Sentement_Analysis.ipynb

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      "cell_type": "markdown",
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        "id": "qvsUR6GrjuCL"
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      "source": [
        "## **Libraries**\n"
      ]
    },
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        "id": "J-Ytj_m4i1yK"
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        "#For Cleaning\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "import re\n",
        "import nltk\n",
        "from nltk.corpus import stopwords\n",
        "from nltk.stem import PorterStemmer\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "#For Models\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.metrics import classification_report, accuracy_score\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.naive_bayes import MultinomialNB\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "#Downloads\n",
        "nltk.download('stopwords')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wCaCYCsDjFTq"
      },
      "source": [
        "## **Data Cleaning**"
      ]
    },
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      "execution_count": null,
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        "id": "idRtjb-Jjixf"
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      "source": [
        "data = pd.read_csv('/content/sentimentdataset.csv')\n",
        "\n",
        "#Removing non-important columns\n",
        "data = data.drop(columns=['Timestamp'])\n",
        "data = data.drop(columns=['ID'])\n",
        "data = data.drop(columns=['User'])\n",
        "data = data.drop(columns=['Topic'])\n",
        "data = data.drop(columns=['Source'])\n",
        "data = data.drop(columns=['Country'])\n",
        "data = data.drop(columns=['Year'])\n",
        "data = data.drop(columns=['Month'])\n",
        "data = data.drop(columns=['Day'])\n",
        "data = data.drop(columns=['Hour'])\n",
        "data = data.drop(columns=['Retweets'])\n",
        "data = data.drop(columns=['Likes'])\n"
      ]
    },
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            "text/plain": [
              "                                                Text Sentiment (Label)\n",
              "0   enjoying a beautiful day at the park         ...        Positive  \n",
              "1   traffic was terrible this morning            ...        Negative  \n",
              "2   just finished an amazing workout             ...        Positive  \n",
              "3   excited about the upcoming weekend getaway   ...        Positive  \n",
              "4   trying out a new recipe for dinner tonight   ...        Neutral   "
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# removing any non-alphapetical charachters from text column\n",
        "data['Text'] = [re.sub('[^a-zA-Z]', ' ', line).lower() for line in data['Text']]\n",
        "data.head()"
      ]
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      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', \"you're\", \"you've\", \"you'll\", \"you'd\", 'your', 'yours', 'yourself', 'yourselves', 'he', 'him', 'his', 'himself', 'she', \"she's\", 'her', 'hers', 'herself', 'it', \"it's\", 'its', 'itself', 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that', \"that'll\", 'these', 'those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will', 'just', 'don', \"don't\", 'should', \"should've\", 'now', 'd', 'll', 'm', 'o', 're', 've', 'y', 'ain', 'aren', \"aren't\", 'couldn', \"couldn't\", 'didn', \"didn't\", 'doesn', \"doesn't\", 'hadn', \"hadn't\", 'hasn', \"hasn't\", 'haven', \"haven't\", 'isn', \"isn't\", 'ma', 'mightn', \"mightn't\", 'mustn', \"mustn't\", 'needn', \"needn't\", 'shan', \"shan't\", 'shouldn', \"shouldn't\", 'wasn', \"wasn't\", 'weren', \"weren't\", 'won', \"won't\", 'wouldn', \"wouldn't\"]\n"
          ]
        }
      ],
      "source": [
        "print(stopwords.words('english'))"
      ]
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5649cb14-7385-47cf-abe4-49199143f58e 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-5649cb14-7385-47cf-abe4-49199143f58e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-32a29d3d-b3d2-42eb-a7fb-7f772a044dee\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-32a29d3d-b3d2-42eb-a7fb-7f772a044dee')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-32a29d3d-b3d2-42eb-a7fb-7f772a044dee button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                               Text Sentiment (Label)\n",
              "0       enjoying beautiful day park        Positive  \n",
              "1          traffic terrible morning        Negative  \n",
              "2          finished amazing workout        Positive  \n",
              "3  excited upcoming weekend getaway        Positive  \n",
              "4  trying new recipe dinner tonight        Neutral   "
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# removing any stop_word\n",
        "for idx, line in enumerate(data['Text']):\n",
        "    words = line.split()  # Split the line into words\n",
        "    filtered_words = [word for word in words if word.lower() not in stopwords.words('english')]\n",
        "    # Join the filtered words back into a line and update the DataFrame\n",
        "    data.at[idx, 'Text'] = ' '.join(filtered_words)\n",
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iZr6WfO9yQnm",
        "outputId": "1aba7413-ca4b-42de-b0a9-fc2e03fdc475"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 732 entries, 0 to 731\n",
            "Data columns (total 2 columns):\n",
            " #   Column             Non-Null Count  Dtype \n",
            "---  ------             --------------  ----- \n",
            " 0   Text               732 non-null    object\n",
            " 1   Sentiment (Label)  732 non-null    object\n",
            "dtypes: object(2)\n",
            "memory usage: 11.6+ KB\n"
          ]
        }
      ],
      "source": [
        "#Checking for null values\n",
        "data.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MhDF9v7Kz4MZ",
        "outputId": "3fe2fcd0-ae0a-47f7-da90-23ae5120078a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "24\n"
          ]
        }
      ],
      "source": [
        "#Checking for duplicate rows\n",
        "duplicates_count = data.duplicated().sum()\n",
        "print(duplicates_count)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yAjSbRoh0SV5",
