Introduction_to_NLP_Airline_Sentiment.ipynb

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        "<a href=\"https://colab.research.google.com/github/mukul-mschauhan/Machine-Learning-Projects/blob/master/Introduction_to_NLP_Airline_Sentiment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "The data we're providing on Kaggle is a slightly reformatted version of the original source. It includes both a CSV file and SQLite database. The code that does these transformations is available on GitHub\n",
        "\n",
        "For example, it contains whether the sentiment of the tweets in this set was **positive, neutral, or negative** for six US airlines:"
      ]
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        "id": "6oQUt2NlBmmL"
      },
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      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ]
    },
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Request for tomorrow's flight?\",\n          \"@united why I won't check my carry on. Watched a handler throw this bag -- miss the conveyer belt -- sat there 10 min http://t.co/lyoocx5mSH\",\n          \"@SouthwestAir you guys are so clever \\ud83d\\ude03 http://t.co/qn5odUGFqK\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"tweet_coord\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 832,\n        \"samples\": [\n          \"[40.04915451, -75.10364317]\",\n          \"[32.97609561, -96.53349238]\",\n          \"[26.37852293, -81.78472152]\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"tweet_created\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 14247,\n        \"samples\": [\n          \"2015-02-23 07:40:55 -0800\",\n          \"2015-02-21 16:20:09 -0800\",\n          \"2015-02-21 21:33:21 -0800\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"tweet_location\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3081,\n        \"samples\": [\n          \"Oakland, California\",\n          \"Beverly Hills, CA\",\n          \"Austin, TX/NY, NY\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"user_timezone\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 85,\n        \"samples\": [\n          \"Helsinki\",\n          \"Eastern Time (US & Canada)\",\n          \"America/Detroit\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
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              "             tweet_id airline_sentiment  airline_sentiment_confidence  \\\n",
              "0  570306133677760513           neutral                           1.0   \n",
              "\n",
              "  negativereason  negativereason_confidence         airline  \\\n",
              "0            NaN                        NaN  Virgin America   \n",
              "\n",
              "  airline_sentiment_gold     name negativereason_gold  retweet_count  \\\n",
              "0                    NaN  cairdin                 NaN              0   \n",
              "\n",
              "                                  text tweet_coord              tweet_created  \\\n",
              "0  @VirginAmerica What @dhepburn said.         NaN  2015-02-24 11:35:52 -0800   \n",
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              "  tweet_location               user_timezone  \n",
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      "source": [
        "airline = pd.read_csv(\"/content/Tweets.csv\")\n",
        "\n",
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              "\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-76d42757-e687-4eaa-b186-4b8ad8935aed 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": [
              "  airline_sentiment                                               text\n",
              "0           neutral                @VirginAmerica What @dhepburn said.\n",
              "1          positive  @VirginAmerica plus you've added commercials t..."
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Extract Airline Sentiment and text....\n",
        "\n",
        "mydf = airline.loc[:, ['airline_sentiment', 'text']]\n",
        "mydf.head(2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WVDRFXgAO0Ti",
        "outputId": "f31595a2-223b-4685-e0c4-c42f78f1bec4"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n"
          ]
        }
      ],
      "source": [
        "# NLP Libraries\n",
        "import re # Regular Expression\n",
        "import nltk # NLP Library and other one is called 'Spacy'\n",
        "\n",
        "nltk.download(\"stopwords\")\n",
        "nltk.download(\"punkt\")\n",
        "\n",
        "from nltk.corpus import stopwords\n",
        "\n",
        "stop_words = stopwords.words(\"english\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u-BxBT34PxkT",
        "outputId": "d230aec6-97c3-465e-fd94-347dd32ae498"
      },
      "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(stop_words)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fOlChbPEQRGV"
      },
      "outputs": [],
      "source": [
        "# Removal of Stopwords...\n",
        "\n",
        "mytext = '''@VirginAmerica plus you've added \\\n",
        "commercials to the experience... tacky.'''\n",
        "\n",
        "words = mytext.split()\n",
        "\n",
        "newtext = \" \".join([word for word in words if word not in stop_words])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "aHZnX-ykQq55"
      },
      "outputs": [],
      "source": [
        "# For Whole Data\n",
        "def remove_stop(text):\n",
        "  text = text.lower() # converts the text into lowercase\n",
        "  words = text.split() # Split the Sentence into words\n",
        "  return(\" \".join([word for word in words if word not in stop_words]))\n",
        "\n",
        "mydf[\"clean_text\"]=  mydf.text.apply(remove_stop)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AtRLy7evRGNc",
        "outputId": "fd51edb9-8a52-4216-c17a-f02d38c7d71e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "@VirginAmerica plus added commercials experience... tacky.\n",
            "plus added commercials experience    tacky\n"
          ]
        }
      ],
      "source": [
        "# removal of noise in the data...\n",
        "print(newtext)\n",
        "#re.findall(\"[^A-Za-z\\s]\", newtext)\n",
        "\n",
        "def clean_text(text):\n",
        "  #text = re.findall(\"@\\w+|[^A-Za-z\\s]\", text)\n",
        "  text = re.sub(\"@\\w+|[^A-Za-z\\s]\", \" \", text)\n",
        "  #text = re.sub(\"\\s+\", \" \", text) # Additional Whitespace Characters\n",
        "  return(text.strip())\n",
        "\n",
        "print(clean_text(newtext))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vwcBOQ9hTDQr",
        "outputId": "94c44769-fe87-4215-e1ee-65eb09556bf2"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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'@murphyjulie', '@murraysawchuck', '@mwangbickler', '@mxo42', '@my', '@mypompanobeach', '@naia_miaa', '@nanceebing', '@naomi_cooper', '@nascar', '@nashinmypants', '@natca', '@nathankillam', '@nationalairpor', '@natprodexpo', '@nbsnewsr', '@nburnside26', '@nelsjeff', '@newsvp', '@nhlbruins', '@nhlonnbcsports', '@nickcunningham1', '@ninadavuluri', '@nlrphoto', '@nm4agoodlife', '@no_airport', '@nokidhungry', '@noltnancy', '@not', '@notpghtimothy', '@nrhodes85', '@nrosenb1', '@ntrustopen', '@ny_njairports', '@nyjets', '@nytimes', '@nzherald', '@obj_3', '@ods1819', '@of', '@okcthunder', '@olive201', '@orangecounty', '@orlandosentinel', '@pacificbiznews', '@packermama1', '@paigeworthy', '@pamgrout', '@pancho_joe', '@panynj', '@parachuteguy', '@parryaftab', '@patrichruben', '@pattonoswalt', '@paulbev1', '@paulgordonbrown', '@paypal', '@paytontaylor129', '@pbpinftworth', '@pdquigley', '@peaches275', '@perfectomobile', '@peterpiatetsky', '@peterstraubmma', '@pgatour', '@phd_mama_', '@philacarservice', '@philpete', '@phl', '@phlairport', '@phxskyharbor', '@pilyoc', '@pivotalcf', '@pkg49', '@poisonpill76', '@portcolumbuscmh', '@portlandjetport', '@postsecret', '@poteettj', '@praywinn', '@preboard', '@priceline', '@prof_solutions', '@professorpaul15', '@qlyss8', '@rajuchinthala', '@rayja9', '@rcm_oficial', '@reagan', '@reagan_airport', '@reallytallchris', '@reccewife', '@redreserve', '@reebok', '@renhotels', '@renoairport', '@renttherunway', '@retailbagholder', '@reuters', '@rikrik__', '@rizzilient', '@rldelahunty', '@rncahill', '@robbogart', '@robcnyc', '@robertdwyer', '@robertfor39', '@robinreda', '@robthecameraman', '@rockinwellness', '@roxydigital', '@rundisney', '@russellswriting', '@russelneiss', '@ruth_slobodin', '@ryand2285', '@rylietolbert15', '@s_myc88', '@sa_craig', '@sacintlairport', '@sadie4406', '@sagerooski', '@saharasams', '@saianel', '@samchampion', '@sammi_jon3s', '@samoore10', '@samsonite', '@sarahpompei', '@sarahzou', '@satesq', '@saxonandparole', '@saysorrychris', '@sb5551', '@scm1133', '@scotthroth', '@scvpools', '@sdfairport', '@seanmfmadden', '@seanvrose', '@seguinej', '@sentierimelinda', '@setorii', '@sfo', '@shannonbloom', '@shannonwoodward', '@shivadelrahim', '@showexpert', '@shrinerack', '@shulemstern', '@silverairways', '@silverairwsys', '@simonroesner', '@skift', '@skiplagged', '@skywest', '@slacksoft_uk', '@slcairport', '@smiles1307', '@smusportmgt', '@sonyasloanmd', '@souljacoy', '@southwest', '@southwestair', '@southwestoliver', '@southwestverity', '@specialolympics', '@spiritairlines', '@spiritairpr', '@spurs', '@ssal', '@stacycrossb6', '@staralliance', '@starbucks', '@starryeyes_dev_', '@startingbloc', '@stephenrodrick', '@stevelord212', '@stone9956', '@suntimes', '@suntoshi', '@superben', '@supertzar85', '@superyan', '@suuperg', '@svllindia', '@swagglikebean', '@sweetingr', '@sweetmel', '@sxsw', '@sxu', '@sydneyairport', '@sylvie75015', '@t5sparrow', '@tatianaking', '@taylorlumsden', '@taylormdowns', '@tbuccherifrnc3e', '@tcunningham10', '@teamtreehouse', '@tennetexan', '@terrybrokebad', '@tfgreenairport', '@the_uso', '@theacademy', '@theairhelper', '@thecandacesmith', '@theellenshow', '@thefaaonline', '@thehaileytate', '@thehipmunk', '@thenatek', '@thenationaluae', '@therealaviation', '@thetroubadour', '@thevdt', '@thewayoftheid', '@thirty_lives', '@thisiscoach', '@ti2469', '@tiffanyandco', '@tifffyhuang', '@tilleymonsta', '@timbennettg3', '@timieyancey', '@tinaisback', '@tinder', '@tinman2ironman', '@tmadcle', '@tmobile', '@tomvh', '@tonysimsmma', '@tori_leggieri', '@tpallini', '@traveloneworld', '@travelportland', '@travelzoo', '@travisamex', '@triflight', '@truthh4', '@truu_tall', '@tsa', '@ttinac11', '@tuftsenergyconf', '@tumitravel', '@twitter', '@tywinter', '@ubergizmo', '@uctraveladvisor', '@unfriendly', '@united', '@united_airline', '@unitedairlines', '@unitedappeals', '@unitedflyerhd', '@universalorl', '@uno_baseball', '@upgrd', '@upinairclaire', '@ups', '@usair', '@usaireays', '@usairways', '@usairwayscenter', '@usairwaysmobile', '@usairwayssuck', '@usairwis', '@usatoday', '@usatodaytravel', '@uschamber', '@usnavy', '@vainglorygame', '@vanessaannz', '@vegecomgirl', '@velourlive', '@verizonwireless', '@very', '@vincenzolandino', '@vincesviews', '@vindictive_tk', '@vinylvegas', '@viraltech', '@virgin', '@virginamerica', '@virginatlantic', '@virginmedia', '@visa', '@visualclubconcepts', '@vitaminwater', '@vusa_australia', '@walls29', '@wallstslumlord', '@waltdisneyworld', '@wamo66', '@warriors', '@webbernaturals', '@weepysweetmonty', '@were', '@westjet', '@whitterbug', '@wikipearl', '@wmcactionnews5', '@wsj', '@wsjplus', '@wtop', '@xfinity', '@yaffasolin', '@yeniettelswood', '@yorkshire2002', '@yourlocalnyer', '@yvonneokaka', '@yyz', '@zacks_com', '@zakkohane', '@zj76', '@zkatcher', '@zrh_airport', '[', ']', '^', '_', '{', '|', '}', '~', '£', '°', 'º', 'á', 'â', 'ã', 'é', 'ê', 'í', 'ʖ', '͜', '͡', '\\u200b', '–', '—', '‘', '’', '“', '”', '…', '€', '↔', '⌚', '☀', '☕', '☺', '♥', '⛄', '✅', '✈', '✌', '✔', '✨', '❄', '❌', '❗', '❤', '➡', '⤴', '⤵', '⭐', '️', '🆖', '🆘', '🇧', '🇬', '🇸', '🇺', '🌏', '🌞', '🌟', '🌴', '🍅', '🍷', '🍸', '🍻', '🎀', '🎉', '🎲', '🎵', '🐩', '🐳', '🐴', '👀', '👉', '👊', '👋', '👌', '👍', '👎', '👏', '👠', '👸', '👺', '👿', '💁', '💔', '💕', '💖', '💗', '💘', '💙', '💜', '💝', '💤', '💩', '💪', '💯', '💺', '📱', '📲', '🔵', '😀', '😁', '😂', '😃', '😄', '😅', '😆', '😈', '😉', '😊', '😋', '😍', '😎', '😏', '😐', '😑', '😒', '😓', '😔', '😕', '😖', '😘', '😜', '😞', '😠', '😡', '😢', '😣', '😤', '😥', '😦', '😩', '😪', '😫', '😬', '😭', '😮', '😱', '😲', '😳', '😵', '😷', '😻', '🙅', '🙈', '🙉', '🙌', '🙏', '🚪', '🚫', '🚶']\n"
          ]
        }
      ],
      "source": [
        "# Create a function that will expose all the special characters in the data\n",
        "def preview(text):\n",
        "  text = re.findall(\"@\\w+|[^A-Za-z0-9\\s]\", text)\n",
        "  return(text)\n",
        "\n",
        "mydf[\"noise\"] =  mydf.clean_text.apply(preview)\n",
        "\n",
        "noise = set(char for sublist in mydf.noise for char in sublist)\n",
        "sorted_noise = sorted(list(noise))\n",
        "\n",
        "print(sorted_noise)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Iu0BQGjQcG-1"
      },
      "outputs": [],
      "source": [
        "# Clean the Text Column in the DataFrame\n",
        "mydf[\"Cleansed\"] = mydf.clean_text.apply(clean_text)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gFTnudKxgIOm"
      },
      "source": [
        "### Text Visualization"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "x1qQwCiQcIeS"
      },
      "outputs": [],
      "source": [
        "# Convert the Text into Tokens\n",
        "from nltk.probability import FreqDist\n",
        "from nltk.tokenize import word_tokenize\n",
        "\n",
        "all_tokens = [tokens for word in mydf.Cleansed\n",
        "              for tokens in word_tokenize(word)]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 868
        },
        "id": "Rb2n2v3cf0ek",
        "outputId": "081dcbe7-ba4e-4290-c101-9fad59e97fef"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Tokens</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>flight</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>t</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <td>i</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>get</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>co</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>103</th>\n",
              "      <td>http</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>thanks</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>500</th>\n",
              "      <td>s</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>482</th>\n",
              "      <td>cancelled</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>254</th>\n",
              "      <td>service</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>137</th>\n",
              "      <td>help</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>time</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>m</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>420</th>\n",
              "      <td>customer</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>380</th>\n",
              "      <td>us</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>231</th>\n",
              "      <td>hours</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>amp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>259</th>\n",
              "      <td>flights</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>400</th>\n",
              "      <td>hold</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>437</th>\n",
              "      <td>plane</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>can</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>464</th>\n",
              "      <td>thank</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>still</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>one</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142</th>\n",
              "      <td>please</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> object</label>"
            ],
            "text/plain": [
              "29        flight\n",
              "43             t\n",
              "94             i\n",
              "204          get\n",
              "55            co\n",
              "103         http\n",
              "105       thanks\n",
              "500            s\n",
