Giovanni_&_Oscar_Milestone_2_Google_Colab.ipynb

{
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      "cell_type": "markdown",
      "metadata": {
        "id": "FWM79lj2LYI6"
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      "source": [
        "# Giovanni & Oscar | ML Final Project | Milestone 2\n",
        "\n",
        "Setup and Baseline, Due 3/30\n",
        "\n",
        "## Points (10 pts)\n",
        "## Tasks:\n",
        "\n",
        "1. Load the data in a colab notebook\n",
        "\n",
        "1. Split the training data into 90% for training and 10% for validation (your experiments).\n",
        "\n",
        "  - **Note:** You will want to run experiments in your colab notebook without always submitting your test predictions to kaggle.\n",
        "\n",
        "1. Figure out how to submit a baseline system to kaggle that makes predictions on the test data. You should receive a score back from kaggle and see your position on the leaderboard.\n",
        "\n",
        "1. Submit a copy of your colab in Classroom that includes your baseline score evaluated on\n",
        "\n",
        "  - your validation data and\n",
        "  - on the official leaderboard."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WPFnCCd7O6fN"
      },
      "source": [
        "### 0. Setup Dependencies"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QiwopORsO-yC",
        "outputId": "d4dadaad-3005-44b9-9218-e7754e649001"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: pip in /usr/local/lib/python3.9/dist-packages (23.0.1)\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "# Ensure that we have the newest version of pip installed\n",
        "%pip install --upgrade pip"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pn1OWO_1PRrO",
        "outputId": "45d5f5a6-41ce-4d7c-da30-dbb56b4641bf"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Using pip 23.0.1 from /usr/local/lib/python3.9/dist-packages/pip (python 3.9)\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.9/dist-packages (1.22.4)\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0mUsing pip 23.0.1 from /usr/local/lib/python3.9/dist-packages/pip (python 3.9)\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.9/dist-packages (1.4.4)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas) (2022.7.1)\n",
            "Requirement already satisfied: numpy>=1.18.5 in /usr/local/lib/python3.9/dist-packages (from pandas) (1.22.4)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.9/dist-packages (from pandas) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.9/dist-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0mUsing pip 23.0.1 from /usr/local/lib/python3.9/dist-packages/pip (python 3.9)\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.9/dist-packages (3.7.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (0.11.0)\n",
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            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (8.4.0)\n",
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            "Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (1.22.4)\n",
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            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (4.39.3)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (1.4.4)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (3.0.9)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (1.0.7)\n",
            "Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.9/dist-packages (from importlib-resources>=3.2.0->matplotlib) (3.15.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.9/dist-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0mUsing pip 23.0.1 from /usr/local/lib/python3.9/dist-packages/pip (python 3.9)\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: seaborn in /usr/local/lib/python3.9/dist-packages (0.12.2)\n",
