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      "cell_type": "markdown",
      "source": [
        "# Import dependencies"
      ],
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        "id": "H160Juq51eRO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "from time import sleep\n",
        "import requests\n",
        "from google.colab import files\n",
        "from bs4 import BeautifulSoup"
      ],
      "metadata": {
        "id": "zfe_3xrI1wn8"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Scraping"
      ],
      "metadata": {
        "id": "OtN9QxYX2ic3"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "To begin with, let's take uhmmm... Mc Donald's"
      ],
      "metadata": {
        "id": "Et5axtql6BkM"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "t7zP37v8Hpwg"
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      "source": [
        "def soup2list(src, list_, attr=None):\n",
        "    if attr:\n",
        "        for val in src:\n",
        "            list_.append(val[attr])\n",
        "    else:\n",
        "        for val in src:\n",
        "            list_.append(val.get_text())\n",
        "\n",
        "users = []\n",
        "userReviewNum = []\n",
        "ratings = []\n",
        "locations = []\n",
        "dates = []\n",
        "reviews = []\n",
        "\n",
        "from_page = 1\n",
        "to_page = 6\n",
        "company = 'mc-donalds.com'\n",
        "\n",
        "for i in range(from_page, to_page+1):\n",
        "\n",
        "   result = requests.get(fr\"https://www.trustpilot.com/review/{company}?page={i}\")\n",
        "   soup = BeautifulSoup(result.content)\n",
        "\n",
        "   # Trust Pilot was setup in a way that's not friendly to scraping, so this hacky method will do.\n",
        "   soup2list(soup.find_all('span', {'class','typography_heading-xxs__QKBS8 typography_appearance-default__AAY17'}), users)\n",
        "   soup2list(soup.find_all('div', {'class','typography_body-m__xgxZ_ typography_appearance-subtle__8_H2l styles_detailsIcon__Fo_ua'}), locations)\n",
        "   soup2list(soup.find_all('span', {'class','typography_body-m__xgxZ_ typography_appearance-subtle__8_H2l'}), userReviewNum)\n",
        "   soup2list(soup.find_all('div', {'class','styles_reviewHeader__iU9Px'}), dates)\n",
        "   soup2list(soup.find_all('div', {'class','styles_reviewHeader__iU9Px'}), ratings, attr='data-service-review-rating')\n",
        "   soup2list(soup.find_all('div', {'class','styles_reviewContent__0Q2Tg'}), reviews)\n",
        "\n",
        "   # To avoid throttling\n",
        "   sleep(1)\n",
        "\n",
        "review_data = pd.DataFrame(\n",
        "{\n",
        "   'Username':users,\n",
        "   'Total reviews':userReviewNum,\n",
        "   'location':locations,\n",
        "   'date':dates,\n",
        "   'content':reviews,\n",
        "   'Rating': ratings\n",
        "})"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# create a dataframe for reviews\n",
        "review_content = review_data['content']\n",
        "df = pd.DataFrame(data = {'review': review_content})\n",
        "\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
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        "id": "UX_XumPEJoOJ",
        "outputId": "e0e2e77f-6653-4918-ac03-968ea4a94ab5"
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            "text/plain": [
              "                                                review\n",
              "0    Couldn't get an order right to save their life...\n",
              "1    McDonald's - Five Lane Ends I never seem to le...\n",
              "2    If i could give you 0 stars i wouldIf i could ...\n",
              "3    The order I placed from McDonald's…The order I...\n",
              "4    Shocking place to get foodShocking place to ge...\n",
              "..                                                 ...\n",
              "115  So badSo bad, there are better optionsDate of ...\n",
              "116  Fast food fastFast food fast.  I like that the...\n",
              "117  I love Mac DonaldsThe food is amazing and ther...\n",
              "118  Poisoning America and the WorldThis company ha...\n",
              "119  i love this its so good and im happy i…i love ...\n",
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              "      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-dcd7f9c0-18c7-4c33-b234-c3d7c8db92f2 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-dcd7f9c0-18c7-4c33-b234-c3d7c8db92f2');\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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              "            title=\"Suggest charts\"\n",
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              "  </button>\n",
