Assignment_16.ipynb

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  "metadata": {
    "colab": {
      "name": "Assignment_16.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyN201PtODa96C0vEdcJ3SHk",
      "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/Jagannath8/GoeduHub-Training/blob/main/Assignment_16.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "27vQNzq8IqV4"
      },
      "source": [
        "# **GO_STP_579 -> Jagannath Pal**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jsf6a2PdIp4-"
      },
      "source": [
        "# ***Assignment_16***\n",
        "\n",
        "\n",
        "---\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cAgHsL6kIps0"
      },
      "source": [
        "Naive Bayes classifiers are built on Bayesian classification methods. These rely on Bayes's theorem, which is an equation describing the relationship of conditional probabilities of statistical quantities.\n",
        "\n",
        "\n",
        "Create a Model using Naive Bayes classifiers to predict whether a passenger on the titanic would have been survived or not.\n",
        "\n",
        "Dataset can be downloaded from Kaggle."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gU5_flpjMDim"
      },
      "source": [
        "# Importing Libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L82bhZkeIoxE"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import sklearn"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_u4RdO3PMHZp"
      },
      "source": [
        "# Reading the Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "xCHzM44MMKI0",
        "outputId": "de7f6675-6658-4b52-ad0c-1a82648830ba"
      },
      "source": [
        "df = pd.read_csv('/content/titanic_train.csv')\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\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>PassengerId</th>\n",
              "      <th>Survived</th>\n",
              "      <th>Pclass</th>\n",
              "      <th>Name</th>\n",
              "      <th>Sex</th>\n",
              "      <th>Age</th>\n",
              "      <th>SibSp</th>\n",
              "      <th>Parch</th>\n",
              "      <th>Ticket</th>\n",
              "      <th>Fare</th>\n",
              "      <th>Cabin</th>\n",
              "      <th>Embarked</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>Braund, Mr. Owen Harris</td>\n",
              "      <td>male</td>\n",
              "      <td>22.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>A/5 21171</td>\n",
              "      <td>7.2500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
              "      <td>female</td>\n",
              "      <td>38.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>PC 17599</td>\n",
              "      <td>71.2833</td>\n",
              "      <td>C85</td>\n",
              "      <td>C</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>Heikkinen, Miss. Laina</td>\n",
              "      <td>female</td>\n",
              "      <td>26.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>STON/O2. 3101282</td>\n",
              "      <td>7.9250</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
              "      <td>female</td>\n",
              "      <td>35.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>113803</td>\n",
              "      <td>53.1000</td>\n",
              "      <td>C123</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>Allen, Mr. William Henry</td>\n",
              "      <td>male</td>\n",
              "      <td>35.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>373450</td>\n",
              "      <td>8.0500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>886</th>\n",
              "      <td>887</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>Montvila, Rev. Juozas</td>\n",
              "      <td>male</td>\n",
              "      <td>27.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>211536</td>\n",
              "      <td>13.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>887</th>\n",
              "      <td>888</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Graham, Miss. Margaret Edith</td>\n",
              "      <td>female</td>\n",
              "      <td>19.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>112053</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>B42</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>888</th>\n",
              "      <td>889</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
              "      <td>female</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>W./C. 6607</td>\n",
              "      <td>23.4500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>889</th>\n",
              "      <td>890</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Behr, Mr. Karl Howell</td>\n",
              "      <td>male</td>\n",
              "      <td>26.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>111369</td>\n",
              "      <td>30.0000</td>\n",
              "      <td>C148</td>\n",
              "      <td>C</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>890</th>\n",
              "      <td>891</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>Dooley, Mr. Patrick</td>\n",
              "      <td>male</td>\n",
              "      <td>32.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>370376</td>\n",
              "      <td>7.7500</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Q</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>891 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     PassengerId  Survived  Pclass  ...     Fare Cabin  Embarked\n",
              "0              1         0       3  ...   7.2500   NaN         S\n",