            "Requirement already satisfied: numpy!=1.24.0,>=1.17 in /usr/local/lib/python3.9/dist-packages (from seaborn) (1.22.4)\n",
            "Requirement already satisfied: pandas>=0.25 in /usr/local/lib/python3.9/dist-packages (from seaborn) (1.4.4)\n",
            "Requirement already satisfied: matplotlib!=3.6.1,>=3.1 in /usr/local/lib/python3.9/dist-packages (from seaborn) (3.7.1)\n",
            "Requirement already satisfied: importlib-resources>=3.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (5.12.0)\n",
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            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (3.0.9)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (1.4.4)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (1.0.7)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (0.11.0)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (2.8.2)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (23.0)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (4.39.3)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas>=0.25->seaborn) (2022.7.1)\n",
            "Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.9/dist-packages (from importlib-resources>=3.2.0->matplotlib!=3.6.1,>=3.1->seaborn) (3.15.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.9/dist-packages (from python-dateutil>=2.7->matplotlib!=3.6.1,>=3.1->seaborn) (1.16.0)\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "# Install necessary libraries\n",
        "%pip install -v numpy\n",
        "%pip install -v pandas\n",
        "%pip install -v matplotlib\n",
        "%pip install -v seaborn\n",
        "\n",
        "# Helps avoid showing plots in a separate line\n",
        "# %matplotlib inline\n",
        "\n",
        "# %pip install -v scikit-learn"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ycGSQ31nQRa8"
      },
      "outputs": [],
      "source": [
        "# Import the modules\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn import datasets\n",
        "\n",
        "# Set the styling of the plt plots to darkgrid\n",
        "sns.set(style='darkgrid')\n",
        "\n",
        "# Removes error messsages and sets precision to 3 decimal places\n",
        "# import warnings\n",
        "# warnings.filterwarnings('ignore')\n",
        "# np.set_printoptions(precision=3, suppress=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UJCd5JzUNNuk"
      },
      "source": [
        "### 1. Load the Data in a Colab Notebook"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ct512u3DuP7E",
        "outputId": "b3641ce6-576a-421e-bcc2-f0e494d8f043"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "\n",
        "# Please update the Path here to the location of your train.csv and test.csv files\n",
        "path_to_csv = '/content/drive/MyDrive/Final_Project_Oscar_Giovanni'\n",
        "\n",
        "# Load the Data Frames from the Training and Testing Data Frame\n",
        "train_df = pd.read_csv(f'{path_to_csv}/train.csv')\n",
        "test_df = pd.read_csv(f'{path_to_csv}/test.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "Ha6EJ6wsvxPw",
        "outputId": "895717ea-1c29-4981-c9a4-8bc633573d79"
      },
      "outputs": [
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              "7610  M1.94 [01:04 UTC]?5km S of Volcano Hawaii. htt...       1  \n",
              "7611  Police investigating after an e-bike collided ...       1  \n",
              "7612  The Latest: More Homes Razed by Northern Calif...       1  \n",
              "\n",
              "[7613 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Verifying that the Train Data Frame is loaded in properly\n",