              "\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "      --hover-bg-color: #E2EBFA;\n",
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              "      --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",
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              "      --disabled-fill-color: #666;\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",
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              "    height: 32px;\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    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",
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              "      border-color: transparent;\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "      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-2a07ab8c-b38d-4a11-b0f4-2be3e7cf6b7e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_ca28e8be-0b9e-4709-85c4-f798b01c1f52\">\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('df')\"\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",
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              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_ca28e8be-0b9e-4709-85c4-f798b01c1f52 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 120,\n  \"fields\": [\n    {\n      \"column\": \"review\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 120,\n        \"samples\": [\n          \"FOOD POISONINGFOOD POISONING - Five of us including two children ate at Fraddon McDonalds after a day at Motocross just up the road, we hadn't eaten anything all day and were very hungry. We all ate burger and chip meals along with a various sides. Around an hour later I felt Ill, two hours later I was being sick, then my girlfriend started being sick just before my son started being sick. Our friend had a very bad stomach all day, and our 3 year old was the only one that didn't get affected. We were laid up for three days, and were in no fit state to work. Contacted McDonalds with clear evidence of food positioning including symptons, we were told that no else has reported reported food poisoning so we dont believe you. However they then accepted the claim, and all they offered a \\u00a310 gift voucher which didn't even cover the cost for a  refund, another corporate company which the little guy is powerless to take on, declined the refund and wont go there again.Date of experience: July 21, 2023\",\n          \"MacDonalds IrvineMacDonalds Irvine : Chicken McSandwich, may as well have been a drinks mat in the bun. Tons of shredded lettuce, some insipid sauce and an utterly lifeless piece of reconstituted \\u201cchicken\\u201d. The fries have virtually nothing to do with potatoes.Date of experience: February 15, 2023\",\n          \"Shocking place to get foodShocking place to get food! Wouldn\\u2019t visit again Date of experience: February 15, 2024\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# examine review\n",
        "df['review'][0]"
      ],
      "metadata": {
        "id": "hvpWZ83CJquJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "baf5b999-779d-4f9b-f2e2-cf631a2a96c7"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"Couldn't get an order right to save their life It's one thing when you're in store and can confront the staff about them giving you incomplete orders, but I shouldn't be surprised when I ordered a bic mac for delivery and there was no burger! After being at work ALL DAY, I spent £12 to recieve only a shake and fries! I tried calling several times but got not answer.  Could have got chips from the local chippy for a couple quid. What an absolute waste.Date of experience: March 11, 2024\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['review'][2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "id": "nxCQ0qGqEBCo",
        "outputId": "6efadb6d-cb90-4887-ac63-70708ec2836b"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"If i could give you 0 stars i wouldIf i could give you 0 stars i would. You are so embarrassing for supporting genocide. IMAGINE. couldn't be me. you are disgusting you fagg autistic c u n t. I hope you kill your self no one likes you. go cut yourself, hang yourself, jump off a building. commit. I HOPE YOUR PLACE BURNS DOWN AND YOUR PEOPLE ARE STILL IN IT. IMAGINE SUPPORTING A FAKE COUNTRY YOU FAKE A S S    H O E S. I mean I understand since your meat is fake.Date of experience: February 07, 2024\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Wow this guy ☝️ was livid.\n"
      ],
      "metadata": {
        "id": "X-Akbo47ENV2"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Anyway, it seems like we have a problem. At the end of every review, an unwelcome 'Date of experience' is included."
