Titanic_Survival_Prediction_using_Machine_Learning.ipynb

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      "cell_type": "markdown",
      "source": [
        "## Titanic Survival Prediction using Machine Learning\n",
        "\n",
        "- Logistic Regression model "
      ],
      "metadata": {
        "id": "5TMHxu_2BvqU"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Importing Dependencies "
      ],
      "metadata": {
        "id": "o9MiCs-qB91r"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score"
      ],
      "metadata": {
        "id": "MaKlciqGB8MG"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Data Collection and Preprocessing"
      ],
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      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"train.csv\")\n",
        "# load the data from csv file in pandas dataframe"
      ],
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        "id": "4TFRQt7CCrPB"
      },
      "execution_count": 8,
      "outputs": []
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      "source": [
        "df.head()"
      ],
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      "execution_count": 9,
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              "   PassengerId  Survived  Pclass  \\\n",
              "0            1         0       3   \n",
              "1            2         1       1   \n",
              "2            3         1       3   \n",
              "3            4         1       1   \n",
              "4            5         0       3   \n",
              "\n",
              "                                                Name     Sex   Age  SibSp  \\\n",
              "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
              "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
              "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
              "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
              "4                           Allen, Mr. William Henry    male  35.0      0   \n",
              "\n",
              "   Parch            Ticket     Fare Cabin Embarked  \n",
              "0      0         A/5 21171   7.2500   NaN        S  \n",
              "1      0          PC 17599  71.2833   C85        C  \n",
              "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
              "3      0            113803  53.1000  C123        S  \n",
              "4      0            373450   8.0500   NaN        S  "
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              "      <td>0</td>\n",
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        "df.shape\n",
        "# rows and columns in the dataset"
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            "text/plain": [
              "(891, 12)"
            ]
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          "execution_count": 10
        }
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      "cell_type": "code",
      "source": [
        "df.dtypes"
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        "outputId": "c639cb8f-f8b5-4227-8a41-ee5f3271e6fe"
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      "execution_count": 11,
      "outputs": [
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          "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": {},
          "execution_count": 11
        }
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      "cell_type": "code",
      "source": [
        "# information about the data\n",
        "df.info()"
      ],
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        "id": "b8fm1J5TCrFC",
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          "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"
          ]
        }
      ]
    },
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      "cell_type": "code",
      "source": [
        "# desecribing the dataset\n",
        "\n",
        "df.describe()"
      ],
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      "execution_count": 13,
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            "text/plain": [
              "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
              "count   891.000000  891.000000  891.000000  714.000000  891.000000   \n",
              "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
              "std     257.353842    0.486592    0.836071   14.526497    1.102743   \n",
              "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
              "25%     223.500000    0.000000    2.000000   20.125000    0.000000   \n",
              "50%     446.000000    0.000000    3.000000   28.000000    0.000000   \n",
              "75%     668.500000    1.000000    3.000000   38.000000    1.000000   \n",
              "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
              "\n",
              "            Parch        Fare  \n",
              "count  891.000000  891.000000  \n",
              "mean     0.381594   32.204208  \n",
              "std      0.806057   49.693429  \n",
              "min      0.000000    0.000000  \n",
