/+M9/+9rdz6KGH5s4778zQoUPTvn37nHfeefn973+fmpqa+hoTAAAAoM4U4lufKisr87nPfS6PPPJInn/++YwcOTJdu3bNL37xi/Tv3z9du3at7xEBAAAAdrhChJr/a999982IESPyq1/9Kueff35qamoyb968+h4LAAAAYIdrVN8D/F+zZs3KhAkTMmHChDz99NOpqalJixYtcsYZZ9T3aAAAAAA7XL2HmkcffTQTJkzIbbfdlrlz56ampibNmjXLkCFDMmTIkBx//PFp3LhxfY8JAAAAsMPVS6h56KGHMmHChNx+++1ZsGBBampqUlFRkcGDB2fIkCEZNGhQmjRpUh+jAQAAANSbOg01n/vc5/Kb3/wmL774YmpqarLbbrtlwIABGTp0aE466aQ0b968LscBAAAAKJQ6DTXf+9730rBhw3z4wx/OkCFDcvLJJ6dVq1Z1OQIAAABAYdVpqPnFL36RAQMGpE2bNnV5WQAAAICdQp1+Pfe9996byy+/vC4vCQAAALDTqNNQc8cdd6S6urouLwkAAACw06jTUNOyZcu8+uqrdXlJAAAAgJ1GnYaawYMH58EHH8yLL75Yl5cFAAAA2CnUaaj5+te/nu7du6d///557rnn6vLSAAAAAIVXp9/6VF1dnbFjx+Y73/lOunfvnn79+uX444/PPvvsk3bt2qVRo02P06RJk/Tu3bsuRwUAAACoc3Uaavbbb7/U1NQkSWpqanLffffl/vvv36Jz165duwMnAwAAAKh/dRpqhg8fntdee22rz2vatOkOmAYAAACgWOo01Fx//fV1eTkAAACAnUqdvkwYAAAAgLcn1AAAAAAUhFADAAAAUBB1+o6a3/72t1m1atVWn9ekSZOcdtppO2AiAAAAgOKo01Bz+umnp1QqbdU5NTU1KZVKQg0AAACwy6vTUDNy5MisXr36bY+vXLkyzzzzTO6///5UV1dn6NChOemkk9KsWbM6nBIAAACgftRpqLn88su3aN3KlSszcuTIXHPNNWndunV+9KMf7eDJAAAAAOpfnYaaLdWsWbN87WtfS9u2bfO5z30u73//+zN06ND6HgsAAABghyr0tz5deuml2X///TNmzJj6HgUAAABghyt0qEmSo446Kk8//XR9jwEAAACwwxU+1DRq1CjLly+v7zEAAAAAdrjCh5qHH3447dq1q+8xAAAAAHa4Qoear3zlK5k9e3aOPvro+h4FAAAAYIer0299+u1vf5tVq1Ztds3rr7+e559/PnfeeWf+9re/paKiIldccUUdTQgAAABQf+o01Jx++ukplUrvuK6mpiZJsu++++anP/1punXrtqNHAwAAAKh3dRpqRo4cmdWrV292TcOGDdOqVav06NEj73//+9OgQaGfzgIAAACoNXUaai6//PK6vBwAAADATsXtKgAAAAAFUaehZtWqVVm0aNHbHl+5cmW+9KUvpVevXunZs2e++MUvvuOjUgAAAAC7ijp99Ok///M/89Of/jQrVqxIRUXFRsdWrlyZ973vfXnqqac2vEx45syZefDBB3P//fenYcOGdTkqAAAAQJ2r0ztq/vznP+eQQw55S6RJkq997WuZNWtWjj322Dz00EOZMGFCOnXqlGnTpuVnP/tZXY4JAAAAUC/qNNTMnTs3nTt3fsvPly9fnuuvvz5HHHFE7rnnnvTr1y+DBw/O3XffnVKplJtvvrkuxwQAAACoF3Uaal577bVNPsJ0/fXXp7q6Ot/97nfTqNH/Po114IEHpnfv3nnuuefqckwAAACAelGnoWavvfZ6y8uE16xZkx/96Ec5+uij07dv37ecs88++6SqqqquRgQAAACoN3Uaag488MD8+c9/zvz58zf87Hvf+14WL16cL37xi5s8Z8WKFRteLgwAAACwK6vTb306//zz88c//jFHH310Pv3pT6e6ujrf/va3069fv3zoQx/a5Dlz585N69at63JMAAAAgHpRp6Fm