        "display(train_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "JpgS5aDr68ZQ",
        "outputId": "55bed36c-36e8-453d-922a-d92debc3b6ec"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Input Data Frame:\n"
          ]
        },
        {
          "data": {
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              "\n",
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              "</style>\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
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              "      <th>text</th>\n",
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              "      <td>Just got sent this photo from Ruby #Alaska as ...</td>\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",
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              "\n",
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              "      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",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5249365e-3e6b-490f-864d-02cc78c1b93d');\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",
              "  "
            ],
            "text/plain": [
              "   id keyword location                                               text\n",
              "0   1     NaN      NaN  Our Deeds are the Reason of this #earthquake M...\n",
              "1   4     NaN      NaN             Forest fire near La Ronge Sask. Canada\n",
              "2   5     NaN      NaN  All residents asked to 'shelter in place' are ...\n",
              "3   6     NaN      NaN  13,000 people receive #wildfires evacuation or...\n",
              "4   7     NaN      NaN  Just got sent this photo from Ruby #Alaska as ..."
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Output Data Frame:\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-5592c5d8-e06b-41bd-abff-a63c9de2db31\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
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              "        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>target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5592c5d8-e06b-41bd-abff-a63c9de2db31')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "       width=\"24px\">\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",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
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              "      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-5592c5d8-e06b-41bd-abff-a63c9de2db31 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-5592c5d8-e06b-41bd-abff-a63c9de2db31');\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",
              "  "
            ],
            "text/plain": [
              "   target\n",
              "0       1\n",
              "1       1\n",
              "2       1\n",
              "3       1\n",
              "4       1"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Reformat the single training dataframe to input and output dataframes\n",
        "input_names = ['id', 'keyword', 'location', 'text']\n",
        "input_df = train_df[input_names]\n",
        "print('Input Data Frame:')\n",
        "display(input_df.head())\n",
        "\n",
        "output_names = ['target']\n",
        "output_df = train_df[output_names]\n",
        "print('Output Data Frame:')\n",
        "display(output_df.head())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r8xKWGXD6-Pd",
        "outputId": "54752236-67c5-4a8c-9cf8-0aaaf6294b0a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[[1 nan nan\n",
            "  'Our Deeds are the Reason of this #earthquake May ALLAH Forgive us all']\n",
            " [4 nan nan 'Forest fire near La Ronge Sask. Canada']\n",