              "25%      0.000000    7.910400  \n",
              "50%      0.000000   14.454200  \n",
              "75%      0.000000   31.000000  \n",
              "max      6.000000  512.329200  "
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              "\n",
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              "  <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",
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              "      <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",
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              "      <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",
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              "      <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",
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              "    <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",
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              "    <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",
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              "    <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",
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              "    <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",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
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              "      </button>\n",
              "      \n",
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              "    .colab-df-container {\n",
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              "    .colab-df-convert {\n",
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              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "\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",
              "    [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-da461a8e-04a5-4b48-be90-dd9d5fb431f8 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-da461a8e-04a5-4b48-be90-dd9d5fb431f8');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# check the number of missing values in each columns\n",
        "\n",
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8yJ3lF7DCq_Y",
        "outputId": "0a1e0341-6915-4ada-c9aa-0fe8d24ace6c"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PassengerId      0\n",
              "Survived         0\n",
              "Pclass           0\n",
              "Name             0\n",
              "Sex              0\n",
              "Age            177\n",
              "SibSp            0\n",
              "Parch            0\n",
              "Ticket           0\n",
              "Fare             0\n",
              "Cabin          687\n",
              "Embarked         2\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Handling the missing values"
      ],
      "metadata": {
        "id": "2We9AKmtFd3Q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.drop(columns = 'Cabin',axis = 1)"
      ],
      "metadata": {
        "id": "gSiCcE13Cq8e"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lbPPRQw2Cq4T",
        "outputId": "57bce726-5ce4-4bc1-a9ed-d557830d3870"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['PassengerId', 'Survived', 'Pclass', 'Name', 'Sex', 'Age', 'SibSp',\n",
              "       'Parch', 'Ticket', 'Fare', 'Embarked'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# replacing the missing values in age by mean value in age column\n",
        "\n",
        "df['Age'].fillna(df['Age'].mean(), inplace = True)\n",
        "\n",
        "df['Age']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5DIF6ijuFrGD",
        "outputId": "fa364400-771e-4129-c558-55c527be13e0"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      22.000000\n",
              "1      38.000000\n",
              "2      26.000000\n",
              "3      35.000000\n",
              "4      35.000000\n",
              "         ...    \n",
              "886    27.000000\n",
              "887    19.000000\n",
              "888    29.699118\n",
              "889    26.000000\n",
              "890    32.000000\n",
              "Name: Age, Length: 891, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CocfrVZeGPhI",
        "outputId": "bbd97092-db78-411e-cfe5-5754cabf271d"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PassengerId    0\n",
              "Survived       0\n",
              "Pclass         0\n",
              "Name           0\n",
              "Sex            0\n",
              "Age            0\n",
              "SibSp          0\n",
              "Parch          0\n",
              "Ticket         0\n",
              "Fare           0\n",
              "Embarked       2\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# finding the mode value of \"Embarked\" columns\n",
        "\n",
        "print(df['Embarked'].mode())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0bm7sircGySo",
        "outputId": "646d0aec-b27c-4e43-cd0a-383ea11cc4e5"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    S\n",
            "dtype: object\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Embarked'].fillna(df['Embarked'].mode()[0], inplace = True)\n",