              "482    cancelled\n",
              "254      service\n",
              "137         help\n",
              "37          time\n",
              "95             m\n",
              "420     customer\n",
              "380           us\n",
              "231        hours\n",
              "20           amp\n",
              "259      flights\n",
              "400         hold\n",
              "437        plane\n",
              "203          can\n",
              "464        thank\n",
              "109        still\n",
              "242          one\n",
              "142       please\n",
              "Name: Tokens, dtype: object"
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Freq Distribution\n",
        "pd.DataFrame(FreqDist(all_tokens).items(), columns = [\"Tokens\", \"Freq\"]).\\\n",
        "sort_values(by = \"Freq\", ascending = False).head(25).Tokens"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gbuULkYCgzOb"
      },
      "outputs": [],
      "source": [
        "# List of words\n",
        "\n",
        "stops = [\"t\", \"s\", \"http\", \"https\", \"co\", \"i\",\n",
        "         \"m\", \"w\", \"b\", \"ve\", \"ll\", \"u\"]\n",
        "\n",
        "def custom_stop(text):\n",
        "  text = text.lower() # converts the text into lowercase\n",
        "  words = text.split() # Split the Sentence into words\n",
        "  return(\" \".join([word for word in words if word not in stops]))\n",
        "\n",
        "mydf[\"Cleansed\"]=  mydf.Cleansed.apply(custom_stop)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lietFWyIjVZz"
      },
      "outputs": [],
      "source": [
        "all_tokens = [tokens for word in mydf.Cleansed\n",
        "              for tokens in word_tokenize(word)]\n",
        "\n",
        "freqdf = pd.DataFrame(FreqDist(all_tokens).items(), columns = [\"Tokens\", \"Freq\"]).\\\n",
        "sort_values(by = \"Freq\", ascending = False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "id": "8AJJwN_Xj9gj",
        "outputId": "a49e26a7-ffbf-463b-f4df-d21fb3ec0fc8"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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PrP5QrVu3xqBBg7B69Wo8efIETk5OCAkJEadAKO7Zh9atW+Po0aNYtWoVbGxsULduXXGQ8du2bt2Kbdu2YcCAAWjdujUMDQ1x8+ZNbNq0CUZGRvj//r//DwCgp6eHjRs3omfPnmjSpAnGjBmDGjVq4N9//8Xx48ehUqnw999/l2qtH+qnn35Chw4d0KxZM0yYMAF2dnZISEhAWFgYHj9+LP4cFUXr1q2xYcMGfP3117C3t4eFhYV4AwDJCwMRUT709PSwf/9+LFy4EH/88Qf8/f1Rp04drFy5ErNnz87Tv3PnznB2doaPjw9iYmLg4OCAgIAAMcy8y19//YXNmzeL61euXBEnpKtZs6a4D319ffzzzz+YO3cu1q5dixcvXuCjjz5CQEBAvgOii6JJkyY4deoUvL294evri5ycHLRt2xa//fbbez/c/Pz8kJaWhjFjxsDMzAz9+vXD3r178cMPP2DLli3Ys2cPTExMYGdnhxkzZhT50p6JiQmmTJmCI0eOYPfu3cjJyYG9vT3Wr1+PyZMnf8hhl4gtW7bAysoKO3bswJ49e9C9e3f88ccf4iSdxbFq1SpMnDgR8+fPx4sXL+Du7l7g/8P//vc/mJiYIDg4GPv27YNarUb16tXh4uICb29vtGrVSuz7ySefICwsDEuXLsW6deuQlpYGKysrtG3b9r3zB5VErR/KwcEBFy9ehI+PDwICAvDkyRNYWFigVatWWLhwYbH2uXDhQjx8+BArVqxAamoqOnfuzEAkUwqBo8uIPohCoYCHh0eRJgSk8i08PBytWrXCb7/9huHDh0tdDhEVAscQERF9gPzmf1q9ejX09PTQqVMnCSoiouLgJTMiog+wYsUKXLp0CV26dIGBgQECAwMRGBiIiRMn5rk7j4i0FwMREdEHaNeuHYKCgrB06VKkpaWhVq1aWLx4MZ+JRaRjOIaIiIiIZI9jiIiIiEj2GIiIiIhI9jiGqBBycnIQGxsLMzMzTvNORESkIwRBQGpqKmxsbDQeeZQfBqJCiI2N5d0iREREOurRo0eoWbPmO/swEBVC7sM9Hz16lO8znYiIiEj7qNVq2NraajykuyAMRIWQe5lMpVIxEBEREemYwgx34aBqIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj2tCUTLli2DQqHAzJkzxbaXL1/Cw8MDVatWRcWKFTFo0CAkJCRovC4mJgZubm4wMTGBhYUF5s6di6ysLI0+J06cgKOjI5RKJezt7REQEFAGR0RERES6QisC0YULF/Dzzz+jefPmGu2zZs3C33//jV27diEkJASxsbEYOHCguD07Oxtubm549eoVzpw5g82bNyMgIAALFy4U+0RHR8PNzQ1dunRBeHg4Zs6cifHjx+Pw4cNldnxERESk3RSCIAhSFpCWlgZHR0esX78eX3/9NVq2bInVq1cjJSUF1atXx/bt2zF48GAAwK1bt9C4cWOEhYXByckJgYGB6N27N2JjY2FpaQkA8PPzg5eXF5KSkmBoaAgvLy8cPHgQkZGR4nsOHToUycnJOHToUKFqVKvVMDc3R0pKCmeqJiIi0hFF+fyW/AyRh4cH3Nzc0L17d432S5cuITMzU6O9UaNGqFWrFsLCwgAAYWFhaNasmRiGAMDV1RVqtRrXr18X+7y9b1dXV3Ef+cnIyIBardZYiIiIqPyS9Flmv//+Oy5fvowLFy7k2RYfHw9DQ0NUqlRJo93S0hLx8fFinzfDUO723G3v6qNWq/HixQsYGxvneW9fX1/4+PgU+7iIiIhIt0h2hujRo0eYMWMGtm3bBiMjI6nKyJe3tzdSUlLE5dGjR1KXRERERKVIskB06dIlJCYmwtHREQYGBjAwMEBISAjWrl0LAwMDWFpa4tWrV0hOTtZ4XUJCAqysrAAAVlZWee46y11/Xx+VSpXv2SEAUCqV4pPt+YR7IiKi8k+yQNStWzdcu3YN4eHh4tKmTRsMHz5c/HeFChUQHBwsviYqKgoxMTFwdnYGADg7O+PatWtITEwU+wQFBUGlUsHBwUHs8+Y+cvvk7kMrKLRwISIikhHJxhCZmZmhadOmGm2mpqaoWrWq2D5u3Dh4enqiSpUqUKlUmDZtGpydneHk5AQAcHFxgYODA0aOHIkVK1YgPj4e8+fPh4eHB5RKJQBg0qRJWLduHebNm4exY8fi2LFj2LlzJw4ePFi2B0xERERaS9JB1e/zww8/QE9PD4MGDUJGRgZcXV2xfv16cbu+vj4OHDiAyZMnw9nZGaampnB3d8eSJUvEPnXr1sXBgwcxa9YsrFmzBjVr1sTGjRvh6uoqxSERERGRFpJ8HiJdUOrzEGnjJSp+VxARkY7TqXmIiIiIiKTGQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREssdARERERLLHQERERESyx0BEREREsidpINqwYQOaN28OlUoFlUoFZ2dnBAYGits/+eQTKBQKjWXSpEka+4iJiYGbmxtMTExgYWGBuXPnIisrS6PPiRMn4OjoCKVSCXt7ewQEBJTF4REREZGOMJDyzWvWrIlly5ahfv36EAQBmzdvRr9+/XDlyhU0adIEADBhwgQsWbJEfI2JiYn47+zsbLi5ucHKygpnzpxBXFwcRo0ahQoVKuDbb78FAERHR8PNzQ2TJk3Ctm3bEBwcjPHjx8Pa2hqurq5le8BERESklRSCIAhSF/GmKlWqYOXKlRg3bhw++eQTtGzZEqtXr863b2BgIHr37o3Y2FhYWloCAPz8/ODl5YWkpCQYGhrCy8sLBw8eRGRkpPi6oUOHIjk5GYcOHSpUTWq1Gubm5khJSYFKpfrgY8xDUfK7/GBa9V1BRERUdEX5/NaaMUTZ2dn4/fffkZ6eDmdnZ7F927ZtqFatGpo2bQpvb288f/5c3BYWFoZmzZqJYQgAXF1doVarcf36dbFP9+7dNd7L1dUVYWFhBdaSkZEBtVqtsRAREVH5JeklMwC4du0anJ2d8fLlS1SsWBF79uyBg4MDAGDYsGGoXbs2bGxscPXqVXh5eSEqKgq7d+8GAMTHx2uEIQDienx8/Dv7qNVqvHjxAsbGxnlq8vX1hY+PT4kfKxEREWknyQNRw4YNER4ejpSUFPz5559wd3dHSEgIHBwcMHHiRLFfs2bNYG1tjW7duuHevXuoV69eqdXk7e0NT09PcV2tVsPW1rbU3o+IiIikJfklM0NDQ9jb26N169bw9fVFixYtsGbNmnz7tm3bFgBw9+5dAICVlRUSEhI0+uSuW1lZvbOPSqXK9+wQACiVSvHOt9yFiIiIyi/JA9HbcnJykJGRke+28PBwAIC1tTUAwNnZGdeuXUNiYqLYJygoCCqVSrzs5uzsjODgYI39BAUFaYxTIiIiInmT9JKZt7c3evbsiVq1aiE1NRXbt2/HiRMncPjwYdy7dw/bt29Hr169ULVqVVy9ehWzZs1Cp06d0Lx5cwCAi4sLHBwcMHLkSKxYsQLx8fGYP38+PDw8oFQqAQCTJk3CunXrMG/ePIwdOxbHjh3Dzp07cfDgQSkPnYiIiLSIpIEoMTERo0aNQlxcHMzNzdG8eXMcPnwYn376KR49eoSjR49i9erVSE9Ph62tLQYNGoT58+eLr9fX18eBAwcwefJkODs7w9TUFO7u7hrzFtWtWxcHDx7ErFmzsGbNGtSsWRMbN27kHEREREQk0rp5iLQR5yEiIiLSPTo5DxERERGRVBiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9iQNRBs2bEDz5s2hUqmgUqng7OyMwMBAcfvLly/h4eGBqlWromLFihg0aBASEhI09hETEwM3NzeYmJjAwsICc+fORVZWlkafEydOwNHREUqlEvb29ggICCiLwyMiIiIdIWkgqlmzJpYtW4ZLly7h4sWL6Nq1K/r164fr168DAGbNmoW///4bu3btQkhICGJjYzFw4EDx9dnZ2XBzc8OrV69w5swZbN68GQEBAVi4cKHYJzo6Gm5ubujSpQvCw8Mxc+ZMjB8/HocPHy7z4yUiIiLtpBAEQZC6iDdVqVIFK1euxODBg1G9enVs374dgwcPBgDcunULjRs3RlhYGJycnBAYGIjevXsjNjYWlpaWAAA/Pz94eXkhKSkJhoaG8PLywsGDBxEZGSm+x9ChQ5GcnIxDhw4Vqia1Wg1zc3OkpKRApVKV/EErSn6XH0yrviuIiIiKriif31ozhig7Oxu///470tPT4ezsjEuXLiEzMxPdu3cX+zRq1Ai1atVCWFgYACAsLAzNmjUTwxAAuLq6Qq1Wi2eZwsLCNPaR2yd3H/nJyMiAWq3WWIiIiKj8kjwQXbt2DRUrVoRSqcSkSZOwZ88eODg4ID4+HoaGhqhUqZJGf0tLS8THxwMA4uPjNcJQ7vbcbe/qo1ar8eLFi3xr8vX1hbm5ubjY2tqWxKESERGRlpI8EDVs2BDh4eE4d+4cJk+eDHd3d9y4cUPSmry9vZGSkiIujx49krQeIiIiKl0GUhdgaGgIe3t7AEDr1q1x4cIFrFmzBp9//jlevXqF5ORkjbNECQkJsLKyAgBYWVnh/PnzGvvLvQvtzT5v35mWkJAAlUoFY2PjfGtSKpVQKpUlcnxERESk/SQ/Q/S2nJwcZGRkoHXr1qhQoQKCg4PFbVFRUYiJiYGzszMAwNnZGdeuXUNiYqLYJygoCCqVCg4ODmKfN/eR2yd3H0RERESSniHy9vZGz549UatWLaSmpmL79u04ceIEDh8+DHNzc4wbNw6enp6oUqUKVCoVpk2bBmdnZzg5OQEAXFxc4ODggJEjR2LFihWIj4/H/Pnz4eHhIZ7hmTRpEtatW4d58+Zh7NixOHbsGHbu3ImDBw9KeehERESkRSQNRImJiRg1ahTi4uJgbm6O5s2b4/Dhw/j0008BAD/88AP09PQwaNAgZGRkwNXVFevXrxdfr6+vjwMHDmDy5MlwdnaGqakp3N3dsWTJErFP3bp1cfDgQcyaNQtr1qxBzZo1sXHjRri6upb58RIREZF20rp5iLQR5yEiIiLSPTo5DxERERGRVBiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2JA1Evr6++Oijj2BmZgYLCwv0798fUVFRGn0++eQTKBQKjWXSpEkafWJiYuDm5gYTExNYWFhg7ty5yMrK0uhz4sQJODo6QqlUwt7eHgEBAaV9eERERKQjJA1EISEh8PDwwNmzZxEUFITMzEy4uLggPT1do9+ECRMQFxcnLitWrBC3ZWdnw83NDa9evcKZM2ewefNmBAQEYOHChWKf6OhouLm5oUuXLggPD8fMmTMxfvx4HD58uMyOlYiIiLSXQhAEQeoiciUlJcHCwgIhISHo1KkTgNdniFq2bInVq1fn+5rAwED07t0bsbGxsLS0BAD4+fnBy8sLSUlJMDQ0hJeXFw4ePIjIyEjxdUOHDkVycjIOHTr03rrUajXMzc2RkpIClUr14Qf6NkXJ7/KDac13BRERUfEU5fNbq8YQpaSkAACqVKmi0b5t2zZUq1YNTZs2hbe3N54/fy5uCwsLQ7NmzcQwBACurq5Qq9W4fv262Kd79+4a+3R1dUVYWFi+dWRkZECtVmssREREVH4ZSF1ArpycHMycORPt27dH06ZNxfZhw4ahdu3asLGxwdWrV+Hl5YWoqCjs3r0bABAfH68RhgCI6/Hx8e/so1ar8eLFCxgbG2ts8/X1hY+PT4kfIxEREWknrQlEHh4eiIyMxOnTpzXaJ06cKP67WbNmsLa2Rrdu3XDv3j3Uq1evVGrx9vaGp6enuK5Wq2Fra1sq70VERETS04pLZlOnTsWBAwdw/Phx1KxZ851927ZtCwC4e/cuAMDKygoJCQkafXLXrays3tlHpVLlOTsEAEqlEiqVSmMhIiKi