            " [5 nan nan\n",
            "  \"All residents asked to 'shelter in place' are being notified by officers. No other evacuation or shelter in place orders are expected\"]\n",
            " [6 nan nan\n",
            "  '13,000 people receive #wildfires evacuation orders in California ']\n",
            " [7 nan nan\n",
            "  'Just got sent this photo from Ruby #Alaska as smoke from #wildfires pours into a school ']]\n",
            "[1 1 1 1 1]\n",
            "(7613, 4)\n",
            "(7613,)\n"
          ]
        }
      ],
      "source": [
        "# Convert the train dataframes into numpy arrays for easier use in our model\n",
        "X_data = input_df.to_numpy()\n",
        "Y_data = output_df.to_numpy().flatten()   # Change dim from (n, 1) to (1,)\n",
        "\n",
        "# Show sample data from the train data\n",
        "print(X_data[:5])\n",
        "print(Y_data[:5])\n",
        "\n",
        "print(X_data.shape)\n",
        "print(Y_data.shape)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aEUKdwxcreac"
      },
      "source": [
        "### 2. Split the training data into 90% training and 10% for validation (your experiments)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "TTk_z6ug6GIu"
      },
      "outputs": [],
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "# Split the data into train and test using sklearn\n",
        "X_train, X_test, Y_train, Y_test = train_test_split(X_data, Y_data, train_size=0.90)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oMYXyEPO6HXM",
        "outputId": "6421d264-43fa-455d-93c7-7f9e889abf82"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Text\n",
            "[6839 'loud%20bang' nan\n",
            " '@Bang_Me_Up_Guk he was ;-; like he was singing so loud ;-;']\n",
            "\n",
            "Is Natural Disaster?\n",
            "0 No\n",
            "======================\n",
            "\n",
            "Text\n",
            "[3816 'detonate' 'Ottawa,Ontario Canada'\n",
            " 'Real Hip Hop: Apollo Brown Feat M.O.P. - Detonate \\n#JTW http://t.co/cEiaO1TEXr']\n",
            "\n",
            "Is Natural Disaster?\n",
            "0 No\n",
            "======================\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Print first two training examples\n",
        "for index in range(2):\n",
        "  print('Text')\n",
        "  print(X_train[index])\n",
        "  print()\n",
        "  \n",
        "  print('Is Natural Disaster?')\n",
        "  print(Y_train[index], 'Yes' if Y_train[index] == 1 else 'No')\n",
        "  print('======================')\n",
        "  print()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zu66JlkE6Jgr"
      },
      "source": [
        "### 3. Testing and Submitting a Baseline"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ohlJeJup6J5x"
      },
      "outputs": [],
      "source": [
        "# Returns a positive result, regardless of the input\n",
        "def baseline_model(text_inputs):\n",
        "  return 1\n",
        "\n",
        "# Modify the function for numpy arrays\n",
        "baseline_model_np = np.vectorize(baseline_model, signature='(n) -> ()')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vqe4g7hK6Mxp",
        "outputId": "7e5df2c2-2f9e-4677-d329-98a852cdb450"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Input:\n",
            "[6839 'loud%20bang' nan\n",
            " '@Bang_Me_Up_Guk he was ;-; like he was singing so loud ;-;']\n",
            "\n",
            "Output\n",
            "0\n",
            "\n",
            "Prediction\n",
            "1\n",
            "==================\n",
            "\n",
            "Input:\n",
            "[3816 'detonate' 'Ottawa,Ontario Canada'\n",