        "outputId": "31bc673a-4d2e-41a9-a9d2-61be0927d148"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Index: 708 entries, 0 to 731\n",
            "Data columns (total 2 columns):\n",
            " #   Column             Non-Null Count  Dtype \n",
            "---  ------             --------------  ----- \n",
            " 0   Text               708 non-null    object\n",
            " 1   Sentiment (Label)  708 non-null    object\n",
            "dtypes: object(2)\n",
            "memory usage: 16.6+ KB\n"
          ]
        }
      ],
      "source": [
        "#Dropping duplicates\n",
        "data.drop_duplicates(inplace=True)\n",
        "data.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "Y2Sohtr8-wQU",
        "outputId": "323c6296-db69-476c-d823-ccb900f32b80"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 708,\n  \"fields\": [\n    {\n      \"column\": \"Text\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sentiment (Label)\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 279,\n        \"samples\": [\n          \" Elation       \",\n          \" Confidence    \",\n          \" Loss \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
              "type": "dataframe",
              "variable_name": "data"
            },
            "text/html": [
              "\n",
              "  <div id=\"df-3a19316b-20ce-434d-8a1b-51dd7667c9df\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Text</th>\n",
              "      <th>Sentiment (Label)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>[enjoying, beautiful, day, park]</td>\n",
              "      <td>Positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>[traffic, terrible, morning]</td>\n",
              "      <td>Negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>[finished, amazing, workout]</td>\n",
              "      <td>Positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>[excited, upcoming, weekend, getaway]</td>\n",
              "      <td>Positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>[trying, new, recipe, dinner, tonight]</td>\n",
              "      <td>Neutral</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>727</th>\n",
              "      <td>[collaborating, science, project, received, re...</td>\n",
              "      <td>Happy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>728</th>\n",
              "      <td>[attending, surprise, birthday, party, organiz...</td>\n",
              "      <td>Happy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>729</th>\n",
              "      <td>[successfully, fundraising, school, charity, i...</td>\n",
              "      <td>Happy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>730</th>\n",
              "      <td>[participating, multicultural, festival, celeb...</td>\n",
              "      <td>Happy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>731</th>\n",
              "      <td>[organizing, virtual, talent, show, challengin...</td>\n",
              "      <td>Happy</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>708 rows × 2 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3a19316b-20ce-434d-8a1b-51dd7667c9df')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-3a19316b-20ce-434d-8a1b-51dd7667c9df 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-3a19316b-20ce-434d-8a1b-51dd7667c9df');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-49efc916-4a2d-47b9-b1c9-496e5aeef3b8\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-49efc916-4a2d-47b9-b1c9-496e5aeef3b8')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-49efc916-4a2d-47b9-b1c9-496e5aeef3b8 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_957efaf4-b287-476c-8e3d-b5d14bf1c504\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('data')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('data');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                                                  Text Sentiment (Label)\n",
              "0                     [enjoying, beautiful, day, park]        Positive  \n",
              "1                         [traffic, terrible, morning]        Negative  \n",
              "2                         [finished, amazing, workout]        Positive  \n",
              "3                [excited, upcoming, weekend, getaway]        Positive  \n",
              "4               [trying, new, recipe, dinner, tonight]        Neutral   \n",
              "..                                                 ...               ...\n",
              "727  [collaborating, science, project, received, re...            Happy \n",
              "728  [attending, surprise, birthday, party, organiz...            Happy \n",
              "729  [successfully, fundraising, school, charity, i...            Happy \n",
              "730  [participating, multicultural, festival, celeb...            Happy \n",
              "731  [organizing, virtual, talent, show, challengin...            Happy \n",
              "\n",
              "[708 rows x 2 columns]"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#Split each row in column text\n",
        "data['Text'] = [line.split() for line in data['Text']]\n",
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "WIhtdKYv1RAD",
        "outputId": "1dab301d-1230-466d-9b89-75df5aa18aee"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 708,\n  \"fields\": [\n    {\n      \"column\": \"Text\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sentiment (Label)\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 279,\n        \"samples\": [\n          \" Elation       \",\n          \" Confidence    \",\n          \" Loss \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Stemmed_Text\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
              "type": "dataframe",
              "variable_name": "data"
            },
            "text/html": [
              "\n",
              "  <div id=\"df-672646ed-7d58-4e27-a240-70d1dcb5ddab\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Text</th>\n",
              "      <th>Sentiment (Label)</th>\n",
              "      <th>Stemmed_Text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>[enjoying, beautiful, day, park]</td>\n",
              "      <td>Positive</td>\n",
              "      <td>[enjoy, beauti, day, park]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>[traffic, terrible, morning]</td>\n",
              "      <td>Negative</td>\n",