8kvSQCQIAqZOnYo9e/bg2LFjqFu37ntfEx4eDgCwtrYGADg7O+PatWtITEwU+wQFBUGlUsHBwUHsExwcrLGfoKAgODs7l9CREBERkS6TNBB5eHjgt99+w/bt22FmZob4+HjEx8fjxYsXAIB79+5h6dKluHTpEh48eID9+/dj1KhR6NSpE5o3bw4AcHFxgYODA0aOHImIiAgcPnwY8+fPh4eHB5RKJQBg0qRJuH//PubNm4dbt25h/fr12LlzJ2bNmiXZsRMREZH2KNZt9/fv34ednd2Hv7ki//vN/f39MXr0aDx69AgjRoxAZGQk0tPTYWtriwEDBmD+/Pkal7EePnyIyZMn48SJEzA1NYW7uzuWLVsGA4P/N0TqxIkTmDVrFm7cuIGaNWtiwYIFGD16dKHq5G33REREuqcon9/FCkR6enro3Lkzxo0bh8GDB8PIyKjYxeoCBiIiIiLdU+rzEF2+fBnNmzeHp6cnrKys8L///Q/nz58vVrFEREREUitWIGrZsiXWrFmD2NhYbNq0CXFxcejQoQOaNm2KVatWISkpqaTrJCIiIio1HzSo2sDAAAMHDsSuXbuwfPly3L17F3PmzIGtrS1GjRqFuLi4kqqTiIiIqNR8UCC6ePEipkyZAmtra6xatQpz5szBvXv3EBQUhNjYWPTr16+k6iQiIiIqNcWaqXrVqlXw9/dHVFQUevXqhS1btqBXr17Q03udr+rWrYuAgADUqVOnJGslIiIiKhXFCkQbNmzA2LFjMXr0aHGCxLdZWFjg119//aDiiIiIiMpCsW67lxvedk9ERKR7Sv22e39/f+zatStP+65du7B58+bi7JKIiIhIMsUKRL6+vqhWrVqedgsLC3z77bcfXBQRERFRWSpWIIqJicn3Qay1a9dGTEzMBxdFREREVJaKFYgsLCxw9erVPO0RERGoWrXqBxdFREREVJaKFYi++OILTJ8+HcePH0d2djays7Nx7NgxzJgxA0OHDi3pGomIiIhKVbFuu1+6dCkePHiAbt26iU+Uz8nJwahRoziGiIiIiHTOB912f/v2bURERMDY2BjNmjVD7dq1S7I2rcHb7omIiHRPUT6/i3WGKFeDBg3QoEGDD9kFERERkeSKFYiys7MREBCA4OBgJCYmIicnR2P7sWPHSqQ4IiIiorJQrEA0Y8YMBAQEwM3NDU2bNoVCoY3XfIiIiIgKp1iB6Pfff8fOnTvRq1evkq6HiIiIqMwV67Z7Q0ND2Nvbl3QtRERERJIoViCaPXs21qxZAz4XloiIiMqDYl0yO336NI4fP47AwEA0adIEFSpU0Ni+e/fuEimOiIiIqCwUKxBVqlQJAwYMKOlaiIiIiCRRrEDk7+9f0nUQERERSaZYY4gAICsrC0ePHsXPP/+M1NRUAEBsbCzS0tJKrDgiIiKislCsM0QPHz5Ejx49EBMTg4yMDHz66acwMzPD8uXLkZGRAT8/v5Kuk4iIiKjUFOsM0YwZM9CmTRs8e/YMxsbGYvuAAQMQHBxcYsURERERlYVinSE6deoUzpw5A0NDQ432OnXq4N9//y2RwoiIiIjKSrHOEOXk5CA7OztP++PHj2FmZvbBRRERERGVpWIFIhcXF6xevVpcVygUSEtLw6JFi/g4DyIiItI5CqEY000/fvwYrq6uEAQBd+7cQZs2bXDnzh1Uq1YNJ0+ehIWFRWnUKhm1Wg1zc3OkpKRApVKV/Bto47NxOQk5ERHpuKJ8fhcrEAGvb7v//fffcfXqVaSlpcHR0RHDhw/XGGRdXjAQERER6Z6ifH4Xa1A1ABgYGGDEiBHFfTkRERGR1ihWINqyZcs7t48aNapYxRARERFJoViXzCpXrqyxnpmZiefPn8PQ0BAmJiZ4+vRpiRWoDXjJjIiISPcU5fO7WHeZPXv2TGNJS0tDVFQUOnTogB07dhR6P76+vvjoo49gZmYGCwsL9O/fH1FRURp9Xr58CQ8PD1StWhUVK1bEoEGDkJCQoNEnJiYGbm5uMDExgYWFBebOnYusrCyNPidOnICjoyOUSiXs7e0REBBQnEMnIiKicqjYzzJ7W/369bFs2TLMmDGj0K8JCQmBh4cHzp49i6CgIGRmZsLFxQXp6elin1mzZuHvv//Grl27EBISgtjYWAwcOFDcnp2dDTc3N7x69QpnzpzB5s2bERAQgIULF4p9oqOj4ebmhi5duiA8PBwzZ87E+PHjcfjw4ZI5eCIiItJpxb7LLD/h4eHo1KkT1Gp1sV6flJQECwsLhISEoFOnTkhJSUH16tWxfft2DB48GABw69YtNG7cGGFhYXByckJgYCB69+6N2NhYWFpaAgD8/Pzg5eWFpKQkGBoawsvLCwcPHkRkZKT4XkOHDkVycjIOHTr03rp4yYyIiEj3lPpdZvv379dYFwQBcXFxWLduHdq3b1+cXQIAUlJSAABVqlQBAFy6dAmZmZno3r272KdRo0aoVauWGIjCwsLQrFkzMQwBgKurKyZPnozr16+jVatWCAsL09hHbp+ZM2fmW0dGRgYyMjLE9eIGPCIiItINxQpE/fv311hXKBSoXr06unbtiu+//75YheTk5GDmzJlo3749mjZtCgCIj4+HoaEhKlWqpNHX0tIS8fHxYp83w1Du9txt7+qjVqvx4sWLPHMn+fr6wsfHp1jHQURERLqnWIEoJyenpOuAh4cHIiMjcfr06RLfd1F5e3vD09NTXFer1bC1tZWwIiIiIipNxZ6YsSRNnToVBw4cwMmTJ1GzZk2x3crKCq9evUJycrLGWaKEhARYWVmJfc6fP6+xv9y70N7s8/adaQkJCVCpVPnOrK1UKqFUKkvk2IiIiEj7FSsQvXn25H1WrVpV4DZBEDBt2jTs2bMHJ06cQN26dTW2t27dGhUqVEBwcDAGDRoEAIiKikJMTAycnZ0BAM7Ozvjmm2+QmJgoPkMtKCgIKpUKDg4OYp9//vlHY99BQUHiPoiIiEjeihWIrly5gitXriAzMxMNGzYEANy+fRv6+vpwdHQU+ykU7759ysPDA9u3b8e+fftgZmYmjvkxNzeHsbExzM3NMW7cOHh6eqJKlSpQqVSYNm0anJ2d4eTkBABwcXGBg4MDRo4ciRUrViA+Ph7z58+Hh4eHeJZn0qRJWLduHebNm4exY8fi2LFj2LlzJw4ePFicwyciIqLyRiiG77//XujTp4/w9OlTse3p06dCv379hO+++67Q+8Hrm7vzLP7+/mKfFy9eCFOmTBEqV64smJiYCAMGDBDi4uI09vPgwQOhZ8+egrGxsVCtWjVh9uzZQmZmpkaf48ePCy1bthQMDQ0FOzs7jfd4n5SUFAGAkJKSUujXFAm0cCEiItJxRfn8LtY8RDVq1MCRI0fQpEkTjfbIyEi4uLggNjb2g4OaNuE8RERERLqn1B/doVarkZSUlKc9KSkJqampxdklERERkWSKFYgGDBiAMWPGYPfu3Xj8+DEeP36Mv/76C+PGjdN4rAYRERGRLijWoGo/Pz/MmTMHw4YNQ2Zm5usdGRhg3LhxWLlyZYkWSERERFTaPuhZZunp6bh37x4AoF69ejA1NS2xwrQJxxARERHpnlIfQ5QrLi4OcXFxqF+/PkxNTfEB2YqIiIhIMsUKRE+ePEG3bt3QoEED9OrVC3FxcQCAcePGYfbs2SVaIBEREVFpK1YgmjVrFipUqICYmBiYmJiI7Z9//jkOHTpUYsURERERlYViDao+cuQIDh8+rPHcMQCoX78+Hj58WCKFEREREZWVYp0hSk9P1zgzlOvp06d8KCoRERHpnGIFoo4dO2LLli3iukKhQE5ODlasWIEuXbqUWHFEREREZaFYl8xWrFiBbt264eLFi3j16hXmzZuH69ev4+nTpwgNDS3pGomIiIhKVbHOEDVt2hS3b99Ghw4d0K9fP6Snp2PgwIG4cuUK6tWrV9I1EhEREZWqIp8hyszMRI8ePeDn54evvvqqNGoiIiIiKlNFPkNUoUIFXL16tTRqISIiIpJEsS6ZjRgxAr/++mtJ10JEREQkiWINqs7KysKmTZtw9OhRtG7dOs8zzFatWlUixRERERGVhSIFovv376NOnTqIjIyEo6MjAOD27dsafRQKbXxSKREREVHBihSI6tevj7i4OBw/fhzA60d1rF27FpaWlqVSHBEREVFZKNIYorefZh8YGIj09PQSLYiIiIiorBVrUHWutwMSERERkS4qUiBSKBR5xghxzBARERHpuiKNIRIEAaNHjxYf4Pry5UtMmjQpz11mu3fvLrkKiYiIiEpZkQKRu7u7xvqIESNKtBgiIiIiKRQpEPn7+5dWHURERESS+aBB1URERETlAQMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREcmepIHo5MmT6NOnD2xsbKBQKLB3716N7aNHjxYfKJu79OjRQ6PP06dPMXz4cKhUKlSqVAnjxo1DWlqaRp+rV6+iY8eOMDIygq2tLVasWFHah0ZEREQ6RNJAlJ6ejhYtWuCnn34qsE+PHj0QFxcnLjt27NDYPnz4cFy/fh1BQUE4cOAATp48iYkTJ4rb1Wo1XFxcULt2bVy6dAkrV67E4sWL8csvv5TacREREZFuKdKzzEpaz5490bNnz3f2USqVsLKyynfbzZs3cejQIVy4cAFt2rQBAPz444/o1asXvvvuO9jY2GDbtm149eoVNm3aBENDQzRp0gTh4eFYtWqVRnAiIiIi+dL6MUQnTpyAhYUFGjZsiMmTJ+PJkyfitrCwMFSqVEkMQwDQvXt36Onp4dy5c2KfTp06wdDQUOzj6uqKqKgoPHv2LN/3zMjIgFqt1liIiIio/NLqQNSjRw9s2bIFwcHBWL58OUJCQtCzZ09kZ2cDAOLj42FhYaHxGgMDA1SpUgXx8fFiH0tLS40+ueu5fd7m6+sLc3NzcbG1tS3pQyMiIiItIukls/cZOnSo+O9mzZqhefPmqFevHk6cOIFu3bqV2vt6e3vD09NTXFer1QxFRERE5ZhWnyF6m52dHapVq4a7d+8CAKysrJCYmKjRJysrC0+fPhXHHVlZWSEhIUGjT+56QWOTlEolVCqVxkJERETll04FosePH+PJkyewtrYGADg7OyM5ORmXLl0S+xw7dgw5OTlo27at2OfkyZPIzMwU+wQFBaFhw4aoXLly2R4AERERaSVJA1FaWhrCw8MRHh4OAIiOjkZ4eDhiYmKQlpaGuXPn4uzZs3jw4AGCg4PRr18/2Nvbw9XVFQDQuHFj9OjRAxMmTMD58+cRGhqKqVOnYujQobCxsQEADBs2DIaGhhg3bhyuX7+OP/74A2vWrNG4JEZERETyphAEQZDqzU+cOIEuXbrkaXd3d8eGDRvQv39/XLlyBcnJybCxsYGLiwuWLl2qMUj66dOnmDp1Kv7++2/o6elh0KBBWLt2LSpWrCj2uXr1Kjw8PHDhwgVUq1YN06ZNg5eXV6HrVKvVMDc3R0pKSulcPlOU/C4/mGTfFURERCWjKJ/fkgYiXcFAREREpHuK8vmtU2OIiIiIiEoDAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREcmeVj/clbQc508iIqJygmeIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9hiIiIiISPYMpC6AqMwppC4gH4LUBRARyRvPEBEREZHs8QwRka7gmS0iolIj6RmikydPok+fPrCxsYFCocDevXs1tguCgIULF8La2hrGxsbo3r077ty5o9Hn6dOnGD58OFQqFSpVqoRx48YhLS1No8/Vq1fRsWNHGBkZwdbWFitWrCjtQyMiIiIdImkgSk9PR4sWLfDTTz/lu33FihVYu3Yt/Pz8cO7cOZiamsLV1RUvX74U+wwfPhzXr19HUFAQDhw4gJMnT2LixInidrVaDRcXF9SuXRuXLl3CypUrsXjxYvzyyy+lfnxERESkIwQtAUDYs2ePuJ6TkyNYWVkJK1euFNuSk5MFpVIp7NixQxAEQbhx44YAQLhw4YLYJzAwUFAoFMK///4rCIIgrF+/XqhcubKQkZEh9vHy8hIaNmxY6NpSUlIEAEJKSkpxD+/doIUL62bdJVU3EZFEivL5rbWDqqOjoxEfH4/u3buLbebm5mjbti3CwsIAAGFhYahUqRLatGkj9unevTv09PRw7tw5sU+nTp1gaGgo9nF1dUVUVBSePXtWRkdDRERE2kxrB1XHx8cDACwtLTXaLS0txW3x8fGwsLDQ2G5gYIAqVapo9Klbt26efeRuq1y5cp73zsjIQEZGhriuVqs/8GiIiIhIm2ntGSIp+fr6wtzcXFxsbW2lLomIiIhKkdYGIisrKwBAQkKCRntCQoK4zcrKComJiRrbs7Ky8PTpU40++e3jzfd4m7e3N1JSUsTl0aNHH35AREREpLW0NhDVrVsXVlZWCA4OFtvUajXOnTsHZ2dnAICzszOSk5Nx6dIlsc+xY8eQk5ODtm3bin1OnjyJzMxMsU9QUBAaNmyY7+UyAFAqlVCpVBoLERWTQgsXIqK3SBqI0tLSEB4ejvDwcACvB1KHh4cjJiYGCoUCM2fOxNdff439+/fj2rVrGDVqFGxsbNC/f38AQOPGjdGjRw9MmDAB58+fR2hoKKZOnYqhQ4fCxsYGADBs2DAYGhpi3LhxuH79Ov744w+sWbMGnp6eEh01ERERaZ0yuOutQMePHxfweq5bjcXd3V0QhNe33i9YsECwtLQUlEql0K1bNyEqKkpjH0+ePBG++OILoWLFioJKpRLGjBkjpKamavSJiIgQOnToICiVSqFGjRrCsmXLilQnb7tn3axbhnUTkc4ryue3QhAETr7/Hmq1Gubm5khJSSmdy2faeAq/MN8VrLvksO6yxd96RLJQlM9vrR1DRERERFRWGIiIiIhI9hiIiIiISPYYiIiIiEj2GIiIiIhI9rT2WWZERJLi3XFEssIzRERERCR7DEREREQkewxEREREJHsMRERERCR7DEREREQkewxEREREJHu87Z6IqDzhdAFExcIzRERERCR7DEREREQke7xkRkRE0uOlPpIYzxARERGR7DEQERERkewxEBEREZHsMRARERGR7HFQNRERUXFxMHi5wTNEREREJHs8Q0RERCQ3PLOVB88QERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsMRARERGR7DEQERERkewxEBEREZHsaXUgWrx4MRQKhcbSqFEjcfvLly/h4eGBqlWromLFihg0aBASEhI09hETEwM3NzeYmJjAwsICc+fORVZWVlkfChEREWkxrX+4a5MmTXD06FFx3cDg/5U8a9YsHDx4ELt27YK5uTmmTp2KgQMHIjQ0FACQnZ0NNzc3WFlZ4cyZM4iLi8OoUaNQoUIFfPvtt2V+LERERKSdtD4QGRgYwMrKKk97SkoKfv31V2zfvh1du3YFAPj7+6Nx48Y4e/YsnJyccOTIEdy4cQNHjx6FpaUlWrZsiaVLl8LLywuLFy+GoaFhWR8OERERaSGtvmQGAHfu3IGNjQ3s7OwwfPhwxMTEAAAuXbqEzMxMdO/eXezbqFEj1KpVC2FhYQCAsLAwNGvWDJaWlmIfV1dXqNVqXL9+vcD3zMjIgFqt1liIiIio/NLqQNS2bVsEBATg0KFD2LBhA6Kjo9GxY0ekpqYiPj4ehoaGqFSpksZrLC0tER8fDwCIj4/XCEO523O3FcTX1xfm5ubiYmtrW7IHRkRERFpFqy+Z9ezZU/x38+bN0bZtW9SuXRs7d+6EsbFxqb2vt7c3PD09xXW1Ws1QREREVI5p9Rmit1WqVAkNGjTA3bt3YWVlhVevXiE5OVmjT0JCgjjmyMrKKs9dZ7nr+Y1LyqVUKqFSqTQWIiIiKr90KhClpaXh3r17sLa2RuvWrVGhQgUEBweL26OiohATEwNnZ2cAgLOzM65du4bExESxT1BQEFQqFRwcHMq8fiIiItJOWn3JbM6cOejTpw9q166N2NhYLFq0CPr6+vjiiy9gbm6OcePGwdPTE1WqVIFKpcK0adPg7OwMJycnAICLiwscHBwwcuRIrFixAvHx8Zg/fz48PDygVColPjoiIiLSFlodiB4/fowvvvgCT548QfXq1dGhQwecPXsW1atXBwD88MMP0NPTw6BBg5CRkQFXV1esX79efL2+vj4OHDiAyZMnw9nZGaampnB3d8eSJUukOiQiIiLSQgpBEASpi9B2arUa5ubmSElJKZ3xRIqS3+UHK8x3BesuOay7bLHussW6y1Z5rruIivL5rVNjiIiIiIhKAwMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREckeAxERERHJHgMRERERyR4DEREREcmerALRTz/9hDp16sDIyAht27bF+fPnpS6JiIiItIBsAtEff/wBT09PLFq0CJcvX0aLFi3g6uqKxMREqUsjIiIiickmEK1atQoTJkzAmDFj4ODgAD8/P5iYmGDTpk1Sl0ZEREQSM5C6gLLw6tUrXLp0Cd7e3mKbnp4eunfvjrCwsDz9MzIykJGRIa6npKQAANRqdekXqy109VBZd9li3WWLdZct1l22SqHu3M9tQRDe21cWgei///5DdnY2LC0tNdotLS1x69atPP19fX3h4+OTp93W1rbUatQ65lIXUEysu2yx7rLFussW6y5bpVh3amoqzM3f/QayCERF5e3tDU9PT3E9JycHT58+RdWqVaFQKCSsrGBqtRq2trZ49OgRVCqV1OUUGusuW6y7bLHussW6y5Yu1C0IAlJTU2FjY/PevrIIRNWqVYO+vj4SEhI02hMSEmBlZZWnv1KphFKp1GirVKlSaZZYYlQqldZ+Y74L6y5brLtsse6yxbrLlrbX/b4zQ7lkMaja0NAQrVu3RnBwsNiWk5OD4OBgODs7S1gZERERaQNZnCECAE9PT7i7u6NNmzb4+OOPsXr1aqSnp2PMmDFSl0ZEREQSk00g+vzzz5GUlISFCxciPj4eLVu2xKFDh/IMtNZVSqUSixYtynOpT9ux7rLFussW6y5brLts6WrdBVEIhbkXjYiIiKgck8UYIiIiIqJ3YSAiIiIi2WMgIiIiItljICIiIiLZYyAiIiIi2WMgIiIinZSdnY2TJ08iOTlZ6lKoHGAg0mFLlizB8+fP87S/ePECS5YskaCiwtHVut+WnZ2N8PBwPHv2TOpSyq2tW7eiffv2sLGxwcOHDwEAq1evxr59+ySurHy6d+8e5s+fjy+++AKJiYkAgMDAQFy/fl3iyvKnr68PFxcX/gxSiWAg0mE+Pj5IS0vL0/78+XP4+PhIUFHh6GrdM2fOxK+//grgdRjq3LkzHB0dYWtrixMnTkhb3FsqV66MKlWqFGrRVhs2bICnpyd69eqF5ORkZGdnA3j9XMHVq1dLW1wRPHr0CI8ePZK6jPcKCQlBs2bNcO7cOezevVv8GY2IiMCiRYskrq5gTZs2xf3796Uuo0To6h9Zulp3HgLpLIVCISQmJuZpDw4OFqpVqyZBRYWjq3XXqFFDuHDhgiAIgrBnzx7BxsZGiIqKEubPny+0a9dO4uo0BQQEiMv3338vVK5cWRg6dKiwZs0aYc2aNcLQoUOFypUrC6tWrZK61AI1btxY2LNnjyAIglCxYkXh3r17giAIwrVr14SqVatKWNn7ZWZmCvPnzxdUKpWgp6cn6OnpCSqVSvjqq6+EV69eSV1evpycnITvv/9eEATNr/e5c+eEGjVqSFnaOwUGBgotW7YU/v77byE2NlZISUnRWLTZjBkzhI0bNwqCIAhZWVlC+/btBYVCIZiamgrHjx+Xtrh30NW634eBSAdVqlRJqFy5sqCnpyf+O3fJ/QU8ZcoUqcvMQ1frzqVUKoVHjx4JgiAIEyZMEGbMmCEIgiDcv39fMDMzk7Cydxs4cKDw448/5mn/8ccfhX79+pV9QYVkZGQkPHjwQBAEzQ/o27dvC0ZGRlKW9l6TJk0SLCwsBD8/PyEiIkKIiIgQ/Pz8BCsrK2HSpElSl5cvU1NT4f79+4IgaH69o6OjBaVSKWVp76RQKMQlN3zq6emJ69pMl/7IepOu1v0+snmWWXmyevVqCIKAsWPHwsfHB+bm5uI2Q0ND1KlTB87OzhJWmD9drTuXpaUlbty4AWtraxw6dAgbNmwA8PpSn76+vsTVFezw4cNYvnx5nvYePXrgyy+/lKCiwqlbty7Cw8NRu3ZtjfZDhw6hcePGElVVONu3b8fvv/+Onj17im3NmzeHra0tvvjiC/F7R5tUqlQJcXFxqFu3rkb7lStXUKNGDYmqer/jx49LXUKx/ffff7CysgIA/PPPP/jss8/QoEEDjB07FmvWrJG4uoLpat3vw0Ckg9zd3QG8/sBo164dKlSoIHFFhfNm3e3bt4eBgW59+40ZMwZDhgyBtbU1FAoFunfvDgA4d+4cGjVqJHF1BatatSr27duH2bNna7Tv27cPVatWlaiq9/P09ISHhwdevnwJQRBw/vx57NixA76+vti4caPU5b2TUqlEnTp18rTXrVsXhoaGZV9QIQwdOhReXl7YtWsXFAoFcnJyEBoaijlz5mDUqFFSl1egzp07S11CsenqH1m6Wvd7SXyGij5Qdna2EBUVJZw6dUoICQnRWLTZ3bt3ha+++koYOnSokJCQIAiCIPzzzz9CZGSkxJW9265du4RVq1aJl84E4fV4nb1790pY1bv5+/sL+vr6Qu/evYWlS5cKS5cuFXr37i0YGBgI/v7+Upf3Tr/99ptgb28vXhKpUaOGOHZBm/n4+AhffPGF8PLlS7Ht5cuXwvDhw4XFixdLWFnBMjIyhPHjxwsGBgaCQqEQKlSoIOjp6QkjRowQsrKypC7vnU6ePCkMHz5ccHZ2Fh4/fiwIgiBs2bJFOHXqlMSVvduiRYsEc3NzoVGjRkKtWrXE75dff/1VcHJykri6gulq3e/Dp93rsLNnz2LYsGF4+PAh3v5vVCgU4l052iYkJAQ9e/ZE+/btcfLkSdy8eRN2dnZYtmwZLl68iD///FPqEvP1+PFj1KxZM99tZ8+ehZOTUxlXVHjnzp3D2rVrcfPmTQBA48aNMX36dLRt21biygrn+fPnSEtLg4WFhdSlFMqAAQMQHBwMpVKJFi1aAHh9t9arV6/QrVs3jb67d++WosQCxcTEIDIyEmlpaWjVqhXq168vdUnv9Ndff2HkyJEYPnw4tm7dihs3bsDOzg7r1q3DP//8g3/++UfqEt/pr7/+QkxMDD777DPx98vmzZtRuXJl9O3bV+LqClZQ3ZUqVUK/fv0krq54GIh0WMuWLdGgQQP4+PiIl3He9OYYHW3i7OyMzz77DJ6enjAzM0NERATs7Oxw/vx5DBw4EI8fP5a6xHw5ODjg9OnTeW5VDw0NhZubGyeHK2HR0dHIysrK84F8584dVKhQId9LUtpizJgxhe7r7+9fipWUf61atcKsWbMwatQojd8nV65cQc+ePREfHy91iQV637xrCxcuLKNKCi8zMxM9evSAn5+f1oflotKtQRyk4c6dO/jzzz9hb28vdSlFcu3aNWzfvj1Pu4WFBf777z8JKiocJycnuLi44Pjx4zAzMwMAnDx5Er1799bq+ZOA1xPu+fv74/79+1i9ejUsLCwQGBiIWrVqoUmTJlKXl6/Ro0dj7NixeX7pnjt3Dhs3btS6uZ/epIshRxAE/Pnnnzh+/DgSExORk5OjsV3bzmTlioqKQqdOnfK0m5uba/0fKXv27NFYz8zMRHR0NAwMDFCvXj2tDEQVKlTA1atXpS6jVHBiRh3Wtm1b3L17V+oyiiz3bpa3afvdLBs3bkStWrXQp08fZGRk4Pjx43Bzc8PSpUsxa9Ysqcsr0JsT7v311186M+HelStX0L59+zztTk5OCA8PL/uCyrmZM2di5MiRiI6ORsWKFWFubq6xaCsrK6t8fw+ePn0adnZ2ElRUeFeuXNFYIiMjERcXh27dumn175QRI0aIk9SWJzxDpGPeTObTpk3D7NmzER8fj2bNmuW526x58+ZlXV6h6OrdLHp6evj999/h5uaGrl274urVq/D19cXUqVOlLu2dvvzyS3z99dfiJcpcXbt2xbp16ySs7N0UCgVSU1PztKekpGjl+LhWrVrluWxdkMuXL5dyNUW3detW7N69G7169ZK6lCKZMGECZsyYgU2bNkGhUCA2NhZhYWGYM2cOFixYIHV5RaZSqeDj44M+ffpg5MiRUpeTr6ysLGzatAlHjx5F69atYWpqqrF91apVElX2YTiGSMfo6elBoVDkGUSdK3ebNg+qfvXqFTw8PBAQEIDs7GwYGBggKysLw4cPR0BAgFbdtpnfqeHU1FR88cUXcHNzw+TJk8V2bQ2gFStWxLVr11C3bl2NMRYPHjxAo0aN8PLlS6lLzFefPn1gbGyMHTt2iN8T2dnZ+Pzzz5Geno7AwECJK9RUlMum2nhmrm7duggMDNTqKSTyIwgCvv32W/j6+orPSFQqlZgzZw6WLl0qcXXFc/r0afTp00drH4XRpUuXArcpFAocO3asDKspOQxEOib3AZeF8faEdtrm0aNHuHbtmlbfzZJfAH1zXRcCaM2aNbFz5060a9dOIxDt2bMHc+bMwb1796QuMV83btxAp06dUKlSJXTs2BEAcOrUKajVahw7dgxNmzaVuMLyZfPmzTh06BA2bdoEY2NjqcspslevXuHu3btIS0uDg4MDKlasKHVJ77V27VqNdUEQEBcXh61bt6Jz5875jrWk0sNARGXO09Mz33aFQgEjIyPY29ujX79+WvHg0fIQQOfMmYNz585h165daNCgAS5fvoyEhASMGjUKo0aN0sqzFbliY2Oxbt06REREwNjYGM2bN8fUqVO14nvjfZKTk/Hnn3/i3r17mDt3LqpUqYLLly/D0tJSK8fKvXjxAgMGDEBoaCjq1KmT5xK8Nl7m03Vvzwqup6eH6tWro2vXrvD29ta4xE2lj4FIh+3fvz/f9jeDxds/cNqgS5cuuHz5MrKzs9GwYUMAwO3bt6Gvr49GjRohKioKCoUCp0+fhoODg8TV6r78LlFmZ2dj2LBhWneJsry4evUqunfvDnNzczx48ABRUVGws7PD/PnzERMTgy1btkhdYh5DhgzB8ePHMXjwYFhaWuYZD6Wtwfnly5f48ccfC7w7jkGu5HXp0uWd4+V4yYzKXEHjid68jNOhQwfs3bsXlStXlqjKvFavXo1Tp07B398fKpUKwOuBsuPHj0eHDh0wYcIEDBs2DC9evMDhw4clrlbTnTt3CvzFq423yL5JFybcu3r1Kpo2bQo9Pb333tqrrWO2AKB79+5wdHTEihUrNC5TnjlzBsOGDcODBw+kLjEPU1NTHD58GB06dJC6lCIZPnw4jhw5onNBTpe9fQdcZmYmwsPDERkZCXd3d919nlmZzYlNJe7o0aNC27ZthaNHjwpqtVpQq9XC0aNHBWdnZ+HgwYPC6dOnhSZNmghjx46VulQNNjY2wvXr1/O0R0ZGCjY2NoIgCMKlS5eEqlWrlnVp7/TLL78I+vr6gqWlpdCiRQuhZcuW4tKqVSupyysXFAqF+CiX3KeVv/k08zefaq7NVCqVcPfuXUEQNJ8c/+DBA619cnzDhg2FiIgIqcsoMpVKJZw+fVrqMkh4/UiP2bNnS11GsfG2ex02Y8YM/PLLL2jXrp3Y1q1bNxgZGWHixIm4fv06Vq9ejbFjx0pYZV4pKSlITEzMczksKSkJarUawOu5il69eiVFeQX6+uuv8c0338DLy0vqUt6roHFa+dGmW2Sjo6NRvXp18d+6SqlUit/Lb7p9+7Z4fNrm+++/x7x58+Dn56fVs4C/rUaNGhxroyVGjBiBjz/+GN99953UpRQLA5EOu3fvnnjJ6U0qlQr3798HANSvX1/rZn/u168fxo4di++//x4fffQRAODChQuYM2cO+vfvDwA4f/48GjRoIGGVeT179gyfffaZ1GUUypUrVwrVr7Dz5pSVNwemW1pawsjISMJqiq9v375YsmQJdu7cCeD11zkmJgZeXl4YNGiQxNXlb8SIEXj+/Dnq1asHExOTPIOqnz59KlFl7/b999/Dy8sLfn5+Wntjg1yEhYXp7M8swDFEOq1Dhw4wMzPDli1bxL86k5KSMGrUKKSnp+PkyZM4evQoPDw8EBUVJXG1/09aWhpmzZqFLVu2ICsrCwBgYGAAd3d3/PDDDzA1NRVnIm7ZsqV0hb5l3Lhx+OijjzBp0iSpS5EFlUqFAQMGYMSIEejWrRv09HRnYv2UlBQMHjwYFy9eRGpqKmxsbBAfHw8nJycEBgbmmchOG2zevPmd293d3cuokqJJSkrCkCFDcPLkSZ0Kcrps4MCBGuvC/3+6gIsXL2LBggU6O26LgUiHRUVFoV+/foiOjoatrS2A13P72NnZYd++fWjQoAH27t2L1NRUrZzxNC0tTTyTZWdnp/Xzhvj6+mLVqlVwc3PLd2bw6dOnS1RZ+bRnzx5s374dBw8ehLm5OT7//HOMGDECbdq0kbq0QgsNDUVERATS0tLg6OiI7t27S11SudO9e3fExMRg3Lhx+Q6q1tYgp8vefnjxm9MFuLi4SFTVh2Mg0nE5OTk4cuQIbt++DQBo2LAhPv30U536a1pXvGsKA4VCIYY7bfD2X3Dvoq0P7cyVmpqKP//8Ezt27MCxY8dgZ2eHESNGaP1dfcHBwQgODs73jsRNmzZJVJUmtVotXnbPb8zTm/K7PK8NTExMEBYWhhYtWkhdCuk4BiKicujtv+DeRZeezH7jxg0MHz4cV69e1dqZwYHXj/FYsmQJ2rRpA2tr6zxnLd5+yrlU9PX1ERcXBwsLC3Eaj7cJWj4Tu6OjI9avXw8nJyepS5GdS5cu4ebNmwCAJk2aoFWrVhJX9GE4qFrHrF27FhMnToSRkVGead/fxks48qVLIed9Xr58if3792P79u04dOgQLC0tMXfuXKnLeic/Pz8EBARo5aXqNx07dkyc9dvf3x+2trZ5JurMyclBTEyMFOUVyrJlyzB79mx88803+V7K1tYzW7osMTERQ4cOxYkTJ1CpUiUAr2dm79KlC37//XetvZPyfXiGSMfUrVsXFy9eRNWqVXXqEk558fjxY+zfvx8xMTF5pgXQptvX35aVlYUTJ07g3r17GDZsGMzMzBAbGwuVSqW1Y7cOHz6M7du3Y+/evTAwMMDgwYMxfPhwdOrUSerS3qtq1ao4f/486tWrJ3Uphfbm2aI3PXnyBBYWFlp7hih3eMDbZ7e0/cyWLvv8889x//59bNmyBY0bNwbw+uytu7s77O3tsWPHDokrLB4GIqJCCg4ORt++fWFnZ4dbt26hadOmePDgAQRBgKOjo9ZOV//w4UP06NEDMTExyMjIwO3bt2FnZ4cZM2YgIyMDfn5+UpeYLxMTE/Tp0wfDhg1Dr1698vzlr828vLxQsWJFLFiwQOpSCk1PTw8JCQl5/rp/+PAhHBwckJ6eLlFl7xYSEvLO7Z07dy6jSuTD3NwcR48eFadNyXX+/Hm4uLggOTlZmsI+EC+ZERWSt7c35syZAx8fH5iZmeGvv/6ChYUFhg8fjh49ekhdXoFmzJiBNm3aICIiAlWrVhXbBwwYgAkTJkhYWcGysrKwfPlyfPbZZ7CyspK6nEJ5czLMnJwc/PLLLzh69CiaN2+eJ8xp09nE3LoVCgUWLFgAExMTcVt2djbOnTunVdNfvI2Bp+zl5OTk+wdKhQoV8txAoEt4hkjH6OoMxOWBmZkZwsPDUa9ePVSuXBmnT59GkyZNEBERgX79+mnl86mA15dvzpw5g4YNG2o8V+vBgwdwcHDA8+fPpS4xXyYmJrh586bOTLbXpUuXQvVTKBRadTYxt+6QkBA4OzvD0NBQ3GZoaIg6depgzpw5Wvnsu1zJycn49ddfNQb4jh07Fubm5hJXVj7169cPycnJ2LFjB2xsbAAA//77L4YPH47KlStrzU0DRcUzRDrG398fTZs2hYGBQb4Pds2lbTMQlwempqbiuCFra2vcu3cPTZo0AQCtmw38TTk5OfmOo3j8+LFWP/Lg448/xpUrV3QmEB0/flzqEoolt+4xY8ZgzZo1OjcI+eLFi3B1dYWxsTE+/vhjAK//GPzmm29w5MgRODo6Slxh+bNu3Tr07dsXderUEefAi4mJQbNmzfDbb79JXF3x8QyRjtHT00N8fDwsLCxgZ2eHCxcuaFwGodLTv39/uLm5YcKECZgzZw727duH0aNHY/fu3ahcuTKOHj0qdYn5