            " 'Real Hip Hop: Apollo Brown Feat M.O.P. - Detonate \\n#JTW http://t.co/cEiaO1TEXr']\n",
            "\n",
            "Output\n",
            "0\n",
            "\n",
            "Prediction\n",
            "1\n",
            "==================\n",
            "\n",
            "Input:\n",
            "[1699 'bridge%20collapse' 'US'\n",
            " 'Two giant cranes holding a bridge collapse into nearby homes http://t.co/jBJRg3eP1Q']\n",
            "\n",
            "Output\n",
            "1\n",
            "\n",
            "Prediction\n",
            "1\n",
            "==================\n",
            "\n",
            "Input:\n",
            "[9226 'suicide%20bombing' 'Australia'\n",
            " \"Erdogan's Bloody Gambit: on July 20 a suicide bombing in Turkey took the lives of 31 socialists in SuruÌ¤ http://t.co/z6xAUIDRXu @Shareaholic\"]\n",
            "\n",
            "Output\n",
            "1\n",
            "\n",
            "Prediction\n",
            "1\n",
            "==================\n",
            "\n",
            "Input:\n",
            "[8356 'ruin' 'Garrett'\n",
            " \"like why on earth would you want anybody to be unhappy don't purposely ruin somebody else's happiness\"]\n",
            "\n",
            "Output\n",
            "0\n",
            "\n",
            "Prediction\n",
            "1\n",
            "==================\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Predict on the train portion of the train.csv data\n",
        "baseline_predictions_train = baseline_model_np(X_train)\n",
        "\n",
        "# Print out the first 5 training inputs\n",
        "# and their labels alongside their predictions\n",
        "for i in range(5):\n",
        "  print('Input:')\n",
        "  print(X_train[i])\n",
        "  print()\n",
        "\n",
        "  print('Output')\n",
        "  print(Y_train[i])\n",
        "  print()\n",
        "\n",
        "  print('Prediction')\n",
        "  print(baseline_predictions_train[i])\n",
        "  print('==================')\n",
        "  print()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "szQF3hCWPdBW"
      },
      "outputs": [],
      "source": [
        "# Calculates Log Loss\n",
        "def calculate_loss(labels, predictions):\n",
        "  epsilon = 0.000001  # Prevents taking the natural log of non-positive values\n",
        "  ce_values = -labels * np.log(predictions + epsilon) - (1 - labels) * np.log(1 - predictions + epsilon)\n",
        "  loss = ce_values.mean()\n",
        "  return loss"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UrSSWgUQPn5X",
        "outputId": "b7e0f132-9b01-4e44-992f-50a76e74d76f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Training Loss: 7.90293138879922\n"
          ]
        }
      ],
      "source": [
        "training_loss = calculate_loss(Y_train, baseline_predictions_train)\n",
        "print('Training Loss:', training_loss)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cTa7fDquP2_m",
        "outputId": "b2043cce-74b2-4187-e7f8-636caa4ceeb1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Testing Loss: 7.669239668004012\n"
          ]
        }
      ],
      "source": [
        "# Run on the validation data\n",
        "baseline_predictions_test = baseline_model_np(X_test)\n",
        "testing_loss = calculate_loss(Y_test, baseline_predictions_test)\n",
        "print('Testing Loss:', testing_loss)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YcSDxs5EVV_v"
      },
      "source": [
        "### 4. Submission"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hnA-rrlG6On1"
      },
      "outputs": [],
      "source": [
        "# Create the submission CSV file for our Kaggle submission\n",