              "      <td>[traffic, terribl, morn]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>[finished, amazing, workout]</td>\n",
              "      <td>Positive</td>\n",
              "      <td>[finish, amaz, workout]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>[excited, upcoming, weekend, getaway]</td>\n",
              "      <td>Positive</td>\n",
              "      <td>[excit, upcom, weekend, getaway]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>[trying, new, recipe, dinner, tonight]</td>\n",
              "      <td>Neutral</td>\n",
              "      <td>[tri, new, recip, dinner, tonight]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>[feeling, grateful, little, things, life]</td>\n",
              "      <td>Positive</td>\n",
              "      <td>[feel, grate, littl, thing, life]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>[rainy, days, call, cozy, blankets, hot, cocoa]</td>\n",
              "      <td>Positive</td>\n",
              "      <td>[raini, day, call, cozi, blanket, hot, cocoa]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>[new, movie, release, must, watch]</td>\n",
              "      <td>Positive</td>\n",
              "      <td>[new, movi, releas, must, watch]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>[political, discussions, heating, timeline]</td>\n",
              "      <td>Negative</td>\n",
              "      <td>[polit, discuss, heat, timelin]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>[missing, summer, vibes, beach, days]</td>\n",
              "      <td>Neutral</td>\n",
              "      <td>[miss, summer, vibe, beach, day]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-672646ed-7d58-4e27-a240-70d1dcb5ddab')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
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              "\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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",
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              "      fill: #FFFFFF;\n",
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              "\n",
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              "        document.querySelector('#df-672646ed-7d58-4e27-a240-70d1dcb5ddab 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-672646ed-7d58-4e27-a240-70d1dcb5ddab');\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",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
              "\n",
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              "            title=\"Suggest charts\"\n",
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              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
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              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f1ad43e7-531a-47a4-81ae-90fd64896884 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                                              Text Sentiment (Label)  \\\n",
              "0                 [enjoying, beautiful, day, park]        Positive     \n",
              "1                     [traffic, terrible, morning]        Negative     \n",
              "2                     [finished, amazing, workout]        Positive     \n",
              "3            [excited, upcoming, weekend, getaway]        Positive     \n",
              "4           [trying, new, recipe, dinner, tonight]        Neutral      \n",
              "5        [feeling, grateful, little, things, life]        Positive     \n",
              "6  [rainy, days, call, cozy, blankets, hot, cocoa]        Positive     \n",
              "7               [new, movie, release, must, watch]        Positive     \n",
              "8      [political, discussions, heating, timeline]        Negative     \n",
              "9            [missing, summer, vibes, beach, days]        Neutral      \n",
              "\n",
              "                                    Stemmed_Text  \n",
              "0                     [enjoy, beauti, day, park]  \n",
              "1                       [traffic, terribl, morn]  \n",
              "2                        [finish, amaz, workout]  \n",
              "3               [excit, upcom, weekend, getaway]  \n",
              "4             [tri, new, recip, dinner, tonight]  \n",
              "5              [feel, grate, littl, thing, life]  \n",
              "6  [raini, day, call, cozi, blanket, hot, cocoa]  \n",
              "7               [new, movi, releas, must, watch]  \n",
              "8                [polit, discuss, heat, timelin]  \n",
              "9               [miss, summer, vibe, beach, day]  "
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#using porter stemmer to reduce words to their base form and putting them in a new column\n",
        "ps = PorterStemmer()\n",
        "\n",
        "def stem_words(word_list):\n",
        "    if isinstance(word_list, list):\n",
        "        return [ps.stem(word) for word in word_list]\n",
        "    else:\n",
        "        return []\n",
        "\n",
        "data['Stemmed_Text'] = data['Text'].apply(stem_words)\n",
        "data.head(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "2V5xWKGPelxd",
        "outputId": "9b961324-237f-4320-d1ff-21e9ce586e91"
      },
      "outputs": [
        {
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              "type": "dataframe",
              "variable_name": "data"
            },
            "text/html": [
              "\n",
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              "<style scoped>\n",
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              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\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>Text</th>\n",
              "      <th>Sentiment (Label)</th>\n",
              "      <th>Stemmed_Text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>[enjoying, beautiful, day, park]</td>\n",
              "      <td>positive</td>\n",
              "      <td>[enjoy, beauti, day, park]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>[traffic, terrible, morning]</td>\n",
              "      <td>negative</td>\n",
              "      <td>[traffic, terribl, morn]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>[finished, amazing, workout]</td>\n",
              "      <td>positive</td>\n",
              "      <td>[finish, amaz, workout]</td>\n",
              "    </tr>\n",
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              "      <th>3</th>\n",