              "1              2         1       1  ...  71.2833   C85         C\n",
              "2              3         1       3  ...   7.9250   NaN         S\n",
              "3              4         1       1  ...  53.1000  C123         S\n",
              "4              5         0       3  ...   8.0500   NaN         S\n",
              "..           ...       ...     ...  ...      ...   ...       ...\n",
              "886          887         0       2  ...  13.0000   NaN         S\n",
              "887          888         1       1  ...  30.0000   B42         S\n",
              "888          889         0       3  ...  23.4500   NaN         S\n",
              "889          890         1       1  ...  30.0000  C148         C\n",
              "890          891         0       3  ...   7.7500   NaN         Q\n",
              "\n",
              "[891 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 95
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ETnAYEnCONcc"
      },
      "source": [
        "# Understanding the Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aKs_oSQcORPo",
        "outputId": "aea3727c-7685-4885-b1ef-e28c0c04beb1"
      },
      "source": [
        "df.dtypes"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PassengerId      int64\n",
              "Survived         int64\n",
              "Pclass           int64\n",
              "Name            object\n",
              "Sex             object\n",
              "Age            float64\n",
              "SibSp            int64\n",
              "Parch            int64\n",
              "Ticket          object\n",
              "Fare           float64\n",
              "Cabin           object\n",
              "Embarked        object\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "joqrnH3oOUYE",
        "outputId": "2dcfb41e-de97-484a-ab6c-afecf1afcebc"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(891, 12)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k9Vs44EZOWbN",
        "outputId": "588e8c56-c164-4bbc-e86e-ae6cecdd2ce5"
      },
      "source": [
        "df.size"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10692"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HKSlP_AfOY8H",
        "outputId": "c52e6f33-cde5-4cac-837b-24d1c85c9095"
      },
      "source": [
        "df.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n",
              "       'Parch', 'Ticket', 'Fare', 'Cabin', 'Embarked'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nG4M9tzgOnrW",
        "outputId": "f5f3dde1-65e0-420a-cd3c-179e68c5c5cd"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 891 entries, 0 to 890\n",
            "Data columns (total 12 columns):\n",
            " #   Column       Non-Null Count  Dtype  \n",
            "---  ------       --------------  -----  \n",
            " 0   PassengerId  891 non-null    int64  \n",
            " 1   Survived     891 non-null    int64  \n",
            " 2   Pclass       891 non-null    int64  \n",
            " 3   Name         891 non-null    object \n",
            " 4   Sex          891 non-null    object \n",
            " 5   Age          714 non-null    float64\n",
            " 6   SibSp        891 non-null    int64  \n",
            " 7   Parch        891 non-null    int64  \n",
            " 8   Ticket       891 non-null    object \n",
            " 9   Fare         891 non-null    float64\n",
            " 10  Cabin        204 non-null    object \n",
            " 11  Embarked     889 non-null    object \n",
            "dtypes: float64(2), int64(5), object(5)\n",
            "memory usage: 83.7+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "13sOnlmrOqRQ",
        "outputId": "16f70d90-80be-4495-9ed3-3c850a12dded"
      },
      "source": [
        "df.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PassengerId</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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>891.000000</td>\n",
              "      <td>891.000000</td>\n",
              "      <td>891.000000</td>\n",
              "      <td>714.000000</td>\n",
              "      <td>891.000000</td>\n",
              "      <td>891.000000</td>\n",
              "      <td>891.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>446.000000</td>\n",
              "      <td>0.383838</td>\n",
              "      <td>2.308642</td>\n",
              "      <td>29.699118</td>\n",
              "      <td>0.523008</td>\n",
              "      <td>0.381594</td>\n",
              "      <td>32.204208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>257.353842</td>\n",
              "      <td>0.486592</td>\n",
              "      <td>0.836071</td>\n",
              "      <td>14.526497</td>\n",
              "      <td>1.102743</td>\n",
              "      <td>0.806057</td>\n",
              "      <td>49.693429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.420000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>223.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>20.125000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>7.910400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>446.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>14.454200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>668.500000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>38.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>31.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>891.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>512.329200</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       PassengerId    Survived      Pclass  ...       SibSp       Parch        Fare\n",
              "count   891.000000  891.000000  891.000000  ...  891.000000  891.000000  891.000000\n",