        "\n"
      ],
      "metadata": {
        "id": "cXaEjPlOHB_5"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hv3WDXbbHJM5",
        "outputId": "23da6c33-aa39-4301-8721-e5d5d3266346"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PassengerId    0\n",
              "Survived       0\n",
              "Pclass         0\n",
              "Name           0\n",
              "Sex            0\n",
              "Age            0\n",
              "SibSp          0\n",
              "Parch          0\n",
              "Ticket         0\n",
              "Fare           0\n",
              "Embarked       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Data Analysis\n"
      ],
      "metadata": {
        "id": "VLpgKmaSIQgV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe() \n",
        "\n",
        "#statistical measures about the data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "eTgfh1grHLVh",
        "outputId": "4012c044-70b3-41d6-9a01-07dbea187ec4"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
              "count   891.000000  891.000000  891.000000  891.000000  891.000000   \n",
              "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
              "std     257.353842    0.486592    0.836071   13.002015    1.102743   \n",
              "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
              "25%     223.500000    0.000000    2.000000   22.000000    0.000000   \n",
              "50%     446.000000    0.000000    3.000000   29.699118    0.000000   \n",
              "75%     668.500000    1.000000    3.000000   35.000000    1.000000   \n",
              "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
              "\n",
              "            Parch        Fare  \n",
              "count  891.000000  891.000000  \n",
              "mean     0.381594   32.204208  \n",
              "std      0.806057   49.693429  \n",
              "min      0.000000    0.000000  \n",
              "25%      0.000000    7.910400  \n",
              "50%      0.000000   14.454200  \n",
              "75%      0.000000   31.000000  \n",
              "max      6.000000  512.329200  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-2eb2e485-028c-4b31-a9d0-9b81f44c0510\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "    .dataframe tbody tr th {\n",
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              "    .dataframe thead th {\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>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>891.000000</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>13.002015</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>22.000000</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>29.699118</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>35.000000</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>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2eb2e485-028c-4b31-a9d0-9b81f44c0510')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
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              "    .colab-df-convert {\n",
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              "\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",
              "    [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",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-2eb2e485-028c-4b31-a9d0-9b81f44c0510 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-2eb2e485-028c-4b31-a9d0-9b81f44c0510');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# finding the number of people survived and not survived\n",
        "\n",
        "df['Survived'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XZD5pMBaIUx2",
        "outputId": "3825fdba-7cc1-49b8-83c9-f7862acaa928"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    549\n",
              "1    342\n",
              "Name: Survived, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Measure of dispersion \n",
        "\n",
        "df.var()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Zwk3jKp68tlh",
        "outputId": "69546f38-b85f-4e1c-ff07-a973ddab5d9f"
      },
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-76-27fb041735f4>:3: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError.  Select only valid columns before calling the reduction.\n",
            "  df.var()\n"
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          "data": {
            "text/plain": [
              "PassengerId    66231.000000\n",
              "Survived           0.236772\n",
              "Pclass             0.699015\n",
              "Sex                0.228475\n",
              "Age              169.052400\n",
              "SibSp              1.216043\n",
              "Parch              0.649728\n",
              "Fare            2469.436846\n",
              "Embarked           0.404081\n",
              "dtype: float64"
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        "id": "w9HRvaJL-Cap",
        "outputId": "6b08c39d-f915-46ab-9b46-5ef1787df0e0"
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      "execution_count": 85,