              "      <td>[excited, upcoming, weekend, getaway]</td>\n",
              "      <td>positive</td>\n",
              "      <td>[excit, upcom, weekend, getaway]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>[trying, new, recipe, dinner, tonight]</td>\n",
              "      <td>neutral</td>\n",
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              "      buttonEl.style.display =\n",
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              "          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",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "  }\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-46151f2d-f94f-4915-a1cc-05b174f970b1 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                                     Text Sentiment (Label)  \\\n",
              "0        [enjoying, beautiful, day, park]        positive     \n",
              "1            [traffic, terrible, morning]        negative     \n",
              "2            [finished, amazing, workout]        positive     \n",
              "3   [excited, upcoming, weekend, getaway]        positive     \n",
              "4  [trying, new, recipe, dinner, tonight]        neutral      \n",
              "\n",
              "                         Stemmed_Text  \n",
              "0          [enjoy, beauti, day, park]  \n",
              "1            [traffic, terribl, morn]  \n",
              "2             [finish, amaz, workout]  \n",
              "3    [excit, upcom, weekend, getaway]  \n",
              "4  [tri, new, recip, dinner, tonight]  "
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#Lower casing Sentiment (Label) column\n",
        "data['Sentiment (Label)'] = [re.sub('[^a-zA-Z]', ' ', line).lower() for line in data['Sentiment (Label)']]\n",
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8LcPtC7aU4aH",
        "outputId": "c3a4efa5-7e05-414a-88a5-9a67652d6772"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[' positive  ' ' negative  ' ' neutral   ' ' anger        '\n",
            " ' fear         ' ' sadness      ' ' disgust      ' ' happiness    '\n",
            " ' joy          ' ' love         ' ' amusement    ' ' enjoyment    '\n",
            " ' admiration   ' ' affection    ' ' awe          ' ' disappointed '\n",
            " ' surprise     ' ' acceptance   ' ' adoration    ' ' anticipation '\n",
            " ' bitter       ' ' calmness     ' ' confusion    ' ' excitement   '\n",
            " ' kind         ' ' pride        ' ' shame        ' ' confusion '\n",
            " ' excitement ' ' shame ' ' elation       ' ' euphoria      '\n",
            " ' contentment   ' ' serenity      ' ' gratitude     ' ' hope          '\n",
            " ' empowerment   ' ' compassion    ' ' tenderness    ' ' arousal       '\n",
            " ' enthusiasm    ' ' fulfillment  ' ' reverence     ' ' compassion'\n",
            " ' fulfillment   ' ' reverence ' ' elation   ' ' despair         '\n",
            " ' grief           ' ' loneliness      ' ' jealousy        '\n",
            " ' resentment      ' ' frustration     ' ' boredom         '\n",
            " ' anxiety         ' ' intimidation    ' ' helplessness    '\n",
            " ' envy            ' ' regret         ' ' disgust         '\n",
            " ' despair      ' ' loneliness ' ' frustration ' ' anxiety   '\n",
            " ' intimidation ' ' helplessness ' ' jealousy    ' ' curiosity       '\n",
            " ' indifference    ' ' confusion       ' ' numbness        '\n",
            " ' melancholy      ' ' nostalgia       ' ' ambivalence     '\n",
            " ' acceptance      ' ' determination   ' ' serenity        ' ' numbness '\n",
            " ' zest ' ' contentment ' ' hopeful ' ' proud ' ' grateful '\n",
            " ' empathetic ' ' compassionate ' ' playful ' ' free spirited '\n",
            " ' inspired ' ' confident ' ' serenity ' ' curiosity ' ' ambivalence '\n",
            " ' despair ' ' bitterness ' ' yearning ' ' fearful ' ' apprehensive '\n",
            " ' overwhelmed ' ' jealous ' ' devastated ' ' frustrated ' ' envious '\n",
            " ' dismissive ' ' awe           ' ' determination ' ' nostalgia      '\n",
            " ' thrill        ' ' calmness      ' ' overwhelmed   ' ' gratitude   '\n",
            " ' bittersweet ' ' curiosity     ' ' admiration    ' ' overjoyed     '\n",
            " ' inspiration   ' ' motivation    ' ' amusement     ' ' contemplation '\n",
            " ' joyfulreunion ' ' excitement    ' ' satisfaction  ' ' blessed       '\n",
            " ' anticipation  ' ' reflection    ' ' nostalgia     ' ' appreciation  '\n",
            " ' confidence    ' ' surprise      ' ' accomplishment ' ' wonderment    '\n",
            " ' optimism      ' ' pride         ' ' happiness     ' ' curiosity   '\n",
            " ' enchantment   ' ' intrigue      ' ' playfuljoy    ' ' mindfulness   '\n",
            " ' dreamchaser   ' ' elegance ' ' whimsy        ' ' pensive '\n",
            " ' thrill      ' ' harmony    ' ' creativity   ' ' radiance    '\n",
            " ' wonder     ' ' rejuvenation ' ' inspiration ' ' coziness     '\n",
            " ' gratitude  ' ' adventure ' ' euphoria   ' ' awe    ' ' melodic       '\n",
            " ' festivejoy    ' ' innerjourney  ' ' freedom       ' ' dazzle        '\n",
            " ' adrenaline     ' ' harmony       ' ' artisticburst ' ' radiance      '\n",
            " ' wonder       ' ' inspiration  ' ' culinaryodyssey ' ' euphoria     '\n",
            " ' curiosity  ' ' resilience   ' ' immersion ' ' nostalgia '\n",
            " ' spark        ' ' gratitude    ' ' marvel       ' ' serenity   '\n",
            " ' heartbreak    ' ' loneliness    ' ' grief      ' ' despair   '\n",
            " ' betrayal      ' ' suffering ' ' emotionalstorm ' ' regret        '\n",
            " ' isolation ' ' disappointment ' ' lostlove ' ' melancholy '\n",
            " ' exhaustion ' ' sorrow      ' ' darkness     ' ' desperation '\n",
            " ' ruins      ' ' desolation ' ' regret ' ' grief ' ' heartbreak '\n",
            " ' betrayal ' ' resilience ' ' sorrow ' ' loss ' ' heartache '\n",
            " ' solitude ' ' joy ' ' happiness ' ' enthusiasm ' ' gratitude '\n",
            " ' positivity ' ' kindness ' ' friendship ' ' love ' ' surprise '\n",
            " ' success ' ' thrill ' ' reflection ' ' enchantment ' ' exploration '\n",