+vzzz2Fubo5ffvkFZmZmuHr1KqpXr45+/fqhVq1aWntH2s6dO+Ht7Y1Zs2ahdevWeWZ31uan3VPZ6dixI+zt7fF///d/MDB4/Td+VlYWxo8fj/v37+PkyZMSV1g+CYKA4OBg8axc48aNdX7iUQYiHVO1alX8888/aNu2bYGDIKl03L9/H2lpaWjevDnS09Mxe/ZsnDlzBvXr18eqVau09kzG48eP4erqCkEQcOfOHbRp0wZ37txBtWrVcPLkyTx3FWmL/CYXzT0ryruHKJexsTGuXLmCRo0aabTfuHEDbdq00dpLwrpOFyYeLSpeMtMxgwYNQqdOnWBjYwOFQoE2bdrkmTckF2+7L1l2dnbiv01NTbX27qy31axZExEREfjjjz/Ex0iMGzcOw4cPh7GxsdTlFUiXn3ZPZUelUiEmJiZPIHr06JFWXxLWZe+beFRX8QyRDjp06BDu3r2L6dOnY8mSJQX+0M+YMaOMK5OHV69e5ftXUa1atSSqiEi+pk+fjj179uC7775Du3btALx+htzcuXMxaNAgrF69WtoCyyFra2usWLFC6yceLSqeIdJBubd4X7p0CTNmzOBfQWXk9u3bGDduHM6cOaPRru2XcHx9fWFpaYmxY8dqtG/atAlJSUnw8vKSqLL327p1K/z8/BAdHY2wsDDUrl0bq1evRt26ddGvXz+pyyMt8N1330GhUGDUqFHIysoC8Pr278mTJ2PZsmUSV1c+vXr1Sgyf5QnPEBEVUvv27WFgYIAvv/wy39PE2vpwyTp16mD79u15foGdO3cOQ4cO1dpLUxs2bMDChQsxc+ZMfPPNN4iMjISdnR0CAgKwefNmnb2ri0rH8+fPce/ePQBAvXr1NOZTopKlixOPFgYDEVEhmZqa4tKlS3nGKmg7IyMj3Lx5M8+jXu7fvw8HBwe8fPlSosrezcHBAd9++y369++vMX9SZGQkPvnkE62e6oDKztixY7FmzZo8Z8rT09Mxbdo0nR3gq23ennh08+bNaN68udZPPFoUvGRGVEgODg46+SFsa2uL0NDQPIEoNDRUnFRNG0VHR+f79GylUqm1j5Ggsrd582YsW7YsTyB68eIFtmzZwkBUQq5cuaKxnjt7eWRkpEa7Lg+wZiAiege1Wi3+e/ny5Zg3bx6+/fZbnXqq9oQJEzBz5kxkZmaia9euAF7fMjtv3jzMnj1b4uoKVrduXYSHh+eZzuDQoUPiAyVJvtRqNQRBgCAISE1NhZGRkbgtOzsb//zzj9ZOKaGL5HCJmoGI6B0qVaqk8RePIAjo1q2bRh9tH1Q9d+5cPHnyBFOmTBFn2jYyMoKXlxe8vb0lrq5gnp6e8PDwwMuXLyEIAs6fP48dO3bA19cXGzdulLo8kljuz6ZCoUCDBg3ybFcoFPDx8ZGgMtJVHENE9A5vPkn7wYMHsLW1zTPvU05ODmJiYuDu7l7W5RVJWloabt68CWNjY9SvXx9KpVLqkt5r27ZtWLx4sThYtkaNGli8eDHGjRsncWUktZCQEAiCgK5du+Kvv/5ClSpVxG2GhoaoXbu2Vl8SJu3DQERUSPr6+oiLi8tzGv7JkyewsLDQ2jNEuurFixcQBAEmJiZ4/vw5IiMjERoaCgcHB7i6ukpdHmmJhw8folatWjo9doW0Q9658YkoX7mXxt6WlpamMX5B26Snp2PBggVo164d7O3tYWdnp7Foq379+mHLli0AXs970rdvX6xatQr9+/fHhg0bJK6OtMXNmzcRGhoqrv/0009o2bIlhg0bhmfPnklYGekajiEieo/c200VCgUWLFigMb9JdnY2zp07J95xoY3Gjx+PkJAQjBw5Uqem2b98+TJ++OEHAMCff/4JS0tLXLlyBX/99RcWLlyIyZMnS1whaYO5c+di+fLlAIBr167B09MTs2fPxvHjx+Hp6am1Dy8m7cNARPQeubebCoKAa9euwdDQUNxmaGiIFi1aYM6cOVKV916BgYE4ePAg2rdvL3UpRfL8+XPxVuojR45g4MCB0NPTg5OTEx4+fChxdaQtoqOj4eDgAAD466+/0KdPH3z77be4fPkyevXqJXF1pEsYiIjeI/d20zFjxmDNmjVae3t9QSpXrqwx4FRX2NvbY+/evRgwYAAOHz6MWbNmAQASExN17v+ASo+hoaH4RPujR49i1KhRAIAqVapoTJtB9D4cQ0RUSP7+/jr5Qbx06VIsXLhQ/NDQFQsXLsScOXNQp04dtG3bFs7OzgBeny3Kb8JGkqcOHTrA09MTS5cuxfnz5+Hm5gbg9bMHa9asKXF1pEt4lxlROdeqVSvcu3cPgiCgTp06eSaUvHz5skSVvV98fDzi4uLQokUL6Om9/vvt/PnzUKlUOvcIFSodMTExmDJlCh49eoTp06eLUzLMmjUL2dnZWLt2rcQVkq5gICIq5943Od2iRYvKqBIiIu3FQERERDorJibmndtr1apVRpWQrmMgIiIinaWnp/fOqSQ4YSoVFu8yIyrnsrOz8cMPP2Dnzp2IiYkRn2eW6+nTpxJVRvTh3n4Ke2ZmJq5cuYJVq1bhm2++kagq0kUMRETlnI+PDzZu3IjZs2dj/vz5+Oqrr/DgwQPs3bsXCxculLo8og/SokWLPG1t2rSBjY0NVq5ciYEDB0pQFekiXjIjKufq1auHtWvXws3NDWZmZggPDxfbzp49i+3bt0tdIlGJu3v3Llq0aIH09HSpSyEdwTNEROVcfHw8mjVrBgCoWLEiUlJSAAC9e/fGggULpCyN6IO9PfmiIAiIi4vD4sWLUb9+fYmqIl3EQERUztWsWRNxcXGoVasW6tWrhyNHjsDR0REXLlyAUqmUujyiD1KpUqU8g6oFQYCtrS127NghUVWkixiIiMq5AQMGIDg4GG3btsW0adMwYsQI/Prrr4iJiREfh0Gkq3IfrZNLT08P1atXh729PQwM+BFHhccxREQyc/bsWZw5cwb169dHnz59pC6H6IP4+vrC0tISY8eO1WjftGkTkpKS4OXlJVFlpGv4LDOics7X1xebNm0S152cnODp6YmkpCQsX75cwsqIPtzPP/+c72NcmjRpAj8/PwkqIl3FQERUzvEDg8qz+Ph4WFtb52mvXr064uLiJKiIdBUDEVE5xw8MKs9sbW0RGhqapz00NBQ2NjYSVES6iiPOiMq53A+MunXrarTzA4PKgwkTJmDmzJnIzMxE165dAQDBwcGYN28eZs+eLXF1pEsYiIjKOX5gUHk2d+5cPHnyBFOmTBEfS2NkZAQvLy94e3tLXB3pEt5lRlTOCYKAL7/8EmvXrs3zgcFHd1B5kZaWhps3b8LY2Bj169fnHFtUZAxERDLBDwwiooIxEBEREZHs8S4zIiIikj0GIiIiIpI9BiIiIiKSPQYiIir3Hjx4AIVCgfDwcKlLISItxUBERDpBoVC8c1m8eLHUJRKRDuPEjESkE958zMgff/yBhQsXIioqSmyrWLGiFGURUTnBM0REpBOsrKzExdzcHAqFQly3sLDAqlWrULNmTSiVSrRs2RKHDh0qcF/Z2dkYO3YsGjVqhJiYGADAvn374OjoCCMjI9jZ2cHHxwdZWVniaxQKBTZu3IgBAwbAxMQE9evXx/79+8Xtz549w/Dhw1G9enVxrid/f//S+4IQUYliICIinbdmzRp8//33+O6773D16lW4urqib9++uHPnTp6+GRkZ+OyzzxAeHo5Tp06hVq1aOHXqFEaNGoUZM2bgxo0b+PnnnxEQEIBvvvlG47U+Pj4YMmQIrl69il69emH48OF4+vQpAGDBggW4ceMGAgMDcfPmTWzYsAHVqlUrk+MnohIgEBHpGH9/f8Hc3Fxct7GxEb755huNPh999JEwZcoUQRAEITo6WgAgnDp1SujWrZvQoUMHITk5WezbrVs34dtvv9V4/datWwVra2txHYAwf/58cT0tLU0AIAQGBgqCIAh9+vQRxowZU2LHSERli2OIiEinqdVqxMbGon379hrt7du3R0REhEbbF198gZo1a+LYsWMwNjYW2yMiIhAaGqpxRig7OxsvX77E8+fPYWJiAgBo3ry5uN3U1BQqlQqJiYkAgMmTJ2PQoEG4fPkyXFxc0L9/f7Rr167Ej5eISgcvmRGRbPTq1QtXr15FWFiYRntaWhp8fHwQHh4uLteuXcOdO3dgZGQk9qtQoYLG6xQKBXJycgAAPXv2xMOHDzFr1izExsaiW7dumDNnTukfFBGVCAYiItJpKpUKNjY2CA0N1WgPDQ2Fg4ODRtvkyZOxbNky9O3bFyEhIWK7o6MjoqKiYG9vn2fR0yv8r8nq1avD3d0dv/32G1avXo1ffvnlww6OiMoML5kRkc6bO3cuFi1ahHr16qFly5bw9/dHeHg4tm3blqfvtGnTkJ2djd69eyMwMBAdOnTAwoUL0bt3b9SqVQuDBw+Gnp4eIiIiEBkZia+//rpQNSxcuBCtW7dGkyZNkJGRgQMHDqBx48YlfahEVEoYiIhI502fPh0pKSmYPXs2EhMT4eDggP3796N+/fr59p85cyZycnLQq1cvHDp0CK6urjhw4ACWLFmC5cuXo0KFCmjUqBHGjx9f6BoMDQ3h7e2NBw8ewNjYGB07dsTvv/9eUodIRKVMIQiCIHURRERERFLiGCIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpI9BiIiIiKSPQYiIiIikj0GIiIiIpK9/x8O1HpCKe4L0gAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Visualize the df\n",
        "plt.bar(freqdf.Tokens[:10], freqdf.Freq[:10], color = \"magenta\")\n",
        "plt.title(\"Top 10 Tokens: Flight Sentiment\")\n",
        "plt.xlabel(\"Tokens\")\n",
        "plt.xticks(rotation = 90)\n",
        "plt.ylabel(\"Frequency\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 422
        },
        "id": "9qLRCSdIkcuL",
        "outputId": "2034bfb1-5fb7-4026-8f5e-3fe34efe4560"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Word Cloud of the Flight Data\n",
        "\n",
        "from wordcloud import WordCloud\n",
        "wordcloud = WordCloud(width = 800, height = 400,\n",
        "                      background_color = \"white\").\\\n",
        "                      generate(\" \".join(all_tokens))\n",
        "\n",
        "plt.figure(figsize = (10, 5))\n",
        "plt.imshow(wordcloud)\n",
        "plt.axis(\"off\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "mCQ8tcC6EPCT"
      },
      "outputs": [],
      "source": [
        "mapped = {'neutral':0 ,'positive':1, 'negative':2}\n",
        "mydf[\"Target\"]=  mydf.airline_sentiment.map(mapped)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 432
        },
        "id": "ex1ZoDNoBF3p",
        "outputId": "b66c4f3b-812a-48bc-dc58-b50d85f9fbe7"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "summary": "{\n  \"name\": \"mydf\",\n  \"rows\": 14640,\n  \"fields\": [\n    {\n      \"column\": \"airline_sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"neutral\",\n          \"positive\",\n          \"negative\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 14427,\n        \"samples\": [\n          \"@JetBlue so technically I could drive to JFK now and put in. Request for tomorrow's flight?\",\n          \"@united why I won't check my carry on. Watched a handler throw this bag -- miss the conveyer belt -- sat there 10 min http://t.co/lyoocx5mSH\",\n          \"@SouthwestAir you guys are so clever \\ud83d\\ude03 http://t.co/qn5odUGFqK\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"clean_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 14389,\n        \"samples\": [\n          \"@usairways need apologies unfortunate situation . date, i've landed suppose land 5\",\n          \"@usairways thank\",\n          \"@united ua1740 admit clue flight leave denver. #unfriendlyskies\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"noise\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Cleansed\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 14190,\n        \"samples\": [\n          \"finally got through thanks\",\n          \"thanks epic service always pleasure outstanding crew trqlpeinzw\",\n          \"going since can take option gave me type refund me\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Target\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 2,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          0,\n          1,\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
              "type": "dataframe",
              "variable_name": "mydf"
            },
            "text/html": [
              "\n",
              "  <div id=\"df-312cb54a-81ee-49bb-aaba-2bab8336d9b1\" 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>airline_sentiment</th>\n",
              "      <th>text</th>\n",
              "      <th>clean_text</th>\n",
              "      <th>noise</th>\n",