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              "              PassengerId  Survived     Pclass       Sex         Age  \\\n",
              "PassengerId  66231.000000 -0.626966  -7.561798 -5.282022  111.113042   \n",
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        "\n",
        "np.mean(df, axis = 0)"
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              "PassengerId    446.000000\n",
              "Survived         0.383838\n",
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              "      <td>NaN</td>\n",
              "      <td>de Pelsmaeker, Mr. Alfons</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>888</th>\n",
              "      <td>889</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>del Carlo, Mr. Sebastiano</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>889</th>\n",
              "      <td>890</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>van Billiard, Mr. Austin Blyler</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>890</th>\n",
              "      <td>891</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>van Melkebeke, Mr. Philemon</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>891 rows × 11 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-27e1dd5d-5899-47f0-951f-d1632f1d7b88')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-27e1dd5d-5899-47f0-951f-d1632f1d7b88 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-27e1dd5d-5899-47f0-951f-d1632f1d7b88');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 5 Point Summary "
      ],
      "metadata": {
        "id": "Xbt8T2dz9bta"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Minimum value is: {}\".format(df['Survived'].min())) # zeroth Percentile or minimum value\n",
        "print(\"1st quartile is: {}\".format(np.percentile(df['Survived'], 25))) # 1st quartile\n",
        "print(\"Median is: {}\".format(np.percentile(df['Survived'], 50))) # 2nd quartile or median\n",
        "print(\"3rd quartile is: {}\".format(np.percentile(df['Survived'], 75))) # 3rd quartile\n",
        "print(\"Maximum value is: {}\".format(df['Survived'].max())) # 100th Percentile or maximum value"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ap9kzFU69a1Y",
        "outputId": "6b616bd7-5e34-4d62-98e9-53261cdffc21"
      },
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Minimum value is: 0\n",
            "1st quartile is: 0.0\n",
            "Median is: 0.0\n",
            "3rd quartile is: 1.0\n",
            "Maximum value is: 1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data Visualization "
      ],
      "metadata": {
        "id": "c-yDSv0MI8yn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Box plot\n",
        "\n",
        "sns.set(rc={'figure.figsize':(15,5)})\n",
        "sns.boxplot(data=df['Age'], orient=\"h\")\n",
        "#since age column contains outliers so it is better to use median for filling NAN values but the median of\n",
        "#age is NAN itself so using mean of age to fill NAN values\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 339
        },
        "id": "wzoq-0yS8byD",
        "outputId": "3fdd8fb8-2714-422f-bd8c-b26e69785171"
      },
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:>"
            ]
          },
          "metadata": {},
          "execution_count": 74
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(df.Survived)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "id": "r2Q15u44Ilzp",
        "outputId": "53f18959-86eb-429e-ed7c-b4a6f94e431f"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: 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",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='Survived', ylabel='count'>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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vKI3KUNCiV1UPAM8D1gNTwEVJXv8om22qqv9p7YuBV7X2acAlc4y/CHh1a5/ePuNQ4IXAJ5JcC/wN07MWgBcBH2/tC/bk+0iPxZJxFyAtBFX1IHAVcFWS64G1wA4e+h+nQ3ba5Huztt2W5O4kz2L6D/9vz/ERm4A/S3Ik0wF0BfBE4L6qOm5XZe3dt5H2njMFLXpJnp5k9ayu44DbgFuZ/gMO8BuPspuLgLcCh1XVdTuvbLORrzJ9WOjTVfVgVX0H+K8kp7Y6kuTZbZMvMT2jAHjtHn8paS8ZChIcCmxMclOS65g+X/B24B3AOUkmgQcfZR+XMP1H/OLdjLkIeF17n/FaYF2SrwM38tBPob4ROKvNWvwlPM0bL0mVJHXOFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1/w/4gcjVwj04NgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(df.Sex)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 353
        },
        "id": "GbY9oWSJJU1Y",
        "outputId": "b21e4f7a-43e3-4a32-be5a-acabb1eabd9d"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: 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",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='Sex', ylabel='count'>"
            ]
          },
          "metadata": {},