        "def save_to_submissions_csv(text_inputs, prediction_labels):\n",
        "  print('Generating \"submission.csv\" file...')\n",
        "  # Extract the ids of the text inputs and flatten to a 1D ndarray\n",
        "  test_ids = text_inputs[:,0].flatten()\n",
        "\n",
        "  # Write the submission file and save to 'submission.csv'\n",
        "  np.savetxt(\n",
        "    'submission.csv',\n",
        "    np.rec.fromarrays([test_ids, prediction_labels]),\n",
        "    fmt=['%s', '%d'],\n",
        "    delimiter=',',\n",
        "    header='id,target',\n",
        "    comments=''\n",
        "  )\n",
        "  print('Successfully created \"submission.csv\"')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MWttSP6tMIzR",
        "outputId": "89979c37-97a6-47a1-af44-d6f7810350a3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Generating \"submission.csv\" file...\n",
            "Successfully created \"submission.csv\"\n"
          ]
        }
      ],
      "source": [
        "# Reformat the single training dataframe to an input dataframe\n",
        "input_names = ['id', 'keyword', 'location', 'text']\n",
        "test_input_df = test_df[input_names]\n",
        "\n",
        "# Reformat the input dataframe into a numpy array for running through our model\n",
        "test_input_np = test_input_df.to_numpy()\n",
        "\n",
        "# Predict by using the baseline model on the test input and save to a .csv\n",
        "baseline_predictions_test = baseline_model_np(test_input_np)\n",
        "save_to_submissions_csv(test_input_np, baseline_predictions_test)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UxQMMQHbMCAJ",
        "outputId": "9f6dd504-4db4-42ef-ff4c-7755d7e98bb7"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "id,target\n",
            "0,1\n",
            "2,1\n",
            "3,1\n",
            "9,1\n",
            "11,1\n",
            "12,1\n",
            "21,1\n",
            "22,1\n",
            "27,1\n"
          ]
        }
      ],
      "source": [
        "# Look at the first few predictions to ensure things went smoothly\n",
        "!head submission.csv"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ftZG--Z-Ls4A"
      },
      "source": [
        "### Validation score and leaderboard rankings\n",
        "It's last place but its honest work :'("
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "om3piRIhLgRw"
      },
      "source": [
        "![Screenshot 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Afxzfat8CbD4gfBrxDJo+h/Fb4m3lxD4m8IfZ1sbOe4vn0+aaBYxDapJujaEAKmWXZ2rofhL+zRJ4J+GPw71HQ/gJJpOtaP8AtSa9qHmW/hlobiy0qTWNZhSfiMNHatYyQqrcRmFo8HaVr7corST/AHinHS0oS9eRxdn/AIuVJ+Qn71OrF/bcn6c0ZxsvJc7a80jxH/gnN4T8U+B/2PvC/hnxp4a1DR9St77WGuNP1Sze3njD6teSIWjkAYBkZWGRyrAjgivbqKKhKysTGPLFLsFFFFMoKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigArgviJpkWoeGbe2vLZZoI5Jre6hkUMrB+zA9QQCOfWu9rL1jTIpFm862M1tcLi4iXqD/fHvQB8m/Fv9h34BfEnSWk0PwbD4X1u3FxLpeteFpH02SG5lyWlcW5VZctgtvDE888mvm/9lPxX461j9qXwPDrXiPU9XtEN9D5l9cQSJb/8SyV2UMiId+4KGXDZZicrsIP6EeKPhtq9/ptxZ+HLo3C3S+SslvMsc0Cudpk+YgZQHdwcnbwM4FeNeG/2F/Enhf8AahsPi0uq6dZ6DZvdTzmSYNcymSGWFYUiVMLw6EvvwBEFCHcSoB7z4FtpV0O8lI4uriKKL3IyT/Ou6rL0fTIo1h8m2MNtbri3ibqT/fPvWpQBwXxE0yLUPDNvbXlss0Eck1vdQyKGVg/ZgeoIBHPrXzt8W/2HfgF8SdJaTQ/BsPhfW7cXEul614WkfTZIbmXJaVxblVly2C28MTzzya+stY0yKRZvOtjNbXC4uIl6g/3x71wvij4bavf6bcWfhy6Nwt0vkrJbzLHNArnaZPmIGUB3cHJ28DOBTA/Pf9lPxX461j9qXwPDrXiPU9XtEN9D5l9cQSJb/wDEsldlDIiHfuChlw2WYnK7CD+jngW2lXQ7yUji6uIoovcjJP8AOvBvDf7C/iTwv+1DYfFpdV06z0Gze6nnMkwa5lMkMsKwpEqYXh0JffgCIKEO4lfp/R9MijWHybYw21uuLeJupP8AfPvSA1KKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPif4uP498J/Cf49fsXw/Bjxpqnij4o61r3/CBatpXhK9udJv7bW4QPtFzqUUTWliLWSaZJEuZYn2WymNX8yMN638e7/wN40+Ces