              "mean    446.000000    0.383838    2.308642  ...    0.523008    0.381594   32.204208\n",
              "std     257.353842    0.486592    0.836071  ...    1.102743    0.806057   49.693429\n",
              "min       1.000000    0.000000    1.000000  ...    0.000000    0.000000    0.000000\n",
              "25%     223.500000    0.000000    2.000000  ...    0.000000    0.000000    7.910400\n",
              "50%     446.000000    0.000000    3.000000  ...    0.000000    0.000000   14.454200\n",
              "75%     668.500000    1.000000    3.000000  ...    1.000000    0.000000   31.000000\n",
              "max     891.000000    1.000000    3.000000  ...    8.000000    6.000000  512.329200\n",
              "\n",
              "[8 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 101
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 254
        },
        "id": "IeWGzsweO9qb",
        "outputId": "062eab25-5c0e-4841-fdbe-35233776335b"
      },
      "source": [
        "df.corr()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PassengerId</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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>PassengerId</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.005007</td>\n",
              "      <td>-0.035144</td>\n",
              "      <td>0.036847</td>\n",
              "      <td>-0.057527</td>\n",
              "      <td>-0.001652</td>\n",
              "      <td>0.012658</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Survived</th>\n",
              "      <td>-0.005007</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.338481</td>\n",
              "      <td>-0.077221</td>\n",
              "      <td>-0.035322</td>\n",
              "      <td>0.081629</td>\n",
              "      <td>0.257307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pclass</th>\n",
              "      <td>-0.035144</td>\n",
              "      <td>-0.338481</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.369226</td>\n",
              "      <td>0.083081</td>\n",
              "      <td>0.018443</td>\n",
              "      <td>-0.549500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Age</th>\n",
              "      <td>0.036847</td>\n",
              "      <td>-0.077221</td>\n",
              "      <td>-0.369226</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.308247</td>\n",
              "      <td>-0.189119</td>\n",
              "      <td>0.096067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SibSp</th>\n",
              "      <td>-0.057527</td>\n",
              "      <td>-0.035322</td>\n",
              "      <td>0.083081</td>\n",
              "      <td>-0.308247</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.414838</td>\n",
              "      <td>0.159651</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Parch</th>\n",
              "      <td>-0.001652</td>\n",
              "      <td>0.081629</td>\n",
              "      <td>0.018443</td>\n",
              "      <td>-0.189119</td>\n",
              "      <td>0.414838</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.216225</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fare</th>\n",
              "      <td>0.012658</td>\n",
              "      <td>0.257307</td>\n",
              "      <td>-0.549500</td>\n",
              "      <td>0.096067</td>\n",
              "      <td>0.159651</td>\n",
              "      <td>0.216225</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             PassengerId  Survived    Pclass  ...     SibSp     Parch      Fare\n",
              "PassengerId     1.000000 -0.005007 -0.035144  ... -0.057527 -0.001652  0.012658\n",
              "Survived       -0.005007  1.000000 -0.338481  ... -0.035322  0.081629  0.257307\n",
              "Pclass         -0.035144 -0.338481  1.000000  ...  0.083081  0.018443 -0.549500\n",
              "Age             0.036847 -0.077221 -0.369226  ... -0.308247 -0.189119  0.096067\n",
              "SibSp          -0.057527 -0.035322  0.083081  ...  1.000000  0.414838  0.159651\n",
              "Parch          -0.001652  0.081629  0.018443  ...  0.414838  1.000000  0.216225\n",
              "Fare            0.012658  0.257307 -0.549500  ...  0.159651  0.216225  1.000000\n",
              "\n",
              "[7 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BDrRuootOtmh",
        "outputId": "fdf1c9ea-eb39-4ff7-bf97-33b98a973a50"
      },
      "source": [
        "df.nunique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PassengerId    891\n",
              "Survived         2\n",
              "Pclass           3\n",
              "Name           891\n",
              "Sex              2\n",
              "Age             88\n",
              "SibSp            7\n",
              "Parch            7\n",
              "Ticket         681\n",
              "Fare           248\n",
              "Cabin          147\n",
              "Embarked         3\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 103
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nkegz6wqOwB6",
        "outputId": "1fef3704-8267-4fc2-b7fd-c9b9db9bf7c4"
      },
      "source": [
        "df.isnull().any"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method DataFrame.any of      PassengerId  Survived  Pclass   Name  ...  Ticket   Fare  Cabin  Embarked\n",
              "0          False     False   False  False  ...   False  False   True     False\n",
              "1          False     False   False  False  ...   False  False  False     False\n",
              "2          False     False   False  False  ...   False  False   True     False\n",
              "3          False     False   False  False  ...   False  False  False     False\n",