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEICAYAAACwDehOAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAAsTAAALEwEAmpwYAAARfklEQVR4nO3de7DndV3H8ecLFjVRuchpo11sTRkduihwQkybMSkvVEKmaKksuNPWRGTZjWzKxkvZTQMrakfUxTGV0GRzLNsQb3nJs4EgoLGRxm4gxxtgjDjouz9+n/34Yzm7/Hbhe36Hc56Pmd/8vt/P9/P7/N5n9rv72u/nezmpKiRJAjhg2gVIkpYOQ0GS1BkKkqTOUJAkdYaCJKkzFCRJ3aChkOTQJBcn+UySa5M8McnhSbYmua69H9b6Jsl5SbYnuTLJcUPWJkm6uwx5n0KSzcCHq+oNSR4APBh4GfDlqnpNknOAw6rqt5OcDJwNnAw8ATi3qp6wt/GPOOKIWrdu3WD1S9JytG3bti9W1cxC2wYLhSSHAFcA31tjX5Lks8BTqurGJEcCH6iqxyT527b8tt377ek7Zmdna25ubpD6JWm5SrKtqmYX2jbk9NEjgXngTUkuT/KGJAcDq8f+ob8JWN2W1wA3jH1+R2u7iyQbk8wlmZufnx+wfElaeYYMhVXAccD5VXUs8H/AOeMd2hHEPh2qVNWmqpqtqtmZmQWPfiRJ+2nIUNgB7KiqT7T1ixmFxBfatBHt/ea2fSdw1Njn17Y2SdIiGSwUquom4IYkj2lNJwHXAFuA9a1tPXBJW94CnN6uQjoRuGVv5xMkSfe9VQOPfzbw1nbl0fXAmYyC6KIkG4DPA6e1vu9ldOXRduD21leStIgGDYWqugJY6Az3SQv0LeCsIeuRJO2ddzRLkjpDQZLUGQqSpG7oE81L3vG/eeG0S9AStO1PT592CdJUeKQgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVJnKEiSOkNBktQZCpKkzlCQJHWGgiSpMxQkSZ2hIEnqDAVJUmcoSJI6Q0GS1BkKkqTOUJAkdYaCJKkbNBSSfC7JVUmuSDLX2g5PsjXJde39sNaeJOcl2Z7kyiTHDVmbJOnuFuNI4Uer6vFVNdvWzwEuraqjgUvbOsAzgaPbayNw/iLUJkkaM43po1OAzW15M3DqWPuFNfJx4NAkR06hPklasYYOhQL+Jcm2JBtb2+qqurEt3wSsbstrgBvGPrujtd1Fko1J5pLMzc/PD1W3JK1IqwYe/8lVtTPJdwJbk3xmfGNVVZLalwGrahOwCWB2dnafPitJ2rtBjxSqamd7vxn4B+AE4Au7poXa+82t+07gqLGPr21tkqRFMlgoJDk4yUN3LQNPAz4NbAHWt27rgUva8hbg9HYV0onALWPTTJKkRTDk9NFq4B+S7Pqev6uqf07ySeCiJBuAzwOntf7vBU4GtgO3A2cOWJskaQGDhUJVXQ88boH2LwEnLdBewFlD1SNJumfe0SxJ6gwFSVJnKEiSOkNBktQZCpKkzlCQJHWGgiSpMxQkSZ2hIEnqDAVJUmcoSJI6Q0GS1BkKkqTOUJAkdYaCJKkzFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVJnKEiSusFDIcmBSS5P8p62/sgkn0iyPck7kjygtT+wrW9v29cNXZsk6a4W40jhJcC1Y+t/DLyuqh4NfAXY0No3AF9p7a9r/SRJi2jQUEiyFvgJ4A1tPcBTgYtbl83AqW35lLZO235S6y9JWiRDHyn8BfBbwLfa+sOBr1bVnW19B7CmLa8BbgBo229p/e8iycYkc0nm5ufnByxdklaewUIhyU8CN1fVtvty3KraVFWzVTU7MzNzXw4tSSveqgHHfhLwrCQnAw8CHgacCxyaZFU7GlgL7Gz9dwJHATuSrAIOAb40YH2SpN0MdqRQVb9TVWurah3wfOD9VfUC4DLgOa3beuCStrylrdO2v7+qaqj6JEl3N437FH4beGmS7YzOGVzQ2i8AHt7aXwqcM4XaJGlFG3L6qKuqDwAfaMvXAycs0OfrwHMXox5J0sK8o1mS1BkKkqTOUJAkdYaCJKkzFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVJnKEiSOkNBktQZCpKkbqJQSHLpJG2SpPu3vf6O5iQPAh4MHJHkMCBt08OANQPXJklaZHsNBeAXgF8FvhvYxrdD4VbgL4crS5I0DXsNhao6Fzg3ydlV9fpFqkmSNCX3dKQAQFW9PskPA+vGP1NVFw5UlyRpCiYKhSRvAR4FXAF8szUXYChI0jIyUSgAs8AxVVVDFiNJmq5JQ+HTwHcBNw5Yi6Qx//OKH5h2CVqCHvH7Vw06/qShcARwTZJ/B+7Y1VhVzxqkKknSVEwaCn+wrwO3exw+BDywfc/FVfXyJI8E3g48nNFlri+qqm8keSCjcxTHA18CnldVn9vX75Uk7b9Jrz764H6MfQfw1Kr6WpKDgI8k+SfgpcDrqurtSf4G2ACc396/UlWPTvJ84I+B5+3H90qS9tOkj7m4Lcmt7fX1JN9McuvePlMjX2urB7VXAU8FLm7tm4FT2/IpbZ22/aQku26WkyQtgolCoaoeWlUPq6qHAd8B/Azw1/f0uSQHJrkCuBnYCvwX8NWqurN12cG3H5exBrihfd+dwC2Mpph2H3Njkrkkc/Pz85OUL0ma0D4/JbUdAbwbePoEfb9ZVY8H1gInAI/d1+9bYMxNVTVbVbMzMzP3djhJ0phJb1579tjqAYzuW/j6pF9SVV9NchnwRODQJKva0cBaYGfrthM4CtiRZBVwCKMTzpKkRTLpkcJPjb2eDtzG6BzAHiWZSXJoW/4O4MeBa4HLgOe0buuBS9rylrZO2/5+b5aTpMU16dVHZ+7H2EcCm5McyCh8Lqqq9yS5Bnh7klcBlwMXtP4XAG9Jsh34MvD8/fhOSdK9MOn00Vrg9cCTWtOHgZdU1Y49faaqrgSOXaD9ekbnF3Zv/zrw3EnqkSQNY9Lpozcxmt757vb6x9YmSVpGJg2Fmap6U1Xd2V5vBrz0R5KWmUlD4UtJXtjuOzgwyQvxyiBJWnYmDYUXA6cBNzF6UupzgDMGqkmSNCWTPhDvFcD6qvoKQJLDgT9jFBaSpGVi0iOFH9wVCABV9WUWuLJIknT/NmkoHJDksF0r7Uhh0qMMSdL9xKT/sP858LEkf9/Wnwu8epiSJEnTMukdzRcmmWP02GuAZ1fVNcOVJUmahomngFoIGASStIzt86OzJUnLl6EgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVJnKEiSOkNBktQZCpKkzlCQJHWGgiSpMxQkSd1goZDkqCSXJbkmydVJXtLaD0+yNcl17f2w1p4k5yXZnuTKJMcNVZskaWFDHincCfx6VR0DnAicleQY4Bzg0qo6Gri0rQM8Ezi6vTYC5w9YmyRpAYOFQlXdWFX/0ZZvA64F1gCnAJtbt83AqW35FODCGvk4cGiSI4eqT5J0d4tyTiHJOuBY4BPA6qq6sW26CVjdltcAN4x9bEdr232sjUnmkszNz88PV7QkrUCDh0KShwDvBH61qm4d31ZVBdS+jFdVm6pqtqpmZ2Zm7sNKJUmDhkKSgxgFwlur6l2t+Qu7poXa+82tfSdw1NjH17Y2SdIiGfLqowAXANdW1WvHNm0B1rfl9cAlY+2nt6uQTgRuGZtmkiQtglUDjv0k4EXAVUmuaG0vA14DXJRkA/B54LS27b3AycB24HbgzAFrkyQtYLBQqKqPANnD5pMW6F/AWUPVI0m6Z97RLEnqDAVJUmcoSJI6Q0GS1BkKkqTOUJAkdYaCJKkzFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVJnKEiSOkNBktQZCpKkzlCQJHWGgiSpMxQkSZ2hIEnqDAVJUmcoSJK6wUIhyRuT3Jzk02NthyfZmuS69n5Ya0+S85JsT3JlkuOGqkuStGdDHim8GXjGbm3nAJdW1dHApW0d4JnA0e21ETh/wLokSXswWChU1YeAL+/WfAqwuS1vBk4da7+wRj4OHJrkyKFqkyQtbLHPKayuqhvb8k3A6ra8BrhhrN+O1nY3STYmmUsyNz8/P1ylkrQCTe1Ec1UVUPvxuU1VNVtVszMzMwNUJkkr12KHwhd2TQu195tb+07gqLF+a1ubJGkRLXYobAHWt+X1wCVj7ae3q5BOBG4Zm2aSJC2SVUMNnORtwFOAI5LsAF4OvAa4KMkG4PPAaa37e4GTge3A7cCZQ9UlSdqzwUKhqn52D5tOWqBvAWcNVYskaTLe0SxJ6gwFSVJnKEiSOkNBktQZCpKkzlCQJHWGgiSpMxQkSZ2hIEnqDAVJUmcoSJI6Q0GS1BkKkqTOUJAkdYaCJKkzFCRJnaEgSeoMBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6gwFSVJnKEiSuiUVCkmekeSzSbYnOWfa9UjSSrNkQiHJgcBfAc8EjgF+Nskx061KklaWJRMKwAnA9qq6vqq+AbwdOGXKNUnSirJq2gWMWQPcMLa+A3jC7p2SbAQ2ttWvJfnsItS2UhwBfHHaRSwF+bP10y5Bd+W+ucvLc1+M8j172rCUQmEiVbUJ2DTtOpajJHNVNTvtOqTduW8unqU0fbQTOGpsfW1rkyQtkqUUCp8Ejk7yyCQPAJ4PbJlyTZK0oiyZ6aOqujPJLwPvAw4E3lhVV0+5rJXGaTktVe6biyRVNe0aJElLxFKaPpIkTZmhIEnqDAUtKMlTkrxn2nVoeUjyK0muTfLWgcb/gyS/McTYK82SOdEsaVn7JeDHqmrHtAvR3nmksIwlWZfkM0nenOQ/k7w1yY8l+bck1yU5ob0+luTyJB9N8pgFxjk4yRuT/Hvr5+NHNLEkfwN8L/BPSX53oX0pyRlJ3p1ka5LPJfnlJC9tfT6e5PDW7+eTfDLJp5K8M8mDF/i+RyX55yTbknw4yWMX9ye+fzMUlr9HA38OPLa9fg54MvAbwMuAzwA/UlXHAr8P/OECY/wu8P6qOgH4UeBPkxy8CLVrGaiqXwT+l9G+czB73pe+H3g28EPAq4Hb2375MeD01uddVfVDVfU44FpgwwJfuQk4u6qOZ7Sf//UwP9ny5PTR8vffVXUVQJKrgUurqpJcBawDDgE2JzkaKOCgBcZ4GvCssTnbBwGPYPSXUtoXe9qXAC6rqtuA25LcAvxja78K+MG2/P1JXgUcCjyE0X1NXZKHAD8M/H3SnxH0wAF+jmXLUFj+7hhb/tbY+rcY/fm/ktFfxp9Osg74wAJjBPiZqvLhg7q3FtyXkjyBe95XAd4MnFpVn0pyBvCU3cY/APhqVT3+Pq16BXH6SIfw7WdMnbGHPu8Dzk77r1eSYxehLi1P93ZfeihwY5KDgBfsvrGqbgX+O8lz2/hJ8rh7WfOKYijoT4A/SnI5ez5yfCWjaaUr2xTUKxerOC0793Zf+j3gE8C/MToftpAXABuSfAq4Gn8vyz7xMReSpM4jBUlSZyhIkjpDQZLUGQqSpM5QkCR1hoK0n9pzfK5OcmWSK9oNWNL9mnc0S/shyROBnwSOq6o7khwBPGDKZUn3mkcK0v45EvhiVd0BUFVfrKr/TXJ8kg+2J3S+L8mRSQ5J8tldT6BN8rYkPz/V6qU98OY1aT+0B699BHgw8K/AO4CPAh8ETqmq+STPA55eVS9O8uPAK4BzgTOq6hlTKl3aK6ePpP1QVV9LcjzwI4weAf0O4FWMHv+8tT3a50DgxtZ/a3sez18BPotHS5ZHCtJ9IMlzgLOAB1XVExfYfgCjo4h1wMm7HmcuLTWeU5D2Q5LHtN9BscvjGf1+iZl2EpokByX5vrb919r2nwPe1J7yKS05HilI+6FNHb2e0S97uRPYDmwE1gLnMXok+SrgL4APAe8GTqiq25K8Fritql6+6IVL98BQkCR1Th9JkjpDQZLUGQqSpM5QkCR1hoIkqTMUJEmdoSBJ6v4fFZiFomQxq2MAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Sex'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hC8sMabSJm9Y",
