DATA_PREPROCESSING.ipynb

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      "execution_count": null,
      "metadata": {
        "id": "mRP8vH3krsou"
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      "source": [
        "#IMPORT THE INDEPEDENCIES\n",
        "import numpy as np\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#MOUNTING WITH GOOLGE COLAB\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZR4xWVRtuD4a",
        "outputId": "d9962741-f319-41e4-bac8-fc0368e1a379"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#LOADING THE DATASET THROUGH PANDAS\n",
        "data = pd.read_csv('/content/drive/MyDrive/Datasets/Datasets/titanic_data.csv')"
      ],
      "metadata": {
        "id": "VtwvAOnvuxiN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#UNCLEANED DATA\n",
        "data"
      ],
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          "height": 423
        },
        "id": "-oW6bPqJvNoq",
        "outputId": "b8b44ce5-b4ab-4e62-b736-34b31e09bdba"
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      "execution_count": null,
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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",
              "1304         1305         0       3   \n",
              "1305         1306         1       1   \n",
              "1306         1307         0       3   \n",
              "1307         1308         0       3   \n",
              "1308         1309         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",
              "1304                                 Spector, Mr. Woolf    male   NaN      0   \n",
              "1305                       Oliva y Ocana, Dona. Fermina  female  39.0      0   \n",
              "1306                       Saether, Mr. Simon Sivertsen    male  38.5      0   \n",
              "1307                                Ware, Mr. Frederick    male   NaN      0   \n",
              "1308                           Peter, Master. Michael J    male   NaN      1   \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  \n",
              "...     ...                 ...       ...   ...      ...  \n",
              "1304      0           A.5. 3236    8.0500   NaN        S  \n",
              "1305      0            PC 17758  108.9000  C105        C  \n",
              "1306      0  SOTON/O.Q. 3101262    7.2500   NaN        S  \n",
              "1307      0              359309    8.0500   NaN        S  \n",
              "1308      1                2668   22.3583   NaN        C  \n",
              "\n",
              "[1309 rows x 12 columns]"
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              "      <td>Braund, Mr. Owen Harris</td>\n",
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              "      <td>Heikkinen, Miss. Laina</td>\n",
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              "      <td>26.0</td>\n",
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              "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
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              "<p>1309 rows × 12 columns</p>\n",
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      "cell_type": "markdown",
      "source": [
        "**DATA PREPROCESSING:**\n",
        "\n",
        "1-CHECKING AND REMOVING ALL NULL VALUES.\n",
        "\n",
        "2-REMOVING IRRELEVANT COLUMNS LIKE 'NAME' etc.\n",
        "\n",
        "3-CHANGING COLUMNS TO CATEGORICAL NUMERIC VALUES."
      ],
      "metadata": {
        "id": "G9CYcGX_5R4k"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#CHECKING COLUMS OF OUR DATA\n",
        "data.columns "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CuV0FWSkvtDS",
        "outputId": "146d2fc6-416b-4bff-d6c1-0b562d9a1e81"
      },
      "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": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#CHECKING NULL VALUES IN OUR DATA\n",
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fUSZMbtovOee",
        "outputId": "5e74ba99-108a-4b53-c8f1-f0e47a5c7a4f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PassengerId       0\n",
              "Survived          0\n",
              "Pclass            0\n",
              "Name              0\n",
              "Sex               0\n",
              "Age             263\n",
              "SibSp             0\n",
              "Parch             0\n",
              "Ticket            0\n",
              "Fare              1\n",
              "Cabin          1014\n",
              "Embarked          2\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "#REMOVING COLUMNS THAT HAS MORE THAN 80% NULL VALUES\n",
        "data = data.drop(['Cabin'], axis=1)"
      ],
      "metadata": {
        "id": "dQqw023_vgp_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pJTgJbE-xJKF",
        "outputId": "4f2b229d-a55f-4358-940b-0cb600293aa7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PassengerId      0\n",
              "Survived         0\n",
              "Pclass           0\n",
              "Name             0\n",
              "Sex              0\n",
              "Age            263\n",
              "SibSp            0\n",
              "Parch            0\n",
              "Ticket           0\n",
              "Fare             1\n",
              "Embarked         2\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#FILLING OTHER NULL values with median i.e (AGE, EMARKED, FARE)\n",
        "#FILLING THE NULL VALUES BY MEDIAN VALUES\n",
        "data.Age = data.Age.fillna(data.Age.median())\n",
        "data.Fare = data.Fare.fillna(data.Fare.median())\n",
        "\n",
        "#THIS COLUMN HAS NO NUMERICAL VALUES SO WE CANT PUT MEDIAN IN BLANK SPACES\n",
        "data.Embarked = data.Embarked.fillna('S')\n",