            " ' awe ' ' amazement ' ' romance ' ' captivation ' ' wonder '\n",
            " ' tranquility ' ' grandeur ' ' emotion ' ' energy ' ' celebration '\n",
            " ' charm ' ' ecstasy ' ' hope ' ' creativity ' ' colorful ' ' pride '\n",
            " ' hypnotic ' ' connection ' ' iconic ' ' euphoria ' ' journey '\n",
            " ' engagement ' ' touched ' ' suspense ' ' satisfaction ' ' admiration '\n",
            " ' triumph ' ' heartwarming ' ' obstacle ' ' sympathy ' ' pressure '\n",
            " ' renewed effort ' ' miscalculation ' ' challenge ' ' solace '\n",
            " ' breakthrough ' ' harmony ' ' joy in baking ' ' envisioning history '\n",
            " ' imagination ' ' vibrancy ' ' mesmerizing ' ' culinary adventure '\n",
            " ' winter magic ' ' thrilling journey ' ' nature s beauty '\n",
            " ' celestial wonder ' ' creative inspiration ' ' runway creativity '\n",
            " ' ocean s freedom ' ' whispers of the past ' ' boredom ' ' indifference '\n",
            " ' disgust ' ' relief ' ' positive ' ' embarrassed ' ' mischievous '\n",
            " ' sad ' ' hate ' ' bad ' ' neutral ' ' happy ']\n"
          ]
        }
      ],
      "source": [
        "#unique values in Sentiment (Label) column\n",
        "print(data['Sentiment (Label)'].unique())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "i74pn_zEalLW",
        "outputId": "22ba9dab-8916-4a60-c20a-dc800dc48751"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 708,\n  \"fields\": [\n    {\n      \"column\": \"Text\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sentiment (Label)\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 279,\n        \"samples\": [\n          \" elation       \",\n          \" confidence    \",\n          \" loss \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Stemmed_Text\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sentiment_Class\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"positive\",\n          \"negative\",\n          \"neutral\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
              "type": "dataframe",
              "variable_name": "data"
            },
            "text/html": [
              "\n",
              "  <div id=\"df-de0697f3-9ef0-4a54-a23a-4f0769f0b855\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Text</th>\n",
              "      <th>Sentiment (Label)</th>\n",
              "      <th>Stemmed_Text</th>\n",
              "      <th>Sentiment_Class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>[enjoying, beautiful, day, park]</td>\n",
              "      <td>positive</td>\n",
              "      <td>[enjoy, beauti, day, park]</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>[traffic, terrible, morning]</td>\n",
              "      <td>negative</td>\n",
              "      <td>[traffic, terribl, morn]</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>[finished, amazing, workout]</td>\n",
              "      <td>positive</td>\n",
              "      <td>[finish, amaz, workout]</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>[excited, upcoming, weekend, getaway]</td>\n",
              "      <td>positive</td>\n",
              "      <td>[excit, upcom, weekend, getaway]</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>[trying, new, recipe, dinner, tonight]</td>\n",
              "      <td>neutral</td>\n",
              "      <td>[tri, new, recip, dinner, tonight]</td>\n",
              "      <td>neutral</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>727</th>\n",
              "      <td>[collaborating, science, project, received, re...</td>\n",
              "      <td>happy</td>\n",
              "      <td>[collabor, scienc, project, receiv, recognit, ...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>728</th>\n",
              "      <td>[attending, surprise, birthday, party, organiz...</td>\n",
              "      <td>happy</td>\n",
              "      <td>[attend, surpris, birthday, parti, organ, frie...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>729</th>\n",
              "      <td>[successfully, fundraising, school, charity, i...</td>\n",
              "      <td>happy</td>\n",
              "      <td>[success, fundrais, school, chariti, initi, jo...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>730</th>\n",
              "      <td>[participating, multicultural, festival, celeb...</td>\n",
              "      <td>happy</td>\n",
              "      <td>[particip, multicultur, festiv, celebr, divers...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>731</th>\n",
              "      <td>[organizing, virtual, talent, show, challengin...</td>\n",
              "      <td>happy</td>\n",
              "      <td>[organ, virtual, talent, show, challeng, time,...</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>708 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-de0697f3-9ef0-4a54-a23a-4f0769f0b855')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-de0697f3-9ef0-4a54-a23a-4f0769f0b855 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-de0697f3-9ef0-4a54-a23a-4f0769f0b855');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-2f4ba197-0246-4262-a341-44cdb838a9af\">\n",
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              "            title=\"Suggest charts\"\n",
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              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
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              "    }\n",
              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-2f4ba197-0246-4262-a341-44cdb838a9af button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_41cb2f60-7990-465f-a16d-9cb508da34cf\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('data')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_41cb2f60-7990-465f-a16d-9cb508da34cf button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('data');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                                                  Text Sentiment (Label)  \\\n",
              "0                     [enjoying, beautiful, day, park]        positive     \n",
              "1                         [traffic, terrible, morning]        negative     \n",
              "2                         [finished, amazing, workout]        positive     \n",
              "3                [excited, upcoming, weekend, getaway]        positive     \n",
              "4               [trying, new, recipe, dinner, tonight]        neutral      \n",