        "outputId": "e12fb350-76e6-465a-c2db-b1237b6b3241"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "male      577\n",
              "female    314\n",
              "Name: Sex, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# classifying survived people on basis on gender\n",
        "\n",
        "sns.countplot(\"Sex\", hue = \"Survived\", data = df)\n",
        "plt.show()\n",
        "\n",
        "# insight : more females survived during titanic accident"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "r7FQIBsmJuN3",
        "outputId": "0bc17932-368f-495e-e939-8608672ebe06"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: 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",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (20,11))\n",
        "# heatmap size in ration 16:9\n",
        "\n",
        "sns.heatmap(df.corr(), annot = True, cmap = 'coolwarm')\n",
        "# heatmap parameters\n",
        "\n",
        "plt.title(\"Heatmap for correlation matrix for titanic data \", fontsize = 22)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 668
        },
        "id": "uTtUWni_Ira2",
        "outputId": "ce5464cc-6ce1-494d-a2ef-f33102a5f3a0"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x792 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.pairplot(df, hue = \"Survived\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ndfMAlLjJDu6",
        "outputId": "68619cd1-d6ad-4cee-9d80-d4aacbdbfcfd"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fc284412490>"
            ]
          },
          "metadata": {},
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1131.88x1080 with 42 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# making a count plot for \"PClass\" columns\n",
        "\n",
        "sns.countplot(\"Pclass\", data = df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "id": "SRsWPRUiJDsF",
        "outputId": "26a7cf84-1cff-41c1-f8c5-b44a41e793be"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: 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",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='Pclass', ylabel='count'>"
            ]
          },
          "metadata": {},
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(\"Pclass\", hue = \"Survived\", data = df)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "id": "OQ0Bkd2iJDp-",
        "outputId": "85406085-c861-4f0a-880c-0a27a22fcc0e"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: 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",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='Pclass', ylabel='count'>"
            ]
          },
          "metadata": {},
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Data Encoding "
      ],
      "metadata": {
        "id": "dItMtXwpMwOQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df ['Sex'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2nT8MYyVMuRM",
        "outputId": "beefd8b0-41b4-44bb-a137-213f6e9e6c58"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "male      577\n",
              "female    314\n",
              "Name: Sex, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Embarked'].value_counts()"
      ],
      "metadata": {
        "id": "K9AIqGGfMuN6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "534888da-faf8-4a5a-88d1-d8b1b469745c"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "S    646\n",
              "C    168\n",
              "Q     77\n",
              "Name: Embarked, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# converting categorical Columns\n",
        "\n",
        "df.replace({'Sex':{'male':0,'female':1}, 'Embarked':{'S':0,'C':1,'Q':2}}, inplace=True)"
      ],
      "metadata": {
        "id": "WE6n2h9bMuH1"
      },
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.Embarked"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gxJpk3Ll3mF5",
        "outputId": "0297446a-9226-4306-f31c-7aa3f4a2446c"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      S\n",
              "1      1\n",
              "2      S\n",
              "3      S\n",
              "4      S\n",
              "      ..\n",
              "886    S\n",
              "887    S\n",
              "888    S\n",
              "889    1\n",
              "890    2\n",
              "Name: Embarked, Length: 891, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Sex"
      ],
      "metadata": {
        "id": "-3umOhRTMuFJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d1a07671-df11-4d7f-9f4e-91a44f9723dd"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      0\n",