              "4          False     False   False  False  ...   False  False   True     False\n",
              "..           ...       ...     ...    ...  ...     ...    ...    ...       ...\n",
              "886        False     False   False  False  ...   False  False   True     False\n",
              "887        False     False   False  False  ...   False  False  False     False\n",
              "888        False     False   False  False  ...   False  False   True     False\n",
              "889        False     False   False  False  ...   False  False  False     False\n",
              "890        False     False   False  False  ...   False  False   True     False\n",
              "\n",
              "[891 rows x 12 columns]>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "10DC7OGdPNpY"
      },
      "source": [
        "# Visualization"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 713
        },
        "id": "HzHG92i9PQJq",
        "outputId": "1849f146-083b-43bf-a313-7d4c55b24e0c"
      },
      "source": [
        "import missingno as no\n",
        "no.bar(df, color='Lightblue')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fadedd47b50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 105
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1728x720 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "waGfVduESz0J",
        "outputId": "eedbdadc-dd34-44f2-f32a-922166554373"
      },
      "source": [
        "sns.heatmap(df.isnull(), yticklabels='False', cmap='YlOrRd_r')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fadee361790>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 106
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d6_QpqwCVHuE"
      },
      "source": [
        "# Handling Missing Values"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hdmS5BmVTpaL",
        "outputId": "4b18b39c-58b7-41dd-80b9-d4474fad1223"
      },
      "source": [
        "df['Age'].fillna(df.Age.median(), inplace=True)\n",
        "df.Age.isna().any()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KrLDx7s8Ub3w",
        "outputId": "a10733a6-d875-4c48-9c63-f7d47b51ea67"
      },
      "source": [
        "np.random.seed(42)\n",
        "df['Cabin'].fillna(np.random.choice(df.Cabin.unique()), inplace=True)\n",
        "df['Cabin'].isna().any()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aAg12loqU1zP"
      },
      "source": [
        "df.dropna(inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6_0FOo85U_LH",
        "outputId": "db94c360-b4b2-4503-861c-edd566997d4b"
      },
      "source": [
        "df.isnull().any()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PassengerId    False\n",
              "Survived       False\n",
              "Pclass         False\n",
              "Name           False\n",
              "Sex            False\n",
              "Age            False\n",
              "SibSp          False\n",
              "Parch          False\n",
              "Ticket         False\n",
              "Fare           False\n",
              "Cabin          False\n",
              "Embarked       False\n",
              "dtype: bool"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 713
        },
        "id": "U8TbVRDYVNUJ",
        "outputId": "ce8d1695-197c-4af0-d95a-f54328da285a"
      },
      "source": [
        "import missingno as no\n",
        "no.bar(df, color='pink')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fadee32efd0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 111
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1728x720 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BsSqsZFfVqND",
        "outputId": "4fa972a1-cbb2-4260-eb04-40193f8b1b9c"
      },
      "source": [
        "df.Survived.value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    549\n",
              "1    340\n",
              "Name: Survived, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 112
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 333
        },
        "id": "A0UuGf1PWEds",
        "outputId": "40c437f0-1d4e-47ed-f54c-2897fcdecca6"
      },
      "source": [
        "sns.countplot(df.Survived, palette='gist_rainbow_r')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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NOQ84v6p+DrjrcX9DaUSGgha9qnoIeD6wEZgCLknyhsfYbEtV/U9rXwq8qrXPBC6bZfwlwKtb+6z2GUcCLwI+luR64G+ZnrUAvBj4aGtfNKcvJD0OS8ZdgLQQVNXDwDXANUluBNYDu3jkf5yO2GOT787YdkeSe5M8m+k//L89y0dsAf48ybFMB9BVwJOBB6rqhL2VtZ9fR9pvzhS06CV5ZpK1M7pOAO4Abmf6DzjAbzzGbi4B3gYcVVU37LmyzUa+zPRhoU9W1cNV9W3gG0nOaHUkyXPaJl9gekYB8Nq5fytp/xgKEhwJbE5yS5IbmD5f8HbgHcB5SSaBhx9jH5cx/Uf80n2MuQR4XXvf7bXAhiRfBW7mkZ9CfRNwTpu1+Et4mjdekipJ6pwpSJI6Q0GS1BkKkqTOUJAkdYaCJKkzFCRJnaEgSer+H2pzyHvC8EW2AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3J77wdBfVyCl",
        "outputId": "53e70a14-a2aa-4cce-9d91-674e78300149"
      },
      "source": [
        "df.Sex.value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "male      577\n",
              "female    312\n",
              "Name: Sex, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "_UeA4GyXWnxs",
        "outputId": "7dd7908d-0f07-44f9-9743-015a57324799"
      },
      "source": [
        "df1 = df['Sex'].value_counts()\n",
        "plt.pie(df1.values, labels=df1.index, autopct='%0.2f%%', colors='my')\n",
        "plt.title('Pecentage of Gender', fontsize=15)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pbBrwrJeV2EZ",
        "outputId": "6419e92a-9ab6-4392-b404-f9da100fed90"
      },
      "source": [
        "df.Embarked.value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "S    644\n",
              "C    168\n",
              "Q     77\n",
              "Name: Embarked, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 116