              "..                                                 ...               ...   \n",
              "727  [collaborating, science, project, received, re...            happy    \n",
              "728  [attending, surprise, birthday, party, organiz...            happy    \n",
              "729  [successfully, fundraising, school, charity, i...            happy    \n",
              "730  [participating, multicultural, festival, celeb...            happy    \n",
              "731  [organizing, virtual, talent, show, challengin...            happy    \n",
              "\n",
              "                                          Stemmed_Text Sentiment_Class  \n",
              "0                           [enjoy, beauti, day, park]        positive  \n",
              "1                             [traffic, terribl, morn]        negative  \n",
              "2                              [finish, amaz, workout]        positive  \n",
              "3                     [excit, upcom, weekend, getaway]        positive  \n",
              "4                   [tri, new, recip, dinner, tonight]         neutral  \n",
              "..                                                 ...             ...  \n",
              "727  [collabor, scienc, project, receiv, recognit, ...        positive  \n",
              "728  [attend, surpris, birthday, parti, organ, frie...        positive  \n",
              "729  [success, fundrais, school, chariti, initi, jo...        positive  \n",
              "730  [particip, multicultur, festiv, celebr, divers...        positive  \n",
              "731  [organ, virtual, talent, show, challeng, time,...        positive  \n",
              "\n",
              "[708 rows x 4 columns]"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "\n",
        "#Categorize into POSITIVE or NEGATIVE or NEUTRAL\n",
        "positive_keywords = { 'positive', 'happiness', 'joy', 'love', 'amusement','enjoyment', 'admiration', 'excitement', 'kind', 'pride', 'gratitude', 'hope',\n",
        "                    'empowerment', 'arousal', 'enthusiasm', 'hopeful', 'proud', 'grateful', 'free', 'inspired',\n",
        "                      'overjoyed', 'inspiration', 'motivation', 'joyfulreunion', 'satisfaction', 'blessed', 'optimism',\n",
        "                       'enchantment', 'playfuljoy', 'dreamchaser', 'thrill', 'creativity',\n",
        "                      'adventure', 'euphoria', 'festivejoy', 'freedom', 'artisticburst', 'marvel', 'positivity',\n",
        "                      'kindness', 'friendship', 'success', 'amazement', 'celebration', 'charm', 'ecstasy',\n",
        "                      'iconic', 'engagement', 'touched', 'heartwarming',\n",
        "                      'renewed effort', 'thrilling journey', 'celestial wonder', 'creative inspiration',\n",
        "                     'runway creativity', 'relief', 'happy', 'elation', 'contentment', 'reverence', 'dazzle'}\n",
        "\n",
        "negative_keywords = {'negative', 'anger', 'fear', 'sadness', 'disgust', 'awe', 'disappointment', 'bitterness', 'shame', 'despair', 'grief', 'loneliness', 'jealousy',\n",
        "                     'resentment', 'frustration', 'boredom', 'anxiety', 'intimidation', 'helplessness', 'envy', 'regret', 'melancholy', 'exhaustion', 'sorrow', 'darkness',\n",
        "                   'desperation', 'desolation', 'heartbreak','overwhelmed', 'devastated', 'betrayal', 'suffering', 'isolation', 'suspense'}\n",
        "\n",
        "def classify_sentiment(label):\n",
        "    #Split column elements\n",
        "    label = label.split()\n",
        "\n",
        "    # Check if any positive keywords are in the label\n",
        "    if set(label).intersection(positive_keywords):\n",
        "        return 'positive'\n",
        "\n",
        "    # Check if any negative keywords are in the label\n",
        "    elif set(label).intersection(negative_keywords):\n",
        "        return 'negative'\n",
        "\n",
        "    return 'neutral'\n",
        "\n",
        "\n",
        "\n",
        "# Apply the classify_sentiment function to the 'Sentiment (Label)' column\n",
        "data['Sentiment_Class'] = data['Sentiment (Label)'].apply(classify_sentiment)\n",
        "\n",
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "YlGNCr7ENtMW"
      },
      "outputs": [],
      "source": [
        "\n",
        "X = data['Stemmed_Text']  # Feature (text)\n",
        "y = data['Sentiment_Class']  # Target labels (positive, negative, neutral)\n",
        "\n",
        "# Split the data into train and test sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.15, random_state=25)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9rJ53Amc2t1C"
      },
      "outputs": [],
      "source": [
        "# Convert lists of lists to lists of strings\n",
        "X_train = [\" \".join(doc) for doc in X_train]\n",
        "X_test = [\" \".join(doc) for doc in X_test]\n",
        "\n",
        "# Initialize the TF-IDF vectorizer\n",
        "tfidf_vectorizer = TfidfVectorizer(max_features=1700)\n",
        "\n",
        "# Fit and transform the training data\n",
        "X_train_tfidf = tfidf_vectorizer.fit_transform(X_train)\n",
        "\n",
        "# Transform the testing data\n",
        "X_test_tfidf = tfidf_vectorizer.transform(X_test)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uUiY2_-tyFRj"
      },
      "source": [
        "## **Models**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q6ppuJ-XyLAm"
      },
      "source": [
        "# SVM"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "p0CoYzN1N90v"
      },
      "outputs": [],
      "source": [
        "# Initialize the SVM classifier\n",
        "svm_classifier = SVC(kernel = 'linear')\n",
        "\n",
        "# Train the model\n",
        "svm_classifier.fit(X_train_tfidf, y_train)\n",
        "\n",
        "# Make predictions\n",
        "y_pred_Test = svm_classifier.predict(X_test_tfidf)\n",
        "y_pred_Train = svm_classifier.predict(X_train_tfidf)\n",
        "\n",
        "print(classification_report(y_test, y_pred_Test))\n",
        "print(\"Test Accuracy:\", accuracy_score(y_test, y_pred_Test))\n",
        "\n",
        "print(classification_report(y_train, y_pred_Train))\n",
        "print(\"Train Accuracy:\", accuracy_score(y_train, y_pred_Train))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wLZ-Mo9YyOjo"
      },
      "source": [