              "1      1\n",
              "2      1\n",
              "3      1\n",
              "4      0\n",
              "      ..\n",
              "886    0\n",
              "887    1\n",
              "888    1\n",
              "889    0\n",
              "890    0\n",
              "Name: Sex, Length: 891, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "de-dBCwp0pcI",
        "outputId": "94815306-cbc6-40b5-fc5f-3616b9d4913a"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   PassengerId  Survived  Pclass  \\\n",
              "0            1         0       3   \n",
              "1            2         1       1   \n",
              "2            3         1       3   \n",
              "3            4         1       1   \n",
              "4            5         0       3   \n",
              "\n",
              "                                                Name  Sex   Age  SibSp  Parch  \\\n",
              "0                            Braund, Mr. Owen Harris    0  22.0      1      0   \n",
              "1  Cumings, Mrs. John Bradley (Florence Briggs Th...    1  38.0      1      0   \n",
              "2                             Heikkinen, Miss. Laina    1  26.0      0      0   \n",
              "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)    1  35.0      1      0   \n",
              "4                           Allen, Mr. William Henry    0  35.0      0      0   \n",
              "\n",
              "             Ticket     Fare  Embarked  \n",
              "0         A/5 21171   7.2500         0  \n",
              "1          PC 17599  71.2833         1  \n",
              "2  STON/O2. 3101282   7.9250         0  \n",
              "3            113803  53.1000         0  \n",
              "4            373450   8.0500         0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f122445c-8cc1-4aa1-9276-e6f25d08139f\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\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>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>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>0</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>0</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>1</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>1</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>1</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>0</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>1</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>0</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>0</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>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f122445c-8cc1-4aa1-9276-e6f25d08139f')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-f122445c-8cc1-4aa1-9276-e6f25d08139f 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-f122445c-8cc1-4aa1-9276-e6f25d08139f');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Separating features and target\n"
      ],
      "metadata": {
        "id": "qyZ-QWtQ0sOQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X = df.drop(columns = ['PassengerId', 'Name','Ticket','Survived'], axis = 1)\n",
        "Y = df['Survived']"
      ],
      "metadata": {
        "id": "BBNkojuEJDnj"
      },
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# print(X)\n",
        "X.dtypes"
      ],
      "metadata": {
        "id": "vm9zSJW-JDlC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "68d0b2f2-93f2-4633-b822-dfec7ec453f2"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pclass        int64\n",
              "Sex           int64\n",
              "Age         float64\n",
              "SibSp         int64\n",
              "Parch         int64\n",
              "Fare        float64\n",
              "Embarked      int64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(Y)"
      ],
      "metadata": {
        "id": "rO-xzKKHJDij",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c5ba2193-f07d-4809-ad4f-1668307546ad"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0      0\n",
            "1      1\n",
            "2      1\n",
            "3      1\n",
            "4      0\n",
            "      ..\n",
            "886    0\n",
            "887    1\n",
            "888    0\n",
            "889    1\n",
            "890    0\n",
            "Name: Survived, Length: 891, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, Y_train, Y_test = train_test_split(X,Y, test_size = 0.2, random_state = 2)"
      ],
      "metadata": {
        "id": "WEgyOf9LJDfK"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Shape of X_train : \", X_train.shape)\n",
        "print(\"Shape of X_test : \", X_test.shape)\n",
        "print(\"Shape of Y_train : \", Y_train.shape)\n",
        "print(\"Shape of Y_test : \", Y_test.shape)\n"
      ],
      "metadata": {
        "id": "Lft2OKwKJDYD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8b7fd513-2dc0-4d7a-9e4e-345e1226ff45"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shape of X_train :  (712, 7)\n",
            "Shape of X_test :  (179, 7)\n",