              "      <th>Cleansed</th>\n",
              "      <th>Target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>neutral</td>\n",
              "      <td>@VirginAmerica What @dhepburn said.</td>\n",
              "      <td>@virginamerica @dhepburn said.</td>\n",
              "      <td>[@virginamerica, @dhepburn, .]</td>\n",
              "      <td>said</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>positive</td>\n",
              "      <td>@VirginAmerica plus you've added commercials t...</td>\n",
              "      <td>@virginamerica plus added commercials experien...</td>\n",
              "      <td>[@virginamerica, ., ., ., .]</td>\n",
              "      <td>plus added commercials experience tacky</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>neutral</td>\n",
              "      <td>@VirginAmerica I didn't today... Must mean I n...</td>\n",
              "      <td>@virginamerica today... must mean need take an...</td>\n",
              "      <td>[@virginamerica, ., ., ., !]</td>\n",
              "      <td>today must mean need take another trip</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>negative</td>\n",
              "      <td>@VirginAmerica it's really aggressive to blast...</td>\n",
              "      <td>@virginamerica really aggressive blast obnoxio...</td>\n",
              "      <td>[@virginamerica, \", \", ', &amp;, ;]</td>\n",
              "      <td>really aggressive blast obnoxious entertainmen...</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>negative</td>\n",
              "      <td>@VirginAmerica and it's a really big bad thing...</td>\n",
              "      <td>@virginamerica really big bad thing</td>\n",
              "      <td>[@virginamerica]</td>\n",
              "      <td>really big bad thing</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
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              "        document.querySelector('#df-312cb54a-81ee-49bb-aaba-2bab8336d9b1 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-312cb54a-81ee-49bb-aaba-2bab8336d9b1');\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-d0e2b27a-aff4-4f02-a314-164663b1cd26\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d0e2b27a-aff4-4f02-a314-164663b1cd26')\"\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-d0e2b27a-aff4-4f02-a314-164663b1cd26 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": [
              "  airline_sentiment                                               text  \\\n",
              "0           neutral                @VirginAmerica What @dhepburn said.   \n",
              "1          positive  @VirginAmerica plus you've added commercials t...   \n",
              "2           neutral  @VirginAmerica I didn't today... Must mean I n...   \n",
              "3          negative  @VirginAmerica it's really aggressive to blast...   \n",
              "4          negative  @VirginAmerica and it's a really big bad thing...   \n",
              "\n",
              "                                          clean_text  \\\n",
              "0                     @virginamerica @dhepburn said.   \n",
              "1  @virginamerica plus added commercials experien...   \n",
              "2  @virginamerica today... must mean need take an...   \n",
              "3  @virginamerica really aggressive blast obnoxio...   \n",
              "4                @virginamerica really big bad thing   \n",
              "\n",
              "                             noise  \\\n",
              "0   [@virginamerica, @dhepburn, .]   \n",
              "1     [@virginamerica, ., ., ., .]   \n",
              "2     [@virginamerica, ., ., ., !]   \n",
              "3  [@virginamerica, \", \", ', &, ;]   \n",
              "4                 [@virginamerica]   \n",
              "\n",
              "                                            Cleansed  Target  \n",
              "0                                               said       0  \n",
              "1            plus added commercials experience tacky       1  \n",
              "2             today must mean need take another trip       0  \n",
              "3  really aggressive blast obnoxious entertainmen...       2  \n",
              "4                               really big bad thing       2  "
            ]
          },
          "execution_count": 33,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "mydf.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QTGNAXKhBUIp",
        "outputId": "ea54d09c-ea23-4e3c-93a2-8c082f2c4ea0"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[31mERROR: Could not find a version that satisfies the requirement transformer (from versions: none)\u001b[0m\u001b[31m\n",
            "\u001b[0m\u001b[31mERROR: No matching distribution found for transformer\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "!pip install transformer torch"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "O0WJG3fIBY7F"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "\n",
        "from transformers import BertTokenizer, BertForSequenceClassification\n",
        "from transformers import pipeline\n",
        "\n",
        "\n",
        "# Load pre-trained BERT model and tokenizer for sentiment analysis\n",
        "model_name = \"nlptown/bert-base-multilingual-uncased-sentiment\"\n",
        "model = BertForSequenceClassification.from_pretrained(model_name)\n",
        "tokenizer = BertTokenizer.from_pretrained(model_name)\n",
        "\n",
        "# Sentiment analysis pipeline\n",
        "sentiment_analyzer = pipeline(\"sentiment-analysis\", model=model, tokenizer=tokenizer)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bvxhkq6WH3cG"
      },
      "source": [
        "## BERT Model for Prediction"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-K34o3w6CrU4",
        "outputId": "28b47c82-6933-425f-9131-daddf43ce44c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting simpletransformers\n",
            "  Downloading simpletransformers-0.70.1-py3-none-any.whl.metadata (42 kB)\n",
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            "Building wheels for collected packages: seqeval\n",
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            "Successfully installed datasets-3.0.1 dill-0.3.8 docker-pycreds-0.4.0 gitdb-4.0.11 gitpython-3.1.43 multiprocess-0.70.16 pydeck-0.9.1 sentry-sdk-2.15.0 seqeval-1.2.2 setproctitle-1.3.3 simpletransformers-0.70.1 smmap-5.0.1 streamlit-1.39.0 tensorboardx-2.6.2.2 wandb-0.18.3 watchdog-5.0.3 xxhash-3.5.0\n"
          ]
        }
      ],
      "source": [
        "!pip install simpletransformers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "zFBanNn0CtSx"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "V7h78_OxCtJ6"
      },
      "outputs": [],
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "from sklearn.metrics import classification_report\n",
        "\n",
        "# Split the data into training and testing sets\n",
        "X = mydf['Cleansed']\n",
        "y = mydf['Target']\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yzMPuq9uDOUF"
      },
      "outputs": [],
      "source": [
        "# Prepare data as DataFrames (adjust your X_train, Y_train, X_test, Y_test accordingly)\n",
        "train_data = pd.DataFrame({\n",
        "    'text': X_train,\n",
        "    'labels': y_train\n",
        "})\n",
        "\n",
        "test_data = pd.DataFrame({\n",
        "    'text': X_test,\n",
        "    'labels': y_test\n",
        "})"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 454
        },
        "id": "_DsBfXilC7qE",
        "outputId": "1408d4d8-84f8-4f2a-dbc1-f03f07d8884b"
      },
      "outputs": [
        {
          "ename": "TypeError",