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "q35s0DoEYDnN",
        "outputId": "890bfe8e-4380-43ed-ff3f-3277f2b5c018"
      },
      "source": [
        "df1 = df['Embarked'].value_counts()\n",
        "plt.pie(df1.values, labels=df1.index, autopct='%0.2f%%')\n",
        "plt.title('Pecentage of Embarked', fontsize=15)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "8PdAalBcYCc9",
        "outputId": "864825a7-6e35-4aa5-bd10-4418d7424062"
      },
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "sns.stripplot(x=df['Survived'], y=df.Fare, palette='magma_r')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "NHDi-sP8ZTLp",
        "outputId": "0b6cd612-0708-472b-ebcf-4bb2a23bd1fb"
      },
      "source": [
        "sns.violinplot(x=df.Survived, y=df.Age, palette='rainbow')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fadee1e8050>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 119
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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wq7uoey6TiaaRI9lZUNC2qIsQl+nAgQMAxLpoGOe5OoaHFhWdv3iL+HYS/N3cqlWr0EDLyJEu33dr+5fJihUrXL5v4fuKioqIiAzA378Tq8BdgejoIEwmJcF/BST4uzGHw8HKVauwJyejw8Jcvn8dFETrgAGsXrOGlpYWl+9f+LaiogPExgW6bf8WPxM9owIl+K+ABH83lpubS/XJk7SMGOG2Y7SMHElDXZ3cySsuS11dHeXlx4mJdU83T4eYuCAOHCiUC7yXSYK/G8vIyGi7qNuvn9uO4ejbF8LCWCVj+sVl2L9/P+C+C7sdevcOpqamloqKCrcex9dI8HdTp06daruom5rq2ou651KK5iFDyM/Pp6qqyn3HET5lz549KMVlr617uXontA0VlZXjLo8Efze1ceNGHA4HrUOGuP1YrUOGgNasW7fO7ccSviEvL5e43iHY3HRht0NMbBABgX5s377drcfxNRL83dS6rCx0ZCTOmCtf0aiznD164IyNJUtmQxSdUFNTw/79haenVXAnk0mRlBxGbu5WHA6H24/nKyT4u6Hq6mp27dxJy6BB4KIZDy+lZdAgDhQWys0y4pLWr1+P1prUoVc/fUhnDErtSXV1DQWyXnSnSfB3Q9nZ2WitaR08uMuO2TpoEACbNm3qsmOK7kdrzerVGUTHBBEdE9QlxxyQEoHNZpFJBS/DJYNfKRWjlHpTKfVV+8+pSqkH3V+auJj1GzZAZKRLJmTrLB0ejjM2tu3YQlzEjh07KCo6SPrYuC47pp+fmZGjo9mwYYOckXZSZ1r8bwMrgF7tP+8DHndXQeLb1dS0ndI2d2E3T4eWlBQK9++XoXPigrTWvP/++wQHWxnuomUWO2vs+N4oBUuXLu3S43ZXnQn+nlrrJYATQGttB+Qqiods3rwZ7XTS6sIJ2Tqro7tng7T6xQVs2rSJXbt2ce11CVj8urYXOTTMxugxsWRkZMidvJ3Qmf879UqpHoAGUEqNA2o6ewCllFkplaeUWtb+c5JSKlspVaiU+kApZb2iyg3q63Xr0D164Izu2hYVgI6IwBkby9dZWV1+bOHd6urqePPNN4iJDSJtdKxHapg8tQ8BgX689tqrso7EJXQm+H8CfAb0U0ptAP4GPHIZx3gMOPPuiheB/9Fa9wdOAnK9oJPKy8vZtXNn201bXdzN06ElNZWDBw5w9OhRjxxfeB+tNa+99honT57kxnn9MZk889n0D7Bw/Zwk9u8v5MMPP/RIDd3FJYNfa50LTAEmAN8HhmitO7XemVIqHrgReKP9ZwVMAzo64hYDt1x+2caUmZkJStE6dKjHamgdMgRMJhlBIU776quv2LBhA5Ov60Ov3u6douFShgyLYtjIaJYsWUJubq5Ha/FmnRnVcytwM5ACDARuUkpNV0p1pq/hd8CTtF8fAHoA1e3XCQCKgd6XXbUBtba2snzlSuxJSW6ZibOzOmbsXJWRQXNzs8fqEN4hNzeXv/zlLwwYGMmEa+M9XQ4AN9zYj+iYIF566SWOHDni6XK8Ume6eh6krcV+d/t/fwGeAjYopRZebCOl1FzguNZ665UUppR6WCmVo5TKkVEkkJWVRc3Jk7SMHu3pUmhJT6ehvl5a/Qa3Z88efvObF4mOCeI7d6R4rIvnXFabmfl3D8ZscfKrX/2S0tJST5fkdToT/BZgsNb6Nq31bUAqbRd6x9L2BXAxE4GblVKHgPdp6+L5PRCulOqYwCMeOHahjbXWr2ut07XW6VFRUZ36y/gqu93Oex98gDMmpm1JRA9zxMfjiI9nydKl0uo3qL179/KrX/2SwCAzd94zGKvNjRMFXoGwMBt3LRxMQ+Mp/vM//5OysjJPl+RVOhP8CVrrM++KON7+XBXQerGNtNbPaK3jtdaJwAIgU2t9N7AGuL39bfcBn15R5Qby+eefU1FeTtO113rsou5ZlKJp8mRqTp7k448/9nQ1oovl5ubyi1/8nIBAxT0PDCE01Obpki4oJjaYu+8bQkNDLc8884wM8zxDZ4J/rVJqmVLqPqVUR1CvVUoFAdVXcMyngJ8opQpp6/N/8wr2YRjHjh3j3X/8g9YBA9w67/7lcvTpQ8uQIXy4dCmHDh3ydDmii6xcuZLnnnuO8Ag/Fj4w1GtDv0NsXDALFw3F4WzkP/7jGbng264zwf/vwFvAyPb/cgCtta7XWl/XmYNorddqree2Py7SWo/RWvfXWt+htZa+gouoq6vjuV//GofFQtOsWd7R2j9D8/TpOP39ee7Xv6amptO3dohuqKWlhddee41XX32VpH5hLFw0lBAvD/0O0TFB3P+9YYRH+PHss8/y0Ucf4XQ6L72hD+vMcE4NFAF24DvAdZw9Ll+4QWNjI//9wguUlpVR953voEM8O0zuQnRgIHW33caJqiqee/556urqPF2ScIOysjKefvopVqxYwfiJvbnzu6nYbO6dZ9/VQkNtLFw0lMFDevD3v/+d559/jtraWk+X5TEXDX6l1ECl1C+UUnuA/wccAZTW+jqt9f92WYUGVFlZydPPPMPOXbtomDMHR58+ni7popy9etFw003sP3CAp55+WibJ8iFaa1auXMnjjz9GSWkx8787mOnXJ2Eye9eZZ2fZbBa+c0cKs+f2Y9u2bTz22KPk5OR4uiyP+LYW/x7aRuLM1VpP0lr/P2SOHrfbsmULP33iCY6UlFB/++3Yu2CFratlT0mhfv58Sk6c4Kc/+xkbN26Uxa+7uYqKCn71q1/y6quvEhsXwEM/GMHAQT08XdZVU0qRPiaOBx4ejp+1leeee44//OEPhjtbVRf7BVVK3ULbaJyJwHLahmS+obVO6rry2qSnp2tf/2Y+efIkf3njDTZu2ICOiqJ+7lyXr65ly8jAumMHAI7oaBwxMTTPmOGy/ZtOnCDw888xlZdzzTXX8P3vf5+eXTh1tLh6drudZcuW8f777+Fw2Jl+fSKj02NRbh6jv/LLIrbntZ0txsQFERsbzKw57h26bLc7yVp7lE3riwkJCeWBBx5gypQpKC+7lnY1lFJbtdbp5z5/0Y46rfU/gX+2j96ZR9tUzNFKqdeAT7TWK91WrYFUVVXx6aef8tXy5bTY7TRdey0t48a5ZQF1c3k5qn3cvcUNc+04e/ak7r77sH7zDd+sX0/ev/0b18+axS233ILR78XoDgoKCvjzn//E0aPF9B8YyfU3JhMR4d8lxy4rq6O5ua1D4cihrul7t1hMXDejL4NSe/DVsgP87ne/Y+XKlXz/+9+nb9++XVKDp1zyCo3Wuh74B/APpVQEcAdtQzIl+K9CSUkJn332GRmrV2O322lJTaVl4kSckZGeLu3qmEy0jB1La0oKtg0b+OKrr/hq+XKmXXcd8+bNIyEhwdMVinOUlpayePFiNm/eTHiEP/O/O9gnunU6K65XMA88NJy83HLWZOznxz/+MTNnzuSuu+4iPNz96wZ7wmVdmtdanwReb/9PXKbGxkbWr1/P6sxM9uzeDWYzLUOH0jxuHDoiwtPluZQOD6fpxhtpnjQJW3Y2GWvXkpGRwYCBA5kxfToTJ04kODjY02Ua2qlTp1iyZAlffvklZjNMmdaHcRN642f1rrtwu4IyKUalxzJocA/WrT3CqlUrWbfua2677XZuuukmbLbuMXS1s7rXmKxuqKWlhfz8fNavX8+GTZtobW5G9+hB89SptA4Z4pXDNF1Jh4XRNGsWzRMn4ldQwL6CAva/9hp/eeMNxo8bx6RJkxg5cqTP/WJ5s+bmZpYtW8bHH39EQ0MjI0dFM2VaX4JDZGmMwCA/Zt/Yj2vGxrF65SHeeecdvvrqSxYsuItp06ZhdkMXrCdI8LtBfX09OTk5ZGdnszU3l+amJrDZaBk8mNZhw3D06uV1N2O5mw4KomXsWFrGjMFUVoZ1xw6yvvmGrKws/Gw2Ro0cybhx40hPTyfEx78MPcXhcLB69Wree+89Tp48yYCBkVw3M6XLFkXvTnr0DGT+d1M5fKiGzFWH+eMf/8inn/6Te+5ZyNixY7v9BWAJfhfQWnPs2DFyc3PZunUrOwoKcDocEBxMy6BBtA4c2DYW3yL/3CiFMy6Oprg4mqZPx3z0KH779pG9axfZ2dkok4khQ4aQPno0o0aNIiEhodv/knma1potW7bwt78t5tixEuITQrnpO8Pok+i56b27i76JYdz/0DD27q5kTcYRXnjhBVJSUnjggQcY1L4UaXckSXSFGhoayM/PJy8vj5zcXCrbp47WPXrQkp6OfeBAQ7bsL4vZjCMxEUdiIk0zZ2IqK8Nv3z52FBZS8PbbvP3220T06EH6qFGkpaUxfPhwuS5wmfbu3cvbb7/F7t176NEzkDvuGszAQZHyZXoZlFIMSu3JwJQebMsrJ2vNIZ5++mnGjh3LvffeS+/e3W9JEQn+TnI6nRQVFZGXl0fetm3s2bMHp8OBslpp6dsX+6hRbYuk+OgoALdrPxNojoujecoUVG0tloMHaS0qImPdOlatWoUymRg4cCCj0tJIS0ujX79+PtPn6mrV1dUsXryYNWvWEBxs5Yab+pE2Krbb3nXrDUzmtgvAQ4dHkb3xGJvWbyUnJ4d58+Zxxx13EBAQ4OkSO02C/1tUVVWRl5fHtm3byNu2jbpTpwBwxsTQes012JOScMTHu2XMvdHp0FBaR4ygdcQIGh0OzCUlWIqK2H3oEHvff5/33nuPwKAgRo4YQVpaGiNHjpR7BWjrx1++fDnvvvsOzc3NTLg2nkmTE7xuvvzuzGo1c+3UPqSlx7Im4zAff/wxX3+9lkWLHmTChAnd4mxKgv8MWmsOHjzIN998w+YtWzh44EDbC0FBtCQm4khKamvVB8nFsC5lNuNISMCRkNB2NtDQgPnQIVoOHmTjjh1s3LgRgL5JSYy95hrGjBlDcnIyJlNnJp/1HZWVlbzyyivs2rWLpH7hzL5xMD16Bnq6LJ8VHGzlplsGkDYqhuVfFPHSSy8xadIkfvjDHxIY6N3/7oYPfofDQUFBAZs3byZ7yxaqKitBKRy9etE6ZQr25GSc0dHSV+9FdGAg9tRU7KmpNGmN6cQJLEVFFBUWcvjDD1myZAnhERGMueYaxo4dy8iRI32+Syg3N5f/+Z/f0tzcyM23DmDYiOhu0fL0BfF9Qln0/RFszCrm68wNFBbu58knnyLZC1bLuxjDBn9FRQWrV69mZUYGVSdOoPz8aElMxD52LPZ+/aRV310ohTMqipaoKFrGjkU1NGA5cIDWwkJWrV3LypUrCY+MZOb06cyYMYMYF89/5A02b97Miy++SFR0IHffP4KeUd7d2vRFJpNi0pQE+vQN5Z9L9/HMM8/w/PPP079/f0+XdkGGC/5du3bx4dKl5OXlgdbYExNpmTgRe//+4Ofn6fLEVdKBgbQOG0brsGE02u1YDhzAnp/Ph0uX8uGHHzJ8+HBuv/12hg8f7ulSXWLPnj288sor9IoP4e77hmA14F233qRPYhgPfH8Ei9/I59ln/4sXX/wNsbGxni7rPIYJ/ubmZt555x0+X7YMgoJoHj+eluHDZRSOL7NYsKekYE9JQdXW4pefT35+Pvk//znXX389999/f7caiXEurTW//e0rhIRauPO7gyX0vURIiJUF96Sy+I0d/OnPf+KXv/ilp0s6jyGuftXW1vL4j3/M559/TktaGrUPP0zz5MnGC/3mZvz9/Zk7dy7+/v7QbJxVL3VoKC2TJlH7ve/RfM01rFi5kkcee4zKykpPl3bF9u/fz/HjFUycHE9gUPc+W21usp/12Wxusnu6pKvSMyqQtPQY8rfne+VKX4YI/uzsbEpLSmi47ba2tWutxpyTRDU3M2PGDB566CFmzJhxeopmQ/Hzo3n6dOrvvJMTx4+zYcMGT1d0xXbt2gVAUr/u34BpanKc9dlsaur+az4l9QvH6XSyd+9eT5dyHkN09ezfvx/MZuyJiZ4uxaO0zUZGRgYAGRkZ6NBQD1fkOY74eLDZ2j4b3VTHnPEV5Q2EdpOFzy/G39981mczLLz7d1sdL6sH8Mq5/Q3R4h89ejQ4nQR+8gnYu/cp5FWx2WhqamLZsmU0tU8cZ0hOJwGffQbNzaSnn7c4UbeRmpqK1erH5g3HcDq691KXNn/LWZXwCdsAABsrSURBVJ9Nm3/3bpM2N9nJ21pOr169iI6O9nQ55zFE8I8dO5Z//+EPsRQVEbJ4MZZ9+0DWhDUerbEcOEDw4sX47dvHokWLmDJliqerumI2m43vfe9hDhZVs3rlQU+XI9o5nZp/Lt1HVWUTP/jBDzxdzgV176/VyzBz5kxCQ0N56+23Kfv4Y5xxcTROnowjMVFuzvJ1WmM+cgT/rCzMxcVExcRw3xNPMGnSJE9XdtVmzpzJoUOH+OKLL7Dbncy8IRmLxRDtOa/U1Gjn04/2sX9fFQ8//LDXDhs2TPBDW8s/PT2dNWvW8I/33qPqgw8gIoKmkSNpHTpUbtryNY2NWAsKsG3fjjpxgrCICO76wQ+YPn06fj50z8aiRYuwWq188sknlJXWc9udgwgNM2g3ngeVl9Wz9P091Na08PDDDzNnzhxPl3RRhgp+ALPZzIwZM5g8eTIbN25k+YoV7FmzBv9162gdOJCW4cNx9O0LBpvnxWdojfnwYfx27MC6dy/Y7QwYOJDZd93FpEmTfHKlL7PZzH333ceAAQP4wx9+z+t/zGParETSRsWgTHI26252u5ONWcVsWFdMaGgYzz//C6+fq99wwd/BarUydepUpk6dytGjR1mxYgWZa9bQsHs3hITQnJpK69ChOGXGx27BVFmJX0EBtp07obYW/4AArps5k1mzZpGUlOTp8rrEhAkTSExM5NVXX+XLzwrYse04c27uT1S0TOHgLkcO1fDl5wc4UdHAtddey4MPPtgtFmg3bPCfKSEhgYceeoh7772XnJwc1qxZw9acHGzZ2ThjY2kZOpTW1FS0l8+4ZzhNTfjt2oWtoABTSQlKKUampTHtuusYM2aMT7buL6VXr148++yzZGZm8tZbf+Uvr+aRPjaOyVP74B8gv+6uUlPTTObKQ+zcUUFUVBQ///kTjBo1ytNldZp8Es5gtVqZMGECEyZMoKamhqysLFavWcPBjAz816yhtX9/WocNw56cLF1BnuJ0Yj50COuOHfjt3w92O3369mX6Aw8wefJkIiIiPF2hxymlmD59Ounp6bz77rusWrWKgvwTTJmWQNroWEzS/XPFWlscbNpwjE3rjwEm7rjjDm677ba2O+G7EQn+iwgLC2Pu3LnMnTuXQ4cOkZmZSebatdTt3QvBwTQPH05LWhpaFgbvEqquDr/t2/Hfvh1qawkMDmbqrFlMnz6d5ORkmYL4AsLCwvjhD3/I7NmzeeONN/jq813kflPGjNlJJCV7f3eEN9Fas3PHCdasOkxNTRMTJkzgvvvu67azvUrwd0JiYiKLFi1i4cKFbN26lZWrVpG7aRO2zZtpHTCAlrS0tgvCEj6upTXm4mKsubn47dsHDgfDR4zg+lmzGDNmjE+NzHGn5ORknn/+eTZt2sRbb73Fu28XMHBQJDOuTyKyR/edpK6rHCs+xaqvDlJ8tJakpCSefPIhhgwZ4umyrooE/2Xw8/Nj3LhxjBs3jrKyMpYvX87KjAwa9u7FGRND07hx2FNSvLYbyBETg/n48bbH0dE4vLW1ojWWffvw37wZU2kp/oGBzJwzh9mzZ3fLha29gVKKCRMmkJ6ezueff86HHy7hz/+bx7iJvZg4OUFm9ryA+roWMjMOsz23nLCwMH70ox9x3XXX+cSiPkq76Q5WpVQC8DcgBtDA61rr3yulIoEPgETgEDBfa33y2/aVnp6uc3Jy3FLn1WpubiYrK4uPPvmE0mPHICKCxrFjaR02zCvX4g18910AGu6+28OVXIDTid/Onfhv3oyqrCQ6Jobbbr2VKVOmdLs+VG9XVVXF3/72N9auXUtomD8zrk9k8JAeHusy+9tf8zly6F+zWPZJDOXeRZ65+cnp1Gz9ppSvM4/S2uLgpptuZv78+V6/nOKFKKW2aq3Pm5fEnS1+O/BTrXWuUioE2KqUWgXcD6zWWr+glHoaeBp4yo11uJXNZmPGjBlMmzaN7OxsPly6lKLlywnYvJnGSZNoTU312jMAr6E1lj17CMjKQlVV0ScxkTvuv58JEyb4ROvKG0VGRvL4449z/fXX8/rrf+bjJXvoPzCSG+YmExZu3C/Z8rI6vvj0ACXHTjF8+HAefvhh4uPjPV2Wy7kt+LXWpUBp++NTSqndQG9gHjC1/W2LgbV04+DvYDKZGD9+POPGjSM3N5e/v/MOh5Ytwz87m8bJk9tW+JJrAOcxHzxIwNq1mMrLiU9IYOH3v8+YMWPkYm0XGTx4MC+//ApffPEF7777Dn/+321MndGH9DFxhhr909rqIGvtUTZvOEZISAhPPPEEEydO9NnPYZf08SulEoE0IBuIaf9SACijrSvoQts8DDwM0KdPH/cX6SJKKUaPHk1aWhobN27knXffpeyjj3D07Uvjddfh9MJl2DzBVFGB/5o1WIqK6BkdzT2PP861114rLXwPMJvN3HzzzYwdO5bX/vQaK7/cxt5dldx06wDCu6j1HxsbTHlp2zTGMXFBxMYGd8lxAUpL6vj0o32cqGhg2rRpPPDAA4T4+Gg9t/Xxnz6AUsHA18DzWuuPlVLVWuvwM14/qbX+1sHX3tzHfyl2u52VK1fyj/feo66ujpahQ9tW//LQB8vTffyqvh5bVhbW7dsJCAxkwfz5zJkzR0boeAmtNZmZmbzxxl9wajvXz0li2IjoLmn5/u2v+QBd1rfvdGo2rS/m68wjhIWF8eijj5GWltYlx+4qnujjRynlB3wEvKu1/rj96XKlVJzWulQpFQccd2cNnmaxWJgzZw6TJ09m6dKlfL5sGba9e2kcO5aWMWOMs8C73Y41J4eATZtQdjtzbryR+fPnE2rgxWC8UcfNX0OHDuX3v/8dn328m6LCaubc1B+rzXfOxk6dauGfS/dy+GANEyZM4N/+7d98vpV/JrcFv2prIrwJ7NZa//aMlz4D7gNeaP/zU3fV4E2Cg4O5//77mT17Nm8vXszmrCz8t2+ncfJkWocM8d3+//YLt4Fffw3V1Yy+5hoeuP9+GZbp5WJiYnj22edYunQp77//PqUl9dw6P4WY2O4/g21R4Uk+/Xg/rS2aRx55hGnTpvlsX/7FuLPFPxFYCOxQSm1rf+4/aAv8JUqpB4HDwHw31uB1YmNjefqpp9i5cydv/vWvFC1bhi0nh8brrmu7CcyHmIuLCcjMxFRSQp++fXnwxz9mxIgRni5LdJLZbObOO+8kNTWVV155mbf/ks+cm/sxbIT3rSjVGVprNqwr5uvMw/TuHc+TTz7Zra4fupI7R/WsBy72NTrdXcftLoYMGcLLL71EVlYWi//+d6reew97v340TZ3a7WcENVVWYvv6a/z27SM8IoKFjzzC1KlT5cJtNzVs2DB+97vf85vfvMinH+2mtKSO6bMSMZu7zzDl5mY7n3+ynz27Kpk0aRI/+tGPDH1viNy560Emk4kpU6Ywfvx4li1bxpKlS7H89a+0DBtG87XXdrt5gFR9Pbb167Fu347NauXWu+5i3rx5hv4F8xXh4eH81389y1tvvcUXX3xBRXkDt945iIBuMONn9ckmlvxjNycqGnnggQe4+eabDde1cy7v/79mAFarlVtvvZUZM2awdOlSvvjyS2y7d9OUnk7zuHHevyh6SwvWLVsI2LIF5XAwe/Zs5s+f3y3mJRedZ7FY+N73vkdycjKvvvoqb72ez513D6JHT++9o/XI4RqWvr8XhYVf/OIX0tXYToLfi4SGhrJo0SJuvPFG3n33XdatW4dt+3YaJ06kNS3N++4Adjrx27GDgKwsqKtj7Pjx3LtwIb169fJ0ZcKNpk+fTlxcHP/937/m7b/s4I7vDqJP3zBPl3WegvwKPv9kPzExMfyf//OfMqDgDF6WJALaRlT85Cc/4eWXX2ZIcjIBq1YR8tZbmA8e9HRpp5mPHCF48WICvvqKgb1788ILL/D0U09J6BtEamoqL7/8ChERUfxj8U52FVR4uqTTtNZszCrmn0v3kpIyiBdf/I2E/jmkxe/F+vfvz3PPPkt2djZvvvUWFR98QOuAATTNnIn20Ph3VVeHf0YGfnv2ENmjB4t8/NZ2cXExMTG8+OKL/PrXz/PJh3toaLCTPibOozVprclYfpDsTSVce+21PProo3Jz4AVI8Hs5pRTjxo1j9OjRfPbZZ7y/ZAnWN9+kYcqUtu6frgpcrfHLzydwzRrMDge3L1jAd77zHUMubyj+JSQkhF/96r946aXfsHxZDs1NdiZOTvBILU6n5ovPCtmeW87cuXNZtGgRJm/rHvUSEvzdhJ+fH7fddhuTJk3ij6++Sv7KlVh376bh5pvdPvpH1dcT+PnnmA8dYvCQIfz7D38op87iNKvVylNPPc0f/vAH1mSsA+jy8NdOzbJP95Ofd5w777yTBQsWyFnot5Dg72ZiYmL41S9/SWZmJn9+/XXMb71F/U034UhKcsvxzEeOEPTZZ1iam3noBz9g1qxZ0ooS57FYLDz++OMArMlYh9Vq5ppxXXO9R2vNiq+KyM87zoIFC1iwYEGXHLc7k9/gbqhjPpXfvvIK8T16ELRkCX55eS4/jl9BAUHvv09MSAgvv/QSs2fPltAXF2UymXjssccYO3YMK74sYt+eyi45bvbGEnKyS5k3bx533nlnlxyzu5Pf4m4sPj6eV15+mdGjRhGwYgXW7GyX7dsvL4+AZcsYOmQI//PKKyQmJrps38J3mc1mfvKTn5KcnMSnH+2n8kSjW493qKiazFWHGDt2LPfff79073SSBH83Z7PZePrpp5kwcWLb/PY7d171Pi379hGwYgWj09P5+f/9v91yyTnhOW2fyWewWv359ON9aKd7pn5vbrbz6cf7iYuL47HHHpPQvwwS/D7Az8+Pn/z4xwxOTSVw+XJMx698pmtTVRVBX3xBcr9+PPXkk1itVhdWKowiOjqaRYsepKT4FNvyyt1yjKy1RzlV28yjjz4mjZPLJMHvIywWC0/+7GeEBAYSsGIFXOECO/6rVuFvNvPM009L6IurMnXqVAYNGsS6NUdxurjVX1/fyjebS5k2bRopKSku3bcRSPD7kIiICBbefTfmY8ew7Nt32dubDx7EcvAgdy1YQFQ3nyFUeJ5Sinnz5nGqtpmiwpMu3XfB9uM4HE7mzZvn0v0ahQS/j5k+fTpRMTHYcnMve1vb1q2ERURwww03uKEyYUTp6ekEBgWyZ7drR/js3V1FUlIifX1sDYuuIsHvY8xmMzOmTcN8+DCqpqbT26mGBixFRUy/7jq5xV24jJ+fH4l9+1JZ4drRPSdONNK//wCX7tNIJPh90Pjx4wGwHD7c6W3Mhw+D08m4cePcVZYwqJiYWGpqWly2v9YWBw31LcTExLhsn0Yjwe+DEhISCAoJwXz0aKe3sRw9itVmo1+/fm6sTBiR3W7HYnFd1Jjb92W32122T6OR4PdBSin6Jydjqej8VLnmigoSExNleUThcrW1tfj7u+5zZTIpbDYLtbW1Ltun0Ujw+6iEhARMlZWdHtZpqaqiT4JnZlUUvktrTVHRAaJiXDvOPiomkKKiIpfu00gk+H1UbGwstLaiGjtxUa21FV1fL32mwuVKS0s5daqOXr2DXbrfXr2DKSo6QEuL664dGIkEv4/q2bMnAKoTp8Om9vd0bCOEq2zduhWA5H4RLt1vcr9wWlpaKSgocOl+jUKC30dFRkYCYKqru+R7Vft7OrYRwlVycnLoGRVIRKS/S/fbNykMPz8zOTk5Lt2vUUjw+6iIiLYWlqqvP+t5R0wMjnO6dDre07GNEK7Q0NBAQUEB/Qe6/nPl52cmMTmMb77Zgr7C6UmMTILfR4WHhwPnB3/zjBk0z5hx1nOm9vd0bCOEK+zYsQOHw8GAge45kxyQEklFxQmOHTvmlv37Mgl+H+Xn50dAYGDnunrq6zGbzYS4eQlHYSy7d+/GbDbRO949n6u+iaGnjyMujwS/D4uIiDjdf/9tVF0doeHhMp+5cKkDBw4QExeExc89MRPZIwB/fwsHDhxwy/59mQS/D4uJjsbciVE95poaomU2TuFiVSerCA1139TeSilCQm2cPOnamT+NQILfh0VHR2OuqbnkTVzm2lpiZQy/cLGG+nps/ha3HsPmb6b+nOtY4tIk+H1Y79690Y2NqIaGi7+ppQVqaoiPj++6woQhhIaG0tjQ6tZjNDbYCQ0NdesxfJEEvw/rmKv825ZiNLfP55Mg0zUIF4uKiqbyRJPb9m9vdVJT3SSLBl0BCX4f1jHTprmk5KLv6Xht4MCBXVKTMI4RI0ZQeaKBqkrXzsXf4WBRNXa7k5EjR7pl/77MI8GvlJqtlNqrlCpUSj3tiRqMIDg4mN4JCVi+ZXpm89Gj9IyKkrt2hcuNGTMGgPxtFz/jvBr5244TEBDA0KFD3bJ/X9blwa+UMgN/BG4AUoG7lFKpXV2HUaSNGIGluBguNHe504n1yBFGjhjR9YUJnxcTE8P48eP5ZnMpjY2unTv/eHk9e3adYO7cubJi3BXwRIt/DFCotS7SWrcA7wOyYrKbjB49Gux2LIcOnfeaubgY3dTEqFGjur4wYQh33nknLS0O1mVeejW42NhgYmMvPYun1pqM5Qfx9/fnpptuckWZhuOJ4O8NnNn3UNz+3FmUUg8rpXKUUjkVl7GgiDjb0KFDsfn7Y9m//7zXLPv3Y7ZYSEtL80BlwggSExOZM2cOOVtKOXr42+8pmTUnmVlzki+5z/xtxyk6UM3ChffKiJ4r5LUXd7XWr2ut07XW6XLV/sr5+flxTXo61v37wen81wtaY9u3j5EjRxIQEOC5AoXPu+eee+jZsyeffbKfpqar6/I5WdXEyi8Pkpo6mNmzZ7uoQuPxRPAfA84cOxjf/pxwkwkTJkBDw1lr8JrKyqCmhgntC7ML4S4BAQH89KdPUFPdzBefFl7xbJoOu5NPPtyLxWLlsccex2Ty2nar1/PEv9w3wAClVJJSygosAD7zQB2GMWrUKPysVvz27j39nN/evZjM5tMjL4Rwp0GDBnHPPfewe+cJtm4pvaJ9rFpxkJJjp3jkkUdltbir1OXBr7W2Az8CVgC7gSVa651dXYeR+Pv7k5aWhrWw8PT0DdbCQoYMGSIzcoouc8stt5Cens6q5Yc4dvTUZW27c0cFOdml3HzzzYwbN85NFRqHR86VtNZfaq0Haq37aa2f90QNRnNNejrU1mKqqEBVV6NOnGh7ToguYjKZePzxx4mM7MHHH+7t9BDPqspGvvj0ACkpKdx7771urtIYpJPMIDrubrQcPnx6aKcM4xRdLTg4mJ/97GfUnWrhi0/3X7K/32538vGSvVitNp544gksFvdO+mYUEvwGERUVRVRMDOYjRzAfPUpIWBi9e583ilYItxs4cCALF97Lnl2Vl7yrd92aI5SV1vHoo4/JnDwuJMFvIKmDBuFXVoa1rIzBKSmy8IrwmJtvvplBg1LIWH6IulMtF3xPaUkdmzccY9q0aTIIwcUk+A0kKSkJTp2CykqSky99o4wQ7mIymXjkkUex2zWrVx0673WtNcu/KCI0NJRFixZ1fYE+ToLfQM6cc1/m3xee1rt3b268cS4F249TXnb2EqF7dlVy7Ggtd999D8HBl57GQVweCX4DiYuLO/04NjbWg5UI0eb2228nMDCQ9V//6+ZCrTXrvy4mPr4306ZN82B1vkuC30DOnHpZpmEW3iA4OJiZM2exd3cVNTXNABw5VEt5WR3z5t2C2Wz2cIW+SYLfQPz9/YmOiSE8IoKwsDBPlyMEADfccANOp2ZH+wifbbllBAUFMnnyZA9X5rtkUKyBKKX402uvobWWlpTwGjExMQwcOIC9u0sZP6k3+/dVM37cJGw2m6dL81nS4jcYk8kkoS+8zpgxYyktqWP/3iqaGltl+KabSfALITwuNbVtEb6NWcUADB482JPl+DwJfiGEx/Xr14+AAH9KjtURHx9PeHi4p0vyadLHL4TwOJvNxmuv/Yna2loZcdYFJPiFEF4hPDxcWvpdRLp6hBDCYCT4hRDCYCT4hRDCYCT4hRDCYCT4hRDCYCT4hRDCYCT4hRDCYNSlFjv2BkqpCuCwp+vwIT2BE54uQogLkM+ma/XVWp+3WHG3CH7hWkqpHK11uqfrEOJc8tnsGtLVI4QQBiPBL4QQBiPBb0yve7oAIS5CPptdQPr4hRDCYKTFL4QQBiPBL4QQBiPBbyBKqdlKqb1KqUKl1NOerkeIDkqpvyqljiulCjxdixFI8BuEUsoM/BG4AUgF7lJKpXq2KiFOexuY7ekijEKC3zjGAIVa6yKtdQvwPjDPwzUJAYDWeh1Q5ek6jEKC3zh6A0fP+Lm4/TkhhMFI8AshhMFI8BvHMSDhjJ/j258TQhiMBL9xfAMMUEolKaWswALgMw/XJITwAAl+g9Ba24EfASuA3cASrfVOz1YlRBul1HvAJiBFKVWslHrQ0zX5MpmyQQghDEZa/EIIYTAS/EIIYTAS/EIIYTAS/EIIYTAS/EIIYTAS/MJQlFL/Rym1UymVr5TappQa64J93uyq2U6VUnWu2I8Q30aGcwrDUEqNB34LTNVaNyulegJWrXVJJ7a1tN8L4e4a67TWwe4+jjA2afELI4kDTmitmwG01ie01iVKqUPtXwIopdKVUmvbH/9SKfV3pdQG4O9Kqc1KqSEdO1NKrW1///1Kqf9VSoUppQ4rpUztrwcppY4qpfyUUv2UUsuVUluVUllKqUHt70lSSm1SSu1QSj3Xxf8ewqAk+IWRrAQSlFL7lFKvKqWmdGKbVGCG1vou4ANgPoBSKg6I01rndLxRa10DbAM69jsXWKG1bqVtEfFHtNajgSeAV9vf83vgNa31MKD0qv+GQnSCBL8wDK11HTAaeBioAD5QSt1/ic0+01o3tj9eAtze/ng+sPQC7/8AuLP98YL2YwQDE4APlVLbgD/TdvYBMBF4r/3x3y/rLyTEFbJ4ugAhupLW2gGsBdYqpXYA9wF2/tUI8j9nk/oztj2mlKpUSg2nLdx/cIFDfAb8WikVSduXTCYQBFRrrUderKwr/OsIcUWkxS8MQymVopQacMZTI4HDwCHaQhrgtkvs5gPgSSBMa51/7ovtZxXf0NaFs0xr7dBa1wIHlVJ3tNehlFIj2jfZQNuZAcDdl/+3EuLySfALIwkGFiuldiml8mnrv/8l8Cvg90qpHMBxiX0spS2ol3zLez4A7mn/s8PdwINKqe3ATv617OVjwL+3n33IimiiS8hwTiGEMBhp8QshhMFI8AshhMFI8AshhMFI8AshhMFI8AshhMFI8AshhMFI8AshhMH8f0DDNy+59zDvAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 920
        },
        "id": "3btEjveBZoQl",
        "outputId": "b7abba12-e7fd-456e-bf36-45fe1a6bcc5d"
      },
      "source": [
        "sns.pairplot(df,hue='Survived',vars=['Age', 'Pclass', 'SibSp',\t'Parch', 'Fare' ],palette='YlOrRd')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fadee1687d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 120
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 951.875x900 with 30 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 330
        },
        "id": "qMg9XxkbavhS",
        "outputId": "dd13d64a-b389-40f6-be3b-8be8d81a4392"
      },
      "source": [
        "sns.heatmap(df.corr(), annot=True, fmt='.2f', square=True, cmap=\"YlGn\")\n",
        "plt.title(\"Correaltion\", size=10)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4fyq9VsSeJNS"
      },
      "source": [