      ],
      "metadata": {
        "id": "pvXlVVO8GltZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import re\n",
        "\n",
        "def remove_date(review):\n",
        "    # Define the date pattern using regular expression\n",
        "    date_pattern = r\"Date of experience: \\w+ \\d{1,2}, \\d{4}$\"\n",
        "    # Replace the date pattern with an empty string\n",
        "    cleaned_review = re.sub(date_pattern, \"\", review)\n",
        "    return cleaned_review.strip()  # Strip any leading/trailing whitespace\n",
        "\n",
        "# Apply the function to each review\n",
        "cleaned_reviews = [remove_date(review) for review in reviews]\n",
        "\n",
        "df['review'] = cleaned_reviews"
      ],
      "metadata": {
        "id": "qWZkGhIZ_yyd"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['review'][0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "id": "b_4FE5KPCiRO",
        "outputId": "f7878f79-cbf4-422b-d9d3-0f25c4b77cdb"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"Couldn't get an order right to save their life It's one thing when you're in store and can confront the staff about them giving you incomplete orders, but I shouldn't be surprised when I ordered a bic mac for delivery and there was no burger! After being at work ALL DAY, I spent £12 to recieve only a shake and fries! I tried calling several times but got not answer.  Could have got chips from the local chippy for a couple quid. What an absolute waste.\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['review'][5]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 105
        },
        "id": "2-BCFDuS-ci4",
        "outputId": "a0bf6cdb-a065-4f10-aa23-d1e25e3af594"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"Untrained staff rude behaviour MC…Untrained staff rude behaviour MC Donald's refused to take order after 9:40 pm.pre ordered food is cancelled by the staff without acknowledged the staff doesn't have any manners and doesn't care about how to deal with a cancelled order they didn't even tried to call back the customer and let us know the order cancellation details the staff who talked from the outlet ( after we contacted them) is not polite and doesn't offer an order replacement options or nothing Completely unsatisfied with the staff in Abad nucleus mall McDonald's outlet kochi.Terrible experience..becoz the staff seemed untrained they were slow made mistake with my order and seemed confused wen I asked for help.frustating staff untrained and rude.\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['review'][2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "id": "CjMue2i7K4E0",
        "outputId": "cb108ed4-9f45-4eec-877b-8cf4d76052b7"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"If i could give you 0 stars i wouldIf i could give you 0 stars i would. You are so embarrassing for supporting genocide. IMAGINE. couldn't be me. you are disgusting you fagg autistic c u n t. I hope you kill your self no one likes you. go cut yourself, hang yourself, jump off a building. commit. I HOPE YOUR PLACE BURNS DOWN AND YOUR PEOPLE ARE STILL IN IT. IMAGINE SUPPORTING A FAKE COUNTRY YOU FAKE A S S    H O E S. I mean I understand since your meat is fake.\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "# Building Model"
      ],
      "metadata": {
        "id": "jjeX4MsKNt4I"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "from keras.preprocessing import sequence\n",
        "import os\n",
        "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n",
        "import torch\n",
        "import re"
      ],
      "metadata": {
        "id": "otk4QczuMsTP"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tokenizer = AutoTokenizer.from_pretrained('nlptown/bert-base-multilingual-uncased-sentiment')\n",
        "\n",
        "model = AutoModelForSequenceClassification.from_pretrained('nlptown/bert-base-multilingual-uncased-sentiment')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336,
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        "outputId": "328b1437-dee2-41a6-b729-cbbb130154b7"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
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              "tokenizer_config.json:   0%|          | 0.00/39.0 [00:00<?, ?B/s]"
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          "text": [
            "/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n",
            "  return self.fget.__get__(instance, owner)()\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# function for rating review\n",
        "\n",
        "def sentiment_score(review):\n",
        "  tokens = tokenizer.encode(review, return_tensors = 'pt')\n",
        "  result = model(tokens)\n",
        "  return int(torch.argmax(result.logits)) + 1\n",
        "\n",
        "\n",
        "df['rating'] = df['review'].apply(lambda x: sentiment_score(x[:512]))"