          "evalue": "BertForSequenceClassification.__init__() got an unexpected keyword argument 'overwrite_output_dir'",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-45-fbba38e1a011>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Define a BERT model using simpletransformers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0msimpletransformers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclassification\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mClassificationModel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m model = ClassificationModel('bert', 'bert-large-uncased', \n\u001b[0m\u001b[1;32m      4\u001b[0m                             num_labels=3, use_cuda=True, overwrite_output_dir=True)  # For binary classification (use_cuda=True if you want to use GPU)\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/simpletransformers/classification/classification_model.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, model_type, model_name, tokenizer_type, tokenizer_name, num_labels, weight, args, use_cuda, cuda_device, onnx_execution_provider, **kwargs)\u001b[0m\n\u001b[1;32m    420\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    421\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquantized_model\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 422\u001b[0;31m                 self.model = model_class.from_pretrained(\n\u001b[0m\u001b[1;32m    423\u001b[0m                     \u001b[0mmodel_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    424\u001b[0m                 )\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m   3830\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mContextManagers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minit_contexts\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3831\u001b[0m             \u001b[0;31m# Let's make sure we don't run the init function of buffer modules\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3832\u001b[0;31m             \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mmodel_args\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mmodel_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3833\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3834\u001b[0m         \u001b[0;31m# make sure we use the model's config since the __init__ call might have copied it\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mTypeError\u001b[0m: BertForSequenceClassification.__init__() got an unexpected keyword argument 'overwrite_output_dir'"
          ]
        }
      ],
      "source": [
        "# Define a BERT model using simpletransformers\n",
        "from simpletransformers.classification import ClassificationModel\n",
        "# Initialize the BERT model with 3 output labels\n",
        "model = ClassificationModel('bert', 'bert-base-uncased',\n",
        "                            num_labels=3, use_cuda=True)\n",
        "\n",
        "# Train the model on your data\n",
        "model.train_model(train_data)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "background_save": true,
          "base_uri": "https://localhost:8080/",
          "height": 169,
          "referenced_widgets": [
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            "f368c6ec8ecf47a4a8c96c03e5f9227a",
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          "text": [
            "Some weights of BertForSequenceClassification were not initialized from the model checkpoint at bert-large-uncased and are newly initialized: ['classifier.bias', 'classifier.weight']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
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              "Epoch:   0%|          | 0/1 [00:00<?, ?it/s]"
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              "Running Epoch 1 of 1:   0%|          | 0/1464 [00:00<?, ?it/s]"
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      "source": [
        "# Define a BERT model using simpletransformers\n",
        "from simpletransformers.classification import ClassificationModel\n",
        "model = ClassificationModel('bert', 'bert-large-uncased',\n",
        "                            num_labels=3, use_cuda=True,\n",
        "                            args={'overwrite_output_dir': True})  # For binary classification (use_cuda=True if you want to use GPU)\n",
        "\n",
        "# Train the model on your data\n",
        "model.train_model(train_data)"
      ]
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          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "     Neutral       0.64      0.57      0.60       580\n",
            "    Positive       0.77      0.73      0.75       459\n",
            "    Negative       0.87      0.90      0.89      1889\n",
            "\n",
            "    accuracy                           0.81      2928\n",
            "   macro avg       0.76      0.74      0.75      2928\n",
            "weighted avg       0.81      0.81      0.81      2928\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Make predictions on test data\n",
        "predictions, raw_outputs = model.predict(test_data['text'].tolist())\n",
        "\n",
        "# Generate classification report\n",
        "print(classification_report(test_data['labels'],\n",
        "                            predictions, target_names=['Neutral', 'Positive', 'Negative']))"
      ]
    },
    {
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        },
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        "outputId": "8e6c697b-7f6f-4a8d-d754-8332a072f272"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "          -1       0.85      0.89      0.87      1889\n",
            "           0       0.60      0.57      0.58       580\n",
            "           1       0.78      0.69      0.73       459\n",
            "\n",
            "    accuracy                           0.79      2928\n",
            "   macro avg       0.74      0.72      0.73      2928\n",
            "weighted avg       0.79      0.79      0.79      2928\n",
            "\n"
          ]
        }
      ],
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import accuracy_score, classification_report\n",
        "\n",
        "# Split the data into training and testing sets\n",
        "X = mydf['Cleansed']\n",
        "y = mydf['Target']\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# Create a CountVectorizer object\n",
        "vectorizer = CountVectorizer()\n",
        "\n",
        "# Fit and transform the training data\n",
        "X_train_vec = vectorizer.fit_transform(X_train)\n",
        "\n",
        "# Transform the testing data\n",
        "X_test_vec = vectorizer.transform(X_test)\n",
        "\n",
        "# Create a Logistic Regression model\n",
        "model = LogisticRegression()\n",
        "\n",
        "# Train the model\n",
        "model.fit(X_train_vec, y_train)\n",
        "\n",
        "# Make predictions on the testing data\n",
        "y_pred = model.predict(X_test_vec)\n",
        "\n",
        "# Evaluate the model\n",
        "print(classification_report(y_test, y_pred))\n"
      ]
    },
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      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "          -1       0.81      0.94      0.87      1889\n",
            "           0       0.68      0.44      0.53       580\n",
            "           1       0.83      0.62      0.71       459\n",
            "\n",
            "    accuracy                           0.79      2928\n",
            "   macro avg       0.77      0.67      0.70      2928\n",
            "weighted avg       0.79      0.79      0.78      2928\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# prompt: Give me Tf-IDF Code for the same\n",
        "\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "\n",
        "# Create a TfidfVectorizer object\n",
        "tfidf_vectorizer = TfidfVectorizer()\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",
        "# Create a Logistic Regression model\n",
        "model_tfidf = LogisticRegression()\n",
        "\n",
        "# Train the model\n",
        "model_tfidf.fit(X_train_tfidf, y_train)\n",
        "\n",
        "# Make predictions on the testing data\n",
        "y_pred_tfidf = model_tfidf.predict(X_test_tfidf)\n",
        "\n",
        "# Evaluate the model\n",
        "print(classification_report(y_test, y_pred_tfidf))"
      ]
    },
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