        "# Splitting the Data into Dependent and Indpendent variables"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DYe8GnRzkGIq",
        "outputId": "d4cf0c88-3ed6-469a-c4e2-9d27ddbe2163"
      },
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "le = LabelEncoder()\n",
        "df.Sex = le.fit_transform(df.Sex)\n",
        "df.Sex.unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 163
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cgCTV9DYeQe_"
      },
      "source": [
        "x = df.drop(['PassengerId',\t'Survived',\t'Ticket',\t'Name', 'Cabin','Embarked'], axis='columns')\n",
        "y = df['Survived']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "id": "QiLK5nc1ejlz",
        "outputId": "8f4c6854-3172-4aa7-b927-681ec8d9bfd4"
      },
      "source": [
        "x[:5]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pclass</th>\n",
              "      <th>Sex</th>\n",
              "      <th>Age</th>\n",
              "      <th>SibSp</th>\n",
              "      <th>Parch</th>\n",
              "      <th>Fare</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>22.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7.2500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>71.2833</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7.9250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>53.1000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>35.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>8.0500</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Pclass  Sex   Age  SibSp  Parch     Fare\n",
              "0       3    1  22.0      1      0   7.2500\n",
              "1       1    0  38.0      1      0  71.2833\n",
              "2       3    0  26.0      0      0   7.9250\n",
              "3       1    0  35.0      1      0  53.1000\n",
              "4       3    1  35.0      0      0   8.0500"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 165
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0qMS3VIIiDUA",
        "outputId": "a02c041e-4303-4ebc-96da-95bc23de4c6f"
      },
      "source": [
        "y[:5]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    0\n",
              "1    1\n",
              "2    1\n",
              "3    1\n",
              "4    0\n",
              "Name: Survived, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 167
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "drftnhMSiMcS"
      },
      "source": [
        "# Training and Testing the Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iaQJdDl3iV-l"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "xtrain, xtest, ytrain, ytest = train_test_split(x, y, test_size=0.25, random_state=20)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SLna7j9_ia3t",
        "outputId": "7b796ce6-ae4a-47b9-af2d-7a151847ea17"
      },
      "source": [
        "from sklearn.naive_bayes import GaussianNB\n",
        "gnb = GaussianNB()\n",
        "gnb.fit(xtrain, ytrain)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "GaussianNB(priors=None, var_smoothing=1e-09)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 218
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BxyaRQD-l3SH"
      },
      "source": [
        "# Prediction"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "COaK6Tjgiwwy",
        "outputId": "3ff046fd-5067-4722-c95d-a4fa0ca563af"
      },
      "source": [
        "ypred = gnb.predict(xtest)\n",
        "ypred"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0,\n",
              "       1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0,\n",
              "       1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0,\n",
              "       1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,\n",
              "       0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1,\n",
              "       0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0,\n",
              "       0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1,\n",
              "       0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0,\n",
              "       1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1,\n",
              "       0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0,\n",
              "       0, 0, 1])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 219
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q1MaM1mzl6ZN"
      },
      "source": [
        "# Confusion Matrix"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SgxZplPvi1pM",
        "outputId": "be932495-b754-476c-8346-64782daf39b4"
      },
      "source": [
        "from sklearn.metrics import confusion_matrix, classification_report,accuracy_score\n",
        "cm = confusion_matrix(ytest, ypred)\n",
        "cm"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[117,  21],\n",
              "       [ 20,  65]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 220
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "WYrqIulGi7un",
        "outputId": "047d85f3-8c74-42c5-fa96-23b76a8766a8"
      },
      "source": [
        "sns.heatmap(pd.DataFrame(cm), annot=True, cmap=\"RdYlBu\" ,fmt='g')\n",
        "plt.title('Confusion matrix', y=5.1)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0ZxQ5VIWl9-3"
      },
      "source": [
        "# Accuracy Score"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EQ2rsXfTi-vm",
        "outputId": "8bf65434-9dd2-4e3e-a129-49cf75797ab8"
      },
      "source": [
        "ac = accuracy_score(ytest, ypred)\n",
        "print(\"Accuracy score =\", ac)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Accuracy score = 0.8161434977578476\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KjUMFUzLly9n"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    }
  ]
}