      ],
      "metadata": {
        "id": "UaqlwystM5gw"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
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      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
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        "id": "e0amBjVgN-FK",
        "outputId": "34068a60-e61d-4bf8-a9c8-2a1cda636408"
      },
      "execution_count": 17,
      "outputs": [
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              "                                                review  rating\n",
              "0    Couldn't get an order right to save their life...       1\n",
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              "2    If i could give you 0 stars i wouldIf i could ...       1\n",
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              "..                                                 ...     ...\n",
              "115             So badSo bad, there are better options       1\n",
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              "117  I love Mac DonaldsThe food is amazing and ther...       5\n",
              "118  Poisoning America and the WorldThis company ha...       1\n",
              "119  i love this its so good and im happy i…i love ...       5\n",
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              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 120,\n  \"fields\": [\n    {\n      \"column\": \"review\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 120,\n        \"samples\": [\n          \"FOOD POISONINGFOOD POISONING - Five of us including two children ate at Fraddon McDonalds after a day at Motocross just up the road, we hadn't eaten anything all day and were very hungry. We all ate burger and chip meals along with a various sides. Around an hour later I felt Ill, two hours later I was being sick, then my girlfriend started being sick just before my son started being sick. Our friend had a very bad stomach all day, and our 3 year old was the only one that didn't get affected. We were laid up for three days, and were in no fit state to work. Contacted McDonalds with clear evidence of food positioning including symptons, we were told that no else has reported reported food poisoning so we dont believe you. However they then accepted the claim, and all they offered a \\u00a310 gift voucher which didn't even cover the cost for a  refund, another corporate company which the little guy is powerless to take on, declined the refund and wont go there again.\",\n          \"MacDonalds IrvineMacDonalds Irvine : Chicken McSandwich, may as well have been a drinks mat in the bun. Tons of shredded lettuce, some insipid sauce and an utterly lifeless piece of reconstituted \\u201cchicken\\u201d. The fries have virtually nothing to do with potatoes.\",\n          \"Shocking place to get foodShocking place to get food! Wouldn\\u2019t visit again\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 1,\n        \"max\": 5,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          4,\n          3,\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# unique ratings\n",
        "df['rating'].unique().tolist()"
      ],
      "metadata": {
        "id": "OACQA95fQdQh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bd6c2aee-3e3c-4762-b535-307c1e6db0bd"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[1, 4, 2, 5, 3]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "average_rating = df['rating'].mean()\n",
        "print(f'Average rating is {round(average_rating, 1)} out of 5 stars.')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VxecMYjXOQIK",
        "outputId": "4d31f624-1fd5-4b2b-cd62-dc8036345970"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average rating is 1.9 out of 5 stars.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Making it a function"
      ],
      "metadata": {
        "id": "FspJdt9MQaSw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def soup2list(src, list_, attr=None):\n",
        "    if attr:\n",
        "        for val in src:\n",
        "            list_.append(val[attr])\n",
        "    else:\n",
        "        for val in src:\n",
        "            list_.append(val.get_text())\n",
        "\n",
        "def sentiment_score(review):\n",
        "  tokens = tokenizer.encode(review, return_tensors = 'pt')\n",
        "  result = model(tokens)\n",
        "  return int(torch.argmax(result.logits)) + 1\n",
        "\n",
        "\n",
        "def review(company_link):\n",
        "  users = []\n",
        "  userReviewNum = []\n",
        "  ratings = []\n",
        "  locations = []\n",
        "  dates = []\n",
        "  reviews = []\n",
        "\n",
        "  from_page = 1\n",
        "  to_page = 6\n",
        "\n",
        "\n",
        "  for i in range(from_page, to_page+1):\n",