            "Shape of Y_train :  (712,)\n",
            "Shape of Y_test :  (179,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Model Training\n",
        "*Logistic Model*\n"
      ],
      "metadata": {
        "id": "qRGZ2bqY22dg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# training the logistic regression model with training data\n",
        "\n",
        "model = LogisticRegression()\n",
        "model.fit(X_train, Y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GJirVRJP26Wb",
        "outputId": "9a9a733b-1c63-458d-9d0a-043ed24287db"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "Please also refer to the documentation for alternative solver options:\n",
            "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
            "  n_iter_i = _check_optimize_result(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LogisticRegression()"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Model Evaluation\n",
        "\n",
        "*Accuracy Score*"
      ],
      "metadata": {
        "id": "kEeG2BIu4W9S"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# accuracy score on training data\n",
        "\n",
        "X_train_prediction = model.predict(X_train)\n",
        "print(X_train_prediction)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kxx6sFBX26G-",
        "outputId": "b8e2b07b-7dc7-417c-b3b4-bd973ecbbc89"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0 1 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 0 1 0 1 1 0 0 1 0 1\n",
            " 0 0 0 0 0 0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 1 1 0 0 1 1 0 1 0 0 1\n",
            " 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 1 0 0 1 0 0 0 1 1 1 0 1 0 0 0 0 0 1 0 0 0\n",
            " 1 1 0 0 1 0 0 1 0 0 1 0 0 1 0 1 0 1 0 1 0 1 1 1 1 1 1 0 0 1 1 1 0 0 1 0 0\n",
            " 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 1 0 1 1 1\n",
            " 0 0 0 1 0 0 0 1 0 0 1 0 0 0 1 1 0 1 0 0 0 0 0 1 1 0 1 1 1 1 0 0 0 0 0 0 0\n",
            " 0 1 0 0 1 1 1 0 0 1 0 1 1 1 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0 1 0 1 0 0 0\n",
            " 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 1 0 1 1 0 0 0 0 1 0 1 0 0 1 0 0 0 1 0 0 0\n",
            " 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 1 0 0 0 1 0 1 0 0 0 0 0 0 1 1 0 1 1\n",
            " 0 1 1 1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 1 0 0 0 0 1 1 0 0 0 1 0 1 1 1 0 0\n",
            " 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 1 1 1 0 1 1 0 0 0\n",
            " 0 1 0 1 0 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 1 0 1 0 0 0 0 0 1 0 0 0 0 1 1 0 0\n",
            " 1 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 1 0 1 0 0 1 0 0 0 1 1 0 1 0\n",
            " 0 0 0 0 1 0 0 1 0 1 1 0 0 1 0 0 1 0 0 0 1 0 1 1 0 0 1 1 0 1 0 1 1 1 0 1 0\n",
            " 0 1 0 0 1 0 0 1 0 0 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 1 1 1 0 0 1 1 0 0 0 0 0\n",
            " 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0\n",
            " 0 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 1 0 1 1 1 0 0 0 1 0 1 0 0 0 1 1 1 0 0 1 1\n",
            " 0 0 0 1 0 1 0 0 0 0 0 1 1 0 1 1 1 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0\n",
            " 1 0 0 1 0 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 1 1 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0\n",
            " 0 0 0 1 1 0 0 1 0]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "training_data_accuracy = accuracy_score(Y_train, X_train_prediction)\n",
        "print(\"Accuracy score of training data : \", training_data_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AiJ9GCbq26Cy",
        "outputId": "45b84629-70b6-4f18-a5a4-20d1e605d8f9"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score of training data :  0.8075842696629213\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_test_prediction = model.predict(X_test)\n",
        "print(X_test_prediction)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "65B1RbmI45yD",
        "outputId": "165a5558-51ee-4541-f0a1-26783c114d42"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 1 1 0 1 0 1 1 0 0 0 0 0 0 0 0 1 1\n",
            " 0 0 0 0 0 1 0 0 1 1 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 1 0 0 0 1 0 1 0\n",
            " 1 0 0 0 1 0 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 1 0 1 1 0 1 1 0 0 0 0\n",
            " 0 0 0 1 1 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 1 1 1 1 0 1 0 0\n",
            " 0 1 0 0 0 0 1 0 0 1 1 0 1 0 0 0 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "testing_data_accuracy = accuracy_score(Y_test, X_test_prediction)\n",
        "print(\"Accuracy score of training data : \", testing_data_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I0DNbyPR25_Z",
        "outputId": "038ef064-b4e3-4b54-f55c-a14152d23b72"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy score of training data :  0.7821229050279329\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "6snyUftv57qm"
      },
      "execution_count": 72,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "PSq5XnKL5_ul"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}