6NCheeihh3L99dfnv/7rv1JTU5OOHTvmxhtv3OT6efPmZe7cuTnmmGPqckwAAACAelGnoSZJrrvuupx99tl56KGH0qpVq5x22mlp2bLlJteuXbs2F1xwQY4//vg6nhIAAACg7tV5qEmSvn37bvLFwf+/Aw44ID/+8Y/rYCIAAACA+lenLxMGAAAA4O0JNQAAAAAFIdQAAAAAFERZh5oHHnggQ4YMSefOnVNRUZHKysoMGDAgt99++3btO3369Hz1q1/Nhz70oXTp0iXNmzffsP/xxx+f0aNHZ/Xq1bX0KQAAAIBdRdmGmiuvvDLHHHNMxo8fn7Zt22bQoEHp1KlTpkyZkpNPPjnDhg3LmjVrtmnvY489NldffXUee+yxVFZWZuDAgTn66KOz++6755577skFF1yQ9773vXn00Udr+VMBAAAAO7N6+dan+nbDDTdk5MiR6dSpUyZMmJCePXtuODZ37tyceuqpuemmm9KhQ4d861vf2ur9r7nmmhx22GE56qij0qjRxn+LZ8yYkf/6r//KPffck+OPPz5PPfVU9tprr+3+TAAAAMDOr+zuqFm2bFlGjBiRxo0bZ+LEiRtFmiTZf//9M2nSpLRu3TqjRo3K7Nmzt/oan/vc53Lssce+JdIkyWGHHZY777wzRxxxRF5++eX8/Oc/39aPAgAAAOxiyi7UjBs3LtXV1Rk6dGi6d+++yTUdO3bMRRddlHXr1mXs2LG1PkOjRo1y5plnJknmzJlT6/sDAAAAO6eyCzWTJk1Kkpx++umbXbf++N13371D5njxxReTJHvuuedWn7tgwYLN/qmqqqrtcQEAAIA6UHbvqJk+fXqSpF+/fptd161bt7Rs2TJz5szJ0qVL07p161qbYfHixRk7dmwaNWqUs88+e6vP32effWptFgAAAKA4yuqOmqqqqlRXV6dNmzZp1arVZteWSqV06dIlSfLcc8/VyvVXrFiRn/zkJ+ndu3eWLl2an/70pzn44INrZW8AAABg51dWd9S88MILSbb8caP27dsn+fcdMFtrzZo1+dSnPpVVq1Zl+fLl+de//pW///3vWbduXT784Q9n4sSJOeyww7Z63ySZP3/+Zo9XVVWlT58+27Q3AAAAUH/KKtSsXLkySdK0adMtWr9+3frztsaaNWty0003Ze3atRv9vLKyMj169Ejbtm23es//uwcAAACw6ymrR59KpdJWra+pqdnmazVv3jxvvvlmampqsmrVqjz//PP53e9+l6OOOirf/e53c/DBB2fq1KnbvD8AAACw6ymrUNOsWbMkyapVq7Zo/erVq5P8O7psjyZNmmS//fbLiSeemF//+teZOHFiVq1alVNOOSUrVqzYrr0BAACAXUdZhZr139y0/l0172T9u2natGlTq3MMHDgwH//4x/Piiy/m17/+da3uDQAAAOy8yirUVFZWpmnTplm6dGmWL1++2bU1NTWZN29ekqRr1661PsuRRx6ZJHn88cdrfW8AAABg51RWoaZUKuWQQw5Jknd8P8ysWbOyYsWKdOzYMe3atav1WV5//fUNMwEAAAAkZRZqkmTQoEFJkvHjx2923a233rrR+tr2pz/9KUnSrVu3HbI/AAAAsPMpu1BzzjnnpKKiIjfffHNmzZq1yTWLFi3KddddlyQZPnx4rc8wYcKE3HXXXdljjz3y8Y9/vNb3BwAAAHZOZRdq9t5771xxxRV54403cuKJJ+aJJ57Y6PjcuXMzcODALFu2LMOGDUuvXr22av8xY8Zk9uzZmzy2bNmyfPGLX8yQIUPSoEGDXH/99TvksSoAAABg59SovgeoD1dddVUWLlyYsWPH5vDDD0/v3r2z3377ZfHixZk+fXrWrl2b4447LmPGjNnk+SNGjMi0adMyevTotzy6dOmll+a1117L3nvvnfe85z0bvjFq4cKFeeyxx/L6669nr732yo9//OMMHjx4h39WAAAAYOdRlqGmVCplzJgxOfnkkzNmzJg88sgjmTlzZlq1apVjjz02Z599ds4666xNvuj3pZdeyrXXXpskGT16dH74wx9udPwnP/lJ/vCHP+SRRx7Jo48+mpUrV6Zhw4Zp27ZtPvzhD+ekk07KGWeckWbNmtXJZwUAAAB2HmUZatbr379/+vfvv1XntGnTJoMGDcq0adM2eUfMmWeemTPPPLO2RgQAAADKSFmHmm1RKpVy55131vcYAAAAwC6o7F4mDAAAAFBU7qgBAACgsNauXZslS5Zs8li7du3SsGHDOp4IdiyhBgAAgMJasmTJ274H9Fe/+lX22muvOp4IdiyPPgEAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABREo/oeAAAAYHMOHzGuvkegHjV4vTot3ubYCdfclnW7N6/TeSiex799dn2PUKvcUQMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBlHWoeeCBBzJkyJB07tw5FRUVqayszIABA3L77bdv175r167NXXfdlU984hN5z3vek6ZNm6ZJkybp0qVLzj777DzyyCO19AkAAACAXUnZhporr7wyxxxzTMaPH5+2bdtm0KBB6dSpU6ZMmZKTTz45w4YNy5o1a7Z63+XLl6dz58454YQTMm7cuOy222756Ec/moEDByZJfvnLX+bII4/Mf//3f9f2RwIAAAB2co3qe4D6cMMNN2TkyJHp1KlTJkyYkJ49e244Nnfu3Jx66qm56aab0qFDh3zrW9/aqr2bNWuWtm3bZsSIERk6dGjatWu34VhNTU2uv/76XHLJJfnKV76SQw89NCeeeGKtfS4AAABg51Z2d9QsW7YsI0aMSOPGjTNx4sSNIk2S7L///pk0aVJat26dUaNGZfbs2Vu1/2677ZYnnngil1xyyUaRJklKpVIuuuiiXH755UmSH/zgB9v3YQAAAIBdStmFmnHjxqW6ujpDhw5N9+7dN7mmY8eOueiii7Ju3bqMHTu21mc4//zzkySPP/54re8NAAAA7LzKLtRMmjQpSXL66advdt3643fffXetz9C2bdsk2aZ34AAAAJSTdY2bZsXBp2zyz7rGTet7PKh1ZfeOmunTpydJ+vXrt9l13bp1S8uWLTNnzpwsXbo0rVu3rrUZZsyYkSTp0aPHNp2/YMGCzR6vqqrapn0BAAAKp9Qg63ZvXt9TQJ0pq1BTVVWV6urqtGnTJq1atdrs2lKplC5dumTGjBl57rnn0rdv31qb44YbbkiSnHXWWdt0/j777FNrswAAAADFUVaPPr3wwgtJkj333HOL1rdv3z5Jsnjx4lqbYfr06bn11luzzz77bHhXDQAAAEBSZnfUrFy5MknStOmWPce4ft3682rj+ueee25qamryox/9KBUVFdu0z/z58zd7vKqqKn369NmmvQEAAID6U1ahplQqbdX6mpqaWr3++eefn2effTaXXnppTjzxxG3ep7KyshanAgAAAIqirB59atasWZJk1apVW7R+9erVSZLmzbf/xVVf/epXc8stt+SjH/1oRo0atd37AQAAALuesgo167+5af27at7J+nfTtGnTZruue8MNN+Tqq69Ojx49cuutt6Zhw4bbtR8AAACwayqrUFNZWZmmTZtm6dKlWb58+WbX1tTUZN68eUmSrl27bvM1b7rpplx88cXp0qVL7rnnnrRo0WKb9wIAAAB2bWUVakqlUg455JAkydSpUze7dtasWVmxYkU6duyYdu3abdP1JkyYkHPPPTd77bVX/vCHP6RDhw7btA8AAABQHsoq1CTJoEGDkiTjx4/f7Lpbb711o/Vb6+67784ZZ5yRd73rXfnDH/6Qzp07b9M+AAAAQPkou1BzzjnnpKKiIjfffHNmzZq1yTWLFi3KddddlyQZPnz4Vl/jT3/6U0455ZQ0adIkU6ZMyXvf+97tmhkAAAAoD2UXavbee+9cccUVeeONN3LiiSfmiSee2Oj43LlzM3DgwCxbtizDhg1Lr169tmr/adOm5cQTT0yDBg1y1113pWfPnrU5PgAAALALa1TfA9SHq666KgsXLszYsWNz+OGHp3fv3tlvv/2yePHiTJ8+PWvXrs1xxx2XMWPGbPL8ESNGZNq0aRk9enS6deu20bFTTjklK1euzHve857ccMMNueGGGzY7y5lnnpnjjz++1j4bAAAAsPMqy1BTKpUyZsyYnHzyyRkzZkweeeSRzJw5M61atcqxxx6bs88+O2eddVZKpdJbzn3ppZdy7bXXJklGjx6dH/7whxsdf+WVV5IkzzzzTJ555pl3nKV79+5CDQAAAJCkTEPNev3790///v236pw2bdpk0KBBmTZtWgYPHvyW46tWraqt8QAAAIAyU9ahZluUSqXceeed9T0GAAAAsAsqu5cJAwAAABSVUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQZR1qHnggQcyZMiQdO7cORUVFamsrMyAAQNy++231+p1li1blgEDBqRUKuXaa6+t1b0BAACAXUfZhporr7wyxxxzTMaPH5+2bdtm0KBB6dSpU6ZMmZKTTz45w4YNy5o1a7b7OrNnz06fPn0yefLkJEl1dfV27wkAAADsmsoy1Nxwww0ZOXJkOnXqlMcffzyPPvpofvvb32bq1Kl59tlnc+ihh+amm27Kl770pe26zl133ZUjjjgiVVVVOe2002ppegAAAGBXVXahZtmyZRkxYkQaN26ciRMnpmfPnhsd33///TNp0qS0bt06o0aNyuzZs7fpOtddd11OOumktGzZMg8//HAGDBhQG+MDAAAAu7CyCzXjxo1LdXV1hg4dmu7du29yTceOHXPRRRdl3bp1GTt27DZdp0mTJjnyyCPzl7/8JYcccsj2jAwAAACUibILNZMmTUqSnH766Ztdt/743XffvU3X+cQnPpGpU6dmr7322qbzAQAAgPLTqL4HqGvTp09PkvTr12+z67p165aWLVtmzpw5Wbp0aVq3bl0X422RBQsWbPZ4VVVVHU0CAAAA1KayCjVVVVWprq5OmzZt0qpVq82uLZVK6dKlS2bMmJHnnnsuffv2rZsht8A+++xT3yMAAAAAO0BZPfr0wgsvJEn23HPPLVrfvn37JMnixYt32EwAAAAA65XVHTUrV65MkjRt2nSL1q9ft/68opg/f/5mj1dVVaVPnz51NA0AAABQW8oq1JRKpa1aX1NTs4Mm2T6VlZX1PQIAAACwA5TVo0/NmjVLkqxatWqL1q9evTpJ0rx58x02EwAAAMB6ZRVq1n9z0/p31byT9e+madOmzQ6bCQAAAGC9sgo1lZWVadq0aZYuXZrly5dvdm1NTU3mzZuXJOnatWsdTAcAAACUu7IKNaVSKYccckiSZOrUqZtdO2vWrKxYsSIdO3ZMu3bt6mI8AAAAoMyVVahJkkGDBiVJxo8fv9l1t95660brAQAAAHa0sgs155xzTioqKnLzzTdn1qxZm1yzaNGiXHfddUmS4cOH1+V4AAAAQBkru1Cz995754orrsgbb7yRE088MU888cRGx+fOnZuBAwdm2bJlGTZsWHr16lVPkwIAAADlplF9D1AfrrrqqixcuDBjx47N4Ycfnt69e2e//fbL4sWLM3369KxduzbHHXdcxowZs8nzR4wYkWnTpmX06NHp1q1bHU8PAAAA7KrK7o6a5N8vFR4zZkwmT56cwYMHZ+HChZk4cWKeffbZHHvssRk3blwmT56cioqKt5z70ksv5dprr90QarZUkyZNNvpXAAAAgP9fWd5Rs17//v3Tv3//rTqnTZs2GTRoUKZNm5bBgwdv8XlDhgzJkCFDtnZEAAAAoIyUdajZFqVSKXfeeWd9jwEAAADsgsry0ScAAACAIhJqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIMo61DzwwAMZMmRIOnfunIqKilRWVmbAgAG5/fbba2X/v//977n00kvznve8J82aNUvbtm1zxBFH5Ec/+lFWr15dK9cAAAAAdh1lG2quvPLKHHPMMRk/fnzatm2bQYMGpVOnTpkyZUpOPvnkDBs2LGvWrNnm/W+77bYceuih+cEPfpA333wzxx13XA4//PD87W9/yyWXXJJ+/fpl4cKFtfiJAAAAgJ1do/oeoD7ccMMNGTlyZDp16pQJEyakZ8+eG47NnTs3p556am666aZ06NAh3/rWt7Z6/7/+9a/5+Mc/noYNG+ZXv/pVzjjjjA3HXn311VxwwQX59a9/ndNOOy0PPfRQGjZsWCufCwAAANi5ld0dNcuWLcuIESPSuHHjTJw4caNIkyT7779/Jk2alNatW2fUqFGZPXv2Vl/joosuypo1a/Ld7353o0iTJHvssUfGjRuXfv36Zfr06fnJT36yXZ8HAAAA2HWUXagZN25cqqurM3To0HTv3n2Tazp27JiLLroo69aty9ixY7dq/5kzZ+bhhx9O586dM3z48E2uadiwYa6++uokyejRo7fuAwAAAAC7rLJ79GnSpElJktNPP32z604//fR8/etfz913353vfOc7W73/KaeckgYN3r6DffCDH0zbtm0zY8aMLF68OHvttdcWX2PBggWbPT5//vwNf11VVbXF++4Ia15dWq/XB4rrnX6XlQu/J4HN8bvy3/yuBDanPn9X/t9/5n7zzTdrZc9STU1NTa3stJPYY489Ul1dnWXLlqVVq1Zvu66mpibvete78sorr+Tll19O69att2j/E044IXfddVduv/32fOxjH9vs2pNOOikTJ07MbbfdlsGDB2/xZyiVSlu8FgAAANjx/vKXv6R3797bvU9ZPfpUVVWV6urqtGnTZrORJvl3DOnSpUuS5Lnnntviazz77LNJkne/+93vuHb//fff6BwAAACgvJXVo08vvPBCkmTPPffcovXt27dPkixevHiHXGNb9k82frRpU1577bU888wzad++fdq1a5dGjcrqP2YKqKqqKn369Eny78rcoUOHep4IoHj8rgTYPL8nKaI333wzS5YsSZK3fQ/u1iqrf4JfuXJlkqRp06ZbtH79uvXn1fY1tmX/JKmsrHzHNVtyRw/Uhw4dOmzRf4cBypnflQCb5/ckRdKpU6da3a+sHn3a2ne7bMvre7bmGmX2eiAAAADgHZRVqGnWrFmSZNWqVVu0fvXq1UmS5s2b75BrbMv+AAAAwK6rrELN+m9uWv8emXey/t0xbdq02SHX2Jb9AQAAgF1XWYWaysrKNG3aNEuXLs3y5cs3u7ampibz5s1LknTt2nWLr7F+7dy5c99x7fo1W7M/AAAAsOsqq1BTKpVyyCGHJEmmTp262bWzZs3KihUr0rFjx7Rr126Lr3HYYYdt0f41NTWZNm1akmyYCQAAAChvZRVqkmTQoEFJkvHjx2923a233rrR+q3d/7bbbsvatWvfdt2f/vSnvPzyy+natas7agAAAIAkZRhqzjnnnFRUVOTmm2/OrFmzNrlm0aJFue6665Ikw4cP36r9jzzyyBxyyCH5xz/+kZ/85CebXLN27dpcddVV27Q/AAAAsOsqu1Cz995754orrsgbb7yRE088MU888cRGx+fOnZuBAwdm2bJlGTZsWHr16rVV+5dKpXznO99Jw4YN89nPfja/+c1vNjr+6quv5uyzz860adPStWvXfOYzn9nuzwRFV1lZmZqamtTU1KSysrK+xwEoJL8rATbP70nKRammpqamvoeoazU1Nfn0pz+dsWPHJkl69+6d/fbbL4sXL8706dOzdu3aHHfccbnjjjtSUVHxlvNHjBiRadOmZfTo0enWrdsmr/Gzn/0sF154YdasWZN3v/vd6dGjR1auXJmHH3441dXV6dKlS+69997sv//+O/SzAgAAADuPsgw1691zzz0ZM2ZMHnnkkbz00ktp1apVevTokbPPPjtnnXVWSqXSW8556aWXNrxc+DOf+Ux++MMfvu3+Tz/9dL7//e/nj3/8YxYtWpTGjRvn3e9+d0455ZT8x3/8R5o1a7bDPhsAAACw8ynrULMtampqcuKJJ2batGm59dZb88EPfrC+RwIAAAB2EUINAAAAQEGU3cuEAQAAAIpKqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQaoA68dRTT+WAAw5Iw4YN8+ijj9b3OACF8Oqrr+ZnP/tZBg8enH322SeNGzfOHnvskR49euTzn/98/vWvf9X3iAD1au3atfnd736Xyy67LH379s0+++yT3XffPc2aNcsBBxyQM844I3feeWdqamrqe1SoNaUa/40GdrDbb789Z599dqqrq5Mk9913X4455pj6HQqgnj3wwAMZNGhQqqur06RJkxxyyCGprKzMa6+9locffjjLli1L8+bNM378+Bx//PH1PS5Avfjzn/+cI488MknSsWPHdOvWLa1atcrixYsze/bsLFmyJElyzDHH5JZbbsmee+5Zn+NCrWhU3wMAu66ampp87Wtfy1e/+tXsv//+6dChQx566KH6HgugEBo3bpxevXrl4osvzsCBA9OkSZMNx1auXJlLLrkkN954Y04//fTMmTMnHTt2rMdpAepH165dM3LkyBx//PHp0aPHRsfWrl2bKVOm5LLLLsv999+fk08+OVOnTq2nSaH2uKMG2GFOP/303HrrrTnmmGMyYcKEfO5zn8svfvELd9QAbIF169blqKOOyrRp0/K1r30tX/rSl+p7JIBCWrRoUd773vdmxYoVmT59eo444oj6Hgm2i3fUADtM06ZNM3z48Nx7771p3bp1fY8DsFNp0KBBzjvvvCTJ448/Xs/TABRXx44d85GPfCRJMmfOnHqeBrafR5+AHebnP/95fY8AsFNr27ZtkmTNmjX1PAlAsb344otJ4h017BLcUQMAUFAzZsxIkre8lwGA/3Xfffdl6tSp6dSpUz74wQ/W9ziw3YQaAIACWrNmTX72s5+lVCrlzDPPrO9xAApn/vz5+cpXvpIBAwakffv2uf3227P77rvX91iw3Tz6BABQQN/97nezYMGCnHbaaenWrVt9jwNQr/72t7/lmmuuyWuvvZaXX345c+fOzYIFC9KkSZN8/OMfzze/+c20a9euvseEWiHUAAAUzFNPPZWvfOUr2WOPPfKd73ynvscBqHf/+te/8utf//otPz/wwANz0EEHpVmzZvUwFewYHn0CACiQV155JaecckrWrFmTX/ziF6msrKzvkQDq3fHHH5+ampqsW7cur776ap5++unceOONad68eUaMGJHDDz88ixcvru8xoVYINQAABfHGG2/k1FNPzbPPPpurr746gwcPru+RAAqlVCqlefPmee9735tzzz03Dz30UK644oo888wzOe+88+p7PKgVQg0AQAGsW7cu5557bv7whz/k3HPPzZe//OX6Hglgp/A///M/2W+//XLPPffkmWeeqe9xYLsJNQAABXDhhRfm17/+dU444YSMHTu2vscB2Gk0aNAgffr0SZI8/vjj9TwNbD+hBgCgnn32s5/NmDFjcuyxx2b8+PFp1Mj3PQBsjddffz3Jvx+Ngp2dUAMAUI++9KUv5Xvf+1769u2biRMnpqKior5HAtiprFmzJg8//HCSpFu3bvU8DWw/oQYAoJ584xvfyP/8z/+kR48emTx5cpo3b17fIwHsdEaMGJGXX345ffv2TY8ePep7HNhuQg0AQD34/ve/n//6r//KAQcckHvvvTfvete76nskgEJZvnx5Ro8enRdeeGGTx+fOnZvBgwfnBz/4Qd71rnflZz/7WR1PCDuGB6ABAOrYM888k89+9rNJko4dO+Y///M/N7u+VCrla1/7Wjp16lQH0wEUw5w5c3LBBRfkwgsvzIEHHpguXbqkRYsWWbNmTf7+979n1qxZqampSc+ePTNu3LgcdNBB9T0y1AqhBqgzTZo02ehfAcrVK6+8suGvH3jggS065zOf+YxQA5SVbt26ZdSoUZk6dWpmzJiR+++/P6+99loqKirSsWPHnHHGGRkyZEgGDhyYBg08LMKuo1RTU1NT30MAAAAA4B01AAAAAIUh1AAAAAAUhFADAAAAUBBCDQAAAEBBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAAAAFIRQAwAAAFAQQg0AAABAQQg1AAAAAAUh1AAAAAAUhFADAFDHqqqq0rBhw3Tp0qW+RwEACkaoAQCoY6+//nrWrVuXVatW1fcoAEDBCDUAAAAABSHUAAAAABSEUAMAAABQEEINAAAAQEEINQAAAAAFIdQAAGXt+OOPT5MmTbJu3bq8/PLLufrqq9OjR4/sscceadGiRQ499NB87WtfS3V19Tvude+992bYsGHp3LlzmjRpkoqKiuy11145+uijc//992/xTNOnT8+FF16Yww8/PHvvvXcaN26cli1bplevXvn617+elStXvu25U6ZMyYknnpjOnTuncePGadasWQ466KCcc845WbRo0VvW33zzzfnIRz6SffbZJ7vttlv22GOPHHroobngggu26DMDALWrVFNTU1PfQwAA1JdjjjkmDzzwQJ588smccMIJWbBgQfr06ZN99903L774Yh5++OG8+eab6dKlS/70pz9lv/32e8seS5cuzRlnnJEpU6YkSQ4++ODsv//+2X333fPSSy/lySefzDe+8Y18+tOfTpI8//zz6dy5c9q3b5/FixdvtNdjjz2W3r17p1QqZf/990/Hjh3Tvn37rFq1Kn/5y1+yZMmS9OjRIw8//HCaN2++0bnf/va3c/nll6dUKqV3797Zd999UyqVMn/+/DzxxBP54x//mPe///0b1l988cX58Y9/nEaNGuWII45Ix44ds3bt2vzjH//IzJkz8/zzz6eysrK2/5YDAJvRqL4HAAAogjPOOCMVFRWZOXNmunfvvuHnCxYsyJAhQzJt2rQMHjw4jz76aBo2bLjh+KuvvpoPfOAD+dvf/pbjjz8+3/ve99K1a9eN9q6pqcmW/n9jLVq0yDe+8Y2cd955ad++/UbH1qxZk7POOiu33nprvv3tb+fqq6/eaM4rr7wyLVu2zH333ZfDDjtso3Nfe+217L777hv+/Z///Of8+Mc/zr777psHHnggnTp12mj9qlWr0rRp0y2aGQCoPR59AgBIMnfu3EyaNGmjSJMklZWVmTRpUjp06JAZM2bktttu2+j45z//+fztb3/LKaeckrvuuustkSZJSqVSGjTYsv/Z1bVr11xxxRVviTRJ0rhx4/zoRz9Kktx+++0bHZs+fXrWrl2bIUOGvCXSJElFRUVKpdKGf//QQw8lSS644IK3RJokIg0A1BOhBgAgyZlnnpkDDjhgk8datWqVSy+9NEny29/+dsPPq6qqcuONN6ZJkya5/vrrtzjGbI8999wz7du3z9y5c98yY5Itfq/M1q4HAOqGR58AAJIMHDhws8ePPvroJMnjjz++4Wf33HNP3njjjZxwwglp165drc80e/bszJgxI/PmzcuSJUuycuXKrFmzJtXV1Vm1atVGaz/4wQ+mR48e+fWvf50OHTrkK1/5SvbYY4+33fu0007LV7/61Xz7299OixYtctlll230aBQAUD+EGgCAJAceeOBmj69/qe7/ffnv008/nSTp2bNnrc5yyy235Ctf+UrmzJmzxec0bNgwU6ZMyac+9amMGjUqP/3pT/OpT30ql156aTp27PiW9a1atcr999+f8847L1dccUW+//3v5zOf+UwuvPDCvOtd76rNjwMAbAWPPgEAJO94N0nLli2T/PuFvuu98sorGx2rDddcc02GDh2aOXPm5KijjsoPfvCDPPzww1m4cGFWr16ddevWbfKbp5Jkr732ysSJE/PII4/k6KOPzre//e106dIln/70p/Piiy++Zf0BBxyQqVOn5t57703Xrl3zxS9+Mfvtt1++8IUveCQKAOqJUAMAkGTFihWbPb58+fIk//tul+R/A81LL71UKzPMmzcvV111VRo2bJhf/epXefDBB3PJJZfkfe97Xzp27LjhhcArV67c7D59+vTJHXfckVmzZuWDH/xgxowZk8MOOywLFizY5PqPfOQjuf/++zNt2rQcdNBB+da3vpUjjzwyr776aq18LgBgywk1AABJnnnmmc0e/9vf/pYkec973rPhZ926dUuSTJ06tVZmuPXWW7N27dqcfvrpOeOMMza5ZsWKFVm6dOkW7XfwwQdn0qRJGTZsWBYtWpTLL798s+uPPPLIPPjgg/ngBz+Yp556Kt/4xje2+jMAANtHqAEASDJ58uTNHr/zzjuTJB/4wAc2/Oy4447Lbrvtlvvuuy+zZ8/e7hn++c9/Jkl69er1tmumTJmSdevWbfGepVIp11xzTZJ/v/z4nTRu3DhXX331Fq8HAGqXUAMAkGT8+PEbXg78/3v++edz4403pkGDBjn77LM3/HyvvfbKsGHDsm7dupx33nlv+SamrbX+m6Pmz5+/yeOvv/56vva1r231vkuWLEmSLQ48W7seAKg9Qg0AQJJ3vetdGThwYJ544omNfv7ss89mwIABWb16dS644IJ07dp1o+PXXnttOnXqlEceeSTHHnts/vrXv25y/5qamnecYcCAAUmSX/7yl2+ZY+HChRk0aFCef/759OvX7y3nLliwIE899dRbfr5w4cJ8+tOfTpL0799/o881d+7ct6yfM2dOPv/5z79lPQBQN0o1W/K/GgAAdlHHHHNMHnjggUyaNCmf/OQns3jx4vTu3Tv77bdfqqqqMn369KxduzYDBw7MbbfdlsaNG79ljwULFuRjH/tYHn/88SRJ9+7dc8ABB6Rx48Z56aWX8uSTT+brX//6hmDy/PPPp3Pnzmnfvv1GX/edJBdddFGuv/76lEql9O7dO/vuu2+WLFmS6dOnp1GjRrnppptyyy235JZbbskbb7yRRo0aJUm++c1v5oorrkhlZWUOPPDAtG7dOosXL84jjzySNWvW5MADD8x9992XDh06JEkuvPDC3HDDDdl///2z//77p0WLFpk/f34effTRrFu3LkceeWR+//vfp1mzZjvybz8A8P9pVN8DAAAUwUEHHZQnn3wyo0aNysSJEzNp0qTstttu6du3b84///ycd955KZVKmzy3srIyf/nLX/LrX/86N998c5544onMnj0769atS/PmzdOpU6fss88+G9bvvvvuadCgQZo2bfqWva677rq8733vy09+8pPMnDkzM2fOTGVlZc4///xcdtll6dq1a+66667stttuWbNmzYZQc9RRR+W4447Lk08+mfvuuy81NTXZc889c/jhh+djH/tYLr744o2iy/HHH5/Zs2fnqaeeyu9///uUSqV06NAhH/jABzJkyJCcf/752W233Wr57zIA8E7cUQMAlLX1d9T84x//SKdOnep7HACgzHlHDQAAAEBBCDUAAAAABSHUAABlbY899kjDhg1TUVFR36MAAHhHDQAAAEBRuKMGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIIQagAAAAAKQqgBAAAAKAihBgAAAKAghBoAAACAghBqAAAAAApCqAEAAAAoCKEGAAAAoCCEGgAAAICCEGoAAAAACkKoAQAAACgIoQYAAACgIIQaAAAAgIL4f7o4UAIfpWt3AAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "image/png": {
              "width": 565,
              "height": 430
            }
          }
        }
      ]
    }
  ]
}