+AvHH7PPxA8XaT4F8T6Lb6tZaXp9/ZXN2IGtLkanpxgZJtRjtyyuyW7M0jQSxKruNje+0UU/3dGEF9lQS/7h2UL9dEndpptu6cbK1SlzSu9rzfzqaz+9pWTTStZp3Z8o/s4+J9S+Fml/GP4t/CL4T/ABIl+F9rp9leeAfBOteH9Wg1O+1aOCc3yafYaiou7a2lY2caRtFFH5qzyKoRi7L4n/Z4+J3ws/ZU8LeJbjQZfFnjrR/iXpnxB+I1ppURmm1e8a7WTUVtk+9KYIXZbaIZYpZW8a5O0V9W0VUpe8prdODV9fgaku2jkotr+7FK1jPli6bhL4XzXS68ycX3s1FySa/mk3e6t8x+DPiH418c/Gf4i/tgfDb4E+Mr/RNK+G+m6H4a0XXtBufD+qeJLyC6vbu5WC11OOCWJVWaGNHmRFlkLhTtXecH9n+7v/EX7YuqfF74F+E/irqHh/UvBOpf8Jg3xe8O6tpZsNU+1QS2NhpT6zbxTxxPuvPNit99mgihb5Xxv+uqKmKjTty6WUkvJz5uZ+esnJK2jt0Vi5Pmu5a3cW+z5VFR9GlFK9+/fT418L+JdY+MX7Ynw9+Lnw5+Gnxi0vxDHdXMXxP8N/Erw3qcWg+GLBtMljk+wXF7CLP7X9qjtYxJpcsizxyTNJujO9fsqiiqclypJWt93or627JtvfUn7V/Retur7vpdJKyStoFFFFSMKKKKACiiigAooooAKKKKACiiigDxT9snwr4o8Uax8G5fDPhvUNRXS/jVpV9qTWNm8wtLVLW9V55dgPlxqWUF2woLAE8iva6KKUFyQlHvJy++MI2/8kT+YS96opdoqP3SlK//AJM/uCiiimAUUUUAFFFFABRRRQB8G/tIfB3/AIKHWfi7WPH1l8C/hr4un174zeF7rStWtviJqy3lnodhrMElhaPaJoUi21vGPMmuZRPKEee4mAZQsYt/tG+F7LS7z9o/wf8AF39l3xR438U/EnTVl+HN54f8D3urQ3tomhwQQWCajFA0Wmvb38d1KBPJBhpxNHlpDj7norOVPmwcsP0kpJvraUYRuv737tPm3d3fdt6RqcuLWIW6tp092UpL5e80l007K3J/AfTtQ0f4HeDNJ1awmtbq18J6dDdWtxEUkhkW2jDIynBVgQQQeQRXWUUV01qrrVpVGvibf3u5z0afsaMaa+ykvuVgooorI0CiiigAooooAKKKKACiiigArN1v/kJ6P/2Em/8ASaetKs3W/wDkJ6P/ANhJv/SaegDSooooAKKKKACiiigArN8U/wDIMi/7CVn/AOlMdaVZfi9Gl0ZY0maNm1C0CyJjcv8ApMfIyCMj3BFCA1KKzf7E1P8A6HDUv+/Vt/8AGaP7E1P/AKHDUv8Av1bf/GaANKis3+xNT/6HDUv+/Vt/8Zo/sTU/+hw1L/v1bf8AxmgDSorN/sTU/wDocNS/79W3/wAZo/sTU/8AocNS/wC/Vt/8ZoA0qKzf7E1P/ocNS/79W3/xmj+xNT/6HDUv+/Vt/wDGaANKis3+xNT/AOhw1L/v1bf/ABmj+xNT/wChw1L/AL9W3/xmgDSorN/sTU/+hw1L/v1bf/GaP7E1P/ocNS/79W3/AMZoA0qKzf7E1P8A6HDUv+/Vt/8AGaP7E1P/AKHDUv8Av1bf/GaANKis3+xNT/6HDUv+/Vt/8Zo/sTU/+hw1L/v1bf8AxmgDSorN/sTU/wDocNS/79W3/wAZo/sTU/8AocNS/wC/Vt/8ZoA0qKzf7E1P/ocNS/79W3/xmj+xNT/6HDUv+/Vt/wDGaANKis3+xNT/AOhw1L/v1bf/ABmj+xNT/wChw1L/AL9W3/xmgDSorN/sTU/+hw1L/v1bf/GaP7E1P/ocNS/79W3/AMZoA0qKzf7E1P8A6HDUv+/Vt/8AGaP7E1P/AKHDUv8Av1bf/GaANKis3+xNT/6HDUv+/Vt/8Zo/sTU/+hw1L/v1bf8AxmgDSorN/sTU/wDocNS/79W3/wAZo/sTU/8AocNS/wC/Vt/8ZoA0qKzf7E1P/ocNS/79W3/xmj+xNT/6HDUv+/Vt/wDGaANKis3+xNT/AOhw1L/v1bf/ABmj+xNT/wChw1L/AL9W3/xmgDSorN/sTU/+hw1L/v1bf/GaP7E1P/ocNS/79W3/AMZoA0qKzf7E1P8A6HDUv+/Vt/8AGaP7E1P/AKHDUv8Av1bf/GaANKis3+xNT/6HDUv+/Vt/8Zo/sTU/+hw1L/v1bf8AxmgDSorN/sTU/wDocNS/79W3/wAZo/sTU/8AocNS/wC/Vt/8ZoA0qKzf7E1P/ocNS/79W3/xmj+xNT/6HDUv+/Vt/wDGaANKis3+xNT/AOhw1L/v1bf/ABmj+xNT/wChw1L/AL9W3/xmgDSorN/sTU/+hw1L/v1bf/GaP7E1P/ocNS/79W3/AMZoA0qKzf7E1P8A6HDUv+/Vt/8AGaP7E1P/AKHDUv8Av1bf/GaANKis3+xNT/6HDUv+/Vt/8Zo/sTU/+hw1L/v1bf8AxmgC1PpWn3Lb5rVd3qvGfyog0rT7Zt8Nqu71bnH51V/sTU/+hw1L/v1bf/GaP7E1P/ocNS/79W3/AMZpgaVFZv8AYmp/9DhqX/fq2/8AjNH9ian/ANDhqX/fq2/+M0gNKq8+lafctvmtV3eq8Z/Kqv8AYmp/9DhqX/fq2/8AjNH9ian/ANDhqX/fq2/+M0AWoNK0+2bfDaru9W5x+dWKzf7E1P8A6HDUv+/Vt/8AGaP7E1P/AKHDUv8Av1bf/GaANKis3+xNT/6HDUv+/Vt/8Zo/sTU/+hw1L/v1bf8AxmgDSorN/sTU/wDocNS/79W3/wAZo/sTU/8AocNS/wC/Vt/8ZoA0qKzf7E1P/ocNS/79W3/xmj+xNT/6HDUv+/Vt/wDGaANKis3+xNT/AOhw1L/v1bf/ABmj+xNT/wChw1L/AL9W3/xmgDSorN/sTU/+hw1L/v1bf/GaP7E1P/ocNS/79W3/AMZoA0qKzf7E1P8A6HDUv+/Vt/8AGaP7E1P/AKHDUv8Av1bf/GaANKis3+xNT/6HDUv+/Vt/8Zo/sTU/+hw1L/v1bf8AxmgDSorN/sTU/wDocNS/79W3/wAZo/sTU/8AocNS/wC/Vt/8ZoA0qKzf7E1P/ocNS/79W3/xmj+xNT/6HDUv+/Vt/wDGaANKis3+xNT/AOhw1L/v1bf/ABmj+xNT/wChw1L/AL9W3/xmgDSorN/sTU/+hw1L/v1bf/GaP7E1P/ocNS/79W3/AMZoA0qKzf7E1P8A6HDUv+/Vt/8AGaP7E1P/AKHDUv8Av1bf/GaANKis3+xNT/6HDUv+/Vt/8Zo/sTU/+hw1L/v1bf8AxmgDSorN/sTU/wDocNS/79W3/wAZo/sTU/8AocNS/wC/Vt/8ZoA0qKzf7E1P/ocNS/79W3/xmj+xNT/6HDUv+/Vt/wDGaANKis3+xNT/AOhw1L/v1bf/ABmj+xNT/wChw1L/AL9W3/xmgDSorN/sTU/+hw1L/v1bf/GaP7E1P/ocNS/79W3/AMZoA0qKzf7E1P8A6HDUv+/Vt/8AGaP7E1P/AKHDUv8Av1bf/GaANKis3+xNT/6HDUv+/Vt/8Zo/sTU/+hw1L/v1bf8AxmgDSorN/sTU/wDocNS/79W3/wAZo/sTU/8AocNS/wC/Vt/8ZoA0qKzf7E1P/ocNS/79W3/xmj+xNT/6HDUv+/V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