        "\n",
        "    result = requests.get(fr\"https://www.trustpilot.com/review/{company_link}?page={i}\")\n",
        "    soup = BeautifulSoup(result.content)\n",
        "\n",
        "    # Trust Pilot was setup in a way that's not friendly to scraping, so this hacky method will do.\n",
        "    soup2list(soup.find_all('span', {'class','typography_heading-xxs__QKBS8 typography_appearance-default__AAY17'}), users)\n",
        "    soup2list(soup.find_all('div', {'class','typography_body-m__xgxZ_ typography_appearance-subtle__8_H2l styles_detailsIcon__Fo_ua'}), locations)\n",
        "    soup2list(soup.find_all('span', {'class','typography_body-m__xgxZ_ typography_appearance-subtle__8_H2l'}), userReviewNum)\n",
        "    soup2list(soup.find_all('div', {'class','styles_reviewHeader__iU9Px'}), dates)\n",
        "    soup2list(soup.find_all('div', {'class','styles_reviewHeader__iU9Px'}), ratings, attr='data-service-review-rating')\n",
        "    soup2list(soup.find_all('div', {'class','styles_reviewContent__0Q2Tg'}), reviews)\n",
        "\n",
        "    # To avoid throttling\n",
        "    sleep(1)\n",
        "\n",
        "  review_data = pd.DataFrame(\n",
        "  {\n",
        "    'Username':users,\n",
        "    'Total reviews':userReviewNum,\n",
        "    'location':locations,\n",
        "    'date':dates,\n",
        "    'content':reviews,\n",
        "    'Rating': ratings\n",
        "  })\n",
        "\n",
        "  review_content = review_data['content']\n",
        "  df = pd.DataFrame(data = {'review': review_content})\n",
        "\n",
        "  tokenizer = AutoTokenizer.from_pretrained('nlptown/bert-base-multilingual-uncased-sentiment')\n",
        "\n",
        "  model = AutoModelForSequenceClassification.from_pretrained('nlptown/bert-base-multilingual-uncased-sentiment')\n",
        "\n",
        "\n",
        "\n",
        "  df['rating'] = df['review'].apply(lambda x: sentiment_score(x[:512]))\n",
        "\n",
        "  average_rating = df['rating'].mean()\n",
        "  print(f'Average rating is {round(average_rating, 1)} out of 5 stars.')"
      ],
      "metadata": {
        "id": "dCTWWG3YQcj8"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Review companies"
      ],
      "metadata": {
        "id": "VQbDSaENUvBO"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "\n",
        "*    Old Mutual Invest\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "h8qJempFdMRu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "company_link = 'www.oldmutualinvest.com'\n",
        "\n",
        "review(company_link)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Sh9lwiHSRx8M",
        "outputId": "7eccf57e-d611-475d-826e-5d809cb9928a"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average rating is 1.7 out of 5 stars.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "*   Capitec Bank\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "_hSlKdpseKCm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "company_link = 'capitecbank.co.za'\n",
        "\n",
        "review(company_link)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ssJut9s5TEs0",
        "outputId": "6153d9ba-b770-4b4a-a2a1-bfd3b8863f54"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average rating is 1.3 out of 5 stars.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "*   Discovery\n",
        "\n"
      ],
      "metadata": {
        "id": "AmfPebPYeRYQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "company_link = 'discovery.co.za'\n",
        "\n",
        "review(company_link)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_KB4gJhtTHio",
        "outputId": "fddafc0a-2621-441d-8b12-f544066901d0"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average rating is 1.0 out of 5 stars.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "*   Nedbank\n",
        "\n"
      ],
      "metadata": {
        "id": "sUvswnCReVBX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "company_link = 'nedbank.co.za'\n",
        "\n",
        "review(company_link)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zW4GOenTTfWy",
        "outputId": "811b982b-2158-48ae-e5c5-e869e3ac8ea6"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average rating is 1.2 out of 5 stars.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "*   Makro\n",
        "\n"
      ],
      "metadata": {
        "id": "jdXT7fSpdZAn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "company_link = 'makro.co.za'\n",
        "\n",
        "review(company_link)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PRSQATIjTE7H",
        "outputId": "33cba95e-c4a6-4269-a79e-7fa0eb57a041"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average rating is 1.2 out of 5 stars.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "12FGN0a0UVhy"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}