        "# Naive Bayes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ynwXER0gLps5",
        "outputId": "3175d4db-f5fd-4a4d-91cd-e4c726a4b0cc"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Naive Bayes Test Accuracy: 0.719626168224299\n",
            "Naive Bayes Train Accuracy: 0.9068219633943427\n"
          ]
        }
      ],
      "source": [
        "\n",
        "# Define the Naive Bayes pipeline with TF-IDF vectorizer and Multinomial Naive Bayes classifier\n",
        "nb_pipeline = Pipeline([\n",
        "    ('tfidf', tfidf_vectorizer),  # TF-IDF vectorizer\n",
        "    ('nb', MultinomialNB())  # Multinomial Naive Bayes classifier\n",
        "])\n",
        "\n",
        "# Train the Naive Bayes model\n",
        "nb_pipeline.fit(X_train, y_train)\n",
        "\n",
        "# Predict on the test data\n",
        "y_pred_nb = nb_pipeline.predict(X_test)\n",
        "y_pred_nb_train = nb_pipeline.predict(X_train)\n",
        "\n",
        "# Calculate accuracy\n",
        "accuracy_nb = accuracy_score(y_test, y_pred_nb)\n",
        "accuracy_nb_train = accuracy_score(y_train, y_pred_nb_train)\n",
        "\n",
        "print(\"Naive Bayes Test Accuracy:\", accuracy_nb)\n",
        "print(\"Naive Bayes Train Accuracy:\", accuracy_nb_train)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NukKjZ1NySpS"
      },
      "source": [
        "# Logistic Regression"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BuVCoeuaOftM",
        "outputId": "2fbd1129-ed24-4671-9ff3-4ca3e46cb825"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Logistic Regression Test Accuracy: 0.7663551401869159\n",
            "Logistic Regression train Accuracy: 0.9550748752079867\n"
          ]
        }
      ],
      "source": [
        "# Define the Logistic Regression pipeline with TF-IDF vectorizer and Logistic Regression classifier\n",
        "logreg_pipeline = Pipeline([\n",
        "    ('tfidf', TfidfVectorizer(max_features=1700)),  # Convert text to TF-IDF features\n",
        "    ('logreg', LogisticRegression(max_iter=1000))  # Logistic Regression classifier\n",
        "])\n",
        "\n",
        "# Train the Logistic Regression model\n",
        "logreg_pipeline.fit(X_train, y_train)\n",
        "\n",
        "# Predict on the test data\n",
        "y_pred_logreg = logreg_pipeline.predict(X_test)\n",
        "y_pred_logreg_Train = logreg_pipeline.predict(X_train)\n",
        "\n",
        "\n",
        "# Calculate accuracy\n",
        "accuracy_logreg = accuracy_score(y_test, y_pred_logreg)\n",
        "accuracy_logreg_Train = accuracy_score(y_train, y_pred_logreg_Train)\n",
        "\n",
        "print(\"Logistic Regression Test Accuracy:\", accuracy_logreg)\n",
        "print(\"Logistic Regression train Accuracy:\", accuracy_logreg_Train)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "32Kx_9TiyWXZ"
      },
      "source": [
        "## **GUI**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VXjnUxDh3GcE",
        "outputId": "69bd4b72-c365-46d1-b816-35aec8639af4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Writing app.py\n"
          ]
        }
      ],
      "source": [
        "%%writefile app.py"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_GZWwBC0p4pW",
        "outputId": "2dfeb2b5-43f0-4541-af60-ef0f58c8ee68"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting streamlit\n",
            "  Downloading streamlit-1.35.0-py2.py3-none-any.whl (8.6 MB)\n",
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            "Collecting gitpython!=3.1.19,<4,>=3.0.7 (from streamlit)\n",
            "  Downloading GitPython-3.1.43-py3-none-any.whl (207 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.3/207.3 kB\u001b[0m \u001b[31m10.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting pydeck<1,>=0.8.0b4 (from streamlit)\n",
            "  Downloading pydeck-0.9.1-py2.py3-none-any.whl (6.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.9/6.9 MB\u001b[0m \u001b[31m45.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Collecting watchdog>=2.1.5 (from streamlit)\n",
            "  Downloading watchdog-4.0.1-py3-none-manylinux2014_x86_64.whl (83 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m83.0/83.0 kB\u001b[0m \u001b[31m10.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Collecting gitdb<5,>=4.0.1 (from gitpython!=3.1.19,<4,>=3.0.7->streamlit)\n",
            "  Downloading gitdb-4.0.11-py3-none-any.whl (62 kB)\n",
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            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.27->streamlit) (2024.2.2)\n",
            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich<14,>=10.14.0->streamlit) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich<14,>=10.14.0->streamlit) (2.16.1)\n",
            "Collecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->gitpython!=3.1.19,<4,>=3.0.7->streamlit)\n",
            "  Downloading smmap-5.0.1-py3-none-any.whl (24 kB)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->altair<6,>=4.0->streamlit) (2.1.5)\n",
            "Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit) (23.2.0)\n",
            "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit) (2023.12.1)\n",
            "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit) (0.35.1)\n",
            "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit) (0.18.1)\n",
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            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas<3,>=1.3.0->streamlit) (1.16.0)\n",
            "Installing collected packages: watchdog, smmap, pydeck, gitdb, gitpython, streamlit\n",
            "Successfully installed gitdb-4.0.11 gitpython-3.1.43 pydeck-0.9.1 smmap-5.0.1 streamlit-1.35.0 watchdog-4.0.1\n"
          ]
        }
      ],
      "source": [
        "pip install streamlit\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Xd19N8khcUhE"
      },
      "outputs": [],
      "source": [
        "! wget -q -o - ipv4.incanhazip.com\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-prKskOqePLg",
        "outputId": "67e898fa-7a5e-4a8e-84a8-bb760ab8f9f8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "34.86.183.101"
          ]
        }
      ],
      "source": [
        "! wget -q -O - https://loca.lt/mytunnelpassword\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L0pvUhwbdBcb",
        "outputId": "50b2bef9-dbdb-484c-9f91-88f90b6eec73"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Collecting usage statistics. To deactivate, set browser.gatherUsageStats to false.\n",