        "\n",
        "\n",
        "#CHECKING AGAIN FOR ANY NULL VALUES IN DATA\n",
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rK4QUqUbwqTM",
        "outputId": "25f0e82d-48ed-49c9-c42a-ca58b17c6b4f"
      },
      "execution_count": null,
      "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": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#CHECKING THE DATSET\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
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        "id": "V_0jfE4e1dUD",
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              "      PassengerId  Survived  Pclass  \\\n",
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              "...                                                 ...     ...   ...    ...   \n",
              "1304                                 Spector, Mr. Woolf    male  28.0      0   \n",
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              "1307                                Ware, Mr. Frederick    male  28.0      0   \n",
              "1308                           Peter, Master. Michael J    male  28.0      1   \n",
              "\n",
              "      Parch              Ticket      Fare Embarked  \n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#REMOVING IRRELEVANT COLUMNS/FEATURES\n",
        "data = data.drop(['PassengerId','Name', 'Ticket'], axis=1) #axis 1 is to actually remove the whole column"
      ],
      "metadata": {
        "id": "wImQTwRK2Him"
      },
      "execution_count": null,
      "outputs": []
    },
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        "id": "OAPju4yk2m5m",
        "outputId": "fd7d4131-9518-471d-966e-092315366227"
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      "execution_count": null,
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              "      Survived  Pclass     Sex   Age  SibSp  Parch      Fare Embarked\n",
              "0            0       3    male  22.0      1      0    7.2500        S\n",
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              "1304         0       3    male  28.0      0      0    8.0500        S\n",
              "1305         1       1  female  39.0      0      0  108.9000        C\n",
              "1306         0       3    male  38.5      0      0    7.2500        S\n",
              "1307         0       3    male  28.0      0      0    8.0500        S\n",
              "1308         0       3    male  28.0      1      1   22.3583        C\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c3b7fc24-86d5-49db-a935-ff3a5a0efef2')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \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",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
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              "\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",
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              "\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-c3b7fc24-86d5-49db-a935-ff3a5a0efef2 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-c3b7fc24-86d5-49db-a935-ff3a5a0efef2');\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": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#now we have two columNs to change that are (SEX & EMBARKED).\n",
        "#WE WANT TO CONVERT THEM TO CATEGORICAL VALUES TO FEED INTO OUR MODEL. FOR EXAMPLE (MALE IS 1 AND FEMALE IS 0)\n",
        "\n",
        "#For changing values to numericals categories we can use LabelEncoder library drom sklearn OR MANUALLY LIKE HERE:\n",
        "\n",
        "#CHANGING TWO COLUMN VALUES TO CATEGORICAL & NUMERICAL VALUES\n",
        "data.Embarked = data.Embarked.map( {'S':0,'C':1,'Q':2} )\n",
        "data.Sex = data.Sex.map( {\"male\":0, \"female\":1} )"
      ],
      "metadata": {
        "id": "3CWhVcGZ26bU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#CLEANED DATA (ALL NUMERICAL VALUES THAT CAN BE FED INTO ANY MACHINE LEARNING ALGORITHM)\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "-NEOAuUj4WvA",
        "outputId": "98e8e8a3-0820-4cae-e6a7-f00e46ac9c74"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Survived  Pclass  Sex   Age  SibSp  Parch      Fare  Embarked\n",
              "0            0       3    0  22.0      1      0    7.2500         0\n",
              "1            1       1    1  38.0      1      0   71.2833         1\n",
              "2            1       3    1  26.0      0      0    7.9250         0\n",
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              "4            0       3    0  35.0      0      0    8.0500         0\n",
              "...        ...     ...  ...   ...    ...    ...       ...       ...\n",
              "1304         0       3    0  28.0      0      0    8.0500         0\n",
              "1305         1       1    1  39.0      0      0  108.9000         1\n",
              "1306         0       3    0  38.5      0      0    7.2500         0\n",
              "1307         0       3    0  28.0      0      0    8.0500         0\n",
              "1308         0       3    0  28.0      1      1   22.3583         1\n",
              "\n",
              "[1309 rows x 8 columns]"
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              "<p>1309 rows × 8 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b6f2d43c-a1e7-468f-bb3f-5ec8dcb6552a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      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-b6f2d43c-a1e7-468f-bb3f-5ec8dcb6552a 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-b6f2d43c-a1e7-468f-bb3f-5ec8dcb6552a');\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": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "wzL3_t-G4ZVZ"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}