            "\u001b[0m\n",
            "\u001b[0m\n",
            "\u001b[34m\u001b[1m  You can now view your Streamlit app in your browser.\u001b[0m\n",
            "\u001b[0m\n",
            "\u001b[34m  Local URL: \u001b[0m\u001b[1mhttp://localhost:8501\u001b[0m\n",
            "\u001b[34m  Network URL: \u001b[0m\u001b[1mhttp://172.28.0.12:8501\u001b[0m\n",
            "\u001b[34m  External URL: \u001b[0m\u001b[1mhttp://34.86.183.101:8501\u001b[0m\n",
            "\u001b[0m\n",
            "\u001b[K\u001b[?25hnpx: installed 22 in 3.86s\n",
            "your url is: https://cool-keys-drum.loca.lt\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/stopwords.zip.\n",
            "Accuracy: 0.7663551401869159\n",
            "Accuracy: 0.9434276206322796\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "    negative       0.92      0.60      0.73        20\n",
            "     neutral       0.71      0.74      0.73        43\n",
            "    positive       0.78      0.86      0.82        44\n",
            "\n",
            "    accuracy                           0.77       107\n",
            "   macro avg       0.80      0.74      0.76       107\n",
            "weighted avg       0.78      0.77      0.76       107\n",
            "\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "2024-05-27 23:23:24.189 `label` got an empty value. This is discouraged for accessibility reasons and may be disallowed in the future by raising an exception. Please provide a non-empty label and hide it with label_visibility if needed.\n",
            "Accuracy: 0.7663551401869159\n",
            "Accuracy: 0.9434276206322796\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "    negative       0.92      0.60      0.73        20\n",
            "     neutral       0.71      0.74      0.73        43\n",
            "    positive       0.78      0.86      0.82        44\n",
            "\n",
            "    accuracy                           0.77       107\n",
            "   macro avg       0.80      0.74      0.76       107\n",
            "weighted avg       0.78      0.77      0.76       107\n",
            "\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "2024-05-27 23:23:30.361 `label` got an empty value. This is discouraged for accessibility reasons and may be disallowed in the future by raising an exception. Please provide a non-empty label and hide it with label_visibility if needed.\n",
            "Accuracy: 0.7663551401869159\n",
            "Accuracy: 0.9434276206322796\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "    negative       0.92      0.60      0.73        20\n",
            "     neutral       0.71      0.74      0.73        43\n",
            "    positive       0.78      0.86      0.82        44\n",
            "\n",
            "    accuracy                           0.77       107\n",
            "   macro avg       0.80      0.74      0.76       107\n",
            "weighted avg       0.78      0.77      0.76       107\n",
            "\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "2024-05-27 23:23:35.123 `label` got an empty value. This is discouraged for accessibility reasons and may be disallowed in the future by raising an exception. Please provide a non-empty label and hide it with label_visibility if needed.\n",
            "Accuracy: 0.7663551401869159\n",
            "Accuracy: 0.9434276206322796\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "    negative       0.92      0.60      0.73        20\n",
            "     neutral       0.71      0.74      0.73        43\n",
            "    positive       0.78      0.86      0.82        44\n",
            "\n",
            "    accuracy                           0.77       107\n",
            "   macro avg       0.80      0.74      0.76       107\n",
            "weighted avg       0.78      0.77      0.76       107\n",
            "\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "2024-05-27 23:24:34.032 `label` got an empty value. This is discouraged for accessibility reasons and may be disallowed in the future by raising an exception. Please provide a non-empty label and hide it with label_visibility if needed.\n",
            "Accuracy: 0.7663551401869159\n",
            "Accuracy: 0.9434276206322796\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "    negative       0.92      0.60      0.73        20\n",
            "     neutral       0.71      0.74      0.73        43\n",
            "    positive       0.78      0.86      0.82        44\n",
            "\n",
            "    accuracy                           0.77       107\n",
            "   macro avg       0.80      0.74      0.76       107\n",
            "weighted avg       0.78      0.77      0.76       107\n",
            "\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "2024-05-27 23:29:13.316 `label` got an empty value. This is discouraged for accessibility reasons and may be disallowed in the future by raising an exception. Please provide a non-empty label and hide it with label_visibility if needed.\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "2024-05-27 23:29:23.177 `label` got an empty value. This is discouraged for accessibility reasons and may be disallowed in the future by raising an exception. Please provide a non-empty label and hide it with label_visibility if needed.\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "2024-05-27 23:29:25.928 `label` got an empty value. This is discouraged for accessibility reasons and may be disallowed in the future by raising an exception. Please provide a non-empty label and hide it with label_visibility if needed.\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "2024-05-27 23:33:16.279 `label` got an empty value. This is discouraged for accessibility reasons and may be disallowed in the future by raising an exception. Please provide a non-empty label and hide it with label_visibility if needed.\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "2024-05-27 23:33:25.866 `label` got an empty value. This is discouraged for accessibility reasons and may be disallowed in the future by raising an exception. Please provide a non-empty label and hide it with label_visibility if needed.\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
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          ]
        }
      ],
      "source": [
        "! streamlit run app.py & npx localtunnel --port 8501"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}